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tensorflow/tensor2tensor
|
tensor2tensor/data_generators/ice_parsing.py
|
tabbed_parsing_token_generator
|
def tabbed_parsing_token_generator(data_dir, tmp_dir, train, prefix,
source_vocab_size, target_vocab_size):
"""Generate source and target data from a single file."""
filename = "parsing_{0}.pairs".format("train" if train else "dev")
source_vocab = generator_utils.get_or_generate_tabbed_vocab(
data_dir, tmp_dir, filename, 0,
prefix + "_source.tokens.vocab.%d" % source_vocab_size, source_vocab_size)
target_vocab = generator_utils.get_or_generate_tabbed_vocab(
data_dir, tmp_dir, filename, 1,
prefix + "_target.tokens.vocab.%d" % target_vocab_size, target_vocab_size)
pair_filepath = os.path.join(tmp_dir, filename)
return text_problems.text2text_generate_encoded(
text_problems.text2text_txt_tab_iterator(pair_filepath), source_vocab,
target_vocab)
|
python
|
def tabbed_parsing_token_generator(data_dir, tmp_dir, train, prefix,
source_vocab_size, target_vocab_size):
"""Generate source and target data from a single file."""
filename = "parsing_{0}.pairs".format("train" if train else "dev")
source_vocab = generator_utils.get_or_generate_tabbed_vocab(
data_dir, tmp_dir, filename, 0,
prefix + "_source.tokens.vocab.%d" % source_vocab_size, source_vocab_size)
target_vocab = generator_utils.get_or_generate_tabbed_vocab(
data_dir, tmp_dir, filename, 1,
prefix + "_target.tokens.vocab.%d" % target_vocab_size, target_vocab_size)
pair_filepath = os.path.join(tmp_dir, filename)
return text_problems.text2text_generate_encoded(
text_problems.text2text_txt_tab_iterator(pair_filepath), source_vocab,
target_vocab)
|
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Generate source and target data from a single file.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/data_generators/ice_parsing.py#L37-L50
|
train
|
Generate source and target data from a single file.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x33' + chr(0b110000 + 0o5) + chr(48), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1011 + 0o144) + '\062' + '\x31' + chr(389 - 341), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\062' + chr(0b11 + 0o64) + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(4010 - 3899) + '\062' + '\x35' + '\063', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2164 - 2113) + '\x34' + chr(519 - 469), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(7404 - 7293) + chr(0b110001) + chr(0b110001) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b11111 + 0o24) + chr(0b110110) + chr(1935 - 1887), 0b1000), ehT0Px3KOsy9(chr(48) + chr(8561 - 8450) + chr(0b11101 + 0o24) + '\064' + chr(2196 - 2143), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + '\x32' + chr(0b110010), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + '\061' + '\067', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b111100 + 0o63) + chr(50) + '\066', 11595 - 11587), ehT0Px3KOsy9(chr(1433 - 1385) + '\157' + chr(1313 - 1264) + chr(50) + chr(848 - 794), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b101110 + 0o101) + chr(0b101000 + 0o11) + chr(0b110110) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\x32' + '\061' + chr(0b100 + 0o63), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(190 - 139) + chr(0b110110) + chr(52), 0b1000), ehT0Px3KOsy9(chr(1600 - 1552) + '\157' + chr(277 - 227) + '\x36' + chr(0b100101 + 0o22), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + chr(113 - 60) + chr(0b100100 + 0o17), 15006 - 14998), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1217 - 1168) + '\x30' + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1233 - 1182) + chr(53) + chr(55), 0o10), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(0b1101111) + chr(0b110011) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + '\062' + '\x33', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110110) + chr(0b100100 + 0o22), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + chr(1880 - 1825) + chr(601 - 547), 9928 - 9920), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(0b110101) + '\x35', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110000 + 0o3) + '\x33' + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(73 - 25) + chr(111) + chr(0b101111 + 0o4) + chr(0b11010 + 0o30) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(7889 - 7778) + chr(61 - 11) + '\061' + '\x35', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b101101 + 0o4) + '\x34' + chr(50), 17563 - 17555), ehT0Px3KOsy9(chr(48) + chr(2081 - 1970) + chr(0b110011) + chr(736 - 685) + chr(51), 29043 - 29035), ehT0Px3KOsy9('\x30' + chr(0b101001 + 0o106) + chr(0b110100 + 0o0), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1100110 + 0o11) + chr(1591 - 1540) + chr(316 - 261) + chr(49), 0o10), ehT0Px3KOsy9(chr(1216 - 1168) + chr(0b1101111) + chr(52) + chr(1156 - 1105), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(1659 - 1609) + '\063' + '\x33', 0b1000), ehT0Px3KOsy9(chr(2022 - 1974) + '\x6f' + chr(0b110011) + chr(48) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b1101111) + chr(52) + '\x31', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\063' + '\x33', 8), ehT0Px3KOsy9(chr(1722 - 1674) + '\157' + chr(51) + chr(1320 - 1267) + '\x35', 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + '\x36' + '\060', 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + chr(2423 - 2370) + chr(0b10011 + 0o36), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + chr(0b10111 + 0o40), 48280 - 48272)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b11011 + 0o32) + chr(0b110000), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xc6'), chr(0b1010011 + 0o21) + chr(101) + chr(99) + chr(7518 - 7407) + chr(0b1011101 + 0o7) + '\145')('\x75' + chr(116) + '\x66' + chr(45) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def cLzM01NYVQIH(kVFRD544hi_1, JsZ36NJUqtml, e80gRioCjdat, K1Ha0XjJTAE7, XUqE0GHx9ndw, HHpQzG13Xmp7):
xw4DsBfIJ22E = xafqLlk3kkUe(SXOLrMavuUCe(b'\x98\xe9\xca\xd8\x8b!\x97:\xe9\xffkx\x05\xee\x9d\xc5\x98'), chr(0b10 + 0o142) + '\x65' + chr(0b1100011) + chr(0b1101111) + chr(100) + '\145')(chr(117) + '\164' + '\146' + chr(958 - 913) + chr(0b111000)).V4roHaS3Ppej(xafqLlk3kkUe(SXOLrMavuUCe(b'\x9c\xfa\xd9\xc2\x8c'), chr(5247 - 5147) + chr(101) + chr(99) + chr(0b1101111) + chr(0b1100100) + '\x65')('\165' + '\x74' + chr(5360 - 5258) + '\x2d' + chr(0b111000)) if e80gRioCjdat else xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c\xed\xce'), chr(0b1100100) + chr(0b1100101) + '\143' + chr(0b1101111) + chr(100) + '\x65')(chr(0b111011 + 0o72) + '\x74' + chr(0b1100110) + '\x2d' + '\070'))
QlK7eAQfFWD3 = g1Z_RG9zP4cD.get_or_generate_tabbed_vocab(kVFRD544hi_1, JsZ36NJUqtml, xw4DsBfIJ22E, ehT0Px3KOsy9('\060' + chr(111) + '\x30', 0o10), K1Ha0XjJTAE7 + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb7\xfb\xd7\xde\x90,\x95K\xe6\xa0}3\x1b\xfc\xda\xc1\x84$\x8ey\xfd\x13\x9a'), chr(0b1100100) + chr(1485 - 1384) + chr(0b1000000 + 0o43) + chr(111) + '\x64' + chr(0b110111 + 0o56))(chr(0b111100 + 0o71) + '\164' + chr(0b1001110 + 0o30) + '\055' + chr(0b111000)) % XUqE0GHx9ndw, XUqE0GHx9ndw)
bjsd1KDtchwA = g1Z_RG9zP4cD.get_or_generate_tabbed_vocab(kVFRD544hi_1, JsZ36NJUqtml, xw4DsBfIJ22E, ehT0Px3KOsy9(chr(48) + '\157' + chr(49), ord("\x08")), K1Ha0XjJTAE7 + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb7\xfc\xd9\xd9\x85*\x84K\xe6\xa0}3\x1b\xfc\xda\xc1\x84$\x8ey\xfd\x13\x9a'), '\144' + '\x65' + '\143' + '\x6f' + chr(100) + chr(101))(chr(0b1110101) + chr(0b1110100) + '\146' + chr(0b1100 + 0o41) + chr(56)) % HHpQzG13Xmp7, HHpQzG13Xmp7)
oUSJt1egghhO = oqhJDdMJfuwx.path.join(JsZ36NJUqtml, xw4DsBfIJ22E)
return xafqLlk3kkUe(GkH56QMxhclz, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9c\xed\xc0\xdf\xd0;\x95\x1d\xe6\x90q3\x1b\xea\x86\xd6\x9f"\xb0~\xbdU\x91\x89\xbf\xb5'), '\x64' + chr(101) + chr(99) + chr(111) + '\x64' + '\x65')('\165' + chr(116) + chr(0b1100110) + chr(1337 - 1292) + '\070'))(xafqLlk3kkUe(GkH56QMxhclz, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9c\xed\xc0\xdf\xd0;\x95\x1d\xe6\x90b.\x01\xd0\x80\xd6\x89\x18\x86o\xb6D\x9f\x99\xb5\xa3'), '\144' + chr(0b1100101) + '\143' + chr(0b1101111) + chr(100) + '\x65')(chr(117) + chr(116) + chr(9727 - 9625) + '\x2d' + chr(188 - 132)))(oUSJt1egghhO), QlK7eAQfFWD3, bjsd1KDtchwA)
|
tensorflow/tensor2tensor
|
tensor2tensor/data_generators/ice_parsing.py
|
tabbed_parsing_character_generator
|
def tabbed_parsing_character_generator(tmp_dir, train):
"""Generate source and target data from a single file."""
character_vocab = text_encoder.ByteTextEncoder()
filename = "parsing_{0}.pairs".format("train" if train else "dev")
pair_filepath = os.path.join(tmp_dir, filename)
return text_problems.text2text_generate_encoded(
text_problems.text2text_txt_tab_iterator(pair_filepath), character_vocab)
|
python
|
def tabbed_parsing_character_generator(tmp_dir, train):
"""Generate source and target data from a single file."""
character_vocab = text_encoder.ByteTextEncoder()
filename = "parsing_{0}.pairs".format("train" if train else "dev")
pair_filepath = os.path.join(tmp_dir, filename)
return text_problems.text2text_generate_encoded(
text_problems.text2text_txt_tab_iterator(pair_filepath), character_vocab)
|
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Generate source and target data from a single file.
|
[
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/data_generators/ice_parsing.py#L53-L59
|
train
|
Generate source and target data from a single file.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + chr(1584 - 1531) + chr(0b101010 + 0o11), 0b1000), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(1123 - 1012) + chr(0b110001) + chr(54) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + chr(0b110000) + chr(1523 - 1474), 0o10), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(9709 - 9598) + chr(0b110010) + chr(0b101 + 0o60), 0b1000), ehT0Px3KOsy9(chr(0b111 + 0o51) + '\x6f' + '\x33' + chr(0b110011) + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(54) + chr(0b11010 + 0o31), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\063' + '\x37' + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + chr(281 - 233) + '\x35', 0b1000), ehT0Px3KOsy9(chr(889 - 841) + chr(0b1101111) + chr(940 - 889) + '\063' + chr(55), 8), ehT0Px3KOsy9(chr(131 - 83) + chr(111) + chr(0b10100 + 0o35) + chr(0b100110 + 0o20) + chr(0b1000 + 0o53), 18123 - 18115), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10101 + 0o36) + chr(2783 - 2729) + chr(1433 - 1378), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(49) + chr(53) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10101 + 0o40) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(10602 - 10491) + '\x31' + chr(53) + chr(0b100 + 0o54), 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + chr(52) + '\067', 49683 - 49675), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\157' + chr(2005 - 1956) + '\x36' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1010 + 0o145) + chr(49) + chr(0b110001) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(85 - 37) + '\157' + '\061' + '\067', 0b1000), ehT0Px3KOsy9(chr(48) + chr(1316 - 1205) + chr(0b110010) + '\x36' + chr(0b10110 + 0o32), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\x34' + '\x30', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\064', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101 + 0o142) + '\x32' + chr(328 - 273) + chr(2057 - 2003), 0b1000), ehT0Px3KOsy9(chr(1718 - 1670) + chr(0b1000 + 0o147) + '\061' + '\x36' + chr(2053 - 2002), 8), ehT0Px3KOsy9('\x30' + chr(111) + '\x31' + chr(2746 - 2692) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b1101111) + chr(51) + chr(0b101 + 0o53) + chr(1637 - 1586), 61019 - 61011), ehT0Px3KOsy9(chr(48) + chr(111) + chr(49) + '\065' + '\x35', 9389 - 9381), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(2500 - 2389) + chr(2410 - 2360) + '\x36' + '\x31', 37716 - 37708), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + chr(2101 - 2051) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + '\x37', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b1000 + 0o53) + '\064' + '\067', 8), ehT0Px3KOsy9(chr(1587 - 1539) + chr(0b1101111) + '\062' + '\x32' + chr(905 - 855), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1475 - 1424) + chr(49), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100101 + 0o14) + chr(54) + chr(839 - 788), 8), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(111) + '\063' + chr(55) + chr(160 - 112), 64595 - 64587), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(0b1010101 + 0o32) + '\062' + '\066' + chr(0b101100 + 0o11), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1000001 + 0o56) + '\x33' + chr(2338 - 2283) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061' + chr(0b110000) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(0b1110 + 0o44) + '\x36', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110 + 0o55) + '\x35' + '\x33', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + chr(637 - 588) + '\x30', 49471 - 49463)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b1100011 + 0o14) + chr(174 - 121) + chr(0b1101 + 0o43), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'E'), chr(1025 - 925) + chr(0b10000 + 0o125) + chr(99) + '\x6f' + chr(8488 - 8388) + chr(101))('\165' + '\x74' + '\146' + chr(0b100100 + 0o11) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def l8qj47zmHcHF(JsZ36NJUqtml, e80gRioCjdat):
Z9K10onjVV5P = nCRDzZ_Is9fz.ByteTextEncoder()
xw4DsBfIJ22E = xafqLlk3kkUe(SXOLrMavuUCe(b'\x1b\x10\xf3f\xb6]\x9e\x9a\xa4C\x8aF_\t\x8e\x02='), '\144' + chr(1550 - 1449) + '\143' + chr(111) + chr(0b110010 + 0o62) + '\x65')('\x75' + '\164' + '\x66' + '\x2d' + chr(0b110010 + 0o6)).V4roHaS3Ppej(xafqLlk3kkUe(SXOLrMavuUCe(b'\x1f\x03\xe0|\xb1'), '\144' + chr(101) + '\x63' + '\x6f' + chr(100) + chr(0b1100101))('\x75' + '\164' + '\x66' + chr(45) + chr(0b11 + 0o65)) if e80gRioCjdat else xafqLlk3kkUe(SXOLrMavuUCe(b'\x0f\x14\xf7'), '\144' + '\x65' + chr(0b1100011) + '\x6f' + chr(0b111001 + 0o53) + chr(0b1000 + 0o135))(chr(0b1110 + 0o147) + chr(116) + chr(0b1100110) + chr(644 - 599) + '\070'))
oUSJt1egghhO = oqhJDdMJfuwx.path.join(JsZ36NJUqtml, xw4DsBfIJ22E)
return xafqLlk3kkUe(GkH56QMxhclz, xafqLlk3kkUe(SXOLrMavuUCe(b'\x1f\x14\xf9a\xedG\x9c\xbd\xab,\x90\rA\r\x95\x11:j\xefEj\xdd\x1c\x11\xa6\t'), '\144' + chr(7611 - 7510) + chr(0b1001001 + 0o32) + chr(5213 - 5102) + chr(0b1100100) + chr(0b1100101))('\165' + chr(9320 - 9204) + '\x66' + '\055' + '\070'))(xafqLlk3kkUe(GkH56QMxhclz, xafqLlk3kkUe(SXOLrMavuUCe(b'\x1f\x14\xf9a\xedG\x9c\xbd\xab,\x83\x10[7\x93\x11,P\xd9Ta\xcc\x12\x01\xac\x1f'), chr(2611 - 2511) + chr(7836 - 7735) + chr(99) + chr(236 - 125) + chr(0b1100100) + chr(5203 - 5102))('\165' + chr(0b1 + 0o163) + chr(0b1100110) + chr(45) + chr(0b11001 + 0o37)))(oUSJt1egghhO), Z9K10onjVV5P)
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
_make_list
|
def _make_list(predictions, targets):
"""Helper: make predictions and targets lists, check they match on length."""
# Our models sometimes return predictions in lists, make it a list always.
# TODO(lukaszkaiser): make abstractions for nested structures and refactor.
if not isinstance(predictions, (list, tuple)):
if isinstance(targets, (list, tuple)):
raise ValueError("Targets are a list or tuple but predictions are not.")
predictions, targets = [predictions], [targets]
if len(predictions) != len(targets):
raise ValueError("Predictions and targets have different lengths.")
return list(predictions), list(targets)
|
python
|
def _make_list(predictions, targets):
"""Helper: make predictions and targets lists, check they match on length."""
# Our models sometimes return predictions in lists, make it a list always.
# TODO(lukaszkaiser): make abstractions for nested structures and refactor.
if not isinstance(predictions, (list, tuple)):
if isinstance(targets, (list, tuple)):
raise ValueError("Targets are a list or tuple but predictions are not.")
predictions, targets = [predictions], [targets]
if len(predictions) != len(targets):
raise ValueError("Predictions and targets have different lengths.")
return list(predictions), list(targets)
|
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] |
Helper: make predictions and targets lists, check they match on length.
|
[
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L54-L64
|
train
|
Helper function to make predictions and targets lists.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(0b1100010 + 0o15) + chr(0b110001) + chr(0b10111 + 0o35) + '\063', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(0b101011 + 0o5), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(9463 - 9352) + chr(55) + '\064', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + chr(2374 - 2323) + '\x31', 0b1000), ehT0Px3KOsy9(chr(113 - 65) + chr(111) + chr(0b10111 + 0o33) + chr(0b110110) + chr(0b110111), 60582 - 60574), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b10101 + 0o37) + chr(0b11 + 0o61), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(5672 - 5561) + chr(0b110110 + 0o1), 31470 - 31462), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + '\x36' + chr(0b10101 + 0o33), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b100100 + 0o15) + chr(49) + '\x37', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(1237 - 1187) + chr(922 - 870) + chr(1698 - 1646), 0o10), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(111) + chr(51) + chr(0b101101 + 0o7) + chr(51), 0o10), ehT0Px3KOsy9(chr(84 - 36) + chr(0b1101111) + chr(50) + chr(0b110101 + 0o1) + chr(2322 - 2273), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b101000 + 0o107) + '\063' + chr(1754 - 1699) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(1348 - 1300) + '\157' + chr(268 - 218) + chr(171 - 122) + '\064', 348 - 340), ehT0Px3KOsy9('\x30' + '\x6f' + chr(473 - 424) + '\060' + chr(0b110111), 36152 - 36144), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + chr(53) + chr(559 - 506), 0b1000), ehT0Px3KOsy9(chr(830 - 782) + chr(3555 - 3444) + chr(0b100 + 0o56) + '\066' + chr(0b10001 + 0o37), 50516 - 50508), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b11101 + 0o32) + chr(0b100000 + 0o21), ord("\x08")), ehT0Px3KOsy9('\060' + chr(2554 - 2443) + '\x33' + chr(48) + '\x35', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b110010) + '\060' + chr(0b101010 + 0o10), 0b1000), ehT0Px3KOsy9(chr(2158 - 2110) + chr(111) + chr(0b1100 + 0o45) + chr(52) + chr(51), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50) + '\x36' + '\x34', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b111100 + 0o63) + chr(421 - 371) + chr(0b11111 + 0o25) + chr(454 - 400), ord("\x08")), ehT0Px3KOsy9(chr(691 - 643) + '\157' + chr(0b10 + 0o61) + chr(53) + chr(2606 - 2552), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1493 - 1442) + '\064' + chr(0b110011), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(1776 - 1727) + chr(0b1100 + 0o46) + '\063', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\x31' + '\x33' + chr(0b110010 + 0o5), 0b1000), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b100000 + 0o117) + chr(0b110111) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(0b11001 + 0o126) + chr(0b110001) + chr(2075 - 2027) + chr(0b100010 + 0o17), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(11942 - 11831) + chr(51) + chr(158 - 108) + chr(0b11100 + 0o30), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\061' + '\066' + chr(0b110001 + 0o3), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110011) + chr(52) + '\x30', 42529 - 42521), ehT0Px3KOsy9('\060' + '\157' + '\x33' + '\062' + '\x32', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b0 + 0o66) + '\064', 0b1000), ehT0Px3KOsy9(chr(48) + chr(11699 - 11588) + chr(0b10111 + 0o40) + chr(0b101000 + 0o16), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\062' + chr(0b101011 + 0o10) + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + chr(9430 - 9319) + '\x31' + chr(49) + chr(55), 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b10011 + 0o36) + chr(1850 - 1801) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49) + chr(0b1100 + 0o50), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b111 + 0o51) + '\x6f' + chr(0b110101) + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'M'), '\x64' + chr(101) + chr(0b11101 + 0o106) + '\157' + chr(100) + chr(101))(chr(0b111000 + 0o75) + chr(0b1110100) + chr(10186 - 10084) + chr(1011 - 966) + chr(0b101011 + 0o15)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def B7W5SED2iol2(qIQi_VFCIFZL, xIEmRseySp3z):
if not PlSM16l2KDPD(qIQi_VFCIFZL, (YyaZ4tpXu4lf, KNyTy8rYcwji)):
if PlSM16l2KDPD(xIEmRseySp3z, (YyaZ4tpXu4lf, KNyTy8rYcwji)):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'7qN\xfe\xd2PtP.\xd6\x86\x91\x99\xac+\x04\xc3y\x19\xaa\xf0C\xc0\xd3\x9e\x8f6\x7fY4\xa0T\x90\xa0QZ\xf1,9e\x0c~O\xb9\xd6VbP!\xcb\x97\x9f'), chr(4092 - 3992) + '\x65' + '\x63' + '\157' + chr(0b1111 + 0o125) + chr(0b1001 + 0o134))(chr(12445 - 12328) + '\164' + '\x66' + chr(580 - 535) + chr(1149 - 1093)))
(qIQi_VFCIFZL, xIEmRseySp3z) = ([qIQi_VFCIFZL], [xIEmRseySp3z])
if c2A0yzQpDQB3(qIQi_VFCIFZL) != c2A0yzQpDQB3(xIEmRseySp3z):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'3bY\xfd\xdeGs\x19 \xca\x90\x91\x99\xe2#M\xc4lK\xa2\xe7\x17\xc7\x86\x86\x82%:\x1b%\xbd\x12\x86\xb7F[\xf6;m`\x06~[\xed\xdfW)'), '\144' + chr(6350 - 6249) + '\x63' + chr(111) + chr(2492 - 2392) + chr(101))(chr(10582 - 10465) + chr(632 - 516) + chr(102) + chr(0b10100 + 0o31) + '\x38'))
return (YyaZ4tpXu4lf(qIQi_VFCIFZL), YyaZ4tpXu4lf(xIEmRseySp3z))
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
masked_mean
|
def masked_mean(inputs, targets, mask_id=None):
"""Mean of the inputs but counting only those where targets != mask_id."""
inputs = [x.astype(np.float32) for x in inputs]
# We assume all elements in the list contribute equally.
# TODO(lukaszkaiser): remove this assumption (e.g., when masks differ).
length = len(inputs)
if mask_id is None:
# TODO(lukaszkaiser): can we just divide the sum by length? XLA optimizes?
return sum([np.mean(x) / length for x in inputs])
unmask = [1.0 - np.equal(t, mask_id).astype(np.float32) for t in targets]
return sum([np.sum(x * m) / (length * np.sum(m))
for x, m in zip(inputs, unmask)])
|
python
|
def masked_mean(inputs, targets, mask_id=None):
"""Mean of the inputs but counting only those where targets != mask_id."""
inputs = [x.astype(np.float32) for x in inputs]
# We assume all elements in the list contribute equally.
# TODO(lukaszkaiser): remove this assumption (e.g., when masks differ).
length = len(inputs)
if mask_id is None:
# TODO(lukaszkaiser): can we just divide the sum by length? XLA optimizes?
return sum([np.mean(x) / length for x in inputs])
unmask = [1.0 - np.equal(t, mask_id).astype(np.float32) for t in targets]
return sum([np.sum(x * m) / (length * np.sum(m))
for x, m in zip(inputs, unmask)])
|
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Mean of the inputs but counting only those where targets != mask_id.
|
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L68-L79
|
train
|
Mean of the inputs but counting only those where targets == mask_id.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(3081 - 2970) + chr(0b1111 + 0o43) + chr(53) + chr(0b100100 + 0o15), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(5526 - 5415) + '\x31' + chr(51), 46184 - 46176), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1896 - 1847) + chr(0b100100 + 0o20) + chr(0b110101 + 0o1), 38496 - 38488), ehT0Px3KOsy9(chr(0b0 + 0o60) + '\157' + '\061' + chr(354 - 303) + '\x37', 46945 - 46937), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110111) + chr(52), 0b1000), ehT0Px3KOsy9('\060' + chr(0b11100 + 0o123) + chr(2207 - 2158) + '\x37' + chr(1995 - 1940), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + chr(1956 - 1904) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(1288 - 1177) + chr(51) + chr(0b101110 + 0o2) + chr(0b100110 + 0o13), 0b1000), ehT0Px3KOsy9(chr(936 - 888) + chr(3877 - 3766) + chr(0b100100 + 0o15) + '\x36' + chr(542 - 489), 0o10), ehT0Px3KOsy9('\x30' + chr(0b111100 + 0o63) + chr(0b101001 + 0o10) + chr(54) + chr(0b110111), 15469 - 15461), ehT0Px3KOsy9(chr(1390 - 1342) + chr(0b100111 + 0o110) + '\x35' + chr(0b100101 + 0o21), 50462 - 50454), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(1649 - 1595) + '\x36', 20140 - 20132), ehT0Px3KOsy9('\060' + '\157' + chr(0b11010 + 0o27) + chr(0b10 + 0o64) + chr(0b110100), 39407 - 39399), ehT0Px3KOsy9('\060' + chr(425 - 314) + chr(0b110111) + chr(49), 58151 - 58143), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(2515 - 2461) + chr(1384 - 1335), 0b1000), ehT0Px3KOsy9('\060' + chr(4898 - 4787) + '\x33' + '\x31' + '\x34', 0o10), ehT0Px3KOsy9(chr(1367 - 1319) + chr(11689 - 11578) + chr(50) + chr(0b111 + 0o56) + '\062', 30100 - 30092), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(6852 - 6741) + '\061' + chr(0b110010) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(111) + chr(49) + chr(49) + chr(2018 - 1965), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + '\064' + chr(0b110000), 21353 - 21345), ehT0Px3KOsy9(chr(1380 - 1332) + chr(111) + '\x33' + '\062' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + '\x34' + '\x37', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + '\067' + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(1401 - 1353) + chr(111) + chr(0b10 + 0o61) + chr(1813 - 1758) + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000011 + 0o54) + '\x31' + chr(0b100010 + 0o24) + chr(2651 - 2597), 8), ehT0Px3KOsy9(chr(48) + chr(5253 - 5142) + chr(87 - 36) + chr(196 - 146), 0o10), ehT0Px3KOsy9('\060' + chr(0b1011 + 0o144) + chr(0b110010) + '\064' + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(291 - 180) + chr(51) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(1534 - 1486) + chr(0b1101111) + chr(0b110010) + '\061' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b1101100 + 0o3) + chr(0b10011 + 0o40) + chr(0b101001 + 0o12) + chr(55), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110110) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b1001100 + 0o43) + chr(2166 - 2115) + chr(2708 - 2653) + '\x37', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + '\064' + '\065', 45 - 37), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x33' + chr(87 - 36) + '\x37', 8), ehT0Px3KOsy9(chr(48) + chr(0b111010 + 0o65) + chr(0b100111 + 0o12) + chr(322 - 269) + chr(0b1010 + 0o52), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + chr(1958 - 1910) + '\061', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110100) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(111) + '\065' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110011) + chr(0b11101 + 0o26) + chr(0b110101 + 0o2), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(504 - 456) + '\157' + '\065' + chr(0b10111 + 0o31), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x87'), chr(0b10011 + 0o121) + '\145' + chr(1857 - 1758) + '\x6f' + '\144' + chr(101))('\165' + chr(2449 - 2333) + chr(102) + '\055' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def cw_lit_0tgaI(vXoupepMtCXU, xIEmRseySp3z, trCVl8AmSLLM=None):
vXoupepMtCXU = [OeWW0F1dBPRQ.astype(WqUC3KWvYVup.float32) for OeWW0F1dBPRQ in vXoupepMtCXU]
CHAOgk5VCHH_ = c2A0yzQpDQB3(vXoupepMtCXU)
if trCVl8AmSLLM is None:
return xkxBmo49x2An([xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc8Sc/+\x7f \xb7\xa0\x02\x1bY'), chr(0b1010001 + 0o23) + chr(0b1100101) + '\143' + '\157' + '\144' + '\x65')(chr(117) + chr(116) + chr(102) + chr(0b101101) + '\x38'))(OeWW0F1dBPRQ) / CHAOgk5VCHH_ for OeWW0F1dBPRQ in vXoupepMtCXU])
VaSywsJjEIhn = [1.0 - WqUC3KWvYVup.equal(YeT3l7JgTbWR, trCVl8AmSLLM).astype(WqUC3KWvYVup.float32) for YeT3l7JgTbWR in xIEmRseySp3z]
return xkxBmo49x2An([xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd1rs$2SK\xd8\xb9G6@'), '\144' + chr(0b101000 + 0o75) + '\143' + chr(0b110010 + 0o75) + chr(0b11011 + 0o111) + chr(8601 - 8500))(chr(0b1110101) + chr(0b1101101 + 0o7) + '\x66' + chr(781 - 736) + '\070'))(OeWW0F1dBPRQ * r8ufID9JCHnI) / (CHAOgk5VCHH_ * xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd1rs$2SK\xd8\xb9G6@'), '\x64' + '\x65' + '\x63' + '\157' + chr(5078 - 4978) + chr(2232 - 2131))('\165' + '\x74' + chr(8182 - 8080) + chr(45) + '\070'))(r8ufID9JCHnI)) for (OeWW0F1dBPRQ, r8ufID9JCHnI) in pZ0NK2y6HRbn(vXoupepMtCXU, VaSywsJjEIhn)])
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
accuracy
|
def accuracy(batch, model_predictions):
"""Calculate accuracy."""
_, targets = batch
model_predictions, targets = _make_list(model_predictions, targets)
correct = []
for (prediction, target) in zip(model_predictions, targets):
predicted_class = np.argmax(prediction, axis=-1)
correct.append(np.equal(predicted_class, target))
return masked_mean(correct, targets)
|
python
|
def accuracy(batch, model_predictions):
"""Calculate accuracy."""
_, targets = batch
model_predictions, targets = _make_list(model_predictions, targets)
correct = []
for (prediction, target) in zip(model_predictions, targets):
predicted_class = np.argmax(prediction, axis=-1)
correct.append(np.equal(predicted_class, target))
return masked_mean(correct, targets)
|
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] |
Calculate accuracy.
|
[
"Calculate",
"accuracy",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L82-L90
|
train
|
Calculate accuracy.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b11 + 0o60) + chr(0b110011) + chr(159 - 106), 23991 - 23983), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(0b1101111) + chr(0b110010) + '\060' + chr(1937 - 1887), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1010011 + 0o34) + chr(0b11111 + 0o30) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(7236 - 7125) + '\x31' + chr(49) + chr(52), 50607 - 50599), ehT0Px3KOsy9('\x30' + chr(0b111110 + 0o61) + '\061' + chr(1367 - 1316), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1001110 + 0o41) + chr(0b110001) + '\x33' + chr(0b100011 + 0o23), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + '\x32' + chr(0b11011 + 0o33), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110010) + chr(0b10011 + 0o37) + chr(0b1101 + 0o44), 24010 - 24002), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010 + 0o0) + chr(615 - 561) + '\064', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b10110 + 0o35) + '\x30' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\065' + chr(467 - 417), 43627 - 43619), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + chr(0b10101 + 0o35) + chr(0b11110 + 0o31), 0o10), ehT0Px3KOsy9(chr(1895 - 1847) + chr(111) + chr(49) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b101001 + 0o7) + '\x6f' + '\x32' + '\067' + chr(0b101100 + 0o13), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b1001 + 0o51) + '\x30' + '\062', 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + chr(0b1001 + 0o52) + chr(0b110000), 24827 - 24819), ehT0Px3KOsy9(chr(0b110000) + chr(7038 - 6927) + '\063' + '\066' + chr(0b11001 + 0o33), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(2615 - 2504) + chr(204 - 155) + chr(52) + chr(1186 - 1136), 20163 - 20155), ehT0Px3KOsy9(chr(387 - 339) + '\157' + '\x33' + '\064' + chr(0b110111), 22710 - 22702), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(49) + chr(0b110101), 64694 - 64686), ehT0Px3KOsy9('\x30' + chr(0b1011000 + 0o27) + chr(1612 - 1560) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(416 - 368) + '\157' + chr(50) + '\063' + chr(652 - 599), ord("\x08")), ehT0Px3KOsy9(chr(800 - 752) + chr(0b1101111) + chr(0b0 + 0o63) + '\x34' + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(52) + '\x36', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10011 + 0o43) + chr(0b100111 + 0o15), 46940 - 46932), ehT0Px3KOsy9('\060' + chr(2925 - 2814) + chr(51) + chr(0b110001) + chr(0b110001 + 0o0), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1523 - 1474) + chr(48) + '\061', 21655 - 21647), ehT0Px3KOsy9(chr(48) + chr(0b1010 + 0o145) + '\x31' + '\x33' + chr(0b1010 + 0o52), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b100011 + 0o17) + chr(0b110010) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + chr(0b10011 + 0o37) + chr(0b101011 + 0o11), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(315 - 266) + '\062', 57948 - 57940), ehT0Px3KOsy9('\060' + chr(0b1100 + 0o143) + '\061' + chr(2118 - 2066) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x34' + '\060', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + chr(0b1000 + 0o51) + chr(186 - 132), 49376 - 49368), ehT0Px3KOsy9('\x30' + chr(111) + chr(50) + chr(53) + '\x30', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x33' + chr(0b110010) + '\065', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(0b10011 + 0o36) + chr(52), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + chr(50) + chr(2476 - 2424), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + '\066' + '\x37', 51427 - 51419), ehT0Px3KOsy9(chr(48) + chr(0b101000 + 0o107) + chr(1529 - 1479) + chr(0b100000 + 0o24) + '\x33', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b101 + 0o152) + chr(53) + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf3'), '\x64' + '\145' + chr(0b1100011) + chr(111) + chr(0b1001 + 0o133) + chr(754 - 653))('\165' + chr(0b1110100) + '\x66' + chr(0b101101) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Nb7fObKn_ZBQ(dNwAahu8tvoY, RlyTNtStp_yT):
(VNGQdHSFPrso, xIEmRseySp3z) = dNwAahu8tvoY
(RlyTNtStp_yT, xIEmRseySp3z) = B7W5SED2iol2(RlyTNtStp_yT, xIEmRseySp3z)
Tt6DAvwz9s1U = []
for (ys6Y0jo7ObhM, GR1581dR5rDS) in pZ0NK2y6HRbn(RlyTNtStp_yT, xIEmRseySp3z):
O2jtkVYHAc1F = WqUC3KWvYVup.argmax(ys6Y0jo7ObhM, axis=-ehT0Px3KOsy9(chr(0b10101 + 0o33) + '\157' + chr(49), 0b1000))
xafqLlk3kkUe(Tt6DAvwz9s1U, xafqLlk3kkUe(SXOLrMavuUCe(b'\xbc\xf2J)e:'), '\x64' + chr(7482 - 7381) + '\143' + '\157' + chr(1728 - 1628) + '\x65')(chr(117) + chr(0b1110100) + '\x66' + chr(0b101101) + chr(2126 - 2070)))(xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb8\xf3O-g'), '\x64' + chr(3547 - 3446) + '\x63' + chr(0b1010011 + 0o34) + chr(100) + chr(0b100 + 0o141))(chr(117) + '\x74' + chr(102) + '\055' + chr(56)))(O2jtkVYHAc1F, GR1581dR5rDS))
return cw_lit_0tgaI(Tt6DAvwz9s1U, xIEmRseySp3z)
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
neg_log_perplexity
|
def neg_log_perplexity(batch, model_predictions):
"""Calculate negative log perplexity."""
_, targets = batch
model_predictions, targets = _make_list(model_predictions, targets)
xent = []
for (prediction, target) in zip(model_predictions, targets):
hot_target = layers.one_hot(target, prediction.shape[-1])
xent.append(np.sum(prediction * hot_target, axis=-1))
return masked_mean(xent, targets)
|
python
|
def neg_log_perplexity(batch, model_predictions):
"""Calculate negative log perplexity."""
_, targets = batch
model_predictions, targets = _make_list(model_predictions, targets)
xent = []
for (prediction, target) in zip(model_predictions, targets):
hot_target = layers.one_hot(target, prediction.shape[-1])
xent.append(np.sum(prediction * hot_target, axis=-1))
return masked_mean(xent, targets)
|
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] |
Calculate negative log perplexity.
|
[
"Calculate",
"negative",
"log",
"perplexity",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L93-L101
|
train
|
Calculate negative log perplexity.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(0b1100011 + 0o14) + chr(49) + '\064', 0o10), ehT0Px3KOsy9('\060' + chr(7775 - 7664) + '\062' + chr(1430 - 1382) + chr(0b100100 + 0o17), 24059 - 24051), ehT0Px3KOsy9('\x30' + chr(4255 - 4144) + '\x31' + chr(673 - 622) + chr(0b110110), 62478 - 62470), ehT0Px3KOsy9('\060' + chr(954 - 843) + chr(0b110001) + chr(268 - 214) + chr(0b11110 + 0o25), 0b1000), ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\157' + chr(0b11011 + 0o26) + '\065' + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + chr(0b11001 + 0o27) + chr(855 - 806), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + '\x35' + '\x31', 54058 - 54050), ehT0Px3KOsy9('\x30' + chr(0b1011110 + 0o21) + chr(2241 - 2191) + chr(0b110111) + '\065', 0o10), ehT0Px3KOsy9(chr(1388 - 1340) + chr(0b1101111) + '\x32' + chr(0b110111) + chr(1088 - 1040), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b110 + 0o151) + '\x34', 0o10), ehT0Px3KOsy9(chr(1410 - 1362) + '\x6f' + chr(0b110001) + chr(983 - 934) + chr(1050 - 1000), 35391 - 35383), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + chr(0b101101 + 0o5) + chr(0b101 + 0o54), 20184 - 20176), ehT0Px3KOsy9(chr(892 - 844) + chr(0b1101111) + chr(0b1010 + 0o51) + '\066' + chr(0b110011), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b1100 + 0o50) + chr(2588 - 2536), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\066' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b11011 + 0o30) + chr(0b110010) + chr(0b0 + 0o61), 59362 - 59354), ehT0Px3KOsy9(chr(224 - 176) + '\x6f' + chr(55) + '\063', 28626 - 28618), ehT0Px3KOsy9(chr(0b110000) + chr(6867 - 6756) + '\x32' + '\x36' + chr(0b0 + 0o64), ord("\x08")), ehT0Px3KOsy9(chr(415 - 367) + '\x6f' + chr(0b10000 + 0o42) + '\062' + chr(0b1 + 0o66), 0b1000), ehT0Px3KOsy9(chr(91 - 43) + chr(0b10011 + 0o134) + '\067' + chr(668 - 620), 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + chr(0b10011 + 0o44) + chr(526 - 471), ord("\x08")), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1101111) + chr(55) + chr(0b110 + 0o60), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1375 - 1325) + chr(0b11011 + 0o27) + '\061', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\062' + '\065' + chr(0b110110), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(388 - 337) + chr(0b110101) + chr(0b10110 + 0o41), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + '\x36' + chr(915 - 866), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x31' + chr(617 - 563), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1358 - 1307) + chr(0b101010 + 0o13) + chr(0b100000 + 0o23), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + chr(0b110101) + '\x36', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(50) + chr(0b1011 + 0o54), 0b1000), ehT0Px3KOsy9(chr(1702 - 1654) + '\x6f' + '\x33' + '\066' + '\x36', 0o10), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(111) + chr(51) + chr(54) + chr(0b10000 + 0o47), ord("\x08")), ehT0Px3KOsy9(chr(1084 - 1036) + chr(3671 - 3560) + chr(50) + '\066' + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b111 + 0o51) + '\x6f' + '\x31' + chr(0b110011) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + '\061' + chr(2072 - 2024), 5219 - 5211), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + chr(1046 - 995) + chr(0b100 + 0o57), 53652 - 53644), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + '\060' + chr(827 - 776), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(1435 - 1385) + chr(0b11100 + 0o24) + chr(0b100001 + 0o20), 0o10), ehT0Px3KOsy9('\060' + chr(0b101011 + 0o104) + '\x31' + chr(0b110100) + chr(52), 0o10), ehT0Px3KOsy9('\x30' + chr(600 - 489) + chr(1289 - 1239) + '\066' + '\061', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b101101 + 0o102) + chr(63 - 10) + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'"'), '\x64' + chr(0b110 + 0o137) + chr(0b1100011) + '\x6f' + '\144' + chr(2453 - 2352))(chr(9648 - 9531) + chr(3647 - 3531) + '\x66' + '\055' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def MuwB6IpD5T7A(dNwAahu8tvoY, RlyTNtStp_yT):
(VNGQdHSFPrso, xIEmRseySp3z) = dNwAahu8tvoY
(RlyTNtStp_yT, xIEmRseySp3z) = B7W5SED2iol2(RlyTNtStp_yT, xIEmRseySp3z)
_YHpmhjj_eGR = []
for (ys6Y0jo7ObhM, GR1581dR5rDS) in pZ0NK2y6HRbn(RlyTNtStp_yT, xIEmRseySp3z):
zt7LYzfBr2eK = sGi5Aql23May.Hq3fv4Yp0EhD(GR1581dR5rDS, ys6Y0jo7ObhM.nauYfLglTpcb[-ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49), 0o10)])
xafqLlk3kkUe(_YHpmhjj_eGR, xafqLlk3kkUe(SXOLrMavuUCe(b'm\xf3.\x16\x05\xa5'), chr(4624 - 4524) + '\145' + chr(0b110100 + 0o57) + chr(111) + chr(0b1100100) + '\x65')(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + chr(0b101101) + chr(56)))(xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b't\xe8&1\x06\xae\xdd\x84\xc06\x0b?'), chr(931 - 831) + chr(0b10110 + 0o117) + chr(99) + chr(8825 - 8714) + '\x64' + chr(0b1100101))(chr(2105 - 1988) + chr(0b1110100) + chr(102) + chr(0b1110 + 0o37) + chr(0b100101 + 0o23)))(ys6Y0jo7ObhM * zt7LYzfBr2eK, axis=-ehT0Px3KOsy9(chr(1257 - 1209) + '\x6f' + '\x31', 8)))
return cw_lit_0tgaI(_YHpmhjj_eGR, xIEmRseySp3z)
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
loss
|
def loss(params, batch, model_predict, rng):
"""Calculate loss."""
inputs, targets = batch
predictions = model_predict(inputs, params, rng=rng)
predictions, targets = _make_list(predictions, targets)
xent = []
for (pred, target) in zip(predictions, targets):
xent.append(np.sum(pred * layers.one_hot(target, pred.shape[-1]), axis=-1))
return - masked_mean(xent, targets)
|
python
|
def loss(params, batch, model_predict, rng):
"""Calculate loss."""
inputs, targets = batch
predictions = model_predict(inputs, params, rng=rng)
predictions, targets = _make_list(predictions, targets)
xent = []
for (pred, target) in zip(predictions, targets):
xent.append(np.sum(pred * layers.one_hot(target, pred.shape[-1]), axis=-1))
return - masked_mean(xent, targets)
|
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] |
Calculate loss.
|
[
"Calculate",
"loss",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L104-L112
|
train
|
Calculate loss.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(111) + chr(49) + chr(0b11100 + 0o31) + chr(0b101001 + 0o7), ord("\x08")), ehT0Px3KOsy9(chr(2031 - 1983) + chr(972 - 861) + '\063' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b1011 + 0o46) + '\063' + '\067', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + chr(55) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + chr(1500 - 1389) + '\x33' + '\062' + '\064', 0o10), ehT0Px3KOsy9(chr(2055 - 2007) + chr(0b1010010 + 0o35) + chr(0b110001) + '\x36' + chr(516 - 462), 0o10), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(1633 - 1522) + chr(0b110110) + chr(0b110110), 2213 - 2205), ehT0Px3KOsy9('\060' + chr(111) + chr(614 - 564) + chr(0b110010) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110 + 0o54) + '\x34' + chr(0b11001 + 0o36), 30274 - 30266), ehT0Px3KOsy9('\060' + chr(3996 - 3885) + chr(49) + chr(0b110010) + '\x31', 2468 - 2460), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(0b10010 + 0o45) + chr(51), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100110 + 0o14) + '\x34' + chr(50), 0b1000), ehT0Px3KOsy9(chr(257 - 209) + chr(807 - 696) + chr(0b101011 + 0o10) + '\062' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(1668 - 1620) + '\157' + '\x33' + chr(1974 - 1923) + chr(748 - 693), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b111110 + 0o61) + chr(0b110010) + chr(0b110000) + '\062', 63467 - 63459), ehT0Px3KOsy9('\060' + chr(8128 - 8017) + '\x33' + chr(51) + chr(1778 - 1729), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(0b110101), 8), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1101111) + chr(0b111 + 0o52) + chr(0b101010 + 0o15) + '\x37', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(1641 - 1589) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b1010101 + 0o32) + chr(0b110010) + chr(0b110011) + chr(0b101101 + 0o10), 0o10), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b11100 + 0o123) + chr(50) + chr(0b110100) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(1803 - 1755) + chr(0b1101111) + chr(0b110010) + chr(0b110011), 58389 - 58381), ehT0Px3KOsy9(chr(0b110000) + chr(0b111001 + 0o66) + '\x33' + chr(0b110111) + chr(0b110011), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x31' + chr(0b100 + 0o57) + chr(0b110100), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + chr(0b110100) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(111) + '\x36' + chr(797 - 746), ord("\x08")), ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\x6f' + '\063' + '\067', 0o10), ehT0Px3KOsy9(chr(516 - 468) + '\x6f' + chr(51) + chr(52), 0b1000), ehT0Px3KOsy9(chr(484 - 436) + chr(111) + chr(0b1011 + 0o54) + '\x32', 0b1000), ehT0Px3KOsy9(chr(374 - 326) + chr(8246 - 8135) + chr(0b110111) + '\x36', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\065' + '\065', 64214 - 64206), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + chr(0b10 + 0o56) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101111) + '\x32' + chr(0b110001) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b1101111) + chr(49) + chr(3003 - 2948) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\x32' + '\x34' + chr(0b110011), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\063' + chr(0b110111) + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b101100 + 0o7) + chr(50) + chr(0b110110), 2971 - 2963), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + '\x30' + chr(1335 - 1285), 55844 - 55836), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b100101 + 0o14) + chr(0b110000) + chr(186 - 135), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(111) + chr(53) + chr(48), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'F'), chr(100) + '\145' + chr(99) + chr(111) + chr(0b1100100) + chr(101))(chr(0b0 + 0o165) + chr(0b1110100) + chr(0b1100110) + chr(275 - 230) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def YpO0BcZ6fMsf(nEbJZ4wfte2w, dNwAahu8tvoY, KRRucTXFamOQ, OKPXzuZwN61O):
(vXoupepMtCXU, xIEmRseySp3z) = dNwAahu8tvoY
qIQi_VFCIFZL = KRRucTXFamOQ(vXoupepMtCXU, nEbJZ4wfte2w, rng=OKPXzuZwN61O)
(qIQi_VFCIFZL, xIEmRseySp3z) = B7W5SED2iol2(qIQi_VFCIFZL, xIEmRseySp3z)
_YHpmhjj_eGR = []
for (eyamnrN0elUS, GR1581dR5rDS) in pZ0NK2y6HRbn(qIQi_VFCIFZL, xIEmRseySp3z):
xafqLlk3kkUe(_YHpmhjj_eGR, xafqLlk3kkUe(SXOLrMavuUCe(b'\tm/\x1d\xba\x12'), '\144' + chr(101) + chr(0b1010001 + 0o22) + chr(111) + '\x64' + chr(101))(chr(0b10110 + 0o137) + '\164' + chr(0b11101 + 0o111) + chr(0b101101) + '\070'))(xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b"\x10v':\xb9\x19\x02\xab\xdfc\xfa\xcc"), chr(6886 - 6786) + chr(0b1100101) + '\143' + chr(0b1001 + 0o146) + '\x64' + chr(101))(chr(117) + chr(116) + chr(10102 - 10000) + chr(45) + chr(56)))(eyamnrN0elUS * xafqLlk3kkUe(sGi5Aql23May, xafqLlk3kkUe(SXOLrMavuUCe(b' ll\x1e\xa2Bo\xe2\x97\x14\xd3\xe6'), chr(3231 - 3131) + '\145' + chr(0b11001 + 0o112) + chr(111) + chr(100) + chr(0b1000001 + 0o44))(chr(117) + '\164' + chr(0b1100110) + chr(444 - 399) + chr(0b111000)))(GR1581dR5rDS, xafqLlk3kkUe(eyamnrN0elUS, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06|*!\xb2:Q\xfe\xf3!\xd8\xc0'), chr(0b1100100) + chr(0b1100101) + chr(0b1000111 + 0o34) + chr(0b1011000 + 0o27) + chr(6526 - 6426) + chr(0b1100101))(chr(0b1010011 + 0o42) + chr(13202 - 13086) + chr(0b1100110) + chr(0b100000 + 0o15) + '\070'))[-ehT0Px3KOsy9('\060' + chr(111) + '\061', 61933 - 61925)]), axis=-ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31', 8)))
return -cw_lit_0tgaI(_YHpmhjj_eGR, xIEmRseySp3z)
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
restore_state
|
def restore_state(output_dir):
"""Restore State."""
params_file = os.path.join(output_dir, "model.pkl")
if not gfile.exists(params_file):
return State(step=None, params=None, history=trax_history.History())
with gfile.GFile(params_file, "rb") as f:
(params, step, history) = pickle.load(f)
log("Model loaded from %s at step %d" % (params_file, step))
logging.debug("From loaded model : history = %s", history)
return State(step=step, params=params, history=history)
|
python
|
def restore_state(output_dir):
"""Restore State."""
params_file = os.path.join(output_dir, "model.pkl")
if not gfile.exists(params_file):
return State(step=None, params=None, history=trax_history.History())
with gfile.GFile(params_file, "rb") as f:
(params, step, history) = pickle.load(f)
log("Model loaded from %s at step %d" % (params_file, step))
logging.debug("From loaded model : history = %s", history)
return State(step=step, params=params, history=history)
|
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] |
Restore State.
|
[
"Restore",
"State",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L129-L139
|
train
|
Restore state from pickle file.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(111) + '\062' + chr(51) + chr(0b110000), 64426 - 64418), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(1187 - 1135) + '\066', 0b1000), ehT0Px3KOsy9(chr(2160 - 2112) + chr(0b110001 + 0o76) + chr(0b110010) + chr(0b110110) + '\x33', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b100100 + 0o113) + chr(0b10 + 0o60) + chr(50) + chr(1624 - 1569), 0b1000), ehT0Px3KOsy9('\x30' + chr(7000 - 6889) + '\063' + chr(1195 - 1144) + chr(51), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + '\064' + chr(51), 60523 - 60515), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + chr(0b110011) + '\060', 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1 + 0o61) + chr(0b101 + 0o60) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + '\060' + chr(1966 - 1912), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110110) + chr(1650 - 1596), 48194 - 48186), ehT0Px3KOsy9(chr(48) + chr(7672 - 7561) + chr(1775 - 1724) + '\063' + chr(51), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x32' + chr(0b10110 + 0o32) + chr(52), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10010 + 0o41) + chr(0b110100) + chr(0b110 + 0o60), 12690 - 12682), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010 + 0o0) + chr(0b110001) + chr(0b110111 + 0o0), 0o10), ehT0Px3KOsy9(chr(0b100111 + 0o11) + '\157' + chr(0b110011) + chr(0b10000 + 0o43) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32' + '\061' + chr(0b10 + 0o57), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + chr(1649 - 1598) + chr(0b111 + 0o53), 0b1000), ehT0Px3KOsy9('\x30' + chr(12167 - 12056) + '\062' + chr(0b1011 + 0o46) + chr(2998 - 2943), 8), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(111) + chr(454 - 403) + '\x30' + '\x35', 52482 - 52474), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(48) + chr(48), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\062' + chr(880 - 828) + '\064', 7051 - 7043), ehT0Px3KOsy9(chr(911 - 863) + chr(5809 - 5698) + chr(51) + chr(0b110110) + chr(0b11000 + 0o33), 0o10), ehT0Px3KOsy9(chr(185 - 137) + chr(9278 - 9167) + '\x33' + chr(51) + chr(1191 - 1138), 9906 - 9898), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + '\063' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010 + 0o145) + chr(1586 - 1535) + chr(53) + chr(2315 - 2262), 8537 - 8529), ehT0Px3KOsy9('\060' + chr(111) + '\x35' + chr(2320 - 2270), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1589 - 1539) + chr(0b101111 + 0o6), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\063' + '\067', 48635 - 48627), ehT0Px3KOsy9(chr(48) + chr(2920 - 2809) + chr(50) + chr(54) + '\061', 0b1000), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b101010 + 0o105) + chr(0b110001) + '\063' + '\064', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\062' + chr(0b110011) + chr(0b110110), 8), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(111) + '\062' + chr(1045 - 991) + '\063', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b10011 + 0o35) + '\157' + chr(0b110001) + chr(55) + '\x36', 55265 - 55257), ehT0Px3KOsy9(chr(2009 - 1961) + chr(5068 - 4957) + chr(49) + chr(0b1011 + 0o47) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + '\066' + chr(2405 - 2355), 44323 - 44315), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + chr(1796 - 1742) + '\061', 0o10), ehT0Px3KOsy9(chr(826 - 778) + '\x6f' + chr(0b110011) + chr(115 - 67) + '\x35', 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + chr(0b100000 + 0o20) + '\062', 51010 - 51002), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001) + chr(681 - 631) + chr(54), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(111) + chr(1372 - 1319) + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb6'), chr(0b1100100) + chr(101) + '\143' + chr(5267 - 5156) + chr(0b1100010 + 0o2) + '\x65')(chr(0b1110101) + '\x74' + chr(102) + chr(1225 - 1180) + chr(0b111 + 0o61)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def nlUwZia7nbz5(nd0OX_BS6_o4):
dk9FBhGiUbti = oqhJDdMJfuwx.path.join(nd0OX_BS6_o4, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf5\xc9\xd7\xf2\xb7\x8d\xe8\xc6*'), chr(6528 - 6428) + '\145' + chr(0b11010 + 0o111) + chr(0b1101111) + chr(0b1100100) + chr(101))(chr(0b1001011 + 0o52) + '\164' + '\x66' + '\055' + chr(2731 - 2675)))
if not xafqLlk3kkUe(YwCPldGHQanD, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfd\xde\xda\xe4\xaf\xd0'), chr(8606 - 8506) + chr(0b1100101) + chr(5228 - 5129) + '\157' + chr(0b1100100) + '\145')('\x75' + chr(0b1001010 + 0o52) + '\x66' + chr(0b101101) + chr(0b11100 + 0o34)))(dk9FBhGiUbti):
return uWBOm14kSj2p(step=None, params=None, history=xafqLlk3kkUe(IiBvQNmmYZwc, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd0\xcf\xc0\xe3\xb4\xd1\xe1'), '\x64' + chr(4407 - 4306) + chr(0b1100011) + '\x6f' + chr(0b10010 + 0o122) + '\145')(chr(9863 - 9746) + chr(0b1110100) + chr(102) + '\055' + chr(56)))())
with xafqLlk3kkUe(YwCPldGHQanD, xafqLlk3kkUe(SXOLrMavuUCe(b'\xdf\xe0\xda\xfb\xbe'), chr(0b1100100) + chr(101) + '\143' + chr(11446 - 11335) + chr(0b1100100) + chr(0b111110 + 0o47))('\165' + chr(11784 - 11668) + chr(0b1100000 + 0o6) + chr(0b101101) + '\x38'))(dk9FBhGiUbti, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\xc4'), chr(0b1100100) + chr(0b10010 + 0o123) + '\143' + chr(10242 - 10131) + chr(3130 - 3030) + '\x65')(chr(5217 - 5100) + '\164' + chr(102) + chr(45) + chr(56))) as EGyt1xfPT1P6:
(nEbJZ4wfte2w, kDuFsAhEatcU, sD1K7SLfPnDB) = b1Ng5DsPF9ZY.mxtdQMeiwJZJ(EGyt1xfPT1P6)
WHAFymdp8Jcy(xafqLlk3kkUe(SXOLrMavuUCe(b"\xd5\xc9\xd7\xf2\xb7\x83\xf4\xc2'R\xbe\xe0\xc6\xe9\xab\xe6\xb7\xaf\xe0\xb3\x84\x92\xa9\xbe\x9e^po\x91y\xfa"), chr(0b1100100) + chr(101) + chr(9297 - 9198) + '\x6f' + chr(0b1100100) + '\145')(chr(0b1110101) + chr(116) + '\146' + chr(45) + chr(56)) % (dk9FBhGiUbti, kDuFsAhEatcU))
xafqLlk3kkUe(UeotCCWOPSQS, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfc\xc3\xd1\xe2\xbc'), chr(0b1100100) + '\x65' + chr(0b1100011) + chr(111) + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + chr(0b101110 + 0o106) + '\x66' + '\x2d' + chr(534 - 478)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xde\xd4\xdc\xfa\xfb\xcf\xf7\xcc"S\xbf\xa4\x8b\xe0\xbd\xec\xb6\xaf\xff\xe0\xcc\x9a\xae\xea\x82Xl?\x8c|\xbb\xc0'), '\x64' + chr(101) + chr(0b110001 + 0o62) + '\157' + chr(0b1100100) + '\x65')('\x75' + '\x74' + chr(7191 - 7089) + chr(45) + chr(56)), sD1K7SLfPnDB)
return uWBOm14kSj2p(step=kDuFsAhEatcU, params=nEbJZ4wfte2w, history=sD1K7SLfPnDB)
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
save_state
|
def save_state(state, output_dir, keep=False):
"""Save State and optionally gin config."""
params_file = os.path.join(output_dir, "model.pkl")
with gfile.GFile(params_file, "wb") as f:
pickle.dump((state.params, state.step, state.history), f)
if keep:
params_file = os.path.join(output_dir, "model_{}.pkl".format(state.step))
with gfile.GFile(params_file, "wb") as f:
pickle.dump((state.params, state.step, state.history), f)
log("Model saved to %s" % params_file, stdout=False)
|
python
|
def save_state(state, output_dir, keep=False):
"""Save State and optionally gin config."""
params_file = os.path.join(output_dir, "model.pkl")
with gfile.GFile(params_file, "wb") as f:
pickle.dump((state.params, state.step, state.history), f)
if keep:
params_file = os.path.join(output_dir, "model_{}.pkl".format(state.step))
with gfile.GFile(params_file, "wb") as f:
pickle.dump((state.params, state.step, state.history), f)
log("Model saved to %s" % params_file, stdout=False)
|
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] |
Save State and optionally gin config.
|
[
"Save",
"State",
"and",
"optionally",
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"config",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L152-L161
|
train
|
Save state and optionally gin config.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + '\157' + '\063' + chr(0b101 + 0o57) + chr(0b110001 + 0o2), 0o10), ehT0Px3KOsy9(chr(1199 - 1151) + chr(0b11101 + 0o122) + chr(1791 - 1740) + '\063' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(7289 - 7178) + '\x33' + chr(0b10 + 0o63) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(1176 - 1127) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1723 - 1674) + chr(51) + chr(1626 - 1577), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + chr(0b110011) + chr(52), 8), ehT0Px3KOsy9('\060' + chr(0b110000 + 0o77) + chr(0b11100 + 0o27) + '\x34' + chr(52), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(0b100011 + 0o21) + chr(1573 - 1522), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(4133 - 4022) + chr(0b100110 + 0o13) + chr(0b110110) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(0b1101111) + '\061' + '\067' + '\067', ord("\x08")), ehT0Px3KOsy9('\060' + chr(1947 - 1836) + chr(49) + chr(0b110011) + '\x33', 43827 - 43819), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + '\062' + chr(0b110000 + 0o6), ord("\x08")), ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\x6f' + chr(0b110010 + 0o1) + chr(0b101101 + 0o5) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b110110 + 0o71) + '\061' + '\064' + '\x37', 43840 - 43832), ehT0Px3KOsy9('\x30' + '\x6f' + '\x32' + chr(0b110010) + chr(0b1000 + 0o54), 18505 - 18497), ehT0Px3KOsy9(chr(48) + chr(0b1001100 + 0o43) + chr(0b110010) + chr(0b10001 + 0o44) + chr(0b110111), 45313 - 45305), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + '\x30' + chr(2631 - 2578), 0o10), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b100111 + 0o110) + '\063' + chr(0b11100 + 0o27) + chr(0b110000), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110110) + '\066', 0b1000), ehT0Px3KOsy9('\x30' + chr(10300 - 10189) + chr(50) + chr(2317 - 2268) + '\065', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(166 - 116), ord("\x08")), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b1001011 + 0o44) + chr(0b110010) + chr(0b110011) + '\060', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\063' + chr(50) + chr(0b1101 + 0o51), 43690 - 43682), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\x6f' + '\061' + '\063' + chr(386 - 338), 49873 - 49865), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + chr(0b110010) + chr(1342 - 1290), 8), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1101111) + '\067' + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(51) + chr(1053 - 998) + chr(0b101110 + 0o6), 22113 - 22105), ehT0Px3KOsy9(chr(48) + '\157' + chr(52) + chr(0b110011), 43051 - 43043), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10000 + 0o41) + '\x34', 0b1000), ehT0Px3KOsy9(chr(1381 - 1333) + chr(0b1101111) + chr(0b110011) + chr(49) + chr(0b101010 + 0o15), 23889 - 23881), ehT0Px3KOsy9(chr(697 - 649) + chr(2796 - 2685) + '\062' + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x33' + chr(0b1001 + 0o51) + chr(51), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\x31' + '\066' + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + chr(1265 - 1211) + chr(0b11110 + 0o27), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + '\x34' + chr(381 - 329), 0b1000), ehT0Px3KOsy9(chr(1223 - 1175) + chr(0b1101111) + chr(0b11000 + 0o33) + '\065' + chr(1167 - 1112), 8), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + '\x34' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(691 - 643) + '\x6f' + chr(0b110001) + chr(48) + chr(924 - 872), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(258 - 207) + chr(993 - 938), 38581 - 38573)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110101) + '\060', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xcd'), chr(0b1001011 + 0o31) + chr(9025 - 8924) + chr(99) + chr(0b1101111) + '\x64' + chr(0b1100101))('\165' + chr(116) + '\x66' + '\x2d' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def KKcceDaTyz__(KKFQISrGeiAm, nd0OX_BS6_o4, KYBTv50xVjCE=ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b1101111) + chr(0b1111 + 0o41), 61025 - 61017)):
dk9FBhGiUbti = oqhJDdMJfuwx.path.join(nd0OX_BS6_o4, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e\xb3\x8bh5\xf2\x94\x08\x19'), '\x64' + chr(0b100 + 0o141) + '\x63' + chr(0b1101111) + chr(0b1100100) + chr(0b1100101))(chr(0b1000101 + 0o60) + chr(0b110000 + 0o104) + chr(0b1100110) + chr(0b101101 + 0o0) + chr(0b111000)))
with xafqLlk3kkUe(YwCPldGHQanD, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa4\x9a\x86a<'), chr(9225 - 9125) + chr(0b1100101) + chr(0b10111 + 0o114) + '\157' + chr(0b1100100) + '\x65')(chr(0b1100101 + 0o20) + '\164' + '\146' + '\x2d' + '\070'))(dk9FBhGiUbti, xafqLlk3kkUe(SXOLrMavuUCe(b'\x94\xbe'), '\x64' + chr(0b1000110 + 0o37) + '\143' + '\x6f' + '\x64' + chr(101))('\x75' + chr(0b101010 + 0o112) + chr(5160 - 5058) + '\055' + chr(133 - 77))) as EGyt1xfPT1P6:
xafqLlk3kkUe(b1Ng5DsPF9ZY, xafqLlk3kkUe(SXOLrMavuUCe(b'\x87\xa9\x82}'), chr(0b101 + 0o137) + chr(4596 - 4495) + chr(958 - 859) + '\157' + '\144' + '\145')(chr(0b11110 + 0o127) + '\164' + chr(0b1100110) + chr(0b11111 + 0o16) + chr(0b101010 + 0o16)))((xafqLlk3kkUe(KKFQISrGeiAm, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8d\x99\x8dG\x03\xe8\x93\x05\x01\x1ai\xe1'), '\144' + chr(0b1010101 + 0o20) + '\143' + chr(1694 - 1583) + '\144' + '\x65')('\165' + chr(116) + chr(102) + chr(0b101101) + chr(0b111000))), xafqLlk3kkUe(KKFQISrGeiAm, xafqLlk3kkUe(SXOLrMavuUCe(b'\x88\x98\x9aK*\x9d\x8c&\x14\x0b8\xc3'), chr(0b1100100) + chr(101) + chr(0b1100011) + chr(0b1101111) + '\x64' + '\145')('\x75' + '\x74' + chr(581 - 479) + '\055' + chr(0b110110 + 0o2))), xafqLlk3kkUe(KKFQISrGeiAm, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8b\xb5\x9cy6\xae\x9d'), chr(0b1000001 + 0o43) + chr(0b1000000 + 0o45) + '\x63' + '\157' + chr(6011 - 5911) + '\145')(chr(0b1110101) + '\164' + chr(0b1100110) + chr(0b101101) + chr(0b111000)))), EGyt1xfPT1P6)
if KYBTv50xVjCE:
dk9FBhGiUbti = oqhJDdMJfuwx.path.join(nd0OX_BS6_o4, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e\xb3\x8bh5\x83\x9f\x1e[\x0f0\xfa'), '\x64' + chr(1560 - 1459) + chr(7275 - 7176) + chr(111) + chr(0b110000 + 0o64) + chr(5982 - 5881))(chr(117) + chr(12941 - 12825) + chr(0b1100011 + 0o3) + chr(0b100001 + 0o14) + chr(56)).V4roHaS3Ppej(KKFQISrGeiAm.kDuFsAhEatcU))
with xafqLlk3kkUe(YwCPldGHQanD, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa4\x9a\x86a<'), chr(0b110011 + 0o61) + '\145' + chr(99) + chr(1296 - 1185) + '\x64' + chr(0b11000 + 0o115))(chr(117) + chr(0b1100110 + 0o16) + '\146' + chr(0b101101) + chr(0b111000)))(dk9FBhGiUbti, xafqLlk3kkUe(SXOLrMavuUCe(b'\x94\xbe'), chr(0b1100100) + chr(0b1100101) + '\143' + chr(6206 - 6095) + chr(4036 - 3936) + '\145')(chr(0b111001 + 0o74) + chr(116) + '\x66' + chr(1418 - 1373) + chr(0b1101 + 0o53))) as EGyt1xfPT1P6:
xafqLlk3kkUe(b1Ng5DsPF9ZY, xafqLlk3kkUe(SXOLrMavuUCe(b'\x87\xa9\x82}'), chr(0b1100100) + '\x65' + chr(8654 - 8555) + chr(0b110000 + 0o77) + chr(4117 - 4017) + chr(101))(chr(0b1000111 + 0o56) + chr(8443 - 8327) + '\146' + '\x2d' + chr(0b111000)))((xafqLlk3kkUe(KKFQISrGeiAm, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8d\x99\x8dG\x03\xe8\x93\x05\x01\x1ai\xe1'), chr(0b1100100) + chr(0b1100011 + 0o2) + chr(0b110000 + 0o63) + chr(2175 - 2064) + chr(0b0 + 0o144) + '\145')(chr(11776 - 11659) + chr(9039 - 8923) + chr(733 - 631) + '\x2d' + chr(0b111000))), xafqLlk3kkUe(KKFQISrGeiAm, xafqLlk3kkUe(SXOLrMavuUCe(b'\x88\x98\x9aK*\x9d\x8c&\x14\x0b8\xc3'), '\144' + '\x65' + chr(99) + chr(0b1101111) + chr(100) + chr(0b1011101 + 0o10))(chr(0b10001 + 0o144) + chr(0b1110 + 0o146) + chr(0b1100110) + chr(703 - 658) + chr(0b0 + 0o70))), xafqLlk3kkUe(KKFQISrGeiAm, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8b\xb5\x9cy6\xae\x9d'), chr(100) + '\145' + chr(1113 - 1014) + chr(11093 - 10982) + '\x64' + chr(1054 - 953))(chr(117) + chr(0b1110000 + 0o4) + '\146' + '\055' + '\x38'))), EGyt1xfPT1P6)
WHAFymdp8Jcy(xafqLlk3kkUe(SXOLrMavuUCe(b'\xae\xb3\x8bh5\xfc\x97\x02\x03\x1a?\xb6\xa6\x08\xb4\x8a\xb6'), chr(2393 - 2293) + chr(101) + chr(0b100 + 0o137) + '\x6f' + chr(0b1100100) + chr(0b1100101))(chr(11249 - 11132) + chr(6861 - 6745) + chr(102) + '\055' + chr(0b111000)) % dk9FBhGiUbti, stdout=ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(48), 8))
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
evaluate_train_and_eval
|
def evaluate_train_and_eval(step, inputs, predict_fun, eval_steps, rng,
train_sw=None, eval_sw=None, history=None):
"""Evalaute on train and eval data, and log metrics."""
step_log(step, "Evaluation")
train_metrics, eval_metrics = [
evaluate( # pylint: disable=g-complex-comprehension
itertools.islice(input_stream(), eval_steps),
predict_fun,
_METRICS,
rng)
for input_stream in
[inputs.train_eval_stream, inputs.eval_stream]]
if train_sw:
log_metrics(train_metrics, train_sw, "train", step, history=history)
if eval_sw:
log_metrics(eval_metrics, eval_sw, "eval", step, history=history)
step_log(step, "Finished evaluation")
return train_metrics, eval_metrics
|
python
|
def evaluate_train_and_eval(step, inputs, predict_fun, eval_steps, rng,
train_sw=None, eval_sw=None, history=None):
"""Evalaute on train and eval data, and log metrics."""
step_log(step, "Evaluation")
train_metrics, eval_metrics = [
evaluate( # pylint: disable=g-complex-comprehension
itertools.islice(input_stream(), eval_steps),
predict_fun,
_METRICS,
rng)
for input_stream in
[inputs.train_eval_stream, inputs.eval_stream]]
if train_sw:
log_metrics(train_metrics, train_sw, "train", step, history=history)
if eval_sw:
log_metrics(eval_metrics, eval_sw, "eval", step, history=history)
step_log(step, "Finished evaluation")
return train_metrics, eval_metrics
|
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] |
Evalaute on train and eval data, and log metrics.
|
[
"Evalaute",
"on",
"train",
"and",
"eval",
"data",
"and",
"log",
"metrics",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L172-L189
|
train
|
Evaluate on train and eval data and log metrics.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + '\x6f' + chr(0b10010 + 0o37) + chr(0b10011 + 0o35), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1760 - 1711) + chr(0b110111) + '\064', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + chr(51) + '\x34', 0o10), ehT0Px3KOsy9(chr(871 - 823) + chr(111) + '\061' + chr(0b110011) + chr(1186 - 1131), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + '\x36', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(1794 - 1746) + '\157' + '\x32' + chr(0b100110 + 0o12) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + chr(54) + '\060', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\062' + chr(788 - 733) + '\064', 1191 - 1183), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + chr(0b100111 + 0o16) + chr(0b110011), 0o10), ehT0Px3KOsy9('\x30' + chr(3231 - 3120) + chr(52) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(196 - 85) + chr(0b110011 + 0o0) + '\x35' + '\x31', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + chr(54) + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + chr(9768 - 9657) + '\063' + chr(0b110011) + '\066', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(9212 - 9101) + chr(0b110011) + chr(1255 - 1205) + chr(0b1111 + 0o42), 0o10), ehT0Px3KOsy9(chr(1842 - 1794) + chr(0b1101111) + '\061' + chr(1396 - 1344) + chr(0b110001 + 0o5), 18055 - 18047), ehT0Px3KOsy9(chr(0b10001 + 0o37) + '\x6f' + chr(0b110011) + chr(0b110111) + chr(0b1111 + 0o50), ord("\x08")), ehT0Px3KOsy9(chr(2244 - 2196) + chr(0b1101111) + chr(0b110010) + '\064' + '\x31', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(2943 - 2832) + chr(0b0 + 0o63) + '\x37' + chr(0b100000 + 0o27), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + chr(0b101010 + 0o14), ord("\x08")), ehT0Px3KOsy9(chr(1124 - 1076) + '\x6f' + chr(0b110011) + chr(0b110011) + '\067', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + '\067' + '\066', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(49) + chr(285 - 237) + chr(0b10000 + 0o41), 58966 - 58958), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + chr(0b100001 + 0o20) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(111) + '\062' + chr(50) + chr(55), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\067' + chr(0b110110), 0o10), ehT0Px3KOsy9('\060' + chr(178 - 67) + '\x32' + '\x31' + chr(260 - 208), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x32' + '\063' + chr(1831 - 1781), 0o10), ehT0Px3KOsy9('\x30' + chr(0b110011 + 0o74) + '\x32' + '\x33' + chr(53), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + '\060' + '\x35', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1001000 + 0o47) + '\063' + '\060' + chr(0b110111), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101001 + 0o6) + chr(479 - 429) + chr(0b1111 + 0o45) + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b10001 + 0o136) + '\061' + '\x33', 0b1000), ehT0Px3KOsy9(chr(2130 - 2082) + '\157' + chr(2231 - 2178) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(0b1101111) + chr(51) + chr(0b100111 + 0o20) + chr(0b10110 + 0o40), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(49) + '\x30', 8), ehT0Px3KOsy9(chr(48) + chr(0b111010 + 0o65) + chr(0b110101) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\x32' + '\x32' + chr(0b110011), 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\064' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1010010 + 0o35) + chr(0b110001) + chr(0b110100 + 0o3) + chr(1686 - 1638), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010 + 0o3) + '\x30', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'&'), '\x64' + chr(2721 - 2620) + chr(0b1100011) + chr(0b110111 + 0o70) + chr(2465 - 2365) + chr(8547 - 8446))(chr(0b1110101) + chr(0b1110100) + chr(102) + chr(45) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def vUII_0MJ6hhJ(kDuFsAhEatcU, vXoupepMtCXU, Zkpe_s4zIdFG, K3bHLghgmarn, OKPXzuZwN61O, ctt4rWba3c7D=None, PnA6lwGM1GND=None, sD1K7SLfPnDB=None):
COZYwvUvwkQz(kDuFsAhEatcU, xafqLlk3kkUe(SXOLrMavuUCe(b'M\n\xfd3cg\xf5\x19\xd3\xc5'), chr(6508 - 6408) + '\145' + chr(0b110001 + 0o62) + '\157' + chr(0b1100100) + '\145')('\x75' + chr(12692 - 12576) + chr(7795 - 7693) + '\x2d' + chr(2909 - 2853)))
(QB7zBR8PywQ1, gEY30c7K0x8W) = [Usx5_tnbQ5R4(nLSuLqmR6kNP.islice(UbxWqxh19pch(), K3bHLghgmarn), Zkpe_s4zIdFG, rvQbhJm5TAKt, OKPXzuZwN61O) for UbxWqxh19pch in [vXoupepMtCXU.train_eval_stream, vXoupepMtCXU.eval_stream]]
if ctt4rWba3c7D:
DeZNIRM1RGwj(QB7zBR8PywQ1, ctt4rWba3c7D, xafqLlk3kkUe(SXOLrMavuUCe(b'|\x0e\xfd6x'), '\144' + chr(0b1000110 + 0o37) + chr(3634 - 3535) + '\x6f' + '\x64' + chr(0b1011001 + 0o14))(chr(117) + chr(0b1110100) + '\x66' + chr(0b101101) + chr(0b100001 + 0o27)), kDuFsAhEatcU, history=sD1K7SLfPnDB)
if PnA6lwGM1GND:
DeZNIRM1RGwj(gEY30c7K0x8W, PnA6lwGM1GND, xafqLlk3kkUe(SXOLrMavuUCe(b'm\n\xfd3'), chr(100) + chr(101) + chr(99) + '\157' + chr(2481 - 2381) + chr(0b1100101))('\x75' + chr(0b111010 + 0o72) + chr(102) + chr(0b10101 + 0o30) + '\x38'), kDuFsAhEatcU, history=sD1K7SLfPnDB)
COZYwvUvwkQz(kDuFsAhEatcU, xafqLlk3kkUe(SXOLrMavuUCe(b'N\x15\xf26en\xe4\x14\x9c\xceP\x88\x1a\xab\xb0\x12\x96\xce\x91'), chr(0b11111 + 0o105) + chr(5207 - 5106) + chr(0b111011 + 0o50) + '\x6f' + chr(2714 - 2614) + chr(101))(chr(0b1110101) + '\164' + chr(102) + chr(1989 - 1944) + '\070'))
return (QB7zBR8PywQ1, gEY30c7K0x8W)
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
evaluate
|
def evaluate(inputs_stream, predict_fun, metric_funs, rng):
"""Evaluate.
Args:
inputs_stream: iterable of inputs to evaluate on.
predict_fun: function from inputs to predictions. params should already be
partially applied.
metric_funs: dict from metric name to metric function, which takes inputs
and predictions and returns a scalar metric value.
rng: random number generator.
Returns:
metrics: dict from metric name to metric value averaged over the number of
inputs.
"""
metrics = collections.defaultdict(float)
count = 0
for inp in inputs_stream:
count += 1
rng, subrng = jax_random.split(rng)
preds = predict_fun(inp[0], rng=subrng)
for m, f in six.iteritems(metric_funs):
metrics[m] += f(inp, preds)
return {m: v / count for (m, v) in six.iteritems(metrics)}
|
python
|
def evaluate(inputs_stream, predict_fun, metric_funs, rng):
"""Evaluate.
Args:
inputs_stream: iterable of inputs to evaluate on.
predict_fun: function from inputs to predictions. params should already be
partially applied.
metric_funs: dict from metric name to metric function, which takes inputs
and predictions and returns a scalar metric value.
rng: random number generator.
Returns:
metrics: dict from metric name to metric value averaged over the number of
inputs.
"""
metrics = collections.defaultdict(float)
count = 0
for inp in inputs_stream:
count += 1
rng, subrng = jax_random.split(rng)
preds = predict_fun(inp[0], rng=subrng)
for m, f in six.iteritems(metric_funs):
metrics[m] += f(inp, preds)
return {m: v / count for (m, v) in six.iteritems(metrics)}
|
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] |
Evaluate.
Args:
inputs_stream: iterable of inputs to evaluate on.
predict_fun: function from inputs to predictions. params should already be
partially applied.
metric_funs: dict from metric name to metric function, which takes inputs
and predictions and returns a scalar metric value.
rng: random number generator.
Returns:
metrics: dict from metric name to metric value averaged over the number of
inputs.
|
[
"Evaluate",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L192-L215
|
train
|
Evaluate.
.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1742 - 1694) + chr(6717 - 6606) + '\x32' + '\066' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\157' + chr(0b101110 + 0o5) + chr(51) + '\060', 15058 - 15050), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(111) + chr(51) + chr(0b101010 + 0o13) + chr(50), 37885 - 37877), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(2470 - 2359) + '\x36' + '\x33', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(108 - 55) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(377 - 329) + '\157' + '\x31' + '\060' + chr(0b110111), 53621 - 53613), ehT0Px3KOsy9('\x30' + chr(5972 - 5861) + '\x32' + chr(0b10000 + 0o42) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010) + chr(0b110010 + 0o5) + '\x30', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b11000 + 0o33) + '\061' + '\x36', 0o10), ehT0Px3KOsy9(chr(1782 - 1734) + chr(7950 - 7839) + chr(0b110001) + chr(0b110001) + chr(49), 48885 - 48877), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1101111) + chr(0b101110 + 0o5) + chr(0b100011 + 0o23) + chr(0b100110 + 0o12), 0b1000), ehT0Px3KOsy9('\x30' + chr(12015 - 11904) + chr(0b110100) + '\x34', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(0b101110 + 0o7) + chr(0b1000 + 0o54), ord("\x08")), ehT0Px3KOsy9(chr(0b110 + 0o52) + '\x6f' + chr(50) + '\x33' + chr(1565 - 1517), 0b1000), ehT0Px3KOsy9('\060' + chr(2530 - 2419) + chr(472 - 423) + chr(2608 - 2556) + '\061', 30574 - 30566), ehT0Px3KOsy9(chr(2174 - 2126) + chr(10234 - 10123) + chr(0b110001) + '\x36', 0o10), ehT0Px3KOsy9('\060' + '\157' + '\062' + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b10011 + 0o134) + '\x31' + chr(54) + chr(55), 29042 - 29034), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b10111 + 0o34) + chr(54) + chr(0b110000), 8), ehT0Px3KOsy9(chr(48) + '\157' + '\067' + '\066', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11101 + 0o26), 11734 - 11726), ehT0Px3KOsy9('\060' + '\157' + '\062' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1010100 + 0o33) + '\063' + '\066' + '\062', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\063' + chr(0b110100) + chr(49), 13513 - 13505), ehT0Px3KOsy9('\060' + chr(0b1000000 + 0o57) + chr(310 - 260) + chr(1460 - 1409) + '\060', 8), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1101111) + chr(1613 - 1563) + chr(0b10100 + 0o34) + '\x32', 65125 - 65117), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011) + chr(0b110001) + chr(0b1101 + 0o47), 35353 - 35345), ehT0Px3KOsy9('\060' + chr(0b1011110 + 0o21) + '\064' + chr(48), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b100011 + 0o114) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(111) + chr(868 - 817) + chr(55) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1001010 + 0o45) + chr(1201 - 1147) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x36' + chr(1858 - 1807), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(2018 - 1967) + '\x35' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b100010 + 0o22) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(1985 - 1937) + chr(2179 - 2068) + chr(0b110010) + chr(53), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1011100 + 0o23) + '\x33' + chr(0b101110 + 0o4) + chr(0b101100 + 0o13), 52855 - 52847), ehT0Px3KOsy9(chr(1347 - 1299) + chr(0b100100 + 0o113) + chr(50) + '\060', 0o10), ehT0Px3KOsy9('\060' + chr(7513 - 7402) + chr(0b0 + 0o63) + '\060' + chr(0b101101 + 0o7), 24891 - 24883), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\157' + '\063' + chr(2379 - 2326), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(52) + chr(0b110 + 0o56), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(2000 - 1952) + chr(0b1001101 + 0o42) + chr(53) + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x98'), '\x64' + '\145' + chr(0b1100011) + chr(0b1010000 + 0o37) + chr(0b1100100) + chr(0b100000 + 0o105))('\x75' + '\x74' + '\146' + chr(45) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Usx5_tnbQ5R4(k9AHAMqNQuYF, Zkpe_s4zIdFG, SeQBpZQIQbiF, OKPXzuZwN61O):
yYegMqDoSfs5 = FGhnnwoh1Dd8.defaultdict(kkSX4ccExqw4)
ualWdDeXJEGO = ehT0Px3KOsy9(chr(48) + chr(8053 - 7942) + chr(1462 - 1414), 0o10)
for _axPQ91Y6C0x in k9AHAMqNQuYF:
ualWdDeXJEGO += ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\x6f' + '\x31', 61669 - 61661)
(OKPXzuZwN61O, iq95UtudmcSD) = Fei3U0xopite.split(OKPXzuZwN61O)
rFir39ju85_Z = Zkpe_s4zIdFG(_axPQ91Y6C0x[ehT0Px3KOsy9(chr(439 - 391) + chr(0b1001010 + 0o45) + chr(0b110000), 8)], rng=iq95UtudmcSD)
for (r8ufID9JCHnI, EGyt1xfPT1P6) in xafqLlk3kkUe(sYby0kpfssd4, xafqLlk3kkUe(SXOLrMavuUCe(b'\xdf\xac\x8fAC3\xf2\xd5\xbd'), chr(100) + '\x65' + '\143' + chr(0b11001 + 0o126) + chr(6980 - 6880) + chr(0b1001011 + 0o32))(chr(0b1110101) + '\164' + chr(0b1100110) + chr(0b101101) + '\x38'))(SeQBpZQIQbiF):
yYegMqDoSfs5[r8ufID9JCHnI] += EGyt1xfPT1P6(_axPQ91Y6C0x, rFir39ju85_Z)
return {r8ufID9JCHnI: cMbll0QYhULo / ualWdDeXJEGO for (r8ufID9JCHnI, cMbll0QYhULo) in xafqLlk3kkUe(sYby0kpfssd4, xafqLlk3kkUe(SXOLrMavuUCe(b'\xdf\xac\x8fAC3\xf2\xd5\xbd'), '\144' + '\145' + chr(99) + '\x6f' + '\144' + '\145')(chr(117) + chr(0b11111 + 0o125) + chr(130 - 28) + chr(1807 - 1762) + chr(0b101 + 0o63)))(yYegMqDoSfs5)}
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
log_metrics
|
def log_metrics(metrics, summ_writer, log_prefix, step, history=None):
"""Log metrics to summary writer and history."""
rjust_len = max([len(name) for name in metrics])
for name, value in six.iteritems(metrics):
step_log(step, "%s %s | % .8f" % (
log_prefix.ljust(5), name.rjust(rjust_len), value))
full_name = "metrics/" + name
if history:
history.append(log_prefix, full_name, step, value)
if summ_writer:
summ_writer.scalar(full_name, value, step)
|
python
|
def log_metrics(metrics, summ_writer, log_prefix, step, history=None):
"""Log metrics to summary writer and history."""
rjust_len = max([len(name) for name in metrics])
for name, value in six.iteritems(metrics):
step_log(step, "%s %s | % .8f" % (
log_prefix.ljust(5), name.rjust(rjust_len), value))
full_name = "metrics/" + name
if history:
history.append(log_prefix, full_name, step, value)
if summ_writer:
summ_writer.scalar(full_name, value, step)
|
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] |
Log metrics to summary writer and history.
|
[
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L218-L228
|
train
|
Log metrics to summary writer and history.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31' + '\060' + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(0b1101111) + chr(52) + '\061', 43834 - 43826), ehT0Px3KOsy9(chr(48) + chr(0b111 + 0o150) + chr(0b110011) + chr(110 - 62) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\064' + chr(0b1011 + 0o50), 4017 - 4009), ehT0Px3KOsy9('\x30' + chr(6897 - 6786) + chr(0b11111 + 0o22) + chr(0b110000) + chr(0b100100 + 0o16), 0o10), ehT0Px3KOsy9('\060' + chr(5972 - 5861) + chr(0b110011) + '\060' + chr(815 - 764), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b101011 + 0o6) + '\x36' + chr(2728 - 2674), 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\x6f' + '\x32' + chr(0b110011 + 0o2) + chr(52), 0o10), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(9763 - 9652) + '\063' + chr(1814 - 1765) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101110 + 0o1) + chr(0b1000 + 0o52) + chr(0b10010 + 0o44) + '\x34', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(50) + chr(0b101011 + 0o11) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(8421 - 8310) + chr(298 - 246) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(871 - 823) + '\157' + chr(541 - 486) + chr(0b110101), 20356 - 20348), ehT0Px3KOsy9(chr(0b110000) + chr(0b100010 + 0o115) + chr(51) + '\x36' + chr(0b10001 + 0o44), ord("\x08")), ehT0Px3KOsy9(chr(239 - 191) + '\x6f' + chr(0b110001) + chr(0b110111) + chr(0b10001 + 0o40), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x31' + chr(0b110011) + chr(55), 0b1000), ehT0Px3KOsy9('\x30' + chr(9089 - 8978) + chr(0b110010) + '\066' + chr(0b11000 + 0o30), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50), 0o10), ehT0Px3KOsy9('\060' + chr(4196 - 4085) + chr(49) + chr(0b11 + 0o55) + chr(51), 8), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(111) + chr(0b1110 + 0o43) + chr(225 - 174) + chr(2896 - 2842), ord("\x08")), ehT0Px3KOsy9(chr(2059 - 2011) + '\157' + chr(2085 - 2036) + chr(48) + chr(80 - 29), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(1046 - 996) + chr(0b11001 + 0o30) + '\065', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1843 - 1793) + chr(0b110101) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(729 - 678) + '\x30', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + '\x32' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + chr(0b11111 + 0o27) + chr(0b100111 + 0o15), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(382 - 334) + '\157' + chr(0b11101 + 0o27), 4702 - 4694), ehT0Px3KOsy9(chr(1301 - 1253) + '\157' + '\x32' + '\066' + chr(0b110100 + 0o0), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061' + '\067' + chr(1846 - 1795), 5091 - 5083), ehT0Px3KOsy9(chr(0b10101 + 0o33) + '\157' + chr(49) + chr(0b110101) + chr(953 - 901), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\061' + '\x32' + chr(52), 1993 - 1985), ehT0Px3KOsy9(chr(48) + chr(111) + chr(274 - 225) + chr(0b11001 + 0o32) + '\x34', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\062' + chr(0b110011) + chr(152 - 102), ord("\x08")), ehT0Px3KOsy9(chr(1909 - 1861) + '\157' + chr(49) + chr(50) + chr(1772 - 1717), 0o10), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\157' + chr(0b101111 + 0o4) + '\066' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b111 + 0o150) + '\x32' + chr(1954 - 1906) + chr(1516 - 1465), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001 + 0o2) + '\060' + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011011 + 0o24) + '\x33' + chr(51) + chr(0b1100 + 0o52), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b10100 + 0o133) + chr(0b101001 + 0o14) + chr(0b110011), 44075 - 44067)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x35' + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'm'), chr(100) + '\145' + chr(218 - 119) + '\157' + '\144' + chr(101))('\165' + chr(0b1110100) + chr(6516 - 6414) + chr(0b101101) + chr(0b110110 + 0o2)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def DeZNIRM1RGwj(yYegMqDoSfs5, op19uQAGLLyD, Fdo7WTLH5p9J, kDuFsAhEatcU, sD1K7SLfPnDB=None):
UIJb3mew79tN = tsdjvlgh9gDP([c2A0yzQpDQB3(AIvJRzLdDfgF) for AIvJRzLdDfgF in yYegMqDoSfs5])
for (AIvJRzLdDfgF, QmmgWUB13VCJ) in xafqLlk3kkUe(sYby0kpfssd4, xafqLlk3kkUe(SXOLrMavuUCe(b'*U\xa1Q+\xb7\x13\xc1\xb9'), '\x64' + '\145' + chr(99) + chr(628 - 517) + '\x64' + chr(0b1001101 + 0o30))(chr(3245 - 3128) + '\x74' + '\146' + '\x2d' + '\x38'))(yYegMqDoSfs5):
COZYwvUvwkQz(kDuFsAhEatcU, xafqLlk3kkUe(SXOLrMavuUCe(b'fR\xe4\x061\xe3\n\x8c\xef\x94\x8c\x1d['), chr(100) + '\145' + chr(0b11111 + 0o104) + chr(0b1101111) + '\x64' + '\145')(chr(0b1110101) + '\164' + chr(102) + chr(0b101101) + '\x38') % (xafqLlk3kkUe(Fdo7WTLH5p9J, xafqLlk3kkUe(SXOLrMavuUCe(b'/K\xb1P6'), '\144' + '\145' + chr(0b111110 + 0o45) + chr(0b110010 + 0o75) + '\144' + '\145')('\165' + chr(0b1011010 + 0o32) + chr(0b1100110) + chr(1067 - 1022) + chr(0b10101 + 0o43)))(ehT0Px3KOsy9(chr(1563 - 1515) + chr(0b1101111) + '\065', ord("\x08"))), xafqLlk3kkUe(AIvJRzLdDfgF, xafqLlk3kkUe(SXOLrMavuUCe(b'1K\xb1P6'), chr(100) + '\x65' + chr(1202 - 1103) + chr(0b1101111) + '\144' + '\145')(chr(117) + '\x74' + chr(0b1011011 + 0o13) + chr(0b101101) + chr(0b110110 + 0o2)))(UIJb3mew79tN), QmmgWUB13VCJ))
je7_3_Zvuq2o = xafqLlk3kkUe(SXOLrMavuUCe(b'.D\xb0Q+\xa0\x05\x83'), '\144' + '\x65' + chr(2265 - 2166) + chr(0b1101111) + '\144' + '\145')(chr(0b1101 + 0o150) + chr(0b1110100) + chr(0b1100110) + chr(45) + '\070') + AIvJRzLdDfgF
if sD1K7SLfPnDB:
xafqLlk3kkUe(sD1K7SLfPnDB, xafqLlk3kkUe(SXOLrMavuUCe(b'"Q\xb4F,\xa7'), '\144' + '\x65' + chr(99) + chr(10046 - 9935) + chr(0b1100100) + '\145')(chr(117) + '\164' + chr(0b1100110) + chr(514 - 469) + chr(0b11 + 0o65)))(Fdo7WTLH5p9J, je7_3_Zvuq2o, kDuFsAhEatcU, QmmgWUB13VCJ)
if op19uQAGLLyD:
xafqLlk3kkUe(op19uQAGLLyD, xafqLlk3kkUe(SXOLrMavuUCe(b'0B\xa5O#\xb1'), chr(3431 - 3331) + chr(0b1100101) + chr(0b1000 + 0o133) + '\x6f' + '\144' + chr(0b100101 + 0o100))(chr(117) + '\164' + '\146' + chr(45) + '\x38'))(je7_3_Zvuq2o, QmmgWUB13VCJ, kDuFsAhEatcU)
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
get_random_number_generator_and_set_seed
|
def get_random_number_generator_and_set_seed(seed=None):
"""Get a JAX random number generator and set random seed everywhere."""
random.seed(seed)
# While python random accepts None as seed and uses time/os seed then,
# some other functions expect integers so we create one here.
if seed is None:
seed = random.randint(0, 2**31 - 1)
tf.set_random_seed(seed)
numpy.random.seed(seed)
return jax_random.get_prng(seed)
|
python
|
def get_random_number_generator_and_set_seed(seed=None):
"""Get a JAX random number generator and set random seed everywhere."""
random.seed(seed)
# While python random accepts None as seed and uses time/os seed then,
# some other functions expect integers so we create one here.
if seed is None:
seed = random.randint(0, 2**31 - 1)
tf.set_random_seed(seed)
numpy.random.seed(seed)
return jax_random.get_prng(seed)
|
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] |
Get a JAX random number generator and set random seed everywhere.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L231-L240
|
train
|
Get a JAX random number generator and set random seed everywhere.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(12265 - 12154) + chr(51) + '\066' + chr(0b10110 + 0o33), 22769 - 22761), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + chr(0b101000 + 0o17) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1339 - 1287) + chr(51), 46572 - 46564), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + chr(50) + chr(0b100011 + 0o21), ord("\x08")), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1101111) + '\061' + chr(54) + chr(0b11111 + 0o25), 7753 - 7745), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(0b1101111) + chr(0b110000 + 0o5) + chr(0b10001 + 0o45), ord("\x08")), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\x6f' + chr(0b1000 + 0o52) + '\063' + chr(0b11111 + 0o24), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + chr(49) + chr(0b110 + 0o54), 0o10), ehT0Px3KOsy9(chr(1861 - 1813) + chr(0b1100011 + 0o14) + chr(640 - 589) + '\060', 0b1000), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b1101111) + chr(1937 - 1886) + '\067' + chr(2379 - 2329), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(5242 - 5131) + chr(0b100111 + 0o13) + '\061' + chr(0b10001 + 0o44), 0o10), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(0b11000 + 0o127) + chr(0b1111 + 0o43) + chr(0b11011 + 0o33) + chr(0b11010 + 0o27), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(678 - 628) + '\064' + chr(52), 4466 - 4458), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1867 - 1817) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(111) + chr(0b110101) + chr(1292 - 1238), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2531 - 2480) + chr(1810 - 1761) + '\065', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1822 - 1771) + chr(2585 - 2534), 0b1000), ehT0Px3KOsy9(chr(524 - 476) + '\157' + chr(0b1011 + 0o50) + chr(50) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(946 - 898) + '\157' + '\x32' + '\065' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(0b110111) + '\x32', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(4479 - 4368) + chr(0b1110 + 0o43) + chr(1457 - 1407) + chr(0b110000), 10497 - 10489), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001 + 0o0) + chr(0b110101) + chr(49), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\063' + '\061' + chr(1425 - 1370), ord("\x08")), ehT0Px3KOsy9(chr(1197 - 1149) + chr(111) + chr(1911 - 1861) + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b101 + 0o152) + chr(0b110001) + '\x33' + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(111) + '\x33' + chr(0b10100 + 0o34) + chr(0b110100), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101010 + 0o5) + '\x33' + chr(0b110000) + '\x31', 0o10), ehT0Px3KOsy9(chr(1587 - 1539) + '\157' + chr(0b110011) + chr(0b100100 + 0o14) + '\066', 0b1000), ehT0Px3KOsy9('\060' + chr(11187 - 11076) + chr(0b110010) + chr(0b101001 + 0o13) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49) + chr(940 - 892) + '\067', 0o10), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b1011010 + 0o25) + chr(0b110010) + chr(51) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\066' + '\061', 31134 - 31126), ehT0Px3KOsy9('\060' + '\x6f' + '\x31' + chr(2523 - 2471) + chr(523 - 475), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(2181 - 2070) + '\062' + chr(48) + chr(923 - 869), ord("\x08")), ehT0Px3KOsy9(chr(1598 - 1550) + '\157' + chr(0b1010 + 0o50) + '\x37' + chr(0b101100 + 0o11), ord("\x08")), ehT0Px3KOsy9(chr(827 - 779) + chr(111) + chr(150 - 99) + chr(0b11010 + 0o26) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + '\066' + chr(1744 - 1691), 0o10), ehT0Px3KOsy9(chr(0b100000 + 0o20) + '\157' + chr(0b100000 + 0o22) + chr(0b110010) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b11001 + 0o126) + chr(0b11110 + 0o25) + '\x31' + chr(53), 8), ehT0Px3KOsy9(chr(1543 - 1495) + chr(0b100010 + 0o115) + chr(736 - 686) + chr(270 - 217), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(0b1101111) + chr(0b110010 + 0o3) + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xdf'), chr(4139 - 4039) + chr(0b1100101) + '\x63' + '\x6f' + '\144' + chr(1825 - 1724))(chr(117) + '\164' + chr(0b1010001 + 0o25) + chr(0b101101) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def KAhsRxZxzwv1(cEhryM0YPR0h=None):
xafqLlk3kkUe(drxw09AdRdci, xafqLlk3kkUe(SXOLrMavuUCe(b'\x82\x1aF\xf0'), '\144' + chr(0b101111 + 0o66) + '\x63' + '\x6f' + '\x64' + chr(8374 - 8273))(chr(0b1110101) + chr(7176 - 7060) + '\146' + '\x2d' + chr(0b11000 + 0o40)))(cEhryM0YPR0h)
if cEhryM0YPR0h is None:
cEhryM0YPR0h = drxw09AdRdci.randint(ehT0Px3KOsy9(chr(360 - 312) + chr(0b1101000 + 0o7) + '\x30', 0b1000), ehT0Px3KOsy9(chr(2182 - 2134) + chr(0b100000 + 0o117) + '\x32', 0b1000) ** ehT0Px3KOsy9('\x30' + '\157' + chr(51) + chr(1973 - 1918), ord("\x08")) - ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(111) + '\x31', 0b1000))
xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x82\x1aW\xcb\x06O\xf5.w\x97\xd2\xc2\xc1pJ'), chr(1949 - 1849) + '\145' + chr(0b1000111 + 0o34) + chr(11470 - 11359) + '\144' + chr(6391 - 6290))(chr(4096 - 3979) + chr(0b1110100) + chr(0b1011100 + 0o12) + '\055' + chr(56)))(cEhryM0YPR0h)
xafqLlk3kkUe(n8mpNwkrxOdz.random, xafqLlk3kkUe(SXOLrMavuUCe(b'\x82\x1aF\xf0'), '\144' + chr(810 - 709) + '\x63' + '\157' + chr(7712 - 7612) + chr(1817 - 1716))(chr(0b111101 + 0o70) + '\164' + '\x66' + '\055' + '\070'))(cEhryM0YPR0h)
return xafqLlk3kkUe(Fei3U0xopite, xafqLlk3kkUe(SXOLrMavuUCe(b'\x96\x1aW\xcb\x04\\\xf5-'), '\x64' + chr(101) + chr(99) + chr(6277 - 6166) + '\x64' + chr(5850 - 5749))(chr(0b111000 + 0o75) + chr(0b110010 + 0o102) + chr(10019 - 9917) + chr(0b111 + 0o46) + chr(1406 - 1350)))(cEhryM0YPR0h)
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
epochs
|
def epochs(steps=None, epoch_steps=1):
"""Iterator over epochs until steps is reached. 1-indexed.
Args:
steps: int, total number of steps. Infinite if None.
epoch_steps: int, number of steps per epoch. Can also be an iterable<int> to
enable variable length epochs.
Yields:
(epoch: int, epoch id, epoch_steps: int, number of steps in this epoch)
"""
try:
iter(epoch_steps)
except TypeError:
epoch_steps = itertools.repeat(epoch_steps)
step = 0
for epoch, epoch_steps in enumerate(epoch_steps):
epoch_steps = min(epoch_steps, steps - step)
yield (epoch + 1, epoch_steps)
step += epoch_steps
if steps and step >= steps:
break
|
python
|
def epochs(steps=None, epoch_steps=1):
"""Iterator over epochs until steps is reached. 1-indexed.
Args:
steps: int, total number of steps. Infinite if None.
epoch_steps: int, number of steps per epoch. Can also be an iterable<int> to
enable variable length epochs.
Yields:
(epoch: int, epoch id, epoch_steps: int, number of steps in this epoch)
"""
try:
iter(epoch_steps)
except TypeError:
epoch_steps = itertools.repeat(epoch_steps)
step = 0
for epoch, epoch_steps in enumerate(epoch_steps):
epoch_steps = min(epoch_steps, steps - step)
yield (epoch + 1, epoch_steps)
step += epoch_steps
if steps and step >= steps:
break
|
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",",
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")",
"step",
"+=",
"epoch_steps",
"if",
"steps",
"and",
"step",
">=",
"steps",
":",
"break"
] |
Iterator over epochs until steps is reached. 1-indexed.
Args:
steps: int, total number of steps. Infinite if None.
epoch_steps: int, number of steps per epoch. Can also be an iterable<int> to
enable variable length epochs.
Yields:
(epoch: int, epoch id, epoch_steps: int, number of steps in this epoch)
|
[
"Iterator",
"over",
"epochs",
"until",
"steps",
"is",
"reached",
".",
"1",
"-",
"indexed",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L255-L277
|
train
|
Iterator over epochs. 1 - indexed.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110000 + 0o1) + '\x33' + chr(283 - 231), 30785 - 30777), ehT0Px3KOsy9(chr(591 - 543) + '\157' + chr(0b11111 + 0o24) + chr(53) + chr(0b110111 + 0o0), 0b1000), ehT0Px3KOsy9(chr(139 - 91) + '\157' + chr(0b101001 + 0o11) + chr(1330 - 1276) + chr(0b11011 + 0o27), 51355 - 51347), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1739 - 1688) + '\061' + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\061' + '\066' + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(3200 - 3089) + chr(0b110 + 0o60), 0o10), ehT0Px3KOsy9('\x30' + chr(0b110000 + 0o77) + chr(1854 - 1805) + chr(432 - 377) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(4038 - 3927) + chr(50) + '\062' + chr(0b110000), 0o10), ehT0Px3KOsy9('\060' + chr(0b11110 + 0o121) + '\064' + '\x36', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b10010 + 0o41), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + '\x31' + '\x32', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + '\060' + chr(1321 - 1269), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(546 - 497) + chr(0b101010 + 0o7) + chr(316 - 267), ord("\x08")), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\157' + chr(0b110010) + chr(531 - 483) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(9889 - 9778) + chr(0b110010) + '\067' + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b11111 + 0o30) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b111 + 0o54) + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101011 + 0o7) + '\x36' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061' + '\061' + chr(54), 0o10), ehT0Px3KOsy9(chr(62 - 14) + '\x6f' + '\062' + chr(0b110010) + chr(54), 27508 - 27500), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b1101111) + '\061' + chr(609 - 558), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + '\063', 58622 - 58614), ehT0Px3KOsy9('\060' + '\157' + chr(664 - 613) + '\060' + '\x36', 14256 - 14248), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1100 + 0o51) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(111) + chr(0b11110 + 0o25) + '\x32' + chr(1140 - 1085), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + '\x33' + '\x30', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b11010 + 0o125) + chr(1168 - 1119) + '\x37' + chr(2544 - 2489), 8), ehT0Px3KOsy9(chr(1054 - 1006) + chr(2035 - 1924) + chr(51) + '\x36', 59324 - 59316), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + '\x37' + '\061', 8), ehT0Px3KOsy9(chr(369 - 321) + chr(0b1101111) + chr(0b11010 + 0o30) + chr(1655 - 1600) + '\x32', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100010 + 0o17) + chr(54) + chr(51), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000100 + 0o53) + chr(0b110101) + chr(505 - 451), 0b1000), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(11660 - 11549) + chr(216 - 165) + '\063' + '\x31', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33', 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b101 + 0o56) + '\x36' + chr(0b110111), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110 + 0o53) + '\064' + '\x37', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + chr(0b110000) + chr(0b111 + 0o52), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x31', 47232 - 47224), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(764 - 653) + '\x33' + chr(0b110001) + chr(1344 - 1293), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\x6f' + chr(0b11101 + 0o30) + '\x30', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'r'), chr(9352 - 9252) + chr(0b1100101) + chr(99) + '\x6f' + '\144' + chr(6295 - 6194))(chr(0b1110101) + '\x74' + chr(0b1000110 + 0o40) + chr(0b101101) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def xvDB7qObFSrr(v0VhEmlMsO_l=None, WakjLwSEDvih=ehT0Px3KOsy9('\060' + chr(0b1001010 + 0o45) + chr(0b110001), 8)):
try:
ZdP978XkGspL(WakjLwSEDvih)
except sznFqDbNBHlx:
WakjLwSEDvih = nLSuLqmR6kNP.repeat(WakjLwSEDvih)
kDuFsAhEatcU = ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(172 - 124), 0o10)
for (LWTVW06OsTjl, WakjLwSEDvih) in YlkZvXL8qwsX(WakjLwSEDvih):
WakjLwSEDvih = Dx22bkKPdt5d(WakjLwSEDvih, v0VhEmlMsO_l - kDuFsAhEatcU)
yield (LWTVW06OsTjl + ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061', 8), WakjLwSEDvih)
kDuFsAhEatcU += WakjLwSEDvih
if v0VhEmlMsO_l and kDuFsAhEatcU >= v0VhEmlMsO_l:
break
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
_jit_predict_fun
|
def _jit_predict_fun(model_predict, num_devices):
"""Use jit on model_predict if required."""
def predict(x, params=(), rng=None):
"""Predict function jited and parallelized as requested."""
# On one device, jit and run.
if num_devices == 1:
return backend.jit(model_predict)(x, params, rng=rng)
# Multi-devices, pmap and run.
@functools.partial(backend.pmap, axis_name="batch")
def mapped_predict(x, params, rng):
return model_predict(x, params, rng=rng)
pred = mapped_predict(
reshape_by_device(x, num_devices),
params,
jax_random.split(rng, num_devices))
# Need to reduce the [device, per-device-batch, ...] tensors back to
# a [batch, ...] tensor. The tensors may be nested.
if not isinstance(x, (list, tuple)): # Not nested.
batch_size = x.shape[0]
return np.reshape(pred, [batch_size] + list(pred.shape[2:]))
batch_size = x[0].shape[0]
return [np.reshape(p, [batch_size] + list(p.shape[2:])) for p in pred]
return predict
|
python
|
def _jit_predict_fun(model_predict, num_devices):
"""Use jit on model_predict if required."""
def predict(x, params=(), rng=None):
"""Predict function jited and parallelized as requested."""
# On one device, jit and run.
if num_devices == 1:
return backend.jit(model_predict)(x, params, rng=rng)
# Multi-devices, pmap and run.
@functools.partial(backend.pmap, axis_name="batch")
def mapped_predict(x, params, rng):
return model_predict(x, params, rng=rng)
pred = mapped_predict(
reshape_by_device(x, num_devices),
params,
jax_random.split(rng, num_devices))
# Need to reduce the [device, per-device-batch, ...] tensors back to
# a [batch, ...] tensor. The tensors may be nested.
if not isinstance(x, (list, tuple)): # Not nested.
batch_size = x.shape[0]
return np.reshape(pred, [batch_size] + list(pred.shape[2:]))
batch_size = x[0].shape[0]
return [np.reshape(p, [batch_size] + list(p.shape[2:])) for p in pred]
return predict
|
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] |
Use jit on model_predict if required.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L280-L304
|
train
|
Use jit on model_predict if required.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(0b111000 + 0o67) + '\x35', 55809 - 55801), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(514 - 403) + chr(253 - 202) + chr(52) + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b10000 + 0o41) + '\x31' + chr(0b110001), 0b1000), ehT0Px3KOsy9('\060' + chr(2660 - 2549) + '\x30', 11705 - 11697), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101110 + 0o5) + chr(0b101010 + 0o10) + '\x37', 37804 - 37796), ehT0Px3KOsy9(chr(48) + chr(11401 - 11290) + chr(0b1111 + 0o44) + chr(0b1000 + 0o50) + chr(788 - 734), 0o10), ehT0Px3KOsy9(chr(2262 - 2214) + chr(111) + chr(0b110010) + chr(0b100100 + 0o15) + chr(827 - 779), 25184 - 25176), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(111) + '\x31' + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(111) + '\062' + chr(948 - 897) + '\x35', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + chr(0b110110) + chr(49), 7746 - 7738), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(111) + chr(0b110010) + '\x32' + '\060', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(0b101011 + 0o12) + chr(0b10010 + 0o43), 0o10), ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\157' + chr(472 - 423) + chr(0b10101 + 0o35) + '\x36', 94 - 86), ehT0Px3KOsy9('\060' + chr(0b111100 + 0o63) + chr(0b100 + 0o55) + chr(48) + chr(50), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1493 - 1444) + '\063' + chr(51), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b110110 + 0o71) + '\x31' + chr(867 - 815) + '\x34', 19863 - 19855), ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\x6f' + chr(0b10000 + 0o43) + chr(0b100001 + 0o24) + chr(110 - 62), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(79 - 30) + '\x31' + chr(1112 - 1058), 40290 - 40282), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(53) + chr(1432 - 1377), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101100 + 0o3) + chr(0b101000 + 0o13) + chr(53) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001) + chr(0b100100 + 0o20) + chr(2365 - 2311), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + chr(930 - 881) + '\x30', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\062' + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001000 + 0o47) + chr(51) + '\x32' + '\x37', 8), ehT0Px3KOsy9('\060' + '\157' + '\062' + chr(0b11010 + 0o35), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + chr(1807 - 1752) + chr(694 - 646), 0b1000), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(111) + chr(0b110010) + chr(0b110000) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(0b1101111) + chr(0b100101 + 0o22) + chr(393 - 339), 27346 - 27338), ehT0Px3KOsy9(chr(48) + chr(3712 - 3601) + '\061' + '\067' + chr(0b10100 + 0o34), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(49) + chr(53) + chr(0b10011 + 0o41), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + '\065' + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + chr(1473 - 1422) + chr(0b110100 + 0o2), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(2154 - 2104) + chr(54) + chr(0b110001), 17804 - 17796), ehT0Px3KOsy9('\060' + '\x6f' + chr(2281 - 2229) + chr(0b1 + 0o57), 55796 - 55788), ehT0Px3KOsy9(chr(754 - 706) + chr(0b1101111) + chr(0b110010) + chr(0b10001 + 0o45) + chr(0b1100 + 0o45), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b11001 + 0o32) + '\x35' + chr(361 - 313), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + '\x31' + chr(0b110110), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100111 + 0o12) + '\x35' + chr(104 - 56), ord("\x08")), ehT0Px3KOsy9(chr(1132 - 1084) + '\x6f' + chr(2124 - 2072) + chr(49), 22154 - 22146), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10011 + 0o41) + chr(49), 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b101001 + 0o14) + chr(0b110000), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'+'), chr(0b1100000 + 0o4) + chr(3516 - 3415) + chr(5598 - 5499) + chr(0b1101111) + chr(0b1100100) + chr(0b110011 + 0o62))(chr(117) + chr(5992 - 5876) + chr(0b1100000 + 0o6) + chr(0b101101) + chr(0b10001 + 0o47)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def iBX1pOFbVq00(KRRucTXFamOQ, eK0vLxsq0cly):
def POyImYQwg5VB(OeWW0F1dBPRQ, nEbJZ4wfte2w=(), OKPXzuZwN61O=None):
if eK0vLxsq0cly == ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49), ord("\x08")):
return xafqLlk3kkUe(bwojgsUvRJpy, xafqLlk3kkUe(SXOLrMavuUCe(b'o\x8a='), chr(100) + chr(8900 - 8799) + '\x63' + chr(0b1101111) + '\144' + '\145')('\x75' + '\x74' + chr(0b1000101 + 0o41) + chr(0b101101) + chr(1409 - 1353)))(KRRucTXFamOQ)(OeWW0F1dBPRQ, nEbJZ4wfte2w, rng=OKPXzuZwN61O)
@xafqLlk3kkUe(E6ula8_Zv1yl, xafqLlk3kkUe(SXOLrMavuUCe(b'u\x82;t\xbe\xa7\xe4'), chr(0b1100100) + chr(101) + chr(0b10111 + 0o114) + chr(12139 - 12028) + chr(1833 - 1733) + chr(8241 - 8140))(chr(10088 - 9971) + '\x74' + chr(4038 - 3936) + chr(45) + chr(2772 - 2716)))(xafqLlk3kkUe(bwojgsUvRJpy, xafqLlk3kkUe(SXOLrMavuUCe(b'u\x8e(p'), chr(3237 - 3137) + chr(2605 - 2504) + '\143' + chr(0b1101111) + '\144' + '\x65')(chr(0b100010 + 0o123) + '\x74' + '\x66' + chr(0b11 + 0o52) + chr(56))), axis_name=xafqLlk3kkUe(SXOLrMavuUCe(b'g\x82=c\xbf'), chr(0b1001100 + 0o30) + '\145' + chr(0b1100011) + chr(111) + chr(6872 - 6772) + '\145')('\165' + chr(0b1110100) + '\x66' + '\x2d' + '\x38'))
def zPVHRNX_SiBG(OeWW0F1dBPRQ, nEbJZ4wfte2w, OKPXzuZwN61O):
return KRRucTXFamOQ(OeWW0F1dBPRQ, nEbJZ4wfte2w, rng=OKPXzuZwN61O)
eyamnrN0elUS = zPVHRNX_SiBG(MFX3ZhZMpjjC(OeWW0F1dBPRQ, eK0vLxsq0cly), nEbJZ4wfte2w, Fei3U0xopite.split(OKPXzuZwN61O, eK0vLxsq0cly))
if not PlSM16l2KDPD(OeWW0F1dBPRQ, (YyaZ4tpXu4lf, KNyTy8rYcwji)):
ix9dZyeAmUxY = OeWW0F1dBPRQ.nauYfLglTpcb[ehT0Px3KOsy9('\x30' + '\157' + chr(0b10010 + 0o36), 8)]
return xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'w\x86:h\xb6\xb6\xed'), chr(7321 - 7221) + chr(0b100011 + 0o102) + chr(0b1100011) + '\x6f' + '\x64' + chr(101))('\165' + chr(0b111 + 0o155) + chr(10257 - 10155) + '\055' + chr(0b111000)))(eyamnrN0elUS, [ix9dZyeAmUxY] + YyaZ4tpXu4lf(xafqLlk3kkUe(eyamnrN0elUS, xafqLlk3kkUe(SXOLrMavuUCe(b'k\x82<Y\xb1\x8a\xefe\xc9\x01\xf3\x8f'), chr(518 - 418) + chr(101) + chr(1012 - 913) + chr(0b11 + 0o154) + chr(0b100101 + 0o77) + '\145')(chr(0b1110101) + chr(116) + chr(0b1011110 + 0o10) + chr(0b11111 + 0o16) + chr(0b111000)))[ehT0Px3KOsy9('\x30' + chr(4980 - 4869) + chr(2230 - 2180), ord("\x08")):]))
ix9dZyeAmUxY = OeWW0F1dBPRQ[ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x30', 8)].nauYfLglTpcb[ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110000), 8)]
return [xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'w\x86:h\xb6\xb6\xed'), '\144' + '\145' + chr(0b101010 + 0o71) + '\157' + chr(100) + '\x65')(chr(0b11 + 0o162) + chr(0b1110100) + chr(0b101011 + 0o73) + '\x2d' + chr(56)))(UyakMW2IMFEj, [ix9dZyeAmUxY] + YyaZ4tpXu4lf(xafqLlk3kkUe(UyakMW2IMFEj, xafqLlk3kkUe(SXOLrMavuUCe(b'k\x82<Y\xb1\x8a\xefe\xc9\x01\xf3\x8f'), chr(0b110011 + 0o61) + chr(0b1000111 + 0o36) + '\x63' + '\x6f' + '\x64' + chr(101))(chr(117) + chr(0b1110100) + '\146' + chr(0b101101) + chr(1215 - 1159)))[ehT0Px3KOsy9(chr(48) + chr(4821 - 4710) + chr(50), 8):])) for UyakMW2IMFEj in eyamnrN0elUS]
return POyImYQwg5VB
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
_jit_update_fun
|
def _jit_update_fun(predict_fun, loss_fun, optimizer, lr_fun, num_devices):
"""Get jit-ed update function for loss, optimizer, learning rate function."""
if num_devices == 1: # TODO(lukaszkaiser): remove branch when not needed.
def single_update(i, opt_state, batch, rng):
rng, subrng = jax_random.split(rng[0])
_, opt_update = optimizer(lr_fun)
params = trax_opt.get_params(opt_state)
return opt_update(i, backend.grad(loss_fun)(
params, batch, predict_fun, rng), opt_state), [subrng]
return backend.jit(single_update)
@functools.partial(backend.pmap, axis_name="batch")
def mapped_update(i, opt_state, batch, rng):
"""This is a multi-device version of the update function above."""
# We assume all tensors have the first dimension = num_devices.
rng, subrng = jax_random.split(rng)
_, opt_update = optimizer(lr_fun)
params = trax_opt.get_params(opt_state)
grads = backend.grad(loss_fun)(params, batch, predict_fun, rng)
grads = jax.tree_util.tree_map(
lambda g: lax.psum(g, "batch"), grads)
return opt_update(i, grads, opt_state), subrng
def update(i, opt_state, batch, rng):
return mapped_update(jax.replicate(i), opt_state, batch, rng)
return update
|
python
|
def _jit_update_fun(predict_fun, loss_fun, optimizer, lr_fun, num_devices):
"""Get jit-ed update function for loss, optimizer, learning rate function."""
if num_devices == 1: # TODO(lukaszkaiser): remove branch when not needed.
def single_update(i, opt_state, batch, rng):
rng, subrng = jax_random.split(rng[0])
_, opt_update = optimizer(lr_fun)
params = trax_opt.get_params(opt_state)
return opt_update(i, backend.grad(loss_fun)(
params, batch, predict_fun, rng), opt_state), [subrng]
return backend.jit(single_update)
@functools.partial(backend.pmap, axis_name="batch")
def mapped_update(i, opt_state, batch, rng):
"""This is a multi-device version of the update function above."""
# We assume all tensors have the first dimension = num_devices.
rng, subrng = jax_random.split(rng)
_, opt_update = optimizer(lr_fun)
params = trax_opt.get_params(opt_state)
grads = backend.grad(loss_fun)(params, batch, predict_fun, rng)
grads = jax.tree_util.tree_map(
lambda g: lax.psum(g, "batch"), grads)
return opt_update(i, grads, opt_state), subrng
def update(i, opt_state, batch, rng):
return mapped_update(jax.replicate(i), opt_state, batch, rng)
return update
|
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"\"batch\"",
")",
",",
"grads",
")",
"return",
"opt_update",
"(",
"i",
",",
"grads",
",",
"opt_state",
")",
",",
"subrng",
"def",
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"(",
"i",
",",
"opt_state",
",",
"batch",
",",
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":",
"return",
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"(",
"jax",
".",
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"(",
"i",
")",
",",
"opt_state",
",",
"batch",
",",
"rng",
")",
"return",
"update"
] |
Get jit-ed update function for loss, optimizer, learning rate function.
|
[
"Get",
"jit",
"-",
"ed",
"update",
"function",
"for",
"loss",
"optimizer",
"learning",
"rate",
"function",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L307-L333
|
train
|
Get jit - ed update function for loss optimizer learning rate function.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1074 - 1023) + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001100 + 0o43) + chr(51) + '\x32' + chr(0b110100), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1011111 + 0o20) + chr(1221 - 1167) + chr(0b10111 + 0o31), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b10101 + 0o132) + chr(55), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(3105 - 2994) + '\063' + chr(0b0 + 0o63), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(689 - 640) + chr(54) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(111) + chr(250 - 199) + chr(0b101111 + 0o7) + '\061', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b11011 + 0o124) + chr(0b110010) + '\065' + chr(0b10010 + 0o40), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110101) + chr(0b100000 + 0o23), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110100) + chr(0b100110 + 0o15), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100111 + 0o10) + chr(0b100010 + 0o17) + '\060' + '\x31', 0b1000), ehT0Px3KOsy9(chr(107 - 59) + '\x6f' + chr(54) + '\x31', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1000011 + 0o54) + '\x34' + chr(0b110110), 55827 - 55819), ehT0Px3KOsy9(chr(0b110000) + chr(11307 - 11196) + '\064', 0b1000), ehT0Px3KOsy9(chr(316 - 268) + '\157' + chr(0b11000 + 0o33) + chr(55) + '\064', 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\x32' + '\x35' + chr(155 - 101), 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\062' + chr(972 - 923), 0b1000), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b110100 + 0o73) + chr(0b0 + 0o62) + chr(2884 - 2829) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(241 - 193) + chr(11530 - 11419) + chr(2516 - 2462) + chr(179 - 125), 45391 - 45383), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + chr(0b110101) + chr(0b110110), 45897 - 45889), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110101) + '\066', 64353 - 64345), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(482 - 427) + '\x31', 0b1000), ehT0Px3KOsy9(chr(902 - 854) + chr(11145 - 11034) + '\x31' + chr(2069 - 2020) + chr(0b110 + 0o53), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10010 + 0o37) + chr(1177 - 1129) + '\061', 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(2243 - 2193) + chr(0b10011 + 0o40) + '\064', 0o10), ehT0Px3KOsy9(chr(834 - 786) + chr(0b1101111) + chr(0b110010) + chr(0b101111 + 0o3) + chr(54), 53239 - 53231), ehT0Px3KOsy9('\060' + '\157' + chr(50) + '\x33', 17900 - 17892), ehT0Px3KOsy9('\060' + '\157' + chr(0b10010 + 0o41) + chr(0b100101 + 0o15) + chr(124 - 69), 18812 - 18804), ehT0Px3KOsy9(chr(48) + chr(0b1010100 + 0o33) + '\063' + chr(0b110 + 0o52), ord("\x08")), ehT0Px3KOsy9(chr(78 - 30) + chr(9351 - 9240) + chr(0b10011 + 0o40) + '\063' + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + chr(5460 - 5349) + chr(0b11 + 0o56) + chr(50) + '\x33', 0o10), ehT0Px3KOsy9(chr(2301 - 2253) + chr(0b1100100 + 0o13) + chr(0b101011 + 0o10) + '\x31' + chr(0b110000), 12576 - 12568), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1473 - 1424) + chr(0b110000 + 0o1) + chr(0b11011 + 0o32), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\063' + chr(0b110100) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50) + chr(1571 - 1522) + chr(0b110001), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + chr(48) + '\063', 0o10), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(111) + '\063' + '\x32', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + chr(0b10010 + 0o42) + chr(2843 - 2789), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(51) + chr(51) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\061' + '\067', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(1319 - 1208) + chr(53) + chr(0b110 + 0o52), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'3'), chr(9480 - 9380) + chr(0b1111 + 0o126) + '\143' + '\157' + '\x64' + '\x65')('\165' + chr(0b1110100) + chr(4119 - 4017) + '\055' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Rsps_2pKZrvf(Zkpe_s4zIdFG, VAWar4BWp9av, XdKNcYRObPK3, DcZqjor1_WnP, eK0vLxsq0cly):
if eK0vLxsq0cly == ehT0Px3KOsy9('\x30' + '\157' + chr(247 - 198), 0b1000):
def yBp3QIoMRtMh(WVxHKyX45z_L, DGBgOB4VcQ8Z, dNwAahu8tvoY, OKPXzuZwN61O):
(OKPXzuZwN61O, iq95UtudmcSD) = Fei3U0xopite.split(OKPXzuZwN61O[ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b111101 + 0o62) + chr(0b1000 + 0o50), ord("\x08"))])
(VNGQdHSFPrso, wyK1v8LaMctd) = XdKNcYRObPK3(DcZqjor1_WnP)
nEbJZ4wfte2w = Hppoazc6lhXg.get_params(DGBgOB4VcQ8Z)
return (wyK1v8LaMctd(WVxHKyX45z_L, xafqLlk3kkUe(bwojgsUvRJpy, xafqLlk3kkUe(SXOLrMavuUCe(b'O\x92o5U\x05\x92\xe0Bzv^'), chr(1566 - 1466) + '\145' + '\143' + '\157' + chr(100) + '\x65')('\165' + chr(0b1001110 + 0o46) + chr(0b1100110) + '\x2d' + '\070'))(VAWar4BWp9av)(nEbJZ4wfte2w, dNwAahu8tvoY, Zkpe_s4zIdFG, OKPXzuZwN61O), DGBgOB4VcQ8Z), [iq95UtudmcSD])
return xafqLlk3kkUe(bwojgsUvRJpy, xafqLlk3kkUe(SXOLrMavuUCe(b'w\xbdD'), chr(100) + '\x65' + chr(0b1100011) + chr(111) + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + '\x74' + chr(0b110110 + 0o60) + chr(0b101101) + chr(0b10001 + 0o47)))(yBp3QIoMRtMh)
@xafqLlk3kkUe(E6ula8_Zv1yl, xafqLlk3kkUe(SXOLrMavuUCe(b'm\xb5Bsr\x11\x9d'), chr(0b1100100) + '\x65' + chr(9058 - 8959) + chr(0b1101111) + chr(0b11110 + 0o106) + chr(0b11110 + 0o107))(chr(3694 - 3577) + chr(4248 - 4132) + chr(102) + chr(0b101101) + '\x38'))(xafqLlk3kkUe(bwojgsUvRJpy, xafqLlk3kkUe(SXOLrMavuUCe(b'm\xb9Qw'), '\144' + chr(0b111000 + 0o55) + '\x63' + chr(111) + '\x64' + '\145')(chr(117) + chr(0b1110100) + chr(9103 - 9001) + '\x2d' + '\070')), axis_name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x7f\xb5Dds'), chr(0b110011 + 0o61) + chr(0b1011000 + 0o15) + chr(2811 - 2712) + '\x6f' + chr(3946 - 3846) + chr(0b1000010 + 0o43))('\165' + chr(3915 - 3799) + chr(0b1100110) + chr(1055 - 1010) + chr(56)))
def SypiS06bfcki(WVxHKyX45z_L, DGBgOB4VcQ8Z, dNwAahu8tvoY, OKPXzuZwN61O):
(OKPXzuZwN61O, iq95UtudmcSD) = Fei3U0xopite.split(OKPXzuZwN61O)
(VNGQdHSFPrso, wyK1v8LaMctd) = XdKNcYRObPK3(DcZqjor1_WnP)
nEbJZ4wfte2w = Hppoazc6lhXg.get_params(DGBgOB4VcQ8Z)
W1s0NiRRDIwA = bwojgsUvRJpy.RF_2NucJiY7o(VAWar4BWp9av)(nEbJZ4wfte2w, dNwAahu8tvoY, Zkpe_s4zIdFG, OKPXzuZwN61O)
W1s0NiRRDIwA = zQs_qWEPq6AC.tree_util.tree_map(lambda RWHpzFEeviFP: j2vHIidTbj13.psum(RWHpzFEeviFP, xafqLlk3kkUe(SXOLrMavuUCe(b'\x7f\xb5Dds'), chr(0b1100011 + 0o1) + chr(101) + chr(0b1100011) + chr(111) + chr(0b1100100) + chr(0b1 + 0o144))(chr(0b110101 + 0o100) + chr(116) + '\146' + chr(45) + chr(56))), W1s0NiRRDIwA)
return (wyK1v8LaMctd(WVxHKyX45z_L, W1s0NiRRDIwA, DGBgOB4VcQ8Z), iq95UtudmcSD)
def ZtAEiNJny4e0(WVxHKyX45z_L, DGBgOB4VcQ8Z, dNwAahu8tvoY, OKPXzuZwN61O):
return SypiS06bfcki(xafqLlk3kkUe(zQs_qWEPq6AC, xafqLlk3kkUe(SXOLrMavuUCe(b'o\xb1@kr\x13\x90\xdeN'), chr(0b111100 + 0o50) + chr(101) + chr(8335 - 8236) + '\157' + chr(0b1100100) + chr(0b10100 + 0o121))('\165' + chr(0b1001100 + 0o50) + '\146' + chr(247 - 202) + chr(0b11110 + 0o32)))(WVxHKyX45z_L), DGBgOB4VcQ8Z, dNwAahu8tvoY, OKPXzuZwN61O)
return ZtAEiNJny4e0
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
_reshape_by_device_single
|
def _reshape_by_device_single(x, num_devices):
"""Reshape x into a shape [num_devices, ...]."""
x_shape = list(x.shape)
batch_size = x_shape[0]
batch_size_per_device = batch_size // num_devices
# We require that num_devices divides batch_size evenly.
if batch_size_per_device * num_devices != batch_size:
logging.fatal(
"We require that num_devices[%d] divides batch_size[%d] evenly.",
num_devices, batch_size)
# New shape.
new_shape_prefix = [num_devices, batch_size_per_device]
return np.reshape(x, new_shape_prefix + x_shape[1:])
|
python
|
def _reshape_by_device_single(x, num_devices):
"""Reshape x into a shape [num_devices, ...]."""
x_shape = list(x.shape)
batch_size = x_shape[0]
batch_size_per_device = batch_size // num_devices
# We require that num_devices divides batch_size evenly.
if batch_size_per_device * num_devices != batch_size:
logging.fatal(
"We require that num_devices[%d] divides batch_size[%d] evenly.",
num_devices, batch_size)
# New shape.
new_shape_prefix = [num_devices, batch_size_per_device]
return np.reshape(x, new_shape_prefix + x_shape[1:])
|
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Reshape x into a shape [num_devices, ...].
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L336-L348
|
train
|
Reshape x into a shape [ num_devices... ].
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + chr(0b100101 + 0o16) + chr(49), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\062' + chr(51) + chr(787 - 739), 0b1000), ehT0Px3KOsy9(chr(2140 - 2092) + '\157' + '\x31' + '\060' + '\x32', 2425 - 2417), ehT0Px3KOsy9(chr(61 - 13) + chr(5865 - 5754) + '\x33' + chr(54) + '\063', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b1000 + 0o52) + chr(0b110101) + chr(1687 - 1637), 0b1000), ehT0Px3KOsy9(chr(662 - 614) + chr(0b1101111) + '\062' + '\066' + '\x35', 24118 - 24110), ehT0Px3KOsy9(chr(643 - 595) + chr(0b11 + 0o154) + chr(0b110010) + '\x37' + chr(0b100011 + 0o16), 0o10), ehT0Px3KOsy9('\060' + chr(5749 - 5638) + chr(50) + chr(0b110001) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(0b10011 + 0o35) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\x6f' + '\x33' + chr(48) + '\061', 0o10), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(139 - 28) + chr(51) + chr(0b11000 + 0o33) + chr(2138 - 2085), ord("\x08")), ehT0Px3KOsy9(chr(85 - 37) + '\x6f' + chr(50) + chr(49) + '\063', 0o10), ehT0Px3KOsy9(chr(337 - 289) + chr(0b1101111) + chr(50) + chr(0b110111) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(0b1110 + 0o141) + chr(51) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(1785 - 1737) + chr(0b1000100 + 0o53) + chr(607 - 557) + chr(0b110001) + '\x35', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1859 - 1810) + chr(0b100 + 0o63) + chr(0b100001 + 0o20), 42201 - 42193), ehT0Px3KOsy9(chr(0b110000) + chr(0b11110 + 0o121) + chr(0b111 + 0o52) + chr(48) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110111) + chr(1721 - 1673), 0o10), ehT0Px3KOsy9(chr(48) + chr(11571 - 11460) + chr(50) + chr(0b110101), 982 - 974), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1011100 + 0o23) + chr(2766 - 2713) + chr(0b1000 + 0o54), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + chr(0b110110 + 0o0) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110101) + chr(0b110001), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b100101 + 0o14), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061' + '\067' + chr(49), 8), ehT0Px3KOsy9(chr(2213 - 2165) + chr(2620 - 2509) + chr(0b110010 + 0o0) + '\065' + chr(0b10100 + 0o43), 42668 - 42660), ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\x6f' + chr(0b110100) + '\063', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b1110 + 0o43) + chr(0b110110) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100010 + 0o25) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(2228 - 2177) + chr(1743 - 1691) + chr(621 - 568), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(53) + '\066', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(239 - 189) + chr(1941 - 1890) + '\x35', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(3140 - 3029) + chr(51) + chr(0b110001) + chr(0b110110), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(2489 - 2439) + chr(0b110101 + 0o1) + '\064', 14494 - 14486), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + chr(0b110101) + chr(894 - 842), 0b1000), ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\x6f' + chr(949 - 900) + chr(0b11001 + 0o30) + '\x30', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(119 - 69) + chr(1330 - 1277) + chr(55), 8), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(0b1011101 + 0o22) + '\x36' + chr(1768 - 1717), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1340 - 1285) + chr(499 - 448), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(0b100000 + 0o22) + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + chr(1435 - 1380) + chr(50), 59581 - 59573)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(825 - 772) + '\x30', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf7'), '\144' + '\x65' + chr(2101 - 2002) + chr(0b1100 + 0o143) + chr(2834 - 2734) + chr(8984 - 8883))('\x75' + chr(116) + chr(0b1100110) + '\055' + chr(0b11110 + 0o32)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def YyGGbu05Y83i(OeWW0F1dBPRQ, eK0vLxsq0cly):
QQEXXbdZyz6m = YyaZ4tpXu4lf(OeWW0F1dBPRQ.nauYfLglTpcb)
ix9dZyeAmUxY = QQEXXbdZyz6m[ehT0Px3KOsy9('\060' + chr(5751 - 5640) + '\x30', 39370 - 39362)]
RWCpFJp5Mi5z = ix9dZyeAmUxY // eK0vLxsq0cly
if RWCpFJp5Mi5z * eK0vLxsq0cly != ix9dZyeAmUxY:
xafqLlk3kkUe(UeotCCWOPSQS, xafqLlk3kkUe(SXOLrMavuUCe(b'\xbf\xf96\x92\xc6'), '\x64' + chr(0b110011 + 0o62) + '\x63' + chr(1799 - 1688) + chr(0b11010 + 0o112) + chr(0b110101 + 0o60))('\x75' + '\x74' + chr(0b1100110) + '\055' + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e\xfdb\x81\xcf\xc4\xcc\xe6\xf5\xa4\xfd\xff\xd3~\xf9Y.Mxs\x15Lw\x10\xccF\x00a\xc0J\xc0\xee\xd0\xc5>\xc6W^\xe1\x9a\xbb\xf96\x90\xc2\xea\xca\xe6\xfd\xa4\x86\xae\xdfB\xad\x1c6]{@\x08\x07'), chr(0b110011 + 0o61) + chr(0b11 + 0o142) + chr(0b11111 + 0o104) + chr(0b1010110 + 0o31) + chr(0b1100100) + chr(0b10 + 0o143))(chr(0b1010111 + 0o36) + chr(0b1010111 + 0o35) + '\146' + chr(0b101101) + '\x38'), eK0vLxsq0cly, ix9dZyeAmUxY)
EfCTwvjDFQLQ = [eK0vLxsq0cly, RWCpFJp5Mi5z]
return xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xab\xfd1\x9b\xcb\xc5\xdc'), chr(0b1100100) + '\x65' + chr(2638 - 2539) + chr(9048 - 8937) + chr(0b1100100) + chr(101))(chr(117) + chr(116) + '\x66' + chr(45) + chr(0b111000)))(OeWW0F1dBPRQ, EfCTwvjDFQLQ + QQEXXbdZyz6m[ehT0Px3KOsy9(chr(48) + chr(111) + chr(910 - 861), 8):])
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
reshape_by_device
|
def reshape_by_device(x, num_devices):
"""Reshape possibly nested x into a shape [num_devices, ...]."""
return layers.nested_map(
x, lambda x: _reshape_by_device_single(x, num_devices))
|
python
|
def reshape_by_device(x, num_devices):
"""Reshape possibly nested x into a shape [num_devices, ...]."""
return layers.nested_map(
x, lambda x: _reshape_by_device_single(x, num_devices))
|
[
"def",
"reshape_by_device",
"(",
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":",
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"layers",
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"nested_map",
"(",
"x",
",",
"lambda",
"x",
":",
"_reshape_by_device_single",
"(",
"x",
",",
"num_devices",
")",
")"
] |
Reshape possibly nested x into a shape [num_devices, ...].
|
[
"Reshape",
"possibly",
"nested",
"x",
"into",
"a",
"shape",
"[",
"num_devices",
"...",
"]",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L351-L354
|
train
|
Reshape possibly nested x into a shape [ num_devices... ].
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + '\x32' + chr(492 - 438), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\065' + '\061', 0o10), ehT0Px3KOsy9(chr(0b110 + 0o52) + '\x6f' + chr(2106 - 2055) + '\061', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + '\x37' + '\x34', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + chr(0b0 + 0o66) + chr(1237 - 1184), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(49) + chr(0b110100) + chr(0b110010), 27917 - 27909), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(10183 - 10072) + chr(0b110001) + '\060' + chr(0b100011 + 0o16), 0o10), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(111) + chr(245 - 196) + '\x30' + chr(0b101111 + 0o1), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\062' + chr(50) + chr(1057 - 1008), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32' + chr(940 - 889) + '\x36', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + '\066' + '\x33', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b10010 + 0o37) + chr(52) + chr(0b0 + 0o64), 0b1000), ehT0Px3KOsy9(chr(48) + chr(12164 - 12053) + '\061' + chr(0b1011 + 0o52) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\x6f' + chr(1206 - 1152) + chr(0b101011 + 0o10), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(152 - 103) + chr(0b110011) + chr(917 - 865), 62707 - 62699), ehT0Px3KOsy9(chr(1664 - 1616) + chr(111) + chr(751 - 701) + '\x32' + chr(0b110011), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + chr(54) + chr(2244 - 2190), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + '\x33' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(111) + '\063' + '\064' + chr(0b100100 + 0o16), 0b1000), ehT0Px3KOsy9(chr(1247 - 1199) + chr(111) + '\062' + chr(48) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\x6f' + '\x31' + chr(52) + '\064', 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(52) + chr(51), 30622 - 30614), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b1000001 + 0o56) + chr(51) + chr(0b101001 + 0o11) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b110001 + 0o76) + chr(0b110010) + chr(50) + chr(51), 8), ehT0Px3KOsy9('\060' + '\157' + chr(1088 - 1038) + chr(0b10 + 0o64) + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(111) + chr(54) + chr(0b110000), 26203 - 26195), ehT0Px3KOsy9(chr(1814 - 1766) + '\157' + chr(0b11000 + 0o34) + '\066', 58062 - 58054), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(50) + chr(0b110100) + chr(934 - 882), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011101 + 0o22) + chr(0b10110 + 0o34) + '\x33' + '\064', 0b1000), ehT0Px3KOsy9('\060' + chr(1700 - 1589) + '\x31' + '\065' + '\066', 0b1000), ehT0Px3KOsy9(chr(748 - 700) + '\x6f' + chr(813 - 763) + chr(51) + chr(0b11 + 0o55), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(55) + chr(1077 - 1027), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(2258 - 2207) + '\063' + '\x30', 6919 - 6911), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + '\x34' + '\062', 8), ehT0Px3KOsy9('\x30' + '\x6f' + chr(2659 - 2604) + chr(0b10001 + 0o41), 6466 - 6458), ehT0Px3KOsy9(chr(968 - 920) + '\157' + chr(1334 - 1284) + chr(0b110111) + chr(2027 - 1976), ord("\x08")), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b1011000 + 0o27) + chr(0b110011) + chr(0b11 + 0o57) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100000 + 0o21) + chr(55) + '\x34', 0b1000), ehT0Px3KOsy9(chr(1390 - 1342) + chr(111) + chr(913 - 864) + chr(2228 - 2180) + '\063', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(2557 - 2506) + '\x34' + '\x35', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110101) + '\x30', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'x'), chr(6006 - 5906) + chr(0b1100101) + '\143' + chr(0b1101111) + chr(0b1100100) + chr(0b1010011 + 0o22))('\x75' + chr(7040 - 6924) + chr(0b1100110) + chr(0b1011 + 0o42) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def MFX3ZhZMpjjC(OeWW0F1dBPRQ, eK0vLxsq0cly):
return xafqLlk3kkUe(sGi5Aql23May, xafqLlk3kkUe(SXOLrMavuUCe(b'8Lj\x88\xd0\x06\x1e-\xf0\xee'), chr(0b110001 + 0o63) + chr(0b1100101) + chr(4629 - 4530) + '\x6f' + chr(0b1100100) + chr(0b101001 + 0o74))(chr(13491 - 13374) + chr(0b1100000 + 0o24) + chr(102) + chr(45) + chr(56)))(OeWW0F1dBPRQ, lambda OeWW0F1dBPRQ: YyGGbu05Y83i(OeWW0F1dBPRQ, eK0vLxsq0cly))
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/trax.py
|
train
|
def train(output_dir,
model=gin.REQUIRED,
loss_fun=loss,
inputs=trax_inputs.inputs,
optimizer=trax_opt.adam,
lr_schedule=lr.MultifactorSchedule,
train_steps=1000,
save_steps=None,
eval_steps=10,
eval_frequency=100,
num_devices=None,
random_seed=None,
run_debug_step=False,
save_forward_graph=False):
"""Train the model on the inputs.
Args:
output_dir: Directory where to put the logs and checkpoints.
model: The model to train as a callable returning 2 callables, an init_fun
and apply_fun.
loss_fun: callable with signature: params, trax.inputs.Inputs, model, rng
-> loss.
inputs: callable returning trax.inputs.Inputs.
optimizer: The optimizer as a callable taking a learning_rate callable and
returning 2 callables, opt_init and opt_update.
lr_schedule: A learning rate schedule as a function that takes history and
returns a function from step to learning rate (a float).
train_steps: int, total number of training steps.
save_steps: list of integers. Keep a model file at each of the supplied save
steps.
eval_steps: int, num of steps per evaluation. If None or 0, eval disabled.
eval_frequency: int, how often to run evaluation (every eval_frequency
steps). If None or 0, eval disabled.
num_devices: how many devices to use (if None, default, use all available)
random_seed: the random seed to use; time/os dependent if None (default).
run_debug_step: bool, if True, will run the model and loss without @jit for
one step.
save_forward_graph: bool, if True, save forward computation graph to file.
Returns:
trax.State
"""
if save_steps is None:
save_steps = []
num_devices = num_devices or jax.lib.xla_bridge.device_count()
rng = get_random_number_generator_and_set_seed(random_seed)
gfile.makedirs(output_dir)
# Create summary writers and history.
train_sw = jaxboard.SummaryWriter(os.path.join(output_dir, "train"))
eval_sw = jaxboard.SummaryWriter(os.path.join(output_dir, "eval"))
inputs = inputs(num_devices)
# Setup optimizer and model
state = restore_state(output_dir)
history = state.history
lr_fun = lr_schedule(history)
opt_init, _ = optimizer(lr_fun)
model_train = model(mode="train")
model_predict_eval = model(mode="eval")
# Setup state
step = state.step or 0
rng, init_rng = jax_random.split(rng)
rngs = jax_random.split(rng, num_devices)
first_shape = inputs.input_shape[0]
# If the inputs are a tuple/list, add [-1] (batch) to each element.
if isinstance(first_shape, (list, tuple)):
model_input_shape = tuple(
[tuple([-1] + list(shape)) for shape in inputs.input_shape])
else: # Otherwise just add [-1] to the input shape.
model_input_shape = tuple([-1] + list(inputs.input_shape))
params = state.params or model_train.initialize(model_input_shape, init_rng)
opt_state = opt_init(params)
if num_devices > 1: # TODO(lukaszkaiser): use everywhere when pmap is stable.
opt_state = jax.replicate(opt_state)
# jit model_predict and update so they're fast
jit_model_predict_eval = _jit_predict_fun(model_predict_eval, num_devices)
jit_update_fun = _jit_update_fun(
model_train, loss_fun, optimizer, lr_fun, num_devices)
train_stream = inputs.train_stream()
epoch_steps = [train_steps] # Only training if eval_frequency is 0 or None.
if eval_frequency and eval_steps > 0:
epoch_steps = itertools.chain([1, # first epoch only 1 step
eval_frequency - 1],
itertools.repeat(eval_frequency))
step_log(step, "Starting training using %d devices" % num_devices)
# Non-compiled debug step helps find problems in models easier.
if run_debug_step:
debug_loss = loss_fun(params, next(train_stream), model_train, rng)
step_log(step, "Debug step loss %.8f" % debug_loss)
for epoch, epoch_steps in epochs(train_steps, epoch_steps):
# Log separator
print()
# Timer
start_time = time.time()
for _ in range(epoch_steps):
# Train
next_train_batch = next(train_stream)
if num_devices > 1: # TODO(lukaszkaiser): use everywhere when possible.
next_train_batch = reshape_by_device(next_train_batch, num_devices)
opt_state, rngs = jit_update_fun(step, opt_state, next_train_batch, rngs)
step += 1
if step in save_steps:
save_state(State(params=params, step=step, history=history),
output_dir,
keep=True)
# LR log
if step == 1 or step % 10 == 0:
train_sw.scalar("training/learning rate",
lr_fun(step), step=step)
# Timer
epoch_time = time.time() - start_time
step_log(step, "Ran %d train steps in %0.2f secs" %
(epoch_steps, epoch_time))
if epoch_steps > 1:
train_sw.scalar("training/steps per second",
epoch_steps / epoch_time, step=step)
# Print number of parameters
params = trax_opt.get_params(opt_state)
if step == 1:
sizes = layers.sizes(params)
total_size = layers.nested_reduce(sizes, sum)
step_log(step, "Total trainable parameters size: %d" % total_size)
# Evaluate
evaluate_train_and_eval(
step=step,
inputs=inputs,
predict_fun=functools.partial(jit_model_predict_eval, params=params),
eval_steps=eval_steps,
rng=rng,
train_sw=train_sw,
eval_sw=eval_sw,
history=history)
# Save computation graph
if save_forward_graph and step == 1:
# Dump forward computation graph to file.
computation = jax.xla_computation(model_predict_eval)(
next_train_batch[0], params=params, rng=rng)
with gfile.GFile(os.path.join(output_dir, "forward_graph.dot"), "w") as f:
f.write(computation.GetHloDotGraph())
# Save state
save_state(State(params=params, step=step, history=history), output_dir)
# Save Gin config
# Gin only tracks the used parameters, so we save it after the first epoch.
if epoch == 1:
save_gin(output_dir, train_sw)
# Update learning rate with new history
old_lr_fun = lr_fun
lr_fun = lr_schedule(history)
if lr_fun != old_lr_fun: # For performance, only jit if there is a change.
jit_update_fun = _jit_update_fun(
model_train, loss_fun, optimizer, lr_fun, num_devices)
# Flush summary writers
train_sw.flush()
eval_sw.flush()
step_log(step, "Training done")
return State(params=params, step=step, history=history)
|
python
|
def train(output_dir,
model=gin.REQUIRED,
loss_fun=loss,
inputs=trax_inputs.inputs,
optimizer=trax_opt.adam,
lr_schedule=lr.MultifactorSchedule,
train_steps=1000,
save_steps=None,
eval_steps=10,
eval_frequency=100,
num_devices=None,
random_seed=None,
run_debug_step=False,
save_forward_graph=False):
"""Train the model on the inputs.
Args:
output_dir: Directory where to put the logs and checkpoints.
model: The model to train as a callable returning 2 callables, an init_fun
and apply_fun.
loss_fun: callable with signature: params, trax.inputs.Inputs, model, rng
-> loss.
inputs: callable returning trax.inputs.Inputs.
optimizer: The optimizer as a callable taking a learning_rate callable and
returning 2 callables, opt_init and opt_update.
lr_schedule: A learning rate schedule as a function that takes history and
returns a function from step to learning rate (a float).
train_steps: int, total number of training steps.
save_steps: list of integers. Keep a model file at each of the supplied save
steps.
eval_steps: int, num of steps per evaluation. If None or 0, eval disabled.
eval_frequency: int, how often to run evaluation (every eval_frequency
steps). If None or 0, eval disabled.
num_devices: how many devices to use (if None, default, use all available)
random_seed: the random seed to use; time/os dependent if None (default).
run_debug_step: bool, if True, will run the model and loss without @jit for
one step.
save_forward_graph: bool, if True, save forward computation graph to file.
Returns:
trax.State
"""
if save_steps is None:
save_steps = []
num_devices = num_devices or jax.lib.xla_bridge.device_count()
rng = get_random_number_generator_and_set_seed(random_seed)
gfile.makedirs(output_dir)
# Create summary writers and history.
train_sw = jaxboard.SummaryWriter(os.path.join(output_dir, "train"))
eval_sw = jaxboard.SummaryWriter(os.path.join(output_dir, "eval"))
inputs = inputs(num_devices)
# Setup optimizer and model
state = restore_state(output_dir)
history = state.history
lr_fun = lr_schedule(history)
opt_init, _ = optimizer(lr_fun)
model_train = model(mode="train")
model_predict_eval = model(mode="eval")
# Setup state
step = state.step or 0
rng, init_rng = jax_random.split(rng)
rngs = jax_random.split(rng, num_devices)
first_shape = inputs.input_shape[0]
# If the inputs are a tuple/list, add [-1] (batch) to each element.
if isinstance(first_shape, (list, tuple)):
model_input_shape = tuple(
[tuple([-1] + list(shape)) for shape in inputs.input_shape])
else: # Otherwise just add [-1] to the input shape.
model_input_shape = tuple([-1] + list(inputs.input_shape))
params = state.params or model_train.initialize(model_input_shape, init_rng)
opt_state = opt_init(params)
if num_devices > 1: # TODO(lukaszkaiser): use everywhere when pmap is stable.
opt_state = jax.replicate(opt_state)
# jit model_predict and update so they're fast
jit_model_predict_eval = _jit_predict_fun(model_predict_eval, num_devices)
jit_update_fun = _jit_update_fun(
model_train, loss_fun, optimizer, lr_fun, num_devices)
train_stream = inputs.train_stream()
epoch_steps = [train_steps] # Only training if eval_frequency is 0 or None.
if eval_frequency and eval_steps > 0:
epoch_steps = itertools.chain([1, # first epoch only 1 step
eval_frequency - 1],
itertools.repeat(eval_frequency))
step_log(step, "Starting training using %d devices" % num_devices)
# Non-compiled debug step helps find problems in models easier.
if run_debug_step:
debug_loss = loss_fun(params, next(train_stream), model_train, rng)
step_log(step, "Debug step loss %.8f" % debug_loss)
for epoch, epoch_steps in epochs(train_steps, epoch_steps):
# Log separator
print()
# Timer
start_time = time.time()
for _ in range(epoch_steps):
# Train
next_train_batch = next(train_stream)
if num_devices > 1: # TODO(lukaszkaiser): use everywhere when possible.
next_train_batch = reshape_by_device(next_train_batch, num_devices)
opt_state, rngs = jit_update_fun(step, opt_state, next_train_batch, rngs)
step += 1
if step in save_steps:
save_state(State(params=params, step=step, history=history),
output_dir,
keep=True)
# LR log
if step == 1 or step % 10 == 0:
train_sw.scalar("training/learning rate",
lr_fun(step), step=step)
# Timer
epoch_time = time.time() - start_time
step_log(step, "Ran %d train steps in %0.2f secs" %
(epoch_steps, epoch_time))
if epoch_steps > 1:
train_sw.scalar("training/steps per second",
epoch_steps / epoch_time, step=step)
# Print number of parameters
params = trax_opt.get_params(opt_state)
if step == 1:
sizes = layers.sizes(params)
total_size = layers.nested_reduce(sizes, sum)
step_log(step, "Total trainable parameters size: %d" % total_size)
# Evaluate
evaluate_train_and_eval(
step=step,
inputs=inputs,
predict_fun=functools.partial(jit_model_predict_eval, params=params),
eval_steps=eval_steps,
rng=rng,
train_sw=train_sw,
eval_sw=eval_sw,
history=history)
# Save computation graph
if save_forward_graph and step == 1:
# Dump forward computation graph to file.
computation = jax.xla_computation(model_predict_eval)(
next_train_batch[0], params=params, rng=rng)
with gfile.GFile(os.path.join(output_dir, "forward_graph.dot"), "w") as f:
f.write(computation.GetHloDotGraph())
# Save state
save_state(State(params=params, step=step, history=history), output_dir)
# Save Gin config
# Gin only tracks the used parameters, so we save it after the first epoch.
if epoch == 1:
save_gin(output_dir, train_sw)
# Update learning rate with new history
old_lr_fun = lr_fun
lr_fun = lr_schedule(history)
if lr_fun != old_lr_fun: # For performance, only jit if there is a change.
jit_update_fun = _jit_update_fun(
model_train, loss_fun, optimizer, lr_fun, num_devices)
# Flush summary writers
train_sw.flush()
eval_sw.flush()
step_log(step, "Training done")
return State(params=params, step=step, history=history)
|
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] |
Train the model on the inputs.
Args:
output_dir: Directory where to put the logs and checkpoints.
model: The model to train as a callable returning 2 callables, an init_fun
and apply_fun.
loss_fun: callable with signature: params, trax.inputs.Inputs, model, rng
-> loss.
inputs: callable returning trax.inputs.Inputs.
optimizer: The optimizer as a callable taking a learning_rate callable and
returning 2 callables, opt_init and opt_update.
lr_schedule: A learning rate schedule as a function that takes history and
returns a function from step to learning rate (a float).
train_steps: int, total number of training steps.
save_steps: list of integers. Keep a model file at each of the supplied save
steps.
eval_steps: int, num of steps per evaluation. If None or 0, eval disabled.
eval_frequency: int, how often to run evaluation (every eval_frequency
steps). If None or 0, eval disabled.
num_devices: how many devices to use (if None, default, use all available)
random_seed: the random seed to use; time/os dependent if None (default).
run_debug_step: bool, if True, will run the model and loss without @jit for
one step.
save_forward_graph: bool, if True, save forward computation graph to file.
Returns:
trax.State
|
[
"Train",
"the",
"model",
"on",
"the",
"inputs",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/trax.py#L358-L532
|
train
|
Train the model on the inputs.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(111) + chr(54) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(111) + '\065' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1350 - 1299) + chr(0b100011 + 0o21) + chr(0b110110), 6327 - 6319), ehT0Px3KOsy9('\x30' + chr(4426 - 4315) + chr(49) + chr(0b110001) + chr(55), 0o10), ehT0Px3KOsy9('\060' + chr(0b1010000 + 0o37) + '\061' + '\061' + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\157' + chr(0b110010) + '\x35' + '\063', 9678 - 9670), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + '\x34' + chr(0b100100 + 0o21), ord("\x08")), ehT0Px3KOsy9(chr(686 - 638) + chr(8425 - 8314) + chr(0b100011 + 0o17) + chr(0b110111) + chr(0b110011), 33482 - 33474), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + '\x30' + chr(55), 0o10), ehT0Px3KOsy9(chr(746 - 698) + chr(111) + chr(0b110001 + 0o2) + chr(2397 - 2345) + chr(2745 - 2690), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x32' + chr(0b10 + 0o64) + chr(52), 53013 - 53005), ehT0Px3KOsy9(chr(952 - 904) + '\x6f' + '\062' + chr(0b110101) + chr(699 - 646), 61196 - 61188), ehT0Px3KOsy9(chr(0b110000) + chr(5742 - 5631) + chr(50) + chr(0b110011 + 0o0) + chr(0b110 + 0o54), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110011) + '\x36' + chr(1604 - 1554), 0o10), ehT0Px3KOsy9('\x30' + chr(6488 - 6377) + chr(49) + chr(0b10110 + 0o40) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110011) + '\x32', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + '\x30' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + chr(136 - 87) + '\060', 8), ehT0Px3KOsy9(chr(909 - 861) + chr(111) + chr(0b110001) + chr(49), 0o10), ehT0Px3KOsy9('\060' + chr(0b1100100 + 0o13) + chr(49) + chr(0b100100 + 0o23), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1011101 + 0o22) + chr(50) + chr(2455 - 2405) + chr(0b11111 + 0o25), 39713 - 39705), ehT0Px3KOsy9(chr(0b110000) + chr(8598 - 8487) + chr(0b110010) + chr(0b11001 + 0o34) + '\x37', 44890 - 44882), ehT0Px3KOsy9('\060' + chr(8319 - 8208) + chr(0b110111) + chr(53), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(2345 - 2296) + '\x37' + '\067', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1088 - 1037) + chr(0b110101) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000010 + 0o55) + chr(0b110010) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(5760 - 5649) + chr(1203 - 1153) + chr(0b110111), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100000 + 0o23) + chr(0b100110 + 0o21) + chr(0b101 + 0o53), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(49) + chr(52) + chr(1359 - 1307), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110111) + chr(0b101001 + 0o12), 36024 - 36016), ehT0Px3KOsy9(chr(212 - 164) + '\x6f' + chr(51) + chr(0b110110) + '\062', 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110111) + '\063', 8), ehT0Px3KOsy9(chr(48) + '\157' + '\x33' + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(564 - 515) + chr(52) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b100010 + 0o22) + chr(0b101 + 0o54), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + chr(52) + chr(0b11100 + 0o30), 8), ehT0Px3KOsy9(chr(429 - 381) + chr(0b10111 + 0o130) + chr(51) + chr(0b110000) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(1723 - 1675) + chr(111) + chr(0b10111 + 0o32) + chr(50) + '\x37', 57369 - 57361), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(0b110000) + chr(0b110110), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110101) + '\x30', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x19'), '\x64' + '\145' + '\143' + chr(6346 - 6235) + chr(100) + chr(1585 - 1484))(chr(0b1110010 + 0o3) + chr(116) + '\x66' + chr(268 - 223) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def e80gRioCjdat(nd0OX_BS6_o4, FK0vqzZ5gPN6=xafqLlk3kkUe(WpThBfI19lUe, xafqLlk3kkUe(SXOLrMavuUCe(b'ej\xb7\x1a\x01\xf9\xe0\xff'), chr(0b1100100) + chr(101) + '\x63' + '\157' + chr(100) + chr(2113 - 2012))(chr(4390 - 4273) + chr(116) + '\x66' + chr(0b101101) + '\x38')), VAWar4BWp9av=YpO0BcZ6fMsf, vXoupepMtCXU=xafqLlk3kkUe(RkPCSLi6gx3s, xafqLlk3kkUe(SXOLrMavuUCe(b'Aw\x89:8\xce\xd5\xf6\xb3\xa4\xec\xf8'), chr(0b1000010 + 0o42) + chr(0b0 + 0o145) + chr(0b110010 + 0o61) + chr(0b1101111) + chr(4686 - 4586) + '\145')(chr(0b1110101) + chr(12701 - 12585) + chr(0b100000 + 0o106) + chr(0b101101) + chr(881 - 825))), XdKNcYRObPK3=xafqLlk3kkUe(Hppoazc6lhXg, xafqLlk3kkUe(SXOLrMavuUCe(b'VK\x87"'), '\144' + chr(0b110010 + 0o63) + chr(99) + chr(8641 - 8530) + chr(9584 - 9484) + chr(10093 - 9992))('\x75' + chr(2301 - 2185) + chr(0b111100 + 0o52) + chr(45) + chr(1108 - 1052))), cwY_BOTK0U5_=xafqLlk3kkUe(Zzs55KO_HKfp, xafqLlk3kkUe(SXOLrMavuUCe(b'zZ\x8a;!\xcd\xc4\xd8\xb3\x88\xc6\xfe\xf9\x9a\x10~\xf7$l'), chr(0b1100100) + '\x65' + chr(99) + '\x6f' + chr(0b1100100) + chr(0b1000111 + 0o36))(chr(0b1110101) + chr(0b1010011 + 0o41) + '\x66' + chr(605 - 560) + chr(2529 - 2473))), daYMko0joBwR=ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + chr(55) + '\x35' + chr(48), 0b1000), x6RXNQXXI_lj=None, K3bHLghgmarn=ehT0Px3KOsy9('\060' + chr(111) + '\x31' + chr(0b110010), ord("\x08")), KIkXX2X7ASLN=ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10110 + 0o33) + chr(52) + chr(52), 8), eK0vLxsq0cly=None, JrhY2RFJObts=None, cu7lKN60d1ys=ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\x6f' + chr(0b1000 + 0o50), ord("\x08")), FnUQpxEddPqg=ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110000), 8)):
if x6RXNQXXI_lj is None:
x6RXNQXXI_lj = []
eK0vLxsq0cly = eK0vLxsq0cly or zQs_qWEPq6AC.lib.xla_bridge.device_count()
OKPXzuZwN61O = KAhsRxZxzwv1(JrhY2RFJObts)
xafqLlk3kkUe(YwCPldGHQanD, xafqLlk3kkUe(SXOLrMavuUCe(b'ZN\x8d*,\xc2\xd7\xc8'), '\144' + '\145' + chr(0b1010100 + 0o17) + chr(10124 - 10013) + chr(100) + '\145')('\165' + chr(0b1110100) + '\x66' + chr(45) + chr(0b111000)))(nd0OX_BS6_o4)
ctt4rWba3c7D = DpbwgUcSjVRE.SummaryWriter(oqhJDdMJfuwx.path.join(nd0OX_BS6_o4, xafqLlk3kkUe(SXOLrMavuUCe(b'C]\x87&&'), '\144' + '\145' + chr(5025 - 4926) + chr(111) + chr(100) + '\145')(chr(0b1110101) + chr(7953 - 7837) + chr(3010 - 2908) + chr(0b111 + 0o46) + chr(0b111000))))
PnA6lwGM1GND = DpbwgUcSjVRE.SummaryWriter(oqhJDdMJfuwx.path.join(nd0OX_BS6_o4, xafqLlk3kkUe(SXOLrMavuUCe(b'RY\x87#'), chr(0b1100100) + '\145' + chr(0b11101 + 0o106) + '\x6f' + chr(100) + '\145')('\x75' + chr(0b1010010 + 0o42) + chr(102) + chr(0b1100 + 0o41) + '\070')))
vXoupepMtCXU = vXoupepMtCXU(eK0vLxsq0cly)
KKFQISrGeiAm = nlUwZia7nbz5(nd0OX_BS6_o4)
sD1K7SLfPnDB = KKFQISrGeiAm.history
DcZqjor1_WnP = cwY_BOTK0U5_(sD1K7SLfPnDB)
(v2mzWK3Zu6rN, VNGQdHSFPrso) = XdKNcYRObPK3(DcZqjor1_WnP)
hLfDxCjU8PS1 = FK0vqzZ5gPN6(mode=xafqLlk3kkUe(SXOLrMavuUCe(b'C]\x87&&'), '\144' + chr(4426 - 4325) + chr(0b1100011) + '\x6f' + chr(100) + chr(101))(chr(0b1110101) + '\x74' + chr(102) + chr(45) + chr(0b111000)))
SQzcBhkb3WgC = FK0vqzZ5gPN6(mode=xafqLlk3kkUe(SXOLrMavuUCe(b'RY\x87#'), chr(0b1100100) + chr(0b1001 + 0o134) + chr(0b1100011) + chr(111) + chr(0b0 + 0o144) + chr(101))('\x75' + chr(116) + chr(0b11101 + 0o111) + chr(45) + '\x38'))
kDuFsAhEatcU = KKFQISrGeiAm.kDuFsAhEatcU or ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(3651 - 3540) + '\x30', 8)
(OKPXzuZwN61O, q902U3C_EwAr) = Fei3U0xopite.split(OKPXzuZwN61O)
kbFqskrg4ru6 = Fei3U0xopite.split(OKPXzuZwN61O, eK0vLxsq0cly)
gqJ8mXykYDBn = vXoupepMtCXU.input_shape[ehT0Px3KOsy9(chr(0b110000) + chr(5039 - 4928) + chr(2050 - 2002), 8)]
if PlSM16l2KDPD(gqJ8mXykYDBn, (YyaZ4tpXu4lf, KNyTy8rYcwji)):
vPZVhVxb45Vm = KNyTy8rYcwji([KNyTy8rYcwji([-ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1154 - 1105), 8)] + YyaZ4tpXu4lf(nauYfLglTpcb)) for nauYfLglTpcb in vXoupepMtCXU.input_shape])
else:
vPZVhVxb45Vm = KNyTy8rYcwji([-ehT0Px3KOsy9('\x30' + chr(0b111111 + 0o60) + chr(2363 - 2314), 8)] + YyaZ4tpXu4lf(vXoupepMtCXU.input_shape))
nEbJZ4wfte2w = KKFQISrGeiAm.nEbJZ4wfte2w or hLfDxCjU8PS1.initialize(vPZVhVxb45Vm, q902U3C_EwAr)
DGBgOB4VcQ8Z = v2mzWK3Zu6rN(nEbJZ4wfte2w)
if eK0vLxsq0cly > ehT0Px3KOsy9('\060' + '\157' + chr(0b1 + 0o60), 8):
DGBgOB4VcQ8Z = zQs_qWEPq6AC.replicate(DGBgOB4VcQ8Z)
_XcNZtUPapkp = iBX1pOFbVq00(SQzcBhkb3WgC, eK0vLxsq0cly)
ymBrNrXVIWIo = Rsps_2pKZrvf(hLfDxCjU8PS1, VAWar4BWp9av, XdKNcYRObPK3, DcZqjor1_WnP, eK0vLxsq0cly)
DewFj9qP3sYO = vXoupepMtCXU.train_stream()
WakjLwSEDvih = [daYMko0joBwR]
if KIkXX2X7ASLN and K3bHLghgmarn > ehT0Px3KOsy9(chr(48) + chr(111) + chr(48), 8):
WakjLwSEDvih = nLSuLqmR6kNP.chain([ehT0Px3KOsy9(chr(57 - 9) + chr(0b11110 + 0o121) + chr(2296 - 2247), 8), KIkXX2X7ASLN - ehT0Px3KOsy9('\060' + chr(0b111000 + 0o67) + '\061', 8)], nLSuLqmR6kNP.repeat(KIkXX2X7ASLN))
COZYwvUvwkQz(kDuFsAhEatcU, xafqLlk3kkUe(SXOLrMavuUCe(b'd[\x87=<\xc2\xcb\xdc\xe7\x93\xc6\xcc\xf3\x9c\x1ct\xe5h||\xfd\xc1Z_\xcce1s\x9d\x12R\x91^k'), chr(0b11001 + 0o113) + '\x65' + chr(0b1100011) + chr(10590 - 10479) + chr(0b1100100) + chr(101))('\165' + chr(1575 - 1459) + '\x66' + '\x2d' + chr(2947 - 2891)) % eK0vLxsq0cly)
if cu7lKN60d1ys:
vn8e7DPOOOS2 = VAWar4BWp9av(nEbJZ4wfte2w, nSwwHEeM4cxI(DewFj9qP3sYO), hLfDxCjU8PS1, OKPXzuZwN61O)
COZYwvUvwkQz(kDuFsAhEatcU, xafqLlk3kkUe(SXOLrMavuUCe(b'sJ\x84:/\x8b\xd6\xcf\xa2\x97\x94\xc1\xf5\x81\x06:\xa7f1i'), chr(0b1100100) + chr(1386 - 1285) + chr(0b100000 + 0o103) + chr(0b111110 + 0o61) + chr(100) + chr(0b101 + 0o140))(chr(12891 - 12774) + chr(0b1100000 + 0o24) + chr(0b1001111 + 0o27) + chr(45) + '\070') % vn8e7DPOOOS2)
for (LWTVW06OsTjl, WakjLwSEDvih) in xvDB7qObFSrr(daYMko0joBwR, WakjLwSEDvih):
zLUzGokYBM2Z()
tSzPDN5a8DrS = ltvhPP4VhXre.time()
for VNGQdHSFPrso in vQr8gNKaIaWE(WakjLwSEDvih):
lGax9BUDwvPg = nSwwHEeM4cxI(DewFj9qP3sYO)
if eK0vLxsq0cly > ehT0Px3KOsy9('\x30' + '\x6f' + '\x31', 8):
lGax9BUDwvPg = MFX3ZhZMpjjC(lGax9BUDwvPg, eK0vLxsq0cly)
(DGBgOB4VcQ8Z, kbFqskrg4ru6) = ymBrNrXVIWIo(kDuFsAhEatcU, DGBgOB4VcQ8Z, lGax9BUDwvPg, kbFqskrg4ru6)
kDuFsAhEatcU += ehT0Px3KOsy9('\060' + '\x6f' + '\061', 8)
if kDuFsAhEatcU in x6RXNQXXI_lj:
KKcceDaTyz__(uWBOm14kSj2p(params=nEbJZ4wfte2w, step=kDuFsAhEatcU, history=sD1K7SLfPnDB), nd0OX_BS6_o4, keep=ehT0Px3KOsy9('\060' + '\x6f' + '\061', 8))
if kDuFsAhEatcU == ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001), 8) or kDuFsAhEatcU % ehT0Px3KOsy9('\060' + chr(0b11111 + 0o120) + chr(0b110001) + chr(2316 - 2266), 8) == ehT0Px3KOsy9('\060' + chr(0b1101111) + '\060', 8):
xafqLlk3kkUe(ctt4rWba3c7D, xafqLlk3kkUe(SXOLrMavuUCe(b'DL\x87#)\xd9'), chr(6368 - 6268) + chr(0b10111 + 0o116) + '\143' + '\157' + chr(100) + '\x65')(chr(1431 - 1314) + chr(9584 - 9468) + '\146' + '\x2d' + chr(0b100011 + 0o25)))(xafqLlk3kkUe(SXOLrMavuUCe(b'C]\x87&&\xc2\xcb\xdc\xe8\x8b\xd1\xcc\xe8\x9c\x1ct\xe5h{n\xe0\xca'), chr(6093 - 5993) + chr(0b1100101) + chr(99) + chr(111) + chr(2608 - 2508) + chr(7259 - 7158))('\165' + chr(116) + chr(0b1100 + 0o132) + '\055' + '\070'), DcZqjor1_WnP(kDuFsAhEatcU), step=kDuFsAhEatcU)
gw1Z2HL5TmRa = ltvhPP4VhXre.time() - tSzPDN5a8DrS
COZYwvUvwkQz(kDuFsAhEatcU, xafqLlk3kkUe(SXOLrMavuUCe(b'eN\x88om\xcf\x85\xcf\xb5\x86\xdd\xc3\xba\x81\x01\x7f\xf2;)f\xfa\x8f\x18O\xc73w7\x8b\x01X\x81'), chr(100) + chr(4581 - 4480) + chr(99) + '\x6f' + chr(0b110 + 0o136) + chr(8343 - 8242))('\x75' + chr(0b1101 + 0o147) + '\x66' + '\x2d' + '\070') % (WakjLwSEDvih, gw1Z2HL5TmRa))
if WakjLwSEDvih > ehT0Px3KOsy9('\x30' + chr(0b1001100 + 0o43) + '\x31', 8):
xafqLlk3kkUe(ctt4rWba3c7D, xafqLlk3kkUe(SXOLrMavuUCe(b'DL\x87#)\xd9'), '\x64' + chr(0b1100101) + chr(0b101011 + 0o70) + '\x6f' + chr(2537 - 2437) + chr(0b101001 + 0o74))('\x75' + chr(0b11101 + 0o127) + chr(720 - 618) + chr(45) + chr(2796 - 2740)))(xafqLlk3kkUe(SXOLrMavuUCe(b'C]\x87&&\xc2\xcb\xdc\xe8\x94\xc0\xc8\xea\x81Uj\xe7:)|\xf1\xccR\x11\x8d'), '\144' + chr(101) + '\143' + '\x6f' + chr(0b101010 + 0o72) + chr(8912 - 8811))('\165' + chr(12220 - 12104) + '\146' + '\055' + chr(768 - 712)), WakjLwSEDvih / gw1Z2HL5TmRa, step=kDuFsAhEatcU)
nEbJZ4wfte2w = Hppoazc6lhXg.get_params(DGBgOB4VcQ8Z)
if kDuFsAhEatcU == ehT0Px3KOsy9(chr(1724 - 1676) + chr(0b1010100 + 0o33) + chr(1487 - 1438), 8):
Q55tUpoH0W5L = sGi5Aql23May.sizes(nEbJZ4wfte2w)
aRDYUgtuFxYy = sGi5Aql23May.nested_reduce(Q55tUpoH0W5L, xkxBmo49x2An)
COZYwvUvwkQz(kDuFsAhEatcU, xafqLlk3kkUe(SXOLrMavuUCe(b'c@\x92.$\x8b\xd1\xc9\xa6\x8e\xda\xcc\xf8\x9e\x10:\xf2){n\xf9\xcaI\x1a\x9br1d\x91\x1e^\xc8\x1b=\x01'), '\x64' + chr(0b101010 + 0o73) + chr(99) + '\157' + chr(0b1000110 + 0o36) + '\145')(chr(0b1110101) + chr(9232 - 9116) + chr(0b101110 + 0o70) + '\055' + '\070') % aRDYUgtuFxYy)
vUII_0MJ6hhJ(step=kDuFsAhEatcU, inputs=vXoupepMtCXU, predict_fun=xafqLlk3kkUe(E6ula8_Zv1yl, xafqLlk3kkUe(SXOLrMavuUCe(b'GN\x94;!\xca\xc9'), chr(0b1100100) + chr(1373 - 1272) + '\143' + chr(0b1000110 + 0o51) + '\144' + chr(3791 - 3690))('\165' + chr(0b1110100) + chr(102) + chr(572 - 527) + '\x38'))(_XcNZtUPapkp, params=nEbJZ4wfte2w), eval_steps=K3bHLghgmarn, rng=OKPXzuZwN61O, train_sw=ctt4rWba3c7D, eval_sw=PnA6lwGM1GND, history=sD1K7SLfPnDB)
if FnUQpxEddPqg and kDuFsAhEatcU == ehT0Px3KOsy9(chr(48) + chr(0b101101 + 0o102) + chr(2397 - 2348), 8):
ODH6TmP_wQrs = zQs_qWEPq6AC.xla_computation(SQzcBhkb3WgC)(lGax9BUDwvPg[ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\x6f' + chr(48), 8)], params=nEbJZ4wfte2w, rng=OKPXzuZwN61O)
with xafqLlk3kkUe(YwCPldGHQanD, xafqLlk3kkUe(SXOLrMavuUCe(b'pi\x8f#-'), '\144' + chr(0b1100101) + chr(479 - 380) + chr(111) + '\x64' + '\x65')(chr(0b1011 + 0o152) + '\164' + '\x66' + chr(0b101101) + chr(0b111000)))(xafqLlk3kkUe(oqhJDdMJfuwx.path, xafqLlk3kkUe(SXOLrMavuUCe(b']@\x8f!'), chr(100) + chr(101) + chr(5477 - 5378) + '\x6f' + '\144' + '\x65')(chr(3738 - 3621) + chr(0b1101011 + 0o11) + '\x66' + '\x2d' + '\x38'))(nd0OX_BS6_o4, xafqLlk3kkUe(SXOLrMavuUCe(b'Q@\x948)\xd9\xc1\xe4\xa0\x95\xd5\xdd\xf2\xdc\x11u\xf6'), chr(0b1100100) + chr(0b111000 + 0o55) + chr(0b1100011) + chr(6671 - 6560) + chr(100) + '\145')('\165' + '\x74' + chr(0b1100110) + '\x2d' + '\x38')), xafqLlk3kkUe(SXOLrMavuUCe(b'@'), chr(100) + chr(101) + '\143' + '\x6f' + chr(0b100010 + 0o102) + chr(101))(chr(3248 - 3131) + chr(0b1110100) + chr(102) + chr(1209 - 1164) + '\x38')) as EGyt1xfPT1P6:
xafqLlk3kkUe(EGyt1xfPT1P6, xafqLlk3kkUe(SXOLrMavuUCe(b'@]\x8f;-'), chr(100) + '\145' + chr(0b1100011) + chr(0b1010001 + 0o36) + chr(3383 - 3283) + chr(4446 - 4345))('\x75' + chr(2899 - 2783) + chr(102) + '\x2d' + chr(2705 - 2649)))(xafqLlk3kkUe(ODH6TmP_wQrs, xafqLlk3kkUe(SXOLrMavuUCe(b'pJ\x92\x07$\xc4\xe1\xd4\xb3\xa0\xc6\xcc\xea\x9a'), '\144' + '\145' + chr(99) + chr(111) + '\x64' + '\145')('\x75' + chr(4877 - 4761) + chr(0b1100110) + chr(0b100111 + 0o6) + chr(56)))())
KKcceDaTyz__(uWBOm14kSj2p(params=nEbJZ4wfte2w, step=kDuFsAhEatcU, history=sD1K7SLfPnDB), nd0OX_BS6_o4)
if LWTVW06OsTjl == ehT0Px3KOsy9('\060' + '\x6f' + chr(505 - 456), 8):
H37IyhSTwHro(nd0OX_BS6_o4, ctt4rWba3c7D)
xcm1n04loTSy = DcZqjor1_WnP
DcZqjor1_WnP = cwY_BOTK0U5_(sD1K7SLfPnDB)
if DcZqjor1_WnP != xcm1n04loTSy:
ymBrNrXVIWIo = Rsps_2pKZrvf(hLfDxCjU8PS1, VAWar4BWp9av, XdKNcYRObPK3, DcZqjor1_WnP, eK0vLxsq0cly)
xafqLlk3kkUe(ctt4rWba3c7D, xafqLlk3kkUe(SXOLrMavuUCe(b'QC\x93< '), chr(8115 - 8015) + chr(101) + chr(2430 - 2331) + chr(0b100110 + 0o111) + chr(9879 - 9779) + chr(1770 - 1669))(chr(117) + chr(6843 - 6727) + '\x66' + chr(103 - 58) + chr(0b111000)))()
xafqLlk3kkUe(PnA6lwGM1GND, xafqLlk3kkUe(SXOLrMavuUCe(b'QC\x93< '), chr(100) + chr(101) + chr(0b101110 + 0o65) + chr(111) + chr(0b1100100) + '\x65')(chr(4507 - 4390) + chr(116) + chr(0b1011011 + 0o13) + chr(357 - 312) + chr(0b1000 + 0o60)))()
COZYwvUvwkQz(kDuFsAhEatcU, xafqLlk3kkUe(SXOLrMavuUCe(b'c]\x87&&\xc2\xcb\xdc\xe7\x83\xdb\xc3\xff'), '\144' + '\x65' + chr(2393 - 2294) + '\x6f' + '\144' + chr(0b10001 + 0o124))('\x75' + chr(0b1010 + 0o152) + '\146' + chr(1209 - 1164) + '\x38'))
return uWBOm14kSj2p(params=nEbJZ4wfte2w, step=kDuFsAhEatcU, history=sD1K7SLfPnDB)
|
tensorflow/tensor2tensor
|
tensor2tensor/keras/initializers.py
|
_compute_fans
|
def _compute_fans(shape):
"""Computes the number of input and output units for a weight shape.
Args:
shape: Integer shape tuple or TF tensor shape.
Returns:
A tuple of scalars (fan_in, fan_out).
"""
if len(shape) < 1: # Just to avoid errors for constants.
fan_in = fan_out = 1
elif len(shape) == 1:
fan_in = fan_out = shape[0]
elif len(shape) == 2:
fan_in = shape[0]
fan_out = shape[1]
else:
# Assuming convolution kernels (2D, 3D, or more).
# kernel shape: (..., input_depth, depth)
receptive_field_size = 1.
for dim in shape[:-2]:
receptive_field_size *= dim
fan_in = shape[-2] * receptive_field_size
fan_out = shape[-1] * receptive_field_size
if isinstance(fan_in, tf.Dimension):
fan_in = fan_in.value
if isinstance(fan_out, tf.Dimension):
fan_out = fan_out.value
return fan_in, fan_out
|
python
|
def _compute_fans(shape):
"""Computes the number of input and output units for a weight shape.
Args:
shape: Integer shape tuple or TF tensor shape.
Returns:
A tuple of scalars (fan_in, fan_out).
"""
if len(shape) < 1: # Just to avoid errors for constants.
fan_in = fan_out = 1
elif len(shape) == 1:
fan_in = fan_out = shape[0]
elif len(shape) == 2:
fan_in = shape[0]
fan_out = shape[1]
else:
# Assuming convolution kernels (2D, 3D, or more).
# kernel shape: (..., input_depth, depth)
receptive_field_size = 1.
for dim in shape[:-2]:
receptive_field_size *= dim
fan_in = shape[-2] * receptive_field_size
fan_out = shape[-1] * receptive_field_size
if isinstance(fan_in, tf.Dimension):
fan_in = fan_in.value
if isinstance(fan_out, tf.Dimension):
fan_out = fan_out.value
return fan_in, fan_out
|
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] |
Computes the number of input and output units for a weight shape.
Args:
shape: Integer shape tuple or TF tensor shape.
Returns:
A tuple of scalars (fan_in, fan_out).
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/keras/initializers.py#L32-L60
|
train
|
Computes the number of input and output units for a weight shape.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(0b101110 + 0o101) + chr(87 - 35) + chr(1648 - 1593), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x33' + chr(0b100010 + 0o23) + chr(1230 - 1175), 39409 - 39401), ehT0Px3KOsy9('\060' + '\157' + chr(2407 - 2353) + chr(128 - 75), ord("\x08")), ehT0Px3KOsy9(chr(779 - 731) + chr(111) + chr(1316 - 1262) + '\x37', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011) + chr(0b110010 + 0o0), 41169 - 41161), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(0b1101111) + '\x32' + chr(0b110000) + chr(0b110000), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b101100 + 0o6) + chr(0b110111) + chr(0b110111 + 0o0), 3330 - 3322), ehT0Px3KOsy9('\060' + chr(0b1010101 + 0o32) + chr(2350 - 2300) + chr(0b11111 + 0o27) + '\067', 0b1000), ehT0Px3KOsy9(chr(1664 - 1616) + chr(0b10 + 0o155) + '\067' + '\063', 0o10), ehT0Px3KOsy9(chr(142 - 94) + '\157' + chr(49) + '\067' + '\066', 0b1000), ehT0Px3KOsy9(chr(48) + chr(5379 - 5268) + chr(92 - 42) + '\x35' + '\064', 0o10), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(0b10 + 0o155) + '\x31' + chr(0b11 + 0o55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010111 + 0o30) + '\062' + chr(0b110011) + chr(2626 - 2573), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(50) + '\x33' + '\x36', 39866 - 39858), ehT0Px3KOsy9(chr(48) + chr(9037 - 8926) + '\066' + '\x30', 1658 - 1650), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(51) + chr(0b110011) + chr(54), 41119 - 41111), ehT0Px3KOsy9(chr(1608 - 1560) + chr(0b1101111) + chr(495 - 444) + chr(0b100000 + 0o26) + '\x30', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b101001 + 0o10) + '\x36' + chr(0b10101 + 0o36), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + '\x34' + chr(52), 0o10), ehT0Px3KOsy9(chr(48) + chr(9874 - 9763) + chr(51) + chr(53) + chr(934 - 886), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + chr(0b1110 + 0o51) + '\064', 0b1000), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(9941 - 9830) + '\x31' + '\067' + chr(0b1001 + 0o54), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(0b11000 + 0o30) + '\060', 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + '\065' + '\x34', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1325 - 1275) + chr(330 - 279) + chr(0b11 + 0o64), 48030 - 48022), ehT0Px3KOsy9('\060' + chr(0b1100110 + 0o11) + '\061' + chr(956 - 907) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(48) + chr(1718 - 1607) + '\x37' + chr(0b11100 + 0o33), 17789 - 17781), ehT0Px3KOsy9(chr(1771 - 1723) + chr(0b1101111) + '\x33' + chr(0b0 + 0o63) + chr(2286 - 2236), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + chr(0b110110), 58356 - 58348), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(111) + chr(0b110001) + '\x32' + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b10111 + 0o130) + '\061' + '\065' + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(6278 - 6167) + '\061' + chr(2212 - 2161) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(6772 - 6661) + chr(0b110011 + 0o0) + chr(53) + chr(0b1111 + 0o50), 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(0b110010) + chr(2394 - 2342), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b11111 + 0o120) + chr(50) + chr(52) + chr(2155 - 2101), 57539 - 57531), ehT0Px3KOsy9(chr(1708 - 1660) + chr(111) + chr(50) + '\061', 0o10), ehT0Px3KOsy9(chr(1236 - 1188) + chr(0b1101111) + chr(50), 0o10), ehT0Px3KOsy9(chr(1565 - 1517) + chr(5306 - 5195) + '\x32' + '\x33' + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110 + 0o53) + chr(0b110001) + '\060', 24194 - 24186), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1010 + 0o50) + '\065' + chr(52), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110101) + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\t'), '\x64' + '\145' + '\x63' + chr(0b101011 + 0o104) + '\x64' + chr(101))('\165' + '\164' + chr(102) + chr(0b10010 + 0o33) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Xhbl0eXiDOdW(nauYfLglTpcb):
if c2A0yzQpDQB3(nauYfLglTpcb) < ehT0Px3KOsy9('\x30' + '\157' + '\x31', 0b1000):
kYjP5QHf1hbW = U9oyJbhKVteb = ehT0Px3KOsy9(chr(0b110000) + chr(3310 - 3199) + chr(1548 - 1499), 8)
elif c2A0yzQpDQB3(nauYfLglTpcb) == ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b10010 + 0o37), 8):
kYjP5QHf1hbW = U9oyJbhKVteb = nauYfLglTpcb[ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\060', 0b1000)]
elif c2A0yzQpDQB3(nauYfLglTpcb) == ehT0Px3KOsy9('\x30' + chr(111) + '\x32', 8):
kYjP5QHf1hbW = nauYfLglTpcb[ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(111) + chr(0b110000), 8)]
U9oyJbhKVteb = nauYfLglTpcb[ehT0Px3KOsy9('\060' + '\157' + chr(1407 - 1358), 8)]
else:
SQ018rCfcHEM = 1.0
for Nl_JhL3qUwSN in nauYfLglTpcb[:-ehT0Px3KOsy9(chr(0b110000) + chr(0b1001010 + 0o45) + chr(0b100011 + 0o17), 8)]:
SQ018rCfcHEM *= Nl_JhL3qUwSN
kYjP5QHf1hbW = nauYfLglTpcb[-ehT0Px3KOsy9(chr(0b110000) + chr(11377 - 11266) + chr(0b110001 + 0o1), 8)] * SQ018rCfcHEM
U9oyJbhKVteb = nauYfLglTpcb[-ehT0Px3KOsy9(chr(48) + chr(0b100011 + 0o114) + chr(0b100110 + 0o13), 8)] * SQ018rCfcHEM
if PlSM16l2KDPD(kYjP5QHf1hbW, xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'c\x86XRt\xf3\xd6\xd8U'), '\144' + '\145' + chr(5308 - 5209) + chr(0b1001000 + 0o47) + chr(0b1000 + 0o134) + chr(0b1100101))(chr(0b1110101 + 0o0) + '\164' + chr(102) + chr(1489 - 1444) + chr(0b101 + 0o63)))):
kYjP5QHf1hbW = kYjP5QHf1hbW.QmmgWUB13VCJ
if PlSM16l2KDPD(U9oyJbhKVteb, xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'c\x86XRt\xf3\xd6\xd8U'), chr(100) + chr(0b1111 + 0o126) + chr(99) + chr(0b1101111) + '\x64' + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + chr(0b10100 + 0o122) + chr(45) + chr(0b111000)))):
U9oyJbhKVteb = U9oyJbhKVteb.QmmgWUB13VCJ
return (kYjP5QHf1hbW, U9oyJbhKVteb)
|
tensorflow/tensor2tensor
|
tensor2tensor/keras/initializers.py
|
get
|
def get(identifier, value=None):
"""Getter for loading from strings; returns value if can't load."""
if value is None:
value = identifier
if identifier is None:
return None
elif isinstance(identifier, dict):
try:
return deserialize(identifier)
except ValueError:
return value
elif isinstance(identifier, six.string_types):
config = {'class_name': str(identifier), 'config': {}}
try:
return deserialize(config)
except ValueError:
return value
elif callable(identifier):
return identifier
return value
|
python
|
def get(identifier, value=None):
"""Getter for loading from strings; returns value if can't load."""
if value is None:
value = identifier
if identifier is None:
return None
elif isinstance(identifier, dict):
try:
return deserialize(identifier)
except ValueError:
return value
elif isinstance(identifier, six.string_types):
config = {'class_name': str(identifier), 'config': {}}
try:
return deserialize(config)
except ValueError:
return value
elif callable(identifier):
return identifier
return value
|
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] |
Getter for loading from strings; returns value if can't load.
|
[
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";",
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/keras/initializers.py#L279-L298
|
train
|
Getter for loading from strings ; returns value if can t load.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(0b110011 + 0o74) + chr(0b110010) + '\066' + chr(1676 - 1623), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + chr(0b110110) + chr(0b110111), 18300 - 18292), ehT0Px3KOsy9('\x30' + chr(12257 - 12146) + '\067' + chr(0b1110 + 0o47), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(880 - 769) + chr(0b11011 + 0o27) + '\x37' + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(236 - 188) + '\157' + chr(313 - 262) + chr(48) + '\x30', 0o10), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(1359 - 1248) + chr(2294 - 2242) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(111) + chr(0b11 + 0o60) + chr(0b110011) + chr(51), 0o10), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(0b1101111) + chr(0b110011) + chr(0b110011) + chr(55), 0o10), ehT0Px3KOsy9('\060' + chr(2147 - 2036) + chr(0b110001) + chr(51) + '\x36', 25466 - 25458), ehT0Px3KOsy9(chr(48) + chr(6706 - 6595) + '\x33' + chr(48) + '\x30', 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(1824 - 1774) + '\065' + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(2593 - 2482) + chr(0b11 + 0o60) + chr(49) + '\x36', 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\x32' + '\x32' + '\x35', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110001) + chr(0b110001 + 0o5), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b10000 + 0o41) + chr(0b110011) + chr(0b11 + 0o55), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(2137 - 2026) + '\062' + chr(0b1100 + 0o53) + chr(48), 59799 - 59791), ehT0Px3KOsy9(chr(0b110000) + chr(11562 - 11451) + '\x32' + '\x32' + chr(50), 35858 - 35850), ehT0Px3KOsy9('\060' + '\157' + chr(49) + '\064' + '\060', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b111111 + 0o60) + chr(1735 - 1684) + chr(1534 - 1482) + chr(0b10100 + 0o43), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\063' + chr(0b110000) + chr(0b11101 + 0o23), 8), ehT0Px3KOsy9(chr(48) + chr(0b1010101 + 0o32) + '\064' + '\x32', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(0b110100 + 0o2) + chr(0b1110 + 0o44), 0b1000), ehT0Px3KOsy9(chr(1455 - 1407) + chr(0b101 + 0o152) + chr(49) + chr(0b1101 + 0o51) + chr(0b110000), 15066 - 15058), ehT0Px3KOsy9(chr(1557 - 1509) + '\157' + '\062' + chr(0b101011 + 0o14) + chr(53), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x32' + chr(50) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(101 - 53) + '\157' + chr(51) + chr(0b100110 + 0o13) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + '\x32' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1803 - 1754) + '\062' + '\x36', 48353 - 48345), ehT0Px3KOsy9(chr(48) + chr(3158 - 3047) + chr(50) + chr(0b110010) + chr(0b101100 + 0o4), 13173 - 13165), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + '\x32' + '\x34', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(51) + '\x37', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + '\x35' + chr(1839 - 1784), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x32' + '\x36' + chr(633 - 585), 20604 - 20596), ehT0Px3KOsy9('\x30' + chr(9295 - 9184) + '\061' + '\067' + chr(0b101000 + 0o12), 27289 - 27281), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x32' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(1328 - 1280) + '\157' + chr(1837 - 1786) + '\063', 61844 - 61836), ehT0Px3KOsy9(chr(1375 - 1327) + '\157' + '\x32' + '\x34' + '\063', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(50) + chr(53) + '\x31', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(1932 - 1882) + '\061' + '\x33', 21865 - 21857), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + '\061' + chr(0b110010), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(0b1000100 + 0o53) + '\x35' + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x9b'), '\x64' + chr(101) + '\x63' + '\157' + '\x64' + '\145')(chr(0b1011101 + 0o30) + '\x74' + chr(0b1100110) + '\055' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Q8b5UytA0vqH(IndhTE9HSpWS, QmmgWUB13VCJ=None):
if QmmgWUB13VCJ is None:
QmmgWUB13VCJ = IndhTE9HSpWS
if IndhTE9HSpWS is None:
return None
elif PlSM16l2KDPD(IndhTE9HSpWS, wLqBDw8l0eIm):
try:
return DNu32EriaOEo(IndhTE9HSpWS)
except q1QCh3W88sgk:
return QmmgWUB13VCJ
elif PlSM16l2KDPD(IndhTE9HSpWS, xafqLlk3kkUe(sYby0kpfssd4, xafqLlk3kkUe(SXOLrMavuUCe(b"\xc6\x03O\xd4\xaeG\x84\xab'\xb0\xcb\xbd"), '\x64' + chr(0b1100101) + '\x63' + '\x6f' + '\144' + '\x65')('\165' + chr(602 - 486) + '\x66' + chr(0b101101) + chr(56)))):
jAj7S20Ct06o = {xafqLlk3kkUe(SXOLrMavuUCe(b'\xd6\x1b\\\xce\xb3\x7f\xb5\xbe3\xa5'), chr(4503 - 4403) + chr(101) + '\x63' + chr(10954 - 10843) + chr(0b1100100) + chr(0b1100010 + 0o3))(chr(0b1110101) + '\164' + '\x66' + '\x2d' + chr(949 - 893)): M8_cKLkHVB2V(IndhTE9HSpWS), xafqLlk3kkUe(SXOLrMavuUCe(b'\xd6\x18S\xdb\xa9G'), '\x64' + '\145' + '\x63' + chr(0b11000 + 0o127) + '\x64' + chr(101))(chr(117) + chr(0b1110100) + '\146' + chr(0b101101) + chr(0b111000)): {}}
try:
return DNu32EriaOEo(jAj7S20Ct06o)
except q1QCh3W88sgk:
return QmmgWUB13VCJ
elif tzcpInYwBvYW(IndhTE9HSpWS):
return IndhTE9HSpWS
return QmmgWUB13VCJ
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/trajectory.py
|
Trajectory.add_time_step
|
def add_time_step(self, **create_time_step_kwargs):
"""Creates a time-step and appends it to the list.
Args:
**create_time_step_kwargs: Forwarded to
time_step.TimeStep.create_time_step.
"""
ts = time_step.TimeStep.create_time_step(**create_time_step_kwargs)
assert isinstance(ts, time_step.TimeStep)
self._time_steps.append(ts)
|
python
|
def add_time_step(self, **create_time_step_kwargs):
"""Creates a time-step and appends it to the list.
Args:
**create_time_step_kwargs: Forwarded to
time_step.TimeStep.create_time_step.
"""
ts = time_step.TimeStep.create_time_step(**create_time_step_kwargs)
assert isinstance(ts, time_step.TimeStep)
self._time_steps.append(ts)
|
[
"def",
"add_time_step",
"(",
"self",
",",
"*",
"*",
"create_time_step_kwargs",
")",
":",
"ts",
"=",
"time_step",
".",
"TimeStep",
".",
"create_time_step",
"(",
"*",
"*",
"create_time_step_kwargs",
")",
"assert",
"isinstance",
"(",
"ts",
",",
"time_step",
".",
"TimeStep",
")",
"self",
".",
"_time_steps",
".",
"append",
"(",
"ts",
")"
] |
Creates a time-step and appends it to the list.
Args:
**create_time_step_kwargs: Forwarded to
time_step.TimeStep.create_time_step.
|
[
"Creates",
"a",
"time",
"-",
"step",
"and",
"appends",
"it",
"to",
"the",
"list",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/trajectory.py#L42-L51
|
train
|
Creates a time - step and appends it to the list.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(111) + chr(0b1000 + 0o51) + chr(2531 - 2478) + chr(50), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001) + '\062' + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(2206 - 2158) + chr(0b110000 + 0o77) + chr(0b110001) + chr(50) + '\x31', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110010) + '\x36' + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(747 - 699) + chr(0b10 + 0o155) + chr(1423 - 1370), 38890 - 38882), ehT0Px3KOsy9('\x30' + chr(8248 - 8137) + '\061' + chr(49) + chr(0b110010 + 0o0), 0b1000), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(5907 - 5796) + chr(1920 - 1867) + chr(538 - 483), 23677 - 23669), ehT0Px3KOsy9(chr(591 - 543) + chr(111) + '\x37' + chr(0b110101), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1010011 + 0o34) + '\x31' + chr(53) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b1001101 + 0o42) + chr(118 - 67) + chr(52) + chr(0b100101 + 0o21), 0b1000), ehT0Px3KOsy9(chr(165 - 117) + '\157' + chr(51) + '\x36' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(1094 - 1046) + '\x6f' + chr(49) + chr(1341 - 1293) + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + chr(51) + '\066' + chr(0b10111 + 0o34), 0o10), ehT0Px3KOsy9('\060' + chr(0b100101 + 0o112) + '\063' + chr(0b101 + 0o60) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + '\061' + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b111101 + 0o62) + chr(0b10110 + 0o41) + chr(55), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001) + chr(2196 - 2148) + chr(0b10011 + 0o36), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(186 - 132) + '\x32', 59525 - 59517), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(9985 - 9874) + '\062' + chr(55) + chr(0b110101), 5608 - 5600), ehT0Px3KOsy9(chr(592 - 544) + '\157' + '\061' + chr(1121 - 1066), 32031 - 32023), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + '\062' + chr(1557 - 1506), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1111 + 0o42) + chr(0b110100 + 0o3) + '\x34', ord("\x08")), ehT0Px3KOsy9('\060' + chr(10590 - 10479) + '\061' + chr(48) + chr(0b100000 + 0o23), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(11469 - 11358) + chr(0b100101 + 0o14) + chr(2478 - 2425) + chr(0b110010), 8), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(111) + chr(51) + '\067', 39390 - 39382), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\065' + chr(0b101011 + 0o10), 15438 - 15430), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1640 - 1591) + '\062' + '\067', 12523 - 12515), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\066' + '\x34', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(276 - 226) + '\x33' + chr(0b1110 + 0o42), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\063' + '\067' + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(6970 - 6859) + chr(763 - 711) + '\061', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\062' + chr(1578 - 1529), 10120 - 10112), ehT0Px3KOsy9('\060' + chr(111) + '\061' + chr(2685 - 2633) + chr(54), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b11010 + 0o34) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b11111 + 0o22) + chr(0b101010 + 0o6) + chr(761 - 707), 8), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(0b1011011 + 0o24) + chr(2331 - 2280) + '\063' + '\064', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\065' + '\066', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11110 + 0o24) + '\063' + chr(55), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + chr(0b11100 + 0o32) + chr(0b101110 + 0o4), 0o10), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b100011 + 0o114) + chr(1024 - 975) + chr(49) + chr(1036 - 983), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(3798 - 3687) + '\x35' + chr(48), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'D'), '\x64' + '\145' + chr(0b1100001 + 0o2) + '\157' + '\144' + chr(0b100110 + 0o77))(chr(117) + '\x74' + chr(102) + '\x2d' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def V9QiEgd6qLdQ(oVre8I6UXc3b, **TIuN0TwdEFDA):
vRr8KUuV1pxu = zVXIFxIBf7Io.TimeStep.create_time_step(**TIuN0TwdEFDA)
assert PlSM16l2KDPD(vRr8KUuV1pxu, xafqLlk3kkUe(zVXIFxIBf7Io, xafqLlk3kkUe(SXOLrMavuUCe(b'>9<\xd1V>JM'), chr(0b1100100) + chr(101) + chr(99) + chr(0b1101111) + chr(0b1010010 + 0o22) + '\x65')('\165' + '\x74' + chr(102) + chr(45) + '\x38')))
xafqLlk3kkUe(oVre8I6UXc3b._time_steps, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0b !\xd1k.'), '\144' + '\x65' + '\143' + chr(9960 - 9849) + chr(7606 - 7506) + '\145')(chr(0b1110101) + chr(0b1110100) + chr(102) + '\x2d' + chr(0b110110 + 0o2)))(vRr8KUuV1pxu)
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/trajectory.py
|
Trajectory.change_last_time_step
|
def change_last_time_step(self, **replace_time_step_kwargs):
"""Replace the last time-steps with the given kwargs."""
# Pre-conditions: self._time_steps shouldn't be empty.
assert self._time_steps
self._time_steps[-1] = self._time_steps[-1].replace(
**replace_time_step_kwargs)
|
python
|
def change_last_time_step(self, **replace_time_step_kwargs):
"""Replace the last time-steps with the given kwargs."""
# Pre-conditions: self._time_steps shouldn't be empty.
assert self._time_steps
self._time_steps[-1] = self._time_steps[-1].replace(
**replace_time_step_kwargs)
|
[
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"*",
"replace_time_step_kwargs",
")",
":",
"# Pre-conditions: self._time_steps shouldn't be empty.",
"assert",
"self",
".",
"_time_steps",
"self",
".",
"_time_steps",
"[",
"-",
"1",
"]",
"=",
"self",
".",
"_time_steps",
"[",
"-",
"1",
"]",
".",
"replace",
"(",
"*",
"*",
"replace_time_step_kwargs",
")"
] |
Replace the last time-steps with the given kwargs.
|
[
"Replace",
"the",
"last",
"time",
"-",
"steps",
"with",
"the",
"given",
"kwargs",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/trajectory.py#L53-L59
|
train
|
Replace the last time - step with the given kwargs.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(111) + chr(53) + '\066', 4992 - 4984), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + chr(55) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\066' + '\x32', 4878 - 4870), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + chr(0b110110) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b1101 + 0o47) + chr(2468 - 2417), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + '\x31' + '\x31', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\063' + '\067' + chr(0b110010), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001) + '\061' + chr(0b110100), 53766 - 53758), ehT0Px3KOsy9(chr(0b110000) + chr(7863 - 7752) + chr(951 - 902) + chr(0b10010 + 0o36) + '\x35', 34750 - 34742), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + chr(0b110000) + '\066', 0b1000), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b1101111) + chr(50) + chr(0b100 + 0o61) + '\x36', 0o10), ehT0Px3KOsy9(chr(127 - 79) + chr(111) + '\063' + '\065' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(12249 - 12138) + chr(0b110010 + 0o1) + '\x34' + '\x32', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(54), 0b1000), ehT0Px3KOsy9(chr(2137 - 2089) + chr(111) + '\062' + chr(49) + chr(51), 26285 - 26277), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + chr(2461 - 2407), 0b1000), ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\x6f' + '\062' + '\x35' + '\x32', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\062' + chr(0b11000 + 0o31) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(4313 - 4202) + chr(49) + chr(0b1001 + 0o53) + chr(0b1010 + 0o52), 32923 - 32915), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(0b1101111) + '\x31' + chr(291 - 238) + chr(0b110111), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b111100 + 0o63) + chr(2082 - 2031) + chr(0b11101 + 0o23) + chr(0b110010), 8970 - 8962), ehT0Px3KOsy9('\060' + chr(0b1001001 + 0o46) + chr(1284 - 1235) + chr(0b110100) + '\064', 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + chr(49) + chr(0b110011), 30490 - 30482), ehT0Px3KOsy9('\060' + chr(111) + chr(52) + chr(0b100010 + 0o17), 0b1000), ehT0Px3KOsy9(chr(0b1010 + 0o46) + '\x6f' + '\062' + chr(2209 - 2161) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2479 - 2429) + chr(55) + chr(0b10 + 0o56), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(2399 - 2348) + chr(0b101010 + 0o6) + chr(0b110010), 8), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(0b1100000 + 0o17) + chr(50) + chr(0b110010), 46989 - 46981), ehT0Px3KOsy9('\060' + chr(6214 - 6103) + chr(50) + chr(0b110110) + '\x34', 38135 - 38127), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b1101111) + chr(0b110001) + chr(1132 - 1084) + chr(0b101100 + 0o4), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x37' + '\060', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\064' + '\064', 38088 - 38080), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + chr(1307 - 1259), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(7039 - 6928) + '\063' + '\x35' + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + chr(49) + '\x30', 1717 - 1709), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + '\064' + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + '\060' + '\x31', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110110) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(8346 - 8235) + chr(0b110010) + '\063' + chr(0b110100), 35464 - 35456), ehT0Px3KOsy9(chr(48) + chr(0b10100 + 0o133) + '\x32' + chr(0b1001 + 0o54) + chr(0b11 + 0o55), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(8352 - 8241) + chr(2044 - 1991) + '\x30', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x00'), '\144' + chr(0b1100101) + chr(0b1100011) + chr(5163 - 5052) + chr(0b1100100) + chr(101))(chr(0b1110101) + '\164' + chr(0b1010110 + 0o20) + chr(45) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ubwKZso63dXF(oVre8I6UXc3b, **ZcMMZmEz1fZZ):
assert xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'q\r[\xdaF\x16\x898 \xb6\xdd'), chr(0b1100100) + '\x65' + chr(1426 - 1327) + chr(7817 - 7706) + chr(100) + '\x65')(chr(0b1110101) + chr(7151 - 7035) + '\146' + chr(0b11011 + 0o22) + chr(56)))
oVre8I6UXc3b.YXBZA8Amc9YN[-ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(0b1101111) + chr(49), ord("\x08"))] = oVre8I6UXc3b._time_steps[-ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b1101111) + chr(0b101001 + 0o10), 8)].replace(**ZcMMZmEz1fZZ)
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/trajectory.py
|
Trajectory.reward
|
def reward(self):
"""Returns a tuple of sum of raw and processed rewards."""
raw_rewards, processed_rewards = 0, 0
for ts in self.time_steps:
# NOTE: raw_reward and processed_reward are None for the first time-step.
if ts.raw_reward is not None:
raw_rewards += ts.raw_reward
if ts.processed_reward is not None:
processed_rewards += ts.processed_reward
return raw_rewards, processed_rewards
|
python
|
def reward(self):
"""Returns a tuple of sum of raw and processed rewards."""
raw_rewards, processed_rewards = 0, 0
for ts in self.time_steps:
# NOTE: raw_reward and processed_reward are None for the first time-step.
if ts.raw_reward is not None:
raw_rewards += ts.raw_reward
if ts.processed_reward is not None:
processed_rewards += ts.processed_reward
return raw_rewards, processed_rewards
|
[
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"reward",
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")",
":",
"raw_rewards",
",",
"processed_rewards",
"=",
"0",
",",
"0",
"for",
"ts",
"in",
"self",
".",
"time_steps",
":",
"# NOTE: raw_reward and processed_reward are None for the first time-step.",
"if",
"ts",
".",
"raw_reward",
"is",
"not",
"None",
":",
"raw_rewards",
"+=",
"ts",
".",
"raw_reward",
"if",
"ts",
".",
"processed_reward",
"is",
"not",
"None",
":",
"processed_rewards",
"+=",
"ts",
".",
"processed_reward",
"return",
"raw_rewards",
",",
"processed_rewards"
] |
Returns a tuple of sum of raw and processed rewards.
|
[
"Returns",
"a",
"tuple",
"of",
"sum",
"of",
"raw",
"and",
"processed",
"rewards",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/trajectory.py#L85-L94
|
train
|
Returns a tuple of sum of raw and processed rewards.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b10101 + 0o132) + chr(0b101001 + 0o11) + chr(0b110010) + '\064', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b1000 + 0o53) + '\061' + chr(2117 - 2062), 4080 - 4072), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + chr(0b101001 + 0o7) + chr(0b110010), 36543 - 36535), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + chr(761 - 712) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + chr(816 - 765) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(0b11010 + 0o125) + chr(50) + chr(48) + chr(0b110001), 0b1000), ehT0Px3KOsy9('\060' + chr(902 - 791) + chr(0b10100 + 0o36) + chr(54) + '\067', 17000 - 16992), ehT0Px3KOsy9(chr(48) + chr(111) + '\x31' + '\061' + '\x32', 58927 - 58919), ehT0Px3KOsy9(chr(0b110000) + chr(2310 - 2199) + '\062' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(935 - 887) + chr(0b1010011 + 0o34) + chr(0b100000 + 0o23) + '\x36' + '\066', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + chr(49) + chr(905 - 856), 31860 - 31852), ehT0Px3KOsy9('\x30' + chr(111) + chr(50) + chr(1559 - 1504) + '\x34', 37754 - 37746), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10011 + 0o37) + chr(0b100 + 0o62) + '\x33', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b11010 + 0o31) + '\x35' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + chr(0b100101 + 0o22) + chr(52), 8), ehT0Px3KOsy9('\x30' + '\157' + chr(148 - 98) + chr(54) + chr(50), 0b1000), ehT0Px3KOsy9(chr(1707 - 1659) + chr(0b1001010 + 0o45) + '\x33' + '\x31' + chr(946 - 893), 0o10), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(0b1101 + 0o142) + '\063' + chr(682 - 628) + chr(0b111 + 0o55), 27842 - 27834), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + '\066' + '\064', 8), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(111) + '\x33' + chr(440 - 386) + chr(1847 - 1796), 11418 - 11410), ehT0Px3KOsy9(chr(0b10 + 0o56) + '\x6f' + chr(1857 - 1808), 6213 - 6205), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001001 + 0o46) + chr(1191 - 1141) + chr(54) + chr(2749 - 2694), 8), ehT0Px3KOsy9('\060' + '\157' + chr(0b101100 + 0o5) + chr(0b110011) + chr(815 - 762), 0o10), ehT0Px3KOsy9('\060' + chr(11500 - 11389) + chr(50) + chr(1976 - 1926) + chr(0b110100), 8), ehT0Px3KOsy9(chr(1379 - 1331) + chr(6417 - 6306) + chr(0b110001) + '\065' + chr(49), 0o10), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1101111) + chr(49) + chr(448 - 395) + chr(55), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + chr(2434 - 2381) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\157' + chr(50) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + chr(0b101110 + 0o3) + chr(2596 - 2542), 14027 - 14019), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\x6f' + '\x32' + chr(0b100000 + 0o23) + chr(280 - 232), 49783 - 49775), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x34' + chr(0b100001 + 0o21), 15905 - 15897), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\157' + chr(51) + '\067' + chr(0b101111 + 0o7), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110100) + chr(1120 - 1067), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(470 - 421) + '\061' + chr(0b110010), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b100000 + 0o117) + chr(0b110001) + '\061' + '\x34', 36546 - 36538), ehT0Px3KOsy9(chr(0b100 + 0o54) + '\x6f' + '\061' + chr(48) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\063' + chr(54) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\157' + chr(0b110011) + chr(53) + '\x31', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(8147 - 8036) + '\x35' + chr(0b11111 + 0o21), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xba'), chr(0b1100100) + chr(6852 - 6751) + chr(5739 - 5640) + chr(362 - 251) + chr(7539 - 7439) + chr(2969 - 2868))(chr(0b1110101) + '\164' + chr(0b1010100 + 0o22) + chr(0b101101) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def jEXsEsgeguP4(oVre8I6UXc3b):
(Q6_1NAs64aKe, KmO4a71nY2SN) = (ehT0Px3KOsy9(chr(2110 - 2062) + chr(0b1101111) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(1845 - 1797) + '\x6f' + chr(48), 8))
for vRr8KUuV1pxu in xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe0\xa6\xaf+\xc2\xf2\xc3/`\x85'), chr(100) + chr(0b1010000 + 0o25) + chr(99) + chr(0b1101111) + chr(100) + '\145')('\165' + chr(0b1001 + 0o153) + '\146' + '\055' + chr(0b111000))):
if xafqLlk3kkUe(vRr8KUuV1pxu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe6\xae\xb5\x11\xef\xe4\xc0+b\x92'), chr(100) + chr(1851 - 1750) + chr(99) + '\157' + '\x64' + '\145')('\165' + chr(0b1110100) + chr(0b10010 + 0o124) + '\x2d' + '\x38')) is not None:
Q6_1NAs64aKe += vRr8KUuV1pxu.raw_reward
if xafqLlk3kkUe(vRr8KUuV1pxu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe4\xbd\xad-\xf8\xf2\xc4/t\xa9\xfb\xd9\xc4\x8b\xce\xd6'), chr(3613 - 3513) + '\145' + '\x63' + '\157' + chr(100) + chr(0b1100101))(chr(117) + chr(116) + chr(0b1100110) + '\x2d' + chr(0b111000))) is not None:
KmO4a71nY2SN += vRr8KUuV1pxu.processed_reward
return (Q6_1NAs64aKe, KmO4a71nY2SN)
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/trajectory.py
|
BatchTrajectory._complete_trajectory
|
def _complete_trajectory(self, trajectory, index):
"""Completes the given trajectory at the given index."""
assert isinstance(trajectory, Trajectory)
# This *should* be the case.
assert trajectory.last_time_step.action is None
# Add to completed trajectories.
self._completed_trajectories.append(trajectory)
# Make a new one to replace it.
self._trajectories[index] = Trajectory()
|
python
|
def _complete_trajectory(self, trajectory, index):
"""Completes the given trajectory at the given index."""
assert isinstance(trajectory, Trajectory)
# This *should* be the case.
assert trajectory.last_time_step.action is None
# Add to completed trajectories.
self._completed_trajectories.append(trajectory)
# Make a new one to replace it.
self._trajectories[index] = Trajectory()
|
[
"def",
"_complete_trajectory",
"(",
"self",
",",
"trajectory",
",",
"index",
")",
":",
"assert",
"isinstance",
"(",
"trajectory",
",",
"Trajectory",
")",
"# This *should* be the case.",
"assert",
"trajectory",
".",
"last_time_step",
".",
"action",
"is",
"None",
"# Add to completed trajectories.",
"self",
".",
"_completed_trajectories",
".",
"append",
"(",
"trajectory",
")",
"# Make a new one to replace it.",
"self",
".",
"_trajectories",
"[",
"index",
"]",
"=",
"Trajectory",
"(",
")"
] |
Completes the given trajectory at the given index.
|
[
"Completes",
"the",
"given",
"trajectory",
"at",
"the",
"given",
"index",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/trajectory.py#L133-L145
|
train
|
Completes the given trajectory at the given index.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\065' + chr(48), 0o10), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(10721 - 10610) + chr(51) + chr(53) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(784 - 736) + '\157' + chr(765 - 716) + chr(0b110010) + '\x35', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(54) + chr(50), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + '\062' + chr(0b10001 + 0o40), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + '\065' + chr(1954 - 1899), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110 + 0o53) + chr(48), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(0b110010) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(0b1101111) + '\x33' + chr(2295 - 2245) + chr(0b10101 + 0o40), 57488 - 57480), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1011000 + 0o27) + '\x32' + chr(0b110101) + chr(1800 - 1750), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + '\x36' + chr(2154 - 2106), 62258 - 62250), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\x6f' + '\062' + chr(52) + '\x35', 24750 - 24742), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + chr(113 - 60) + chr(0b10110 + 0o36), 0o10), ehT0Px3KOsy9(chr(680 - 632) + chr(0b1101111) + chr(940 - 885) + chr(0b10101 + 0o35), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(2351 - 2301) + chr(0b110100) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b100110 + 0o111) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + chr(0b101100 + 0o12) + chr(53), 0o10), ehT0Px3KOsy9(chr(2172 - 2124) + chr(0b11110 + 0o121) + '\x32' + chr(1179 - 1131) + chr(0b110000), 61244 - 61236), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + '\066' + chr(773 - 724), 0b1000), ehT0Px3KOsy9(chr(1953 - 1905) + '\157' + chr(0b11100 + 0o26) + chr(586 - 537) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(8230 - 8119) + chr(55) + '\061', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1000001 + 0o56) + '\x32' + '\x34' + '\065', 8), ehT0Px3KOsy9('\060' + chr(0b100000 + 0o117) + chr(538 - 487) + chr(50), 11104 - 11096), ehT0Px3KOsy9(chr(48) + chr(111) + chr(818 - 768) + '\066' + chr(0b0 + 0o63), 0o10), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b111100 + 0o63) + chr(49) + chr(1118 - 1067) + '\063', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1281 - 1232) + '\x36' + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\157' + chr(359 - 310) + chr(0b110000) + '\066', 0o10), ehT0Px3KOsy9(chr(277 - 229) + chr(0b1101111) + chr(51) + chr(2531 - 2480) + chr(726 - 673), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b11 + 0o154) + '\x33' + chr(0b11111 + 0o23) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + chr(0b110010) + chr(0b110000), 63962 - 63954), ehT0Px3KOsy9(chr(48) + chr(7129 - 7018) + chr(0b110011) + '\064' + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\063' + '\x31' + chr(0b100 + 0o57), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b1111 + 0o47) + chr(1289 - 1240), 0o10), ehT0Px3KOsy9(chr(511 - 463) + chr(0b1001001 + 0o46) + chr(1107 - 1052), 0b1000), ehT0Px3KOsy9(chr(48) + chr(6246 - 6135) + chr(50) + '\062' + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(685 - 637) + chr(0b1101111) + '\061' + chr(49) + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110010) + '\x36' + chr(0b100111 + 0o17), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + '\065' + chr(51), 0o10), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\x6f' + chr(0b110100 + 0o1) + '\x32', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(2154 - 2103) + '\062' + chr(2333 - 2279), 13695 - 13687)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(10816 - 10705) + '\065' + chr(0b110000), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x06'), '\x64' + '\145' + chr(0b1000010 + 0o41) + chr(111) + chr(0b1100100) + chr(0b1100101))('\x75' + '\164' + '\x66' + chr(0b101101) + chr(0b101000 + 0o20)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def vihjp6f4ypSK(oVre8I6UXc3b, Mzq2fr56UhXf, XdowRbJKZWL9):
assert PlSM16l2KDPD(Mzq2fr56UhXf, uCoE1wq9pn3A)
assert xafqLlk3kkUe(Mzq2fr56UhXf.last_time_step, xafqLlk3kkUe(SXOLrMavuUCe(b'I\x8c![\xfe\xc1'), '\x64' + chr(6960 - 6859) + chr(0b1100011) + chr(111) + '\144' + chr(9772 - 9671))(chr(117) + '\x74' + '\146' + chr(0b1101 + 0o40) + '\x38')) is None
xafqLlk3kkUe(oVre8I6UXc3b._completed_trajectories, xafqLlk3kkUe(SXOLrMavuUCe(b'I\x9f%W\xff\xcb'), '\144' + chr(101) + chr(99) + chr(0b1101 + 0o142) + '\144' + chr(0b101110 + 0o67))('\x75' + '\x74' + '\x66' + chr(912 - 867) + chr(2280 - 2224)))(Mzq2fr56UhXf)
oVre8I6UXc3b.V73mUfYH1QkS[XdowRbJKZWL9] = uCoE1wq9pn3A()
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/trajectory.py
|
BatchTrajectory.reset
|
def reset(self, indices, observations):
"""Resets trajectories at given indices and populates observations.
Reset can either be called right at the beginning, when there are no
time-steps, or to reset a currently active trajectory.
If resetting a currently active trajectory then we save it in
self._completed_trajectories.
Args:
indices: 1-D np.ndarray stating the indices to reset.
observations: np.ndarray of shape (indices len, obs.shape) of observations
"""
# Pre-conditions: indices, observations are np arrays.
# : indices is one-dimensional.
# : their first dimension (batch) is the same.
assert isinstance(indices, np.ndarray)
assert len(indices.shape) == 1
assert isinstance(observations, np.ndarray)
assert indices.shape[0] == observations.shape[0]
for index, observation in zip(indices, observations):
trajectory = self._trajectories[index]
# Are we starting a new trajectory at the given index?
if not trajectory.is_active:
# Then create a new time-step here with the given observation.
trajectory.add_time_step(observation=observation)
# That's all we need to do here.
continue
# If however we are resetting a currently active trajectory then we need
# to put that in self._completed_trajectories and make a new trajectory
# with the current observation.
# TODO(afrozm): Should we mark these are done? Or is the done=False and
# this being the last time-step in the trajectory good enough to recognize
# that this was reset?
# Mark trajectory as completed and move into completed_trajectories.
self._complete_trajectory(trajectory, index)
# Put the observation in the newly created trajectory.
# TODO(afrozm): Add 0 reward.
self._trajectories[index].add_time_step(observation=observation)
|
python
|
def reset(self, indices, observations):
"""Resets trajectories at given indices and populates observations.
Reset can either be called right at the beginning, when there are no
time-steps, or to reset a currently active trajectory.
If resetting a currently active trajectory then we save it in
self._completed_trajectories.
Args:
indices: 1-D np.ndarray stating the indices to reset.
observations: np.ndarray of shape (indices len, obs.shape) of observations
"""
# Pre-conditions: indices, observations are np arrays.
# : indices is one-dimensional.
# : their first dimension (batch) is the same.
assert isinstance(indices, np.ndarray)
assert len(indices.shape) == 1
assert isinstance(observations, np.ndarray)
assert indices.shape[0] == observations.shape[0]
for index, observation in zip(indices, observations):
trajectory = self._trajectories[index]
# Are we starting a new trajectory at the given index?
if not trajectory.is_active:
# Then create a new time-step here with the given observation.
trajectory.add_time_step(observation=observation)
# That's all we need to do here.
continue
# If however we are resetting a currently active trajectory then we need
# to put that in self._completed_trajectories and make a new trajectory
# with the current observation.
# TODO(afrozm): Should we mark these are done? Or is the done=False and
# this being the last time-step in the trajectory good enough to recognize
# that this was reset?
# Mark trajectory as completed and move into completed_trajectories.
self._complete_trajectory(trajectory, index)
# Put the observation in the newly created trajectory.
# TODO(afrozm): Add 0 reward.
self._trajectories[index].add_time_step(observation=observation)
|
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"(",
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] |
Resets trajectories at given indices and populates observations.
Reset can either be called right at the beginning, when there are no
time-steps, or to reset a currently active trajectory.
If resetting a currently active trajectory then we save it in
self._completed_trajectories.
Args:
indices: 1-D np.ndarray stating the indices to reset.
observations: np.ndarray of shape (indices len, obs.shape) of observations
|
[
"Resets",
"trajectories",
"at",
"given",
"indices",
"and",
"populates",
"observations",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/trajectory.py#L147-L192
|
train
|
Resets trajectories at given indices and populates observations.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b111010 + 0o65) + chr(51) + '\066' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b10 + 0o57) + '\x32' + chr(0b110000 + 0o5), 0o10), ehT0Px3KOsy9(chr(988 - 940) + '\x6f' + '\x31' + chr(0b1011 + 0o51) + chr(48), 52978 - 52970), ehT0Px3KOsy9('\x30' + chr(111) + chr(50) + chr(0b101000 + 0o14) + '\062', 13407 - 13399), ehT0Px3KOsy9(chr(48) + chr(0b101101 + 0o102) + '\x33' + chr(0b100110 + 0o20) + chr(0b110100), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(2106 - 2056) + chr(0b110111) + chr(1540 - 1491), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10010 + 0o41) + chr(2100 - 2048) + chr(1151 - 1098), 16210 - 16202), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\157' + chr(0b110011) + chr(0b10110 + 0o33) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(905 - 855) + chr(0b110101) + chr(1118 - 1067), 0b1000), ehT0Px3KOsy9('\x30' + chr(4386 - 4275) + chr(0b110001) + chr(0b110000) + '\066', 23073 - 23065), ehT0Px3KOsy9('\060' + chr(0b1100100 + 0o13) + chr(0b110001) + '\x37' + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b110001 + 0o76) + '\063' + chr(51) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + chr(860 - 809), ord("\x08")), ehT0Px3KOsy9(chr(1102 - 1054) + chr(111) + chr(51) + chr(49) + chr(0b10111 + 0o31), 60391 - 60383), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\064' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b111000 + 0o67) + chr(1255 - 1205) + chr(782 - 732) + chr(0b101000 + 0o10), 29502 - 29494), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(51) + chr(0b110010) + '\066', 0o10), ehT0Px3KOsy9(chr(1049 - 1001) + '\x6f' + '\x33' + '\x35' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(564 - 516) + '\x6f' + chr(0b11110 + 0o31), 11711 - 11703), ehT0Px3KOsy9('\x30' + chr(7774 - 7663) + chr(993 - 942) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(5493 - 5382) + '\x34' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\157' + chr(0b110010) + chr(0b110100) + chr(0b1000 + 0o54), 41432 - 41424), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + '\x35' + '\066', 21774 - 21766), ehT0Px3KOsy9('\060' + chr(11018 - 10907) + '\061' + chr(0b10111 + 0o31) + '\062', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(54) + chr(52), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(55) + chr(51), 29257 - 29249), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100001 + 0o22) + chr(0b110100) + chr(0b1000 + 0o54), 43216 - 43208), ehT0Px3KOsy9(chr(0b1100 + 0o44) + '\157' + chr(49) + chr(0b101001 + 0o13) + chr(2985 - 2930), ord("\x08")), ehT0Px3KOsy9(chr(254 - 206) + chr(11407 - 11296) + chr(51) + chr(1094 - 1040) + '\x35', 0o10), ehT0Px3KOsy9(chr(196 - 148) + chr(0b1100101 + 0o12) + chr(1322 - 1271) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b101000 + 0o107) + '\063' + chr(0b10010 + 0o44) + '\x30', 0o10), ehT0Px3KOsy9(chr(1407 - 1359) + chr(111) + chr(1176 - 1124), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(5139 - 5028) + '\061' + '\067' + chr(0b100110 + 0o17), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(291 - 241) + chr(49) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b111000 + 0o67) + '\062' + chr(0b110111) + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(111) + '\061' + chr(2665 - 2611) + chr(150 - 102), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + chr(50) + chr(852 - 797), 0b1000), ehT0Px3KOsy9(chr(48) + chr(8800 - 8689) + chr(55) + '\x32', 2661 - 2653), ehT0Px3KOsy9('\x30' + '\157' + '\x32' + chr(0b110110), 51649 - 51641), ehT0Px3KOsy9('\060' + '\x6f' + chr(913 - 862) + chr(52), 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\157' + chr(0b110101) + chr(0b100100 + 0o14), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd9'), '\x64' + '\145' + '\x63' + chr(0b1000100 + 0o53) + '\144' + chr(0b1100101))('\x75' + chr(1040 - 924) + chr(102) + chr(45) + chr(0b1010 + 0o56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def G0V856pwkJmZ(oVre8I6UXc3b, pIcoaXENl5Pw, uswa0rn3Tb4L):
assert PlSM16l2KDPD(pIcoaXENl5Pw, xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x991\x01\xd0\x86\xd8\x9c'), '\144' + chr(101) + chr(99) + chr(0b1101011 + 0o4) + chr(0b1000010 + 0o42) + chr(5915 - 5814))('\x75' + '\164' + chr(102) + chr(1318 - 1273) + chr(56))))
assert c2A0yzQpDQB3(xafqLlk3kkUe(pIcoaXENl5Pw, xafqLlk3kkUe(SXOLrMavuUCe(b'\x994\x15\xfb\x92\xf5\x82\xa5\xff6\x1b\xba'), chr(100) + chr(0b1100 + 0o131) + chr(456 - 357) + '\157' + chr(100) + '\x65')(chr(117) + chr(0b1110100) + '\146' + chr(0b10101 + 0o30) + '\070'))) == ehT0Px3KOsy9('\x30' + '\157' + chr(49), ord("\x08"))
assert PlSM16l2KDPD(uswa0rn3Tb4L, xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x991\x01\xd0\x86\xd8\x9c'), chr(2428 - 2328) + chr(0b111000 + 0o55) + chr(0b11010 + 0o111) + chr(9932 - 9821) + '\144' + chr(6843 - 6742))('\165' + '\164' + chr(102) + chr(1369 - 1324) + chr(0b111000))))
assert xafqLlk3kkUe(pIcoaXENl5Pw, xafqLlk3kkUe(SXOLrMavuUCe(b'\x994\x15\xfb\x92\xf5\x82\xa5\xff6\x1b\xba'), '\x64' + '\x65' + '\x63' + chr(0b11101 + 0o122) + chr(0b1100001 + 0o3) + '\145')(chr(117) + chr(0b1011001 + 0o33) + chr(102) + '\x2d' + chr(150 - 94)))[ehT0Px3KOsy9(chr(48) + chr(111) + chr(1995 - 1947), ord("\x08"))] == xafqLlk3kkUe(uswa0rn3Tb4L, xafqLlk3kkUe(SXOLrMavuUCe(b'\x994\x15\xfb\x92\xf5\x82\xa5\xff6\x1b\xba'), '\x64' + '\x65' + chr(5365 - 5266) + chr(1543 - 1432) + '\144' + '\x65')(chr(0b111100 + 0o71) + chr(2571 - 2455) + '\146' + chr(45) + chr(0b1010 + 0o56)))[ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1101111) + chr(1430 - 1382), 8)]
for (XdowRbJKZWL9, mKQm526a9xSD) in pZ0NK2y6HRbn(pIcoaXENl5Pw, uswa0rn3Tb4L):
Mzq2fr56UhXf = oVre8I6UXc3b.V73mUfYH1QkS[XdowRbJKZWL9]
if not xafqLlk3kkUe(Mzq2fr56UhXf, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9e&?\xc3\x97\xcd\x8c\xbf\xce'), chr(3105 - 3005) + '\145' + chr(6374 - 6275) + '\x6f' + chr(0b1000011 + 0o41) + chr(0b1100101))('\165' + chr(0b1110100) + chr(6981 - 6879) + chr(0b101101) + chr(383 - 327))):
xafqLlk3kkUe(Mzq2fr56UhXf, xafqLlk3kkUe(SXOLrMavuUCe(b'\x961\x04\xfd\x80\xd0\x88\xac\xf45\x0c\xbd{'), '\144' + chr(4555 - 4454) + chr(0b1000100 + 0o37) + chr(111) + '\144' + chr(101))(chr(10007 - 9890) + '\164' + chr(0b1001010 + 0o34) + chr(0b101101) + '\x38'))(observation=mKQm526a9xSD)
continue
xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa86\x0f\xcf\x84\xd5\x80\xbd\xce\x19\x0c\xaaj\xa2G\xf3\xa2\x83ue'), '\144' + chr(4379 - 4278) + chr(9449 - 9350) + chr(111) + chr(100) + chr(0b1100101))(chr(0b1110101) + chr(116) + chr(0b1010111 + 0o17) + '\055' + chr(0b111000)))(Mzq2fr56UhXf, XdowRbJKZWL9)
xafqLlk3kkUe(oVre8I6UXc3b._trajectories[XdowRbJKZWL9], xafqLlk3kkUe(SXOLrMavuUCe(b'\x961\x04\xfd\x80\xd0\x88\xac\xf45\x0c\xbd{'), '\144' + '\145' + chr(99) + chr(111) + '\144' + chr(0b101111 + 0o66))(chr(0b1110011 + 0o2) + chr(152 - 36) + chr(4662 - 4560) + chr(711 - 666) + chr(0b111000)))(observation=mKQm526a9xSD)
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/trajectory.py
|
BatchTrajectory.complete_all_trajectories
|
def complete_all_trajectories(self):
"""Essentially same as reset, but we don't have observations."""
for index in range(self.batch_size):
trajectory = self._trajectories[index]
assert trajectory.is_active
self._complete_trajectory(trajectory, index)
|
python
|
def complete_all_trajectories(self):
"""Essentially same as reset, but we don't have observations."""
for index in range(self.batch_size):
trajectory = self._trajectories[index]
assert trajectory.is_active
self._complete_trajectory(trajectory, index)
|
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] |
Essentially same as reset, but we don't have observations.
|
[
"Essentially",
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/trajectory.py#L194-L199
|
train
|
Complete all trajectory in the batch.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + '\x6f' + chr(49) + chr(51) + chr(0b11000 + 0o35), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + '\063' + chr(0b101011 + 0o10), 4838 - 4830), ehT0Px3KOsy9(chr(331 - 283) + chr(7854 - 7743) + '\062' + chr(55) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b10001 + 0o136) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(294 - 246) + '\x6f' + chr(2442 - 2389) + chr(0b110011), 57823 - 57815), ehT0Px3KOsy9('\x30' + chr(7009 - 6898) + '\x33' + chr(0b101110 + 0o3) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1100110 + 0o11) + chr(0b101100 + 0o7) + chr(0b100011 + 0o23) + chr(0b111 + 0o57), 0o10), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(0b1101111) + '\061' + chr(0b110100) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + chr(0b111 + 0o54) + '\060', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1068 - 1018) + '\067' + chr(0b10001 + 0o41), 0b1000), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(111) + '\062' + '\061' + chr(0b110101), 12324 - 12316), ehT0Px3KOsy9(chr(48) + chr(111) + '\x32' + '\066' + chr(0b110011), 47530 - 47522), ehT0Px3KOsy9('\060' + chr(111) + '\062' + chr(0b110111) + chr(53), 0b1000), ehT0Px3KOsy9(chr(838 - 790) + chr(5702 - 5591) + chr(0b1100 + 0o46) + '\x36' + chr(49), 64889 - 64881), ehT0Px3KOsy9(chr(48) + '\157' + '\x31' + chr(0b110011) + chr(0b110000 + 0o2), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + chr(0b101100 + 0o4), 55505 - 55497), ehT0Px3KOsy9(chr(1324 - 1276) + chr(0b1001001 + 0o46) + chr(0b110001) + chr(53) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(111) + chr(0b100010 + 0o21) + chr(0b10 + 0o64) + chr(0b10010 + 0o44), 8), ehT0Px3KOsy9(chr(48) + chr(0b11110 + 0o121) + chr(50) + '\067' + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(49) + chr(0b110111) + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + chr(1775 - 1720), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b100100 + 0o15) + chr(0b101 + 0o60) + '\x37', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + '\060' + '\060', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + '\064' + chr(55), 0o10), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(0b1101111) + chr(1490 - 1439) + '\x32' + chr(1886 - 1833), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b1000 + 0o53) + chr(50) + chr(0b101 + 0o62), 16865 - 16857), ehT0Px3KOsy9('\060' + chr(111) + '\x35', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\064' + '\x36', 0o10), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\x6f' + chr(1692 - 1642) + '\x31' + chr(0b0 + 0o66), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\061' + '\064' + chr(0b110100), 0o10), ehT0Px3KOsy9('\060' + chr(1199 - 1088) + chr(0b110010) + '\065' + chr(400 - 352), 0b1000), ehT0Px3KOsy9('\060' + chr(0b100010 + 0o115) + chr(0b1011 + 0o53) + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\157' + chr(0b110010) + chr(55) + chr(49), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001) + chr(0b110001) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(0b110111 + 0o70) + '\062' + chr(0b101101 + 0o11), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110100) + '\x33', 0o10), ehT0Px3KOsy9(chr(801 - 753) + chr(0b101111 + 0o100) + chr(0b10101 + 0o35) + chr(52) + chr(0b10001 + 0o44), 0b1000), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(7718 - 7607) + chr(2104 - 2051) + chr(0b110 + 0o52), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(5651 - 5540) + chr(0b110101) + chr(0b110000), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b's'), '\144' + chr(101) + chr(8915 - 8816) + chr(111) + '\x64' + chr(1942 - 1841))(chr(0b1110101) + chr(962 - 846) + chr(102) + '\x2d' + chr(0b100101 + 0o23)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def PSL6OVcyfMKq(oVre8I6UXc3b):
for XdowRbJKZWL9 in vQr8gNKaIaWE(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'4#\x87eq\xb1\x93$\xb5\xef\xf5\xea'), '\x64' + '\x65' + chr(99) + chr(3252 - 3141) + chr(9991 - 9891) + '\145')(chr(0b11111 + 0o126) + chr(0b1001101 + 0o47) + chr(102) + chr(0b101101) + chr(56)))):
Mzq2fr56UhXf = oVre8I6UXc3b.V73mUfYH1QkS[XdowRbJKZWL9]
assert xafqLlk3kkUe(Mzq2fr56UhXf, xafqLlk3kkUe(SXOLrMavuUCe(b'4(\xe1`H\xbc\x9f\x13\xbd'), chr(2338 - 2238) + '\145' + chr(0b110010 + 0o61) + '\157' + '\x64' + '\x65')(chr(0b1110101) + chr(371 - 255) + chr(3290 - 3188) + '\055' + chr(0b111000)))
xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x028\xd1l[\xa4\x93\x11\xbd\xe5\xf9\xc1\xdc\xdb?s\x1c\x99\xcb\x00'), chr(0b1100100) + chr(0b110100 + 0o61) + chr(0b1100011) + chr(111) + chr(100) + '\145')('\165' + chr(116) + '\146' + chr(45) + chr(2328 - 2272)))(Mzq2fr56UhXf, XdowRbJKZWL9)
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/trajectory.py
|
BatchTrajectory.step
|
def step(self, observations, raw_rewards, processed_rewards, dones, actions):
"""Record the information obtained from taking a step in all envs.
Records (observation, rewards, done) in a new time-step and actions in the
current time-step.
If any trajectory gets done, we move that trajectory to
completed_trajectories.
Args:
observations: ndarray of first dimension self.batch_size, which has the
observations after we've stepped, i.e. s_{t+1} where t is the current
state.
raw_rewards: ndarray of first dimension self.batch_size containing raw
rewards i.e. r_{t+1}.
processed_rewards: ndarray of first dimension self.batch_size containing
processed rewards. i.e. r_{t+1}
dones: ndarray of first dimension self.batch_size, containing true at an
index if that env is done, i.e. d_{t+1}
actions: ndarray of first dimension self.batch_size, containing actions
applied at the current time-step, which leads to the observations
rewards and done at the next time-step, i.e. a_t
"""
# Pre-conditions
assert isinstance(observations, np.ndarray)
assert isinstance(raw_rewards, np.ndarray)
assert isinstance(processed_rewards, np.ndarray)
assert isinstance(dones, np.ndarray)
assert isinstance(actions, np.ndarray)
# We assume that we step in all envs, i.e. not like reset where we can reset
# some envs and not others.
assert self.batch_size == observations.shape[0]
assert self.batch_size == raw_rewards.shape[0]
assert self.batch_size == processed_rewards.shape[0]
assert self.batch_size == dones.shape[0]
assert self.batch_size == actions.shape[0]
for index in range(self.batch_size):
trajectory = self._trajectories[index]
# NOTE: If the trajectory isn't active, that means it doesn't have any
# time-steps in it, but we are in step, so the assumption is that it has
# a prior observation from which we are stepping away from.
# TODO(afrozm): Let's re-visit this if it becomes too restrictive.
assert trajectory.is_active
# To this trajectory's last time-step, set actions.
trajectory.change_last_time_step(action=actions[index])
# Create a new time-step to add observation, done & rewards (no actions).
trajectory.add_time_step(
observation=observations[index],
done=dones[index],
raw_reward=raw_rewards[index],
processed_reward=processed_rewards[index])
# If the trajectory is completed, i.e. dones[index] == True, then we
# account for it right-away.
if dones[index]:
self._complete_trajectory(trajectory, index)
# NOTE: The new trajectory at `index` is going to be in-active and
# `reset` should be called on it.
assert not self._trajectories[index].is_active
|
python
|
def step(self, observations, raw_rewards, processed_rewards, dones, actions):
"""Record the information obtained from taking a step in all envs.
Records (observation, rewards, done) in a new time-step and actions in the
current time-step.
If any trajectory gets done, we move that trajectory to
completed_trajectories.
Args:
observations: ndarray of first dimension self.batch_size, which has the
observations after we've stepped, i.e. s_{t+1} where t is the current
state.
raw_rewards: ndarray of first dimension self.batch_size containing raw
rewards i.e. r_{t+1}.
processed_rewards: ndarray of first dimension self.batch_size containing
processed rewards. i.e. r_{t+1}
dones: ndarray of first dimension self.batch_size, containing true at an
index if that env is done, i.e. d_{t+1}
actions: ndarray of first dimension self.batch_size, containing actions
applied at the current time-step, which leads to the observations
rewards and done at the next time-step, i.e. a_t
"""
# Pre-conditions
assert isinstance(observations, np.ndarray)
assert isinstance(raw_rewards, np.ndarray)
assert isinstance(processed_rewards, np.ndarray)
assert isinstance(dones, np.ndarray)
assert isinstance(actions, np.ndarray)
# We assume that we step in all envs, i.e. not like reset where we can reset
# some envs and not others.
assert self.batch_size == observations.shape[0]
assert self.batch_size == raw_rewards.shape[0]
assert self.batch_size == processed_rewards.shape[0]
assert self.batch_size == dones.shape[0]
assert self.batch_size == actions.shape[0]
for index in range(self.batch_size):
trajectory = self._trajectories[index]
# NOTE: If the trajectory isn't active, that means it doesn't have any
# time-steps in it, but we are in step, so the assumption is that it has
# a prior observation from which we are stepping away from.
# TODO(afrozm): Let's re-visit this if it becomes too restrictive.
assert trajectory.is_active
# To this trajectory's last time-step, set actions.
trajectory.change_last_time_step(action=actions[index])
# Create a new time-step to add observation, done & rewards (no actions).
trajectory.add_time_step(
observation=observations[index],
done=dones[index],
raw_reward=raw_rewards[index],
processed_reward=processed_rewards[index])
# If the trajectory is completed, i.e. dones[index] == True, then we
# account for it right-away.
if dones[index]:
self._complete_trajectory(trajectory, index)
# NOTE: The new trajectory at `index` is going to be in-active and
# `reset` should be called on it.
assert not self._trajectories[index].is_active
|
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] |
Record the information obtained from taking a step in all envs.
Records (observation, rewards, done) in a new time-step and actions in the
current time-step.
If any trajectory gets done, we move that trajectory to
completed_trajectories.
Args:
observations: ndarray of first dimension self.batch_size, which has the
observations after we've stepped, i.e. s_{t+1} where t is the current
state.
raw_rewards: ndarray of first dimension self.batch_size containing raw
rewards i.e. r_{t+1}.
processed_rewards: ndarray of first dimension self.batch_size containing
processed rewards. i.e. r_{t+1}
dones: ndarray of first dimension self.batch_size, containing true at an
index if that env is done, i.e. d_{t+1}
actions: ndarray of first dimension self.batch_size, containing actions
applied at the current time-step, which leads to the observations
rewards and done at the next time-step, i.e. a_t
|
[
"Record",
"the",
"information",
"obtained",
"from",
"taking",
"a",
"step",
"in",
"all",
"envs",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/trajectory.py#L201-L266
|
train
|
This function is called by the next step in all envs.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1547 - 1499) + chr(0b1010010 + 0o35) + '\x32' + chr(0b110000) + '\x33', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + chr(951 - 903) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\x6f' + chr(409 - 358) + chr(0b110001) + chr(55), 0o10), ehT0Px3KOsy9(chr(1744 - 1696) + chr(0b1101111) + '\063' + chr(53) + chr(641 - 590), 0b1000), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b1101111) + '\x36' + '\x35', 16640 - 16632), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + chr(53) + '\x36', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + '\x36' + '\063', 61384 - 61376), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b1101111) + chr(717 - 666) + '\x31' + chr(50), 51150 - 51142), ehT0Px3KOsy9(chr(0b10 + 0o56) + '\157' + chr(0b110001) + chr(0b11100 + 0o32), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(0b110111) + chr(0b11 + 0o61), 46691 - 46683), ehT0Px3KOsy9('\060' + chr(0b1011010 + 0o25) + chr(50) + '\x35' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(552 - 504) + chr(0b1101101 + 0o2) + '\x33' + '\062' + chr(448 - 395), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x34' + chr(54), 30674 - 30666), ehT0Px3KOsy9(chr(48) + chr(0b1011101 + 0o22) + chr(1317 - 1263) + '\x33', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + chr(48) + '\063', 0o10), ehT0Px3KOsy9(chr(926 - 878) + chr(0b110010 + 0o75) + chr(0b110011) + '\x31' + '\064', 14811 - 14803), ehT0Px3KOsy9(chr(48) + chr(0b101101 + 0o102) + '\063' + '\x34', 21936 - 21928), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(49) + chr(0b110000) + chr(51), 8), ehT0Px3KOsy9(chr(48) + chr(9554 - 9443) + chr(174 - 124) + chr(2434 - 2380) + '\061', 12322 - 12314), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + chr(53) + chr(49), 59092 - 59084), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + '\x35' + chr(0b100001 + 0o21), 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\157' + '\x33' + chr(0b0 + 0o60) + chr(55), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + chr(0b110001) + '\060', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + '\066' + '\065', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b101011 + 0o7) + '\x35' + chr(0b110101), 0o10), ehT0Px3KOsy9('\x30' + chr(5271 - 5160) + '\063' + '\060' + '\x32', 56458 - 56450), ehT0Px3KOsy9(chr(48) + chr(0b11011 + 0o124) + chr(51) + chr(0b11111 + 0o21) + chr(0b110101), 55062 - 55054), ehT0Px3KOsy9('\060' + chr(111) + '\x32' + chr(48) + chr(59 - 5), 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\x6f' + chr(2321 - 2270) + chr(678 - 625) + chr(1302 - 1251), 8), ehT0Px3KOsy9(chr(297 - 249) + chr(1755 - 1644) + '\062' + chr(0b110000) + chr(50), 0b1000), ehT0Px3KOsy9(chr(1850 - 1802) + chr(7297 - 7186) + chr(49) + '\065', 46844 - 46836), ehT0Px3KOsy9(chr(1220 - 1172) + chr(0b1011111 + 0o20) + '\x32' + chr(0b101110 + 0o4) + chr(0b11001 + 0o27), ord("\x08")), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(12140 - 12029) + chr(51) + chr(997 - 944) + '\x37', 45992 - 45984), ehT0Px3KOsy9(chr(48) + chr(0b100010 + 0o115) + '\061' + chr(0b11101 + 0o23) + chr(0b110011), 8), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + chr(0b100010 + 0o24) + '\065', 8), ehT0Px3KOsy9(chr(1225 - 1177) + '\x6f' + chr(50) + chr(2097 - 2044) + chr(0b110001), 8), ehT0Px3KOsy9(chr(269 - 221) + chr(7084 - 6973) + '\061' + chr(0b110011) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + chr(2208 - 2157) + chr(52), 0o10), ehT0Px3KOsy9(chr(1223 - 1175) + chr(111) + chr(0b110 + 0o54) + chr(0b110010) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b111 + 0o53) + chr(0b110100) + '\063', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100110 + 0o17) + chr(677 - 629), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xad'), chr(0b1100100) + chr(0b1011101 + 0o10) + '\x63' + '\x6f' + '\144' + '\145')(chr(117) + chr(0b10101 + 0o137) + '\x66' + chr(0b101101) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def kDuFsAhEatcU(oVre8I6UXc3b, uswa0rn3Tb4L, Q6_1NAs64aKe, KmO4a71nY2SN, ijPEVpFpIejc, WCl6VUkME_8I):
assert PlSM16l2KDPD(uswa0rn3Tb4L, xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\xe3\xae\x99G\x8f\n'), '\x64' + chr(0b1100101) + chr(0b1100011) + '\x6f' + '\144' + '\x65')(chr(0b1110101) + chr(0b1110100) + '\146' + chr(0b1110 + 0o37) + '\x38')))
assert PlSM16l2KDPD(Q6_1NAs64aKe, xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\xe3\xae\x99G\x8f\n'), chr(8255 - 8155) + '\145' + chr(0b1100011) + chr(0b1011101 + 0o22) + '\144' + chr(101))(chr(2358 - 2241) + chr(7134 - 7018) + chr(10256 - 10154) + chr(0b101101) + chr(912 - 856))))
assert PlSM16l2KDPD(KmO4a71nY2SN, xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\xe3\xae\x99G\x8f\n'), chr(0b111 + 0o135) + '\x65' + chr(0b101001 + 0o72) + chr(0b1101111) + '\x64' + chr(101))(chr(0b1110101) + chr(5232 - 5116) + chr(0b1011000 + 0o16) + '\055' + chr(0b111000))))
assert PlSM16l2KDPD(ijPEVpFpIejc, xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\xe3\xae\x99G\x8f\n'), chr(100) + '\145' + chr(9011 - 8912) + '\x6f' + chr(1014 - 914) + chr(9482 - 9381))('\165' + chr(0b1011101 + 0o27) + chr(2525 - 2423) + '\055' + chr(0b11100 + 0o34))))
assert PlSM16l2KDPD(WCl6VUkME_8I, xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\xe3\xae\x99G\x8f\n'), chr(100) + '\x65' + chr(99) + chr(10601 - 10490) + chr(0b1100100) + chr(7894 - 7793))('\165' + '\x74' + chr(0b1100110) + chr(0b0 + 0o55) + chr(0b110000 + 0o10))))
assert xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\xff\xf6\x8fo\x97\x16\x8bc)\xd6\x8c'), '\x64' + chr(0b1010011 + 0o22) + chr(1535 - 1436) + chr(111) + chr(100) + chr(0b1100011 + 0o2))('\x75' + chr(632 - 516) + '\x66' + chr(0b11100 + 0o21) + chr(3089 - 3033))) == xafqLlk3kkUe(uswa0rn3Tb4L, xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\xe6\xba\xb2S\xa2\x14\xa6Z\x0c\xcd\xb7'), chr(100) + '\x65' + chr(99) + chr(6244 - 6133) + chr(0b1100000 + 0o4) + chr(0b11011 + 0o112))(chr(0b110 + 0o157) + '\164' + chr(102) + chr(45) + chr(2481 - 2425)))[ehT0Px3KOsy9(chr(2227 - 2179) + '\157' + chr(0b110000), 0o10)]
assert xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\xff\xf6\x8fo\x97\x16\x8bc)\xd6\x8c'), '\x64' + chr(0b1100 + 0o131) + chr(0b1000101 + 0o36) + chr(0b1011 + 0o144) + chr(0b111010 + 0o52) + chr(9786 - 9685))(chr(117) + '\x74' + '\x66' + chr(0b101101) + '\070')) == xafqLlk3kkUe(Q6_1NAs64aKe, xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\xe6\xba\xb2S\xa2\x14\xa6Z\x0c\xcd\xb7'), chr(100) + '\145' + chr(4650 - 4551) + '\x6f' + chr(100) + '\145')(chr(117) + '\x74' + chr(102) + '\055' + chr(0b111000)))[ehT0Px3KOsy9(chr(0b110000) + '\157' + '\060', 8)]
assert xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\xff\xf6\x8fo\x97\x16\x8bc)\xd6\x8c'), chr(0b1100100) + chr(0b10000 + 0o125) + chr(99) + '\x6f' + chr(4970 - 4870) + chr(7502 - 7401))('\165' + chr(0b1110100) + chr(0b110110 + 0o60) + '\055' + '\070')) == xafqLlk3kkUe(KmO4a71nY2SN, xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\xe6\xba\xb2S\xa2\x14\xa6Z\x0c\xcd\xb7'), chr(0b1100100) + chr(101) + chr(2766 - 2667) + '\157' + '\144' + chr(0b1100101))(chr(11289 - 11172) + '\164' + chr(102) + chr(0b10001 + 0o34) + '\070'))[ehT0Px3KOsy9('\060' + chr(0b1101111) + '\060', 8)]
assert xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\xff\xf6\x8fo\x97\x16\x8bc)\xd6\x8c'), chr(0b110110 + 0o56) + chr(0b1110 + 0o127) + chr(0b1100011) + chr(0b100100 + 0o113) + chr(0b1100100) + '\x65')(chr(904 - 787) + chr(0b1110100) + chr(102) + '\x2d' + '\070')) == xafqLlk3kkUe(ijPEVpFpIejc, xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\xe6\xba\xb2S\xa2\x14\xa6Z\x0c\xcd\xb7'), chr(0b100100 + 0o100) + chr(101) + chr(0b1100011) + '\x6f' + chr(100) + chr(2960 - 2859))(chr(117) + chr(0b1110100) + chr(0b1010110 + 0o20) + chr(45) + chr(56)))[ehT0Px3KOsy9(chr(48) + chr(11889 - 11778) + chr(0b110000), 8)]
assert xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\xff\xf6\x8fo\x97\x16\x8bc)\xd6\x8c'), chr(4974 - 4874) + chr(5149 - 5048) + chr(99) + chr(111) + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + '\164' + '\x66' + '\055' + chr(711 - 655))) == xafqLlk3kkUe(WCl6VUkME_8I, xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\xe6\xba\xb2S\xa2\x14\xa6Z\x0c\xcd\xb7'), '\144' + chr(4974 - 4873) + chr(0b1100011) + '\x6f' + chr(5831 - 5731) + '\x65')('\x75' + '\164' + chr(0b1010010 + 0o24) + chr(625 - 580) + chr(0b111000)))[ehT0Px3KOsy9('\x30' + '\x6f' + '\x30', 8)]
for XdowRbJKZWL9 in vQr8gNKaIaWE(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\xff\xf6\x8fo\x97\x16\x8bc)\xd6\x8c'), chr(6734 - 6634) + chr(7868 - 7767) + chr(99) + chr(111) + chr(100) + chr(101))(chr(3504 - 3387) + '\164' + chr(0b1100110) + chr(1112 - 1067) + chr(982 - 926)))):
Mzq2fr56UhXf = oVre8I6UXc3b.V73mUfYH1QkS[XdowRbJKZWL9]
assert xafqLlk3kkUe(Mzq2fr56UhXf, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\xf4\x90\x8aV\x9a\x1a\xbck'), chr(0b1100100) + chr(0b1100010 + 0o3) + '\x63' + chr(5739 - 5628) + '\x64' + '\145')(chr(4043 - 3926) + chr(116) + chr(0b1100110) + chr(0b10111 + 0o26) + chr(0b1000 + 0o60)))
xafqLlk3kkUe(Mzq2fr56UhXf, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe0\xef\xae\x85R\x8b,\xa6o\x0f\xda\x8aRZ.\xa9C0\xc5\xcc\x1a'), '\x64' + chr(0b11100 + 0o111) + '\143' + chr(0b1001100 + 0o43) + '\144' + chr(101))(chr(10188 - 10071) + chr(0b110000 + 0o104) + chr(0b110 + 0o140) + '\055' + chr(0b111000)))(action=WCl6VUkME_8I[XdowRbJKZWL9])
xafqLlk3kkUe(Mzq2fr56UhXf, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe2\xe3\xab\xb4A\x87\x1e\xafQ\x0f\xda\xb0V'), chr(100) + '\x65' + '\x63' + chr(0b1101111) + chr(9692 - 9592) + '\145')(chr(0b1110101) + '\164' + '\146' + chr(45) + chr(0b1000 + 0o60)))(observation=uswa0rn3Tb4L[XdowRbJKZWL9], done=ijPEVpFpIejc[XdowRbJKZWL9], raw_reward=Q6_1NAs64aKe[XdowRbJKZWL9], processed_reward=KmO4a71nY2SN[XdowRbJKZWL9])
if ijPEVpFpIejc[XdowRbJKZWL9]:
xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xdc\xe4\xa0\x86E\x82\x16\xbek#\xda\xa7GY&\xafh,\xc3\xd0'), chr(0b1000001 + 0o43) + chr(0b1100101) + chr(0b1100011) + chr(111) + '\144' + '\145')('\x75' + '\164' + chr(3875 - 3773) + '\055' + chr(56)))(Mzq2fr56UhXf, XdowRbJKZWL9)
assert not xafqLlk3kkUe(oVre8I6UXc3b._trajectories[XdowRbJKZWL9], xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\xf4\x90\x8aV\x9a\x1a\xbck'), chr(100) + chr(101) + chr(99) + '\157' + chr(0b1100100) + chr(101))(chr(0b111010 + 0o73) + chr(0b110101 + 0o77) + chr(9309 - 9207) + '\055' + chr(0b111000)))
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/trajectory.py
|
BatchTrajectory.num_time_steps
|
def num_time_steps(self):
"""Returns the number of time-steps in completed and incomplete trajectories."""
num_time_steps = sum(t.num_time_steps for t in self.trajectories)
return num_time_steps + self.num_completed_time_steps
|
python
|
def num_time_steps(self):
"""Returns the number of time-steps in completed and incomplete trajectories."""
num_time_steps = sum(t.num_time_steps for t in self.trajectories)
return num_time_steps + self.num_completed_time_steps
|
[
"def",
"num_time_steps",
"(",
"self",
")",
":",
"num_time_steps",
"=",
"sum",
"(",
"t",
".",
"num_time_steps",
"for",
"t",
"in",
"self",
".",
"trajectories",
")",
"return",
"num_time_steps",
"+",
"self",
".",
"num_completed_time_steps"
] |
Returns the number of time-steps in completed and incomplete trajectories.
|
[
"Returns",
"the",
"number",
"of",
"time",
"-",
"steps",
"in",
"completed",
"and",
"incomplete",
"trajectories",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/trajectory.py#L275-L279
|
train
|
Returns the number of time - steps in completed and incomplete trajectories.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(3742 - 3631) + chr(0b110001) + chr(0b11001 + 0o30) + chr(939 - 885), 28762 - 28754), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(111) + chr(1173 - 1122) + chr(49) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b101011 + 0o104) + chr(0b110111) + chr(0b110010), 0o10), ehT0Px3KOsy9('\060' + chr(8009 - 7898) + '\061' + chr(2526 - 2472) + chr(0b101001 + 0o16), 0o10), ehT0Px3KOsy9(chr(2027 - 1979) + chr(111) + chr(1690 - 1637) + '\067', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + '\x36' + '\067', 8), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b111110 + 0o61) + chr(711 - 660) + chr(0b101100 + 0o11) + chr(54), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110010) + chr(53) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(3430 - 3319) + chr(0b110011) + chr(0b10110 + 0o36) + chr(2539 - 2488), 0b1000), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\x6f' + '\x33' + '\x30' + '\x33', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + chr(0b110111) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(1880 - 1832) + chr(111) + chr(0b110011) + chr(0b100010 + 0o17) + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\x6f' + chr(0b110010) + chr(0b101000 + 0o11) + chr(0b11100 + 0o30), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + chr(54) + chr(0b110000), 21151 - 21143), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + '\x37' + chr(51), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2218 - 2167) + '\064' + '\x33', 8), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + chr(0b110110) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(1454 - 1406) + chr(0b1101111) + '\062' + chr(0b110000) + chr(1162 - 1114), ord("\x08")), ehT0Px3KOsy9(chr(1514 - 1466) + chr(4374 - 4263) + chr(0b100110 + 0o12), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b1101 + 0o44) + chr(55) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b11010 + 0o27) + '\x33' + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(48) + chr(3776 - 3665) + chr(1629 - 1579) + chr(52) + chr(1948 - 1898), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b101001 + 0o12) + chr(0b10001 + 0o46) + chr(48), 0b1000), ehT0Px3KOsy9(chr(240 - 192) + chr(111) + chr(0b110001) + '\x31' + chr(0b110101), 12411 - 12403), ehT0Px3KOsy9('\060' + '\157' + chr(540 - 491) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + '\x35' + chr(0b110101 + 0o1), 8), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\157' + chr(0b10 + 0o60) + chr(49) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(6259 - 6148) + '\062' + '\061' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b1100 + 0o47) + chr(0b101111 + 0o2), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110011) + chr(0b1111 + 0o41) + '\066', 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(111) + chr(1200 - 1150) + chr(51) + '\x32', 27226 - 27218), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + '\x31' + '\067', 0o10), ehT0Px3KOsy9(chr(1741 - 1693) + '\x6f' + chr(2193 - 2143) + chr(0b110000) + chr(54), 58057 - 58049), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100111 + 0o12) + chr(50) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + chr(0b10110 + 0o35) + '\x31', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011 + 0o0) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\157' + chr(2764 - 2709) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101011 + 0o11) + chr(0b10111 + 0o35), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(0b110011) + '\x36', 0o10), ehT0Px3KOsy9(chr(628 - 580) + chr(111) + '\x31' + '\x35' + chr(0b100110 + 0o14), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(5037 - 4926) + '\x35' + chr(0b110000 + 0o0), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'`'), '\x64' + chr(5728 - 5627) + '\143' + '\x6f' + chr(3779 - 3679) + '\145')(chr(0b1010001 + 0o44) + '\x74' + chr(0b1011001 + 0o15) + chr(0b101101) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ZzbSOhfzsUax(oVre8I6UXc3b):
ZzbSOhfzsUax = xkxBmo49x2An((YeT3l7JgTbWR.num_time_steps for YeT3l7JgTbWR in oVre8I6UXc3b.trajectories))
return ZzbSOhfzsUax + xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b' \xbcW(L\x18\x83\xde\x8f\xa6\x0e\xaa\xe8\xef\x8f\x8a\x9d\xe5_\x08)\xc7\x88>'), '\x64' + '\145' + chr(99) + chr(111) + chr(751 - 651) + chr(0b1010010 + 0o23))('\x75' + chr(0b1110100) + chr(102) + chr(0b101101) + chr(56)))
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/trajectory.py
|
BatchTrajectory.observations_np
|
def observations_np(self, boundary=20):
"""Pads the observations in all the trajectories and returns them.
Args:
boundary: integer, Observations will be padded to (n * boundary) + 1 where
n is an integer.
Returns:
a tuple(padded_observations, time_steps), with shapes:
padded_observations: (self.batch_size, n * boundary + 1) + OBS
time_steps: integer list of length = self.batch_size
"""
list_observations_np_ts = [t.observations_np for t in self.trajectories]
# Every element in `list_observations_np_ts` is shaped (t,) + OBS
OBS = list_observations_np_ts[0].shape[1:] # pylint: disable=invalid-name
num_time_steps = [t.num_time_steps for t in self.trajectories]
t_max = max(num_time_steps)
# t_max is rounded to the next multiple of `boundary`
boundary = int(boundary)
bucket_length = boundary * int(np.ceil(float(t_max) / boundary))
def padding_config(obs):
# We're padding the first axis only, since that is the time-step.
num_to_pad = bucket_length + 1 - obs.shape[0]
return [(0, num_to_pad)] + [(0, 0)] * len(OBS)
return np.stack([
np.pad(obs, padding_config(obs), "constant")
for obs in list_observations_np_ts]), num_time_steps
|
python
|
def observations_np(self, boundary=20):
"""Pads the observations in all the trajectories and returns them.
Args:
boundary: integer, Observations will be padded to (n * boundary) + 1 where
n is an integer.
Returns:
a tuple(padded_observations, time_steps), with shapes:
padded_observations: (self.batch_size, n * boundary + 1) + OBS
time_steps: integer list of length = self.batch_size
"""
list_observations_np_ts = [t.observations_np for t in self.trajectories]
# Every element in `list_observations_np_ts` is shaped (t,) + OBS
OBS = list_observations_np_ts[0].shape[1:] # pylint: disable=invalid-name
num_time_steps = [t.num_time_steps for t in self.trajectories]
t_max = max(num_time_steps)
# t_max is rounded to the next multiple of `boundary`
boundary = int(boundary)
bucket_length = boundary * int(np.ceil(float(t_max) / boundary))
def padding_config(obs):
# We're padding the first axis only, since that is the time-step.
num_to_pad = bucket_length + 1 - obs.shape[0]
return [(0, num_to_pad)] + [(0, 0)] * len(OBS)
return np.stack([
np.pad(obs, padding_config(obs), "constant")
for obs in list_observations_np_ts]), num_time_steps
|
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] |
Pads the observations in all the trajectories and returns them.
Args:
boundary: integer, Observations will be padded to (n * boundary) + 1 where
n is an integer.
Returns:
a tuple(padded_observations, time_steps), with shapes:
padded_observations: (self.batch_size, n * boundary + 1) + OBS
time_steps: integer list of length = self.batch_size
|
[
"Pads",
"the",
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"in",
"all",
"the",
"trajectories",
"and",
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/trajectory.py#L286-L315
|
train
|
Pads the observations in all the trajectories and returns them.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(6299 - 6188) + chr(0b110010) + chr(0b110100) + chr(0b10111 + 0o37), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(3159 - 3048) + '\063' + chr(827 - 775) + chr(2005 - 1950), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101000 + 0o7) + '\063' + chr(0b110111) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(0b10001 + 0o45) + '\067', 0b1000), ehT0Px3KOsy9('\x30' + chr(8406 - 8295) + chr(0b110101) + chr(0b100 + 0o56), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110011) + chr(0b110010) + chr(0b10111 + 0o31), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b11000 + 0o127) + chr(2216 - 2163) + chr(53), 0o10), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\x6f' + chr(1744 - 1693) + '\x36' + chr(0b10101 + 0o35), 0b1000), ehT0Px3KOsy9(chr(110 - 62) + '\x6f' + chr(2224 - 2174) + chr(2877 - 2823) + chr(1660 - 1606), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(0b110110), 0o10), ehT0Px3KOsy9('\x30' + chr(8069 - 7958) + chr(0b110010) + '\060' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(3330 - 3219) + '\x34', 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(0b110010) + '\x34', 24186 - 24178), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\062' + chr(50) + chr(0b101110 + 0o3), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\061' + '\064' + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1010010 + 0o35) + chr(0b10001 + 0o42) + chr(52 - 4) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b1101111) + '\x32' + chr(0b110011), 23944 - 23936), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + '\062' + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1039 - 990) + '\x35' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1001001 + 0o46) + chr(2172 - 2122) + '\062' + chr(105 - 51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001 + 0o0) + chr(0b110101) + '\x33', 53437 - 53429), ehT0Px3KOsy9('\x30' + chr(0b1000111 + 0o50) + chr(0b11101 + 0o24) + chr(0b110010), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10000 + 0o41) + '\x34' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(1870 - 1822) + chr(0b1101111) + chr(49) + chr(0b1110 + 0o43) + chr(54), 29934 - 29926), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + chr(966 - 917) + '\060', 49405 - 49397), ehT0Px3KOsy9(chr(414 - 366) + '\x6f' + chr(0b101011 + 0o6) + chr(0b10001 + 0o44) + '\x35', 8), ehT0Px3KOsy9(chr(1684 - 1636) + chr(0b1101111) + chr(234 - 184) + chr(0b101001 + 0o13) + chr(0b1111 + 0o44), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10110 + 0o34) + chr(312 - 259) + '\060', 0b1000), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b1101111) + chr(0b100110 + 0o13) + chr(53) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\x6f' + chr(2331 - 2280) + '\064' + chr(0b1010 + 0o52), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000001 + 0o56) + chr(50) + chr(1686 - 1637) + chr(0b10011 + 0o42), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + chr(2405 - 2354), 8), ehT0Px3KOsy9(chr(2296 - 2248) + chr(236 - 125) + chr(52) + chr(0b1001 + 0o56), 30659 - 30651), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b1101111) + '\062' + chr(1380 - 1327) + chr(1802 - 1753), 41248 - 41240), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + chr(0b110110), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + '\061' + chr(53), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b11110 + 0o121) + chr(843 - 792) + '\066' + chr(53), 0b1000), ehT0Px3KOsy9('\x30' + chr(6840 - 6729) + '\x32' + chr(51) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x33' + chr(0b101011 + 0o5) + chr(0b1101 + 0o47), 0b1000), ehT0Px3KOsy9(chr(1701 - 1653) + chr(2085 - 1974) + chr(0b110001) + '\061' + chr(52), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\157' + '\065' + '\060', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x88'), '\144' + chr(0b1011101 + 0o10) + '\x63' + chr(7501 - 7390) + chr(0b1100100) + chr(0b1100101))(chr(117) + '\x74' + chr(102) + chr(0b1111 + 0o36) + chr(0b1110 + 0o52)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def tNu156dvIXtJ(oVre8I6UXc3b, btzPOzjO3_Wq=ehT0Px3KOsy9(chr(48) + chr(0b1101111 + 0o0) + chr(1080 - 1030) + chr(0b110100), ord("\x08"))):
gQ6L_o4_th1L = [YeT3l7JgTbWR.observations_np for YeT3l7JgTbWR in oVre8I6UXc3b.trajectories]
BvIYG5xOkzfs = gQ6L_o4_th1L[ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b10111 + 0o31), 0o10)].nauYfLglTpcb[ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(111) + chr(282 - 233), 0o10):]
ZzbSOhfzsUax = [YeT3l7JgTbWR.num_time_steps for YeT3l7JgTbWR in oVre8I6UXc3b.trajectories]
bXFPk1sDAmDO = tsdjvlgh9gDP(ZzbSOhfzsUax)
btzPOzjO3_Wq = ehT0Px3KOsy9(btzPOzjO3_Wq)
srtJwWjdcntc = btzPOzjO3_Wq * ehT0Px3KOsy9(WqUC3KWvYVup.ceil(kkSX4ccExqw4(bXFPk1sDAmDO) / btzPOzjO3_Wq))
def Adf6rcZmHlbv(HUAx0lWcwxPP):
cPChzOCItNCx = srtJwWjdcntc + ehT0Px3KOsy9(chr(1755 - 1707) + chr(0b101001 + 0o106) + '\x31', 8) - HUAx0lWcwxPP.nauYfLglTpcb[ehT0Px3KOsy9('\x30' + chr(0b1010001 + 0o36) + chr(0b110000), 8)]
return [(ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\157' + chr(48), 8), cPChzOCItNCx)] + [(ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(111) + chr(48), 8), ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\x6f' + chr(0b100 + 0o54), 8))] * c2A0yzQpDQB3(BvIYG5xOkzfs)
return (xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd5\x93\x9d\xd4A'), chr(0b1100100) + chr(0b1100101) + chr(0b1100011) + chr(0b1101111) + '\x64' + chr(8149 - 8048))(chr(12264 - 12147) + chr(9936 - 9820) + '\146' + chr(45) + chr(0b111000)))([xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd6\x86\x98'), '\x64' + chr(101) + '\x63' + chr(0b1001010 + 0o45) + chr(2270 - 2170) + chr(101))(chr(0b1110101) + '\x74' + chr(0b1100110) + chr(1308 - 1263) + '\x38'))(HUAx0lWcwxPP, Adf6rcZmHlbv(HUAx0lWcwxPP), xafqLlk3kkUe(SXOLrMavuUCe(b'\xc5\x88\x92\xc4^\xb1C\x86'), chr(4492 - 4392) + '\145' + chr(7848 - 7749) + chr(0b1101111) + '\144' + '\x65')(chr(2353 - 2236) + '\x74' + chr(1085 - 983) + chr(0b101101) + '\x38')) for HUAx0lWcwxPP in gQ6L_o4_th1L]), ZzbSOhfzsUax)
|
tensorflow/tensor2tensor
|
tensor2tensor/data_generators/squad.py
|
_generate_examples
|
def _generate_examples(tmp_dir, dataset_split):
"""Generate squad examples.
Args:
tmp_dir: a string
dataset_split: problem.DatasetSplit.TRAIN or problem.DatasetSplit.EVAL
Yields:
dictionaries representing examples
"""
if dataset_split == problem.DatasetSplit.TRAIN:
file_name = _TRAINING_SET
else:
file_name = _DEV_SET
squad_file = generator_utils.maybe_download(tmp_dir,
file_name,
os.path.join(_URL, file_name))
with tf.gfile.GFile(squad_file, mode="r") as fp:
squad = json.load(fp)
version = squad["version"]
for article in squad["data"]:
if "title" in article:
title = article["title"].strip()
else:
title = "no title"
for paragraph in article["paragraphs"]:
context = paragraph["context"].strip()
for qa in paragraph["qas"]:
question = qa["question"].strip()
id_ = qa["id"]
answer_starts = [answer["answer_start"] for answer in qa["answers"]]
answers = [answer["text"].strip() for answer in qa["answers"]]
# Features currently used are "context", "question", and "answers".
# Others are extracted here for the ease of future expansions.
example = {
"version": version,
"title": title,
"context": context,
"question": question,
"id": id_,
"answer_starts": answer_starts,
"answers": answers,
"num_answers": len(answers),
"is_supervised": True,
}
yield example
|
python
|
def _generate_examples(tmp_dir, dataset_split):
"""Generate squad examples.
Args:
tmp_dir: a string
dataset_split: problem.DatasetSplit.TRAIN or problem.DatasetSplit.EVAL
Yields:
dictionaries representing examples
"""
if dataset_split == problem.DatasetSplit.TRAIN:
file_name = _TRAINING_SET
else:
file_name = _DEV_SET
squad_file = generator_utils.maybe_download(tmp_dir,
file_name,
os.path.join(_URL, file_name))
with tf.gfile.GFile(squad_file, mode="r") as fp:
squad = json.load(fp)
version = squad["version"]
for article in squad["data"]:
if "title" in article:
title = article["title"].strip()
else:
title = "no title"
for paragraph in article["paragraphs"]:
context = paragraph["context"].strip()
for qa in paragraph["qas"]:
question = qa["question"].strip()
id_ = qa["id"]
answer_starts = [answer["answer_start"] for answer in qa["answers"]]
answers = [answer["text"].strip() for answer in qa["answers"]]
# Features currently used are "context", "question", and "answers".
# Others are extracted here for the ease of future expansions.
example = {
"version": version,
"title": title,
"context": context,
"question": question,
"id": id_,
"answer_starts": answer_starts,
"answers": answers,
"num_answers": len(answers),
"is_supervised": True,
}
yield example
|
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] |
Generate squad examples.
Args:
tmp_dir: a string
dataset_split: problem.DatasetSplit.TRAIN or problem.DatasetSplit.EVAL
Yields:
dictionaries representing examples
|
[
"Generate",
"squad",
"examples",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/data_generators/squad.py#L39-L85
|
train
|
Generate squad examples.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(3691 - 3580) + chr(0b10111 + 0o33) + chr(51) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\x6f' + '\061' + '\x36' + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\x6f' + chr(0b111 + 0o53) + chr(52), 0o10), ehT0Px3KOsy9(chr(0b10100 + 0o34) + '\x6f' + chr(0b110001 + 0o1) + chr(2262 - 2213), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + chr(1584 - 1535) + '\063', 16316 - 16308), ehT0Px3KOsy9(chr(2264 - 2216) + chr(111) + '\x33' + '\066' + chr(0b11001 + 0o31), 1298 - 1290), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\157' + chr(2468 - 2418) + chr(742 - 692) + chr(0b110101), 47111 - 47103), ehT0Px3KOsy9('\x30' + chr(111) + '\x31' + chr(138 - 87) + chr(308 - 259), 52342 - 52334), ehT0Px3KOsy9(chr(48) + chr(0b1101000 + 0o7) + '\063' + chr(0b100 + 0o62) + '\x36', 0o10), ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\157' + chr(2348 - 2298) + chr(0b110101 + 0o2) + '\x35', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31' + chr(48) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b1101111) + '\063' + '\065' + chr(0b110010 + 0o1), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1011101 + 0o22) + '\x32' + '\x37' + '\x35', 8), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001) + '\067' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2426 - 2373) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(730 - 682) + chr(111) + '\x32' + chr(0b110100) + chr(0b110011), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x31' + '\060' + chr(51), 0o10), ehT0Px3KOsy9(chr(0b11011 + 0o25) + '\x6f' + chr(352 - 303) + chr(0b110100), 0b1000), ehT0Px3KOsy9('\x30' + chr(2259 - 2148) + '\x37' + '\x33', 34339 - 34331), ehT0Px3KOsy9(chr(2132 - 2084) + chr(111) + '\x33' + '\065' + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(2100 - 2049) + chr(49), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2153 - 2103) + chr(1542 - 1493) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(1930 - 1882) + chr(0b1101111) + chr(92 - 38) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(161 - 113) + '\x6f' + chr(49) + chr(629 - 575) + '\x32', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(111 - 61) + chr(48) + chr(0b110010), 23194 - 23186), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061', 0b1000), ehT0Px3KOsy9('\060' + chr(1518 - 1407) + chr(1879 - 1830) + chr(55) + chr(50), 59170 - 59162), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(111) + chr(0b110101) + chr(0b110010), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101001 + 0o11) + '\064' + '\066', 24678 - 24670), ehT0Px3KOsy9(chr(2140 - 2092) + '\157' + chr(0b110100) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(0b100110 + 0o12) + '\x6f' + chr(0b110010) + '\067' + chr(0b1 + 0o61), ord("\x08")), ehT0Px3KOsy9(chr(115 - 67) + chr(0b1101111) + '\061' + '\067' + chr(50), 8), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\157' + chr(0b110011) + chr(311 - 258) + '\065', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(935 - 881) + chr(53), 46080 - 46072), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110101) + chr(0b100110 + 0o21), 0b1000), ehT0Px3KOsy9(chr(48) + chr(3741 - 3630) + chr(0b110011) + chr(0b11100 + 0o30) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + '\064' + chr(0b10011 + 0o35), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + chr(0b10111 + 0o40) + chr(2619 - 2566), 8), ehT0Px3KOsy9(chr(2238 - 2190) + chr(0b1101111) + '\061' + chr(0b100011 + 0o16) + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(2172 - 2121) + '\063' + chr(2275 - 2223), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(514 - 466) + chr(0b110000 + 0o77) + '\x35' + chr(0b100101 + 0o13), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb5'), chr(0b101001 + 0o73) + chr(0b1100101) + '\143' + '\x6f' + '\x64' + '\x65')('\165' + chr(7918 - 7802) + chr(0b1100110) + chr(834 - 789) + chr(254 - 198)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def vuyp4Fa36Fu7(JsZ36NJUqtml, XqbfPmad1kJ4):
if XqbfPmad1kJ4 == xafqLlk3kkUe(sO7e1A_Mor6Q.DatasetSplit, xafqLlk3kkUe(SXOLrMavuUCe(b'\xcf&UX\x85'), '\144' + chr(0b1100101) + '\x63' + chr(0b11101 + 0o122) + chr(0b1010010 + 0o22) + chr(5849 - 5748))(chr(117) + chr(1437 - 1321) + chr(3777 - 3675) + chr(45) + chr(0b110010 + 0o6))):
OK327sCYstzB = A1RpQri_RHJ7
else:
OK327sCYstzB = DOQGNt3XvNGw
DpzOArsfpsbp = g1Z_RG9zP4cD.maybe_download(JsZ36NJUqtml, OK327sCYstzB, oqhJDdMJfuwx.path.join(pCCmpnhZPmGO, OK327sCYstzB))
with xafqLlk3kkUe(IDJ2eXGCBCDu.gfile, xafqLlk3kkUe(SXOLrMavuUCe(b'\xdc2}}\xae'), chr(100) + '\145' + chr(99) + chr(5902 - 5791) + chr(0b1100100) + chr(101))(chr(0b1110101) + chr(0b110101 + 0o77) + '\x66' + chr(0b1001 + 0o44) + chr(56)))(DpzOArsfpsbp, mode=xafqLlk3kkUe(SXOLrMavuUCe(b'\xe9'), chr(100) + chr(0b101000 + 0o75) + '\x63' + chr(9906 - 9795) + chr(100) + chr(0b111000 + 0o55))(chr(2513 - 2396) + chr(0b1110100) + chr(0b1100110) + chr(45) + chr(0b101100 + 0o14))) as ey_P6rjw_s2D:
U20UoAGPPwFY = fXk443epxtd5.mxtdQMeiwJZJ(ey_P6rjw_s2D)
cpMfQ_4_Vb7C = U20UoAGPPwFY[xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\x11fb\xa2\x9d\xfb'), chr(7291 - 7191) + chr(0b1100101) + '\x63' + '\x6f' + chr(0b1100100) + chr(0b1100101))(chr(0b110111 + 0o76) + chr(1864 - 1748) + chr(102) + '\055' + chr(56))]
for YIr4_u7dR3ET in U20UoAGPPwFY[xafqLlk3kkUe(SXOLrMavuUCe(b'\xff\x15`p'), chr(100) + chr(2199 - 2098) + chr(0b1011110 + 0o5) + '\x6f' + chr(100) + chr(101))(chr(0b1110101) + chr(116) + chr(493 - 391) + '\x2d' + chr(0b0 + 0o70))]:
if xafqLlk3kkUe(SXOLrMavuUCe(b'\xef\x1d`}\xae'), chr(1589 - 1489) + chr(0b1100101) + chr(0b1100011) + chr(0b111 + 0o150) + chr(0b1100100) + chr(0b11001 + 0o114))(chr(117) + chr(0b1110100) + chr(0b1011 + 0o133) + '\055' + chr(2505 - 2449)) in YIr4_u7dR3ET:
IkttdaI0bGlA = YIr4_u7dR3ET[xafqLlk3kkUe(SXOLrMavuUCe(b'\xef\x1d`}\xae'), chr(3898 - 3798) + '\x65' + chr(1522 - 1423) + chr(111) + chr(0b10000 + 0o124) + chr(7066 - 6965))(chr(0b1001000 + 0o55) + '\x74' + chr(102) + chr(0b101001 + 0o4) + chr(0b100111 + 0o21))].strip()
else:
IkttdaI0bGlA = xafqLlk3kkUe(SXOLrMavuUCe(b'\xf5\x1b4e\xa2\x86\xf9<'), '\x64' + chr(6168 - 6067) + chr(0b1100011) + chr(0b11100 + 0o123) + '\x64' + chr(6283 - 6182))(chr(117) + '\164' + '\146' + chr(45) + chr(0b111000))
for jxbOO5ZYnxlv in YIr4_u7dR3ET[xafqLlk3kkUe(SXOLrMavuUCe(b'\xeb\x15fp\xac\x80\xf4)\x9e\xce'), chr(6270 - 6170) + '\x65' + '\143' + chr(0b1101111) + chr(0b11111 + 0o105) + chr(0b1100101))(chr(0b1110101) + chr(0b1101101 + 0o7) + chr(0b1100110) + chr(0b10 + 0o53) + chr(79 - 23))]:
vUUG4_3aIqQC = jxbOO5ZYnxlv[xafqLlk3kkUe(SXOLrMavuUCe(b'\xf8\x1bze\xae\x8a\xe1'), '\144' + chr(0b1100100 + 0o1) + '\143' + chr(111) + chr(100) + chr(101))(chr(0b1110010 + 0o3) + chr(10334 - 10218) + '\x66' + '\055' + chr(0b111000))].strip()
for PMhIzKJKl2fC in jxbOO5ZYnxlv[xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\x15g'), chr(100) + '\x65' + chr(99) + chr(4802 - 4691) + chr(0b0 + 0o144) + chr(776 - 675))('\165' + chr(0b11111 + 0o125) + '\x66' + chr(0b101101) + chr(56))]:
hiLkQHDHvP4B = PMhIzKJKl2fC[xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\x01qb\xbf\x9b\xfa7'), '\x64' + chr(101) + '\x63' + '\x6f' + chr(0b110110 + 0o56) + chr(0b1100101))(chr(117) + chr(3876 - 3760) + '\x66' + '\055' + chr(771 - 715))].strip()
_98QPWqqNw9m = PMhIzKJKl2fC[xafqLlk3kkUe(SXOLrMavuUCe(b'\xf2\x10'), chr(100) + chr(0b1011010 + 0o13) + '\x63' + chr(0b11111 + 0o120) + '\144' + '\x65')('\x75' + chr(5221 - 5105) + chr(0b1100000 + 0o6) + chr(45) + chr(56))]
EhdugViOsCbC = [_aygkdacRfLD[xafqLlk3kkUe(SXOLrMavuUCe(b'\xfa\x1agf\xae\x80\xca*\x82\xdc2\x9f'), '\x64' + chr(864 - 763) + '\143' + chr(111) + chr(0b1100001 + 0o3) + '\x65')(chr(5411 - 5294) + chr(12409 - 12293) + chr(102) + chr(45) + '\x38')] for _aygkdacRfLD in PMhIzKJKl2fC[xafqLlk3kkUe(SXOLrMavuUCe(b'\xfa\x1agf\xae\x80\xe6'), '\x64' + chr(0b1010010 + 0o23) + chr(7303 - 7204) + chr(0b110010 + 0o75) + '\x64' + chr(3868 - 3767))(chr(0b1101010 + 0o13) + chr(13339 - 13223) + chr(102) + chr(45) + chr(0b100000 + 0o30))]]
ldl8JNHMLV3H = [_aygkdacRfLD[xafqLlk3kkUe(SXOLrMavuUCe(b'\xef\x11le'), chr(0b1100100) + chr(0b100001 + 0o104) + chr(0b1100011) + chr(111) + chr(100) + '\145')(chr(2968 - 2851) + '\x74' + chr(102) + chr(0b101101) + '\070')].strip() for _aygkdacRfLD in PMhIzKJKl2fC[xafqLlk3kkUe(SXOLrMavuUCe(b'\xfa\x1agf\xae\x80\xe6'), chr(0b1001100 + 0o30) + '\145' + chr(0b110110 + 0o55) + chr(0b110111 + 0o70) + chr(100) + chr(101))(chr(2453 - 2336) + chr(116) + '\x66' + chr(0b10000 + 0o35) + '\070')]]
kP4qaKv0ZkGv = {xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\x11fb\xa2\x9d\xfb'), chr(100) + '\x65' + chr(232 - 133) + chr(111) + chr(100) + '\145')(chr(0b1110101) + chr(10529 - 10413) + '\x66' + chr(45) + '\x38'): cpMfQ_4_Vb7C, xafqLlk3kkUe(SXOLrMavuUCe(b'\xef\x1d`}\xae'), '\144' + '\145' + '\x63' + chr(111) + chr(0b1100100) + chr(2168 - 2067))(chr(2546 - 2429) + '\x74' + chr(0b1100110) + chr(0b1011 + 0o42) + '\x38'): IkttdaI0bGlA, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf8\x1bze\xae\x8a\xe1'), chr(0b111 + 0o135) + '\145' + chr(99) + chr(111) + chr(0b1101 + 0o127) + '\145')('\165' + '\x74' + '\146' + chr(0b101101) + chr(0b101010 + 0o16)): vUUG4_3aIqQC, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\x01qb\xbf\x9b\xfa7'), chr(100) + chr(2774 - 2673) + chr(99) + '\157' + chr(100) + '\145')('\x75' + '\164' + chr(102) + '\x2d' + chr(2193 - 2137)): hiLkQHDHvP4B, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf2\x10'), chr(0b1011101 + 0o7) + '\x65' + chr(3525 - 3426) + '\x6f' + '\144' + chr(0b1100101))(chr(0b1110101) + '\164' + chr(0b110010 + 0o64) + chr(45) + chr(56)): _98QPWqqNw9m, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfa\x1agf\xae\x80\xca*\x82\xdc2\x9f\xce'), chr(0b11001 + 0o113) + '\x65' + chr(0b1011000 + 0o13) + chr(111) + '\x64' + chr(0b11001 + 0o114))(chr(0b1110010 + 0o3) + chr(116) + '\x66' + chr(539 - 494) + chr(718 - 662)): EhdugViOsCbC, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfa\x1agf\xae\x80\xe6'), chr(7083 - 6983) + chr(101) + '\x63' + '\x6f' + chr(100) + chr(0b1100101))(chr(0b1110101) + chr(0b100110 + 0o116) + '\146' + '\055' + '\x38'): ldl8JNHMLV3H, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf5\x01yN\xaa\x9c\xe6.\x93\xcf3'), chr(0b111000 + 0o54) + chr(101) + chr(0b1010010 + 0o21) + '\x6f' + '\x64' + '\145')(chr(0b1110101) + chr(116) + '\x66' + chr(0b101101) + '\070'): c2A0yzQpDQB3(ldl8JNHMLV3H), xafqLlk3kkUe(SXOLrMavuUCe(b'\xf2\x07Kb\xbe\x82\xf0+\x80\xd43\x8e\xd9'), chr(0b1100 + 0o130) + chr(3641 - 3540) + chr(99) + chr(0b11100 + 0o123) + '\x64' + chr(0b101010 + 0o73))('\165' + '\164' + chr(2278 - 2176) + chr(0b10010 + 0o33) + chr(0b1 + 0o67)): ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061', 8)}
yield kP4qaKv0ZkGv
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tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_transformer2.py
|
self_attention_layer
|
def self_attention_layer(hparams, prefix):
"""Create self-attention layer based on hyperparameters."""
return transformer_layers.SelfAttention(
num_heads=hparams.get(prefix + "num_heads"),
num_memory_heads=hparams.get(prefix + "num_memory_heads"),
key_value_size=hparams.d_kv,
shared_kv=hparams.get(prefix + "shared_kv", False),
attention_kwargs=attention_kwargs_from_hparams(hparams))
|
python
|
def self_attention_layer(hparams, prefix):
"""Create self-attention layer based on hyperparameters."""
return transformer_layers.SelfAttention(
num_heads=hparams.get(prefix + "num_heads"),
num_memory_heads=hparams.get(prefix + "num_memory_heads"),
key_value_size=hparams.d_kv,
shared_kv=hparams.get(prefix + "shared_kv", False),
attention_kwargs=attention_kwargs_from_hparams(hparams))
|
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] |
Create self-attention layer based on hyperparameters.
|
[
"Create",
"self",
"-",
"attention",
"layer",
"based",
"on",
"hyperparameters",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_transformer2.py#L311-L318
|
train
|
Create self - attention layer based on hyperparameters.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(3763 - 3652) + chr(0b110110) + chr(0b101101 + 0o6), 36955 - 36947), ehT0Px3KOsy9('\x30' + chr(8143 - 8032) + chr(0b100 + 0o55) + chr(49) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1100110 + 0o11) + chr(1152 - 1099) + chr(766 - 718), ord("\x08")), ehT0Px3KOsy9(chr(147 - 99) + chr(111) + chr(0b100001 + 0o20) + '\x37' + chr(803 - 750), 65196 - 65188), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(0b1011101 + 0o22) + chr(0b110100) + chr(54), 0b1000), ehT0Px3KOsy9('\060' + chr(2649 - 2538) + chr(0b10101 + 0o37) + chr(0b100110 + 0o14), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061' + chr(2758 - 2704), 21858 - 21850), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1001 + 0o146) + '\061' + '\x36' + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(52) + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2961 - 2906) + '\x37', 0o10), ehT0Px3KOsy9(chr(1728 - 1680) + chr(0b111111 + 0o60) + chr(0b101100 + 0o5) + chr(0b101011 + 0o6) + chr(0b110101), 0o10), ehT0Px3KOsy9('\x30' + chr(6529 - 6418) + '\063' + chr(1805 - 1755) + '\x35', 0b1000), ehT0Px3KOsy9('\060' + chr(0b110001 + 0o76) + chr(926 - 877) + chr(2252 - 2197) + '\065', 8), ehT0Px3KOsy9(chr(48) + chr(10816 - 10705) + '\x32' + '\066' + chr(1292 - 1244), 6282 - 6274), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + chr(55) + '\062', 55242 - 55234), ehT0Px3KOsy9(chr(48) + chr(9134 - 9023) + chr(2173 - 2124) + chr(0b11001 + 0o33) + chr(0b1110 + 0o50), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1011001 + 0o26) + chr(54) + '\061', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b11 + 0o57) + '\x30' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(0b10 + 0o64) + '\x32', 43356 - 43348), ehT0Px3KOsy9('\x30' + chr(232 - 121) + '\062' + chr(1505 - 1451) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1275 - 1225) + '\x30' + chr(49), 9687 - 9679), ehT0Px3KOsy9('\060' + chr(10603 - 10492) + '\063' + chr(0b0 + 0o61) + '\x32', 0b1000), ehT0Px3KOsy9(chr(1992 - 1944) + chr(111) + chr(566 - 516) + '\x31', 0o10), ehT0Px3KOsy9('\x30' + chr(3422 - 3311) + '\064' + '\x36', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000011 + 0o54) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b101000 + 0o107) + chr(1625 - 1575) + chr(2538 - 2483), 0o10), ehT0Px3KOsy9(chr(518 - 470) + chr(111) + chr(0b110101) + chr(0b110101), 37977 - 37969), ehT0Px3KOsy9('\060' + '\157' + chr(641 - 590) + '\063' + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\x6f' + chr(49) + chr(338 - 286) + chr(125 - 74), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1871 - 1822) + chr(0b110111) + chr(0b1000 + 0o51), 45352 - 45344), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110011) + chr(1593 - 1542) + '\061', 8), ehT0Px3KOsy9(chr(606 - 558) + '\x6f' + chr(51) + chr(0b101010 + 0o13), 41896 - 41888), ehT0Px3KOsy9(chr(0b100111 + 0o11) + '\157' + chr(0b110001) + '\x31' + chr(55), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b110010) + chr(0b110000 + 0o5) + '\x34', 0b1000), ehT0Px3KOsy9(chr(48) + chr(9820 - 9709) + '\061' + chr(0b10 + 0o65), 0o10), ehT0Px3KOsy9('\060' + chr(4482 - 4371) + chr(51) + chr(1419 - 1371) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1759 - 1710) + chr(0b11100 + 0o27) + '\x30', 0o10), ehT0Px3KOsy9(chr(48) + chr(1742 - 1631) + '\x33' + chr(0b100100 + 0o21) + '\x35', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + '\x31' + chr(50), 8), ehT0Px3KOsy9(chr(1756 - 1708) + '\157' + chr(0b110011) + '\x37' + '\062', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\157' + chr(1898 - 1845) + chr(48), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x1d'), chr(0b1100100) + chr(101) + '\143' + chr(7090 - 6979) + chr(7612 - 7512) + '\x65')(chr(0b10010 + 0o143) + chr(892 - 776) + chr(102) + chr(807 - 762) + chr(0b100100 + 0o24)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Agj99AbPOd_7(n4ljua2gi1Pr, K1Ha0XjJTAE7):
return xafqLlk3kkUe(Nyy0_cXxpJav, xafqLlk3kkUe(SXOLrMavuUCe(b'`.D\x1bgVz\x13KK$\xba\x13'), chr(6821 - 6721) + chr(2773 - 2672) + '\x63' + chr(9249 - 9138) + chr(1036 - 936) + chr(0b100 + 0o141))(chr(0b11 + 0o162) + chr(0b1110100) + '\146' + chr(0b11001 + 0o24) + '\x38'))(num_heads=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'T.\\'), chr(100) + chr(101) + '\x63' + chr(111) + chr(0b1100100) + '\145')(chr(0b11110 + 0o127) + '\164' + chr(102) + '\x2d' + chr(0b111000)))(K1Ha0XjJTAE7 + xafqLlk3kkUe(SXOLrMavuUCe(b']>E"NGo\x12V'), '\144' + chr(0b1100101) + chr(0b1101 + 0o126) + '\x6f' + chr(2399 - 2299) + '\x65')('\165' + '\164' + chr(102) + '\x2d' + chr(0b111000))), num_memory_heads=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'T.\\'), chr(0b1100100) + '\x65' + '\x63' + chr(111) + chr(0b1100100) + chr(0b1100101))('\x75' + chr(0b10111 + 0o135) + '\146' + '\055' + chr(56)))(K1Ha0XjJTAE7 + xafqLlk3kkUe(SXOLrMavuUCe(b']>E"KGc\x19WF\x12\xbd\x18\xd1\x1e\x15'), '\144' + '\145' + '\x63' + chr(111) + '\x64' + '\x65')('\165' + '\x74' + chr(102) + chr(0b101101) + chr(56))), key_value_size=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'P)G7^Xz\x1dRX#\x83'), chr(6406 - 6306) + chr(9235 - 9134) + '\143' + chr(111) + chr(0b1100100) + '\x65')('\x75' + '\x74' + chr(5820 - 5718) + '\055' + chr(0b111000))), shared_kv=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'T.\\'), chr(100) + chr(0b1100101) + '\x63' + chr(0b1101111) + chr(0b11001 + 0o113) + chr(0b1100101))('\165' + chr(13242 - 13126) + chr(0b10 + 0o144) + '\x2d' + chr(56)))(K1Ha0XjJTAE7 + xafqLlk3kkUe(SXOLrMavuUCe(b'@#I\x0fCFQ\x1dS'), chr(0b1100100) + chr(0b11100 + 0o111) + chr(0b1100011) + chr(288 - 177) + chr(2969 - 2869) + chr(0b1011101 + 0o10))(chr(117) + chr(0b100101 + 0o117) + chr(0b100011 + 0o103) + chr(0b11111 + 0o16) + chr(0b111000)), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1329 - 1281), ord("\x08"))), attention_kwargs=CDrQxkZfqkTj(n4ljua2gi1Pr))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_transformer2.py
|
local_self_attention_layer
|
def local_self_attention_layer(hparams, prefix):
"""Create self-attention layer based on hyperparameters."""
return transformer_layers.LocalSelfAttention(
num_heads=hparams.get(prefix + "num_heads"),
num_memory_heads=hparams.get(prefix + "num_memory_heads"),
radius=hparams.local_attention_radius,
key_value_size=hparams.d_kv,
shared_kv=hparams.get(prefix + "shared_kv", False),
attention_kwargs=attention_kwargs_from_hparams(hparams))
|
python
|
def local_self_attention_layer(hparams, prefix):
"""Create self-attention layer based on hyperparameters."""
return transformer_layers.LocalSelfAttention(
num_heads=hparams.get(prefix + "num_heads"),
num_memory_heads=hparams.get(prefix + "num_memory_heads"),
radius=hparams.local_attention_radius,
key_value_size=hparams.d_kv,
shared_kv=hparams.get(prefix + "shared_kv", False),
attention_kwargs=attention_kwargs_from_hparams(hparams))
|
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] |
Create self-attention layer based on hyperparameters.
|
[
"Create",
"self",
"-",
"attention",
"layer",
"based",
"on",
"hyperparameters",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_transformer2.py#L322-L330
|
train
|
Create self - attention layer based on hyperparameters.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(7235 - 7124) + chr(54 - 5) + chr(0b10101 + 0o40) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1365 - 1314) + '\x31' + '\x31', 57783 - 57775), ehT0Px3KOsy9(chr(386 - 338) + '\x6f' + '\x31' + chr(0b110001), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1100000 + 0o17) + '\x31' + chr(815 - 760), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b101010 + 0o105) + '\062' + '\x37' + '\x34', 0o10), ehT0Px3KOsy9(chr(2194 - 2146) + '\157' + chr(0b100001 + 0o21) + chr(55) + chr(0b110001), 49038 - 49030), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(50) + '\067', 31181 - 31173), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(0b1101111) + chr(0b110001) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(0b110100 + 0o73) + chr(49) + chr(0b110101) + '\x33', 13363 - 13355), ehT0Px3KOsy9(chr(0b110000) + chr(0b111010 + 0o65) + chr(51) + chr(532 - 481) + chr(0b110010), 61138 - 61130), ehT0Px3KOsy9('\060' + chr(3193 - 3082) + chr(50) + chr(0b1 + 0o64) + '\x33', 0o10), ehT0Px3KOsy9('\060' + chr(5162 - 5051) + chr(0b110011) + chr(0b100110 + 0o16) + chr(0b10000 + 0o43), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(2332 - 2282) + chr(0b110011) + '\x32', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b11100 + 0o25) + '\064' + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\157' + '\063' + '\064' + chr(49), 0o10), ehT0Px3KOsy9(chr(571 - 523) + chr(0b111101 + 0o62) + chr(1105 - 1055) + chr(55) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\x30' + chr(7791 - 7680) + chr(1110 - 1060) + '\x37' + chr(0b101011 + 0o5), 0o10), ehT0Px3KOsy9('\060' + chr(0b10011 + 0o134) + chr(0b110001) + chr(0b101110 + 0o5) + '\066', 0o10), ehT0Px3KOsy9(chr(383 - 335) + chr(0b110000 + 0o77) + chr(49) + chr(0b10111 + 0o31), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + chr(400 - 349) + chr(0b101100 + 0o7), 4788 - 4780), ehT0Px3KOsy9(chr(0b10011 + 0o35) + '\x6f' + chr(0b10110 + 0o33) + '\x33' + chr(0b110110), 8), ehT0Px3KOsy9('\x30' + '\157' + chr(1091 - 1042) + '\061' + '\061', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + '\060', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110 + 0o54) + chr(52) + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + chr(2081 - 1970) + '\x32' + '\x36' + chr(0b100100 + 0o22), 0b1000), ehT0Px3KOsy9('\060' + chr(10107 - 9996) + '\062' + chr(0b110001) + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b101101 + 0o102) + '\x31' + chr(2389 - 2336) + '\x33', 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + chr(0b100001 + 0o26) + chr(1601 - 1552), 8), ehT0Px3KOsy9('\060' + '\157' + '\x32' + '\x34' + chr(2222 - 2167), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(49) + chr(0b11111 + 0o25) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(3992 - 3881) + '\x33' + chr(0b110011) + chr(0b100110 + 0o16), 0o10), ehT0Px3KOsy9('\060' + chr(8273 - 8162) + chr(50) + chr(0b110100 + 0o2) + chr(604 - 552), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(49) + '\060' + chr(0b100000 + 0o22), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + chr(51) + '\064', 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + chr(51) + '\064', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b101011 + 0o10) + '\x32' + chr(54), 64281 - 64273), ehT0Px3KOsy9(chr(1188 - 1140) + '\157' + chr(0b110010) + chr(0b110000) + '\060', 64760 - 64752), ehT0Px3KOsy9('\060' + '\x6f' + chr(1306 - 1257) + '\x37' + '\x31', 15029 - 15021), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110101) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + chr(0b100101 + 0o15) + chr(0b101 + 0o62), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1046 - 993) + chr(0b110000), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'A'), chr(0b1001 + 0o133) + '\x65' + '\x63' + chr(0b1101111) + chr(1711 - 1611) + chr(0b1100101))('\x75' + chr(0b1110100) + chr(102) + '\055' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def QqzMuw1dPWb0(n4ljua2gi1Pr, K1Ha0XjJTAE7):
return xafqLlk3kkUe(Nyy0_cXxpJav, xafqLlk3kkUe(SXOLrMavuUCe(b'#\xa6jn\xd0\xea\xb2d\r\x9b\xdf\x97\xff\x08\x95\xd4\xd70'), chr(0b1100100) + '\x65' + chr(0b110100 + 0o57) + chr(0b110 + 0o151) + chr(100) + chr(0b1100101))(chr(0b1110101) + chr(0b10111 + 0o135) + chr(0b100 + 0o142) + chr(45) + chr(1780 - 1724)))(num_heads=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x08\xac}'), '\144' + '\x65' + '\x63' + chr(111) + '\144' + chr(0b1100101))('\x75' + chr(5855 - 5739) + chr(0b1100110) + '\055' + chr(1971 - 1915)))(K1Ha0XjJTAE7 + xafqLlk3kkUe(SXOLrMavuUCe(b'\x01\xbcdP\xd4\xdc\xb6l\x18'), '\x64' + '\x65' + chr(0b1100011) + chr(6022 - 5911) + chr(100) + chr(101))('\165' + chr(116) + chr(0b1100110) + chr(1122 - 1077) + chr(0b10101 + 0o43))), num_memory_heads=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x08\xac}'), chr(8243 - 8143) + chr(0b1100101) + chr(0b1100011) + chr(10972 - 10861) + chr(0b1100100) + chr(7050 - 6949))('\x75' + chr(12230 - 12114) + '\x66' + chr(0b101101) + chr(0b111000)))(K1Ha0XjJTAE7 + xafqLlk3kkUe(SXOLrMavuUCe(b'\x01\xbcdP\xd1\xdc\xbag\x19\xa3\xf4\x8b\xff\x07\x85\xce'), chr(0b1100100) + chr(0b1100101) + chr(0b1100011) + chr(111) + '\x64' + '\145')(chr(3817 - 3700) + chr(7892 - 7776) + '\146' + chr(0b101101) + '\070')), radius=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x03\xa6jn\xd0\xe6\xb6|\x1f\xbf\xc5\x97\xf3\t\x8f\xe2\xca?l\xf2+:'), chr(0b101100 + 0o70) + '\x65' + chr(0b1011100 + 0o7) + chr(0b1101111) + chr(0b1100100) + '\x65')(chr(117) + chr(116) + '\146' + chr(0b101001 + 0o4) + chr(56))), key_value_size=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0c\xabfE\xc4\xc3\xa3c\x1c\xbd\xc5\xb5'), chr(100) + chr(9703 - 9602) + '\143' + '\157' + chr(100) + chr(0b1100101))('\x75' + chr(0b1110100) + chr(0b10011 + 0o123) + chr(0b101101) + chr(0b110110 + 0o2))), shared_kv=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x08\xac}'), chr(100) + chr(0b1100101) + chr(1595 - 1496) + '\x6f' + chr(8882 - 8782) + chr(7119 - 7018))(chr(0b111100 + 0o71) + chr(116) + chr(10373 - 10271) + chr(1443 - 1398) + '\070'))(K1Ha0XjJTAE7 + xafqLlk3kkUe(SXOLrMavuUCe(b'\x1c\xa1h}\xd9\xdd\x88c\x1d'), chr(5169 - 5069) + '\x65' + chr(99) + chr(8726 - 8615) + chr(7421 - 7321) + chr(0b100100 + 0o101))(chr(13604 - 13487) + chr(581 - 465) + chr(102) + chr(1003 - 958) + '\x38'), ehT0Px3KOsy9(chr(2222 - 2174) + chr(111) + chr(873 - 825), ord("\x08"))), attention_kwargs=CDrQxkZfqkTj(n4ljua2gi1Pr))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_transformer2.py
|
layer_stack_from_hparams
|
def layer_stack_from_hparams(hparams, prefix):
"""Create a layer stack based on the hyperparameter values."""
layers = hparams.get(prefix + "layers")
return transformer.LayerStack(
[layers_registry[l](hparams, prefix) for l in layers],
dropout_rate=hparams.layer_prepostprocess_dropout,
norm_epsilon=hparams.norm_epsilon)
|
python
|
def layer_stack_from_hparams(hparams, prefix):
"""Create a layer stack based on the hyperparameter values."""
layers = hparams.get(prefix + "layers")
return transformer.LayerStack(
[layers_registry[l](hparams, prefix) for l in layers],
dropout_rate=hparams.layer_prepostprocess_dropout,
norm_epsilon=hparams.norm_epsilon)
|
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Create a layer stack based on the hyperparameter values.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_transformer2.py#L366-L372
|
train
|
Create a layer stack based on the hyperparameter values.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1211 - 1163) + chr(0b1101111) + chr(0b100001 + 0o26) + chr(1520 - 1469), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\063' + chr(0b1111 + 0o50) + '\062', 51361 - 51353), ehT0Px3KOsy9(chr(1154 - 1106) + chr(0b1000011 + 0o54) + '\x34', 29907 - 29899), ehT0Px3KOsy9(chr(48) + chr(2593 - 2482) + '\063' + '\060' + chr(0b10000 + 0o42), 36084 - 36076), ehT0Px3KOsy9('\x30' + chr(1554 - 1443) + chr(0b1001 + 0o51) + '\065' + chr(0b11001 + 0o31), 0b1000), ehT0Px3KOsy9(chr(287 - 239) + chr(111) + '\x32' + '\065' + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(0b110011) + chr(0b110110), 12621 - 12613), ehT0Px3KOsy9('\060' + chr(0b110011 + 0o74) + chr(49) + chr(50) + '\063', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1432 - 1382) + '\x35' + chr(2554 - 2502), ord("\x08")), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(4264 - 4153) + chr(0b11000 + 0o31) + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b10010 + 0o40) + '\063', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(50) + '\x31' + chr(0b1100 + 0o53), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + '\x30' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(0b1101 + 0o43), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100001 + 0o24), 11206 - 11198), ehT0Px3KOsy9(chr(932 - 884) + '\157' + '\063' + chr(0b101101 + 0o6) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1101111 + 0o0) + chr(2250 - 2199) + chr(0b100111 + 0o12) + '\063', 55912 - 55904), ehT0Px3KOsy9(chr(660 - 612) + chr(2856 - 2745) + chr(50) + '\x33' + chr(0b10 + 0o56), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + chr(49) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(703 - 655) + chr(0b1101111) + chr(1334 - 1284) + chr(1416 - 1362) + chr(2671 - 2617), 0o10), ehT0Px3KOsy9(chr(555 - 507) + chr(111) + chr(51) + '\x32' + chr(0b110100), 0b1000), ehT0Px3KOsy9('\060' + chr(0b101001 + 0o106) + '\066' + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(11441 - 11330) + chr(0b11010 + 0o30) + chr(0b110000) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\157' + '\063' + chr(0b100110 + 0o12) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(111) + '\x31' + chr(54) + chr(0b110 + 0o60), 28399 - 28391), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b111 + 0o53) + chr(1005 - 952) + '\x37', 8), ehT0Px3KOsy9(chr(122 - 74) + chr(0b1101111) + chr(0b11 + 0o57) + chr(1687 - 1636) + '\x35', 0o10), ehT0Px3KOsy9(chr(1892 - 1844) + chr(4023 - 3912) + chr(0b110100), 8), ehT0Px3KOsy9(chr(1304 - 1256) + '\157' + chr(2202 - 2150) + chr(0b110101), 37109 - 37101), ehT0Px3KOsy9('\060' + '\x6f' + chr(2084 - 2033) + '\x34', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b111011 + 0o64) + chr(0b110011) + '\067' + chr(0b110110), 50074 - 50066), ehT0Px3KOsy9(chr(1352 - 1304) + '\157' + chr(0b110000 + 0o1) + chr(0b110010) + chr(144 - 94), 48125 - 48117), ehT0Px3KOsy9('\060' + chr(2409 - 2298) + chr(610 - 561) + '\x32' + '\x35', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1010111 + 0o30) + chr(1241 - 1190) + chr(50) + chr(0b11001 + 0o35), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1000 + 0o147) + chr(50) + chr(49), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + '\x33' + chr(1866 - 1812), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + '\067' + '\x31', 14052 - 14044), ehT0Px3KOsy9(chr(1391 - 1343) + chr(491 - 380) + '\063' + chr(53) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(111) + chr(49) + chr(52), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b111 + 0o150) + '\x32' + chr(0b110111), 56681 - 56673)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b1010010 + 0o35) + chr(53) + '\x30', 18787 - 18779)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x15'), '\x64' + chr(2306 - 2205) + chr(0b101111 + 0o64) + chr(0b1000 + 0o147) + '\144' + chr(0b1101 + 0o130))(chr(0b1110101) + '\164' + chr(6671 - 6569) + chr(862 - 817) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ch6wPqKgLn_N(n4ljua2gi1Pr, K1Ha0XjJTAE7):
sGi5Aql23May = n4ljua2gi1Pr.get(K1Ha0XjJTAE7 + xafqLlk3kkUe(SXOLrMavuUCe(b'W\x9b}\xa7\xd8\xdc'), chr(100) + '\x65' + chr(99) + chr(0b1101111) + chr(7403 - 7303) + chr(4520 - 4419))('\x75' + chr(0b1110100) + '\146' + '\x2d' + chr(1010 - 954)))
return xafqLlk3kkUe(Nk9m9eKr4iuF, xafqLlk3kkUe(SXOLrMavuUCe(b'w\x9b}\xa7\xd8\xfc\xaa2\xcfc'), '\144' + chr(9482 - 9381) + chr(0b1000 + 0o133) + chr(4670 - 4559) + '\x64' + chr(0b1100101))('\165' + chr(0b111000 + 0o74) + chr(0b1100110) + chr(0b1001 + 0o44) + chr(0b111000)))([zYm7P0b2tVqk[aLoH_Mt0dzwO](n4ljua2gi1Pr, K1Ha0XjJTAE7) for aLoH_Mt0dzwO in sGi5Aql23May], dropout_rate=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'i\xad[\xba\xf9\xd5\xaeb\x94]v\xdc'), chr(0b110101 + 0o57) + chr(9670 - 9569) + '\143' + '\157' + '\144' + '\x65')('\x75' + chr(116) + chr(1725 - 1623) + '\x2d' + '\x38')), norm_epsilon=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'N\xc9V\xb1\x98\x9e\x99#\xd6f \xf8'), '\144' + chr(101) + chr(0b1000001 + 0o42) + chr(0b110000 + 0o77) + chr(1299 - 1199) + chr(101))(chr(0b1000100 + 0o61) + '\x74' + chr(0b1100110) + '\x2d' + chr(2018 - 1962))))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_transformer2.py
|
mtf_unitransformer_base
|
def mtf_unitransformer_base():
"""Hyperparameters for single-stack Transformer."""
hparams = mtf_transformer2_base()
hparams.add_hparam("autoregressive", True)
# HYPERPARAMETERS FOR THE SINGLE LAYER STACK
hparams.add_hparam("layers", ["self_att", "drd"] * 6)
# number of heads in multihead attention
hparams.add_hparam("num_heads", 8)
# default of 0 for standard transformer behavior
# 1 means a single set of keys and values that are read by all query heads
hparams.add_hparam("num_memory_heads", 0)
# share attention keys and values
hparams.add_hparam("shared_kv", False)
# if nonzero then use local attention
hparams.add_hparam("local_attention_radius", 128)
return hparams
|
python
|
def mtf_unitransformer_base():
"""Hyperparameters for single-stack Transformer."""
hparams = mtf_transformer2_base()
hparams.add_hparam("autoregressive", True)
# HYPERPARAMETERS FOR THE SINGLE LAYER STACK
hparams.add_hparam("layers", ["self_att", "drd"] * 6)
# number of heads in multihead attention
hparams.add_hparam("num_heads", 8)
# default of 0 for standard transformer behavior
# 1 means a single set of keys and values that are read by all query heads
hparams.add_hparam("num_memory_heads", 0)
# share attention keys and values
hparams.add_hparam("shared_kv", False)
# if nonzero then use local attention
hparams.add_hparam("local_attention_radius", 128)
return hparams
|
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] |
Hyperparameters for single-stack Transformer.
|
[
"Hyperparameters",
"for",
"single",
"-",
"stack",
"Transformer",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_transformer2.py#L454-L469
|
train
|
Hyperparameters for single - stack Transformer.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b1001010 + 0o45) + '\067' + chr(51), 10941 - 10933), ehT0Px3KOsy9('\060' + chr(3807 - 3696) + chr(51) + '\x32' + chr(0b110111), 21595 - 21587), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061' + '\x30' + '\x36', 33847 - 33839), ehT0Px3KOsy9('\x30' + chr(7258 - 7147) + '\061' + chr(0b10111 + 0o36) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1001111 + 0o40) + chr(50) + chr(0b110110) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b10011 + 0o134) + chr(1841 - 1791) + '\065' + chr(0b100001 + 0o20), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + '\063' + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(0b110111) + chr(0b0 + 0o61), ord("\x08")), ehT0Px3KOsy9(chr(2003 - 1955) + chr(111) + chr(52) + chr(0b100 + 0o63), 0o10), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(111) + '\x31' + chr(0b11010 + 0o27), ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\157' + '\x32' + chr(0b110111) + chr(0b110000), 61527 - 61519), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + '\x36' + chr(55), 8635 - 8627), ehT0Px3KOsy9(chr(0b110000) + chr(0b100010 + 0o115) + chr(0b110001) + '\x33' + chr(0b100000 + 0o20), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + '\x30' + '\x36', 35653 - 35645), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b0 + 0o63) + chr(53), 10167 - 10159), ehT0Px3KOsy9('\x30' + chr(111) + chr(1368 - 1317) + chr(0b110000) + chr(1162 - 1114), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b11010 + 0o27) + chr(50) + chr(55), 0o10), ehT0Px3KOsy9(chr(1228 - 1180) + chr(1023 - 912) + chr(51) + '\061' + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\x31' + chr(0b100010 + 0o17) + '\x31', 0o10), ehT0Px3KOsy9(chr(464 - 416) + chr(0b1101111) + chr(54) + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b10100 + 0o34) + '\x6f' + chr(0b101100 + 0o5) + chr(52) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(5539 - 5428) + chr(0b110010) + chr(0b110100), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\x32' + chr(52) + chr(0b10111 + 0o32), 0b1000), ehT0Px3KOsy9(chr(0b10110 + 0o32) + '\x6f' + chr(50) + chr(1849 - 1797) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b100001 + 0o21) + chr(2670 - 2615) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(1248 - 1200) + chr(111) + chr(2094 - 2044) + chr(0b110001), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(876 - 828) + '\060', 61519 - 61511), ehT0Px3KOsy9('\x30' + '\x6f' + chr(55) + chr(396 - 348), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + '\x30' + chr(50), 0o10), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(2483 - 2372) + chr(0b110010) + '\x35' + chr(1945 - 1896), 8), ehT0Px3KOsy9(chr(48) + chr(0b101100 + 0o103) + chr(1889 - 1840) + chr(54) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110011) + chr(0b111 + 0o53) + chr(54), 0b1000), ehT0Px3KOsy9(chr(177 - 129) + chr(0b1001011 + 0o44) + chr(50) + chr(54) + '\062', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + chr(0b110101) + chr(0b101110 + 0o3), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1418 - 1366), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(49) + chr(0b110001) + chr(0b10110 + 0o32), 0b1000), ehT0Px3KOsy9('\060' + chr(0b10111 + 0o130) + chr(0b100111 + 0o11), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(53 - 4) + chr(0b101 + 0o56) + chr(1503 - 1449), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\x31' + chr(0b110011) + '\x37', 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110101) + chr(48), 41142 - 41134)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x15'), '\144' + chr(101) + chr(0b110111 + 0o54) + chr(111) + chr(100) + chr(0b1100101))(chr(0b100100 + 0o121) + chr(7219 - 7103) + chr(0b10001 + 0o125) + '\x2d' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def UsJoV5NmWCXn():
n4ljua2gi1Pr = lVAQkjWu8JCV()
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'Z\xb3"1\xde\xd9>\xcbFd'), chr(100) + chr(0b1011010 + 0o13) + '\143' + chr(0b1001001 + 0o46) + chr(100) + chr(4624 - 4523))('\165' + '\164' + chr(344 - 242) + '\055' + chr(2987 - 2931)))(xafqLlk3kkUe(SXOLrMavuUCe(b'Z\xa22\x01\xc4\xcc8\xcbBz\xcb\xde.\xe3'), chr(5584 - 5484) + chr(101) + '\143' + chr(3039 - 2928) + chr(0b1100100) + chr(7551 - 7450))(chr(0b1110101) + chr(116) + '\146' + '\x2d' + chr(56)), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(49), 24286 - 24278))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'Z\xb3"1\xde\xd9>\xcbFd'), '\144' + chr(1723 - 1622) + chr(0b10010 + 0o121) + '\x6f' + chr(0b1100100) + '\145')('\165' + chr(0b1110100) + chr(3921 - 3819) + '\x2d' + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'W\xb6?\x0b\xc4\xda'), chr(3555 - 3455) + '\x65' + chr(0b1011101 + 0o6) + '\157' + chr(0b1100100) + '\x65')(chr(0b10010 + 0o143) + '\164' + chr(7323 - 7221) + '\x2d' + chr(56)), [xafqLlk3kkUe(SXOLrMavuUCe(b'H\xb2*\x08\xe9\xc8+\xcd'), '\x64' + chr(8036 - 7935) + '\143' + '\x6f' + chr(100) + chr(0b1100101))(chr(0b1110101) + '\164' + chr(0b1100110) + chr(1918 - 1873) + chr(941 - 885)), xafqLlk3kkUe(SXOLrMavuUCe(b'_\xa5"'), chr(0b1010100 + 0o20) + '\x65' + chr(99) + '\x6f' + '\144' + '\x65')('\x75' + chr(116) + chr(102) + chr(45) + '\x38')] * ehT0Px3KOsy9(chr(0b100010 + 0o16) + '\x6f' + chr(2522 - 2468), 0b1000))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'Z\xb3"1\xde\xd9>\xcbFd'), chr(0b1100100) + chr(101) + chr(0b1001010 + 0o31) + '\157' + chr(4740 - 4640) + '\145')('\165' + chr(116) + '\x66' + '\x2d' + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'U\xa2+1\xde\xcc>\xddT'), chr(2814 - 2714) + chr(9781 - 9680) + '\x63' + '\157' + chr(0b1100100) + chr(0b111100 + 0o51))(chr(0b111010 + 0o73) + chr(0b1110100) + chr(102) + chr(0b11 + 0o52) + '\070'), ehT0Px3KOsy9('\x30' + chr(0b11101 + 0o122) + chr(49) + chr(48), 0o10))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'Z\xb3"1\xde\xd9>\xcbFd'), '\x64' + '\145' + '\x63' + chr(0b1100101 + 0o12) + chr(0b1100100) + '\145')(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + chr(0b101010 + 0o3) + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'U\xa2+1\xdb\xcc2\xd6Up\xe7\xdf=\xe7y\xb3'), chr(0b1100100) + chr(0b1000011 + 0o42) + chr(7421 - 7322) + '\x6f' + chr(0b1100100) + chr(0b1100101))(chr(11473 - 11356) + chr(116) + chr(0b1100110) + '\x2d' + '\070'), ehT0Px3KOsy9(chr(222 - 174) + chr(0b1000100 + 0o53) + chr(1296 - 1248), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'Z\xb3"1\xde\xd9>\xcbFd'), chr(0b101000 + 0o74) + chr(101) + chr(0b1010001 + 0o22) + chr(111) + '\144' + chr(0b1010011 + 0o22))('\x75' + '\x74' + chr(102) + '\055' + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b"H\xbf'\x1c\xd3\xcd\x00\xd2Q"), chr(0b1100100) + '\145' + chr(0b1100011) + '\157' + chr(0b110100 + 0o60) + chr(2796 - 2695))(chr(117) + chr(0b101111 + 0o105) + '\146' + chr(266 - 221) + '\070'), ehT0Px3KOsy9('\060' + chr(0b110 + 0o151) + chr(48), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'Z\xb3"1\xde\xd9>\xcbFd'), chr(100) + chr(7237 - 7136) + chr(0b11100 + 0o107) + chr(111) + chr(0b111010 + 0o52) + chr(0b1100101))(chr(117) + chr(0b1110100) + '\146' + chr(0b10101 + 0o30) + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'W\xb8%\x0f\xda\xf6>\xcdSl\xd6\xc31\xe9s\x9f%\xae-^\x10g'), chr(100) + chr(9567 - 9466) + chr(99) + chr(0b111000 + 0o67) + '\x64' + chr(0b1100101))(chr(0b1011010 + 0o33) + chr(0b1100001 + 0o23) + '\x66' + chr(793 - 748) + chr(2548 - 2492)), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(48) + chr(0b1010 + 0o46), 8))
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_transformer2.py
|
mtf_bitransformer_base
|
def mtf_bitransformer_base():
"""Machine translation base configuration."""
hparams = mtf_transformer2_base()
hparams.max_length = 256
hparams.shared_embedding = True
# HYPERPARAMETERS FOR THE LAYER STACKS
hparams.add_hparam("encoder_layers", ["self_att", "drd"] * 6)
hparams.add_hparam("decoder_layers", ["self_att", "enc_att", "drd"] * 6)
hparams.add_hparam("encoder_num_layers", 6)
hparams.add_hparam("decoder_num_layers", 6)
# number of heads in multihead attention
hparams.add_hparam("encoder_num_heads", 8)
hparams.add_hparam("decoder_num_heads", 8)
hparams.add_hparam("local_attention_radius", 128)
# default of 0 for standard transformer behavior
# 1 means a single set of keys and values that are read by all query heads
hparams.add_hparam("encoder_num_memory_heads", 0)
hparams.add_hparam("decoder_num_memory_heads", 0)
# share attention keys and values
hparams.add_hparam("encoder_shared_kv", False)
hparams.add_hparam("decoder_shared_kv", False)
# Parameters for computing the maximum decode length in beam search.
# Maximum decode length is:
# min(max_length,
# decode_length_multiplier * input_length + decode_length_constant)
hparams.add_hparam("decode_length_multiplier", 1.5)
hparams.add_hparam("decode_length_constant", 10.0)
# used during decoding
hparams.add_hparam("alpha", 0.6)
hparams.sampling_temp = 0.0
return hparams
|
python
|
def mtf_bitransformer_base():
"""Machine translation base configuration."""
hparams = mtf_transformer2_base()
hparams.max_length = 256
hparams.shared_embedding = True
# HYPERPARAMETERS FOR THE LAYER STACKS
hparams.add_hparam("encoder_layers", ["self_att", "drd"] * 6)
hparams.add_hparam("decoder_layers", ["self_att", "enc_att", "drd"] * 6)
hparams.add_hparam("encoder_num_layers", 6)
hparams.add_hparam("decoder_num_layers", 6)
# number of heads in multihead attention
hparams.add_hparam("encoder_num_heads", 8)
hparams.add_hparam("decoder_num_heads", 8)
hparams.add_hparam("local_attention_radius", 128)
# default of 0 for standard transformer behavior
# 1 means a single set of keys and values that are read by all query heads
hparams.add_hparam("encoder_num_memory_heads", 0)
hparams.add_hparam("decoder_num_memory_heads", 0)
# share attention keys and values
hparams.add_hparam("encoder_shared_kv", False)
hparams.add_hparam("decoder_shared_kv", False)
# Parameters for computing the maximum decode length in beam search.
# Maximum decode length is:
# min(max_length,
# decode_length_multiplier * input_length + decode_length_constant)
hparams.add_hparam("decode_length_multiplier", 1.5)
hparams.add_hparam("decode_length_constant", 10.0)
# used during decoding
hparams.add_hparam("alpha", 0.6)
hparams.sampling_temp = 0.0
return hparams
|
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"\"encoder_shared_kv\"",
",",
"False",
")",
"hparams",
".",
"add_hparam",
"(",
"\"decoder_shared_kv\"",
",",
"False",
")",
"# Parameters for computing the maximum decode length in beam search.",
"# Maximum decode length is:",
"# min(max_length,",
"# decode_length_multiplier * input_length + decode_length_constant)",
"hparams",
".",
"add_hparam",
"(",
"\"decode_length_multiplier\"",
",",
"1.5",
")",
"hparams",
".",
"add_hparam",
"(",
"\"decode_length_constant\"",
",",
"10.0",
")",
"# used during decoding",
"hparams",
".",
"add_hparam",
"(",
"\"alpha\"",
",",
"0.6",
")",
"hparams",
".",
"sampling_temp",
"=",
"0.0",
"return",
"hparams"
] |
Machine translation base configuration.
|
[
"Machine",
"translation",
"base",
"configuration",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_transformer2.py#L473-L505
|
train
|
Machine translation base configuration.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1100 + 0o45) + chr(376 - 324) + chr(52), 0o10), ehT0Px3KOsy9(chr(1778 - 1730) + '\x6f' + '\x31' + chr(856 - 805) + chr(0b110100), 10817 - 10809), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + '\x34', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1000110 + 0o51) + '\061' + chr(49) + chr(53), 0o10), ehT0Px3KOsy9('\060' + chr(0b1011110 + 0o21) + '\x32' + '\060' + chr(0b110110), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b10111 + 0o40) + '\063', 0b1000), ehT0Px3KOsy9(chr(0b0 + 0o60) + '\x6f' + chr(944 - 894) + chr(0b11011 + 0o33) + chr(50), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x31' + chr(50) + chr(54), 13597 - 13589), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(111) + chr(288 - 239) + chr(0b110101) + '\064', 61304 - 61296), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001) + chr(913 - 860) + chr(48), 60312 - 60304), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + '\x32' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(93 - 41) + chr(0b110011), 64656 - 64648), ehT0Px3KOsy9('\060' + '\157' + chr(52) + chr(0b0 + 0o63), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b101 + 0o62) + chr(0b11110 + 0o26), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(0b1011011 + 0o24) + '\064' + chr(0b10010 + 0o43), 0o10), ehT0Px3KOsy9('\x30' + chr(8691 - 8580) + '\x36' + chr(0b110000), 64792 - 64784), ehT0Px3KOsy9(chr(0b110000) + chr(5811 - 5700) + '\063' + chr(1316 - 1267), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + '\x32' + chr(0b110 + 0o52), 0o10), ehT0Px3KOsy9('\x30' + chr(0b100010 + 0o115) + chr(1808 - 1759) + '\062' + chr(0b110010), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(922 - 872) + '\x34' + chr(2329 - 2274), 7274 - 7266), ehT0Px3KOsy9(chr(596 - 548) + '\157' + '\062' + chr(1729 - 1680) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b1101 + 0o44) + '\x35' + chr(2116 - 2061), 0b1000), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(3057 - 2946) + chr(0b11110 + 0o23) + chr(0b100110 + 0o16), 8), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b1101111) + chr(0b110011) + '\x31' + '\065', 23904 - 23896), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100010 + 0o17) + chr(1506 - 1452) + chr(53), 49282 - 49274), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + '\066' + chr(0b100101 + 0o21), 0o10), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(1605 - 1494) + chr(1295 - 1246) + chr(0b110001) + chr(48), 30959 - 30951), ehT0Px3KOsy9('\060' + '\157' + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + chr(51) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(541 - 493) + chr(0b1101111) + chr(0b101 + 0o55) + chr(1718 - 1665) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(9183 - 9072) + chr(0b110011) + chr(0b110110) + '\061', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + chr(0b110100), 8), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + chr(0b110010) + '\063' + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b11011 + 0o26) + chr(0b110000) + chr(0b110010), 50982 - 50974), ehT0Px3KOsy9(chr(0b10001 + 0o37) + '\157' + chr(51) + chr(52) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + chr(1434 - 1385) + chr(0b0 + 0o60), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + '\x31' + chr(49), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x33' + chr(1279 - 1229) + chr(0b11101 + 0o25), 0b1000), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(111) + '\061' + chr(0b110010) + '\x33', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\x6f' + '\x35' + chr(0b11001 + 0o27), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'J'), '\x64' + chr(0b1100101) + chr(99) + chr(7196 - 7085) + chr(100) + '\x65')('\165' + '\164' + chr(1453 - 1351) + chr(0b101101) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def N1wIS6c9nT6g():
n4ljua2gi1Pr = lVAQkjWu8JCV()
n4ljua2gi1Pr._o7pVXAdOCRy = ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x34' + chr(48) + '\060', 0b1000)
n4ljua2gi1Pr.f7bdxoAgzo_R = ehT0Px3KOsy9(chr(48) + chr(0b1100000 + 0o17) + chr(49), 8)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x058h\x12\xeeK\xd3$\r\x05'), chr(9191 - 9091) + '\x65' + chr(99) + chr(0b1000101 + 0o52) + chr(2164 - 2064) + chr(0b1100101))('\x75' + '\x74' + chr(1578 - 1476) + '\x2d' + chr(0b100000 + 0o30)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x012o"\xe2^\xc0\t\x00\t\xefFQO'), '\x64' + '\x65' + chr(1608 - 1509) + '\157' + chr(7230 - 7130) + '\145')('\165' + chr(116) + '\146' + '\x2d' + chr(3002 - 2946)), [xafqLlk3kkUe(SXOLrMavuUCe(b'\x179`+\xd9Z\xc6"'), chr(3506 - 3406) + chr(2059 - 1958) + chr(4959 - 4860) + chr(0b1101111) + chr(1458 - 1358) + '\145')('\165' + chr(0b10110 + 0o136) + chr(0b1100110) + chr(45) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x00.h'), chr(3271 - 3171) + chr(0b1100101) + chr(0b100111 + 0o74) + chr(2019 - 1908) + '\144' + chr(0b1100101))('\165' + chr(116) + chr(0b1100110) + chr(1184 - 1139) + chr(0b111000))] * ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b1101111) + chr(0b110110), ord("\x08")))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x058h\x12\xeeK\xd3$\r\x05'), '\x64' + chr(101) + '\x63' + chr(111) + '\144' + chr(0b101100 + 0o71))(chr(0b100111 + 0o116) + '\164' + chr(9297 - 9195) + chr(45) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x009o"\xe2^\xc0\t\x00\t\xefFQO'), chr(0b1100100) + '\x65' + chr(99) + chr(0b1101111) + '\144' + '\x65')(chr(0b1110101) + '\164' + chr(102) + chr(0b101101) + chr(0b111000)), [xafqLlk3kkUe(SXOLrMavuUCe(b'\x179`+\xd9Z\xc6"'), '\x64' + chr(0b100011 + 0o102) + chr(0b11100 + 0o107) + chr(0b1101111) + '\x64' + '\145')(chr(0b1110101) + '\164' + chr(102) + chr(948 - 903) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x012o\x12\xe7O\xc6'), '\144' + '\145' + chr(3513 - 3414) + chr(0b1011000 + 0o27) + chr(100) + '\x65')(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + chr(0b10001 + 0o34) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x00.h'), '\144' + '\145' + '\143' + chr(0b1010111 + 0o30) + chr(9925 - 9825) + chr(3122 - 3021))(chr(4166 - 4049) + chr(116) + chr(0b1100110) + chr(0b101101) + chr(2229 - 2173))] * ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b1101111) + chr(0b100101 + 0o21), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x058h\x12\xeeK\xd3$\r\x05'), '\x64' + chr(0b1100101) + chr(6223 - 6124) + '\x6f' + chr(100) + '\x65')(chr(117) + chr(116) + '\x66' + chr(1448 - 1403) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x012o"\xe2^\xc0\t\x02\x1d\xfb|O]x@Bj'), chr(0b101111 + 0o65) + '\x65' + chr(0b1100011) + chr(0b1101111) + chr(7485 - 7385) + chr(101))(chr(117) + chr(0b11100 + 0o130) + '\x66' + chr(1113 - 1068) + chr(306 - 250)), ehT0Px3KOsy9('\x30' + '\x6f' + '\x36', 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x058h\x12\xeeK\xd3$\r\x05'), chr(100) + '\145' + '\x63' + chr(0b1101111) + chr(9819 - 9719) + chr(0b1100010 + 0o3))(chr(2025 - 1908) + '\x74' + chr(4977 - 4875) + chr(1359 - 1314) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x009o"\xe2^\xc0\t\x02\x1d\xfb|O]x@Bj'), '\144' + chr(8751 - 8650) + chr(9323 - 9224) + '\x6f' + chr(6751 - 6651) + chr(0b1100101))('\165' + chr(116) + chr(0b1100110 + 0o0) + chr(45) + chr(56)), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b1101111) + chr(0b110110), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x058h\x12\xeeK\xd3$\r\x05'), chr(4308 - 4208) + '\x65' + chr(99) + chr(11325 - 11214) + chr(5877 - 5777) + '\145')(chr(0b111 + 0o156) + chr(7043 - 6927) + chr(0b11001 + 0o115) + chr(45) + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x012o"\xe2^\xc0\t\x02\x1d\xfb|KY`AC'), chr(0b1100100) + '\145' + '\143' + chr(111) + chr(0b1100100) + '\x65')(chr(0b1110101 + 0o0) + chr(116) + chr(0b111000 + 0o56) + '\x2d' + chr(0b100101 + 0o23)), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31' + '\060', 0o10))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x058h\x12\xeeK\xd3$\r\x05'), chr(0b1000110 + 0o36) + '\x65' + chr(8490 - 8391) + chr(0b1100010 + 0o15) + chr(100) + '\145')(chr(0b1110101) + chr(1844 - 1728) + chr(7094 - 6992) + chr(0b11010 + 0o23) + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x009o"\xe2^\xc0\t\x02\x1d\xfb|KY`AC'), '\144' + '\145' + chr(9576 - 9477) + chr(5212 - 5101) + '\x64' + chr(0b1100101))(chr(117) + chr(0b1010010 + 0o42) + '\x66' + chr(45) + chr(0b111000)), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(49) + chr(336 - 288), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x058h\x12\xeeK\xd3$\r\x05'), chr(0b11001 + 0o113) + '\145' + '\143' + '\x6f' + chr(0b1100100) + '\x65')('\165' + chr(116) + '\146' + chr(45) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x083o,\xead\xd3"\x18\r\xf8WJSozBx\xb4;\xd2\xff'), '\144' + chr(0b1100101) + chr(9718 - 9619) + '\157' + chr(0b1100100) + chr(101))(chr(0b1110101) + chr(4955 - 4839) + '\x66' + chr(0b101101) + '\x38'), ehT0Px3KOsy9('\060' + chr(6983 - 6872) + chr(0b110010) + '\060' + chr(0b11010 + 0o26), 0o10))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x058h\x12\xeeK\xd3$\r\x05'), chr(100) + chr(101) + chr(0b1100011) + chr(111) + chr(0b1011000 + 0o14) + chr(0b1100101))('\x75' + chr(7067 - 6951) + chr(0b1100110) + chr(0b101101) + chr(2917 - 2861)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x012o"\xe2^\xc0\t\x02\x1d\xfb|NYlJB`\x8f:\xc2\xed\x0b\x7f'), '\x64' + chr(9198 - 9097) + chr(4767 - 4668) + chr(0b1010 + 0o145) + chr(0b11011 + 0o111) + chr(0b1100101))('\165' + '\x74' + '\x66' + chr(45) + '\x38'), ehT0Px3KOsy9(chr(0b110000) + chr(11618 - 11507) + chr(340 - 292), 0b1000))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x058h\x12\xeeK\xd3$\r\x05'), chr(438 - 338) + '\145' + '\143' + '\157' + chr(0b1100100) + chr(0b10101 + 0o120))('\165' + '\164' + chr(0b1100110) + '\055' + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x009o"\xe2^\xc0\t\x02\x1d\xfb|NYlJB`\x8f:\xc2\xed\x0b\x7f'), chr(100) + chr(101) + chr(0b10001 + 0o122) + '\x6f' + chr(0b1100100) + chr(101))(chr(0b101111 + 0o106) + chr(0b1110100) + '\146' + chr(45) + chr(0b111000)), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1928 - 1880), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x058h\x12\xeeK\xd3$\r\x05'), '\144' + chr(9567 - 9466) + chr(0b1100011) + chr(0b1101111) + '\x64' + chr(0b101110 + 0o67))('\165' + chr(116) + chr(102) + chr(0b101101) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x012o"\xe2^\xc0\t\x1f\x00\xf7QFX^NF'), chr(100) + chr(586 - 485) + chr(0b1100011) + chr(0b110010 + 0o75) + '\x64' + chr(0b111110 + 0o47))(chr(0b1110101) + '\x74' + chr(8169 - 8067) + '\055' + '\070'), ehT0Px3KOsy9(chr(2071 - 2023) + '\157' + chr(0b110000), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x058h\x12\xeeK\xd3$\r\x05'), '\144' + chr(0b1100101) + '\143' + chr(0b110111 + 0o70) + chr(7931 - 7831) + '\145')('\165' + chr(0b1110100) + '\146' + '\x2d' + chr(704 - 648)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x009o"\xe2^\xc0\t\x1f\x00\xf7QFX^NF'), chr(100) + '\145' + chr(99) + chr(111) + chr(100) + chr(8408 - 8307))(chr(117) + '\x74' + chr(0b1001011 + 0o33) + chr(45) + chr(0b111000)), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110000), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x058h\x12\xeeK\xd3$\r\x05'), chr(0b110100 + 0o60) + chr(5901 - 5800) + '\143' + chr(0b1010111 + 0o30) + chr(0b1011111 + 0o5) + chr(0b1100101))('\x75' + chr(116) + '\146' + chr(0b110 + 0o47) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x009o"\xe2^\xed:\t\x06\xf1WKclP\\m\xb9"\xcb\xe5\n~'), chr(6365 - 6265) + '\x65' + '\143' + chr(0b1101111) + '\144' + '\x65')(chr(117) + chr(4332 - 4216) + '\x66' + chr(0b101 + 0o50) + '\x38'), 1.5)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x058h\x12\xeeK\xd3$\r\x05'), chr(6676 - 6576) + '\145' + chr(5481 - 5382) + chr(0b1001001 + 0o46) + chr(3014 - 2914) + chr(0b1101 + 0o130))(chr(117) + chr(0b1110100) + chr(102) + chr(0b101 + 0o50) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x009o"\xe2^\xed:\t\x06\xf1WKcbJ^j\xa43\xc9\xf8'), chr(3393 - 3293) + chr(0b1100101) + '\143' + chr(0b11001 + 0o126) + '\144' + chr(0b110010 + 0o63))(chr(117) + chr(0b1110100) + chr(0b101100 + 0o72) + chr(1744 - 1699) + chr(558 - 502)), 10.0)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x058h\x12\xeeK\xd3$\r\x05'), chr(0b1100100) + '\x65' + '\x63' + chr(0b100000 + 0o117) + '\144' + '\x65')(chr(0b1110101) + '\x74' + chr(0b101101 + 0o71) + chr(45) + chr(1731 - 1675)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x050|%\xe7'), chr(0b10000 + 0o124) + '\145' + '\143' + '\157' + chr(0b1100100) + chr(0b1100101))(chr(11876 - 11759) + chr(0b1110100) + chr(102) + chr(72 - 27) + '\070'), 0.6)
n4ljua2gi1Pr.Ep30xVZP6Jij = 0.0
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_transformer2.py
|
mtf_bitransformer_tiny
|
def mtf_bitransformer_tiny():
"""Small encoder-decoder model for testing."""
hparams = mtf_bitransformer_base()
hparams.batch_size = 2
hparams.mesh_shape = ""
hparams.d_model = 128
hparams.encoder_layers = ["self_att", "drd"] * 2
hparams.decoder_layers = ["self_att", "enc_att", "drd"] * 2
hparams.num_heads = 4
hparams.d_ff = 512
return hparams
|
python
|
def mtf_bitransformer_tiny():
"""Small encoder-decoder model for testing."""
hparams = mtf_bitransformer_base()
hparams.batch_size = 2
hparams.mesh_shape = ""
hparams.d_model = 128
hparams.encoder_layers = ["self_att", "drd"] * 2
hparams.decoder_layers = ["self_att", "enc_att", "drd"] * 2
hparams.num_heads = 4
hparams.d_ff = 512
return hparams
|
[
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"]",
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] |
Small encoder-decoder model for testing.
|
[
"Small",
"encoder",
"-",
"decoder",
"model",
"for",
"testing",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_transformer2.py#L521-L531
|
train
|
Small encoder - decoder model for testing.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + '\157' + '\x31' + chr(54), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(353 - 304) + '\x34' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + '\063' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b101001 + 0o106) + '\x35' + chr(1970 - 1915), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + chr(0b101001 + 0o12) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\060' + chr(934 - 823) + '\061' + chr(0b11001 + 0o34), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001 + 0o0) + chr(0b110110) + chr(0b110100), 21716 - 21708), ehT0Px3KOsy9(chr(1029 - 981) + chr(7414 - 7303) + chr(0b100110 + 0o14) + chr(0b1011 + 0o54) + chr(52), 15561 - 15553), ehT0Px3KOsy9(chr(0b100111 + 0o11) + '\157' + chr(0b110001) + chr(50) + '\x36', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\x37' + chr(50), 55112 - 55104), ehT0Px3KOsy9(chr(710 - 662) + '\x6f' + '\x32' + chr(0b10100 + 0o42) + '\065', 22551 - 22543), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + chr(0b110111) + '\065', 0o10), ehT0Px3KOsy9('\060' + chr(0b1100000 + 0o17) + '\061' + chr(51) + chr(48), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(878 - 829) + chr(0b110001 + 0o3) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061' + '\067' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(2226 - 2178) + chr(0b1101111) + '\x31' + chr(52) + chr(2589 - 2534), 51512 - 51504), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(111) + chr(0b110110) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(111) + chr(0b10010 + 0o40) + '\061', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(5458 - 5347) + chr(0b11001 + 0o32) + chr(0b110001) + chr(50), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(6401 - 6290) + chr(1557 - 1507) + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b101 + 0o53) + '\157' + '\x33' + chr(0b110110) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061' + chr(106 - 52) + '\x37', 54598 - 54590), ehT0Px3KOsy9(chr(0b100101 + 0o13) + '\157' + '\x32' + chr(48) + '\x35', 0o10), ehT0Px3KOsy9(chr(927 - 879) + chr(0b1100000 + 0o17) + chr(49) + '\x35' + '\065', 0b1000), ehT0Px3KOsy9(chr(0b100010 + 0o16) + '\x6f' + chr(2976 - 2921) + chr(101 - 46), 60171 - 60163), ehT0Px3KOsy9('\060' + chr(111) + chr(51) + chr(0b110000) + chr(2643 - 2588), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + chr(0b110000) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b111111 + 0o60) + chr(0b110111) + '\x35', 0o10), ehT0Px3KOsy9('\060' + chr(0b1011000 + 0o27) + '\x33' + chr(1106 - 1054) + '\066', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + '\061' + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(275 - 223) + '\x33', 40492 - 40484), ehT0Px3KOsy9(chr(48) + '\157' + chr(958 - 907) + '\061' + '\x36', 34401 - 34393), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1100 + 0o47) + '\x36' + '\x36', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + '\063' + '\067', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + chr(1354 - 1306), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + '\061' + '\067', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x31' + '\x30' + '\x33', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + '\062' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\x6f' + chr(0b110001) + '\x30' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(0b1101111) + chr(54) + chr(0b10101 + 0o37), 56662 - 56654)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(0b1010001 + 0o36) + chr(1016 - 963) + '\060', 50645 - 50637)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b' '), chr(0b1100100) + chr(4356 - 4255) + chr(0b1001110 + 0o25) + '\x6f' + chr(100) + chr(7439 - 7338))('\x75' + '\164' + '\x66' + chr(0b101101 + 0o0) + chr(0b100101 + 0o23)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def VI7VZLeirmiO():
n4ljua2gi1Pr = N1wIS6c9nT6g()
n4ljua2gi1Pr.ix9dZyeAmUxY = ehT0Px3KOsy9(chr(48) + '\157' + chr(50), ord("\x08"))
n4ljua2gi1Pr.GnGMnRt7o0q6 = xafqLlk3kkUe(SXOLrMavuUCe(b''), chr(9137 - 9037) + '\145' + chr(0b111001 + 0o52) + chr(111) + chr(6710 - 6610) + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + chr(102) + '\055' + '\070')
n4ljua2gi1Pr.dHIk6a7HYqLO = ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + chr(0b10001 + 0o37) + chr(0b0 + 0o60), 0o10)
n4ljua2gi1Pr.pbeC7au6N1jQ = [xafqLlk3kkUe(SXOLrMavuUCe(b'}\x01\xf6I\x03l\x00\xc8'), chr(0b1100100) + chr(0b100110 + 0o77) + chr(0b1100011) + chr(111) + '\x64' + chr(3610 - 3509))('\165' + '\164' + '\x66' + chr(1741 - 1696) + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'j\x16\xfe'), chr(100) + chr(9177 - 9076) + '\x63' + '\x6f' + '\x64' + chr(0b1100101))(chr(0b1101000 + 0o15) + chr(0b100010 + 0o122) + '\146' + chr(0b101101) + chr(0b111000))] * ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062', 8)
n4ljua2gi1Pr.DuMwu3fbieF4 = [xafqLlk3kkUe(SXOLrMavuUCe(b'}\x01\xf6I\x03l\x00\xc8'), chr(100) + chr(0b10011 + 0o122) + chr(0b1100011) + chr(10074 - 9963) + chr(100) + '\x65')(chr(0b1110101) + chr(0b1110100) + chr(9451 - 9349) + '\x2d' + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'k\n\xf9p=y\x00'), chr(100) + '\x65' + '\143' + chr(0b10001 + 0o136) + chr(0b1100100) + chr(101))(chr(0b1100010 + 0o23) + '\x74' + '\x66' + chr(45) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'j\x16\xfe'), '\x64' + chr(0b110100 + 0o61) + '\x63' + chr(5834 - 5723) + chr(0b1011010 + 0o12) + chr(7012 - 6911))(chr(0b100001 + 0o124) + '\x74' + chr(908 - 806) + chr(0b101101) + chr(1354 - 1298))] * ehT0Px3KOsy9('\x30' + chr(3680 - 3569) + chr(50), 8)
n4ljua2gi1Pr.vRVqPOZ1hUG7 = ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(111) + '\x34', 0o10)
n4ljua2gi1Pr.EpyOHjLLhjxL = ehT0Px3KOsy9('\060' + '\157' + chr(0b110001) + chr(0b10 + 0o56) + '\060' + '\060', ord("\x08"))
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_transformer2.py
|
mtf_unitransformer_all_layers_tiny
|
def mtf_unitransformer_all_layers_tiny():
"""Test out all the layers on local CPU."""
hparams = mtf_unitransformer_tiny()
hparams.moe_num_experts = 4
hparams.moe_expert_x = 4
hparams.moe_expert_y = 4
hparams.moe_hidden_size = 512
hparams.layers = ["self_att", "local_self_att", "moe_1d", "moe_2d", "drd"]
return hparams
|
python
|
def mtf_unitransformer_all_layers_tiny():
"""Test out all the layers on local CPU."""
hparams = mtf_unitransformer_tiny()
hparams.moe_num_experts = 4
hparams.moe_expert_x = 4
hparams.moe_expert_y = 4
hparams.moe_hidden_size = 512
hparams.layers = ["self_att", "local_self_att", "moe_1d", "moe_2d", "drd"]
return hparams
|
[
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",",
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",",
"\"moe_2d\"",
",",
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"]",
"return",
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] |
Test out all the layers on local CPU.
|
[
"Test",
"out",
"all",
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"layers",
"on",
"local",
"CPU",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_transformer2.py#L535-L543
|
train
|
Test out all the layers on local CPU.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\157' + '\x33' + '\x37' + chr(0b11100 + 0o27), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(55) + '\065', 55812 - 55804), ehT0Px3KOsy9(chr(1123 - 1075) + '\157' + chr(1485 - 1436) + chr(2292 - 2237) + chr(0b110010 + 0o5), ord("\x08")), ehT0Px3KOsy9(chr(2087 - 2039) + '\157' + chr(0b100011 + 0o16) + chr(145 - 90), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\062' + '\x30' + '\063', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + chr(72 - 20) + '\066', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + '\063' + chr(50), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + chr(53) + chr(54), 4540 - 4532), ehT0Px3KOsy9('\x30' + chr(0b111 + 0o150) + '\062' + chr(0b1101 + 0o43) + chr(49), 30146 - 30138), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + '\x33' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(1471 - 1423) + '\x6f' + chr(1055 - 1004) + chr(728 - 673) + chr(51), 8), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(0b1101111) + '\x32' + chr(0b11011 + 0o32) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(11446 - 11335) + '\x32' + chr(1634 - 1586) + '\065', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x33' + '\x30' + chr(0b1110 + 0o47), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b10 + 0o155) + chr(1310 - 1261) + chr(0b100 + 0o56) + chr(1417 - 1368), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b10100 + 0o37) + '\067' + chr(55), 0o10), ehT0Px3KOsy9('\x30' + chr(10517 - 10406) + '\062' + '\067', 37144 - 37136), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + chr(0b100001 + 0o22) + '\063', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b11010 + 0o27) + '\064' + chr(1291 - 1238), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b10011 + 0o134) + chr(0b101101 + 0o5) + chr(256 - 206) + chr(0b10110 + 0o37), 0b1000), ehT0Px3KOsy9(chr(0b111 + 0o51) + '\157' + chr(0b110001), 16071 - 16063), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(2859 - 2748) + chr(1505 - 1455) + chr(0b1110 + 0o46) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + '\065' + chr(731 - 678), 15938 - 15930), ehT0Px3KOsy9(chr(0b100111 + 0o11) + '\x6f' + chr(0b10101 + 0o34) + '\064' + '\x30', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(368 - 318) + '\066', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1000011 + 0o54) + chr(0b110010) + '\x32', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + chr(0b110100) + chr(0b110110), 8), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101111) + '\062' + chr(0b11000 + 0o36) + '\066', 0o10), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(2737 - 2626) + chr(50) + '\063' + chr(243 - 188), 31341 - 31333), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10001 + 0o41) + '\066' + chr(51), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(699 - 649) + '\067' + chr(0b101110 + 0o7), 8), ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\x6f' + '\062' + chr(0b110001) + chr(1263 - 1214), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(2054 - 2005) + chr(0b110000) + '\067', 25451 - 25443), ehT0Px3KOsy9('\x30' + '\157' + '\063' + '\x31' + chr(0b110000), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x32' + chr(0b110100) + chr(0b101 + 0o60), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(11158 - 11047) + '\x33' + '\061' + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(111) + chr(0b101111 + 0o2) + chr(0b110100) + '\x36', 50105 - 50097), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b100011 + 0o16) + chr(628 - 579) + chr(52), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061' + '\064' + chr(0b110100), 0o10), ehT0Px3KOsy9('\060' + chr(0b11111 + 0o120) + chr(0b101001 + 0o11) + '\x35' + chr(0b1011 + 0o45), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(0b10111 + 0o130) + chr(53) + '\x30', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd5'), '\144' + '\x65' + chr(0b1100011) + '\157' + chr(100) + chr(0b1100101))(chr(5052 - 4935) + '\x74' + chr(7402 - 7300) + '\055' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def mrM1FTP3jmpn():
n4ljua2gi1Pr = zWetAAOQB_hx()
n4ljua2gi1Pr.r99iQzD4Y8i3 = ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110100), ord("\x08"))
n4ljua2gi1Pr.Jvu8j1yQoKk4 = ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1760 - 1708), 8)
n4ljua2gi1Pr.HCqT_Kt5k5gS = ehT0Px3KOsy9('\060' + '\157' + chr(1609 - 1557), 8)
n4ljua2gi1Pr.IHhsiEth2fU8 = ehT0Px3KOsy9('\060' + chr(111) + chr(0b11 + 0o56) + '\060' + chr(0b11001 + 0o27) + chr(0b101011 + 0o5), 0b1000)
n4ljua2gi1Pr.sGi5Aql23May = [xafqLlk3kkUe(SXOLrMavuUCe(b'\x88\xd8\x13i\xdc\x87\xae\x1a'), chr(0b1100100) + chr(101) + '\x63' + chr(1439 - 1328) + chr(100) + chr(0b10101 + 0o120))('\x75' + '\164' + chr(0b1100110) + '\x2d' + chr(1213 - 1157)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x97\xd2\x1cn\xef\xb9\xa9\x0b\xed\xfa\xa4\xca\xf1\xb1'), chr(100) + chr(101) + '\143' + chr(0b1001010 + 0o45) + chr(0b1100100) + chr(8046 - 7945))(chr(6817 - 6700) + '\x74' + chr(5796 - 5694) + chr(1480 - 1435) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x96\xd2\x1aP\xb2\x82'), chr(100) + '\145' + chr(0b1100011) + chr(0b1100 + 0o143) + '\144' + chr(2554 - 2453))('\165' + chr(0b1110100) + chr(0b1100110) + '\x2d' + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\x96\xd2\x1aP\xb1\x82'), '\x64' + chr(0b11010 + 0o113) + chr(99) + '\x6f' + chr(1109 - 1009) + '\145')(chr(117) + chr(116) + '\x66' + chr(45) + chr(2283 - 2227)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x9f\xcf\x1b'), chr(100) + chr(101) + chr(0b1100011) + chr(1553 - 1442) + '\x64' + '\145')(chr(0b1010101 + 0o40) + '\x74' + '\146' + '\055' + chr(56))]
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_transformer2.py
|
mtf_bitransformer_all_layers_tiny
|
def mtf_bitransformer_all_layers_tiny():
"""Test out all the layers on local CPU."""
hparams = mtf_bitransformer_tiny()
hparams.moe_num_experts = 4
hparams.moe_expert_x = 4
hparams.moe_expert_y = 4
hparams.moe_hidden_size = 512
hparams.encoder_layers = [
"self_att", "local_self_att", "moe_1d", "moe_2d", "drd"]
hparams.decoder_layers = [
"self_att", "local_self_att", "enc_att", "moe_1d", "moe_2d", "drd"]
return hparams
|
python
|
def mtf_bitransformer_all_layers_tiny():
"""Test out all the layers on local CPU."""
hparams = mtf_bitransformer_tiny()
hparams.moe_num_experts = 4
hparams.moe_expert_x = 4
hparams.moe_expert_y = 4
hparams.moe_hidden_size = 512
hparams.encoder_layers = [
"self_att", "local_self_att", "moe_1d", "moe_2d", "drd"]
hparams.decoder_layers = [
"self_att", "local_self_att", "enc_att", "moe_1d", "moe_2d", "drd"]
return hparams
|
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",",
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"]",
"return",
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] |
Test out all the layers on local CPU.
|
[
"Test",
"out",
"all",
"the",
"layers",
"on",
"local",
"CPU",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_transformer2.py#L547-L558
|
train
|
Test out all the layers on local CPU.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + chr(0b110011) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1101111) + chr(2614 - 2561) + chr(2674 - 2620), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(51) + '\064', 0b1000), ehT0Px3KOsy9(chr(1940 - 1892) + '\157' + '\x31' + chr(611 - 559) + chr(0b101011 + 0o5), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100101 + 0o14) + chr(500 - 446) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100010 + 0o20) + chr(0b11101 + 0o26) + chr(54), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110111) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b111111 + 0o60) + chr(0b100011 + 0o16) + chr(2328 - 2279) + chr(51), 46426 - 46418), ehT0Px3KOsy9('\060' + '\157' + '\061' + chr(0b110100) + chr(0b110000), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001011 + 0o44) + '\x33' + chr(0b1111 + 0o45) + chr(2439 - 2389), 47264 - 47256), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + '\x35' + chr(55), 480 - 472), ehT0Px3KOsy9(chr(48) + chr(0b1001 + 0o146) + '\061' + chr(614 - 565), ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\x6f' + '\x33' + chr(49) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\063' + chr(2078 - 2028) + chr(0b1 + 0o57), 28062 - 28054), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001) + chr(1743 - 1692) + chr(0b110010), 53505 - 53497), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + chr(49) + chr(370 - 318), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(2182 - 2132) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(873 - 762) + '\062' + chr(50) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1011 + 0o144) + chr(0b110011) + chr(49) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b11101 + 0o26) + chr(1229 - 1174) + chr(0b100000 + 0o20), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + chr(0b101110 + 0o10) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(50) + chr(49) + chr(0b1011 + 0o47), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + chr(0b11110 + 0o26) + chr(1927 - 1879), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(2557 - 2506) + chr(49) + chr(0b110100), 12644 - 12636), ehT0Px3KOsy9(chr(2224 - 2176) + chr(111) + chr(1849 - 1800) + '\064' + chr(1701 - 1650), ord("\x08")), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\x6f' + chr(1709 - 1660) + '\x37' + chr(0b10110 + 0o35), 42521 - 42513), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(111) + chr(601 - 550) + '\062' + chr(779 - 725), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + chr(67 - 19) + chr(54), 62132 - 62124), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100 + 0o143) + chr(0b110001) + chr(54) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\061' + '\x37' + chr(0b110001 + 0o4), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1011000 + 0o27) + '\062' + chr(55) + '\065', ord("\x08")), ehT0Px3KOsy9('\060' + chr(10505 - 10394) + '\x32' + chr(48) + chr(1619 - 1566), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(129 - 80) + chr(0b110010) + chr(52), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + '\063' + chr(2535 - 2481), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + chr(0b110101 + 0o0) + chr(0b10000 + 0o43), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\061' + chr(0b110001 + 0o6) + chr(1287 - 1233), 0b1000), ehT0Px3KOsy9('\x30' + chr(3387 - 3276) + chr(974 - 923) + chr(51) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(2902 - 2848) + chr(52), 30174 - 30166), ehT0Px3KOsy9(chr(0b1011 + 0o45) + '\x6f' + chr(669 - 620) + '\x35' + chr(0b1001 + 0o54), 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\x37' + chr(0b110111), 36387 - 36379)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\065' + '\060', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf5'), '\144' + '\145' + chr(0b1010110 + 0o15) + '\x6f' + '\144' + chr(6588 - 6487))('\x75' + chr(0b101 + 0o157) + chr(5643 - 5541) + chr(0b100 + 0o51) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def NrF32UsQMC_K():
n4ljua2gi1Pr = VI7VZLeirmiO()
n4ljua2gi1Pr.r99iQzD4Y8i3 = ehT0Px3KOsy9(chr(48) + '\x6f' + '\x34', ord("\x08"))
n4ljua2gi1Pr.Jvu8j1yQoKk4 = ehT0Px3KOsy9(chr(2091 - 2043) + chr(0b111111 + 0o60) + chr(1419 - 1367), 8)
n4ljua2gi1Pr.HCqT_Kt5k5gS = ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b0 + 0o64), 8)
n4ljua2gi1Pr.IHhsiEth2fU8 = ehT0Px3KOsy9(chr(0b100010 + 0o16) + '\x6f' + '\x31' + '\x30' + '\x30' + '\060', 0o10)
n4ljua2gi1Pr.pbeC7au6N1jQ = [xafqLlk3kkUe(SXOLrMavuUCe(b'\xa8K\xf0\x06-\xffM?'), '\x64' + '\x65' + chr(99) + chr(0b1011110 + 0o21) + chr(0b1100100) + chr(4826 - 4725))(chr(117) + '\164' + chr(3455 - 3353) + chr(714 - 669) + chr(0b101100 + 0o14)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xb7A\xff\x01\x1e\xc1J.\x0c\x84\xb0h\xbc\xa4'), chr(0b1100100) + chr(0b1100101) + '\143' + chr(7384 - 7273) + chr(100) + '\145')('\x75' + chr(0b1000010 + 0o62) + '\x66' + chr(45) + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xb6A\xf9?C\xfa'), '\x64' + chr(0b1100101) + '\143' + chr(0b1101111) + chr(0b10100 + 0o120) + chr(9419 - 9318))('\165' + '\164' + '\x66' + chr(661 - 616) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xb6A\xf9?@\xfa'), '\x64' + '\x65' + chr(0b11111 + 0o104) + chr(0b1101111) + chr(0b1100100) + chr(5708 - 5607))(chr(6505 - 6388) + chr(0b1110100) + chr(0b1011100 + 0o12) + chr(0b1101 + 0o40) + '\x38'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xbf\\\xf8'), '\x64' + chr(0b101 + 0o140) + '\143' + '\x6f' + chr(0b1000010 + 0o42) + '\145')('\165' + chr(0b1110100) + chr(102) + chr(45) + chr(0b10011 + 0o45))]
n4ljua2gi1Pr.DuMwu3fbieF4 = [xafqLlk3kkUe(SXOLrMavuUCe(b'\xa8K\xf0\x06-\xffM?'), chr(100) + '\x65' + chr(0b1010111 + 0o14) + chr(4673 - 4562) + '\x64' + chr(101))(chr(7792 - 7675) + '\x74' + chr(0b11000 + 0o116) + '\055' + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xb7A\xff\x01\x1e\xc1J.\x0c\x84\xb0h\xbc\xa4'), '\144' + chr(101) + '\x63' + chr(0b111011 + 0o64) + chr(214 - 114) + chr(0b1100101))(chr(12663 - 12546) + chr(0b1110100) + chr(7354 - 7252) + chr(45) + '\x38'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xbe@\xff?\x13\xeaM'), chr(100) + '\x65' + chr(0b1011111 + 0o4) + chr(0b111111 + 0o60) + chr(6619 - 6519) + chr(0b1100101))(chr(1659 - 1542) + chr(116) + chr(102) + chr(396 - 351) + chr(1630 - 1574)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xb6A\xf9?C\xfa'), '\x64' + '\x65' + chr(99) + '\x6f' + chr(3654 - 3554) + chr(0b1001100 + 0o31))(chr(9900 - 9783) + chr(116) + '\146' + chr(1695 - 1650) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xb6A\xf9?@\xfa'), chr(2549 - 2449) + chr(101) + chr(99) + chr(0b1100001 + 0o16) + '\144' + chr(101))('\165' + chr(6377 - 6261) + '\146' + chr(0b11100 + 0o21) + chr(0b100001 + 0o27)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xbf\\\xf8'), chr(0b111010 + 0o52) + '\x65' + chr(9406 - 9307) + chr(0b110000 + 0o77) + chr(0b111001 + 0o53) + '\145')(chr(3710 - 3593) + '\164' + chr(102) + chr(45) + '\070')]
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_transformer2.py
|
mtr_lm_dense
|
def mtr_lm_dense(sz):
"""Series of architectures for language modeling.
We assume infinite training data, so no dropout necessary.
You can use languagemodel_wiki_noref_v32k_l1k.
(1 epoch = ~46000 steps).
TODO(noam): find a large enough dataset for these experiments.
Args:
sz: an integer
Returns:
a hparams
"""
n = 2 ** sz
hparams = mtf_unitransformer_base()
hparams.d_model = 1024
hparams.max_length = 1024
hparams.batch_size = 128
# Parameters for my_layer_stack()
hparams.num_hidden_layers = 6
hparams.d_ff = 8192 * n
hparams.d_kv = 256
hparams.num_heads = 8 * n
hparams.learning_rate_decay_steps = 65536
hparams.layout = "batch:batch;vocab:model;d_ff:model;heads:model"
hparams.mesh_shape = "batch:32"
return hparams
|
python
|
def mtr_lm_dense(sz):
"""Series of architectures for language modeling.
We assume infinite training data, so no dropout necessary.
You can use languagemodel_wiki_noref_v32k_l1k.
(1 epoch = ~46000 steps).
TODO(noam): find a large enough dataset for these experiments.
Args:
sz: an integer
Returns:
a hparams
"""
n = 2 ** sz
hparams = mtf_unitransformer_base()
hparams.d_model = 1024
hparams.max_length = 1024
hparams.batch_size = 128
# Parameters for my_layer_stack()
hparams.num_hidden_layers = 6
hparams.d_ff = 8192 * n
hparams.d_kv = 256
hparams.num_heads = 8 * n
hparams.learning_rate_decay_steps = 65536
hparams.layout = "batch:batch;vocab:model;d_ff:model;heads:model"
hparams.mesh_shape = "batch:32"
return hparams
|
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] |
Series of architectures for language modeling.
We assume infinite training data, so no dropout necessary.
You can use languagemodel_wiki_noref_v32k_l1k.
(1 epoch = ~46000 steps).
TODO(noam): find a large enough dataset for these experiments.
Args:
sz: an integer
Returns:
a hparams
|
[
"Series",
"of",
"architectures",
"for",
"language",
"modeling",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_transformer2.py#L562-L590
|
train
|
Series of architectures for language modeling.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b10101 + 0o33) + '\x6f' + '\063' + '\x33' + chr(0b101 + 0o53), 20758 - 20750), ehT0Px3KOsy9(chr(48) + '\157' + chr(705 - 655) + chr(48) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b10001 + 0o136) + chr(196 - 147) + chr(0b110000) + '\x30', 41577 - 41569), ehT0Px3KOsy9('\060' + chr(111) + '\062' + chr(793 - 740), 0o10), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(5568 - 5457) + '\x36' + '\060', 2434 - 2426), ehT0Px3KOsy9(chr(48) + '\157' + chr(137 - 87) + chr(1442 - 1394) + chr(0b110110), 53120 - 53112), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + '\x34' + chr(51), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1111 + 0o42) + '\x37' + '\x33', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b101111 + 0o4) + chr(0b10111 + 0o32) + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(5518 - 5407) + chr(277 - 228) + '\064' + '\062', 63677 - 63669), ehT0Px3KOsy9('\060' + '\157' + chr(0b110001) + chr(55) + '\x34', 0b1000), ehT0Px3KOsy9(chr(1831 - 1783) + chr(0b1101111) + chr(50) + chr(0b10101 + 0o37) + chr(54), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + '\061' + '\x34', 37812 - 37804), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(0b1110 + 0o47) + chr(0b1 + 0o63), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1000011 + 0o54) + chr(410 - 359) + chr(320 - 272) + chr(52), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(10296 - 10185) + '\x33' + chr(1524 - 1469) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b1011 + 0o51) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + '\x33' + chr(0b100101 + 0o21), 9822 - 9814), ehT0Px3KOsy9(chr(51 - 3) + chr(0b1101111) + chr(1318 - 1267) + chr(50) + chr(1207 - 1157), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001) + '\061' + '\x37', 13219 - 13211), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110011) + chr(0b101 + 0o54) + chr(1464 - 1415), 40014 - 40006), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(1677 - 1566) + chr(49) + chr(50) + '\x35', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(673 - 622) + chr(0b1 + 0o63) + '\060', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(1100 - 1050) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(7108 - 6997) + '\063' + '\060' + chr(54), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + chr(1972 - 1917) + '\065', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010101 + 0o32) + chr(0b110011) + chr(0b110010) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\064' + chr(0b110100), 21906 - 21898), ehT0Px3KOsy9(chr(48) + '\157' + '\061' + chr(0b1110 + 0o51) + chr(0b100100 + 0o20), 8), ehT0Px3KOsy9('\060' + chr(0b1101010 + 0o5) + '\067', 41840 - 41832), ehT0Px3KOsy9('\x30' + chr(2637 - 2526) + chr(0b11011 + 0o30) + chr(55) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(111) + chr(659 - 610) + chr(54) + chr(54 - 1), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011100 + 0o23) + chr(51) + chr(55) + '\x31', 8), ehT0Px3KOsy9(chr(1969 - 1921) + chr(7089 - 6978) + chr(2421 - 2371) + '\060' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(5103 - 4992) + chr(0b100001 + 0o21) + chr(0b110111) + chr(52), 48895 - 48887), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x31' + '\066' + '\x30', 0o10), ehT0Px3KOsy9('\060' + chr(0b1010111 + 0o30) + chr(0b1011 + 0o54), 8), ehT0Px3KOsy9(chr(469 - 421) + chr(6513 - 6402) + chr(50) + '\067' + chr(1336 - 1281), 30523 - 30515), ehT0Px3KOsy9('\x30' + chr(111) + '\062' + chr(0b10 + 0o61) + chr(1160 - 1110), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b11010 + 0o27) + chr(53) + chr(0b110100), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x35' + chr(0b11111 + 0o21), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf6'), chr(100) + chr(0b1010011 + 0o22) + '\143' + chr(3532 - 3421) + '\x64' + chr(0b101100 + 0o71))(chr(0b10001 + 0o144) + '\x74' + chr(7814 - 7712) + chr(0b101101) + chr(2710 - 2654)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def aQj7OMjYOAmy(hhYs5y35lyzY):
m1NkCryOw9Bx = ehT0Px3KOsy9(chr(0b110000) + chr(0b1101011 + 0o4) + chr(0b101110 + 0o4), 0o10) ** hhYs5y35lyzY
n4ljua2gi1Pr = UsJoV5NmWCXn()
n4ljua2gi1Pr.dHIk6a7HYqLO = ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + '\x30' + '\x30' + chr(0b110000), 0o10)
n4ljua2gi1Pr._o7pVXAdOCRy = ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + '\060' + chr(48) + chr(0b1110 + 0o42), 8)
n4ljua2gi1Pr.ix9dZyeAmUxY = ehT0Px3KOsy9('\x30' + chr(0b10100 + 0o133) + '\x32' + chr(0b100010 + 0o16) + '\x30', 0o10)
n4ljua2gi1Pr.jZh5_pLUoOoZ = ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(2467 - 2413), 0b1000)
n4ljua2gi1Pr.EpyOHjLLhjxL = ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b101111 + 0o100) + chr(0b110010) + '\x30' + '\060' + chr(1987 - 1939) + chr(48), 0o10) * m1NkCryOw9Bx
n4ljua2gi1Pr.cboJxztkwgnV = ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(52) + '\x30' + chr(0b110000), 0o10)
n4ljua2gi1Pr.vRVqPOZ1hUG7 = ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(798 - 749) + chr(0b111 + 0o51), 0b1000) * m1NkCryOw9Bx
n4ljua2gi1Pr.YBAB1XyoxOc5 = ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\x6f' + '\x32' + chr(48) + chr(2148 - 2100) + '\060' + '\060' + '\060', 0b1000)
n4ljua2gi1Pr.HDH7OEwZuDah = xafqLlk3kkUe(SXOLrMavuUCe(b'\xba\xe24vX\xbc\x81\x1a\xbc\x01\x14\x9d\xfa\xc3\xa7\x9fG\xa4\xbf \xad0\x8c\xaf\xa2\xa2\xb5BFj\x96\x11\x9c\xee\x87\x18b\xde\xfe\x1f\xe2\xee/qU\xea'), chr(0b11100 + 0o110) + chr(101) + '\143' + chr(10812 - 10701) + chr(0b1100100) + chr(101))(chr(3988 - 3871) + chr(0b1110100) + chr(2330 - 2228) + '\055' + chr(2866 - 2810))
n4ljua2gi1Pr.GnGMnRt7o0q6 = xafqLlk3kkUe(SXOLrMavuUCe(b'\xba\xe24vX\xbc\xd0I'), '\144' + chr(0b1100101) + chr(0b1100011) + chr(111) + '\x64' + '\x65')(chr(2189 - 2072) + chr(7274 - 7158) + chr(102) + chr(0b101101) + chr(1005 - 949))
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_transformer2.py
|
mtr_lm_v1
|
def mtr_lm_v1():
"""Model incorporating mixture-of-experts, local and global attention.
~6B parameters
32 experts in 3 hierarchichal moe layers.
Returns:
a hparams
"""
hparams = mtr_lm_dense(0)
hparams.layers = (["local_self_att", "local_self_att", "drd",
"self_att", "drd", "local_self_att",
"local_self_att", "moe_2d"] * 4)[:-1]
hparams.d_kv = 128
hparams.moe_expert_x = 8
hparams.moe_expert_y = 4
hparams.moe_hidden_size = 32768
hparams.d_ff = 2048
hparams.num_memory_heads = 0
hparams.mesh_shape = "b0:4;b1:8"
hparams.layout = "outer_batch:b0;inner_batch:b1,expert_x:b1,expert_y:b0"
hparams.outer_batch_size = 4
return hparams
|
python
|
def mtr_lm_v1():
"""Model incorporating mixture-of-experts, local and global attention.
~6B parameters
32 experts in 3 hierarchichal moe layers.
Returns:
a hparams
"""
hparams = mtr_lm_dense(0)
hparams.layers = (["local_self_att", "local_self_att", "drd",
"self_att", "drd", "local_self_att",
"local_self_att", "moe_2d"] * 4)[:-1]
hparams.d_kv = 128
hparams.moe_expert_x = 8
hparams.moe_expert_y = 4
hparams.moe_hidden_size = 32768
hparams.d_ff = 2048
hparams.num_memory_heads = 0
hparams.mesh_shape = "b0:4;b1:8"
hparams.layout = "outer_batch:b0;inner_batch:b1,expert_x:b1,expert_y:b0"
hparams.outer_batch_size = 4
return hparams
|
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] |
Model incorporating mixture-of-experts, local and global attention.
~6B parameters
32 experts in 3 hierarchichal moe layers.
Returns:
a hparams
|
[
"Model",
"incorporating",
"mixture",
"-",
"of",
"-",
"experts",
"local",
"and",
"global",
"attention",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_transformer2.py#L626-L649
|
train
|
Model incorporating mixture - of - experts local and global attention.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\066' + '\064', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101100 + 0o6) + chr(0b110101) + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\x6f' + chr(474 - 423) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(372 - 324) + chr(111) + chr(50) + chr(0b110110) + '\x32', 57181 - 57173), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b100 + 0o56) + chr(1009 - 958) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(2128 - 2080) + '\x6f' + '\063' + chr(0b110001) + chr(55), 24644 - 24636), ehT0Px3KOsy9('\x30' + chr(9653 - 9542) + chr(0b110011) + chr(48) + '\066', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + chr(0b10 + 0o56) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b10000 + 0o137) + chr(53) + chr(0b10100 + 0o40), 45001 - 44993), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + chr(0b110001) + chr(54), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1100010 + 0o15) + chr(50) + chr(0b110110) + '\065', 29858 - 29850), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1101111) + '\065' + chr(0b110 + 0o61), 0o10), ehT0Px3KOsy9('\x30' + chr(564 - 453) + chr(55) + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1011100 + 0o23) + chr(0b1010 + 0o47) + chr(0b110010 + 0o2) + '\067', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101000 + 0o11) + chr(0b10100 + 0o36) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + chr(54) + chr(54), 0o10), ehT0Px3KOsy9('\060' + chr(0b1001110 + 0o41) + chr(2594 - 2543) + chr(0b101110 + 0o7) + '\x31', 38953 - 38945), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b1101111) + chr(881 - 830) + chr(55) + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + chr(188 - 135) + '\062', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b1100 + 0o47) + chr(0b110000) + chr(0b110000), 42149 - 42141), ehT0Px3KOsy9(chr(48) + chr(5541 - 5430) + '\062' + '\060' + '\x30', 0o10), ehT0Px3KOsy9(chr(696 - 648) + '\x6f' + '\062' + chr(0b110010) + chr(0b10111 + 0o36), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + '\x32' + chr(332 - 280), 0b1000), ehT0Px3KOsy9(chr(1059 - 1011) + '\x6f' + chr(429 - 380) + chr(676 - 622) + '\060', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32' + '\x34', 8428 - 8420), ehT0Px3KOsy9(chr(48) + chr(10363 - 10252) + chr(51) + chr(0b110010) + '\064', 57648 - 57640), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + '\x35' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(50) + '\061' + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + chr(0b110100), 20085 - 20077), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x33' + chr(0b110011) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + chr(0b110100) + chr(1099 - 1050), 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(111) + chr(0b110111) + chr(50), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b11101 + 0o25) + '\061', 26337 - 26329), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\157' + chr(49) + chr(49) + '\x30', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101011 + 0o4) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x32' + chr(55) + chr(2600 - 2549), 0o10), ehT0Px3KOsy9(chr(0b101000 + 0o10) + '\157' + chr(0b110111) + chr(1557 - 1503), 0o10), ehT0Px3KOsy9('\x30' + chr(0b10011 + 0o134) + '\x32' + chr(0b100101 + 0o15) + chr(49), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110100) + '\x30', 6834 - 6826), ehT0Px3KOsy9('\060' + chr(10710 - 10599) + '\062' + '\064' + chr(0b110110), 64563 - 64555)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(111) + '\065' + chr(0b110000), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x1a'), chr(0b1011000 + 0o14) + chr(101) + chr(4486 - 4387) + chr(0b1101111) + chr(8017 - 7917) + chr(0b111011 + 0o52))(chr(117) + chr(0b1110100) + '\x66' + '\055' + chr(0b10011 + 0o45)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Z4yy7aswnAnU():
n4ljua2gi1Pr = aQj7OMjYOAmy(ehT0Px3KOsy9(chr(2247 - 2199) + '\157' + '\060', 0o10))
n4ljua2gi1Pr.sGi5Aql23May = ([xafqLlk3kkUe(SXOLrMavuUCe(b'X\xc3~\xd3\xf1\x90\xb5"@(\xeaNK\x13'), chr(0b1011001 + 0o13) + '\x65' + chr(8851 - 8752) + chr(0b1101111) + '\x64' + chr(0b1100101))('\165' + chr(116) + chr(0b111110 + 0o50) + chr(0b101101) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'X\xc3~\xd3\xf1\x90\xb5"@(\xeaNK\x13'), '\144' + chr(5168 - 5067) + chr(5089 - 4990) + chr(0b1100000 + 0o17) + '\x64' + chr(0b1100101))('\165' + chr(13287 - 13171) + '\146' + chr(45) + chr(0b10011 + 0o45)), xafqLlk3kkUe(SXOLrMavuUCe(b'P\xdey'), '\144' + chr(0b1001110 + 0o27) + '\x63' + chr(5653 - 5542) + '\144' + chr(0b11101 + 0o110))(chr(117) + chr(0b1110100) + '\x66' + chr(0b11110 + 0o17) + '\x38'), xafqLlk3kkUe(SXOLrMavuUCe(b'G\xc9q\xd4\xc2\xae\xb23'), chr(0b1100100) + chr(0b111011 + 0o52) + '\x63' + '\157' + chr(100) + chr(0b10 + 0o143))('\165' + chr(169 - 53) + '\146' + '\055' + chr(2272 - 2216)), xafqLlk3kkUe(SXOLrMavuUCe(b'P\xdey'), '\144' + '\145' + chr(0b111110 + 0o45) + '\x6f' + chr(100) + chr(101))(chr(0b1110101) + '\x74' + chr(0b1100110) + chr(0b101101) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'X\xc3~\xd3\xf1\x90\xb5"@(\xeaNK\x13'), chr(2881 - 2781) + '\x65' + chr(9069 - 8970) + chr(3513 - 3402) + chr(948 - 848) + '\145')(chr(0b1110101) + chr(8830 - 8714) + '\146' + '\055' + chr(1872 - 1816)), xafqLlk3kkUe(SXOLrMavuUCe(b'X\xc3~\xd3\xf1\x90\xb5"@(\xeaNK\x13'), '\144' + '\x65' + chr(9771 - 9672) + chr(111) + '\144' + chr(524 - 423))(chr(0b1110101) + '\164' + chr(0b110010 + 0o64) + '\055' + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'Y\xc3x\xed\xaf\xab'), chr(0b11110 + 0o106) + '\145' + chr(0b1011110 + 0o5) + chr(111) + chr(0b1011 + 0o131) + chr(101))(chr(117) + '\164' + chr(0b1100110) + '\x2d' + chr(292 - 236))] * ehT0Px3KOsy9('\x30' + '\157' + chr(52), 0b1000))[:-ehT0Px3KOsy9(chr(48) + chr(0b101010 + 0o105) + chr(49), 0b1000)]
n4ljua2gi1Pr.cboJxztkwgnV = ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\062' + chr(48) + '\x30', 8)
n4ljua2gi1Pr.Jvu8j1yQoKk4 = ehT0Px3KOsy9('\x30' + chr(5907 - 5796) + chr(0b10011 + 0o36) + chr(0b110000), 0b1000)
n4ljua2gi1Pr.HCqT_Kt5k5gS = ehT0Px3KOsy9(chr(146 - 98) + chr(111) + chr(0b110100), 8)
n4ljua2gi1Pr.IHhsiEth2fU8 = ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b10000 + 0o41) + '\x30' + '\060' + '\x30' + '\x30' + chr(0b10110 + 0o32), 0b1000)
n4ljua2gi1Pr.EpyOHjLLhjxL = ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101111) + chr(0b100000 + 0o24) + chr(0b100000 + 0o20) + '\x30' + chr(0b100001 + 0o17), 0o10)
n4ljua2gi1Pr.DghyDIngdCd6 = ehT0Px3KOsy9(chr(0b10101 + 0o33) + '\x6f' + '\x30', 8)
n4ljua2gi1Pr.GnGMnRt7o0q6 = xafqLlk3kkUe(SXOLrMavuUCe(b"V\x9c'\x86\xa6\xad\xf7}\x14"), '\144' + '\x65' + chr(0b100101 + 0o76) + '\157' + chr(0b1100100) + chr(0b1100101))(chr(6284 - 6167) + chr(11480 - 11364) + chr(0b101000 + 0o76) + chr(916 - 871) + '\070')
n4ljua2gi1Pr.HDH7OEwZuDah = xafqLlk3kkUe(SXOLrMavuUCe(b'[\xd9i\xd7\xef\x90\xa4&X-\xdd\x15]Wm\x1f\x87\x91\x8f\xb2\xdf\xf75\x04w\xbc\xd5\xeb=\xf4\xc4Ba-t\xcfa\xe9\x1a\xc4\x05\x80x\xca\xed\xaa\xb43s7\x8fM\x0f'), chr(565 - 465) + '\x65' + chr(0b1100011) + '\157' + '\144' + chr(4406 - 4305))(chr(0b1110101) + '\164' + chr(102) + chr(0b100111 + 0o6) + '\x38')
n4ljua2gi1Pr.OaMZy_d2UJyg = ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b10000 + 0o44), 8)
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_transformer2.py
|
mtr_tr_dense
|
def mtr_tr_dense(sz):
"""Series of machine translation models.
All models are trained on sequences of 256 tokens.
You can use the dataset translate_enfr_wmt32k_packed.
154000 steps = 3 epochs.
Args:
sz: an integer
Returns:
a hparams
"""
n = 2 ** sz
hparams = mtf_bitransformer_base()
hparams.d_model = 1024
hparams.max_length = 256
hparams.batch_size = 128
hparams.d_ff = int(4096 * n)
hparams.d_kv = 128
hparams.encoder_num_heads = int(8 * n)
hparams.decoder_num_heads = int(8 * n)
# one epoch for translate_enfr_wmt32k_packed = 51400 steps
hparams.learning_rate_decay_steps = 51400
hparams.layout = "batch:batch;vocab:model;d_ff:model;heads:model"
hparams.mesh_shape = "batch:32"
hparams.label_smoothing = 0.1
hparams.layer_prepostprocess_dropout = 0.1
hparams.attention_dropout = 0.1
hparams.relu_dropout = 0.1
return hparams
|
python
|
def mtr_tr_dense(sz):
"""Series of machine translation models.
All models are trained on sequences of 256 tokens.
You can use the dataset translate_enfr_wmt32k_packed.
154000 steps = 3 epochs.
Args:
sz: an integer
Returns:
a hparams
"""
n = 2 ** sz
hparams = mtf_bitransformer_base()
hparams.d_model = 1024
hparams.max_length = 256
hparams.batch_size = 128
hparams.d_ff = int(4096 * n)
hparams.d_kv = 128
hparams.encoder_num_heads = int(8 * n)
hparams.decoder_num_heads = int(8 * n)
# one epoch for translate_enfr_wmt32k_packed = 51400 steps
hparams.learning_rate_decay_steps = 51400
hparams.layout = "batch:batch;vocab:model;d_ff:model;heads:model"
hparams.mesh_shape = "batch:32"
hparams.label_smoothing = 0.1
hparams.layer_prepostprocess_dropout = 0.1
hparams.attention_dropout = 0.1
hparams.relu_dropout = 0.1
return hparams
|
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] |
Series of machine translation models.
All models are trained on sequences of 256 tokens.
You can use the dataset translate_enfr_wmt32k_packed.
154000 steps = 3 epochs.
Args:
sz: an integer
Returns:
a hparams
|
[
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_transformer2.py#L660-L691
|
train
|
Series of machine translation models.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100001 + 0o20) + chr(1109 - 1058) + chr(0b11011 + 0o26), ord("\x08")), ehT0Px3KOsy9(chr(589 - 541) + chr(111) + chr(0b1010 + 0o47) + chr(49) + chr(1245 - 1196), 27902 - 27894), ehT0Px3KOsy9('\x30' + chr(8750 - 8639) + '\x32' + chr(0b1110 + 0o44) + chr(0b110100), 11738 - 11730), ehT0Px3KOsy9(chr(695 - 647) + '\x6f' + '\x32' + chr(532 - 482) + chr(48), 59595 - 59587), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(0b1101111) + '\061' + '\062' + chr(48), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + chr(0b110111) + chr(48), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(0b11000 + 0o37) + chr(0b110001), 21406 - 21398), ehT0Px3KOsy9(chr(1541 - 1493) + chr(111) + chr(51) + '\064' + '\063', 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x31' + '\065' + '\067', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + '\065' + '\064', 46277 - 46269), ehT0Px3KOsy9('\060' + chr(2085 - 1974) + chr(51) + chr(0b110010) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(2311 - 2260) + chr(0b110111) + '\061', 8), ehT0Px3KOsy9(chr(1377 - 1329) + '\157' + '\062' + chr(491 - 441) + chr(1863 - 1815), 8), ehT0Px3KOsy9(chr(0b110000) + chr(1283 - 1172) + chr(0b10110 + 0o33) + chr(0b110101) + chr(0b110010), 40234 - 40226), ehT0Px3KOsy9(chr(48) + '\157' + '\063' + '\x31' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b0 + 0o62) + chr(892 - 838) + chr(96 - 44), 17405 - 17397), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\157' + chr(0b11100 + 0o27) + chr(3011 - 2956), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\062' + '\x32', 0o10), ehT0Px3KOsy9(chr(1508 - 1460) + '\157' + '\061' + '\x32' + chr(53), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\x31' + chr(0b110011) + chr(0b1010 + 0o51), 53880 - 53872), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + '\067' + chr(0b101001 + 0o10), 0o10), ehT0Px3KOsy9(chr(1757 - 1709) + '\x6f' + '\062' + '\x37' + '\060', 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110010) + '\066' + chr(115 - 66), 33525 - 33517), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + chr(0b100100 + 0o15), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(2576 - 2525) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(1891 - 1843) + chr(111) + chr(2349 - 2298) + '\067' + chr(0b100111 + 0o13), ord("\x08")), ehT0Px3KOsy9(chr(1998 - 1950) + chr(8296 - 8185) + chr(1348 - 1297) + chr(0b110011) + '\x33', 44021 - 44013), ehT0Px3KOsy9('\x30' + '\x6f' + '\065' + chr(1726 - 1675), ord("\x08")), ehT0Px3KOsy9(chr(447 - 399) + chr(111) + chr(0b110001) + '\x37' + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x34' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b111101 + 0o62) + chr(0b100100 + 0o16) + chr(0b100011 + 0o22) + chr(0b100100 + 0o22), 0b1000), ehT0Px3KOsy9(chr(222 - 174) + '\157' + '\063' + '\x30' + '\x35', 0b1000), ehT0Px3KOsy9(chr(48) + chr(11144 - 11033) + chr(1596 - 1545) + chr(0b100 + 0o62) + chr(0b11 + 0o57), 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\x6f' + chr(49) + '\x30' + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(111) + chr(0b10110 + 0o41) + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b0 + 0o63) + chr(50) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(1293 - 1245) + '\157' + chr(0b110001) + chr(841 - 788) + '\x30', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1 + 0o61) + '\x35' + chr(55), 18590 - 18582), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b101001 + 0o106) + chr(52) + chr(53), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11001 + 0o36) + chr(0b11100 + 0o31), 6456 - 6448)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b11101 + 0o122) + '\x35' + '\x30', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'w'), chr(373 - 273) + chr(0b1100101) + chr(0b1100011) + '\157' + chr(1805 - 1705) + '\145')(chr(0b11001 + 0o134) + chr(0b1001110 + 0o46) + '\146' + '\x2d' + chr(1841 - 1785)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def zyKJtermD9kx(hhYs5y35lyzY):
m1NkCryOw9Bx = ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(0b1101111) + '\x32', 0b1000) ** hhYs5y35lyzY
n4ljua2gi1Pr = N1wIS6c9nT6g()
n4ljua2gi1Pr.dHIk6a7HYqLO = ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062' + chr(0b110000) + chr(578 - 530) + chr(0b100100 + 0o14), ord("\x08"))
n4ljua2gi1Pr._o7pVXAdOCRy = ehT0Px3KOsy9(chr(1830 - 1782) + '\x6f' + chr(0b10 + 0o62) + chr(1255 - 1207) + chr(0b11001 + 0o27), 0o10)
n4ljua2gi1Pr.ix9dZyeAmUxY = ehT0Px3KOsy9(chr(1051 - 1003) + chr(111) + chr(50) + chr(0b110000) + chr(165 - 117), ord("\x08"))
n4ljua2gi1Pr.EpyOHjLLhjxL = ehT0Px3KOsy9(ehT0Px3KOsy9(chr(48) + '\x6f' + chr(405 - 356) + chr(0b11101 + 0o23) + chr(0b101 + 0o53) + chr(1241 - 1193) + chr(1637 - 1589), ord("\x08")) * m1NkCryOw9Bx)
n4ljua2gi1Pr.cboJxztkwgnV = ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b1010 + 0o50) + '\060' + '\x30', 8)
n4ljua2gi1Pr.YBAZlBpskFr_ = ehT0Px3KOsy9(ehT0Px3KOsy9(chr(0b101000 + 0o10) + '\x6f' + '\061' + chr(0b110000), 0b1000) * m1NkCryOw9Bx)
n4ljua2gi1Pr.w4ogLtE6oWZi = ehT0Px3KOsy9(ehT0Px3KOsy9('\x30' + chr(8944 - 8833) + '\061' + '\060', 8) * m1NkCryOw9Bx)
n4ljua2gi1Pr.YBAB1XyoxOc5 = ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(3795 - 3684) + chr(0b110001) + chr(0b0 + 0o64) + chr(0b110 + 0o56) + chr(0b110011) + '\x31' + chr(0b110000), 0b1000)
n4ljua2gi1Pr.HDH7OEwZuDah = xafqLlk3kkUe(SXOLrMavuUCe(b';(\xe0\xf38\x82\x9b\x82\x1b\x8f\xb8\xc2\xe6\x05\xab\xd5}(84\xdd\xdd\xdd2\x7f\xa5\xbdMEK\xc1\xa1\x97*\x07\xbd\r\xceANc$\xfb\xf45\xd4'), chr(0b11 + 0o141) + chr(0b1100101) + chr(0b1100011) + chr(111) + chr(0b1000110 + 0o36) + chr(0b1011100 + 0o11))('\x75' + '\x74' + chr(0b1100110) + chr(0b101101) + chr(0b1001 + 0o57))
n4ljua2gi1Pr.GnGMnRt7o0q6 = xafqLlk3kkUe(SXOLrMavuUCe(b';(\xe0\xf38\x82\xca\xd1'), chr(0b1000 + 0o134) + '\145' + chr(0b1011100 + 0o7) + '\157' + '\x64' + chr(0b1100101))(chr(0b1110101) + chr(4987 - 4871) + chr(102) + '\x2d' + '\070')
n4ljua2gi1Pr.FSjUgdaczzRk = 0.1
n4ljua2gi1Pr.RW_xSzp18UeS = 0.1
n4ljua2gi1Pr.RdMRr3qkYioQ = 0.1
n4ljua2gi1Pr.PJc0PNdBnSag = 0.1
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_transformer2.py
|
mtr_tr_dense_local
|
def mtr_tr_dense_local(sz):
"""With local self-attention in the decoder."""
hparams = mtr_tr_dense(sz)
hparams.decoder_layers = ["local_self_att", "enc_att", "drd"] * 6
hparams.local_attention_radius = 32
return hparams
|
python
|
def mtr_tr_dense_local(sz):
"""With local self-attention in the decoder."""
hparams = mtr_tr_dense(sz)
hparams.decoder_layers = ["local_self_att", "enc_att", "drd"] * 6
hparams.local_attention_radius = 32
return hparams
|
[
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"sz",
")",
":",
"hparams",
"=",
"mtr_tr_dense",
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"sz",
")",
"hparams",
".",
"decoder_layers",
"=",
"[",
"\"local_self_att\"",
",",
"\"enc_att\"",
",",
"\"drd\"",
"]",
"*",
"6",
"hparams",
".",
"local_attention_radius",
"=",
"32",
"return",
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] |
With local self-attention in the decoder.
|
[
"With",
"local",
"self",
"-",
"attention",
"in",
"the",
"decoder",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_transformer2.py#L734-L739
|
train
|
With local self - attention in the decoder.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(111) + chr(2097 - 2046) + chr(53) + '\067', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + chr(0b110011) + chr(1547 - 1493), 58106 - 58098), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(3268 - 3157) + chr(50) + chr(0b1110 + 0o47) + chr(0b101001 + 0o16), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(1472 - 1421) + chr(0b100001 + 0o17) + chr(1874 - 1824), ord("\x08")), ehT0Px3KOsy9(chr(578 - 530) + '\x6f' + chr(1042 - 992) + chr(2115 - 2060) + '\064', 0o10), ehT0Px3KOsy9(chr(1180 - 1132) + chr(0b1000101 + 0o52) + '\062' + '\x36' + chr(0b110111), 49843 - 49835), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(9086 - 8975) + chr(51) + chr(2097 - 2049) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(0b110010) + chr(0b100101 + 0o21), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + chr(972 - 920) + '\065', 0o10), ehT0Px3KOsy9('\060' + chr(1765 - 1654) + '\063' + '\063' + chr(1618 - 1569), 33164 - 33156), ehT0Px3KOsy9(chr(48) + '\157' + chr(1556 - 1505) + chr(50) + chr(1704 - 1651), 41644 - 41636), ehT0Px3KOsy9('\x30' + '\157' + chr(55), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + chr(55) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(51) + '\x32' + chr(0b1100 + 0o51), 8), ehT0Px3KOsy9(chr(393 - 345) + '\157' + chr(0b10101 + 0o34) + '\062' + chr(54), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + chr(52) + chr(0b100101 + 0o21), 28195 - 28187), ehT0Px3KOsy9('\060' + '\x6f' + chr(1094 - 1044) + chr(0b100010 + 0o23) + chr(0b1111 + 0o44), 14358 - 14350), ehT0Px3KOsy9('\060' + chr(0b111011 + 0o64) + '\061' + chr(53) + chr(1445 - 1391), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x37' + chr(0b1010 + 0o46), 26466 - 26458), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\x6f' + chr(54) + chr(2228 - 2178), 0b1000), ehT0Px3KOsy9(chr(1971 - 1923) + '\x6f' + chr(51) + '\062' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\x6f' + chr(0b110000 + 0o2) + chr(0b110010) + '\x32', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + chr(1849 - 1801) + chr(0b1101 + 0o47), 0o10), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(111) + '\062' + '\064' + '\x33', 0o10), ehT0Px3KOsy9(chr(246 - 198) + '\x6f' + chr(0b100000 + 0o22) + chr(0b100001 + 0o22) + chr(53), 12949 - 12941), ehT0Px3KOsy9(chr(2053 - 2005) + '\157' + chr(49) + '\x35' + '\066', 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110 + 0o60) + chr(0b11000 + 0o36), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(7670 - 7559) + '\x31' + chr(127 - 74) + chr(0b11101 + 0o31), 8), ehT0Px3KOsy9(chr(2275 - 2227) + chr(111) + chr(0b101001 + 0o11) + chr(0b110100) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(10941 - 10830) + '\x31' + chr(53), 0o10), ehT0Px3KOsy9(chr(665 - 617) + chr(0b1010111 + 0o30) + chr(0b110111) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1584 - 1534) + chr(1587 - 1536) + '\062', 59062 - 59054), ehT0Px3KOsy9('\x30' + '\157' + '\062' + '\063' + chr(55), 0o10), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(111) + chr(49) + '\x37' + chr(0b110000 + 0o2), ord("\x08")), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\157' + chr(1099 - 1045) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b1101111) + '\x32' + chr(55) + '\x33', 0b1000), ehT0Px3KOsy9(chr(1481 - 1433) + chr(348 - 237) + chr(0b10111 + 0o32), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(830 - 776), 25363 - 25355), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(111) + '\x32' + '\066' + chr(502 - 452), 0o10), ehT0Px3KOsy9(chr(2118 - 2070) + chr(111) + chr(49) + '\x37' + '\x36', 33906 - 33898)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b1100100 + 0o13) + chr(53) + chr(0b110000), 22891 - 22883)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xc1'), chr(2849 - 2749) + chr(101) + chr(0b100101 + 0o76) + chr(0b1100111 + 0o10) + '\x64' + chr(101))(chr(0b1110101) + chr(0b1110100) + '\x66' + chr(45) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def XushQ7nPDAdp(hhYs5y35lyzY):
n4ljua2gi1Pr = zyKJtermD9kx(hhYs5y35lyzY)
n4ljua2gi1Pr.DuMwu3fbieF4 = [xafqLlk3kkUe(SXOLrMavuUCe(b'\x831\xcc\xa3\xd0\xe8\xb33\x89\xbf\x8af\r\xa1'), chr(825 - 725) + '\145' + chr(0b1100011) + '\157' + chr(100) + chr(1378 - 1277))(chr(0b11101 + 0o130) + '\164' + chr(0b1100110) + chr(0b101101) + chr(0b110101 + 0o3)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x8a0\xcc\x9d\xdd\xc3\xb4'), chr(100) + '\x65' + '\143' + '\x6f' + chr(100) + chr(0b111110 + 0o47))(chr(0b1100011 + 0o22) + chr(0b1110100) + chr(102) + chr(1760 - 1715) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x8b,\xcb'), chr(100) + chr(101) + chr(6416 - 6317) + '\x6f' + chr(0b1011 + 0o131) + chr(0b1100101))(chr(0b100100 + 0o121) + chr(0b1110100) + '\x66' + chr(45) + chr(0b100011 + 0o25))] * ehT0Px3KOsy9(chr(0b110000) + chr(0b101 + 0o152) + chr(552 - 498), 8)
n4ljua2gi1Pr.qj99VW_JN_A0 = ehT0Px3KOsy9(chr(0b101 + 0o53) + '\x6f' + chr(0b110100) + '\x30', 0o10)
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/vqa_recurrent_self_attention.py
|
recurrent_transformer_decoder
|
def recurrent_transformer_decoder(
decoder_input,
encoder_output,
decoder_self_attention_bias,
encoder_decoder_attention_bias,
hparams,
name="decoder",
nonpadding=None,
save_weights_to=None,
make_image_summary=True):
"""Recurrent decoder function."""
x = decoder_input
attention_dropout_broadcast_dims = (
common_layers.comma_separated_string_to_integer_list(
getattr(hparams, "attention_dropout_broadcast_dims", "")))
with tf.variable_scope(name):
ffn_unit = functools.partial(
# use encoder ffn, since decoder ffn use left padding
universal_transformer_util.transformer_encoder_ffn_unit,
hparams=hparams,
nonpadding_mask=nonpadding)
attention_unit = functools.partial(
universal_transformer_util.transformer_decoder_attention_unit,
hparams=hparams,
encoder_output=encoder_output,
decoder_self_attention_bias=decoder_self_attention_bias,
encoder_decoder_attention_bias=encoder_decoder_attention_bias,
attention_dropout_broadcast_dims=attention_dropout_broadcast_dims,
save_weights_to=save_weights_to,
make_image_summary=make_image_summary)
x, extra_output = universal_transformer_util.universal_transformer_layer(
x, hparams, ffn_unit, attention_unit)
return common_layers.layer_preprocess(x, hparams), extra_output
|
python
|
def recurrent_transformer_decoder(
decoder_input,
encoder_output,
decoder_self_attention_bias,
encoder_decoder_attention_bias,
hparams,
name="decoder",
nonpadding=None,
save_weights_to=None,
make_image_summary=True):
"""Recurrent decoder function."""
x = decoder_input
attention_dropout_broadcast_dims = (
common_layers.comma_separated_string_to_integer_list(
getattr(hparams, "attention_dropout_broadcast_dims", "")))
with tf.variable_scope(name):
ffn_unit = functools.partial(
# use encoder ffn, since decoder ffn use left padding
universal_transformer_util.transformer_encoder_ffn_unit,
hparams=hparams,
nonpadding_mask=nonpadding)
attention_unit = functools.partial(
universal_transformer_util.transformer_decoder_attention_unit,
hparams=hparams,
encoder_output=encoder_output,
decoder_self_attention_bias=decoder_self_attention_bias,
encoder_decoder_attention_bias=encoder_decoder_attention_bias,
attention_dropout_broadcast_dims=attention_dropout_broadcast_dims,
save_weights_to=save_weights_to,
make_image_summary=make_image_summary)
x, extra_output = universal_transformer_util.universal_transformer_layer(
x, hparams, ffn_unit, attention_unit)
return common_layers.layer_preprocess(x, hparams), extra_output
|
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] |
Recurrent decoder function.
|
[
"Recurrent",
"decoder",
"function",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/vqa_recurrent_self_attention.py#L138-L173
|
train
|
Recurrent decoder function.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1061 - 1013) + chr(111) + chr(50) + chr(0b101110 + 0o4) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061' + chr(0b10011 + 0o44) + chr(50), 11147 - 11139), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + chr(565 - 516) + chr(0b1110 + 0o44), 36234 - 36226), ehT0Px3KOsy9(chr(48) + chr(111) + chr(807 - 758) + chr(0b110011) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b100100 + 0o20) + chr(552 - 497), 49018 - 49010), ehT0Px3KOsy9(chr(1205 - 1157) + '\157' + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b111000 + 0o67) + chr(51) + chr(0b110000) + chr(600 - 551), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(10969 - 10858) + chr(0b110001) + chr(0b101100 + 0o6) + chr(51), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(521 - 470) + chr(0b110000) + '\x34', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + '\x31' + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\x6f' + chr(0b110010) + chr(0b110100) + chr(0b101000 + 0o16), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(2114 - 2065) + chr(2446 - 2393) + '\x37', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + chr(0b110000) + chr(1022 - 967), 6137 - 6129), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(111) + '\x34' + chr(0b110001), 11008 - 11000), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + '\061' + '\x32', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(2554 - 2500) + chr(0b110110), 35258 - 35250), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(435 - 385) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x31' + chr(0b110000) + chr(51), 26553 - 26545), ehT0Px3KOsy9(chr(1157 - 1109) + '\x6f' + chr(50) + chr(0b100011 + 0o24) + '\064', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b100111 + 0o17) + chr(1937 - 1889), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\064' + '\064', 0b1000), ehT0Px3KOsy9('\060' + chr(10857 - 10746) + '\x31' + chr(0b10110 + 0o34) + chr(0b111 + 0o53), 0o10), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b1101111) + '\063' + chr(1583 - 1535) + '\x32', 12513 - 12505), ehT0Px3KOsy9(chr(48) + chr(9627 - 9516) + chr(0b101011 + 0o6) + chr(1102 - 1053) + chr(0b110010), 44938 - 44930), ehT0Px3KOsy9('\060' + '\157' + chr(2489 - 2437) + chr(0b100101 + 0o22), 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b111 + 0o52) + chr(0b110010) + '\066', 0o10), ehT0Px3KOsy9(chr(1809 - 1761) + '\x6f' + chr(0b111 + 0o52) + chr(0b10000 + 0o47), 0o10), ehT0Px3KOsy9(chr(0b101 + 0o53) + '\x6f' + chr(1121 - 1067) + '\062', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110010) + chr(0b101010 + 0o11) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\060' + chr(5895 - 5784) + chr(0b110010) + chr(0b100101 + 0o13) + '\064', 50935 - 50927), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\157' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(51) + '\x33', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + chr(52) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\157' + chr(0b110100) + '\064', 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b1000 + 0o56), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(1040 - 990) + chr(50) + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + chr(53) + '\x30', 1633 - 1625), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + '\064' + '\x34', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + chr(50) + chr(0b101001 + 0o15), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b100111 + 0o110) + '\062' + chr(0b110101), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1679 - 1626) + chr(0b110000), 40548 - 40540)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xbf'), chr(100) + chr(101) + chr(0b1100011) + chr(0b1011101 + 0o22) + '\144' + '\145')('\x75' + chr(0b1110100) + chr(5465 - 5363) + '\055' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def KPxrvdiyr6Gu(t5Jz9byuSQ65, NE_S2zAzN4PI, Z0c2rFCFDCFc, iuvkQfeRHfn5, n4ljua2gi1Pr, AIvJRzLdDfgF=xafqLlk3kkUe(SXOLrMavuUCe(b'\xf5\x1f\xa96Cd\xb3'), chr(0b1100100) + '\145' + chr(0b10110 + 0o115) + chr(0b1101001 + 0o6) + chr(0b1100100) + '\x65')(chr(10840 - 10723) + chr(7380 - 7264) + chr(102) + chr(45) + chr(0b11001 + 0o37)), qpPhEurkAWxO=None, zWaF_2VBEDjk=None, NC2xHNLwzxcH=ehT0Px3KOsy9(chr(48) + chr(0b1010010 + 0o35) + '\061', 8)):
OeWW0F1dBPRQ = t5Jz9byuSQ65
UNqT6jwzCz6Y = jSKPaHwSAfVv.comma_separated_string_to_integer_list(xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf0\x0e\xbe<Iu\xa8<\xaa\x96\xc2\x1d\xe8Q\xe5C\xe3\x1c\xdeBK3\xa6)F%{m\xfc\xedoh'), '\144' + chr(101) + chr(0b110010 + 0o61) + '\x6f' + chr(100) + chr(4514 - 4413))('\165' + chr(0b1011011 + 0o31) + chr(0b1100110) + chr(0b101101) + '\x38'), xafqLlk3kkUe(SXOLrMavuUCe(b''), chr(100) + chr(101) + chr(0b1100011) + '\157' + chr(0b101011 + 0o71) + chr(7332 - 7231))(chr(0b101011 + 0o112) + chr(0b1001101 + 0o47) + '\x66' + chr(1362 - 1317) + chr(0b1001 + 0o57))))
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe7\x1b\xb80Fc\xad6\x9b\xba\xc5\x00\xf7D'), chr(100) + chr(101) + chr(5870 - 5771) + '\x6f' + chr(100) + '\x65')(chr(117) + chr(0b110101 + 0o77) + chr(0b101001 + 0o75) + chr(0b10000 + 0o35) + chr(0b11000 + 0o40)))(AIvJRzLdDfgF):
SHRtjNoPzosY = E6ula8_Zv1yl.partial(X9wj_mQonVjf.transformer_encoder_ffn_unit, hparams=n4ljua2gi1Pr, nonpadding_mask=qpPhEurkAWxO)
ek3fs6JEXh0d = E6ula8_Zv1yl.partial(X9wj_mQonVjf.transformer_decoder_attention_unit, hparams=n4ljua2gi1Pr, encoder_output=NE_S2zAzN4PI, decoder_self_attention_bias=Z0c2rFCFDCFc, encoder_decoder_attention_bias=iuvkQfeRHfn5, attention_dropout_broadcast_dims=UNqT6jwzCz6Y, save_weights_to=zWaF_2VBEDjk, make_image_summary=NC2xHNLwzxcH)
(OeWW0F1dBPRQ, kpP2CsboxNzE) = X9wj_mQonVjf.universal_transformer_layer(OeWW0F1dBPRQ, n4ljua2gi1Pr, SHRtjNoPzosY, ek3fs6JEXh0d)
return (xafqLlk3kkUe(jSKPaHwSAfVv, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfd\x1b\xb3<U^\xb1!\xa1\xb9\xd4\x00\xe4D\xf9E'), '\x64' + chr(0b1100101) + chr(9380 - 9281) + chr(111) + chr(0b110100 + 0o60) + chr(101))(chr(5297 - 5180) + chr(274 - 158) + chr(102) + '\x2d' + chr(0b111000)))(OeWW0F1dBPRQ, n4ljua2gi1Pr), kpP2CsboxNzE)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/vqa_recurrent_self_attention.py
|
vqa_recurrent_self_attention_base
|
def vqa_recurrent_self_attention_base():
"""VQA attention baseline hparams."""
hparams = universal_transformer.universal_transformer_base()
hparams.batch_size = 1024
hparams.use_fixed_batch_size = True
hparams.weight_decay = 0.
hparams.clip_grad_norm = 0.
# use default initializer
# hparams.initializer = "xavier"
hparams.learning_rate_schedule = (
"constant*linear_warmup*rsqrt_normalized_decay")
hparams.learning_rate_warmup_steps = 8000
hparams.learning_rate_constant = 7e-4
hparams.learning_rate_decay_rate = 0.5
hparams.learning_rate_decay_steps = 50000
# hparams.dropout = 0.5
hparams.summarize_grads = True
hparams.summarize_vars = True
# not used hparams
hparams.label_smoothing = 0.1
hparams.multiply_embedding_mode = "sqrt_depth"
# add new hparams
# use raw image as input
hparams.add_hparam("image_input_type", "feature")
hparams.add_hparam("image_model_fn", "resnet_v1_152")
hparams.add_hparam("resize_side", 512)
hparams.add_hparam("height", 448)
hparams.add_hparam("width", 448)
hparams.add_hparam("distort", True)
hparams.add_hparam("train_resnet", False)
# question hidden size
# hparams.hidden_size = 512
# hparams.filter_size = 1024
# hparams.num_hidden_layers = 4
# self attention parts
# hparams.norm_type = "layer"
# hparams.layer_preprocess_sequence = "n"
# hparams.layer_postprocess_sequence = "da"
# hparams.layer_prepostprocess_dropout = 0.1
# hparams.attention_dropout = 0.1
# hparams.relu_dropout = 0.1
# hparams.add_hparam("pos", "timing")
# hparams.add_hparam("num_encoder_layers", 0)
# hparams.add_hparam("num_decoder_layers", 0)
# hparams.add_hparam("num_heads", 8)
# hparams.add_hparam("attention_key_channels", 0)
# hparams.add_hparam("attention_value_channels", 0)
# hparams.add_hparam("self_attention_type", "dot_product")
# iterative part
hparams.transformer_ffn_type = "fc"
return hparams
|
python
|
def vqa_recurrent_self_attention_base():
"""VQA attention baseline hparams."""
hparams = universal_transformer.universal_transformer_base()
hparams.batch_size = 1024
hparams.use_fixed_batch_size = True
hparams.weight_decay = 0.
hparams.clip_grad_norm = 0.
# use default initializer
# hparams.initializer = "xavier"
hparams.learning_rate_schedule = (
"constant*linear_warmup*rsqrt_normalized_decay")
hparams.learning_rate_warmup_steps = 8000
hparams.learning_rate_constant = 7e-4
hparams.learning_rate_decay_rate = 0.5
hparams.learning_rate_decay_steps = 50000
# hparams.dropout = 0.5
hparams.summarize_grads = True
hparams.summarize_vars = True
# not used hparams
hparams.label_smoothing = 0.1
hparams.multiply_embedding_mode = "sqrt_depth"
# add new hparams
# use raw image as input
hparams.add_hparam("image_input_type", "feature")
hparams.add_hparam("image_model_fn", "resnet_v1_152")
hparams.add_hparam("resize_side", 512)
hparams.add_hparam("height", 448)
hparams.add_hparam("width", 448)
hparams.add_hparam("distort", True)
hparams.add_hparam("train_resnet", False)
# question hidden size
# hparams.hidden_size = 512
# hparams.filter_size = 1024
# hparams.num_hidden_layers = 4
# self attention parts
# hparams.norm_type = "layer"
# hparams.layer_preprocess_sequence = "n"
# hparams.layer_postprocess_sequence = "da"
# hparams.layer_prepostprocess_dropout = 0.1
# hparams.attention_dropout = 0.1
# hparams.relu_dropout = 0.1
# hparams.add_hparam("pos", "timing")
# hparams.add_hparam("num_encoder_layers", 0)
# hparams.add_hparam("num_decoder_layers", 0)
# hparams.add_hparam("num_heads", 8)
# hparams.add_hparam("attention_key_channels", 0)
# hparams.add_hparam("attention_value_channels", 0)
# hparams.add_hparam("self_attention_type", "dot_product")
# iterative part
hparams.transformer_ffn_type = "fc"
return hparams
|
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"# hparams.relu_dropout = 0.1",
"# hparams.add_hparam(\"pos\", \"timing\")",
"# hparams.add_hparam(\"num_encoder_layers\", 0)",
"# hparams.add_hparam(\"num_decoder_layers\", 0)",
"# hparams.add_hparam(\"num_heads\", 8)",
"# hparams.add_hparam(\"attention_key_channels\", 0)",
"# hparams.add_hparam(\"attention_value_channels\", 0)",
"# hparams.add_hparam(\"self_attention_type\", \"dot_product\")",
"# iterative part",
"hparams",
".",
"transformer_ffn_type",
"=",
"\"fc\"",
"return",
"hparams"
] |
VQA attention baseline hparams.
|
[
"VQA",
"attention",
"baseline",
"hparams",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/vqa_recurrent_self_attention.py#L177-L233
|
train
|
VQA attention base hparams.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b1101111) + '\x33' + chr(0b110011) + chr(51), 53745 - 53737), ehT0Px3KOsy9('\060' + '\157' + chr(0b110111) + '\063', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + '\062' + chr(0b11100 + 0o24), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1261 - 1210) + '\x36' + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(9981 - 9870) + chr(0b101110 + 0o5) + chr(0b10001 + 0o45) + '\067', 0o10), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(897 - 786) + chr(1102 - 1050) + chr(0b100111 + 0o20), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(1479 - 1429) + chr(2541 - 2490), 0o10), ehT0Px3KOsy9(chr(48) + chr(566 - 455) + chr(0b110010) + '\x34' + chr(49), 0o10), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(111) + chr(50) + '\062' + chr(51), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + '\065' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1000000 + 0o57) + chr(0b110110) + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + chr(0b110110 + 0o1) + '\060', 37431 - 37423), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + chr(2585 - 2534) + chr(0b100011 + 0o15), 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(111) + chr(1597 - 1546) + chr(0b11010 + 0o26) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(421 - 373) + '\157' + chr(0b1111 + 0o42) + '\x36' + chr(2135 - 2080), 49956 - 49948), ehT0Px3KOsy9(chr(409 - 361) + '\x6f' + chr(0b10010 + 0o37) + '\x30' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(546 - 498) + chr(111) + chr(0b110011) + '\066' + '\x32', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x32' + chr(815 - 765) + chr(54), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b100001 + 0o22) + chr(1251 - 1202) + '\064', 47522 - 47514), ehT0Px3KOsy9(chr(48) + chr(111) + '\x32' + '\065' + chr(0b110001), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(49) + '\x33' + chr(2675 - 2620), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100011 + 0o16) + chr(0b110000) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(2044 - 1995) + '\x31' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\157' + chr(49) + chr(0b110011) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b110110 + 0o71) + chr(786 - 736) + chr(0b1111 + 0o46) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011000 + 0o27) + chr(2102 - 2051) + '\067' + '\x33', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(2168 - 2119) + chr(869 - 819) + '\x36', 49412 - 49404), ehT0Px3KOsy9('\x30' + '\x6f' + '\062' + '\x33' + chr(1871 - 1816), 39983 - 39975), ehT0Px3KOsy9(chr(1445 - 1397) + chr(7597 - 7486) + chr(1468 - 1417) + chr(0b110110) + chr(1859 - 1808), 8), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(111) + chr(2003 - 1952) + chr(0b110100) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1010001 + 0o36) + chr(0b10001 + 0o40) + chr(48) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b11000 + 0o33) + chr(0b101001 + 0o10) + '\066', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + chr(0b11000 + 0o36) + chr(0b1101 + 0o50), 59060 - 59052), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(111) + chr(0b110011) + '\x36', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + '\060' + chr(54), 0o10), ehT0Px3KOsy9(chr(553 - 505) + chr(298 - 187) + chr(0b110101) + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(0b1011 + 0o144) + '\x31' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(52) + chr(0b110010), 15293 - 15285), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + chr(53) + '\060', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110000 + 0o2) + chr(48) + chr(295 - 246), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100110 + 0o12) + '\157' + chr(1235 - 1182) + chr(0b101001 + 0o7), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf5'), chr(0b10000 + 0o124) + '\x65' + '\x63' + chr(4935 - 4824) + '\144' + chr(0b1100101))('\x75' + chr(0b1110100) + '\146' + chr(0b101101) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def _im4JlitZASy():
n4ljua2gi1Pr = VEyjCg1lULM7.universal_transformer_base()
n4ljua2gi1Pr.ix9dZyeAmUxY = ehT0Px3KOsy9('\x30' + chr(0b100011 + 0o114) + chr(0b110010) + chr(0b1 + 0o57) + chr(48) + chr(0b110000), 14449 - 14441)
n4ljua2gi1Pr.V9YwhDsFOlGK = ehT0Px3KOsy9(chr(48) + chr(7403 - 7292) + chr(0b11101 + 0o24), ord("\x08"))
n4ljua2gi1Pr.eB4rJl6fUxw9 = 0.0
n4ljua2gi1Pr.SdNSZNVkVjLh = 0.0
n4ljua2gi1Pr.Lz_s7neUzM5V = xafqLlk3kkUe(SXOLrMavuUCe(b'\xb8T\xfe\x80\x83F=\xd5\xb9\x81[\x96\xbd\xa7\x05\x18\x85\xf7\xbe\xc4*5b,\xdf\x8a$\xeb\xac\x89-\xbc\x98\x7f\xeaCtG\xcc\xde\xbf^\xf3\x92\x8e'), '\x64' + chr(101) + chr(0b1001000 + 0o33) + chr(0b100011 + 0o114) + chr(0b1000100 + 0o40) + '\145')(chr(117) + '\164' + '\x66' + chr(45) + '\070')
n4ljua2gi1Pr.fHyhoyGmdvM9 = ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + chr(0b100100 + 0o23) + chr(0b11101 + 0o30) + chr(0b110000) + chr(48), 0o10)
n4ljua2gi1Pr.Ot9HUjnkxXA_ = 0.0007
n4ljua2gi1Pr.cp7EqSq4klv1 = 0.5
n4ljua2gi1Pr.YBAB1XyoxOc5 = ehT0Px3KOsy9(chr(0b110000) + chr(8745 - 8634) + chr(1567 - 1518) + chr(52) + chr(201 - 152) + '\065' + chr(50) + chr(0b110000), 0b1000)
n4ljua2gi1Pr.g1CKJR0X4YHm = ehT0Px3KOsy9(chr(48) + chr(0b101000 + 0o107) + chr(49), 8)
n4ljua2gi1Pr.rMHVOllrHaoo = ehT0Px3KOsy9(chr(48) + chr(4782 - 4671) + chr(0b100100 + 0o15), 8)
n4ljua2gi1Pr.FSjUgdaczzRk = 0.1
n4ljua2gi1Pr.q5UEpHM7ZIlT = xafqLlk3kkUe(SXOLrMavuUCe(b'\xa8J\xe2\x87\xa8C6\xd1\xe7\x85'), chr(0b1100100) + '\x65' + chr(99) + '\x6f' + chr(0b110000 + 0o64) + chr(1779 - 1678))(chr(0b1110101) + '\164' + chr(0b1010000 + 0o26) + chr(751 - 706) + chr(3003 - 2947))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xba_\xf4\xac\x9fW2\xd3\xf2\x80'), chr(0b110100 + 0o60) + '\x65' + '\143' + chr(311 - 200) + chr(100) + chr(8582 - 8481))(chr(0b1110101) + '\164' + chr(0b1011001 + 0o15) + chr(45) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xb2V\xf1\x94\x92x:\xcf\xe3\x98F\xa7\xac\xbf\x07"'), '\x64' + chr(0b1100101) + '\143' + chr(0b111000 + 0o67) + chr(0b1100100) + chr(0b1100101))(chr(12434 - 12317) + chr(0b1110100) + chr(0b10010 + 0o124) + '\055' + chr(1217 - 1161)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xbd^\xf1\x87\x82U6'), chr(0b101100 + 0o70) + chr(0b1100101) + chr(0b1000110 + 0o35) + chr(111) + chr(0b1100100) + chr(0b1111 + 0o126))('\x75' + chr(116) + chr(7836 - 7734) + chr(1544 - 1499) + '\x38'))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xba_\xf4\xac\x9fW2\xd3\xf2\x80'), chr(0b1100100) + chr(762 - 661) + chr(99) + chr(5167 - 5056) + chr(8082 - 7982) + chr(101))('\x75' + '\164' + chr(102) + chr(529 - 484) + chr(461 - 405)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xb2V\xf1\x94\x92x>\xce\xf7\x88^\xa7\xbe\xa8'), chr(100) + chr(0b1100101) + chr(0b1100011) + chr(0b1101111) + chr(100) + chr(0b1100101))(chr(117) + '\164' + chr(8143 - 8041) + chr(721 - 676) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xa9^\xe3\x9d\x92S\x0c\xd7\xa2\xb2\x03\xcd\xea'), chr(4866 - 4766) + chr(0b1001110 + 0o27) + chr(99) + chr(6569 - 6458) + chr(100) + '\145')(chr(0b10101 + 0o140) + chr(116) + '\146' + chr(699 - 654) + chr(0b111000)))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xba_\xf4\xac\x9fW2\xd3\xf2\x80'), chr(0b1100100) + '\145' + chr(99) + '\157' + chr(0b110111 + 0o55) + '\145')('\x75' + '\x74' + '\x66' + chr(0b11110 + 0o17) + chr(1158 - 1102)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xa9^\xe3\x9a\x8dB\x0c\xd2\xfa\x89W'), chr(0b1001001 + 0o33) + chr(3619 - 3518) + chr(0b1100011) + chr(0b1101111) + chr(0b1000111 + 0o35) + '\145')(chr(0b11010 + 0o133) + chr(116) + '\x66' + chr(0b11100 + 0o21) + '\070'), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000001 + 0o56) + chr(49) + '\x30' + chr(48) + chr(48), 30050 - 30042))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xba_\xf4\xac\x9fW2\xd3\xf2\x80'), '\144' + '\x65' + chr(0b1011110 + 0o5) + chr(0b111101 + 0o62) + chr(0b1100100) + chr(0b1100101))(chr(7451 - 7334) + '\x74' + '\x66' + chr(45) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xb3^\xf9\x94\x9fS'), chr(0b1010010 + 0o22) + chr(0b110000 + 0o65) + chr(0b1001110 + 0o25) + '\x6f' + chr(0b1100100) + chr(101))(chr(8829 - 8712) + '\164' + chr(102) + chr(904 - 859) + '\070'), ehT0Px3KOsy9('\060' + chr(0b1000001 + 0o56) + '\x37' + chr(440 - 392) + chr(1943 - 1895), ord("\x08")))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xba_\xf4\xac\x9fW2\xd3\xf2\x80'), chr(100) + chr(0b1100101) + chr(0b100111 + 0o74) + chr(0b1101111) + chr(0b111001 + 0o53) + chr(101))('\165' + chr(116) + chr(102) + '\055' + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xacR\xf4\x87\x9f'), chr(8745 - 8645) + chr(0b1100101 + 0o0) + '\x63' + '\x6f' + '\x64' + '\x65')('\165' + '\x74' + chr(0b1001 + 0o135) + '\055' + chr(0b11101 + 0o33)), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\157' + '\067' + chr(0b110000) + chr(0b101110 + 0o2), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xba_\xf4\xac\x9fW2\xd3\xf2\x80'), chr(100) + chr(101) + chr(0b1010101 + 0o16) + '\157' + chr(0b1100100) + '\145')('\x75' + chr(0b1110100) + '\146' + chr(45) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b"\xbfR\xe3\x87\x98U'"), chr(100) + chr(0b1100101) + chr(0b10100 + 0o117) + chr(111) + chr(0b1100100) + chr(0b1000101 + 0o40))(chr(5242 - 5125) + '\164' + chr(673 - 571) + chr(0b10011 + 0o32) + chr(0b111000)), ehT0Px3KOsy9('\x30' + chr(111) + chr(296 - 247), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xba_\xf4\xac\x9fW2\xd3\xf2\x80'), chr(9898 - 9798) + chr(101) + chr(2273 - 2174) + chr(0b1101111) + chr(0b1000001 + 0o43) + '\x65')('\x75' + chr(0b1110100) + '\x66' + chr(0b1011 + 0o42) + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xafI\xf1\x9a\x99x!\xc4\xe0\x83W\x8c'), chr(0b11111 + 0o105) + chr(5924 - 5823) + chr(0b10000 + 0o123) + chr(0b1101111) + chr(0b1100100) + chr(0b1011000 + 0o15))('\165' + '\164' + chr(4557 - 4455) + chr(45) + '\070'), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\157' + chr(875 - 827), 0o10))
n4ljua2gi1Pr.N_pxiumQPwGS = xafqLlk3kkUe(SXOLrMavuUCe(b'\xbdX'), chr(100) + '\145' + chr(0b1100011 + 0o0) + chr(111) + '\144' + chr(5836 - 5735))(chr(0b1110101) + chr(0b1000101 + 0o57) + chr(0b1 + 0o145) + chr(45) + chr(3064 - 3008))
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_resnet.py
|
batch_norm_relu
|
def batch_norm_relu(inputs, is_training, relu=True):
"""Block of batch norm and relu."""
inputs = mtf.layers.batch_norm(
inputs,
is_training,
BATCH_NORM_DECAY,
epsilon=BATCH_NORM_EPSILON,
init_zero=(not relu))
if relu:
inputs = mtf.relu(inputs)
return inputs
|
python
|
def batch_norm_relu(inputs, is_training, relu=True):
"""Block of batch norm and relu."""
inputs = mtf.layers.batch_norm(
inputs,
is_training,
BATCH_NORM_DECAY,
epsilon=BATCH_NORM_EPSILON,
init_zero=(not relu))
if relu:
inputs = mtf.relu(inputs)
return inputs
|
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",",
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] |
Block of batch norm and relu.
|
[
"Block",
"of",
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"norm",
"and",
"relu",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_resnet.py#L38-L48
|
train
|
Block of batch norm and relu.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + '\x6f' + chr(2471 - 2421) + chr(493 - 445) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b10001 + 0o136) + chr(0b10100 + 0o35) + chr(0b10101 + 0o41) + chr(48), 0b1000), ehT0Px3KOsy9(chr(904 - 856) + chr(0b1101111) + '\061' + '\x33' + chr(0b110100), 25787 - 25779), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + chr(1464 - 1410) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(52) + '\x34', 29616 - 29608), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + chr(51) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(419 - 371) + chr(0b1101111) + '\062' + chr(0b110011) + chr(1493 - 1438), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\064' + chr(642 - 590), ord("\x08")), ehT0Px3KOsy9(chr(771 - 723) + chr(111) + chr(49) + chr(0b100 + 0o54) + chr(51), 22683 - 22675), ehT0Px3KOsy9('\x30' + chr(0b1000111 + 0o50) + '\063' + chr(1532 - 1479) + chr(0b101010 + 0o11), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(51) + chr(0b101111 + 0o3) + chr(54), 56521 - 56513), ehT0Px3KOsy9(chr(0b100000 + 0o20) + '\x6f' + chr(49) + '\x33' + chr(232 - 179), ord("\x08")), ehT0Px3KOsy9(chr(476 - 428) + chr(0b100101 + 0o112) + chr(0b110010) + chr(55), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(49) + chr(0b110101), 43169 - 43161), ehT0Px3KOsy9(chr(1860 - 1812) + chr(3937 - 3826) + chr(0b110010) + '\x37' + chr(2481 - 2429), ord("\x08")), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b111 + 0o150) + '\x33' + chr(0b11101 + 0o26) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(0b101001 + 0o7) + '\x6f' + '\x31' + chr(0b110011) + '\x31', 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2076 - 2021) + chr(0b110010 + 0o2), ord("\x08")), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1101111) + '\x31' + chr(0b1100 + 0o53) + chr(0b10010 + 0o42), 1669 - 1661), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32' + '\x32' + chr(1240 - 1189), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(9769 - 9658) + chr(50) + chr(597 - 543) + chr(59 - 7), 64325 - 64317), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110100) + chr(531 - 478), 0b1000), ehT0Px3KOsy9(chr(1173 - 1125) + '\x6f' + '\064' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + chr(0b10 + 0o56) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b1101111) + chr(805 - 756) + chr(54) + chr(1670 - 1622), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + chr(0b0 + 0o63), 50463 - 50455), ehT0Px3KOsy9(chr(1990 - 1942) + chr(111) + chr(49) + chr(103 - 55) + chr(1251 - 1202), 0o10), ehT0Px3KOsy9(chr(2281 - 2233) + '\x6f' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(111) + chr(0b110001) + chr(2355 - 2300) + chr(1028 - 979), 37186 - 37178), ehT0Px3KOsy9(chr(0b10100 + 0o34) + '\157' + chr(1316 - 1264) + '\x32', 0b1000), ehT0Px3KOsy9(chr(981 - 933) + chr(0b1101111) + '\x32' + '\066' + chr(0b110011 + 0o1), 8), ehT0Px3KOsy9(chr(180 - 132) + chr(0b1101111) + chr(0b101 + 0o55) + chr(51) + chr(0b10100 + 0o37), 37466 - 37458), ehT0Px3KOsy9(chr(189 - 141) + '\x6f' + chr(52) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(639 - 587) + '\x32', 8), ehT0Px3KOsy9('\x30' + chr(0b1001110 + 0o41) + '\062' + chr(0b10010 + 0o42) + chr(50), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(737 - 685) + '\067', 8), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(2518 - 2464) + chr(53), 57950 - 57942), ehT0Px3KOsy9(chr(1399 - 1351) + chr(0b1101111) + chr(0b100000 + 0o23) + '\x36', 2922 - 2914), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010100 + 0o33) + '\063' + '\060' + chr(1056 - 1007), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(11335 - 11224) + chr(53) + '\060', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xad'), chr(0b101111 + 0o65) + chr(4662 - 4561) + chr(8954 - 8855) + '\x6f' + chr(0b1100100) + chr(0b1001 + 0o134))(chr(117) + chr(0b1110100) + chr(1837 - 1735) + '\055' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def TWDBa8qX3MHR(vXoupepMtCXU, XQJVi3cQFN5l, Iy34imuXhyBT=ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(0b1101111) + chr(0b110001), 0b1000)):
vXoupepMtCXU = n08eHRtHxoln.layers.batch_norm(vXoupepMtCXU, XQJVi3cQFN5l, kidLGsxoKxzY, epsilon=kLqehLNcFI2o, init_zero=not Iy34imuXhyBT)
if Iy34imuXhyBT:
vXoupepMtCXU = n08eHRtHxoln.relu(vXoupepMtCXU)
return vXoupepMtCXU
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_resnet.py
|
bottleneck_block
|
def bottleneck_block(inputs,
filters,
is_training,
strides,
projection_shortcut=None,
row_blocks_dim=None,
col_blocks_dim=None):
"""Bottleneck block variant for residual networks with BN after convolutions.
Args:
inputs: a `mtf.Tensor` of shape
`[batch_dim, row_blocks, col_blocks, rows, cols, in_channels]`.
filters: `int` number of filters for the first two convolutions. Note
that the third and final convolution will use 4 times as many filters.
is_training: `bool` for whether the model is in training mode.
strides: `int` block stride. If greater than 1, this block will ultimately
downsample the input.
projection_shortcut: `function` to use for projection shortcuts (typically
a 1x1 convolution to match the filter dimensions). If None, no
projection is used and the input is passed as unchanged through the
shortcut connection.
row_blocks_dim: a mtf.Dimension, row dimension which is
spatially partitioned along mesh axis
col_blocks_dim: a mtf.Dimension, row dimension which is
spatially partitioned along mesh axis
Returns:
The output `Tensor` of the block.
"""
shortcut = inputs
filter_h_dim = mtf.Dimension("filter_height", 3)
filter_w_dim = mtf.Dimension("filter_width", 3)
one_h_dim = mtf.Dimension("filter_height", 1)
one_w_dim = mtf.Dimension("filter_width", 1)
if projection_shortcut is not None:
filters_dim = mtf.Dimension("filtersp", filters)
kernel = mtf.get_variable(
inputs.mesh, "kernel", mtf.Shape(
[one_h_dim, one_w_dim, inputs.shape.dims[-1], filters_dim]))
shortcut = projection_shortcut(inputs, kernel)
# First conv block
filters1_dim = mtf.Dimension("filters1", filters)
kernel1 = mtf.get_variable(
inputs.mesh, "kernel1", mtf.Shape(
[one_h_dim, one_w_dim, inputs.shape.dims[-1], filters1_dim]))
inputs = mtf.conv2d_with_blocks(
inputs,
kernel1,
strides=[1, 1, 1, 1],
padding="SAME",
h_blocks_dim=None, w_blocks_dim=col_blocks_dim)
# TODO(nikip): Add Dropout?
inputs = batch_norm_relu(inputs, is_training)
# Second conv block
filters2_dim = mtf.Dimension("filters2", 4*filters)
kernel2 = mtf.get_variable(
inputs.mesh, "kernel2", mtf.Shape(
[filter_h_dim, filter_w_dim, filters1_dim, filters2_dim]))
inputs = mtf.conv2d_with_blocks(
inputs,
kernel2,
strides=[1, 1, 1, 1],
padding="SAME",
h_blocks_dim=row_blocks_dim, w_blocks_dim=col_blocks_dim)
inputs = batch_norm_relu(inputs, is_training)
# Third wide conv filter block
filters3_dim = mtf.Dimension("filters3", filters)
filters3_kernel = mtf.get_variable(
inputs.mesh, "wide_kernel", mtf.Shape(
[one_h_dim, one_w_dim, filters2_dim, filters3_dim]))
inputs = mtf.conv2d_with_blocks(
inputs,
filters3_kernel,
strides,
padding="SAME",
h_blocks_dim=None, w_blocks_dim=col_blocks_dim)
# TODO(nikip): Althought the original resnet code has this batch norm, in our
# setup this is causing no gradients to be passed. Investigate further.
# inputs = batch_norm_relu(inputs, is_training, relu=True)
# TODO(nikip): Maybe add residual with a projection?
return mtf.relu(
shortcut + mtf.rename_dimension(
inputs, inputs.shape.dims[-1].name, shortcut.shape.dims[-1].name))
|
python
|
def bottleneck_block(inputs,
filters,
is_training,
strides,
projection_shortcut=None,
row_blocks_dim=None,
col_blocks_dim=None):
"""Bottleneck block variant for residual networks with BN after convolutions.
Args:
inputs: a `mtf.Tensor` of shape
`[batch_dim, row_blocks, col_blocks, rows, cols, in_channels]`.
filters: `int` number of filters for the first two convolutions. Note
that the third and final convolution will use 4 times as many filters.
is_training: `bool` for whether the model is in training mode.
strides: `int` block stride. If greater than 1, this block will ultimately
downsample the input.
projection_shortcut: `function` to use for projection shortcuts (typically
a 1x1 convolution to match the filter dimensions). If None, no
projection is used and the input is passed as unchanged through the
shortcut connection.
row_blocks_dim: a mtf.Dimension, row dimension which is
spatially partitioned along mesh axis
col_blocks_dim: a mtf.Dimension, row dimension which is
spatially partitioned along mesh axis
Returns:
The output `Tensor` of the block.
"""
shortcut = inputs
filter_h_dim = mtf.Dimension("filter_height", 3)
filter_w_dim = mtf.Dimension("filter_width", 3)
one_h_dim = mtf.Dimension("filter_height", 1)
one_w_dim = mtf.Dimension("filter_width", 1)
if projection_shortcut is not None:
filters_dim = mtf.Dimension("filtersp", filters)
kernel = mtf.get_variable(
inputs.mesh, "kernel", mtf.Shape(
[one_h_dim, one_w_dim, inputs.shape.dims[-1], filters_dim]))
shortcut = projection_shortcut(inputs, kernel)
# First conv block
filters1_dim = mtf.Dimension("filters1", filters)
kernel1 = mtf.get_variable(
inputs.mesh, "kernel1", mtf.Shape(
[one_h_dim, one_w_dim, inputs.shape.dims[-1], filters1_dim]))
inputs = mtf.conv2d_with_blocks(
inputs,
kernel1,
strides=[1, 1, 1, 1],
padding="SAME",
h_blocks_dim=None, w_blocks_dim=col_blocks_dim)
# TODO(nikip): Add Dropout?
inputs = batch_norm_relu(inputs, is_training)
# Second conv block
filters2_dim = mtf.Dimension("filters2", 4*filters)
kernel2 = mtf.get_variable(
inputs.mesh, "kernel2", mtf.Shape(
[filter_h_dim, filter_w_dim, filters1_dim, filters2_dim]))
inputs = mtf.conv2d_with_blocks(
inputs,
kernel2,
strides=[1, 1, 1, 1],
padding="SAME",
h_blocks_dim=row_blocks_dim, w_blocks_dim=col_blocks_dim)
inputs = batch_norm_relu(inputs, is_training)
# Third wide conv filter block
filters3_dim = mtf.Dimension("filters3", filters)
filters3_kernel = mtf.get_variable(
inputs.mesh, "wide_kernel", mtf.Shape(
[one_h_dim, one_w_dim, filters2_dim, filters3_dim]))
inputs = mtf.conv2d_with_blocks(
inputs,
filters3_kernel,
strides,
padding="SAME",
h_blocks_dim=None, w_blocks_dim=col_blocks_dim)
# TODO(nikip): Althought the original resnet code has this batch norm, in our
# setup this is causing no gradients to be passed. Investigate further.
# inputs = batch_norm_relu(inputs, is_training, relu=True)
# TODO(nikip): Maybe add residual with a projection?
return mtf.relu(
shortcut + mtf.rename_dimension(
inputs, inputs.shape.dims[-1].name, shortcut.shape.dims[-1].name))
|
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] |
Bottleneck block variant for residual networks with BN after convolutions.
Args:
inputs: a `mtf.Tensor` of shape
`[batch_dim, row_blocks, col_blocks, rows, cols, in_channels]`.
filters: `int` number of filters for the first two convolutions. Note
that the third and final convolution will use 4 times as many filters.
is_training: `bool` for whether the model is in training mode.
strides: `int` block stride. If greater than 1, this block will ultimately
downsample the input.
projection_shortcut: `function` to use for projection shortcuts (typically
a 1x1 convolution to match the filter dimensions). If None, no
projection is used and the input is passed as unchanged through the
shortcut connection.
row_blocks_dim: a mtf.Dimension, row dimension which is
spatially partitioned along mesh axis
col_blocks_dim: a mtf.Dimension, row dimension which is
spatially partitioned along mesh axis
Returns:
The output `Tensor` of the block.
|
[
"Bottleneck",
"block",
"variant",
"for",
"residual",
"networks",
"with",
"BN",
"after",
"convolutions",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_resnet.py#L51-L142
|
train
|
Bottleneck block variant for residual networks with BN after convolutions.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + '\063' + chr(0b110 + 0o55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + chr(0b110111) + chr(55), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + chr(0b11 + 0o61) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b0 + 0o157) + '\x31' + '\065' + chr(0b110000), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + chr(0b110000 + 0o1), 0o10), ehT0Px3KOsy9('\x30' + chr(7882 - 7771) + chr(863 - 814) + chr(570 - 517) + chr(188 - 134), ord("\x08")), ehT0Px3KOsy9(chr(337 - 289) + '\157' + chr(55) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + chr(0b100011 + 0o21), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b11100 + 0o25) + '\x31' + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(111) + '\061' + chr(0b110110) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1011011 + 0o24) + chr(0b110001) + chr(0b110010) + chr(1583 - 1531), 0o10), ehT0Px3KOsy9(chr(0b100110 + 0o12) + '\157' + '\061' + '\x36' + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(11656 - 11545) + chr(0b100111 + 0o16), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1111 + 0o140) + chr(51) + chr(54) + chr(1245 - 1197), 22026 - 22018), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(111) + chr(0b110100) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\066', 6298 - 6290), ehT0Px3KOsy9(chr(636 - 588) + chr(0b1100 + 0o143) + chr(49) + chr(1452 - 1402) + '\x33', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + chr(50) + chr(54), 26962 - 26954), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + '\x34' + '\x30', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(842 - 793) + chr(1958 - 1904) + '\x33', 8), ehT0Px3KOsy9(chr(1438 - 1390) + '\157' + '\061' + '\067' + '\x33', 58722 - 58714), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(0b1101111) + '\065', 8), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b11011 + 0o124) + '\x32' + chr(52) + chr(877 - 825), 0o10), ehT0Px3KOsy9(chr(220 - 172) + chr(0b1101111) + chr(0b110011) + chr(0b101 + 0o57) + chr(173 - 122), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + chr(0b110100), 8), ehT0Px3KOsy9(chr(755 - 707) + chr(0b1100110 + 0o11) + chr(0b101110 + 0o4) + chr(54) + '\x37', 54473 - 54465), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(6668 - 6557) + chr(49) + chr(0b110010) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10110 + 0o33) + chr(2449 - 2396) + chr(48), 8), ehT0Px3KOsy9(chr(99 - 51) + '\x6f' + chr(0b10100 + 0o36) + '\x37' + chr(0b110010 + 0o0), 26061 - 26053), ehT0Px3KOsy9(chr(907 - 859) + chr(7210 - 7099) + chr(48), 43482 - 43474), ehT0Px3KOsy9(chr(186 - 138) + chr(0b10001 + 0o136) + '\x32' + '\x32' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(840 - 792) + chr(9348 - 9237) + chr(0b110001) + '\x34' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(524 - 476) + chr(1031 - 920) + '\061' + chr(50) + '\x32', 53404 - 53396), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + chr(2390 - 2337) + '\064', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(1702 - 1653) + chr(0b100 + 0o62) + '\x35', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(261 - 210) + '\067' + chr(1765 - 1710), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\062' + chr(0b110111) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1000101 + 0o52) + chr(49) + chr(50) + '\x33', 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1224 - 1175) + '\060' + chr(0b101111 + 0o7), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b101001 + 0o13) + chr(0b110010), 3252 - 3244)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(574 - 526) + chr(0b1101111) + '\x35' + '\x30', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf5'), chr(4994 - 4894) + '\145' + chr(0b1000111 + 0o34) + '\157' + '\144' + chr(4791 - 4690))('\165' + chr(4644 - 4528) + chr(102) + chr(1543 - 1498) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def E0umIBQ8_KeA(vXoupepMtCXU, MErh319F3bgE, XQJVi3cQFN5l, r8knJmMTTKwv, CGIr4VFYxKcQ=None, st3PQA9USzCY=None, kcPz6ZZm57ld=None):
c4rbmmlcdkTg = vXoupepMtCXU
DGyZrmk8EwLH = n08eHRtHxoln.Dimension(xafqLlk3kkUe(SXOLrMavuUCe(b'\xbd\x16\x8f\x1c|\x1ccd.\x1a3\x1fq'), chr(100) + chr(0b1100101) + '\143' + chr(10495 - 10384) + '\144' + chr(0b1100101))(chr(0b1110101) + '\x74' + chr(0b1010100 + 0o22) + chr(0b101001 + 0o4) + '\x38'), ehT0Px3KOsy9(chr(2069 - 2021) + chr(0b110011 + 0o74) + chr(0b10010 + 0o41), 0o10))
iL0dFD1Cy375 = n08eHRtHxoln.Dimension(xafqLlk3kkUe(SXOLrMavuUCe(b'\xbd\x16\x8f\x1c|\x1cc{"\x17 \x1f'), '\x64' + chr(9298 - 9197) + '\143' + chr(0b1101100 + 0o3) + chr(100) + chr(2149 - 2048))(chr(0b1110101) + '\164' + '\x66' + chr(0b101101) + chr(56)), ehT0Px3KOsy9('\060' + chr(10245 - 10134) + chr(0b11001 + 0o32), 8))
pQ6t0Sh5QeUR = n08eHRtHxoln.Dimension(xafqLlk3kkUe(SXOLrMavuUCe(b'\xbd\x16\x8f\x1c|\x1ccd.\x1a3\x1fq'), chr(100) + chr(902 - 801) + chr(7162 - 7063) + chr(0b1101111) + chr(8620 - 8520) + chr(101))('\x75' + chr(0b11001 + 0o133) + chr(7955 - 7853) + '\055' + '\x38'), ehT0Px3KOsy9(chr(48) + chr(5600 - 5489) + chr(49), 44791 - 44783))
A2BIqj86gmpF = n08eHRtHxoln.Dimension(xafqLlk3kkUe(SXOLrMavuUCe(b'\xbd\x16\x8f\x1c|\x1cc{"\x17 \x1f'), chr(100) + '\145' + chr(0b1100011) + chr(0b1101111) + '\x64' + '\x65')('\165' + chr(3802 - 3686) + chr(0b1001010 + 0o34) + chr(45) + '\x38'), ehT0Px3KOsy9(chr(164 - 116) + chr(0b1010011 + 0o34) + chr(0b11010 + 0o27), 8))
if CGIr4VFYxKcQ is not None:
pkamOzkxYjUt = n08eHRtHxoln.Dimension(xafqLlk3kkUe(SXOLrMavuUCe(b'\xbd\x16\x8f\x1c|\x1cO|'), chr(9593 - 9493) + chr(0b110 + 0o137) + chr(99) + '\157' + '\x64' + '\x65')(chr(117) + '\x74' + '\x66' + '\x2d' + chr(2192 - 2136)), MErh319F3bgE)
iaILEoszmqXb = n08eHRtHxoln.get_variable(vXoupepMtCXU.mesh, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb0\x1a\x91\x06|\x02'), chr(0b101 + 0o137) + chr(4158 - 4057) + chr(0b1100011) + '\x6f' + '\144' + '\x65')(chr(0b1110101) + chr(3429 - 3313) + '\146' + '\x2d' + chr(56)), n08eHRtHxoln.Shape([pQ6t0Sh5QeUR, A2BIqj86gmpF, vXoupepMtCXU.shape.dims[-ehT0Px3KOsy9('\x30' + chr(0b1001010 + 0o45) + '\061', 8)], pkamOzkxYjUt]))
c4rbmmlcdkTg = CGIr4VFYxKcQ(vXoupepMtCXU, iaILEoszmqXb)
sdo9kiS_jtwT = n08eHRtHxoln.Dimension(xafqLlk3kkUe(SXOLrMavuUCe(b'\xbd\x16\x8f\x1c|\x1cO='), chr(0b1100100) + chr(0b1100101) + '\x63' + chr(111) + '\144' + chr(0b11 + 0o142))('\165' + chr(0b1011101 + 0o27) + chr(2883 - 2781) + chr(1272 - 1227) + chr(1563 - 1507)), MErh319F3bgE)
ronbuycn7L4E = n08eHRtHxoln.get_variable(vXoupepMtCXU.mesh, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb0\x1a\x91\x06|\x02\r'), chr(4379 - 4279) + chr(9083 - 8982) + chr(99) + '\x6f' + chr(100) + '\145')(chr(0b1110101) + chr(0b1000011 + 0o61) + chr(102) + '\055' + chr(1744 - 1688)), n08eHRtHxoln.Shape([pQ6t0Sh5QeUR, A2BIqj86gmpF, vXoupepMtCXU.shape.dims[-ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49), 8)], sdo9kiS_jtwT]))
vXoupepMtCXU = n08eHRtHxoln.conv2d_with_blocks(vXoupepMtCXU, ronbuycn7L4E, strides=[ehT0Px3KOsy9(chr(325 - 277) + chr(0b111111 + 0o60) + chr(49), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061', 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31', 8), ehT0Px3KOsy9(chr(673 - 625) + chr(7802 - 7691) + '\061', 8)], padding=xafqLlk3kkUe(SXOLrMavuUCe(b'\x88>\xae-'), '\x64' + '\x65' + '\x63' + chr(111) + '\144' + chr(0b1100101))(chr(117) + chr(11879 - 11763) + chr(0b1100110) + chr(0b110 + 0o47) + chr(56)), h_blocks_dim=None, w_blocks_dim=kcPz6ZZm57ld)
vXoupepMtCXU = TWDBa8qX3MHR(vXoupepMtCXU, XQJVi3cQFN5l)
Wi_jzJa1lqmf = n08eHRtHxoln.Dimension(xafqLlk3kkUe(SXOLrMavuUCe(b'\xbd\x16\x8f\x1c|\x1cO>'), '\x64' + '\145' + chr(2247 - 2148) + chr(111) + chr(5251 - 5151) + '\x65')(chr(117) + chr(0b1110100) + '\x66' + chr(0b11 + 0o52) + chr(0b110011 + 0o5)), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(2234 - 2123) + '\064', 0o10) * MErh319F3bgE)
ZzovVYIpUVZo = n08eHRtHxoln.get_variable(vXoupepMtCXU.mesh, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb0\x1a\x91\x06|\x02\x0e'), chr(0b1100100) + chr(101) + chr(4475 - 4376) + chr(111) + chr(0b1100100) + '\145')(chr(7685 - 7568) + chr(6765 - 6649) + chr(6796 - 6694) + chr(0b101101) + chr(0b111000)), n08eHRtHxoln.Shape([DGyZrmk8EwLH, iL0dFD1Cy375, sdo9kiS_jtwT, Wi_jzJa1lqmf]))
vXoupepMtCXU = n08eHRtHxoln.conv2d_with_blocks(vXoupepMtCXU, ZzovVYIpUVZo, strides=[ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11100 + 0o25), 8), ehT0Px3KOsy9(chr(1660 - 1612) + chr(5731 - 5620) + chr(0b110001), 8), ehT0Px3KOsy9('\x30' + '\157' + chr(49), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001), 8)], padding=xafqLlk3kkUe(SXOLrMavuUCe(b'\x88>\xae-'), chr(100) + chr(0b101001 + 0o74) + chr(0b11111 + 0o104) + chr(0b1101111) + '\144' + '\145')(chr(117) + chr(116) + chr(102) + chr(0b11011 + 0o22) + '\070'), h_blocks_dim=st3PQA9USzCY, w_blocks_dim=kcPz6ZZm57ld)
vXoupepMtCXU = TWDBa8qX3MHR(vXoupepMtCXU, XQJVi3cQFN5l)
jbtOZpD1UUTc = n08eHRtHxoln.Dimension(xafqLlk3kkUe(SXOLrMavuUCe(b'\xbd\x16\x8f\x1c|\x1cO?'), chr(0b1100100) + chr(0b110101 + 0o60) + chr(99) + chr(111) + '\144' + '\145')(chr(0b1000 + 0o155) + chr(116) + '\x66' + chr(45) + chr(289 - 233)), MErh319F3bgE)
aGadUQcN5q7r = n08eHRtHxoln.get_variable(vXoupepMtCXU.mesh, xafqLlk3kkUe(SXOLrMavuUCe(b'\xac\x16\x87\rF\x05Y~%\x168'), '\144' + chr(101) + chr(99) + chr(0b101111 + 0o100) + '\x64' + '\145')('\165' + chr(116) + '\x66' + '\055' + chr(0b111000)), n08eHRtHxoln.Shape([pQ6t0Sh5QeUR, A2BIqj86gmpF, Wi_jzJa1lqmf, jbtOZpD1UUTc]))
vXoupepMtCXU = n08eHRtHxoln.conv2d_with_blocks(vXoupepMtCXU, aGadUQcN5q7r, r8knJmMTTKwv, padding=xafqLlk3kkUe(SXOLrMavuUCe(b'\x88>\xae-'), '\x64' + chr(101) + '\143' + chr(3206 - 3095) + chr(0b11110 + 0o106) + chr(0b1100101))(chr(7794 - 7677) + chr(0b1101100 + 0o10) + chr(102) + chr(0b101101) + '\x38'), h_blocks_dim=None, w_blocks_dim=kcPz6ZZm57ld)
return xafqLlk3kkUe(n08eHRtHxoln, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa9\x1a\x8f\x1d'), chr(0b1100100) + '\x65' + chr(7764 - 7665) + chr(0b1101111) + chr(100) + chr(9884 - 9783))(chr(566 - 449) + '\164' + chr(102) + chr(911 - 866) + chr(0b111000)))(c4rbmmlcdkTg + xafqLlk3kkUe(n08eHRtHxoln, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa9\x1a\x8d\tt\x0bch"\x1e1\x19v\x99Hh'), chr(100) + chr(6487 - 6386) + '\x63' + chr(111) + '\x64' + chr(0b101001 + 0o74))(chr(117) + chr(0b1110100) + chr(3231 - 3129) + chr(0b101101) + chr(346 - 290)))(vXoupepMtCXU, xafqLlk3kkUe(vXoupepMtCXU.shape.dims[-ehT0Px3KOsy9('\060' + '\x6f' + chr(1555 - 1506), 8)], xafqLlk3kkUe(SXOLrMavuUCe(b'\x9a6\x95"K\x14ph\x0f\x1531'), '\x64' + chr(0b1100101) + chr(0b1100011) + '\157' + '\144' + '\x65')(chr(8505 - 8388) + chr(4359 - 4243) + chr(0b1100110) + chr(45) + chr(456 - 400))), xafqLlk3kkUe(c4rbmmlcdkTg.shape.dims[-ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(111) + chr(0b110001), 8)], xafqLlk3kkUe(SXOLrMavuUCe(b'\x9a6\x95"K\x14ph\x0f\x1531'), chr(2664 - 2564) + '\x65' + chr(99) + '\x6f' + chr(6360 - 6260) + '\145')(chr(117) + chr(116) + '\146' + chr(539 - 494) + '\x38'))))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_resnet.py
|
block_layer
|
def block_layer(inputs,
filters,
blocks,
strides,
is_training,
name,
row_blocks_dim=None,
col_blocks_dim=None):
"""Creates one layer of blocks for the ResNet model.
Args:
inputs: `Tensor` of size `[batch, channels, height, width]`.
filters: `int` number of filters for the first convolution of the layer.
blocks: `int` number of blocks contained in the layer.
strides: `int` stride to use for the first convolution of the layer. If
greater than 1, this layer will downsample the input.
is_training: `bool` for whether the model is training.
name: `str`name for the Tensor output of the block layer.
row_blocks_dim: a mtf.Dimension, row dimension which is
spatially partitioned along mesh axis
col_blocks_dim: a mtf.Dimension, row dimension which is
spatially partitioned along mesh axis
Returns:
The output `Tensor` of the block layer.
"""
with tf.variable_scope(name, default_name="block_layer"):
# Only the first block per block_layer uses projection_shortcut and strides
def projection_shortcut(inputs, kernel):
"""Project identity branch."""
inputs = mtf.conv2d_with_blocks(
inputs,
kernel,
strides=strides,
padding="SAME",
h_blocks_dim=None, w_blocks_dim=col_blocks_dim)
return batch_norm_relu(
inputs, is_training, relu=False)
inputs = bottleneck_block(
inputs,
filters,
is_training,
strides=strides,
projection_shortcut=projection_shortcut,
row_blocks_dim=row_blocks_dim,
col_blocks_dim=col_blocks_dim)
for i in range(1, blocks):
with tf.variable_scope("bottleneck_%d" % i):
inputs = bottleneck_block(
inputs,
filters,
is_training,
strides=[1, 1, 1, 1],
projection_shortcut=None,
row_blocks_dim=row_blocks_dim,
col_blocks_dim=col_blocks_dim)
return inputs
|
python
|
def block_layer(inputs,
filters,
blocks,
strides,
is_training,
name,
row_blocks_dim=None,
col_blocks_dim=None):
"""Creates one layer of blocks for the ResNet model.
Args:
inputs: `Tensor` of size `[batch, channels, height, width]`.
filters: `int` number of filters for the first convolution of the layer.
blocks: `int` number of blocks contained in the layer.
strides: `int` stride to use for the first convolution of the layer. If
greater than 1, this layer will downsample the input.
is_training: `bool` for whether the model is training.
name: `str`name for the Tensor output of the block layer.
row_blocks_dim: a mtf.Dimension, row dimension which is
spatially partitioned along mesh axis
col_blocks_dim: a mtf.Dimension, row dimension which is
spatially partitioned along mesh axis
Returns:
The output `Tensor` of the block layer.
"""
with tf.variable_scope(name, default_name="block_layer"):
# Only the first block per block_layer uses projection_shortcut and strides
def projection_shortcut(inputs, kernel):
"""Project identity branch."""
inputs = mtf.conv2d_with_blocks(
inputs,
kernel,
strides=strides,
padding="SAME",
h_blocks_dim=None, w_blocks_dim=col_blocks_dim)
return batch_norm_relu(
inputs, is_training, relu=False)
inputs = bottleneck_block(
inputs,
filters,
is_training,
strides=strides,
projection_shortcut=projection_shortcut,
row_blocks_dim=row_blocks_dim,
col_blocks_dim=col_blocks_dim)
for i in range(1, blocks):
with tf.variable_scope("bottleneck_%d" % i):
inputs = bottleneck_block(
inputs,
filters,
is_training,
strides=[1, 1, 1, 1],
projection_shortcut=None,
row_blocks_dim=row_blocks_dim,
col_blocks_dim=col_blocks_dim)
return inputs
|
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] |
Creates one layer of blocks for the ResNet model.
Args:
inputs: `Tensor` of size `[batch, channels, height, width]`.
filters: `int` number of filters for the first convolution of the layer.
blocks: `int` number of blocks contained in the layer.
strides: `int` stride to use for the first convolution of the layer. If
greater than 1, this layer will downsample the input.
is_training: `bool` for whether the model is training.
name: `str`name for the Tensor output of the block layer.
row_blocks_dim: a mtf.Dimension, row dimension which is
spatially partitioned along mesh axis
col_blocks_dim: a mtf.Dimension, row dimension which is
spatially partitioned along mesh axis
Returns:
The output `Tensor` of the block layer.
|
[
"Creates",
"one",
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"of",
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"for",
"the",
"ResNet",
"model",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_resnet.py#L145-L204
|
train
|
Creates a block layer for the ResNet model.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(548 - 500) + '\x6f' + '\061' + chr(0b110100) + chr(0b100011 + 0o23), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1011010 + 0o25) + chr(0b0 + 0o61) + chr(1836 - 1782) + '\063', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063' + '\x32' + '\064', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b10000 + 0o137) + chr(0b100001 + 0o20) + '\x35' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + chr(54) + chr(0b1010 + 0o53), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + chr(983 - 933) + chr(0b110000), 32047 - 32039), ehT0Px3KOsy9('\x30' + chr(8798 - 8687) + '\067' + chr(48), 0o10), ehT0Px3KOsy9(chr(1139 - 1091) + chr(111) + '\x33' + '\x31' + '\x35', 0b1000), ehT0Px3KOsy9(chr(48) + chr(11658 - 11547) + chr(0b100011 + 0o16) + chr(403 - 353) + chr(0b1110 + 0o43), 55332 - 55324), ehT0Px3KOsy9(chr(0b1000 + 0o50) + '\x6f' + '\063' + chr(49) + chr(0b11 + 0o62), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b11011 + 0o33) + chr(843 - 795), 10988 - 10980), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b111010 + 0o65) + chr(0b110111) + chr(0b100010 + 0o21), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + '\x36' + chr(0b11001 + 0o31), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(3449 - 3338) + chr(50) + chr(1058 - 1006) + '\x32', 61063 - 61055), ehT0Px3KOsy9('\x30' + '\157' + chr(0b10010 + 0o37) + chr(52) + '\x37', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(0b100111 + 0o15) + chr(52), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110000 + 0o1) + chr(0b1101 + 0o52) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(9597 - 9486) + chr(959 - 909) + '\x35' + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(1833 - 1722) + chr(0b110010) + chr(1117 - 1069) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(10276 - 10165) + chr(0b110010) + '\060', 49452 - 49444), ehT0Px3KOsy9(chr(578 - 530) + '\157' + chr(0b111 + 0o60) + chr(1827 - 1777), 41600 - 41592), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1173 - 1123) + '\065', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + '\061' + chr(0b101 + 0o57), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + chr(1611 - 1561) + chr(0b11000 + 0o34), 8), ehT0Px3KOsy9(chr(48) + chr(7316 - 7205) + '\x35' + chr(49), 45348 - 45340), ehT0Px3KOsy9('\x30' + chr(0b111100 + 0o63) + chr(0b110011) + '\064' + '\066', 16092 - 16084), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b100010 + 0o20) + chr(49) + chr(1216 - 1161), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1000001 + 0o56) + '\062' + chr(0b110110) + '\x34', 41522 - 41514), ehT0Px3KOsy9(chr(1224 - 1176) + chr(7562 - 7451) + chr(0b110001) + chr(0b110001) + '\067', 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\x32' + chr(0b100 + 0o60) + '\061', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(0b11001 + 0o34) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + chr(892 - 841) + '\x37', 0o10), ehT0Px3KOsy9('\060' + chr(0b100111 + 0o110) + '\061' + chr(52) + '\x33', 0o10), ehT0Px3KOsy9(chr(289 - 241) + chr(0b1101111) + '\061' + chr(0b1001 + 0o56) + '\060', 5630 - 5622), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + chr(0b110010) + chr(0b101000 + 0o14), 0o10), ehT0Px3KOsy9(chr(1802 - 1754) + '\x6f' + chr(51) + chr(0b100 + 0o60) + '\x31', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + '\065' + chr(0b110000), 44903 - 44895), ehT0Px3KOsy9(chr(1363 - 1315) + chr(111) + chr(0b110010) + chr(0b110100) + chr(51), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1010010 + 0o35) + '\061' + chr(0b101011 + 0o6) + chr(1075 - 1025), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b100100 + 0o16) + '\067' + chr(1798 - 1748), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + '\x6f' + '\x35' + chr(1962 - 1914), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'H'), chr(0b1100100) + chr(0b110 + 0o137) + chr(99) + chr(8197 - 8086) + chr(0b1100100) + '\x65')('\165' + chr(116) + chr(0b100000 + 0o106) + chr(0b11100 + 0o21) + chr(1606 - 1550)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def SqD5Wlqi3VQ_(vXoupepMtCXU, MErh319F3bgE, BCMwZlRkxOMF, r8knJmMTTKwv, XQJVi3cQFN5l, AIvJRzLdDfgF, st3PQA9USzCY=None, kcPz6ZZm57ld=None):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x10\x12\xa6\x00\xd42T\xa8\x0e\xbeST\x02\xc7'), chr(0b111000 + 0o54) + chr(0b1100101) + '\x63' + chr(111) + '\144' + chr(5678 - 5577))(chr(0b10000 + 0o145) + '\x74' + chr(0b1010 + 0o134) + chr(45) + chr(1254 - 1198)))(AIvJRzLdDfgF, default_name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\x1f\xbb\n\xde\x0fT\xac(\xa8B'), chr(100) + chr(0b1100101) + '\x63' + '\157' + chr(100) + '\145')(chr(6570 - 6453) + chr(116) + chr(2218 - 2116) + '\055' + chr(0b1110 + 0o52))):
def CGIr4VFYxKcQ(vXoupepMtCXU, iaILEoszmqXb):
vXoupepMtCXU = n08eHRtHxoln.conv2d_with_blocks(vXoupepMtCXU, iaILEoszmqXb, strides=r8knJmMTTKwv, padding=xafqLlk3kkUe(SXOLrMavuUCe(b'52\x99,'), chr(0b1100100) + '\x65' + chr(0b1100011) + '\x6f' + chr(0b1100100) + chr(0b1100101))(chr(4647 - 4530) + '\164' + chr(0b110101 + 0o61) + '\x2d' + '\070'), h_blocks_dim=None, w_blocks_dim=kcPz6ZZm57ld)
return TWDBa8qX3MHR(vXoupepMtCXU, XQJVi3cQFN5l, relu=ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110000), 0b1000))
vXoupepMtCXU = E0umIBQ8_KeA(vXoupepMtCXU, MErh319F3bgE, XQJVi3cQFN5l, strides=r8knJmMTTKwv, projection_shortcut=CGIr4VFYxKcQ, row_blocks_dim=st3PQA9USzCY, col_blocks_dim=kcPz6ZZm57ld)
for WVxHKyX45z_L in vQr8gNKaIaWE(ehT0Px3KOsy9(chr(0b110000) + chr(0b1001110 + 0o41) + chr(49), ord("\x08")), BCMwZlRkxOMF):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x10\x12\xa6\x00\xd42T\xa8\x0e\xbeST\x02\xc7'), '\144' + '\145' + '\x63' + '\x6f' + '\144' + chr(5585 - 5484))('\x75' + chr(0b1110100) + chr(3576 - 3474) + chr(45) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\x1c\xa0\x1d\xd95V\xa82\xa6o\x1e\x16'), chr(9715 - 9615) + chr(0b1100101) + chr(99) + chr(111) + '\x64' + chr(0b1011011 + 0o12))('\x75' + chr(116) + chr(102) + chr(45) + chr(56)) % WVxHKyX45z_L):
vXoupepMtCXU = E0umIBQ8_KeA(vXoupepMtCXU, MErh319F3bgE, XQJVi3cQFN5l, strides=[ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31', 8), ehT0Px3KOsy9('\060' + '\157' + chr(49), 8), ehT0Px3KOsy9(chr(60 - 12) + chr(0b1101111) + '\061', 8)], projection_shortcut=None, row_blocks_dim=st3PQA9USzCY, col_blocks_dim=kcPz6ZZm57ld)
return vXoupepMtCXU
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_resnet.py
|
mtf_resnet_base
|
def mtf_resnet_base():
"""Set of hyperparameters."""
hparams = common_hparams.basic_params1()
hparams.no_data_parallelism = True
hparams.use_fixed_batch_size = True
hparams.batch_size = 32
hparams.max_length = 3072
hparams.hidden_size = 256
hparams.label_smoothing = 0.0
# 8-way model-parallelism
hparams.add_hparam("mesh_shape", "batch:8")
hparams.add_hparam("layout", "batch:batch")
hparams.add_hparam("filter_size", 1024)
hparams.add_hparam("num_layers", 6)
# Share weights between input and target embeddings
hparams.shared_embedding = True
hparams.shared_embedding_and_softmax_weights = True
hparams.optimizer = "Adafactor"
hparams.learning_rate_schedule = "rsqrt_decay"
hparams.learning_rate_warmup_steps = 10000
hparams.add_hparam("d_kv", 32)
# Image related hparams
hparams.add_hparam("img_len", 32)
hparams.add_hparam("num_channels", 3)
hparams.add_hparam("row_blocks", 1)
hparams.add_hparam("col_blocks", 1)
hparams.add_hparam("rows_size", 32)
hparams.add_hparam("cols_size", 32)
# Model-specific parameters
hparams.add_hparam("layer_sizes", [3, 4, 6, 3])
hparams.add_hparam("filter_sizes", [64, 64, 128, 256, 512])
hparams.add_hparam("is_cifar", False)
# Variable init
hparams.initializer = "normal_unit_scaling"
hparams.initializer_gain = 2.
# TODO(nikip): Change optimization scheme?
hparams.learning_rate = 0.1
return hparams
|
python
|
def mtf_resnet_base():
"""Set of hyperparameters."""
hparams = common_hparams.basic_params1()
hparams.no_data_parallelism = True
hparams.use_fixed_batch_size = True
hparams.batch_size = 32
hparams.max_length = 3072
hparams.hidden_size = 256
hparams.label_smoothing = 0.0
# 8-way model-parallelism
hparams.add_hparam("mesh_shape", "batch:8")
hparams.add_hparam("layout", "batch:batch")
hparams.add_hparam("filter_size", 1024)
hparams.add_hparam("num_layers", 6)
# Share weights between input and target embeddings
hparams.shared_embedding = True
hparams.shared_embedding_and_softmax_weights = True
hparams.optimizer = "Adafactor"
hparams.learning_rate_schedule = "rsqrt_decay"
hparams.learning_rate_warmup_steps = 10000
hparams.add_hparam("d_kv", 32)
# Image related hparams
hparams.add_hparam("img_len", 32)
hparams.add_hparam("num_channels", 3)
hparams.add_hparam("row_blocks", 1)
hparams.add_hparam("col_blocks", 1)
hparams.add_hparam("rows_size", 32)
hparams.add_hparam("cols_size", 32)
# Model-specific parameters
hparams.add_hparam("layer_sizes", [3, 4, 6, 3])
hparams.add_hparam("filter_sizes", [64, 64, 128, 256, 512])
hparams.add_hparam("is_cifar", False)
# Variable init
hparams.initializer = "normal_unit_scaling"
hparams.initializer_gain = 2.
# TODO(nikip): Change optimization scheme?
hparams.learning_rate = 0.1
return hparams
|
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Set of hyperparameters.
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"Set",
"of",
"hyperparameters",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_resnet.py#L333-L376
|
train
|
Set of hyperparameters.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1828 - 1780) + '\157' + chr(0b110010) + chr(1795 - 1745) + '\065', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b11001 + 0o126) + chr(0b11 + 0o57) + chr(0b110110 + 0o1) + '\064', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b101 + 0o62) + chr(1081 - 1032), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x33' + chr(48) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(1506 - 1458) + chr(0b1101111) + chr(654 - 604) + '\065' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b10100 + 0o133) + '\064' + chr(615 - 567), 0b1000), ehT0Px3KOsy9(chr(48) + chr(8647 - 8536) + chr(0b11100 + 0o26) + '\060', 4349 - 4341), ehT0Px3KOsy9('\x30' + chr(0b110 + 0o151) + chr(2154 - 2105) + '\064' + chr(1367 - 1316), 21752 - 21744), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(595 - 545) + '\x36' + chr(1372 - 1321), 28163 - 28155), ehT0Px3KOsy9(chr(48) + chr(0b111 + 0o150) + chr(2023 - 1974) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1011 + 0o144) + chr(0b110001) + '\x33' + chr(358 - 305), 47419 - 47411), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000011 + 0o54) + chr(123 - 73) + '\060' + chr(0b11111 + 0o22), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b101110 + 0o4) + chr(0b101011 + 0o6) + '\x30', 0b1000), ehT0Px3KOsy9(chr(246 - 198) + chr(0b1101111) + '\063' + '\061', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + '\063' + chr(0b10100 + 0o41), 51510 - 51502), ehT0Px3KOsy9('\060' + '\157' + chr(947 - 896) + chr(0b110111) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33', 0o10), ehT0Px3KOsy9(chr(969 - 921) + chr(0b1101111) + chr(0b110110), 60992 - 60984), ehT0Px3KOsy9(chr(48) + '\157' + chr(647 - 593) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + '\064' + chr(50), 34280 - 34272), ehT0Px3KOsy9(chr(48) + chr(1481 - 1370) + chr(0b110011) + chr(0b101 + 0o56) + chr(52), 19296 - 19288), ehT0Px3KOsy9('\x30' + chr(111) + '\x32' + '\065' + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(111) + chr(0b101100 + 0o7) + chr(0b100010 + 0o17) + chr(653 - 603), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + '\x34' + chr(0b110000), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(51) + '\062' + chr(1022 - 973), 7520 - 7512), ehT0Px3KOsy9('\060' + chr(0b1101010 + 0o5) + '\063' + chr(0b110001) + chr(0b10101 + 0o34), ord("\x08")), ehT0Px3KOsy9(chr(1471 - 1423) + '\x6f' + chr(1913 - 1864) + '\065' + '\060', 0b1000), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(111) + '\x32' + chr(0b11111 + 0o22) + chr(0b111 + 0o57), 32490 - 32482), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(346 - 297) + '\063' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1001110 + 0o41) + chr(0b110111) + '\x34', 42241 - 42233), ehT0Px3KOsy9(chr(48) + chr(5537 - 5426) + '\x33' + chr(0b110111), 33304 - 33296), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(111) + '\x35' + chr(2117 - 2069), 41970 - 41962), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(0b1101111) + chr(49) + chr(50) + '\x34', 0o10), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(111) + chr(0b110010) + '\064' + chr(0b110000), 8), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + chr(0b10101 + 0o35) + '\x35', 43334 - 43326), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(0b110000) + '\x35', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(935 - 886) + chr(0b1101 + 0o45), 21672 - 21664), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\157' + chr(0b110101), 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\061' + chr(1583 - 1533) + chr(49), 0o10), ehT0Px3KOsy9('\x30' + chr(10353 - 10242) + chr(0b100011 + 0o17) + '\x35' + chr(0b110011), 56131 - 56123)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(8108 - 7997) + chr(1628 - 1575) + chr(48), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xbb'), '\x64' + chr(7601 - 7500) + chr(0b1100011) + chr(111) + chr(0b101011 + 0o71) + chr(101))('\x75' + '\164' + '\x66' + chr(0b101101) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def PzyeGPl6gc8_():
n4ljua2gi1Pr = vLnG3ZpOXWXZ.basic_params1()
n4ljua2gi1Pr.ahN6YYm9NJTr = ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001), ord("\x08"))
n4ljua2gi1Pr.V9YwhDsFOlGK = ehT0Px3KOsy9(chr(48) + chr(0b1 + 0o156) + chr(49), 8)
n4ljua2gi1Pr.ix9dZyeAmUxY = ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x34' + chr(0b110000), 8)
n4ljua2gi1Pr._o7pVXAdOCRy = ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\066' + chr(0b0 + 0o60) + chr(48) + chr(0b110000), 0b1000)
n4ljua2gi1Pr.qzoyXN3kdhDL = ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b10111 + 0o35) + chr(1096 - 1048) + '\060', 0b1000)
n4ljua2gi1Pr.FSjUgdaczzRk = 0.0
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xd8]\x9f\xc7Pq\x11\xd2c'), '\144' + chr(0b101001 + 0o74) + '\x63' + chr(0b1101111) + chr(100) + '\x65')('\165' + '\164' + '\x66' + chr(0b101101) + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xf8\xd9J\xa8\xf0Sx\x02\xc3k'), chr(0b1100100) + '\x65' + '\x63' + chr(0b1101111) + '\x64' + chr(0b1001011 + 0o32))(chr(0b11010 + 0o133) + chr(0b111111 + 0o65) + chr(0b1100110) + chr(0b10110 + 0o27) + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xf7\xddM\xa3\xc7\x1a('), chr(100) + chr(0b1100101) + chr(0b1100011) + '\157' + chr(100) + chr(101))('\x75' + '\x74' + '\146' + '\x2d' + chr(56)))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xd8]\x9f\xc7Pq\x11\xd2c'), '\x64' + '\x65' + chr(8350 - 8251) + '\x6f' + '\x64' + chr(0b101001 + 0o74))('\x75' + '\164' + chr(0b1100110) + '\055' + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xf9\xdd@\xaf\xdaT'), chr(0b1011001 + 0o13) + chr(0b1100001 + 0o4) + '\x63' + chr(0b10000 + 0o137) + chr(0b1100100) + '\x65')(chr(117) + chr(0b111110 + 0o66) + chr(0b111101 + 0o51) + '\x2d' + chr(0b11110 + 0o32)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xf7\xddM\xa3\xc7\x1ar\x02\xc7m5'), chr(100) + chr(4818 - 4717) + chr(0b11111 + 0o104) + chr(111) + chr(0b1100100) + chr(6140 - 6039))('\165' + '\x74' + '\146' + chr(819 - 774) + chr(56)))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xd8]\x9f\xc7Pq\x11\xd2c'), '\144' + chr(0b10101 + 0o120) + chr(99) + '\x6f' + chr(100) + '\145')(chr(0b1101011 + 0o12) + chr(8404 - 8288) + '\x66' + chr(0b101101) + chr(0b110001 + 0o7)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xf3\xd5U\xb4\xcaRO\x10\xdat8'), chr(100) + chr(0b1100101) + chr(0b11101 + 0o106) + chr(111) + chr(0b1100100) + chr(0b1100101))(chr(117) + chr(116) + '\146' + '\x2d' + chr(0b11111 + 0o31)), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1101111) + chr(0b110010) + chr(1535 - 1487) + chr(48) + chr(0b1011 + 0o45), ord("\x08")))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xd8]\x9f\xc7Pq\x11\xd2c'), chr(100) + '\145' + chr(5915 - 5816) + '\157' + '\x64' + '\x65')('\165' + chr(0b1110100) + chr(0b1100110) + chr(45) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xfb\xc9T\x9f\xc3Ai\x06\xc1}'), chr(0b1100100) + '\145' + chr(99) + '\x6f' + '\x64' + '\x65')(chr(0b100101 + 0o120) + chr(0b1110100) + '\146' + chr(0b100111 + 0o6) + chr(0b111000)), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1595 - 1541), 8))
n4ljua2gi1Pr.f7bdxoAgzo_R = ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31', 8)
n4ljua2gi1Pr.qVamxim0L2I1 = ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(111) + chr(75 - 26), 8)
n4ljua2gi1Pr.XdKNcYRObPK3 = xafqLlk3kkUe(SXOLrMavuUCe(b'\xd4\xd8X\xa6\xceCd\x0c\xc1'), chr(100) + '\x65' + chr(0b1001011 + 0o30) + chr(8655 - 8544) + chr(0b1100 + 0o130) + '\145')(chr(0b11011 + 0o132) + '\x74' + chr(0b1100110) + '\055' + chr(0b111000))
n4ljua2gi1Pr.Lz_s7neUzM5V = xafqLlk3kkUe(SXOLrMavuUCe(b'\xe7\xcfH\xb2\xdb\x7ft\x06\xd0o$'), '\144' + '\145' + chr(0b10000 + 0o123) + '\x6f' + '\144' + chr(0b1100101))(chr(5776 - 5659) + '\164' + '\146' + chr(0b101101) + '\x38')
n4ljua2gi1Pr.fHyhoyGmdvM9 = ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(111) + '\062' + chr(51) + '\x34' + chr(0b1111 + 0o43) + chr(48), 0o10)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xd8]\x9f\xc7Pq\x11\xd2c'), chr(100) + '\145' + chr(0b1100011) + '\x6f' + chr(1141 - 1041) + '\x65')(chr(0b1110101) + chr(0b1110100) + '\146' + '\x2d' + chr(0b100011 + 0o25)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xf1\xe3R\xb6'), '\144' + chr(101) + chr(0b1100011) + chr(4537 - 4426) + '\144' + chr(0b1100101))(chr(11813 - 11696) + chr(0b1110100) + chr(102) + '\055' + '\x38'), ehT0Px3KOsy9(chr(801 - 753) + chr(111) + chr(724 - 672) + chr(0b100001 + 0o17), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xd8]\x9f\xc7Pq\x11\xd2c'), '\x64' + chr(1801 - 1700) + chr(263 - 164) + chr(0b111001 + 0o66) + chr(100) + chr(101))(chr(0b1110101) + '\x74' + chr(0b1100110) + chr(0b10010 + 0o33) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xfc\xd1^\x9f\xc3E~'), '\x64' + chr(0b111 + 0o136) + chr(99) + chr(4460 - 4349) + chr(0b1100100) + '\x65')('\x75' + '\164' + chr(7504 - 7402) + chr(1826 - 1781) + chr(0b111000)), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(0b1101111) + '\x34' + chr(48), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xd8]\x9f\xc7Pq\x11\xd2c'), '\x64' + chr(0b1001010 + 0o33) + chr(0b1101 + 0o126) + '\157' + chr(0b1100100) + chr(844 - 743))('\165' + chr(0b110000 + 0o104) + chr(102) + chr(45) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xfb\xc9T\x9f\xccHq\r\xddk1\xf2'), chr(0b1100100) + chr(1050 - 949) + '\143' + '\x6f' + chr(0b1100100) + '\x65')(chr(2126 - 2009) + chr(116) + '\146' + '\055' + chr(0b111000)), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011 + 0o0), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xd8]\x9f\xc7Pq\x11\xd2c'), '\x64' + chr(101) + '\x63' + chr(0b1101111) + '\144' + chr(0b1010100 + 0o21))(chr(6554 - 6437) + '\x74' + '\x66' + '\x2d' + chr(0b10110 + 0o42)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xe7\xd3N\x9f\xcdL\x7f\x00\xd8}'), chr(0b1010100 + 0o20) + chr(0b1100101) + chr(99) + '\x6f' + chr(100) + '\x65')('\165' + chr(116) + chr(102) + '\055' + '\x38'), ehT0Px3KOsy9(chr(48) + chr(9960 - 9849) + chr(0b11110 + 0o23), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xd8]\x9f\xc7Pq\x11\xd2c'), chr(100) + chr(101) + chr(7200 - 7101) + chr(111) + chr(0b1100100) + '\145')(chr(0b1110000 + 0o5) + '\164' + chr(6295 - 6193) + chr(1487 - 1442) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xf6\xd3U\x9f\xcdL\x7f\x00\xd8}'), chr(0b100001 + 0o103) + '\x65' + chr(99) + chr(0b1101111) + '\x64' + chr(0b1011100 + 0o11))('\165' + chr(116) + chr(102) + chr(466 - 421) + '\070'), ehT0Px3KOsy9('\x30' + chr(111) + chr(1367 - 1318), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xd8]\x9f\xc7Pq\x11\xd2c'), '\144' + chr(6986 - 6885) + '\143' + '\157' + chr(100) + chr(0b1001 + 0o134))(chr(117) + chr(0b101001 + 0o113) + chr(0b1100110) + chr(0b10011 + 0o32) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xe7\xd3N\xb3\xf0Sy\x19\xd6'), chr(0b1100100) + chr(8764 - 8663) + chr(0b1100011) + '\157' + '\x64' + chr(0b1000010 + 0o43))('\165' + '\x74' + '\146' + '\055' + chr(0b111000)), ehT0Px3KOsy9(chr(219 - 171) + '\x6f' + chr(0b110100) + chr(567 - 519), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xd8]\x9f\xc7Pq\x11\xd2c'), '\144' + chr(0b10010 + 0o123) + chr(451 - 352) + chr(111) + '\x64' + chr(101))('\165' + '\164' + '\x66' + chr(45) + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xf6\xd3U\xb3\xf0Sy\x19\xd6'), chr(100) + chr(101) + '\x63' + '\x6f' + '\144' + chr(1371 - 1270))('\165' + chr(116) + chr(2167 - 2065) + chr(0b101101) + chr(0b10011 + 0o45)), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110100) + chr(1276 - 1228), 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xd8]\x9f\xc7Pq\x11\xd2c'), chr(3873 - 3773) + '\x65' + '\x63' + chr(3698 - 3587) + chr(6613 - 6513) + chr(101))('\165' + chr(0b1101010 + 0o12) + chr(0b111001 + 0o55) + '\055' + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xf9\xdd@\xa5\xdd\x7fc\n\xc9k.'), '\x64' + chr(0b1100101) + chr(0b1100011) + '\x6f' + chr(100) + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + chr(0b100010 + 0o13) + chr(56)), [ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(52), 16801 - 16793), ehT0Px3KOsy9(chr(1388 - 1340) + '\157' + chr(0b110110), 8), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b1101111) + chr(51), 8)])
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xd8]\x9f\xc7Pq\x11\xd2c'), chr(0b10011 + 0o121) + chr(101) + chr(6988 - 6889) + chr(0b1101111) + '\144' + '\145')('\165' + chr(0b1110100) + '\x66' + chr(45) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xf3\xd5U\xb4\xcaRO\x10\xdat8\xf2'), '\144' + '\145' + '\143' + chr(1347 - 1236) + chr(0b1001011 + 0o31) + chr(101))(chr(0b1001000 + 0o55) + '\164' + '\x66' + chr(45) + chr(1998 - 1942)), [ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(111) + chr(0b11000 + 0o31) + chr(48) + chr(0b10001 + 0o37), 0o10), ehT0Px3KOsy9(chr(1540 - 1492) + '\x6f' + chr(0b110001) + chr(0b110000) + chr(0b110000), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + chr(669 - 621) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(0b1011111 + 0o20) + chr(2565 - 2513) + chr(0b10001 + 0o37) + chr(0b11110 + 0o22), 8), ehT0Px3KOsy9(chr(335 - 287) + chr(8048 - 7937) + chr(0b110001) + chr(0b101 + 0o53) + chr(48) + chr(48), 0o10)])
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xd8]\x9f\xc7Pq\x11\xd2c'), chr(100) + chr(0b1100101) + '\143' + '\157' + '\x64' + chr(0b1100101))(chr(11548 - 11431) + '\164' + '\x66' + chr(0b100000 + 0o15) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xfc\xcff\xa3\xc6Fq\x11'), chr(6412 - 6312) + '\x65' + '\143' + '\x6f' + chr(100) + '\145')(chr(0b1110101) + '\x74' + chr(0b1011110 + 0o10) + '\055' + chr(56)), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(487 - 439), 0b1000))
n4ljua2gi1Pr.kwfuYzkY5C57 = xafqLlk3kkUe(SXOLrMavuUCe(b'\xfb\xd3K\xad\xceLO\x16\xddg)\xde\xfbz\xfc\x94jhR'), '\x64' + '\145' + chr(0b1000111 + 0o34) + chr(111) + chr(4720 - 4620) + chr(0b1100101))('\165' + chr(0b1000111 + 0o55) + chr(0b100000 + 0o106) + '\055' + '\070')
n4ljua2gi1Pr.S1SbCBXLapw8 = 2.0
n4ljua2gi1Pr.QGSIpd_yUNzU = 0.1
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_resnet.py
|
mtf_resnet_tiny
|
def mtf_resnet_tiny():
"""Catch bugs locally..."""
hparams = mtf_resnet_base()
hparams.num_layers = 2
hparams.hidden_size = 64
hparams.filter_size = 64
hparams.batch_size = 16
# data parallelism and model-parallelism
hparams.col_blocks = 1
hparams.mesh_shape = "batch:2"
hparams.layout = "batch:batch"
hparams.layer_sizes = [1, 2, 3]
hparams.filter_sizes = [64, 64, 64]
return hparams
|
python
|
def mtf_resnet_tiny():
"""Catch bugs locally..."""
hparams = mtf_resnet_base()
hparams.num_layers = 2
hparams.hidden_size = 64
hparams.filter_size = 64
hparams.batch_size = 16
# data parallelism and model-parallelism
hparams.col_blocks = 1
hparams.mesh_shape = "batch:2"
hparams.layout = "batch:batch"
hparams.layer_sizes = [1, 2, 3]
hparams.filter_sizes = [64, 64, 64]
return hparams
|
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] |
Catch bugs locally...
|
[
"Catch",
"bugs",
"locally",
"..."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_resnet.py#L380-L393
|
train
|
Catch bugs locally...
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\157' + '\063' + chr(52) + '\x33', 34946 - 34938), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31' + chr(0b110011 + 0o2) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(117 - 69) + chr(0b10010 + 0o135) + chr(49) + chr(0b110100) + '\x35', 0o10), ehT0Px3KOsy9(chr(1517 - 1469) + chr(9434 - 9323) + '\063' + chr(49) + chr(51), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1001 + 0o146) + chr(0b1 + 0o60) + chr(503 - 453) + '\063', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49) + '\x30' + chr(50), 0o10), ehT0Px3KOsy9(chr(1721 - 1673) + chr(111) + chr(0b11010 + 0o30) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\157' + '\065' + '\x37', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(2016 - 1965) + chr(0b10011 + 0o42), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\x37' + chr(0b11001 + 0o33), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + chr(1912 - 1864) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b11110 + 0o121) + chr(50) + chr(54) + '\063', 0o10), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b11101 + 0o122) + chr(0b110100) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1100001 + 0o16) + '\063' + '\x32' + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(5034 - 4923) + chr(564 - 513) + chr(1152 - 1104) + '\061', 52936 - 52928), ehT0Px3KOsy9('\x30' + '\x6f' + '\x32' + chr(480 - 429) + chr(0b101010 + 0o14), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b11010 + 0o27) + chr(0b110010) + chr(53), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x33' + '\067' + chr(51), 33165 - 33157), ehT0Px3KOsy9('\060' + chr(111) + chr(1907 - 1857) + chr(0b110001 + 0o1) + chr(2348 - 2299), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b10011 + 0o134) + chr(0b110001) + chr(0b110000) + chr(578 - 527), 0b1000), ehT0Px3KOsy9(chr(48) + chr(3172 - 3061) + chr(49) + chr(1790 - 1738) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + chr(172 - 124) + chr(267 - 214), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010000 + 0o37) + chr(0b110010) + chr(0b1001 + 0o55) + '\060', 0b1000), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(2027 - 1916) + chr(0b110011) + '\x36', 19789 - 19781), ehT0Px3KOsy9(chr(0b110000) + chr(5020 - 4909) + chr(0b101010 + 0o11) + '\x36', 8), ehT0Px3KOsy9(chr(48) + '\157' + chr(185 - 135) + chr(0b110011) + chr(0b101001 + 0o12), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + '\065' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + '\066', 8), ehT0Px3KOsy9(chr(447 - 399) + chr(0b1101111) + chr(0b11110 + 0o23) + chr(501 - 453) + '\x35', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + chr(2646 - 2593) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(1519 - 1471) + chr(111) + chr(854 - 805) + chr(0b110101) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(11723 - 11612) + '\066', 55465 - 55457), ehT0Px3KOsy9(chr(0b10100 + 0o34) + '\157' + '\x32' + '\067', 53535 - 53527), ehT0Px3KOsy9(chr(1871 - 1823) + chr(0b1101111) + chr(0b10000 + 0o41) + '\x34' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b101110 + 0o5), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(0b1101111) + '\x33' + chr(112 - 62) + chr(54), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(2205 - 2155) + '\x30' + chr(0b11 + 0o62), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110100) + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b11101 + 0o122) + chr(0b110011) + '\062' + chr(0b101000 + 0o14), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(111) + chr(0b101 + 0o60) + chr(0b10100 + 0o34), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xcd'), chr(3493 - 3393) + chr(4079 - 3978) + chr(99) + chr(10691 - 10580) + chr(100) + '\x65')('\x75' + chr(0b1101000 + 0o14) + chr(0b1100110) + chr(0b101101) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def oCp0uIDic6pi():
n4ljua2gi1Pr = PzyeGPl6gc8_()
n4ljua2gi1Pr.uftkTXJyNORO = ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\157' + chr(244 - 194), 0o10)
n4ljua2gi1Pr.qzoyXN3kdhDL = ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\157' + '\061' + chr(0b110000) + '\x30', ord("\x08"))
n4ljua2gi1Pr.deybX8NJ0oEI = ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + chr(0b110000) + chr(0b100111 + 0o11), 8)
n4ljua2gi1Pr.ix9dZyeAmUxY = ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b10111 + 0o33) + chr(0b11100 + 0o24), 0o10)
n4ljua2gi1Pr.hH_RAIqMLDt7 = ehT0Px3KOsy9('\x30' + chr(0b1100101 + 0o12) + chr(0b110001), ord("\x08"))
n4ljua2gi1Pr.GnGMnRt7o0q6 = xafqLlk3kkUe(SXOLrMavuUCe(b"\x81\x0b\x11\xa8;x'"), chr(3543 - 3443) + chr(0b100101 + 0o100) + chr(99) + chr(0b110010 + 0o75) + '\x64' + chr(101))(chr(0b1101001 + 0o14) + chr(116) + '\x66' + chr(45) + '\x38')
n4ljua2gi1Pr.HDH7OEwZuDah = xafqLlk3kkUe(SXOLrMavuUCe(b'\x81\x0b\x11\xa8;xwNi_)'), '\144' + '\145' + '\x63' + chr(111) + chr(7203 - 7103) + '\x65')(chr(0b1 + 0o164) + chr(116) + chr(0b1100110) + chr(866 - 821) + chr(0b111000))
n4ljua2gi1Pr.kzewOlvk6DmD = [ehT0Px3KOsy9(chr(0b110000) + chr(7177 - 7066) + chr(0b101000 + 0o11), 8), ehT0Px3KOsy9(chr(2297 - 2249) + chr(0b101110 + 0o101) + chr(846 - 796), 8), ehT0Px3KOsy9(chr(0b110000) + chr(5308 - 5197) + '\x33', 8)]
n4ljua2gi1Pr.Dvc8g9nINbiy = [ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\x6f' + chr(0b110001) + chr(0b100011 + 0o15) + chr(1844 - 1796), 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + '\x30' + chr(1572 - 1524), 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001) + '\x30' + '\x30', 8)]
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_resnet.py
|
mtf_resnet_single
|
def mtf_resnet_single():
"""Small single parameters."""
hparams = mtf_resnet_tiny()
hparams.mesh_shape = ""
hparams.layout = ""
hparams.hidden_size = 32
hparams.filter_size = 32
hparams.batch_size = 1
hparams.num_encoder_layers = 1
hparams.num_layers = 1
hparams.block_length = 16
return hparams
|
python
|
def mtf_resnet_single():
"""Small single parameters."""
hparams = mtf_resnet_tiny()
hparams.mesh_shape = ""
hparams.layout = ""
hparams.hidden_size = 32
hparams.filter_size = 32
hparams.batch_size = 1
hparams.num_encoder_layers = 1
hparams.num_layers = 1
hparams.block_length = 16
return hparams
|
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"=",
"16",
"return",
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] |
Small single parameters.
|
[
"Small",
"single",
"parameters",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_resnet.py#L397-L408
|
train
|
Small single parameters.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(0b110000 + 0o77) + '\061' + chr(1615 - 1565) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000101 + 0o52) + chr(0b110001) + chr(585 - 535) + '\x36', 0b1000), ehT0Px3KOsy9(chr(2089 - 2041) + chr(111) + chr(50) + chr(0b110110) + '\063', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(1067 - 1013) + chr(54), 12471 - 12463), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + chr(48) + chr(55), 15177 - 15169), ehT0Px3KOsy9(chr(570 - 522) + '\157' + chr(0b110001) + '\063' + '\x30', 0o10), ehT0Px3KOsy9('\x30' + chr(10356 - 10245) + '\x33' + chr(51), 0o10), ehT0Px3KOsy9('\x30' + chr(9089 - 8978) + chr(0b110011) + chr(52) + chr(1644 - 1594), 20839 - 20831), ehT0Px3KOsy9(chr(598 - 550) + '\157' + '\x33' + '\066' + chr(0b110101), 49907 - 49899), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(111) + chr(0b110101), 4417 - 4409), ehT0Px3KOsy9('\x30' + chr(0b1000100 + 0o53) + chr(0b110011) + chr(54) + chr(0b101111 + 0o5), 0o10), ehT0Px3KOsy9('\x30' + chr(0b101000 + 0o107) + '\066' + chr(0b11111 + 0o25), 0o10), ehT0Px3KOsy9(chr(0b0 + 0o60) + '\x6f' + '\x32' + chr(0b1101 + 0o45) + '\x33', 0o10), ehT0Px3KOsy9(chr(922 - 874) + chr(111) + '\061' + chr(50) + '\067', 8), ehT0Px3KOsy9('\060' + chr(0b101110 + 0o101) + chr(55) + chr(1951 - 1897), 587 - 579), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(111) + '\066' + chr(48), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + '\x36' + chr(0b110110), 10583 - 10575), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + '\066' + chr(0b100010 + 0o20), 0o10), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(0b1101111) + chr(51) + chr(0b11000 + 0o32) + chr(0b110100), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\063' + chr(1108 - 1059) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(6867 - 6756) + chr(0b101100 + 0o11) + chr(2073 - 2022), 8757 - 8749), ehT0Px3KOsy9('\x30' + chr(8282 - 8171) + chr(0b110100) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(1012 - 961) + '\063', 8), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(825 - 714) + chr(51) + '\x31' + chr(485 - 433), 0o10), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(111) + '\066' + chr(1834 - 1784), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + '\060' + '\x30', 0o10), ehT0Px3KOsy9('\x30' + chr(7189 - 7078) + chr(0b110001) + chr(0b101101 + 0o6), ord("\x08")), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\157' + chr(0b11101 + 0o24) + '\060' + chr(50), 59983 - 59975), ehT0Px3KOsy9('\x30' + chr(0b1010111 + 0o30) + '\062' + '\066' + chr(0b11000 + 0o37), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + '\x30' + chr(53), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b110 + 0o151) + chr(0b110011) + chr(50) + chr(1905 - 1851), ord("\x08")), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b1101111) + '\062' + '\x32' + '\066', 0o10), ehT0Px3KOsy9(chr(2171 - 2123) + chr(12098 - 11987) + chr(0b110011) + chr(0b110101) + chr(49), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(304 - 253) + chr(0b11000 + 0o36) + chr(49), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110101) + '\x37', 0o10), ehT0Px3KOsy9(chr(1663 - 1615) + chr(5292 - 5181) + chr(0b110010) + '\060' + '\x33', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b111 + 0o52) + '\x30' + chr(1277 - 1229), 8), ehT0Px3KOsy9('\060' + chr(0b1000011 + 0o54) + chr(0b110010) + '\x30' + '\064', 0o10), ehT0Px3KOsy9(chr(2105 - 2057) + chr(5668 - 5557) + chr(913 - 859) + '\x36', 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + chr(0b100100 + 0o15), 26930 - 26922)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x35' + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'y'), '\x64' + '\x65' + chr(99) + chr(0b1000100 + 0o53) + '\144' + '\x65')(chr(8488 - 8371) + chr(0b11010 + 0o132) + chr(102) + '\055' + chr(0b101010 + 0o16)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def L0Vym22kHz54():
n4ljua2gi1Pr = oCp0uIDic6pi()
n4ljua2gi1Pr.GnGMnRt7o0q6 = xafqLlk3kkUe(SXOLrMavuUCe(b''), '\x64' + '\145' + chr(99) + chr(0b1101111) + chr(2057 - 1957) + '\145')(chr(117) + chr(7047 - 6931) + chr(0b1100110) + '\055' + chr(56))
n4ljua2gi1Pr.HDH7OEwZuDah = xafqLlk3kkUe(SXOLrMavuUCe(b''), chr(0b1010001 + 0o23) + chr(101) + chr(0b11 + 0o140) + chr(0b1001111 + 0o40) + '\144' + chr(0b1011111 + 0o6))(chr(0b1110000 + 0o5) + chr(663 - 547) + '\x66' + chr(45) + chr(1292 - 1236))
n4ljua2gi1Pr.qzoyXN3kdhDL = ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110100) + chr(48), 0b1000)
n4ljua2gi1Pr.deybX8NJ0oEI = ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(52) + chr(48), 8)
n4ljua2gi1Pr.ix9dZyeAmUxY = ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b11011 + 0o26), 0b1000)
n4ljua2gi1Pr.RS6YkARoTleN = ehT0Px3KOsy9('\x30' + chr(0b11101 + 0o122) + chr(0b110001), 8)
n4ljua2gi1Pr.uftkTXJyNORO = ehT0Px3KOsy9(chr(1244 - 1196) + '\x6f' + '\061', 8)
n4ljua2gi1Pr.MMwtQ0bPonxt = ehT0Px3KOsy9('\060' + '\x6f' + '\062' + '\060', 0b1000)
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_resnet.py
|
mtf_resnet_base_single
|
def mtf_resnet_base_single():
"""Small single parameters."""
hparams = mtf_resnet_base()
hparams.num_layers = 6
hparams.filter_size = 256
hparams.block_length = 128
hparams.mesh_shape = ""
hparams.layout = ""
return hparams
|
python
|
def mtf_resnet_base_single():
"""Small single parameters."""
hparams = mtf_resnet_base()
hparams.num_layers = 6
hparams.filter_size = 256
hparams.block_length = 128
hparams.mesh_shape = ""
hparams.layout = ""
return hparams
|
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] |
Small single parameters.
|
[
"Small",
"single",
"parameters",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_resnet.py#L412-L420
|
train
|
Small single parameters.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(385 - 337) + '\x6f' + chr(51) + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(3861 - 3750) + '\x33' + chr(0b110101) + chr(48), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\066', 0b1000), ehT0Px3KOsy9(chr(771 - 723) + '\x6f' + chr(49) + chr(0b11010 + 0o33) + chr(2400 - 2349), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + '\x31' + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110011) + chr(1022 - 974), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x32' + chr(49) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(9700 - 9589) + '\063' + chr(1083 - 1035) + chr(2341 - 2291), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101001 + 0o6) + chr(0b110101) + '\066', 0b1000), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\x6f' + chr(49) + chr(0b11 + 0o61) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1010 + 0o47) + chr(2181 - 2128), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1010011 + 0o34) + chr(1024 - 975) + chr(1614 - 1561), 8), ehT0Px3KOsy9(chr(0b110000) + chr(11708 - 11597) + chr(663 - 612) + chr(2301 - 2251) + chr(0b110001), 56894 - 56886), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + '\061' + '\x31', 0o10), ehT0Px3KOsy9(chr(386 - 338) + '\157' + '\x31' + chr(0b110100 + 0o3) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b1101111) + '\062' + chr(0b110010), 0b1000), ehT0Px3KOsy9('\060' + chr(2016 - 1905) + chr(2460 - 2407) + chr(51), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101101 + 0o7), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1100111 + 0o10) + chr(50) + '\065' + chr(0b1011 + 0o45), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\062' + chr(0b11111 + 0o21) + '\x35', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b111100 + 0o63) + chr(0b110001 + 0o0) + chr(0b110010) + chr(0b1 + 0o65), ord("\x08")), ehT0Px3KOsy9(chr(740 - 692) + chr(0b1101111) + chr(2155 - 2106) + '\x32' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(1956 - 1908) + chr(0b1101111) + chr(0b110111) + '\064', 0o10), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b101 + 0o152) + chr(347 - 297) + chr(494 - 444) + chr(0b101110 + 0o11), 58626 - 58618), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001) + chr(0b101101 + 0o4) + chr(1578 - 1530), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b100001 + 0o22) + chr(2239 - 2190) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(1557 - 1509) + chr(0b1101111) + chr(199 - 149) + chr(0b110010) + chr(1692 - 1644), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b100111 + 0o13) + chr(601 - 546) + chr(50), 0o10), ehT0Px3KOsy9(chr(0b100101 + 0o13) + '\157' + '\062' + chr(0b110011) + chr(1034 - 985), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b101111 + 0o100) + '\061' + chr(1129 - 1078) + chr(1734 - 1685), 43433 - 43425), ehT0Px3KOsy9('\x30' + chr(9043 - 8932) + chr(1232 - 1182) + chr(54) + chr(49), 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\x6f' + chr(0b110001) + chr(0b110100) + chr(0b110000 + 0o0), 19919 - 19911), ehT0Px3KOsy9(chr(48) + chr(10306 - 10195) + '\x31' + '\x31' + chr(0b101010 + 0o15), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1001000 + 0o47) + chr(0b1111 + 0o43) + '\067' + chr(52), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(2225 - 2175) + '\065' + '\060', 8), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(0b1101111) + chr(0b110001) + '\x31' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(6143 - 6032) + '\065' + chr(0b110011), 8), ehT0Px3KOsy9('\x30' + chr(111) + '\063' + chr(0b101001 + 0o11) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\060' + chr(5163 - 5052) + chr(1773 - 1724) + chr(0b110010), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(367 - 319) + chr(0b1101111) + '\x35' + chr(48), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'0'), chr(0b1100100) + chr(101) + chr(6097 - 5998) + chr(6000 - 5889) + chr(0b1100100) + chr(0b1100101))(chr(0b1100001 + 0o24) + chr(116) + chr(0b1100110) + '\x2d' + chr(2402 - 2346)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def HRwFJsG619yQ():
n4ljua2gi1Pr = PzyeGPl6gc8_()
n4ljua2gi1Pr.uftkTXJyNORO = ehT0Px3KOsy9(chr(939 - 891) + chr(0b1010100 + 0o33) + '\066', 8)
n4ljua2gi1Pr.deybX8NJ0oEI = ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x34' + chr(0b101001 + 0o7) + '\060', 0b1000)
n4ljua2gi1Pr.MMwtQ0bPonxt = ehT0Px3KOsy9(chr(492 - 444) + '\x6f' + '\062' + '\060' + '\060', ord("\x08"))
n4ljua2gi1Pr.GnGMnRt7o0q6 = xafqLlk3kkUe(SXOLrMavuUCe(b''), chr(0b1000 + 0o134) + chr(101) + chr(0b100 + 0o137) + chr(111) + chr(100) + chr(0b1010000 + 0o25))('\x75' + chr(12693 - 12577) + chr(0b1100110) + chr(0b101101) + '\070')
n4ljua2gi1Pr.HDH7OEwZuDah = xafqLlk3kkUe(SXOLrMavuUCe(b''), '\x64' + chr(9988 - 9887) + chr(99) + '\x6f' + chr(0b1100100) + chr(0b1100101))(chr(117) + chr(116) + chr(102) + chr(45) + chr(0b101110 + 0o12))
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/mtf_resnet.py
|
mtf_resnet_base_cifar
|
def mtf_resnet_base_cifar():
"""Data parallel CIFAR parameters."""
hparams = mtf_resnet_base()
hparams.mesh_shape = "batch:32"
hparams.layoyt = "batch:batch"
hparams.batch_size = 8
hparams.num_layers = 12
hparams.block_length = 256
hparams.hidden_size = 512
hparams.filter_size = 2048
hparams.learning_rate = 0.5
hparams.learning_rate_warmup_steps = 4000
hparams.layer_preprocess_sequence = "none"
hparams.layer_postprocess_sequence = "dan"
hparams.layer_prepostprocess_dropout = 0.3
hparams.unconditional = True
return hparams
|
python
|
def mtf_resnet_base_cifar():
"""Data parallel CIFAR parameters."""
hparams = mtf_resnet_base()
hparams.mesh_shape = "batch:32"
hparams.layoyt = "batch:batch"
hparams.batch_size = 8
hparams.num_layers = 12
hparams.block_length = 256
hparams.hidden_size = 512
hparams.filter_size = 2048
hparams.learning_rate = 0.5
hparams.learning_rate_warmup_steps = 4000
hparams.layer_preprocess_sequence = "none"
hparams.layer_postprocess_sequence = "dan"
hparams.layer_prepostprocess_dropout = 0.3
hparams.unconditional = True
return hparams
|
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"512",
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"=",
"2048",
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"=",
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"unconditional",
"=",
"True",
"return",
"hparams"
] |
Data parallel CIFAR parameters.
|
[
"Data",
"parallel",
"CIFAR",
"parameters",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_resnet.py#L424-L440
|
train
|
Data parallel CIFAR parameters.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(111) + chr(1038 - 989) + chr(0b10110 + 0o34) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10001 + 0o42) + '\x30' + chr(53), 0b1000), ehT0Px3KOsy9(chr(841 - 793) + '\157' + '\x32' + chr(54) + '\063', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\062' + chr(52) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(452 - 404) + '\x6f' + '\x31' + chr(0b100101 + 0o21), 7558 - 7550), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + chr(2016 - 1965) + chr(291 - 243), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(0b100010 + 0o23) + chr(0b110011), 0o10), ehT0Px3KOsy9('\060' + chr(0b1001110 + 0o41) + '\064' + chr(0b101111 + 0o4), 25205 - 25197), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + '\067' + chr(0b110110), 26845 - 26837), ehT0Px3KOsy9(chr(1699 - 1651) + chr(0b1101111) + chr(759 - 709) + chr(48) + chr(718 - 663), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + '\x31' + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b1101111) + chr(0b11110 + 0o25) + chr(0b110110) + '\062', 15250 - 15242), ehT0Px3KOsy9('\060' + chr(3206 - 3095) + '\061' + chr(0b100111 + 0o12), 0o10), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(8875 - 8764) + chr(0b110100) + chr(1517 - 1466), 8), ehT0Px3KOsy9('\x30' + chr(11733 - 11622) + chr(1836 - 1783) + chr(2292 - 2242), 0o10), ehT0Px3KOsy9('\060' + chr(0b1011 + 0o144) + chr(1456 - 1401) + chr(177 - 125), 0b1000), ehT0Px3KOsy9(chr(2229 - 2181) + chr(0b1101111) + chr(2153 - 2102) + '\060' + '\061', 0o10), ehT0Px3KOsy9('\x30' + chr(6509 - 6398) + chr(0b110001) + chr(0b1 + 0o60) + chr(0b10100 + 0o37), 58521 - 58513), ehT0Px3KOsy9(chr(121 - 73) + chr(0b1101111) + chr(901 - 850) + '\063' + chr(0b101110 + 0o3), 0b1000), ehT0Px3KOsy9('\x30' + chr(3785 - 3674) + '\061' + chr(0b1101 + 0o47) + chr(49), 53573 - 53565), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010) + chr(0b1011 + 0o52) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b1101111) + chr(51) + chr(0b11 + 0o61) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\x31' + chr(0b110011) + chr(1001 - 953), 28203 - 28195), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(0b110010) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + '\061' + chr(55), 36383 - 36375), ehT0Px3KOsy9(chr(1725 - 1677) + '\x6f' + '\x32' + chr(52) + '\065', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(681 - 632) + '\064' + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(1104 - 1056) + '\x6f' + chr(0b100111 + 0o14) + '\060' + chr(1350 - 1298), 51326 - 51318), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(111) + '\061' + chr(49), 8), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(111) + '\x37' + chr(0b101111 + 0o3), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061' + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1101111) + chr(0b110001) + chr(50) + chr(188 - 137), 0b1000), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b1101111) + chr(1211 - 1162) + '\061' + chr(0b110011), 8), ehT0Px3KOsy9('\060' + '\157' + '\062' + chr(0b110011) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1325 - 1273) + chr(48), 54921 - 54913), ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\x6f' + '\x33' + '\066', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(10985 - 10874) + chr(0b110001) + chr(0b110001) + chr(0b110 + 0o57), ord("\x08")), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(3519 - 3408) + chr(1660 - 1607) + chr(750 - 695), 0b1000), ehT0Px3KOsy9('\060' + chr(0b111100 + 0o63) + chr(0b100000 + 0o21) + '\062' + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(55) + chr(52), 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(111) + chr(53) + chr(1600 - 1552), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'~'), chr(0b1100100) + chr(101) + chr(0b100110 + 0o75) + chr(4351 - 4240) + chr(100) + '\145')(chr(0b1110101) + '\x74' + chr(0b1100110) + chr(0b101101) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Tdt3gImMqA4N():
n4ljua2gi1Pr = PzyeGPl6gc8_()
n4ljua2gi1Pr.GnGMnRt7o0q6 = xafqLlk3kkUe(SXOLrMavuUCe(b'2\xa4\xc7\xc3f\xe2X\x11'), '\x64' + chr(0b1100101) + '\143' + chr(0b1010000 + 0o37) + chr(100) + chr(101))(chr(0b1110101) + '\164' + '\146' + chr(461 - 416) + '\070')
n4ljua2gi1Pr.Nv_BsCKYKASM = xafqLlk3kkUe(SXOLrMavuUCe(b'2\xa4\xc7\xc3f\xe2\tB\x8a\xe4\xe7'), chr(100) + chr(101) + '\143' + '\157' + '\x64' + chr(7593 - 7492))(chr(0b1110101) + '\x74' + chr(102) + chr(1274 - 1229) + chr(0b111000))
n4ljua2gi1Pr.ix9dZyeAmUxY = ehT0Px3KOsy9(chr(0b110000) + chr(0b101001 + 0o106) + chr(0b110001) + '\060', 0o10)
n4ljua2gi1Pr.uftkTXJyNORO = ehT0Px3KOsy9('\060' + chr(111) + chr(0b11011 + 0o26) + chr(1685 - 1633), 58113 - 58105)
n4ljua2gi1Pr.MMwtQ0bPonxt = ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(52) + chr(858 - 810) + '\x30', ord("\x08"))
n4ljua2gi1Pr.qzoyXN3kdhDL = ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001) + chr(898 - 850) + chr(1441 - 1393) + '\060', 0o10)
n4ljua2gi1Pr.deybX8NJ0oEI = ehT0Px3KOsy9(chr(99 - 51) + chr(0b1101111) + chr(52) + chr(48) + chr(48) + '\x30', 46056 - 46048)
n4ljua2gi1Pr.QGSIpd_yUNzU = 0.5
n4ljua2gi1Pr.fHyhoyGmdvM9 = ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100010 + 0o25) + chr(0b101110 + 0o10) + '\064' + '\x30', ord("\x08"))
n4ljua2gi1Pr.WjY1aZ7lwLOu = xafqLlk3kkUe(SXOLrMavuUCe(b'>\xaa\xdd\xc5'), chr(100) + chr(0b1100101) + chr(6456 - 6357) + chr(11942 - 11831) + chr(0b1010111 + 0o15) + chr(0b1100101))(chr(0b1101 + 0o150) + chr(10117 - 10001) + '\x66' + chr(0b101101) + '\070')
n4ljua2gi1Pr.s6T_PoakASTI = xafqLlk3kkUe(SXOLrMavuUCe(b'4\xa4\xdd'), chr(6986 - 6886) + '\x65' + chr(99) + chr(0b1101111) + '\x64' + chr(101))(chr(0b1110101) + '\x74' + chr(102) + chr(0b11101 + 0o20) + '\x38')
n4ljua2gi1Pr.RW_xSzp18UeS = 0.3
n4ljua2gi1Pr.IcYfltg0WkcT = ehT0Px3KOsy9(chr(0b110000) + chr(11992 - 11881) + '\x31', ord("\x08"))
return n4ljua2gi1Pr
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
universal_transformer_encoder
|
def universal_transformer_encoder(encoder_input,
encoder_self_attention_bias,
hparams,
name="encoder",
nonpadding=None,
save_weights_to=None,
make_image_summary=True):
"""Universal Transformer encoder function.
Prepares all the arguments and the inputs and passes it to a
universal_transformer_layer to encode the encoder_input.
Args:
encoder_input: a Tensor
encoder_self_attention_bias: bias Tensor for self-attention
(see common_attention.attention_bias())
hparams: hyperparameters for model
name: a string
nonpadding: optional Tensor with shape [batch_size, encoder_length]
indicating what positions are not padding. This must either be
passed in, which we do for "packed" datasets, or inferred from
encoder_self_attention_bias. The knowledge about padding is used
for pad_remover(efficiency) and to mask out padding in convoltutional
layers.
save_weights_to: an optional dictionary to capture attention weights
for vizualization; the weights tensor will be appended there under
a string key created from the variable scope (including name).
make_image_summary: Whether to make an attention image summary.
Returns:
y: a Tensors as the output of the encoder
extra_output: which can be used to pass extra information to the body
"""
x = encoder_input
attention_dropout_broadcast_dims = (
common_layers.comma_separated_string_to_integer_list(
getattr(hparams, "attention_dropout_broadcast_dims", "")))
with tf.variable_scope(name):
if nonpadding is not None:
padding = 1.0 - nonpadding
else:
padding = common_attention.attention_bias_to_padding(
encoder_self_attention_bias)
nonpadding = 1.0 - padding
pad_remover = None
if hparams.use_pad_remover and not common_layers.is_xla_compiled():
pad_remover = expert_utils.PadRemover(padding)
ffn_unit = functools.partial(
transformer_encoder_ffn_unit,
hparams=hparams,
nonpadding_mask=nonpadding,
pad_remover=pad_remover)
attention_unit = functools.partial(
transformer_encoder_attention_unit,
hparams=hparams,
encoder_self_attention_bias=encoder_self_attention_bias,
attention_dropout_broadcast_dims=attention_dropout_broadcast_dims,
save_weights_to=save_weights_to,
make_image_summary=make_image_summary)
x, extra_output = universal_transformer_layer(
x, hparams, ffn_unit, attention_unit, pad_remover=pad_remover)
return common_layers.layer_preprocess(x, hparams), extra_output
|
python
|
def universal_transformer_encoder(encoder_input,
encoder_self_attention_bias,
hparams,
name="encoder",
nonpadding=None,
save_weights_to=None,
make_image_summary=True):
"""Universal Transformer encoder function.
Prepares all the arguments and the inputs and passes it to a
universal_transformer_layer to encode the encoder_input.
Args:
encoder_input: a Tensor
encoder_self_attention_bias: bias Tensor for self-attention
(see common_attention.attention_bias())
hparams: hyperparameters for model
name: a string
nonpadding: optional Tensor with shape [batch_size, encoder_length]
indicating what positions are not padding. This must either be
passed in, which we do for "packed" datasets, or inferred from
encoder_self_attention_bias. The knowledge about padding is used
for pad_remover(efficiency) and to mask out padding in convoltutional
layers.
save_weights_to: an optional dictionary to capture attention weights
for vizualization; the weights tensor will be appended there under
a string key created from the variable scope (including name).
make_image_summary: Whether to make an attention image summary.
Returns:
y: a Tensors as the output of the encoder
extra_output: which can be used to pass extra information to the body
"""
x = encoder_input
attention_dropout_broadcast_dims = (
common_layers.comma_separated_string_to_integer_list(
getattr(hparams, "attention_dropout_broadcast_dims", "")))
with tf.variable_scope(name):
if nonpadding is not None:
padding = 1.0 - nonpadding
else:
padding = common_attention.attention_bias_to_padding(
encoder_self_attention_bias)
nonpadding = 1.0 - padding
pad_remover = None
if hparams.use_pad_remover and not common_layers.is_xla_compiled():
pad_remover = expert_utils.PadRemover(padding)
ffn_unit = functools.partial(
transformer_encoder_ffn_unit,
hparams=hparams,
nonpadding_mask=nonpadding,
pad_remover=pad_remover)
attention_unit = functools.partial(
transformer_encoder_attention_unit,
hparams=hparams,
encoder_self_attention_bias=encoder_self_attention_bias,
attention_dropout_broadcast_dims=attention_dropout_broadcast_dims,
save_weights_to=save_weights_to,
make_image_summary=make_image_summary)
x, extra_output = universal_transformer_layer(
x, hparams, ffn_unit, attention_unit, pad_remover=pad_remover)
return common_layers.layer_preprocess(x, hparams), extra_output
|
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Universal Transformer encoder function.
Prepares all the arguments and the inputs and passes it to a
universal_transformer_layer to encode the encoder_input.
Args:
encoder_input: a Tensor
encoder_self_attention_bias: bias Tensor for self-attention
(see common_attention.attention_bias())
hparams: hyperparameters for model
name: a string
nonpadding: optional Tensor with shape [batch_size, encoder_length]
indicating what positions are not padding. This must either be
passed in, which we do for "packed" datasets, or inferred from
encoder_self_attention_bias. The knowledge about padding is used
for pad_remover(efficiency) and to mask out padding in convoltutional
layers.
save_weights_to: an optional dictionary to capture attention weights
for vizualization; the weights tensor will be appended there under
a string key created from the variable scope (including name).
make_image_summary: Whether to make an attention image summary.
Returns:
y: a Tensors as the output of the encoder
extra_output: which can be used to pass extra information to the body
|
[
"Universal",
"Transformer",
"encoder",
"function",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L62-L128
|
train
|
Universal Transformer encoder function.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\x6f' + chr(583 - 533) + chr(898 - 850) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + chr(53) + chr(48), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1001000 + 0o47) + chr(50) + chr(90 - 40) + '\064', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1000011 + 0o54) + chr(50) + '\x30' + chr(2228 - 2180), 26493 - 26485), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(51) + chr(53) + chr(52), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101110 + 0o1) + chr(0b110010) + chr(0b110111) + chr(0b110101), 18694 - 18686), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b1101111) + chr(0b101101 + 0o6) + chr(992 - 943) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\060' + chr(4217 - 4106) + chr(0b1000 + 0o54), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(0b101 + 0o57) + chr(50), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b110011 + 0o74) + chr(0b11111 + 0o25) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b10110 + 0o32) + '\157' + chr(51) + chr(0b11000 + 0o31) + chr(80 - 28), 0o10), ehT0Px3KOsy9('\060' + chr(7993 - 7882) + chr(0b110010) + chr(51) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1110 + 0o43) + chr(0b110001 + 0o4), 48905 - 48897), ehT0Px3KOsy9('\060' + chr(5197 - 5086) + chr(0b110010) + chr(0b1010 + 0o46) + '\x34', 5022 - 5014), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(0b1101111) + '\062' + '\x32' + chr(0b101101 + 0o5), 31530 - 31522), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(50) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110110) + chr(0b110100), 30959 - 30951), ehT0Px3KOsy9(chr(2090 - 2042) + '\x6f' + chr(1455 - 1403) + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b111 + 0o53) + '\060' + '\x32', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(1693 - 1644) + chr(51) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b1001110 + 0o41) + '\x32' + chr(0b100001 + 0o23) + chr(1878 - 1830), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(50) + chr(0b110011) + '\x31', 32701 - 32693), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + '\065', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(2428 - 2377) + chr(0b110000), 18 - 10), ehT0Px3KOsy9(chr(2298 - 2250) + '\157' + '\x33' + '\x31' + chr(0b110001), 57852 - 57844), ehT0Px3KOsy9(chr(1580 - 1532) + '\x6f' + chr(51) + chr(0b11101 + 0o32) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + '\067' + '\x36', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x36' + chr(0b110 + 0o57), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b101011 + 0o6) + chr(54) + chr(49), 0b1000), ehT0Px3KOsy9(chr(61 - 13) + '\x6f' + chr(0b101001 + 0o12) + chr(0b100100 + 0o22) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x31', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1010101 + 0o32) + '\x31' + chr(0b101000 + 0o15) + chr(54), 16586 - 16578), ehT0Px3KOsy9(chr(905 - 857) + '\157' + '\061' + chr(396 - 345) + chr(0b10000 + 0o42), 57688 - 57680), ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\157' + chr(52), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + '\x37' + chr(1325 - 1271), 8), ehT0Px3KOsy9(chr(0b10 + 0o56) + '\x6f' + chr(0b110011 + 0o0) + chr(0b101000 + 0o14) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(1505 - 1457) + chr(111) + '\x31' + chr(51) + '\x37', 8), ehT0Px3KOsy9(chr(1924 - 1876) + chr(0b1101111) + chr(50) + chr(1755 - 1706), 8), ehT0Px3KOsy9(chr(48) + chr(2566 - 2455) + chr(0b110011) + '\062' + '\x35', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(197 - 146) + chr(48) + chr(0b10011 + 0o35), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(111) + chr(2333 - 2280) + chr(1693 - 1645), 47589 - 47581)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xad'), chr(0b1100100) + '\x65' + chr(7804 - 7705) + '\157' + chr(100) + '\x65')(chr(0b1110101) + chr(0b1110100) + '\146' + chr(0b101101) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def o5Us62Jdoy5n(LDEM1Zag9l0P, cMrr2bkEBgTQ, n4ljua2gi1Pr, AIvJRzLdDfgF=xafqLlk3kkUe(SXOLrMavuUCe(b'\xe6\xc6\xf7\xef\x88\xd8\xba'), chr(9741 - 9641) + chr(101) + chr(0b1100011) + '\157' + chr(0b101100 + 0o70) + '\x65')(chr(0b100101 + 0o120) + '\x74' + chr(102) + chr(1523 - 1478) + chr(56)), qpPhEurkAWxO=None, zWaF_2VBEDjk=None, NC2xHNLwzxcH=ehT0Px3KOsy9('\x30' + '\x6f' + chr(1309 - 1260), 8)):
OeWW0F1dBPRQ = LDEM1Zag9l0P
UNqT6jwzCz6Y = jSKPaHwSAfVv.comma_separated_string_to_integer_list(xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe2\xdc\xe0\xe5\x82\xc9\xa1k\x8c|\xa8\xedb\xf4\xfdd@\x7f\xe0-\xcf\xf8q{\xa8\x8e\xcaj\x15\x9fl\x1d'), chr(0b1100100) + chr(0b100010 + 0o103) + chr(0b100001 + 0o102) + chr(0b1010011 + 0o34) + chr(5900 - 5800) + '\145')('\165' + chr(0b1110100) + chr(102) + chr(45) + chr(1109 - 1053)), xafqLlk3kkUe(SXOLrMavuUCe(b''), chr(100) + '\x65' + chr(0b1010011 + 0o20) + chr(0b10000 + 0o137) + chr(0b1000 + 0o134) + chr(0b1100101))(chr(0b100100 + 0o121) + '\x74' + chr(102) + chr(1594 - 1549) + chr(0b110111 + 0o1))))
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf5\xc9\xe6\xe9\x8d\xdf\xa4a\xbdP\xaf\xf0}\xe1'), '\144' + '\x65' + chr(1345 - 1246) + '\157' + chr(8036 - 7936) + chr(0b1001011 + 0o32))('\x75' + chr(7390 - 7274) + '\x66' + '\055' + chr(1997 - 1941)))(AIvJRzLdDfgF):
if qpPhEurkAWxO is not None:
TFLseEYASEKG = 1.0 - qpPhEurkAWxO
else:
TFLseEYASEKG = WOnrfm4dlYcf.attention_bias_to_padding(cMrr2bkEBgTQ)
qpPhEurkAWxO = 1.0 - TFLseEYASEKG
bLDzE_zU4vXa = None
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf6\xdb\xf1\xdf\x9c\xdc\xac[\x90F\xa1\xf0{\xe1\xe0'), chr(0b1010110 + 0o16) + chr(101) + '\143' + '\x6f' + chr(0b101100 + 0o70) + '\x65')(chr(610 - 493) + '\x74' + chr(0b1100110) + chr(414 - 369) + '\x38')) and (not xafqLlk3kkUe(jSKPaHwSAfVv, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\xdb\xcb\xf8\x80\xdc\x97g\x8dN\xbc\xf6a\xe1\xf6'), '\144' + chr(101) + chr(99) + '\x6f' + chr(0b1100100) + chr(0b1100101))(chr(117) + chr(5338 - 5222) + chr(0b1100110) + chr(0b10010 + 0o33) + '\x38'))()):
bLDzE_zU4vXa = mpdtyez0NuRm.PadRemover(TFLseEYASEKG)
SHRtjNoPzosY = E6ula8_Zv1yl.partial(QXjFvKdTudYV, hparams=n4ljua2gi1Pr, nonpadding_mask=qpPhEurkAWxO, pad_remover=bLDzE_zU4vXa)
ek3fs6JEXh0d = E6ula8_Zv1yl.partial(LemVfCmDdV4S, hparams=n4ljua2gi1Pr, encoder_self_attention_bias=cMrr2bkEBgTQ, attention_dropout_broadcast_dims=UNqT6jwzCz6Y, save_weights_to=zWaF_2VBEDjk, make_image_summary=NC2xHNLwzxcH)
(OeWW0F1dBPRQ, kpP2CsboxNzE) = k8qNqK25xcMa(OeWW0F1dBPRQ, n4ljua2gi1Pr, SHRtjNoPzosY, ek3fs6JEXh0d, pad_remover=bLDzE_zU4vXa)
return (xafqLlk3kkUe(jSKPaHwSAfVv, xafqLlk3kkUe(SXOLrMavuUCe(b'\xef\xc9\xed\xe5\x9e\xe2\xb8v\x87S\xbe\xf0n\xe1\xe1b'), chr(0b1011001 + 0o13) + chr(135 - 34) + '\143' + chr(111) + chr(0b1100100) + chr(0b1100101))(chr(0b111000 + 0o75) + '\164' + chr(8938 - 8836) + chr(0b101101) + '\070'))(OeWW0F1dBPRQ, n4ljua2gi1Pr), kpP2CsboxNzE)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
universal_transformer_layer
|
def universal_transformer_layer(x,
hparams,
ffn_unit,
attention_unit,
pad_remover=None):
"""Core function applying the universal transformer layer.
Args:
x: input
hparams: model hyper-parameters
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
the output tensor, extra output (can be memory, ponder time, etc.)
Raises:
ValueError: Unknown recurrence type
"""
def add_vanilla_transformer_layer(x, num_layers, name):
"""Passes the input through num_layers of vanilla transformer layers.
Args:
x: input
num_layers: number of layers
name: string, prefix of layer names
Returns:
output of vanilla_transformer_layer
"""
if hparams.add_position_timing_signal:
# In case of add_position_timing_signal=true, we set hparams.pos=None
# and add position timing signal at the beginning of each step, so for
# the vanilla transformer, we need to add timing signal here.
x = common_attention.add_timing_signal_1d(x)
for layer in range(num_layers):
with tf.variable_scope(name + "layer_%d" % layer):
x = ffn_unit(attention_unit(x))
return x
with tf.variable_scope("universal_transformer_%s" % hparams.recurrence_type):
if (hparams.mix_with_transformer and
"before_ut" in hparams.mix_with_transformer):
x = add_vanilla_transformer_layer(x, hparams.num_mixedin_layers,
"before_ut_")
if hparams.recurrence_type == "act":
output, extra_output = universal_transformer_act(
x, hparams, ffn_unit, attention_unit)
else: # for all the other recurrency types with fixed number of steps
ut_function, initializer = get_ut_layer(x, hparams, ffn_unit,
attention_unit, pad_remover)
output, _, extra_output = tf.foldl(
ut_function, tf.range(hparams.num_rec_steps),
initializer=initializer)
# Right now, this is only possible when the transition function is an lstm
if (hparams.recurrence_type == "lstm" and
hparams.get("use_memory_as_final_state", False)):
output = extra_output
if (hparams.mix_with_transformer and
"after_ut" in hparams.mix_with_transformer):
output = add_vanilla_transformer_layer(output, hparams.num_mixedin_layers,
"after_ut_")
return output, extra_output
|
python
|
def universal_transformer_layer(x,
hparams,
ffn_unit,
attention_unit,
pad_remover=None):
"""Core function applying the universal transformer layer.
Args:
x: input
hparams: model hyper-parameters
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
the output tensor, extra output (can be memory, ponder time, etc.)
Raises:
ValueError: Unknown recurrence type
"""
def add_vanilla_transformer_layer(x, num_layers, name):
"""Passes the input through num_layers of vanilla transformer layers.
Args:
x: input
num_layers: number of layers
name: string, prefix of layer names
Returns:
output of vanilla_transformer_layer
"""
if hparams.add_position_timing_signal:
# In case of add_position_timing_signal=true, we set hparams.pos=None
# and add position timing signal at the beginning of each step, so for
# the vanilla transformer, we need to add timing signal here.
x = common_attention.add_timing_signal_1d(x)
for layer in range(num_layers):
with tf.variable_scope(name + "layer_%d" % layer):
x = ffn_unit(attention_unit(x))
return x
with tf.variable_scope("universal_transformer_%s" % hparams.recurrence_type):
if (hparams.mix_with_transformer and
"before_ut" in hparams.mix_with_transformer):
x = add_vanilla_transformer_layer(x, hparams.num_mixedin_layers,
"before_ut_")
if hparams.recurrence_type == "act":
output, extra_output = universal_transformer_act(
x, hparams, ffn_unit, attention_unit)
else: # for all the other recurrency types with fixed number of steps
ut_function, initializer = get_ut_layer(x, hparams, ffn_unit,
attention_unit, pad_remover)
output, _, extra_output = tf.foldl(
ut_function, tf.range(hparams.num_rec_steps),
initializer=initializer)
# Right now, this is only possible when the transition function is an lstm
if (hparams.recurrence_type == "lstm" and
hparams.get("use_memory_as_final_state", False)):
output = extra_output
if (hparams.mix_with_transformer and
"after_ut" in hparams.mix_with_transformer):
output = add_vanilla_transformer_layer(output, hparams.num_mixedin_layers,
"after_ut_")
return output, extra_output
|
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"\"\"\"Passes the input through num_layers of vanilla transformer layers.\n\n Args:\n x: input\n num_layers: number of layers\n name: string, prefix of layer names\n\n Returns:\n output of vanilla_transformer_layer\n \"\"\"",
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] |
Core function applying the universal transformer layer.
Args:
x: input
hparams: model hyper-parameters
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
the output tensor, extra output (can be memory, ponder time, etc.)
Raises:
ValueError: Unknown recurrence type
|
[
"Core",
"function",
"applying",
"the",
"universal",
"transformer",
"layer",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L194-L265
|
train
|
Core function applying the universal transformer layer.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(11704 - 11593) + '\062' + chr(51) + chr(990 - 935), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(2026 - 1972) + chr(0b110111), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b101010 + 0o105) + '\x32' + '\061' + chr(2350 - 2295), ord("\x08")), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b1101111) + chr(51) + '\x34' + '\064', 0o10), ehT0Px3KOsy9('\060' + chr(4173 - 4062) + chr(2306 - 2255) + '\x36', 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1011001 + 0o26) + chr(431 - 382) + chr(49) + '\x31', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1920 - 1871) + chr(0b110110) + chr(1648 - 1600), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\063' + '\064' + chr(1510 - 1461), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(53), 39171 - 39163), ehT0Px3KOsy9('\060' + chr(0b1001111 + 0o40) + chr(0b11110 + 0o25) + '\067' + '\x34', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(51) + '\061' + '\060', 0b1000), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(111) + '\x33' + chr(0b110010) + chr(762 - 714), 0o10), ehT0Px3KOsy9(chr(1427 - 1379) + '\157' + chr(0b11011 + 0o32) + chr(927 - 873), ord("\x08")), ehT0Px3KOsy9('\060' + chr(10003 - 9892) + chr(1892 - 1842) + chr(2338 - 2288) + chr(50), 29540 - 29532), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + chr(774 - 725) + chr(55), 8), ehT0Px3KOsy9(chr(389 - 341) + chr(111) + chr(2092 - 2042) + chr(55), ord("\x08")), ehT0Px3KOsy9('\060' + chr(713 - 602) + '\x33' + chr(1199 - 1146) + chr(0b1101 + 0o44), 32173 - 32165), ehT0Px3KOsy9(chr(0b110000) + chr(0b100100 + 0o113) + '\x32' + chr(282 - 230) + chr(1993 - 1944), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(1808 - 1697) + chr(0b110110), 62868 - 62860), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + chr(52) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010 + 0o1) + '\x33' + chr(0b111 + 0o55), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b110010) + chr(2274 - 2225) + '\x36', 0o10), ehT0Px3KOsy9('\x30' + chr(1080 - 969) + chr(0b110011) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1311 - 1261) + chr(939 - 891), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1111 + 0o42) + chr(0b1110 + 0o46) + chr(0b1101 + 0o51), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b1101 + 0o46) + chr(0b110000) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(1862 - 1807) + chr(1720 - 1672), 19065 - 19057), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(111) + chr(0b110010 + 0o1) + '\x30' + chr(1093 - 1043), 0o10), ehT0Px3KOsy9(chr(1466 - 1418) + chr(111) + chr(0b1110 + 0o43) + '\063' + chr(0b1011 + 0o53), 15412 - 15404), ehT0Px3KOsy9(chr(184 - 136) + chr(111) + chr(0b110011) + chr(0b110001) + chr(0b111 + 0o56), ord("\x08")), ehT0Px3KOsy9(chr(547 - 499) + '\157' + chr(0b110011) + '\063' + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110011) + chr(2333 - 2280) + chr(0b110010 + 0o3), 0o10), ehT0Px3KOsy9(chr(203 - 155) + chr(0b1101111) + '\064' + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(0b1101111) + chr(49) + chr(0b100110 + 0o21), 0o10), ehT0Px3KOsy9(chr(403 - 355) + '\x6f' + chr(0b11011 + 0o26) + chr(0b0 + 0o65) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b100 + 0o153) + chr(0b110011) + chr(0b110001 + 0o1) + '\060', 8), ehT0Px3KOsy9('\x30' + chr(6718 - 6607) + '\x36' + '\061', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(971 - 860) + chr(0b10100 + 0o41) + chr(54), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50) + chr(0b110101) + chr(0b1010 + 0o46), 0o10), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\x6f' + chr(49) + chr(429 - 375) + chr(52), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\157' + chr(0b0 + 0o65) + chr(0b110000), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1'), '\x64' + chr(0b10010 + 0o123) + chr(99) + chr(0b1101111) + '\144' + '\145')(chr(0b100010 + 0o123) + '\x74' + chr(0b1111 + 0o127) + '\055' + chr(1800 - 1744)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def k8qNqK25xcMa(OeWW0F1dBPRQ, n4ljua2gi1Pr, SHRtjNoPzosY, ek3fs6JEXh0d, bLDzE_zU4vXa=None):
def zKX2QWkP1IU9(OeWW0F1dBPRQ, uftkTXJyNORO, AIvJRzLdDfgF):
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfe\x93\xeb\xbbn&\x03\x88q\x95\xa7\xbeq\xe6\xe6z\x80\xcfa8\xaf\xe7{~\x07\xaf'), '\x64' + '\145' + '\143' + chr(6028 - 5917) + chr(1565 - 1465) + chr(0b1100101))('\x75' + chr(0b1110100) + chr(7379 - 7277) + '\x2d' + '\070')):
OeWW0F1dBPRQ = WOnrfm4dlYcf.add_timing_signal_1d(OeWW0F1dBPRQ)
for wgamNHppspXj in vQr8gNKaIaWE(uftkTXJyNORO):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe9\x96\xfd\x8d\x7f+\x1c\x84Z\x8f\xab\xbf^\xf7'), chr(2882 - 2782) + '\145' + '\x63' + chr(111) + chr(0b110000 + 0o64) + chr(8809 - 8708))(chr(0b1110101) + chr(0b1110100) + '\x66' + chr(0b101101) + '\070'))(AIvJRzLdDfgF + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf3\x96\xf6\x81l\x16U\x85'), chr(0b11 + 0o141) + '\145' + '\x63' + chr(0b1101111) + chr(1388 - 1288) + chr(5608 - 5507))('\165' + '\164' + chr(102) + '\055' + chr(1586 - 1530)) % wgamNHppspXj):
OeWW0F1dBPRQ = SHRtjNoPzosY(ek3fs6JEXh0d(OeWW0F1dBPRQ))
return OeWW0F1dBPRQ
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe9\x96\xfd\x8d\x7f+\x1c\x84Z\x8f\xab\xbf^\xf7'), chr(100) + chr(0b1000001 + 0o44) + chr(4031 - 3932) + '\157' + chr(100) + '\145')(chr(0b100111 + 0o116) + chr(0b111110 + 0o66) + chr(1812 - 1710) + chr(0b101101) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\x99\xe6\x92{;\x03\x80i\xa3\xbc\xa2O\xfc\xfcq\x86\xd3k\x02\xae\xd19c'), chr(0b1100100) + chr(0b1100101) + chr(7850 - 7751) + chr(0b1011111 + 0o20) + chr(100) + chr(7160 - 7059))('\x75' + chr(12074 - 11958) + chr(0b10000 + 0o126) + chr(0b101101) + chr(0b111000)) % xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\x92\xec\x91l;\x15\x8ff\x99\x97\xa4W\xe2\xea'), chr(0b100110 + 0o76) + chr(0b100101 + 0o100) + chr(317 - 218) + '\x6f' + '\144' + '\145')('\165' + '\164' + chr(3993 - 3891) + chr(826 - 781) + chr(56)))):
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf2\x9e\xf7\xbbi \x04\x89Z\x88\xba\xb1@\xe1\xe9x\x9b\xccc\x15'), chr(0b1001100 + 0o30) + chr(101) + '\143' + chr(111) + chr(0b1100100) + chr(5162 - 5061))(chr(117) + chr(8499 - 8383) + chr(102) + chr(0b101011 + 0o2) + chr(56))) and xafqLlk3kkUe(SXOLrMavuUCe(b'\xfd\x92\xe9\x8bl,/\x94q'), '\144' + '\x65' + chr(1652 - 1553) + chr(2548 - 2437) + chr(6119 - 6019) + '\145')('\x75' + chr(221 - 105) + '\x66' + chr(0b101101) + '\x38') in xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf2\x9e\xf7\xbbi \x04\x89Z\x88\xba\xb1@\xe1\xe9x\x9b\xccc\x15'), chr(0b101001 + 0o73) + chr(0b1100101) + chr(0b1100011) + chr(111) + chr(100) + chr(0b111111 + 0o46))(chr(117) + chr(0b1100100 + 0o20) + '\x66' + chr(1370 - 1325) + chr(0b1110 + 0o52))):
OeWW0F1dBPRQ = zKX2QWkP1IU9(OeWW0F1dBPRQ, n4ljua2gi1Pr.num_mixedin_layers, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfd\x92\xe9\x8bl,/\x94q\xa3'), '\x64' + chr(0b111011 + 0o52) + '\143' + chr(6649 - 6538) + chr(0b101001 + 0o73) + chr(1955 - 1854))('\x75' + chr(0b1011101 + 0o27) + chr(102) + chr(45) + chr(56)))
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\x92\xec\x91l;\x15\x8ff\x99\x97\xa4W\xe2\xea'), chr(0b1100100) + chr(0b1100101) + '\x63' + chr(0b1101111) + chr(100) + chr(5889 - 5788))(chr(117) + chr(369 - 253) + chr(102) + chr(0b100100 + 0o11) + '\070')) == xafqLlk3kkUe(SXOLrMavuUCe(b'\xfe\x94\xfb'), '\144' + chr(6802 - 6701) + '\x63' + '\157' + chr(100) + '\145')(chr(0b1100 + 0o151) + '\x74' + chr(7308 - 7206) + chr(0b101101) + chr(0b111000)):
(e1jVqMSBZ01Y, kpP2CsboxNzE) = kLAnEEMTVVI2(OeWW0F1dBPRQ, n4ljua2gi1Pr, SHRtjNoPzosY, ek3fs6JEXh0d)
else:
(bJ8teQTW0l5A, kwfuYzkY5C57) = NCjymzLXjqvm(OeWW0F1dBPRQ, n4ljua2gi1Pr, SHRtjNoPzosY, ek3fs6JEXh0d, bLDzE_zU4vXa)
(e1jVqMSBZ01Y, VNGQdHSFPrso, kpP2CsboxNzE) = IDJ2eXGCBCDu.foldl(bJ8teQTW0l5A, IDJ2eXGCBCDu.range(n4ljua2gi1Pr.num_rec_steps), initializer=kwfuYzkY5C57)
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\x92\xec\x91l;\x15\x8ff\x99\x97\xa4W\xe2\xea'), chr(100) + chr(0b1100101) + '\143' + chr(0b10000 + 0o137) + chr(100) + chr(0b11110 + 0o107))('\x75' + '\x74' + '\x66' + '\055' + chr(0b101110 + 0o12))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\xf3\x84\xfb\x89'), chr(0b101 + 0o137) + '\x65' + chr(8819 - 8720) + '\x6f' + '\x64' + '\145')(chr(0b1 + 0o164) + chr(0b1110100) + '\x66' + '\055' + chr(1969 - 1913)) and xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf8\x92\xfb'), chr(0b1100100) + chr(101) + '\x63' + chr(111) + chr(100) + chr(101))(chr(117) + chr(0b1101001 + 0o13) + '\x66' + chr(0b101100 + 0o1) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\x84\xea\xbbs,\x1d\x8ew\x85\x97\xb1]\xcd\xe9~\x87\xc0j8\xaf\xfa}d\x03'), chr(100) + chr(101) + chr(99) + chr(111) + chr(0b1000100 + 0o40) + '\x65')(chr(117) + '\x74' + '\x66' + chr(0b101101) + chr(621 - 565)), ehT0Px3KOsy9('\x30' + chr(7442 - 7331) + chr(0b11011 + 0o25), ord("\x08"))):
e1jVqMSBZ01Y = kpP2CsboxNzE
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf2\x9e\xf7\xbbi \x04\x89Z\x88\xba\xb1@\xe1\xe9x\x9b\xccc\x15'), chr(4271 - 4171) + chr(101) + chr(0b1100011) + chr(111) + chr(100) + '\145')(chr(0b110010 + 0o103) + '\164' + chr(0b11000 + 0o116) + chr(898 - 853) + chr(0b111000))) and xafqLlk3kkUe(SXOLrMavuUCe(b'\xfe\x91\xfb\x81l\x16\x05\x95'), chr(2220 - 2120) + '\145' + '\x63' + chr(0b1010010 + 0o35) + '\x64' + chr(0b110101 + 0o60))('\x75' + '\164' + '\146' + chr(0b100 + 0o51) + chr(56)) in xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf2\x9e\xf7\xbbi \x04\x89Z\x88\xba\xb1@\xe1\xe9x\x9b\xccc\x15'), '\144' + '\x65' + chr(99) + chr(111) + chr(100) + chr(0b1100101))(chr(6108 - 5991) + chr(0b1100100 + 0o20) + chr(7090 - 6988) + chr(45) + chr(0b1000 + 0o60))):
e1jVqMSBZ01Y = zKX2QWkP1IU9(e1jVqMSBZ01Y, n4ljua2gi1Pr.num_mixedin_layers, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfe\x91\xfb\x81l\x16\x05\x95Z'), chr(0b1100100) + chr(7173 - 7072) + chr(0b11011 + 0o110) + '\x6f' + chr(2572 - 2472) + chr(0b1000111 + 0o36))('\x75' + chr(0b1110100) + '\146' + chr(0b11110 + 0o17) + '\070'))
return (e1jVqMSBZ01Y, kpP2CsboxNzE)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
get_ut_layer
|
def get_ut_layer(x,
hparams,
ffn_unit,
attention_unit,
pad_remover=None):
"""Provides the function that is used in universal transforemr steps.
Args:
x: input
hparams: model hyper-parameters
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
ut_function and the ut_initializer
Raises:
ValueError: Unknown recurrence type
"""
if hparams.recurrence_type == "basic":
ut_initializer = (x, x, x) # (state, input, memory)
ut_function = functools.partial(
universal_transformer_basic,
hparams=hparams,
ffn_unit=ffn_unit,
attention_unit=attention_unit)
elif hparams.recurrence_type == "highway":
ut_initializer = (x, x, x) # (state, input, memory)
ut_function = functools.partial(
universal_transformer_highway,
hparams=hparams,
ffn_unit=ffn_unit,
attention_unit=attention_unit,
pad_remover=pad_remover)
elif hparams.recurrence_type == "skip":
ut_initializer = (x, x, x) # (state, input, memory)
ut_function = functools.partial(
universal_transformer_skip,
hparams=hparams,
ffn_unit=ffn_unit,
attention_unit=attention_unit,
pad_remover=pad_remover)
elif hparams.recurrence_type == "dwa":
# memory contains the original input + all the states
memory_size = hparams.num_rec_steps + 1
# prepare initializer:
memory_empty = tf.zeros([memory_size] + common_layers.shape_list(x))
# filling the first slot with the original input
memory = fill_memory_slot(memory_empty, x, 0)
ut_initializer = (x, x, memory) # (state, input, memory)
ut_function = functools.partial(
universal_transformer_depthwise_attention,
hparams=hparams,
ffn_unit=ffn_unit,
attention_unit=attention_unit)
elif hparams.recurrence_type == "gru":
ut_initializer = (x, x, x) # (state, input, memory)
ut_function = functools.partial(
universal_transformer_with_gru_as_transition_function,
hparams=hparams,
ffn_unit=ffn_unit,
attention_unit=attention_unit,
pad_remover=pad_remover)
elif hparams.recurrence_type == "lstm":
memory = tf.zeros(common_layers.shape_list(x))
ut_initializer = (x, x, memory) # (state, input, memory)
ut_function = functools.partial(
universal_transformer_with_lstm_as_transition_function,
hparams=hparams,
ffn_unit=ffn_unit,
attention_unit=attention_unit,
pad_remover=pad_remover)
else:
raise ValueError("Unknown recurrence type: %s" % hparams.recurrence_type)
return ut_function, ut_initializer
|
python
|
def get_ut_layer(x,
hparams,
ffn_unit,
attention_unit,
pad_remover=None):
"""Provides the function that is used in universal transforemr steps.
Args:
x: input
hparams: model hyper-parameters
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
ut_function and the ut_initializer
Raises:
ValueError: Unknown recurrence type
"""
if hparams.recurrence_type == "basic":
ut_initializer = (x, x, x) # (state, input, memory)
ut_function = functools.partial(
universal_transformer_basic,
hparams=hparams,
ffn_unit=ffn_unit,
attention_unit=attention_unit)
elif hparams.recurrence_type == "highway":
ut_initializer = (x, x, x) # (state, input, memory)
ut_function = functools.partial(
universal_transformer_highway,
hparams=hparams,
ffn_unit=ffn_unit,
attention_unit=attention_unit,
pad_remover=pad_remover)
elif hparams.recurrence_type == "skip":
ut_initializer = (x, x, x) # (state, input, memory)
ut_function = functools.partial(
universal_transformer_skip,
hparams=hparams,
ffn_unit=ffn_unit,
attention_unit=attention_unit,
pad_remover=pad_remover)
elif hparams.recurrence_type == "dwa":
# memory contains the original input + all the states
memory_size = hparams.num_rec_steps + 1
# prepare initializer:
memory_empty = tf.zeros([memory_size] + common_layers.shape_list(x))
# filling the first slot with the original input
memory = fill_memory_slot(memory_empty, x, 0)
ut_initializer = (x, x, memory) # (state, input, memory)
ut_function = functools.partial(
universal_transformer_depthwise_attention,
hparams=hparams,
ffn_unit=ffn_unit,
attention_unit=attention_unit)
elif hparams.recurrence_type == "gru":
ut_initializer = (x, x, x) # (state, input, memory)
ut_function = functools.partial(
universal_transformer_with_gru_as_transition_function,
hparams=hparams,
ffn_unit=ffn_unit,
attention_unit=attention_unit,
pad_remover=pad_remover)
elif hparams.recurrence_type == "lstm":
memory = tf.zeros(common_layers.shape_list(x))
ut_initializer = (x, x, memory) # (state, input, memory)
ut_function = functools.partial(
universal_transformer_with_lstm_as_transition_function,
hparams=hparams,
ffn_unit=ffn_unit,
attention_unit=attention_unit,
pad_remover=pad_remover)
else:
raise ValueError("Unknown recurrence type: %s" % hparams.recurrence_type)
return ut_function, ut_initializer
|
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] |
Provides the function that is used in universal transforemr steps.
Args:
x: input
hparams: model hyper-parameters
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
ut_function and the ut_initializer
Raises:
ValueError: Unknown recurrence type
|
[
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L268-L354
|
train
|
Returns the function that is used in universal transforemr steps.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b10000 + 0o137) + chr(1896 - 1847) + '\064' + '\060', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b10110 + 0o131) + chr(2210 - 2160) + chr(0b110011) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b111000 + 0o67) + chr(49) + '\x30' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011100 + 0o23) + chr(51) + '\061' + '\x34', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(0b1110 + 0o43) + chr(0b110110), 9825 - 9817), ehT0Px3KOsy9(chr(1712 - 1664) + chr(111) + chr(52) + '\061', 0o10), ehT0Px3KOsy9(chr(145 - 97) + chr(0b1010101 + 0o32) + '\x33' + chr(48) + chr(1358 - 1309), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + '\062' + '\061', 0o10), ehT0Px3KOsy9(chr(1104 - 1056) + chr(0b1101111) + chr(1711 - 1656) + '\x36', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101000 + 0o7) + chr(0b1111 + 0o47) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(945 - 894) + '\x34' + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(216 - 105) + chr(0b110010) + chr(53) + chr(0b101110 + 0o5), 0b1000), ehT0Px3KOsy9('\060' + chr(0b111100 + 0o63) + chr(957 - 907), 0o10), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1011101 + 0o22) + chr(0b101011 + 0o6) + '\x35' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(2029 - 1981) + '\x6f' + '\x32' + '\x32' + chr(1723 - 1675), 4454 - 4446), ehT0Px3KOsy9(chr(48) + chr(111) + '\063' + '\x30' + '\067', 29270 - 29262), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + chr(55) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b111101 + 0o62) + '\062' + chr(0b11000 + 0o34) + chr(655 - 605), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + chr(0b101000 + 0o17) + chr(53), 50302 - 50294), ehT0Px3KOsy9(chr(2094 - 2046) + chr(111) + chr(0b110010) + '\x31' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + chr(1391 - 1338) + chr(0b1000 + 0o50), 39495 - 39487), ehT0Px3KOsy9(chr(48) + chr(0b1001101 + 0o42) + chr(0b101100 + 0o6) + chr(0b1011 + 0o53) + chr(0b1001 + 0o51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b0 + 0o63) + chr(0b110001) + chr(0b10100 + 0o43), 44497 - 44489), ehT0Px3KOsy9(chr(102 - 54) + chr(0b1101111) + chr(1719 - 1670) + chr(0b1011 + 0o53) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(111) + chr(0b110101) + chr(0b110001), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b1111 + 0o44) + chr(0b101111 + 0o7) + chr(54), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + chr(0b101 + 0o53), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010000 + 0o37) + '\065' + chr(48), 58554 - 58546), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b11001 + 0o31) + chr(55) + chr(53), 0o10), ehT0Px3KOsy9(chr(1167 - 1119) + chr(8898 - 8787) + '\x34' + chr(526 - 471), 38668 - 38660), ehT0Px3KOsy9(chr(48) + chr(3025 - 2914) + chr(0b110001) + chr(55) + chr(1691 - 1636), ord("\x08")), ehT0Px3KOsy9(chr(377 - 329) + '\x6f' + '\061' + '\067' + '\x31', 49252 - 49244), ehT0Px3KOsy9('\x30' + chr(111) + '\x36' + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(0b100100 + 0o21) + chr(0b110111), 57060 - 57052), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(8569 - 8458) + '\x31' + chr(396 - 344) + chr(49), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1100000 + 0o17) + chr(0b11111 + 0o23) + chr(1987 - 1938), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(52) + '\065', 0o10), ehT0Px3KOsy9(chr(0b10110 + 0o32) + '\x6f' + chr(0b110010) + '\063' + chr(51), 8), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + chr(0b101101 + 0o12) + chr(52), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + '\060' + chr(54), 40214 - 40206)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x35' + chr(48), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'N'), chr(7970 - 7870) + chr(101) + chr(99) + '\x6f' + chr(0b1100100) + '\x65')(chr(0b1101011 + 0o12) + '\x74' + '\146' + chr(45) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def NCjymzLXjqvm(OeWW0F1dBPRQ, n4ljua2gi1Pr, SHRtjNoPzosY, ek3fs6JEXh0d, bLDzE_zU4vXa=None):
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x12\xfe%\xb9\xfcS\xa4\xff]P\xbe\xdf{\x1d\xf5'), '\144' + '\145' + chr(9168 - 9069) + chr(111) + '\144' + chr(0b1000000 + 0o45))('\x75' + chr(116) + '\146' + chr(45) + chr(56))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x02\xfa5\xa5\xed'), chr(0b1100100) + chr(10144 - 10043) + '\x63' + chr(0b1101111) + chr(0b1100100) + chr(2972 - 2871))('\165' + '\x74' + chr(102) + chr(0b101101) + chr(2541 - 2485)):
hZn8dcT6c45P = (OeWW0F1dBPRQ, OeWW0F1dBPRQ, OeWW0F1dBPRQ)
bJ8teQTW0l5A = E6ula8_Zv1yl.partial(_jtXM4S1G97k, hparams=n4ljua2gi1Pr, ffn_unit=SHRtjNoPzosY, attention_unit=ek3fs6JEXh0d)
elif xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x12\xfe%\xb9\xfcS\xa4\xff]P\xbe\xdf{\x1d\xf5'), chr(100) + chr(101) + chr(6544 - 6445) + chr(0b100 + 0o153) + chr(3341 - 3241) + chr(6289 - 6188))(chr(0b1000111 + 0o56) + '\x74' + '\146' + '\055' + chr(56))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x08\xf2!\xa4\xf9@\xb8'), chr(0b1100100) + chr(0b1100101) + chr(0b1100011) + chr(1611 - 1500) + chr(1489 - 1389) + '\x65')(chr(0b1110 + 0o147) + chr(8198 - 8082) + chr(0b1100110) + chr(558 - 513) + '\x38'):
hZn8dcT6c45P = (OeWW0F1dBPRQ, OeWW0F1dBPRQ, OeWW0F1dBPRQ)
bJ8teQTW0l5A = E6ula8_Zv1yl.partial(srPX5CAqqznq, hparams=n4ljua2gi1Pr, ffn_unit=SHRtjNoPzosY, attention_unit=ek3fs6JEXh0d, pad_remover=bLDzE_zU4vXa)
elif xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x12\xfe%\xb9\xfcS\xa4\xff]P\xbe\xdf{\x1d\xf5'), chr(8090 - 7990) + chr(101) + chr(0b1100011) + chr(111) + chr(100) + '\145')(chr(117) + chr(2587 - 2471) + '\146' + chr(1050 - 1005) + chr(1237 - 1181))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x13\xf0/\xbc'), '\144' + chr(0b101100 + 0o71) + chr(0b111001 + 0o52) + chr(111) + '\x64' + chr(7845 - 7744))('\165' + chr(0b1110100) + chr(0b101101 + 0o71) + '\x2d' + chr(2124 - 2068)):
hZn8dcT6c45P = (OeWW0F1dBPRQ, OeWW0F1dBPRQ, OeWW0F1dBPRQ)
bJ8teQTW0l5A = E6ula8_Zv1yl.partial(tdo8tQkgw49N, hparams=n4ljua2gi1Pr, ffn_unit=SHRtjNoPzosY, attention_unit=ek3fs6JEXh0d, pad_remover=bLDzE_zU4vXa)
elif xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x12\xfe%\xb9\xfcS\xa4\xff]P\xbe\xdf{\x1d\xf5'), '\x64' + chr(5614 - 5513) + chr(0b1100011) + chr(0b1101111) + '\x64' + chr(0b1100101))('\x75' + '\x74' + chr(4165 - 4063) + '\055' + '\x38')) == xafqLlk3kkUe(SXOLrMavuUCe(b"\x04\xec'"), chr(0b1100100) + chr(8833 - 8732) + '\x63' + chr(8185 - 8074) + chr(0b101101 + 0o67) + '\x65')(chr(0b1000101 + 0o60) + chr(0b1110100) + chr(0b111110 + 0o50) + chr(45) + chr(1083 - 1027)):
jaH8KfMZv9Nv = n4ljua2gi1Pr.num_rec_steps + ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b100111 + 0o12), ord("\x08"))
CKTALRkiBUwC = IDJ2eXGCBCDu.zeros([jaH8KfMZv9Nv] + jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ))
KcR7WgfLppqF = nWMmlaB9bcqE(CKTALRkiBUwC, OeWW0F1dBPRQ, ehT0Px3KOsy9(chr(561 - 513) + chr(0b1101111) + chr(48), 0o10))
hZn8dcT6c45P = (OeWW0F1dBPRQ, OeWW0F1dBPRQ, KcR7WgfLppqF)
bJ8teQTW0l5A = E6ula8_Zv1yl.partial(OQtyjirAul6I, hparams=n4ljua2gi1Pr, ffn_unit=SHRtjNoPzosY, attention_unit=ek3fs6JEXh0d)
elif xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x12\xfe%\xb9\xfcS\xa4\xff]P\xbe\xdf{\x1d\xf5'), chr(0b1100100) + chr(0b1100101) + chr(0b1100011) + '\157' + '\x64' + chr(101))(chr(0b1110101) + chr(0b1110100) + chr(0b1100 + 0o132) + chr(1956 - 1911) + chr(56))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x07\xe93'), chr(100) + '\145' + '\143' + chr(0b1101111) + '\144' + chr(0b1100101))(chr(4676 - 4559) + chr(0b1110100) + chr(102) + chr(98 - 53) + '\070'):
hZn8dcT6c45P = (OeWW0F1dBPRQ, OeWW0F1dBPRQ, OeWW0F1dBPRQ)
bJ8teQTW0l5A = E6ula8_Zv1yl.partial(DEi5fowvIvk0, hparams=n4ljua2gi1Pr, ffn_unit=SHRtjNoPzosY, attention_unit=ek3fs6JEXh0d, pad_remover=bLDzE_zU4vXa)
elif xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x12\xfe%\xb9\xfcS\xa4\xff]P\xbe\xdf{\x1d\xf5'), '\144' + chr(0b1110 + 0o127) + chr(99) + chr(111) + '\144' + chr(101))(chr(0b1110101) + '\x74' + '\146' + '\x2d' + chr(384 - 328))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x0c\xe82\xa1'), chr(100) + chr(3738 - 3637) + '\x63' + '\x6f' + '\x64' + chr(0b1100101))(chr(0b1110101) + chr(0b1010 + 0o152) + chr(0b1001000 + 0o36) + '\055' + '\x38'):
KcR7WgfLppqF = IDJ2eXGCBCDu.zeros(jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ))
hZn8dcT6c45P = (OeWW0F1dBPRQ, OeWW0F1dBPRQ, KcR7WgfLppqF)
bJ8teQTW0l5A = E6ula8_Zv1yl.partial(LwK9_zCyg8Il, hparams=n4ljua2gi1Pr, ffn_unit=SHRtjNoPzosY, attention_unit=ek3fs6JEXh0d, pad_remover=bLDzE_zU4vXa)
else:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'5\xf5-\xa2\xe1V\xaf\xb1LP\x82\xdep\x1f\xf5\xa9\x9b\xc7\xdd\xff\xd1\xc2\xaaN\t\xd3{'), chr(0b1010101 + 0o17) + chr(0b1100101) + '\x63' + chr(0b10010 + 0o135) + chr(2084 - 1984) + chr(7110 - 7009))(chr(117) + chr(10974 - 10858) + '\146' + chr(0b101101) + '\070') % xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x12\xfe%\xb9\xfcS\xa4\xff]P\xbe\xdf{\x1d\xf5'), '\144' + chr(0b111101 + 0o50) + '\x63' + chr(111) + chr(0b1100100) + chr(0b1100101))('\165' + chr(0b11101 + 0o127) + chr(0b1011 + 0o133) + chr(0b1101 + 0o40) + '\x38')))
return (bJ8teQTW0l5A, hZn8dcT6c45P)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
transformer_encoder_ffn_unit
|
def transformer_encoder_ffn_unit(x,
hparams,
nonpadding_mask=None,
pad_remover=None):
"""Applies a feed-forward function which is parametrised for encoding.
Args:
x: input
hparams: model hyper-parameters
nonpadding_mask: optional Tensor with shape [batch_size, encoder_length]
indicating what positions are not padding. This is used
to mask out padding in convoltutional layers. We generally only
need this mask for "packed" datasets, because for ordinary datasets,
no padding is ever followed by nonpadding.
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
the output tensor
"""
with tf.variable_scope("ffn"):
if hparams.transformer_ffn_type == "fc":
y = transformer.transformer_ffn_layer(
common_layers.layer_preprocess(x, hparams),
hparams,
pad_remover,
conv_padding="SAME",
nonpadding_mask=nonpadding_mask)
if hparams.transformer_ffn_type == "sepconv":
assert nonpadding_mask is not None, (
"The nonpadding_mask should be provided, otherwise the model uses "
"the leaked padding information to estimate the length!")
y = common_layers.sepconv_relu_sepconv(
common_layers.layer_preprocess(x, hparams),
filter_size=hparams.filter_size,
output_size=hparams.hidden_size,
first_kernel_size=(3, 1),
second_kernel_size=(5, 1),
padding="SAME",
nonpadding_mask=nonpadding_mask,
dropout=hparams.relu_dropout)
x = common_layers.layer_postprocess(x, y, hparams)
return x
|
python
|
def transformer_encoder_ffn_unit(x,
hparams,
nonpadding_mask=None,
pad_remover=None):
"""Applies a feed-forward function which is parametrised for encoding.
Args:
x: input
hparams: model hyper-parameters
nonpadding_mask: optional Tensor with shape [batch_size, encoder_length]
indicating what positions are not padding. This is used
to mask out padding in convoltutional layers. We generally only
need this mask for "packed" datasets, because for ordinary datasets,
no padding is ever followed by nonpadding.
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
the output tensor
"""
with tf.variable_scope("ffn"):
if hparams.transformer_ffn_type == "fc":
y = transformer.transformer_ffn_layer(
common_layers.layer_preprocess(x, hparams),
hparams,
pad_remover,
conv_padding="SAME",
nonpadding_mask=nonpadding_mask)
if hparams.transformer_ffn_type == "sepconv":
assert nonpadding_mask is not None, (
"The nonpadding_mask should be provided, otherwise the model uses "
"the leaked padding information to estimate the length!")
y = common_layers.sepconv_relu_sepconv(
common_layers.layer_preprocess(x, hparams),
filter_size=hparams.filter_size,
output_size=hparams.hidden_size,
first_kernel_size=(3, 1),
second_kernel_size=(5, 1),
padding="SAME",
nonpadding_mask=nonpadding_mask,
dropout=hparams.relu_dropout)
x = common_layers.layer_postprocess(x, y, hparams)
return x
|
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] |
Applies a feed-forward function which is parametrised for encoding.
Args:
x: input
hparams: model hyper-parameters
nonpadding_mask: optional Tensor with shape [batch_size, encoder_length]
indicating what positions are not padding. This is used
to mask out padding in convoltutional layers. We generally only
need this mask for "packed" datasets, because for ordinary datasets,
no padding is ever followed by nonpadding.
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
the output tensor
|
[
"Applies",
"a",
"feed",
"-",
"forward",
"function",
"which",
"is",
"parametrised",
"for",
"encoding",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L357-L402
|
train
|
Applies a feed - forward function which is parametrised for encoding.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b100110 + 0o111) + chr(0b10101 + 0o36) + '\x30' + chr(0b11 + 0o61), 53773 - 53765), ehT0Px3KOsy9(chr(0b110000) + chr(0b101110 + 0o101) + '\063' + chr(48) + '\x37', 46319 - 46311), ehT0Px3KOsy9('\x30' + chr(111) + chr(1647 - 1595) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(1518 - 1470) + chr(111) + chr(0b11111 + 0o23) + chr(1992 - 1937) + chr(2720 - 2667), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b110000 + 0o77) + chr(0b100010 + 0o17) + chr(2792 - 2737) + chr(2154 - 2102), 18858 - 18850), ehT0Px3KOsy9('\060' + chr(111) + chr(0b11 + 0o60) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(527 - 416) + chr(0b110010 + 0o2) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\060' + chr(6854 - 6743) + chr(49) + chr(0b111 + 0o51) + chr(2883 - 2829), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32' + chr(55) + chr(49), 0o10), ehT0Px3KOsy9(chr(375 - 327) + chr(6848 - 6737) + chr(357 - 307) + chr(0b100101 + 0o22), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100010 + 0o15) + chr(0b110010) + chr(50) + chr(50), 0o10), ehT0Px3KOsy9('\x30' + chr(3077 - 2966) + '\062' + chr(0b11101 + 0o27) + '\065', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b11 + 0o154) + chr(0b110011) + chr(1663 - 1610) + chr(466 - 418), 51240 - 51232), ehT0Px3KOsy9(chr(48) + chr(0b1100010 + 0o15) + '\062' + chr(55) + chr(0b110011), 40915 - 40907), ehT0Px3KOsy9(chr(979 - 931) + '\157' + chr(50) + '\x31' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1304 - 1254) + chr(312 - 262) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(754 - 706) + '\x6f' + chr(0b110010) + '\061' + chr(0b111 + 0o51), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(51) + '\060' + '\x34', 8), ehT0Px3KOsy9(chr(1870 - 1822) + '\157' + '\x31' + chr(440 - 390) + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(0b110110) + chr(0b111 + 0o54), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b111100 + 0o63) + chr(1138 - 1088) + chr(0b110101) + chr(0b10100 + 0o35), 0b1000), ehT0Px3KOsy9(chr(2254 - 2206) + chr(0b1101111) + '\062' + '\064' + '\x35', 8), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(111) + '\062' + '\066', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(431 - 320) + chr(493 - 444) + chr(1378 - 1330) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(2322 - 2211) + '\063' + chr(707 - 659) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b110011 + 0o74) + '\x36' + '\x37', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + chr(0b110101) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110011) + '\061' + chr(0b10100 + 0o36), 0b1000), ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\157' + chr(50) + chr(2287 - 2239) + chr(0b110001), 58941 - 58933), ehT0Px3KOsy9('\060' + chr(0b100100 + 0o113) + chr(0b1100 + 0o45) + '\x31' + '\065', 0b1000), ehT0Px3KOsy9('\060' + chr(0b11111 + 0o120) + chr(51) + chr(0b110011) + chr(0b110011), 5442 - 5434), ehT0Px3KOsy9(chr(1642 - 1594) + chr(0b1101111) + '\061' + '\062' + '\x31', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b101110 + 0o3) + chr(0b110101) + chr(0b110010), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(1420 - 1370) + chr(50), 3889 - 3881), ehT0Px3KOsy9(chr(0b110000) + chr(6385 - 6274) + chr(0b11101 + 0o24) + chr(0b10000 + 0o41) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + chr(2277 - 2227) + '\065', 59811 - 59803), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50), 47765 - 47757), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1456 - 1401) + chr(494 - 445), 11726 - 11718), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(49) + chr(0b101111 + 0o2), ord("\x08")), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(111) + '\062' + '\062', 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110 + 0o57) + '\060', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xea'), '\x64' + chr(101) + '\143' + chr(0b1101111) + '\144' + chr(6867 - 6766))(chr(0b100011 + 0o122) + '\164' + chr(686 - 584) + chr(0b101101) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def QXjFvKdTudYV(OeWW0F1dBPRQ, n4ljua2gi1Pr, UyiM64E6iSsw=None, bLDzE_zU4vXa=None):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb2\xa6V\xd4\x1dyI#\xe6d\xf1\xca\x98\xde'), '\x64' + chr(0b1100101) + chr(9562 - 9463) + '\157' + chr(0b10101 + 0o117) + '\x65')(chr(117) + '\x74' + '\146' + chr(0b111 + 0o46) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xa2\xa1J'), chr(100) + '\145' + '\143' + chr(111) + '\144' + chr(101))('\165' + chr(116) + chr(102) + chr(0b10110 + 0o27) + '\x38')):
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8a\x98T\xc5\x15nH\x17\xe9`\xd5\xf6'), '\x64' + '\x65' + chr(99) + chr(0b0 + 0o157) + chr(100) + chr(0b1100101))(chr(0b1110101) + chr(0b1101110 + 0o6) + '\146' + chr(315 - 270) + chr(0b10101 + 0o43))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\xa2\xa4'), '\144' + chr(7354 - 7253) + '\143' + chr(0b1001010 + 0o45) + chr(0b111110 + 0o46) + chr(0b1001010 + 0o33))('\165' + chr(9926 - 9810) + '\146' + '\055' + chr(2628 - 2572)):
SqiSOtYOqOJH = Nk9m9eKr4iuF.transformer_ffn_layer(jSKPaHwSAfVv.layer_preprocess(OeWW0F1dBPRQ, n4ljua2gi1Pr), n4ljua2gi1Pr, bLDzE_zU4vXa, conv_padding=xafqLlk3kkUe(SXOLrMavuUCe(b'\x97\x86i\xf8'), chr(2544 - 2444) + chr(0b1100101) + chr(0b1100011 + 0o0) + chr(12015 - 11904) + chr(100) + chr(2913 - 2812))('\165' + '\164' + '\146' + '\x2d' + '\070'), nonpadding_mask=UyiM64E6iSsw)
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8a\x98T\xc5\x15nH\x17\xe9`\xd5\xf6'), '\x64' + chr(8772 - 8671) + chr(7096 - 6997) + chr(11782 - 11671) + '\144' + chr(6330 - 6229))(chr(0b10011 + 0o142) + chr(0b1110100) + chr(0b1100110) + chr(0b101101) + '\070')) == xafqLlk3kkUe(SXOLrMavuUCe(b'\xb7\xa2T\xde\x13uS'), chr(100) + chr(0b101010 + 0o73) + chr(0b100001 + 0o102) + chr(0b1101111) + chr(0b1100100) + '\145')(chr(8442 - 8325) + chr(7375 - 7259) + '\146' + chr(0b100101 + 0o10) + chr(56)):
assert UyiM64E6iSsw is not None, xafqLlk3kkUe(SXOLrMavuUCe(b'\x90\xafA\x9d\x12tK6\xd8s\xf6\xcc\x86\xdc\xd0\xfe\xe9\xb7<\xd3\xda\xcdy7\xaeS\xc9\xa8\xe4m\xab#\x05d"\xb1g]\xe52\xab\xb3L\xd8\x0elL5\xdc7\xe6\xcd\x8d\x9b\xe2\xfc\xec\xa1;\xd3\xdc\xd6s1\xe2C\x81\xaf\xa1!\xbe0\x01w/\xf5rX\xadv\xad\xa9C\x9d\x15uC)\xcbz\xf3\xd1\x81\xd4\xe1\xb3\xfc\xabw\x96\xda\xd1\x7f/\xa3C\x8c\xea\xf5%\xbeq\x06w%\xb2vQ\xe8'), chr(0b100101 + 0o77) + chr(101) + chr(6856 - 6757) + chr(111) + chr(100) + '\145')(chr(0b1110101) + chr(116) + '\146' + chr(45) + chr(0b101 + 0o63))
SqiSOtYOqOJH = jSKPaHwSAfVv.sepconv_relu_sepconv(jSKPaHwSAfVv.layer_preprocess(OeWW0F1dBPRQ, n4ljua2gi1Pr), filter_size=n4ljua2gi1Pr.deybX8NJ0oEI, output_size=n4ljua2gi1Pr.qzoyXN3kdhDL, first_kernel_size=(ehT0Px3KOsy9(chr(1934 - 1886) + chr(0b1101111 + 0o0) + chr(332 - 281), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\061', 0b1000)), second_kernel_size=(ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(53), 0b1000), ehT0Px3KOsy9('\x30' + chr(8256 - 8145) + chr(1462 - 1413), 8)), padding=xafqLlk3kkUe(SXOLrMavuUCe(b'\x97\x86i\xf8'), '\x64' + chr(101) + '\143' + chr(0b1101111) + '\144' + chr(0b1100101))(chr(0b1110101) + '\164' + chr(0b1100110) + chr(493 - 448) + chr(3004 - 2948)), nonpadding_mask=UyiM64E6iSsw, dropout=n4ljua2gi1Pr.PJc0PNdBnSag)
OeWW0F1dBPRQ = jSKPaHwSAfVv.layer_postprocess(OeWW0F1dBPRQ, SqiSOtYOqOJH, n4ljua2gi1Pr)
return OeWW0F1dBPRQ
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
transformer_encoder_attention_unit
|
def transformer_encoder_attention_unit(x,
hparams,
encoder_self_attention_bias,
attention_dropout_broadcast_dims,
save_weights_to=None,
make_image_summary=True):
"""Applies multihead attention function which is parametrised for encoding.
Args:
x: input
hparams: model hyper-parameters
encoder_self_attention_bias: a bias tensor for use in encoder self-attention
attention_dropout_broadcast_dims: Fpr noise broadcasting in the dropout
layers to save memory during training
save_weights_to: an optional dictionary to capture attention weights for
visualization; the weights tensor will be appended there under a string
key created from the variable scope (including name).
make_image_summary: Whether to make an attention image summary.
Returns:
the output tensor
"""
with tf.variable_scope("self_attention"):
y = common_attention.multihead_attention(
common_layers.layer_preprocess(x, hparams),
None,
encoder_self_attention_bias,
hparams.attention_key_channels or hparams.hidden_size,
hparams.attention_value_channels or hparams.hidden_size,
hparams.hidden_size,
hparams.num_heads,
hparams.attention_dropout,
attention_type=hparams.self_attention_type,
save_weights_to=save_weights_to,
max_relative_position=hparams.max_relative_position,
make_image_summary=make_image_summary,
dropout_broadcast_dims=attention_dropout_broadcast_dims,
hard_attention_k=hparams.hard_attention_k)
x = common_layers.layer_postprocess(x, y, hparams)
return x
|
python
|
def transformer_encoder_attention_unit(x,
hparams,
encoder_self_attention_bias,
attention_dropout_broadcast_dims,
save_weights_to=None,
make_image_summary=True):
"""Applies multihead attention function which is parametrised for encoding.
Args:
x: input
hparams: model hyper-parameters
encoder_self_attention_bias: a bias tensor for use in encoder self-attention
attention_dropout_broadcast_dims: Fpr noise broadcasting in the dropout
layers to save memory during training
save_weights_to: an optional dictionary to capture attention weights for
visualization; the weights tensor will be appended there under a string
key created from the variable scope (including name).
make_image_summary: Whether to make an attention image summary.
Returns:
the output tensor
"""
with tf.variable_scope("self_attention"):
y = common_attention.multihead_attention(
common_layers.layer_preprocess(x, hparams),
None,
encoder_self_attention_bias,
hparams.attention_key_channels or hparams.hidden_size,
hparams.attention_value_channels or hparams.hidden_size,
hparams.hidden_size,
hparams.num_heads,
hparams.attention_dropout,
attention_type=hparams.self_attention_type,
save_weights_to=save_weights_to,
max_relative_position=hparams.max_relative_position,
make_image_summary=make_image_summary,
dropout_broadcast_dims=attention_dropout_broadcast_dims,
hard_attention_k=hparams.hard_attention_k)
x = common_layers.layer_postprocess(x, y, hparams)
return x
|
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] |
Applies multihead attention function which is parametrised for encoding.
Args:
x: input
hparams: model hyper-parameters
encoder_self_attention_bias: a bias tensor for use in encoder self-attention
attention_dropout_broadcast_dims: Fpr noise broadcasting in the dropout
layers to save memory during training
save_weights_to: an optional dictionary to capture attention weights for
visualization; the weights tensor will be appended there under a string
key created from the variable scope (including name).
make_image_summary: Whether to make an attention image summary.
Returns:
the output tensor
|
[
"Applies",
"multihead",
"attention",
"function",
"which",
"is",
"parametrised",
"for",
"encoding",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L405-L446
|
train
|
Applies multihead attention function which is parametrised for encoding.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + '\157' + chr(49) + chr(55) + '\066', 26608 - 26600), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(111) + '\061' + '\x33' + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101010 + 0o5) + chr(2558 - 2507) + chr(0b10010 + 0o40) + '\x37', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\x35' + '\060', 0b1000), ehT0Px3KOsy9(chr(94 - 46) + '\x6f' + chr(50) + chr(51) + chr(0b101100 + 0o12), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b11100 + 0o25) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(779 - 731) + chr(4304 - 4193) + chr(0b10101 + 0o35) + chr(0b110101) + '\065', 63751 - 63743), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + '\067' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10001 + 0o46) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(272 - 224) + chr(9445 - 9334) + chr(0b110001) + chr(0b10010 + 0o37) + '\x31', 3355 - 3347), ehT0Px3KOsy9(chr(48) + chr(0b1000011 + 0o54) + chr(494 - 443), ord("\x08")), ehT0Px3KOsy9(chr(2117 - 2069) + chr(0b1101101 + 0o2) + chr(0b11101 + 0o26) + chr(2275 - 2226) + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\x6f' + '\x35' + '\065', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b10000 + 0o137) + chr(297 - 247) + chr(54) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + chr(857 - 808) + '\067', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b111 + 0o150) + chr(0b110001) + '\062' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\x6f' + chr(49) + chr(0b1111 + 0o46) + chr(0b10001 + 0o37), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(9308 - 9197) + chr(0b10 + 0o64), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(1817 - 1768) + chr(104 - 52) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b10111 + 0o130) + chr(0b10010 + 0o40) + chr(2062 - 2008), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(1495 - 1441) + '\067', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\061' + chr(55) + '\x32', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101101 + 0o2) + '\x31' + '\063' + '\065', 32318 - 32310), ehT0Px3KOsy9('\060' + '\x6f' + '\061' + chr(0b110100) + chr(0b110000), 61021 - 61013), ehT0Px3KOsy9(chr(0b110000) + chr(10336 - 10225) + '\062' + chr(2662 - 2609) + chr(0b11011 + 0o34), 0o10), ehT0Px3KOsy9(chr(1584 - 1536) + chr(111) + '\061' + chr(2769 - 2714) + chr(0b101010 + 0o6), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1011101 + 0o22) + chr(0b110001) + '\063' + chr(0b110000), 8), ehT0Px3KOsy9('\x30' + chr(111) + '\x31' + '\x32' + chr(0b110010), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + '\x34' + chr(0b1010 + 0o54), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(55), 6679 - 6671), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + chr(53) + '\x33', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10010 + 0o37) + chr(1415 - 1362) + chr(1050 - 1000), 49479 - 49471), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b1101111) + chr(0b110001) + chr(1779 - 1729) + chr(2250 - 2198), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b10100 + 0o133) + chr(0b101001 + 0o11) + '\066' + '\067', 8), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + '\x30' + chr(1573 - 1522), 0b1000), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b1011110 + 0o21) + chr(164 - 110) + chr(50), 0o10), ehT0Px3KOsy9(chr(1235 - 1187) + '\x6f' + chr(51) + chr(0b10 + 0o56) + chr(0b1000 + 0o50), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110111) + '\x32', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(880 - 829) + '\060' + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(3567 - 3456) + chr(0b110010) + chr(1311 - 1263) + '\062', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\065' + chr(48), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'P'), chr(100) + '\x65' + '\143' + '\x6f' + '\144' + '\x65')(chr(11400 - 11283) + chr(0b1000110 + 0o56) + '\146' + chr(0b101101) + chr(0b11 + 0o65)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def LemVfCmDdV4S(OeWW0F1dBPRQ, n4ljua2gi1Pr, cMrr2bkEBgTQ, UNqT6jwzCz6Y, zWaF_2VBEDjk=None, NC2xHNLwzxcH=ehT0Px3KOsy9('\060' + '\157' + chr(0b110001), 0o10)):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x089\xa5A\xffh\xc1\x9c`:`\xa0]\xd5'), chr(0b1100100) + '\145' + '\143' + chr(0b1101111) + '\x64' + chr(9930 - 9829))('\x75' + chr(0b11011 + 0o131) + chr(102) + '\055' + chr(2771 - 2715)))(xafqLlk3kkUe(SXOLrMavuUCe(b"\r=\xbbN\xc1k\xd9\x8dZ'w\xa6B\xde"), chr(0b1100100) + chr(101) + chr(4067 - 3968) + chr(0b1101111) + '\144' + chr(7037 - 6936))(chr(117) + chr(116) + chr(7295 - 7193) + chr(0b111 + 0o46) + chr(56))):
SqiSOtYOqOJH = WOnrfm4dlYcf.multihead_attention(jSKPaHwSAfVv.layer_preprocess(OeWW0F1dBPRQ, n4ljua2gi1Pr), None, cMrr2bkEBgTQ, n4ljua2gi1Pr.Hj_JCZasfmqG or n4ljua2gi1Pr.qzoyXN3kdhDL, n4ljua2gi1Pr.PZHUuenu09ti or n4ljua2gi1Pr.qzoyXN3kdhDL, n4ljua2gi1Pr.qzoyXN3kdhDL, n4ljua2gi1Pr.vRVqPOZ1hUG7, n4ljua2gi1Pr.RdMRr3qkYioQ, attention_type=n4ljua2gi1Pr.self_attention_type, save_weights_to=zWaF_2VBEDjk, max_relative_position=n4ljua2gi1Pr.max_relative_position, make_image_summary=NC2xHNLwzxcH, dropout_broadcast_dims=UNqT6jwzCz6Y, hard_attention_k=n4ljua2gi1Pr.hard_attention_k)
OeWW0F1dBPRQ = jSKPaHwSAfVv.layer_postprocess(OeWW0F1dBPRQ, SqiSOtYOqOJH, n4ljua2gi1Pr)
return OeWW0F1dBPRQ
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
transformer_decoder_attention_unit
|
def transformer_decoder_attention_unit(x,
hparams,
encoder_output,
decoder_self_attention_bias,
encoder_decoder_attention_bias,
attention_dropout_broadcast_dims,
save_weights_to=None,
make_image_summary=True):
"""Applies multihead attention function which is parametrised for decoding.
Args:
x: input (decoder input)
hparams: model hyper-parameters
encoder_output: Encoder representation. [batch_size, input_length,
hidden_dim]
decoder_self_attention_bias: Bias and mask weights for decoder
self-attention. [batch_size, decoder_length]
encoder_decoder_attention_bias: Bias and mask weights for encoder-decoder
attention. [batch_size, input_length]
attention_dropout_broadcast_dims: Fpr noise broadcasting in the dropout
layers to save memory during training
save_weights_to: an optional dictionary to capture attention weights for
visualization; the weights tensor will be appended there under a string
key created from the variable scope (including name).
make_image_summary: Whether to make an attention image summary.
Returns:
The output tensor
"""
with tf.variable_scope("self_attention"):
y = common_attention.multihead_attention(
common_layers.layer_preprocess(x, hparams),
None,
decoder_self_attention_bias,
hparams.attention_key_channels or hparams.hidden_size,
hparams.attention_value_channels or hparams.hidden_size,
hparams.hidden_size,
hparams.num_heads,
hparams.attention_dropout,
attention_type=hparams.self_attention_type,
save_weights_to=save_weights_to,
max_relative_position=hparams.max_relative_position,
cache=None,
make_image_summary=make_image_summary,
dropout_broadcast_dims=attention_dropout_broadcast_dims,
hard_attention_k=hparams.hard_attention_k)
x = common_layers.layer_postprocess(x, y, hparams)
if encoder_output is not None:
with tf.variable_scope("encdec_attention"):
y = common_attention.multihead_attention(
common_layers.layer_preprocess(x, hparams),
encoder_output,
encoder_decoder_attention_bias,
hparams.attention_key_channels or hparams.hidden_size,
hparams.attention_value_channels or hparams.hidden_size,
hparams.hidden_size,
hparams.num_heads,
hparams.attention_dropout,
save_weights_to=save_weights_to,
make_image_summary=make_image_summary,
dropout_broadcast_dims=attention_dropout_broadcast_dims,
hard_attention_k=hparams.hard_attention_k)
x = common_layers.layer_postprocess(x, y, hparams)
return x
|
python
|
def transformer_decoder_attention_unit(x,
hparams,
encoder_output,
decoder_self_attention_bias,
encoder_decoder_attention_bias,
attention_dropout_broadcast_dims,
save_weights_to=None,
make_image_summary=True):
"""Applies multihead attention function which is parametrised for decoding.
Args:
x: input (decoder input)
hparams: model hyper-parameters
encoder_output: Encoder representation. [batch_size, input_length,
hidden_dim]
decoder_self_attention_bias: Bias and mask weights for decoder
self-attention. [batch_size, decoder_length]
encoder_decoder_attention_bias: Bias and mask weights for encoder-decoder
attention. [batch_size, input_length]
attention_dropout_broadcast_dims: Fpr noise broadcasting in the dropout
layers to save memory during training
save_weights_to: an optional dictionary to capture attention weights for
visualization; the weights tensor will be appended there under a string
key created from the variable scope (including name).
make_image_summary: Whether to make an attention image summary.
Returns:
The output tensor
"""
with tf.variable_scope("self_attention"):
y = common_attention.multihead_attention(
common_layers.layer_preprocess(x, hparams),
None,
decoder_self_attention_bias,
hparams.attention_key_channels or hparams.hidden_size,
hparams.attention_value_channels or hparams.hidden_size,
hparams.hidden_size,
hparams.num_heads,
hparams.attention_dropout,
attention_type=hparams.self_attention_type,
save_weights_to=save_weights_to,
max_relative_position=hparams.max_relative_position,
cache=None,
make_image_summary=make_image_summary,
dropout_broadcast_dims=attention_dropout_broadcast_dims,
hard_attention_k=hparams.hard_attention_k)
x = common_layers.layer_postprocess(x, y, hparams)
if encoder_output is not None:
with tf.variable_scope("encdec_attention"):
y = common_attention.multihead_attention(
common_layers.layer_preprocess(x, hparams),
encoder_output,
encoder_decoder_attention_bias,
hparams.attention_key_channels or hparams.hidden_size,
hparams.attention_value_channels or hparams.hidden_size,
hparams.hidden_size,
hparams.num_heads,
hparams.attention_dropout,
save_weights_to=save_weights_to,
make_image_summary=make_image_summary,
dropout_broadcast_dims=attention_dropout_broadcast_dims,
hard_attention_k=hparams.hard_attention_k)
x = common_layers.layer_postprocess(x, y, hparams)
return x
|
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] |
Applies multihead attention function which is parametrised for decoding.
Args:
x: input (decoder input)
hparams: model hyper-parameters
encoder_output: Encoder representation. [batch_size, input_length,
hidden_dim]
decoder_self_attention_bias: Bias and mask weights for decoder
self-attention. [batch_size, decoder_length]
encoder_decoder_attention_bias: Bias and mask weights for encoder-decoder
attention. [batch_size, input_length]
attention_dropout_broadcast_dims: Fpr noise broadcasting in the dropout
layers to save memory during training
save_weights_to: an optional dictionary to capture attention weights for
visualization; the weights tensor will be appended there under a string
key created from the variable scope (including name).
make_image_summary: Whether to make an attention image summary.
Returns:
The output tensor
|
[
"Applies",
"multihead",
"attention",
"function",
"which",
"is",
"parametrised",
"for",
"decoding",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L492-L556
|
train
|
Applies multihead attention function which is parametrised for decoding.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(0b110100) + '\x35', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + '\064' + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b110101 + 0o72) + chr(1694 - 1645) + '\x36', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + '\x31' + '\x34', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100 + 0o143) + chr(2336 - 2286) + '\x35' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061' + chr(53) + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\064' + chr(0b110011), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1100001 + 0o16) + '\063' + '\064', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(1710 - 1661) + chr(1216 - 1167) + chr(53), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(0b10100 + 0o43) + chr(48), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + chr(54) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(866 - 817) + '\x32', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b101011 + 0o104) + chr(0b110011) + '\x35' + chr(0b100001 + 0o25), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b11001 + 0o32) + chr(48) + chr(2095 - 2045), 12469 - 12461), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1011 + 0o47) + chr(2297 - 2242) + '\063', 58131 - 58123), ehT0Px3KOsy9(chr(836 - 788) + chr(111) + chr(51) + chr(49) + chr(2142 - 2092), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + '\065' + chr(55), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + chr(679 - 625) + chr(252 - 199), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1000010 + 0o55) + chr(0b110001 + 0o1) + '\062' + '\x33', 38006 - 37998), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + chr(0b11001 + 0o35) + '\066', 0o10), ehT0Px3KOsy9(chr(1263 - 1215) + chr(0b1001000 + 0o47) + chr(1158 - 1109) + '\062' + '\060', 8917 - 8909), ehT0Px3KOsy9('\060' + chr(193 - 82) + '\x31' + '\060' + '\066', 0o10), ehT0Px3KOsy9('\060' + chr(0b1011011 + 0o24) + '\063' + chr(53) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b0 + 0o157) + chr(0b10 + 0o57) + '\x31' + chr(0b110010 + 0o2), 34755 - 34747), ehT0Px3KOsy9('\060' + chr(9536 - 9425) + chr(49) + '\x33' + chr(765 - 713), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b101110 + 0o101) + '\063' + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001 + 0o4) + '\x36', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1927 - 1872) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(560 - 512) + chr(0b1101111) + chr(264 - 209) + chr(0b10 + 0o62), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101110 + 0o1) + chr(2780 - 2727) + chr(55), 18478 - 18470), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(49) + chr(0b101110 + 0o7), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(54) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061' + chr(814 - 766) + chr(0b100001 + 0o23), 4568 - 4560), ehT0Px3KOsy9(chr(1215 - 1167) + '\x6f' + chr(1723 - 1674) + '\064' + chr(2633 - 2581), 0b1000), ehT0Px3KOsy9(chr(348 - 300) + '\x6f' + '\x33' + '\065' + chr(0b110110), 8), ehT0Px3KOsy9(chr(533 - 485) + '\157' + chr(0b110001) + chr(52) + chr(2331 - 2276), 58124 - 58116), ehT0Px3KOsy9('\060' + '\x6f' + chr(1362 - 1311) + chr(0b110000 + 0o3) + '\x36', 41997 - 41989), ehT0Px3KOsy9(chr(0b100111 + 0o11) + '\157' + chr(50) + chr(53) + '\067', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\066' + '\061', 0b1000), ehT0Px3KOsy9(chr(511 - 463) + chr(0b1101111) + chr(0b110011) + chr(0b101110 + 0o11) + '\x31', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(111) + '\x35' + chr(2001 - 1953), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x8b'), '\144' + chr(101) + chr(2615 - 2516) + chr(0b1011 + 0o144) + chr(100) + '\145')(chr(0b1110101) + chr(0b1001000 + 0o54) + chr(0b11111 + 0o107) + '\x2d' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def bBM7fZaUBn3Q(OeWW0F1dBPRQ, n4ljua2gi1Pr, NE_S2zAzN4PI, Z0c2rFCFDCFc, iuvkQfeRHfn5, UNqT6jwzCz6Y, zWaF_2VBEDjk=None, NC2xHNLwzxcH=ehT0Px3KOsy9('\x30' + chr(0b1000101 + 0o52) + '\x31', 62732 - 62724)):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd3\x81|\xa5\xcb\nOy\x12\xcb\xd6e\x9e\xa7'), chr(100) + chr(0b1000100 + 0o41) + chr(1507 - 1408) + chr(111) + '\x64' + '\x65')(chr(0b1110101) + '\x74' + chr(0b101111 + 0o67) + chr(0b101101) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xd6\x85b\xaa\xf5\tWh(\xd6\xc1c\x81\xac'), chr(1745 - 1645) + chr(4977 - 4876) + '\143' + chr(3908 - 3797) + '\x64' + '\145')(chr(0b1110101) + chr(116) + chr(0b111100 + 0o52) + '\055' + chr(0b111000))):
SqiSOtYOqOJH = WOnrfm4dlYcf.multihead_attention(jSKPaHwSAfVv.layer_preprocess(OeWW0F1dBPRQ, n4ljua2gi1Pr), None, Z0c2rFCFDCFc, n4ljua2gi1Pr.Hj_JCZasfmqG or n4ljua2gi1Pr.qzoyXN3kdhDL, n4ljua2gi1Pr.PZHUuenu09ti or n4ljua2gi1Pr.qzoyXN3kdhDL, n4ljua2gi1Pr.qzoyXN3kdhDL, n4ljua2gi1Pr.vRVqPOZ1hUG7, n4ljua2gi1Pr.RdMRr3qkYioQ, attention_type=n4ljua2gi1Pr.self_attention_type, save_weights_to=zWaF_2VBEDjk, max_relative_position=n4ljua2gi1Pr.max_relative_position, cache=None, make_image_summary=NC2xHNLwzxcH, dropout_broadcast_dims=UNqT6jwzCz6Y, hard_attention_k=n4ljua2gi1Pr.hard_attention_k)
OeWW0F1dBPRQ = jSKPaHwSAfVv.layer_postprocess(OeWW0F1dBPRQ, SqiSOtYOqOJH, n4ljua2gi1Pr)
if NE_S2zAzN4PI is not None:
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd3\x81|\xa5\xcb\nOy\x12\xcb\xd6e\x9e\xa7'), chr(8743 - 8643) + chr(0b1100101) + chr(6484 - 6385) + '\x6f' + chr(0b1010001 + 0o23) + '\145')(chr(0b1101011 + 0o12) + chr(0b11110 + 0o126) + chr(861 - 759) + chr(994 - 949) + chr(0b110100 + 0o4)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xc0\x8em\xa8\xcf\x0b|}9\xcc\xd0d\x9a\xab\xd4\xa4'), chr(0b10011 + 0o121) + chr(0b1100101) + chr(0b1100 + 0o127) + '\157' + '\x64' + chr(0b10011 + 0o122))('\165' + chr(0b1011000 + 0o34) + chr(0b101111 + 0o67) + '\x2d' + chr(56))):
SqiSOtYOqOJH = WOnrfm4dlYcf.multihead_attention(jSKPaHwSAfVv.layer_preprocess(OeWW0F1dBPRQ, n4ljua2gi1Pr), NE_S2zAzN4PI, iuvkQfeRHfn5, n4ljua2gi1Pr.Hj_JCZasfmqG or n4ljua2gi1Pr.qzoyXN3kdhDL, n4ljua2gi1Pr.PZHUuenu09ti or n4ljua2gi1Pr.qzoyXN3kdhDL, n4ljua2gi1Pr.qzoyXN3kdhDL, n4ljua2gi1Pr.vRVqPOZ1hUG7, n4ljua2gi1Pr.RdMRr3qkYioQ, save_weights_to=zWaF_2VBEDjk, make_image_summary=NC2xHNLwzxcH, dropout_broadcast_dims=UNqT6jwzCz6Y, hard_attention_k=n4ljua2gi1Pr.hard_attention_k)
OeWW0F1dBPRQ = jSKPaHwSAfVv.layer_postprocess(OeWW0F1dBPRQ, SqiSOtYOqOJH, n4ljua2gi1Pr)
return OeWW0F1dBPRQ
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
universal_transformer_basic
|
def universal_transformer_basic(layer_inputs,
step, hparams,
ffn_unit,
attention_unit):
"""Basic Universal Transformer.
This model is pretty similar to the vanilla transformer in which weights are
shared between layers. For some tasks, this simple idea brings a
generalization that is not achievable by playing with the size of the model
or drop_out parameters in the vanilla transformer.
Args:
layer_inputs:
- state: state
step: indicates number of steps taken so far
hparams: model hyper-parameters
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
Returns:
layer_output:
new_state: new state
"""
state, inputs, memory = tf.unstack(layer_inputs, num=None, axis=0,
name="unstack")
new_state = step_preprocess(state, step, hparams)
for i in range(hparams.num_inrecurrence_layers):
with tf.variable_scope("rec_layer_%d" % i):
new_state = ffn_unit(attention_unit(new_state))
return new_state, inputs, memory
|
python
|
def universal_transformer_basic(layer_inputs,
step, hparams,
ffn_unit,
attention_unit):
"""Basic Universal Transformer.
This model is pretty similar to the vanilla transformer in which weights are
shared between layers. For some tasks, this simple idea brings a
generalization that is not achievable by playing with the size of the model
or drop_out parameters in the vanilla transformer.
Args:
layer_inputs:
- state: state
step: indicates number of steps taken so far
hparams: model hyper-parameters
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
Returns:
layer_output:
new_state: new state
"""
state, inputs, memory = tf.unstack(layer_inputs, num=None, axis=0,
name="unstack")
new_state = step_preprocess(state, step, hparams)
for i in range(hparams.num_inrecurrence_layers):
with tf.variable_scope("rec_layer_%d" % i):
new_state = ffn_unit(attention_unit(new_state))
return new_state, inputs, memory
|
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] |
Basic Universal Transformer.
This model is pretty similar to the vanilla transformer in which weights are
shared between layers. For some tasks, this simple idea brings a
generalization that is not achievable by playing with the size of the model
or drop_out parameters in the vanilla transformer.
Args:
layer_inputs:
- state: state
step: indicates number of steps taken so far
hparams: model hyper-parameters
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
Returns:
layer_output:
new_state: new state
|
[
"Basic",
"Universal",
"Transformer",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L559-L590
|
train
|
Basic Universal Transformer.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(6662 - 6551) + chr(0b1011 + 0o47) + chr(684 - 635) + '\063', 0o10), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(12315 - 12204) + chr(0b110011) + '\062' + chr(0b110010), 0b1000), ehT0Px3KOsy9('\x30' + chr(2313 - 2202) + chr(0b110 + 0o53) + '\x36', 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1100111 + 0o10) + chr(514 - 465) + '\066' + chr(0b110101), 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\062' + chr(2503 - 2452) + '\x33', 0b1000), ehT0Px3KOsy9(chr(871 - 823) + chr(0b1100000 + 0o17) + chr(0b101100 + 0o6) + chr(0b100 + 0o54) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(51) + chr(0b11100 + 0o33) + chr(48), 47951 - 47943), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b111 + 0o54) + '\x36' + chr(49), 0o10), ehT0Px3KOsy9(chr(48) + chr(4714 - 4603) + chr(0b110101) + '\065', 0o10), ehT0Px3KOsy9(chr(1896 - 1848) + chr(0b1101111) + chr(53) + chr(0b11110 + 0o25), ord("\x08")), ehT0Px3KOsy9(chr(1900 - 1852) + chr(111) + chr(75 - 25) + '\060' + chr(330 - 276), 8), ehT0Px3KOsy9(chr(48) + '\157' + chr(1396 - 1344) + chr(54), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\063' + '\064' + '\066', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + chr(0b100001 + 0o17) + chr(0b11110 + 0o30), 0b1000), ehT0Px3KOsy9(chr(1937 - 1889) + chr(111) + chr(0b110001) + chr(2387 - 2336) + chr(48), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + '\x30', 54129 - 54121), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + chr(1156 - 1104) + chr(0b110011), 47131 - 47123), ehT0Px3KOsy9(chr(48) + chr(0b1100100 + 0o13) + chr(0b111 + 0o55) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110010) + chr(0b100 + 0o61) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + '\x33' + chr(54), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b1100 + 0o51) + chr(273 - 222), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101111 + 0o7) + chr(2333 - 2283), 3952 - 3944), ehT0Px3KOsy9(chr(48) + chr(3080 - 2969) + '\x37' + '\x33', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(1083 - 1035) + chr(0b100011 + 0o17), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(826 - 773) + chr(0b11101 + 0o27), 0b1000), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(0b1000000 + 0o57) + chr(1786 - 1736) + chr(50) + chr(1921 - 1872), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(52) + chr(0b110011), 8), ehT0Px3KOsy9(chr(2172 - 2124) + chr(111) + chr(498 - 449) + chr(0b110000) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(3457 - 3346) + chr(0b1100 + 0o52) + '\067', 54841 - 54833), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(10536 - 10425) + chr(1980 - 1929) + '\065' + chr(444 - 393), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + chr(0b110111) + '\065', 0o10), ehT0Px3KOsy9(chr(1382 - 1334) + chr(8050 - 7939) + chr(0b110011) + chr(50) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(54 - 0) + '\x37', 8), ehT0Px3KOsy9('\060' + chr(4422 - 4311) + '\062' + chr(50) + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010 + 0o145) + chr(1164 - 1110) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(1958 - 1910) + chr(3376 - 3265) + chr(903 - 852) + '\060', 62527 - 62519), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1010 + 0o50) + chr(49) + chr(0b11111 + 0o21), 0o10), ehT0Px3KOsy9(chr(342 - 294) + chr(1050 - 939) + chr(0b10100 + 0o36) + chr(0b11000 + 0o33), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(50) + chr(0b110011 + 0o2) + chr(2079 - 2031), 0b1000), ehT0Px3KOsy9('\060' + chr(8631 - 8520) + chr(0b110010) + chr(0b110000) + '\060', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\x6f' + chr(53) + chr(0b110000), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xa5'), '\144' + chr(0b1100001 + 0o4) + chr(0b1100011) + '\x6f' + chr(9786 - 9686) + chr(0b1010101 + 0o20))(chr(117) + chr(116) + '\146' + chr(0b101101) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def _jtXM4S1G97k(hdidhQtCKIOY, kDuFsAhEatcU, n4ljua2gi1Pr, SHRtjNoPzosY, ek3fs6JEXh0d):
(KKFQISrGeiAm, vXoupepMtCXU, KcR7WgfLppqF) = IDJ2eXGCBCDu.unstack(hdidhQtCKIOY, num=None, axis=ehT0Px3KOsy9(chr(771 - 723) + chr(8838 - 8727) + chr(53 - 5), 0b1000), name=xafqLlk3kkUe(SXOLrMavuUCe(b'\xfe\xbc}\x01\xfa\xe5\x93'), chr(8830 - 8730) + chr(101) + '\x63' + '\157' + '\x64' + '\x65')(chr(0b1110101) + chr(116) + '\x66' + chr(0b10111 + 0o26) + chr(56)))
bzRb0v_p_rjD = A2EO56BplgPh(KKFQISrGeiAm, kDuFsAhEatcU, n4ljua2gi1Pr)
for WVxHKyX45z_L in vQr8gNKaIaWE(xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b"\xe5\xa7c*\xf2\xe8\x8a\x94N^\xf4T\x83\xa8;u\xbcM\xcf'N@H"), chr(100) + chr(101) + '\143' + chr(0b1100101 + 0o12) + '\144' + '\x65')(chr(860 - 743) + '\164' + '\x66' + chr(1475 - 1430) + chr(56)))):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfd\xb3|\x1c\xfa\xe4\x94\x94rX\xe5I\x96\xa3'), chr(0b1100100) + chr(0b1100101) + chr(0b1100011) + chr(111) + chr(100) + '\x65')('\165' + chr(0b1110100) + chr(0b1011100 + 0o12) + '\x2d' + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xf9\xb7m*\xf7\xe7\x81\x94_t\xa3B'), '\144' + chr(1819 - 1718) + chr(99) + chr(0b1101111) + '\144' + '\145')('\x75' + '\x74' + '\146' + chr(45) + chr(0b111000)) % WVxHKyX45z_L):
bzRb0v_p_rjD = SHRtjNoPzosY(ek3fs6JEXh0d(bzRb0v_p_rjD))
return (bzRb0v_p_rjD, vXoupepMtCXU, KcR7WgfLppqF)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
universal_transformer_highway
|
def universal_transformer_highway(layer_inputs,
step, hparams,
ffn_unit,
attention_unit,
pad_remover=None):
"""Universal Transformer with highway connection.
It transforms the state using a block contaaining sel-attention and transition
function and wrap the whole block with a highway connection.
(the new state is a combination of the state and the transformed-state
based on cary/transform gates.)
Interesting observation:
Controlling the cary/transform gate with the original inputs works usually
better (i.e. hparams.gates_inputs="i")
Args:
layer_inputs:
- state: state
- inputs: the original embedded inputs (= inputs to the first step)
step: indicates number of steps taken so far
hparams: model hyper-parameters.
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
layer_output:
new_state: new state
inputs: the original embedded inputs (= inputs to the first step)
"""
state, inputs, memory = layer_inputs
new_state = step_preprocess(state, step, hparams)
for i in range(hparams.num_inrecurrence_layers):
with tf.variable_scope("rec_layer_%d" % i):
new_state = ffn_unit(attention_unit(new_state))
transformed_state = new_state
gate_inputs = []
if "s" in hparams.gates_inputs:
gate_inputs.append(state)
if "t" in hparams.gates_inputs:
gate_inputs.append(transformed_state)
if "i" in hparams.gates_inputs:
gate_inputs.append(inputs)
gate_ffn_layer = hparams.gate_ffn_layer
transform_gate = _ffn_layer_multi_inputs(
gate_inputs,
hparams,
ffn_layer_type=gate_ffn_layer,
name="transform",
bias_initializer=tf.constant_initializer(hparams.transform_bias_init),
activation=tf.sigmoid,
pad_remover=pad_remover,
preprocess=True,
postprocess=True)
if hparams.couple_carry_transform_gates:
carry_gate = tf.subtract(1.0, transform_gate, name="carry")
else:
carry_gate = _ffn_layer_multi_inputs(
gate_inputs,
hparams,
ffn_layer_type=gate_ffn_layer,
name="carry",
bias_initializer=tf.constant_initializer(-hparams.transform_bias_init),
activation=tf.sigmoid,
pad_remover=pad_remover,
preprocess=True,
postprocess=True)
new_state = state * carry_gate + transformed_state * transform_gate
tf.contrib.summary.scalar("highway_transform_gate_layer",
tf.reduce_mean(transform_gate))
tf.contrib.summary.scalar("highway_carry_gate_layer",
tf.reduce_mean(carry_gate))
return new_state, inputs, memory
|
python
|
def universal_transformer_highway(layer_inputs,
step, hparams,
ffn_unit,
attention_unit,
pad_remover=None):
"""Universal Transformer with highway connection.
It transforms the state using a block contaaining sel-attention and transition
function and wrap the whole block with a highway connection.
(the new state is a combination of the state and the transformed-state
based on cary/transform gates.)
Interesting observation:
Controlling the cary/transform gate with the original inputs works usually
better (i.e. hparams.gates_inputs="i")
Args:
layer_inputs:
- state: state
- inputs: the original embedded inputs (= inputs to the first step)
step: indicates number of steps taken so far
hparams: model hyper-parameters.
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
layer_output:
new_state: new state
inputs: the original embedded inputs (= inputs to the first step)
"""
state, inputs, memory = layer_inputs
new_state = step_preprocess(state, step, hparams)
for i in range(hparams.num_inrecurrence_layers):
with tf.variable_scope("rec_layer_%d" % i):
new_state = ffn_unit(attention_unit(new_state))
transformed_state = new_state
gate_inputs = []
if "s" in hparams.gates_inputs:
gate_inputs.append(state)
if "t" in hparams.gates_inputs:
gate_inputs.append(transformed_state)
if "i" in hparams.gates_inputs:
gate_inputs.append(inputs)
gate_ffn_layer = hparams.gate_ffn_layer
transform_gate = _ffn_layer_multi_inputs(
gate_inputs,
hparams,
ffn_layer_type=gate_ffn_layer,
name="transform",
bias_initializer=tf.constant_initializer(hparams.transform_bias_init),
activation=tf.sigmoid,
pad_remover=pad_remover,
preprocess=True,
postprocess=True)
if hparams.couple_carry_transform_gates:
carry_gate = tf.subtract(1.0, transform_gate, name="carry")
else:
carry_gate = _ffn_layer_multi_inputs(
gate_inputs,
hparams,
ffn_layer_type=gate_ffn_layer,
name="carry",
bias_initializer=tf.constant_initializer(-hparams.transform_bias_init),
activation=tf.sigmoid,
pad_remover=pad_remover,
preprocess=True,
postprocess=True)
new_state = state * carry_gate + transformed_state * transform_gate
tf.contrib.summary.scalar("highway_transform_gate_layer",
tf.reduce_mean(transform_gate))
tf.contrib.summary.scalar("highway_carry_gate_layer",
tf.reduce_mean(carry_gate))
return new_state, inputs, memory
|
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] |
Universal Transformer with highway connection.
It transforms the state using a block contaaining sel-attention and transition
function and wrap the whole block with a highway connection.
(the new state is a combination of the state and the transformed-state
based on cary/transform gates.)
Interesting observation:
Controlling the cary/transform gate with the original inputs works usually
better (i.e. hparams.gates_inputs="i")
Args:
layer_inputs:
- state: state
- inputs: the original embedded inputs (= inputs to the first step)
step: indicates number of steps taken so far
hparams: model hyper-parameters.
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
layer_output:
new_state: new state
inputs: the original embedded inputs (= inputs to the first step)
|
[
"Universal",
"Transformer",
"with",
"highway",
"connection",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L593-L682
|
train
|
Universal Transformer with highway connection.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b1010001 + 0o36) + '\066' + chr(1319 - 1270), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1315 - 1264) + '\067' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + chr(0b110 + 0o52) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1128 - 1077) + chr(0b100100 + 0o23) + chr(2172 - 2117), 32045 - 32037), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(0b110000) + chr(54), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + '\061' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1001111 + 0o40) + chr(0b110001 + 0o5), 0o10), ehT0Px3KOsy9(chr(913 - 865) + '\157' + chr(765 - 715) + chr(53) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1011110 + 0o21) + chr(62 - 13) + chr(0b11111 + 0o24), ord("\x08")), ehT0Px3KOsy9(chr(61 - 13) + chr(5054 - 4943) + chr(2306 - 2256) + '\x33' + '\x33', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + '\063' + chr(944 - 895), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(2250 - 2139) + chr(0b11001 + 0o35) + '\x32', 25031 - 25023), ehT0Px3KOsy9(chr(48) + chr(0b1100011 + 0o14) + chr(1825 - 1776) + chr(1504 - 1454) + '\060', 46897 - 46889), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + chr(48) + chr(0b10111 + 0o40), 9489 - 9481), ehT0Px3KOsy9(chr(48) + chr(0b110011 + 0o74) + chr(0b1101 + 0o46) + chr(0b100001 + 0o23) + chr(55), 10220 - 10212), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + chr(283 - 233), 15244 - 15236), ehT0Px3KOsy9(chr(1476 - 1428) + '\157' + chr(0b110001) + '\062' + chr(1507 - 1456), 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b1101111) + '\061' + chr(0b110011) + chr(0b1011 + 0o45), 0o10), ehT0Px3KOsy9(chr(478 - 430) + chr(111) + '\x36' + chr(440 - 391), 8), ehT0Px3KOsy9(chr(48) + chr(8710 - 8599) + chr(0b11011 + 0o26) + chr(0b10110 + 0o37), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110110) + chr(0b100100 + 0o22), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51) + '\x34' + chr(48), 55253 - 55245), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(50) + chr(717 - 666) + chr(0b110000), 0o10), ehT0Px3KOsy9('\060' + chr(11996 - 11885) + chr(0b110011) + chr(51) + chr(0b110001 + 0o6), 20418 - 20410), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(1761 - 1709) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1101111) + chr(1182 - 1133) + chr(51) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b1010 + 0o46) + '\x6f' + chr(0b110 + 0o53) + '\x30' + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b1011100 + 0o23) + '\063' + '\064' + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(5145 - 5034) + '\063' + chr(0b110100) + chr(881 - 833), 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101100 + 0o7) + chr(53) + chr(2113 - 2063), 42585 - 42577), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(111) + '\062' + chr(1306 - 1252) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110100) + '\060', 22562 - 22554), ehT0Px3KOsy9('\x30' + chr(9559 - 9448) + chr(0b10000 + 0o42) + chr(0b110000) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(1539 - 1491) + chr(5511 - 5400) + chr(350 - 299) + chr(0b110000) + chr(55), 8), ehT0Px3KOsy9('\060' + chr(0b1101010 + 0o5) + chr(2161 - 2111) + chr(53) + chr(0b110001 + 0o0), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(50) + '\x37' + chr(52), 27670 - 27662), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + '\065' + chr(1663 - 1612), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(50) + chr(0b100000 + 0o22) + '\x37', 0o10), ehT0Px3KOsy9(chr(55 - 7) + chr(0b1101111) + chr(0b10110 + 0o35) + chr(1144 - 1090) + '\x30', 0o10), ehT0Px3KOsy9(chr(713 - 665) + chr(111) + chr(51) + '\x30' + chr(0b110000), 7640 - 7632)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\x6f' + chr(53) + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x1f'), chr(0b1100100) + chr(3306 - 3205) + chr(0b1001100 + 0o27) + '\x6f' + chr(0b1100100) + chr(101))('\x75' + chr(7854 - 7738) + chr(7110 - 7008) + '\055' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def srPX5CAqqznq(hdidhQtCKIOY, kDuFsAhEatcU, n4ljua2gi1Pr, SHRtjNoPzosY, ek3fs6JEXh0d, bLDzE_zU4vXa=None):
(KKFQISrGeiAm, vXoupepMtCXU, KcR7WgfLppqF) = hdidhQtCKIOY
bzRb0v_p_rjD = A2EO56BplgPh(KKFQISrGeiAm, kDuFsAhEatcU, n4ljua2gi1Pr)
for WVxHKyX45z_L in vQr8gNKaIaWE(xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'_\x89\xac\xa0\xaf\xa4t\xcdh\xee\xab@5\xa9\x84w\x0c4PtS\x92\xeb'), chr(100) + '\145' + chr(2512 - 2413) + '\x6f' + chr(0b1100100) + chr(8885 - 8784))(chr(117) + '\164' + '\146' + chr(0b100001 + 0o14) + chr(0b100000 + 0o30)))):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'G\x9d\xb3\x96\xa7\xa8j\xcdT\xe8\xba] \xa2'), '\x64' + chr(7395 - 7294) + '\143' + chr(0b1101111) + chr(7191 - 7091) + '\x65')('\x75' + chr(0b1101101 + 0o7) + '\x66' + chr(433 - 388) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'C\x99\xa2\xa0\xaa\xab\x7f\xcdy\xc4\xfcV'), '\x64' + chr(0b1100101) + chr(0b1001110 + 0o25) + '\x6f' + chr(100) + chr(0b1100101))(chr(0b11010 + 0o133) + chr(9177 - 9061) + chr(0b1001010 + 0o34) + chr(0b101101) + chr(628 - 572)) % WVxHKyX45z_L):
bzRb0v_p_rjD = SHRtjNoPzosY(ek3fs6JEXh0d(bzRb0v_p_rjD))
mOMnObBgvPkH = bzRb0v_p_rjD
eLkRBVrr3UFV = []
if xafqLlk3kkUe(SXOLrMavuUCe(b'B'), chr(0b1010101 + 0o17) + '\145' + chr(0b101 + 0o136) + '\157' + chr(0b101011 + 0o71) + chr(0b101100 + 0o71))(chr(0b1110101) + chr(5058 - 4942) + chr(102) + chr(45) + '\070') in xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'V\x9d\xb5\x9a\xb5\x95o\xc6{\xee\xadA'), chr(4573 - 4473) + chr(5057 - 4956) + chr(99) + '\x6f' + chr(1416 - 1316) + chr(0b1100101))(chr(0b1000111 + 0o56) + '\x74' + chr(0b1100110) + '\055' + chr(289 - 233))):
xafqLlk3kkUe(eLkRBVrr3UFV, xafqLlk3kkUe(SXOLrMavuUCe(b'P\x8c\xb1\x9a\xa8\xae'), chr(1423 - 1323) + chr(101) + chr(0b100010 + 0o101) + '\157' + '\x64' + '\x65')('\165' + chr(0b1110100) + '\146' + chr(1439 - 1394) + chr(123 - 67)))(KKFQISrGeiAm)
if xafqLlk3kkUe(SXOLrMavuUCe(b'E'), chr(9826 - 9726) + chr(7927 - 7826) + chr(0b100011 + 0o100) + chr(111) + chr(0b11010 + 0o112) + '\145')('\165' + chr(0b1110100) + chr(102) + '\x2d' + chr(74 - 18)) in xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'V\x9d\xb5\x9a\xb5\x95o\xc6{\xee\xadA'), chr(0b1100100) + chr(7090 - 6989) + chr(0b1100011) + chr(111) + '\144' + '\145')(chr(0b1110101) + '\164' + chr(102) + chr(0b101101) + chr(0b101 + 0o63))):
xafqLlk3kkUe(eLkRBVrr3UFV, xafqLlk3kkUe(SXOLrMavuUCe(b'P\x8c\xb1\x9a\xa8\xae'), chr(6050 - 5950) + '\x65' + chr(0b1100011) + '\x6f' + chr(100) + chr(0b1010010 + 0o23))(chr(6156 - 6039) + chr(116) + chr(0b1110 + 0o130) + chr(0b101101) + '\070'))(mOMnObBgvPkH)
if xafqLlk3kkUe(SXOLrMavuUCe(b'X'), chr(0b1100100) + '\145' + '\143' + '\157' + chr(0b11000 + 0o114) + chr(8916 - 8815))(chr(117) + chr(116) + chr(0b1100101 + 0o1) + chr(0b101101) + chr(0b111000)) in xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'V\x9d\xb5\x9a\xb5\x95o\xc6{\xee\xadA'), '\x64' + '\x65' + chr(0b100000 + 0o103) + chr(0b1101111) + chr(0b100110 + 0o76) + '\x65')(chr(0b1000100 + 0o61) + chr(0b1110100) + chr(0b1100110) + chr(0b0 + 0o55) + chr(0b111000))):
xafqLlk3kkUe(eLkRBVrr3UFV, xafqLlk3kkUe(SXOLrMavuUCe(b'P\x8c\xb1\x9a\xa8\xae'), chr(0b1100100) + '\x65' + chr(0b101010 + 0o71) + chr(0b1101111) + chr(7917 - 7817) + '\145')(chr(0b1110101) + chr(4374 - 4258) + chr(0b1100110) + chr(808 - 763) + chr(2001 - 1945)))(vXoupepMtCXU)
GDlKOOMoQbEe = n4ljua2gi1Pr.gate_ffn_layer
RKFDWuquDeS6 = TlcH9M_VkXCB(eLkRBVrr3UFV, n4ljua2gi1Pr, ffn_layer_type=GDlKOOMoQbEe, name=xafqLlk3kkUe(SXOLrMavuUCe(b'E\x8e\xa0\x91\xb5\xaci\xdaf'), chr(0b1100100) + chr(101) + '\x63' + '\x6f' + chr(0b1100100) + chr(4145 - 4044))('\165' + '\164' + chr(6887 - 6785) + chr(726 - 681) + chr(0b111000)), bias_initializer=IDJ2eXGCBCDu.constant_initializer(n4ljua2gi1Pr.transform_bias_init), activation=IDJ2eXGCBCDu.sigmoid, pad_remover=bLDzE_zU4vXa, preprocess=ehT0Px3KOsy9(chr(346 - 298) + chr(4144 - 4033) + '\061', 24491 - 24483), postprocess=ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b1101111) + '\061', 8))
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'R\x93\xb4\x8f\xaa\xafY\xcbj\xe9\xabK\x0f\xb3\x95s=+WbD\x8d\xc7\xb8\xc2.&\x97'), chr(0b111110 + 0o46) + '\145' + chr(0b1010 + 0o131) + '\157' + chr(1262 - 1162) + chr(0b100101 + 0o100))('\165' + chr(0b11 + 0o161) + chr(1774 - 1672) + chr(0b1111 + 0o36) + chr(56))):
d31A_8USniMH = IDJ2eXGCBCDu.subtract(1.0, RKFDWuquDeS6, name=xafqLlk3kkUe(SXOLrMavuUCe(b'R\x9d\xb3\x8d\xbf'), chr(0b1100100) + chr(4982 - 4881) + chr(0b1100011) + '\157' + chr(0b1100100) + '\x65')(chr(339 - 222) + chr(0b101001 + 0o113) + chr(400 - 298) + '\055' + chr(0b111000)))
else:
d31A_8USniMH = TlcH9M_VkXCB(eLkRBVrr3UFV, n4ljua2gi1Pr, ffn_layer_type=GDlKOOMoQbEe, name=xafqLlk3kkUe(SXOLrMavuUCe(b'R\x9d\xb3\x8d\xbf'), '\144' + chr(101) + '\x63' + chr(0b1001100 + 0o43) + chr(3565 - 3465) + chr(0b1100101))(chr(13443 - 13326) + chr(0b1110100) + chr(4240 - 4138) + '\x2d' + chr(0b100010 + 0o26)), bias_initializer=IDJ2eXGCBCDu.constant_initializer(-n4ljua2gi1Pr.transform_bias_init), activation=IDJ2eXGCBCDu.sigmoid, pad_remover=bLDzE_zU4vXa, preprocess=ehT0Px3KOsy9('\x30' + chr(938 - 827) + chr(49), 8), postprocess=ehT0Px3KOsy9('\x30' + chr(111) + chr(49), 8))
bzRb0v_p_rjD = KKFQISrGeiAm * d31A_8USniMH + mOMnObBgvPkH * RKFDWuquDeS6
xafqLlk3kkUe(IDJ2eXGCBCDu.contrib.summary, xafqLlk3kkUe(SXOLrMavuUCe(b'B\x9f\xa0\x93\xa7\xb8'), chr(0b1100100) + '\145' + '\x63' + '\x6f' + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + chr(0b101 + 0o157) + chr(102) + chr(0b101101) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'Y\x95\xa6\x97\xb1\xab\x7f\xf7\x7f\xe9\xb8\\#\xa1\x88`>\x07VlB\x85\xc7\xb3\xc2#&\x96'), chr(0b1001011 + 0o31) + '\x65' + chr(0b1100011) + chr(7370 - 7259) + chr(516 - 416) + '\x65')(chr(0b1000 + 0o155) + chr(0b100 + 0o160) + '\146' + chr(0b101101) + chr(0b11111 + 0o31)), xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'C\x99\xa5\x8a\xa5\xafY\xc5n\xfa\xb7'), '\144' + '\145' + chr(0b1100011) + chr(111) + '\x64' + chr(101))('\x75' + chr(0b110111 + 0o75) + '\146' + '\055' + chr(0b111000)))(RKFDWuquDeS6))
xafqLlk3kkUe(IDJ2eXGCBCDu.contrib.summary, xafqLlk3kkUe(SXOLrMavuUCe(b'B\x9f\xa0\x93\xa7\xb8'), chr(6130 - 6030) + chr(101) + chr(0b1001010 + 0o31) + '\x6f' + '\144' + chr(0b1011010 + 0o13))('\165' + chr(10442 - 10326) + chr(102) + chr(572 - 527) + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b"Y\x95\xa6\x97\xb1\xab\x7f\xf7h\xfa\xab@)\x98\x80s'=naW\x99\xfd\xad"), chr(1941 - 1841) + chr(0b1100101) + chr(99) + chr(111) + chr(0b1100100) + chr(7034 - 6933))('\x75' + chr(1839 - 1723) + chr(0b1000 + 0o136) + chr(1695 - 1650) + '\070'), xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'C\x99\xa5\x8a\xa5\xafY\xc5n\xfa\xb7'), chr(6286 - 6186) + chr(0b1100101) + chr(0b1100011) + '\157' + chr(0b1100100) + chr(0b1100101))(chr(117) + chr(116) + chr(2598 - 2496) + chr(357 - 312) + '\x38'))(d31A_8USniMH))
return (bzRb0v_p_rjD, vXoupepMtCXU, KcR7WgfLppqF)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
universal_transformer_depthwise_attention
|
def universal_transformer_depthwise_attention(layer_inputs,
step, hparams,
ffn_unit,
attention_unit):
"""universal_transformer with depth-wise attention.
It uses an attention mechanism-flipped vertically-
over all the states from previous steps to generate the new_state.
Args:
layer_inputs:
- state: state
- memory: contains states from all the previous steps.
step: indicating number of steps take so far
hparams: model hyper-parameters.
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
Returns:
layer_output:
new_state: new state
memory: contains states from all the previous steps.
"""
_, inputs, memory = layer_inputs
all_states = memory
# add depth signal
if hparams.depth_embedding:
all_states = add_depth_embedding(all_states)
# get the states up to the current step (non-zero part of the memory)
states_so_far = all_states[:step, :, :, :]
states_so_far_weights = tf.nn.softmax(
common_layers.dense(
states_so_far, (hparams.hidden_size if hparams.dwa_elements else 1),
activation=None,
use_bias=True),
axis=-1)
# prepare the state tensor that will be transformed
state_to_be_transformed = tf.reduce_sum(
(states_so_far * states_so_far_weights), axis=0)
new_state = step_preprocess(state_to_be_transformed, step, hparams)
for i in range(hparams.num_inrecurrence_layers):
with tf.variable_scope("rec_layer_%d" % i):
new_state = ffn_unit(attention_unit(new_state))
# add the new state to the memory
memory = fill_memory_slot(memory, new_state, step + 1)
return new_state, inputs, memory
|
python
|
def universal_transformer_depthwise_attention(layer_inputs,
step, hparams,
ffn_unit,
attention_unit):
"""universal_transformer with depth-wise attention.
It uses an attention mechanism-flipped vertically-
over all the states from previous steps to generate the new_state.
Args:
layer_inputs:
- state: state
- memory: contains states from all the previous steps.
step: indicating number of steps take so far
hparams: model hyper-parameters.
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
Returns:
layer_output:
new_state: new state
memory: contains states from all the previous steps.
"""
_, inputs, memory = layer_inputs
all_states = memory
# add depth signal
if hparams.depth_embedding:
all_states = add_depth_embedding(all_states)
# get the states up to the current step (non-zero part of the memory)
states_so_far = all_states[:step, :, :, :]
states_so_far_weights = tf.nn.softmax(
common_layers.dense(
states_so_far, (hparams.hidden_size if hparams.dwa_elements else 1),
activation=None,
use_bias=True),
axis=-1)
# prepare the state tensor that will be transformed
state_to_be_transformed = tf.reduce_sum(
(states_so_far * states_so_far_weights), axis=0)
new_state = step_preprocess(state_to_be_transformed, step, hparams)
for i in range(hparams.num_inrecurrence_layers):
with tf.variable_scope("rec_layer_%d" % i):
new_state = ffn_unit(attention_unit(new_state))
# add the new state to the memory
memory = fill_memory_slot(memory, new_state, step + 1)
return new_state, inputs, memory
|
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] |
universal_transformer with depth-wise attention.
It uses an attention mechanism-flipped vertically-
over all the states from previous steps to generate the new_state.
Args:
layer_inputs:
- state: state
- memory: contains states from all the previous steps.
step: indicating number of steps take so far
hparams: model hyper-parameters.
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
Returns:
layer_output:
new_state: new state
memory: contains states from all the previous steps.
|
[
"universal_transformer",
"with",
"depth",
"-",
"wise",
"attention",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L777-L832
|
train
|
Universal Transformer with depth - wise attention.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1990 - 1942) + chr(0b1101111) + '\x36' + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\x37' + chr(53), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(54) + chr(0b1101 + 0o46), 814 - 806), ehT0Px3KOsy9(chr(629 - 581) + chr(9538 - 9427) + chr(50) + chr(49) + '\067', 0o10), ehT0Px3KOsy9(chr(2278 - 2230) + '\157' + chr(0b100001 + 0o20) + '\061' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + chr(0b10001 + 0o46) + '\x37', 0o10), ehT0Px3KOsy9('\x30' + chr(3447 - 3336) + chr(50) + chr(0b110000) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(1723 - 1675) + chr(111) + chr(51) + chr(382 - 331) + chr(0b10011 + 0o41), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1058 - 1009) + chr(0b110010 + 0o4) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(5152 - 5041) + chr(1432 - 1382) + '\x31' + chr(55), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x36' + chr(50), 0b1000), ehT0Px3KOsy9(chr(256 - 208) + chr(111) + chr(0b1 + 0o62) + chr(0b100111 + 0o15) + chr(53), 0o10), ehT0Px3KOsy9('\x30' + chr(0b110000 + 0o77) + chr(0b1010 + 0o47) + chr(0b110100) + chr(2878 - 2824), 18783 - 18775), ehT0Px3KOsy9('\x30' + chr(10074 - 9963) + chr(646 - 596) + '\x36' + '\x34', 27624 - 27616), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1100 + 0o47) + chr(0b11111 + 0o25) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(3399 - 3288) + chr(51) + '\x34' + '\066', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100100 + 0o13) + '\063' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(7940 - 7829) + chr(0b10010 + 0o40), 53396 - 53388), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(10062 - 9951) + '\x33' + '\066' + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1085 - 1036) + '\065' + chr(0b100010 + 0o20), 59946 - 59938), ehT0Px3KOsy9(chr(429 - 381) + '\x6f' + chr(49) + chr(49) + chr(0b11000 + 0o31), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10010 + 0o37) + chr(54) + chr(0b110110), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b111 + 0o54) + '\x31' + '\064', 61501 - 61493), ehT0Px3KOsy9(chr(0b110000) + chr(0b110010 + 0o75) + '\x32' + '\060' + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + chr(348 - 237) + chr(0b11 + 0o56) + chr(0b1100 + 0o53) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\063' + '\067' + '\064', 989 - 981), ehT0Px3KOsy9(chr(1597 - 1549) + chr(2570 - 2459) + chr(49) + chr(974 - 921) + '\062', 8), ehT0Px3KOsy9(chr(1549 - 1501) + chr(111) + chr(52) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b11000 + 0o31) + chr(0b110010) + chr(2098 - 2050), 15947 - 15939), ehT0Px3KOsy9(chr(1651 - 1603) + chr(111) + chr(51) + chr(0b11001 + 0o34) + '\062', 58262 - 58254), ehT0Px3KOsy9('\060' + '\157' + '\065' + chr(53), 0o10), ehT0Px3KOsy9(chr(2026 - 1978) + chr(0b100100 + 0o113) + chr(0b100001 + 0o21) + '\x36' + '\061', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110010) + chr(0b101 + 0o56) + chr(54), 26722 - 26714), ehT0Px3KOsy9(chr(329 - 281) + chr(111) + chr(1391 - 1342) + chr(556 - 502) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(2017 - 1969) + chr(0b1101111) + chr(0b110010) + chr(0b110001) + chr(0b1111 + 0o42), 35743 - 35735), ehT0Px3KOsy9('\x30' + chr(1830 - 1719) + '\x36' + chr(52), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b100110 + 0o111) + chr(0b110001) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + '\x34' + chr(49), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + chr(49) + '\064', 0o10), ehT0Px3KOsy9(chr(619 - 571) + chr(0b110110 + 0o71) + chr(2290 - 2239) + chr(0b1001 + 0o55) + chr(0b10110 + 0o34), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(333 - 285) + chr(0b1101111) + chr(53) + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x19'), '\x64' + chr(3489 - 3388) + chr(99) + chr(0b111011 + 0o64) + chr(9133 - 9033) + '\x65')('\165' + chr(8368 - 8252) + chr(1126 - 1024) + '\055' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def OQtyjirAul6I(hdidhQtCKIOY, kDuFsAhEatcU, n4ljua2gi1Pr, SHRtjNoPzosY, ek3fs6JEXh0d):
(VNGQdHSFPrso, vXoupepMtCXU, KcR7WgfLppqF) = hdidhQtCKIOY
CFqvId6mdO_e = KcR7WgfLppqF
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b"SXC\xfb' \xe4\xb1\x11\xeaV\x81\x0f\xda\x81"), chr(1372 - 1272) + '\x65' + chr(0b1100011) + '\157' + chr(6778 - 6678) + chr(0b101110 + 0o67))(chr(12180 - 12063) + chr(11958 - 11842) + '\x66' + '\x2d' + '\x38')):
CFqvId6mdO_e = B4mMKRG89s7X(CFqvId6mdO_e)
IrS03T3Rtelk = CFqvId6mdO_e[:kDuFsAhEatcU, :, :, :]
AwYg6vvZKVX2 = IDJ2eXGCBCDu.nn.softmax(jSKPaHwSAfVv.dense(IrS03T3Rtelk, n4ljua2gi1Pr.qzoyXN3kdhDL if n4ljua2gi1Pr.dwa_elements else ehT0Px3KOsy9(chr(48) + chr(0b1010 + 0o145) + '\x31', 0o10), activation=None, use_bias=ehT0Px3KOsy9(chr(72 - 24) + chr(8162 - 8051) + chr(0b110001), 8)), axis=-ehT0Px3KOsy9(chr(0b110000) + chr(0b1000010 + 0o55) + chr(0b110001), 8))
PbYp3B2AwbqO = IDJ2eXGCBCDu.reduce_sum(IrS03T3Rtelk * AwYg6vvZKVX2, axis=ehT0Px3KOsy9(chr(0b110000) + chr(0b11 + 0o154) + '\060', 0b1000))
bzRb0v_p_rjD = A2EO56BplgPh(PbYp3B2AwbqO, kDuFsAhEatcU, n4ljua2gi1Pr)
for WVxHKyX45z_L in vQr8gNKaIaWE(xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'YH^\xd0&\x11\xf3\xb9\x10\xfa@\x97\x03\xda\x85\x83An\x95\x13,\x04\xbf'), chr(100) + '\x65' + '\x63' + chr(8195 - 8084) + chr(0b100011 + 0o101) + '\x65')(chr(117) + chr(0b100001 + 0o123) + chr(3695 - 3593) + chr(0b101101) + '\070'))):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'A\\A\xe6.\x1d\xed\xb9,\xfcQ\x8a\x16\xd1'), chr(100) + '\x65' + chr(7699 - 7600) + chr(0b1101111) + '\144' + chr(101))(chr(0b1001000 + 0o55) + chr(0b1110100) + chr(0b1100110) + chr(0b110 + 0o47) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'EXP\xd0#\x1e\xf8\xb9\x01\xd0\x17\x81'), '\x64' + chr(101) + chr(99) + chr(1951 - 1840) + '\x64' + chr(0b100 + 0o141))(chr(0b101010 + 0o113) + '\164' + chr(102) + chr(0b101101) + chr(0b111000)) % WVxHKyX45z_L):
bzRb0v_p_rjD = SHRtjNoPzosY(ek3fs6JEXh0d(bzRb0v_p_rjD))
KcR7WgfLppqF = nWMmlaB9bcqE(KcR7WgfLppqF, bzRb0v_p_rjD, kDuFsAhEatcU + ehT0Px3KOsy9('\x30' + '\157' + '\x31', 8))
return (bzRb0v_p_rjD, vXoupepMtCXU, KcR7WgfLppqF)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
universal_transformer_with_gru_as_transition_function
|
def universal_transformer_with_gru_as_transition_function(
layer_inputs, step, hparams, ffn_unit, attention_unit, pad_remover=None):
"""Universal Transformer which uses a gru as transition function.
It's kind of like having a gru, filliped vertically next to the Universal
Transformer that controls the flow of the information in depth,
over different steps of the Universal Transformer.
Args:
layer_inputs:
- state: state
- inputs: not used here
- memory: not used here
step: indicates number of steps taken so far
hparams: model hyper-parameters.
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
layer_output:
new_state: new state
inputs: not uesed
memory: not used
"""
state, unused_inputs, unused_memory = tf.unstack(
layer_inputs, num=None, axis=0, name="unstack")
# state (ut_state): output of the gru in the previous step
# Multi_head_attention:
assert not hparams.add_step_timing_signal # Let gru count for us!
mh_attention_input = step_preprocess(state, step, hparams)
transition_function_input = attention_unit(mh_attention_input)
# Transition Function:
if hparams.add_ffn_unit_to_the_transition_function:
transition_function_input = ffn_unit(transition_function_input)
transition_function_input = common_layers.layer_preprocess(
transition_function_input, hparams)
with tf.variable_scope("gru"):
# gru update gate: z_t = sigmoid(W_z.x_t + U_z.h_{t-1})
transition_function_update_gate = _ffn_layer_multi_inputs(
[transition_function_input, state],
hparams,
name="update",
bias_initializer=tf.constant_initializer(1.0),
activation=tf.sigmoid,
pad_remover=pad_remover,
preprocess=False,
postprocess=False)
tf.contrib.summary.scalar("gru_update_gate",
tf.reduce_mean(transition_function_update_gate))
# gru reset gate: r_t = sigmoid(W_r.x_t + U_r.h_{t-1})
transition_function_reset_gate = _ffn_layer_multi_inputs(
[transition_function_input, state],
hparams,
name="reset",
bias_initializer=tf.constant_initializer(1.0),
activation=tf.sigmoid,
pad_remover=pad_remover,
preprocess=False,
postprocess=False)
tf.contrib.summary.scalar("gru_reset_gate",
tf.reduce_mean(transition_function_reset_gate))
reset_state = transition_function_reset_gate * state
# gru_candidate_activation: h' = tanh(W_{x_t} + U (r_t h_{t-1})
transition_function_candidate = _ffn_layer_multi_inputs(
[transition_function_input, reset_state],
hparams,
name="candidate",
bias_initializer=tf.zeros_initializer(),
activation=tf.tanh,
pad_remover=pad_remover,
preprocess=False,
postprocess=False)
transition_function_output = (
(1 - transition_function_update_gate) * transition_function_input +
transition_function_update_gate * transition_function_candidate)
transition_function_output = common_layers.layer_preprocess(
transition_function_output, hparams)
return transition_function_output, unused_inputs, unused_memory
|
python
|
def universal_transformer_with_gru_as_transition_function(
layer_inputs, step, hparams, ffn_unit, attention_unit, pad_remover=None):
"""Universal Transformer which uses a gru as transition function.
It's kind of like having a gru, filliped vertically next to the Universal
Transformer that controls the flow of the information in depth,
over different steps of the Universal Transformer.
Args:
layer_inputs:
- state: state
- inputs: not used here
- memory: not used here
step: indicates number of steps taken so far
hparams: model hyper-parameters.
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
layer_output:
new_state: new state
inputs: not uesed
memory: not used
"""
state, unused_inputs, unused_memory = tf.unstack(
layer_inputs, num=None, axis=0, name="unstack")
# state (ut_state): output of the gru in the previous step
# Multi_head_attention:
assert not hparams.add_step_timing_signal # Let gru count for us!
mh_attention_input = step_preprocess(state, step, hparams)
transition_function_input = attention_unit(mh_attention_input)
# Transition Function:
if hparams.add_ffn_unit_to_the_transition_function:
transition_function_input = ffn_unit(transition_function_input)
transition_function_input = common_layers.layer_preprocess(
transition_function_input, hparams)
with tf.variable_scope("gru"):
# gru update gate: z_t = sigmoid(W_z.x_t + U_z.h_{t-1})
transition_function_update_gate = _ffn_layer_multi_inputs(
[transition_function_input, state],
hparams,
name="update",
bias_initializer=tf.constant_initializer(1.0),
activation=tf.sigmoid,
pad_remover=pad_remover,
preprocess=False,
postprocess=False)
tf.contrib.summary.scalar("gru_update_gate",
tf.reduce_mean(transition_function_update_gate))
# gru reset gate: r_t = sigmoid(W_r.x_t + U_r.h_{t-1})
transition_function_reset_gate = _ffn_layer_multi_inputs(
[transition_function_input, state],
hparams,
name="reset",
bias_initializer=tf.constant_initializer(1.0),
activation=tf.sigmoid,
pad_remover=pad_remover,
preprocess=False,
postprocess=False)
tf.contrib.summary.scalar("gru_reset_gate",
tf.reduce_mean(transition_function_reset_gate))
reset_state = transition_function_reset_gate * state
# gru_candidate_activation: h' = tanh(W_{x_t} + U (r_t h_{t-1})
transition_function_candidate = _ffn_layer_multi_inputs(
[transition_function_input, reset_state],
hparams,
name="candidate",
bias_initializer=tf.zeros_initializer(),
activation=tf.tanh,
pad_remover=pad_remover,
preprocess=False,
postprocess=False)
transition_function_output = (
(1 - transition_function_update_gate) * transition_function_input +
transition_function_update_gate * transition_function_candidate)
transition_function_output = common_layers.layer_preprocess(
transition_function_output, hparams)
return transition_function_output, unused_inputs, unused_memory
|
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] |
Universal Transformer which uses a gru as transition function.
It's kind of like having a gru, filliped vertically next to the Universal
Transformer that controls the flow of the information in depth,
over different steps of the Universal Transformer.
Args:
layer_inputs:
- state: state
- inputs: not used here
- memory: not used here
step: indicates number of steps taken so far
hparams: model hyper-parameters.
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
layer_output:
new_state: new state
inputs: not uesed
memory: not used
|
[
"Universal",
"Transformer",
"which",
"uses",
"a",
"gru",
"as",
"transition",
"function",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L835-L924
|
train
|
Universal Transformer which uses a gru as transition function.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(111) + '\x32' + '\060' + '\063', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b101110 + 0o4) + chr(0b111 + 0o52) + chr(0b0 + 0o67), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110011), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1 + 0o60) + '\x34' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(8211 - 8100) + '\x32' + chr(2324 - 2275) + chr(0b110111), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + chr(0b11010 + 0o34), 42951 - 42943), ehT0Px3KOsy9(chr(0b110000) + chr(0b11001 + 0o126) + chr(1493 - 1443) + chr(0b110111) + chr(0b101011 + 0o6), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b0 + 0o63) + '\x30' + '\065', 8289 - 8281), ehT0Px3KOsy9(chr(636 - 588) + '\157' + '\063' + '\x35' + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110100) + chr(1642 - 1594), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + chr(124 - 71), 33220 - 33212), ehT0Px3KOsy9(chr(1877 - 1829) + chr(0b111010 + 0o65) + chr(0b11001 + 0o31) + chr(2295 - 2245) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(1948 - 1900) + chr(0b11000 + 0o127) + chr(50) + '\061' + chr(2157 - 2107), 11725 - 11717), ehT0Px3KOsy9('\060' + chr(0b10010 + 0o135) + chr(0b110011) + '\x33' + chr(49), 0o10), ehT0Px3KOsy9(chr(585 - 537) + chr(111) + '\x32' + chr(0b110111) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b1101111) + '\063' + '\x36', 8), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(111) + chr(0b110010) + chr(0b110100) + '\061', 35788 - 35780), ehT0Px3KOsy9('\060' + chr(0b100100 + 0o113) + chr(2363 - 2313) + '\064' + chr(708 - 658), 0b1000), ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\157' + '\x32' + '\x31' + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + '\061' + '\x30', 8), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(0b1101111) + chr(51) + '\066', 8), ehT0Px3KOsy9(chr(48) + chr(2536 - 2425) + '\062' + chr(0b110100) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(1428 - 1380) + chr(6675 - 6564) + '\064', 21488 - 21480), ehT0Px3KOsy9(chr(1632 - 1584) + chr(111) + chr(0b110010) + chr(0b111 + 0o52) + chr(983 - 935), 8), ehT0Px3KOsy9(chr(0b100110 + 0o12) + '\157' + chr(49) + '\x31', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(2110 - 2060) + chr(0b110010) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(7750 - 7639) + chr(0b110010 + 0o0) + chr(0b1011 + 0o50) + '\x34', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(51) + chr(0b11 + 0o61) + '\063', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + chr(0b110110) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1373 - 1322) + '\x34', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(55) + chr(53), 55135 - 55127), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b11010 + 0o27) + chr(0b11010 + 0o35), ord("\x08")), ehT0Px3KOsy9(chr(327 - 279) + '\x6f' + chr(0b1011 + 0o46) + chr(2022 - 1970) + chr(0b11 + 0o63), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + chr(0b110101) + chr(0b110010), 1621 - 1613), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b100110 + 0o13) + chr(0b110100) + '\063', 0o10), ehT0Px3KOsy9(chr(493 - 445) + '\x6f' + '\063' + chr(0b110001 + 0o4) + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\x6f' + chr(2282 - 2230), 8), ehT0Px3KOsy9(chr(1728 - 1680) + chr(0b1101111) + chr(0b110001) + chr(48) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(7360 - 7249) + chr(49) + chr(54) + chr(55), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(646 - 535) + chr(0b11 + 0o62) + '\060', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xad'), '\144' + chr(3134 - 3033) + chr(9386 - 9287) + '\x6f' + '\x64' + '\x65')(chr(0b1001 + 0o154) + chr(0b1010100 + 0o40) + chr(102) + chr(354 - 309) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def DEi5fowvIvk0(hdidhQtCKIOY, kDuFsAhEatcU, n4ljua2gi1Pr, SHRtjNoPzosY, ek3fs6JEXh0d, bLDzE_zU4vXa=None):
(KKFQISrGeiAm, nwxKmaSu5BSm, evuFeQ4CXEC8) = IDJ2eXGCBCDu.unstack(hdidhQtCKIOY, num=None, axis=ehT0Px3KOsy9('\x30' + chr(0b1011010 + 0o25) + chr(48), 8), name=xafqLlk3kkUe(SXOLrMavuUCe(b'\xf6\xe1p\x15\xee}\xd2'), '\144' + '\x65' + '\x63' + chr(0b1101111) + chr(0b1000011 + 0o41) + '\145')(chr(3452 - 3335) + chr(116) + chr(0b1100110) + chr(496 - 451) + '\x38'))
assert not xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe2\xebg>\xfcj\xdc\xb5\xb5Tt\xfc\xe3\xb7\xdcA\xd2\xcb\xef\xe6\x7f\xca'), chr(9618 - 9518) + chr(0b1100101) + chr(0b1100011) + '\157' + chr(0b1001 + 0o133) + chr(0b1100101))(chr(117) + '\x74' + '\146' + chr(0b101101) + '\x38'))
tJH321jQYcIb = A2EO56BplgPh(KKFQISrGeiAm, kDuFsAhEatcU, n4ljua2gi1Pr)
hmthMC4Pao6T = ek3fs6JEXh0d(tJH321jQYcIb)
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe2\xebg>\xe9x\xd7\x9a\x9fNt\xe5\xd5\xad\xd4A\xd5\xca\xed\xd7j\xd4e\xe6z\xfa\xe8\x8a\x1drbi\x13\xc4\x00\x99ik-'), chr(0b101011 + 0o71) + chr(0b1000110 + 0o37) + '\x63' + '\x6f' + chr(0b101100 + 0o70) + chr(9423 - 9322))(chr(117) + chr(7550 - 7434) + chr(0b100110 + 0o100) + '\055' + chr(1246 - 1190))):
hmthMC4Pao6T = SHRtjNoPzosY(hmthMC4Pao6T)
hmthMC4Pao6T = jSKPaHwSAfVv.layer_preprocess(hmthMC4Pao6T, n4ljua2gi1Pr)
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf5\xeeq\x08\xee|\xd5\xa0\xb5S~\xfe\xfa\xbc'), '\x64' + chr(8295 - 8194) + chr(99) + chr(0b1101111) + '\x64' + chr(101))('\165' + '\164' + '\146' + chr(45) + chr(0b101 + 0o63)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xe4\xfdv'), '\x64' + '\145' + chr(0b1100011) + chr(0b1101111) + chr(100) + chr(0b1100101))(chr(0b1110010 + 0o3) + chr(116) + chr(0b101111 + 0o67) + '\055' + chr(56))):
Gh7Xq2jRUAYN = TlcH9M_VkXCB([hmthMC4Pao6T, KKFQISrGeiAm], n4ljua2gi1Pr, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\xf6\xffg\x00\xfb{'), '\144' + chr(9044 - 8943) + chr(0b101011 + 0o70) + chr(111) + chr(0b1100100) + chr(0b110100 + 0o61))(chr(0b101010 + 0o113) + '\164' + '\146' + '\055' + chr(56)), bias_initializer=IDJ2eXGCBCDu.constant_initializer(1.0), activation=IDJ2eXGCBCDu.sigmoid, pad_remover=bLDzE_zU4vXa, preprocess=ehT0Px3KOsy9(chr(306 - 258) + chr(0b1101111) + chr(0b110000), 8), postprocess=ehT0Px3KOsy9(chr(258 - 210) + '\157' + chr(48), 8))
xafqLlk3kkUe(IDJ2eXGCBCDu.contrib.summary, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf0\xecb\r\xeel'), chr(5746 - 5646) + chr(5865 - 5764) + chr(0b100010 + 0o101) + chr(1770 - 1659) + chr(1867 - 1767) + chr(7384 - 7283))(chr(4510 - 4393) + chr(3133 - 3017) + chr(0b100101 + 0o101) + chr(0b100010 + 0o13) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xe4\xfdv>\xfan\xdd\xa4\x9eEB\xf6\xeb\xad\xde'), chr(0b10 + 0o142) + chr(101) + chr(99) + '\157' + '\x64' + chr(101))(chr(117) + chr(0b1110100) + chr(809 - 707) + chr(1869 - 1824) + chr(0b0 + 0o70)), xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf1\xeag\x14\xec{\xe6\xa8\x8fAs'), '\144' + '\145' + chr(9577 - 9478) + chr(111) + '\144' + chr(0b100100 + 0o101))(chr(12354 - 12237) + chr(4895 - 4779) + chr(0b11011 + 0o113) + chr(0b101101) + '\070'))(Gh7Xq2jRUAYN))
_gB1Is05ooYe = TlcH9M_VkXCB([hmthMC4Pao6T, KKFQISrGeiAm], n4ljua2gi1Pr, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\xf1\xeap\x04\xfb'), chr(0b1100100) + chr(0b1100101) + chr(99) + chr(0b1101111) + chr(100) + '\x65')('\x75' + '\x74' + chr(102) + chr(394 - 349) + '\x38'), bias_initializer=IDJ2eXGCBCDu.constant_initializer(1.0), activation=IDJ2eXGCBCDu.sigmoid, pad_remover=bLDzE_zU4vXa, preprocess=ehT0Px3KOsy9(chr(48) + chr(111) + chr(578 - 530), 8), postprocess=ehT0Px3KOsy9('\060' + chr(0b1100001 + 0o16) + chr(0b110000), 8))
xafqLlk3kkUe(IDJ2eXGCBCDu.contrib.summary, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf0\xecb\r\xeel'), '\144' + '\145' + chr(0b1100011) + chr(660 - 549) + '\144' + chr(0b1100101))(chr(6847 - 6730) + chr(0b101100 + 0o110) + chr(8595 - 8493) + chr(0b101101) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xe4\xfdv>\xfd{\xca\xa0\x9e\x7fz\xf0\xfe\xbc'), chr(0b1011100 + 0o10) + '\145' + chr(0b10000 + 0o123) + chr(111) + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + '\x74' + '\146' + chr(0b100 + 0o51) + chr(56)), xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf1\xeag\x14\xec{\xe6\xa8\x8fAs'), '\144' + chr(101) + chr(0b11011 + 0o110) + chr(0b1100 + 0o143) + chr(6906 - 6806) + '\x65')('\x75' + chr(0b1110100) + chr(0b1100110) + chr(2011 - 1966) + chr(0b110011 + 0o5)))(_gB1Is05ooYe))
xBbxQetPUTXG = _gB1Is05ooYe * KKFQISrGeiAm
tqU_D98HBRmt = TlcH9M_VkXCB([hmthMC4Pao6T, xBbxQetPUTXG], n4ljua2gi1Pr, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\xe0\xeem\x05\xe6z\xd8\xb1\x8f'), chr(100) + chr(101) + chr(7349 - 7250) + chr(111) + '\x64' + chr(101))(chr(4297 - 4180) + chr(116) + '\146' + chr(0b101101) + chr(0b111000)), bias_initializer=IDJ2eXGCBCDu.zeros_initializer(), activation=IDJ2eXGCBCDu.tanh, pad_remover=bLDzE_zU4vXa, preprocess=ehT0Px3KOsy9(chr(2173 - 2125) + '\x6f' + chr(2212 - 2164), 8), postprocess=ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b1001101 + 0o42) + '\060', 8))
G4J1HOKlqSFw = (ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(111) + '\061', ord("\x08")) - Gh7Xq2jRUAYN) * hmthMC4Pao6T + Gh7Xq2jRUAYN * tqU_D98HBRmt
G4J1HOKlqSFw = jSKPaHwSAfVv.layer_preprocess(G4J1HOKlqSFw, n4ljua2gi1Pr)
return (G4J1HOKlqSFw, nwxKmaSu5BSm, evuFeQ4CXEC8)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
universal_transformer_with_lstm_as_transition_function
|
def universal_transformer_with_lstm_as_transition_function(
layer_inputs, step, hparams, ffn_unit, attention_unit, pad_remover=None):
"""Universal Transformer which uses a lstm as transition function.
It's kind of like having a lstm, filliped vertically next to the Universal
Transformer that controls the flow of the information in depth,
over different steps of the Universal Transformer.
Args:
layer_inputs:
- state: state
- inputs: the original embedded inputs (= inputs to the first step)
- memory: memory used in lstm.
step: indicates number of steps taken so far
hparams: model hyper-parameters.
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
layer_output:
new_state: new state
inputs: the original embedded inputs (= inputs to the first step)
memory: contains information of state from all the previous steps.
"""
state, unused_inputs, memory = tf.unstack(
layer_inputs, num=None, axis=0, name="unstack")
# NOTE:
# state (ut_state): output of the lstm in the previous step
# inputs (ut_input): original input --> we don't use it here
# memory: lstm memory
# Multi_head_attention:
assert not hparams.add_step_timing_signal # Let lstm count for us!
mh_attention_input = step_preprocess(state, step, hparams)
transition_function_input = attention_unit(mh_attention_input)
# Transition Function:
if hparams.add_ffn_unit_to_the_transition_function:
transition_function_input = ffn_unit(transition_function_input)
transition_function_input = common_layers.layer_preprocess(
transition_function_input, hparams)
with tf.variable_scope("lstm"):
# lstm input gate: i_t = sigmoid(W_i.x_t + U_i.h_{t-1})
transition_function_input_gate = _ffn_layer_multi_inputs(
[transition_function_input, state],
hparams,
name="input",
bias_initializer=tf.zeros_initializer(),
activation=tf.sigmoid,
pad_remover=pad_remover,
preprocess=False,
postprocess=False)
tf.contrib.summary.scalar("lstm_input_gate",
tf.reduce_mean(transition_function_input_gate))
# lstm forget gate: f_t = sigmoid(W_f.x_t + U_f.h_{t-1})
transition_function_forget_gate = _ffn_layer_multi_inputs(
[transition_function_input, state],
hparams,
name="forget",
bias_initializer=tf.zeros_initializer(),
activation=None,
pad_remover=pad_remover,
preprocess=False,
postprocess=False)
forget_bias_tensor = tf.constant(hparams.lstm_forget_bias)
transition_function_forget_gate = tf.sigmoid(
transition_function_forget_gate + forget_bias_tensor)
tf.contrib.summary.scalar("lstm_forget_gate",
tf.reduce_mean(transition_function_forget_gate))
# lstm output gate: o_t = sigmoid(W_o.x_t + U_o.h_{t-1})
transition_function_output_gate = _ffn_layer_multi_inputs(
[transition_function_input, state],
hparams,
name="output",
bias_initializer=tf.zeros_initializer(),
activation=tf.sigmoid,
pad_remover=pad_remover,
preprocess=False,
postprocess=False)
tf.contrib.summary.scalar("lstm_output_gate",
tf.reduce_mean(transition_function_output_gate))
# lstm input modulation
transition_function_input_modulation = _ffn_layer_multi_inputs(
[transition_function_input, state],
hparams,
name="input_modulation",
bias_initializer=tf.zeros_initializer(),
activation=tf.tanh,
pad_remover=pad_remover,
preprocess=False,
postprocess=False)
transition_function_memory = (
memory * transition_function_forget_gate +
transition_function_input_gate * transition_function_input_modulation)
transition_function_output = (
tf.tanh(transition_function_memory) * transition_function_output_gate)
transition_function_output = common_layers.layer_preprocess(
transition_function_output, hparams)
return transition_function_output, unused_inputs, transition_function_memory
|
python
|
def universal_transformer_with_lstm_as_transition_function(
layer_inputs, step, hparams, ffn_unit, attention_unit, pad_remover=None):
"""Universal Transformer which uses a lstm as transition function.
It's kind of like having a lstm, filliped vertically next to the Universal
Transformer that controls the flow of the information in depth,
over different steps of the Universal Transformer.
Args:
layer_inputs:
- state: state
- inputs: the original embedded inputs (= inputs to the first step)
- memory: memory used in lstm.
step: indicates number of steps taken so far
hparams: model hyper-parameters.
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
layer_output:
new_state: new state
inputs: the original embedded inputs (= inputs to the first step)
memory: contains information of state from all the previous steps.
"""
state, unused_inputs, memory = tf.unstack(
layer_inputs, num=None, axis=0, name="unstack")
# NOTE:
# state (ut_state): output of the lstm in the previous step
# inputs (ut_input): original input --> we don't use it here
# memory: lstm memory
# Multi_head_attention:
assert not hparams.add_step_timing_signal # Let lstm count for us!
mh_attention_input = step_preprocess(state, step, hparams)
transition_function_input = attention_unit(mh_attention_input)
# Transition Function:
if hparams.add_ffn_unit_to_the_transition_function:
transition_function_input = ffn_unit(transition_function_input)
transition_function_input = common_layers.layer_preprocess(
transition_function_input, hparams)
with tf.variable_scope("lstm"):
# lstm input gate: i_t = sigmoid(W_i.x_t + U_i.h_{t-1})
transition_function_input_gate = _ffn_layer_multi_inputs(
[transition_function_input, state],
hparams,
name="input",
bias_initializer=tf.zeros_initializer(),
activation=tf.sigmoid,
pad_remover=pad_remover,
preprocess=False,
postprocess=False)
tf.contrib.summary.scalar("lstm_input_gate",
tf.reduce_mean(transition_function_input_gate))
# lstm forget gate: f_t = sigmoid(W_f.x_t + U_f.h_{t-1})
transition_function_forget_gate = _ffn_layer_multi_inputs(
[transition_function_input, state],
hparams,
name="forget",
bias_initializer=tf.zeros_initializer(),
activation=None,
pad_remover=pad_remover,
preprocess=False,
postprocess=False)
forget_bias_tensor = tf.constant(hparams.lstm_forget_bias)
transition_function_forget_gate = tf.sigmoid(
transition_function_forget_gate + forget_bias_tensor)
tf.contrib.summary.scalar("lstm_forget_gate",
tf.reduce_mean(transition_function_forget_gate))
# lstm output gate: o_t = sigmoid(W_o.x_t + U_o.h_{t-1})
transition_function_output_gate = _ffn_layer_multi_inputs(
[transition_function_input, state],
hparams,
name="output",
bias_initializer=tf.zeros_initializer(),
activation=tf.sigmoid,
pad_remover=pad_remover,
preprocess=False,
postprocess=False)
tf.contrib.summary.scalar("lstm_output_gate",
tf.reduce_mean(transition_function_output_gate))
# lstm input modulation
transition_function_input_modulation = _ffn_layer_multi_inputs(
[transition_function_input, state],
hparams,
name="input_modulation",
bias_initializer=tf.zeros_initializer(),
activation=tf.tanh,
pad_remover=pad_remover,
preprocess=False,
postprocess=False)
transition_function_memory = (
memory * transition_function_forget_gate +
transition_function_input_gate * transition_function_input_modulation)
transition_function_output = (
tf.tanh(transition_function_memory) * transition_function_output_gate)
transition_function_output = common_layers.layer_preprocess(
transition_function_output, hparams)
return transition_function_output, unused_inputs, transition_function_memory
|
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] |
Universal Transformer which uses a lstm as transition function.
It's kind of like having a lstm, filliped vertically next to the Universal
Transformer that controls the flow of the information in depth,
over different steps of the Universal Transformer.
Args:
layer_inputs:
- state: state
- inputs: the original embedded inputs (= inputs to the first step)
- memory: memory used in lstm.
step: indicates number of steps taken so far
hparams: model hyper-parameters.
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
pad_remover: to mask out padding in convolutional layers (efficiency).
Returns:
layer_output:
new_state: new state
inputs: the original embedded inputs (= inputs to the first step)
memory: contains information of state from all the previous steps.
|
[
"Universal",
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L927-L1037
|
train
|
Universal Transformer which uses a lstm as transition function.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + chr(2217 - 2168) + chr(0b110 + 0o56), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1100 + 0o47) + chr(0b11110 + 0o23) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(919 - 871) + '\157' + chr(0b110001) + chr(0b100101 + 0o15) + '\063', 0b1000), ehT0Px3KOsy9(chr(219 - 171) + chr(0b1101111) + '\061' + chr(54) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(1590 - 1542) + chr(0b1101111) + '\x33' + chr(1586 - 1537) + chr(0b110010 + 0o3), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b111011 + 0o64) + chr(49) + chr(53), 0o10), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(0b11 + 0o154) + chr(0b110011) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(2109 - 2061) + '\157' + '\062' + chr(0b110011) + '\x37', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b10100 + 0o133) + '\063' + chr(1715 - 1665) + chr(0b100100 + 0o15), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063' + '\x34' + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + chr(9481 - 9370) + chr(2277 - 2226) + '\067' + '\061', 7293 - 7285), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + '\065' + chr(0b110000), 1731 - 1723), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + '\061' + '\x37', 0o10), ehT0Px3KOsy9('\x30' + chr(9455 - 9344) + chr(330 - 281) + '\065' + '\x30', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b101111 + 0o4) + chr(0b100111 + 0o14) + chr(52), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b101111 + 0o100) + '\062' + chr(54), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\063' + chr(1711 - 1662) + chr(2144 - 2092), 0b1000), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(111) + chr(0b1 + 0o62) + chr(0b110110) + chr(0b11000 + 0o30), 2165 - 2157), ehT0Px3KOsy9(chr(820 - 772) + chr(111) + chr(0b110110) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111 + 0o0) + chr(0b110001) + chr(54), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b11010 + 0o30) + chr(54) + chr(0b11100 + 0o33), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b11 + 0o63) + chr(246 - 198), 4278 - 4270), ehT0Px3KOsy9(chr(48) + chr(0b101010 + 0o105) + '\x31' + '\062', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + chr(794 - 741) + chr(0b11 + 0o56), 18269 - 18261), ehT0Px3KOsy9(chr(1432 - 1384) + chr(7394 - 7283) + chr(156 - 105) + chr(2063 - 2009), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + chr(0b10011 + 0o44), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(1400 - 1349) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1100 + 0o46) + chr(1539 - 1484) + chr(0b11010 + 0o33), 38141 - 38133), ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\x6f' + '\062' + chr(0b110010) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(10753 - 10642) + chr(0b110000 + 0o2) + chr(54) + '\067', 8), ehT0Px3KOsy9(chr(48) + chr(0b101111 + 0o100) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(210 - 162) + '\x6f' + chr(0b110011) + '\x34' + chr(0b11000 + 0o30), 8), ehT0Px3KOsy9(chr(1742 - 1694) + chr(111) + '\x31' + chr(2252 - 2198), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(50) + chr(502 - 453) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b101101 + 0o102) + '\x34', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + '\062' + chr(51), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + '\063' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + chr(51), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b1101010 + 0o5) + '\065' + chr(48), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'b'), chr(0b110 + 0o136) + '\x65' + chr(0b110101 + 0o56) + chr(0b101010 + 0o105) + chr(0b110110 + 0o56) + chr(0b1010010 + 0o23))(chr(2302 - 2185) + '\164' + chr(102) + chr(45) + chr(0b10111 + 0o41)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def LwK9_zCyg8Il(hdidhQtCKIOY, kDuFsAhEatcU, n4ljua2gi1Pr, SHRtjNoPzosY, ek3fs6JEXh0d, bLDzE_zU4vXa=None):
(KKFQISrGeiAm, nwxKmaSu5BSm, KcR7WgfLppqF) = IDJ2eXGCBCDu.unstack(hdidhQtCKIOY, num=None, axis=ehT0Px3KOsy9(chr(0b110000) + chr(12102 - 11991) + chr(1825 - 1777), 8), name=xafqLlk3kkUe(SXOLrMavuUCe(b'9\xa6 \x07\xacnq'), chr(100) + chr(0b1010110 + 0o17) + chr(0b10010 + 0o121) + chr(0b1001001 + 0o46) + chr(100) + chr(0b10101 + 0o120))('\165' + chr(0b11111 + 0o125) + '\x66' + chr(45) + chr(0b110110 + 0o2)))
assert not xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'-\xac7,\xbey\x7f\xef\x8e\x94\x90\xc5\xa6\x06\xbbI\xbf\x99T`\xd6\\'), chr(100) + chr(0b1100101) + chr(0b1100011) + chr(0b1101111) + chr(0b1100100) + '\x65')(chr(117) + chr(116) + '\146' + chr(0b101101) + chr(0b110110 + 0o2)))
tJH321jQYcIb = A2EO56BplgPh(KKFQISrGeiAm, kDuFsAhEatcU, n4ljua2gi1Pr)
hmthMC4Pao6T = ek3fs6JEXh0d(tJH321jQYcIb)
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'-\xac7,\xabkt\xc0\xa4\x8e\x90\xdc\x90\x1c\xb3I\xb8\x98VQ\xc3Bk\x87mvm\xf4\xd2\xfc\xe8f\x95`\xea\x7fm\xbc\xb7'), chr(3941 - 3841) + chr(0b1100101) + chr(0b111010 + 0o51) + chr(0b10 + 0o155) + '\144' + '\145')('\x75' + '\164' + chr(5863 - 5761) + chr(0b101101) + chr(231 - 175))):
hmthMC4Pao6T = SHRtjNoPzosY(hmthMC4Pao6T)
hmthMC4Pao6T = jSKPaHwSAfVv.layer_preprocess(hmthMC4Pao6T, n4ljua2gi1Pr)
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b':\xa9!\x1a\xacov\xfa\x8e\x93\x9a\xc7\xbf\r'), chr(0b1100100) + chr(0b1010001 + 0o24) + '\x63' + '\157' + chr(0b1011001 + 0o13) + chr(4599 - 4498))(chr(117) + '\164' + chr(0b1100110) + '\055' + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b" \xbb'\x1e"), '\144' + chr(101) + chr(5336 - 5237) + chr(0b1111 + 0o140) + chr(100) + chr(9763 - 9662))(chr(0b1110101) + chr(0b110001 + 0o103) + chr(3900 - 3798) + chr(0b100100 + 0o11) + chr(0b111000))):
fXFfMsSsKLGa = TlcH9M_VkXCB([hmthMC4Pao6T, KKFQISrGeiAm], n4ljua2gi1Pr, name=xafqLlk3kkUe(SXOLrMavuUCe(b'%\xa6#\x06\xb9'), chr(100) + chr(4974 - 4873) + '\x63' + chr(0b1101111) + chr(0b1100100) + chr(0b101001 + 0o74))(chr(117) + chr(116) + '\x66' + chr(45) + chr(56)), bias_initializer=IDJ2eXGCBCDu.zeros_initializer(), activation=IDJ2eXGCBCDu.sigmoid, pad_remover=bLDzE_zU4vXa, preprocess=ehT0Px3KOsy9(chr(1756 - 1708) + chr(111) + chr(0b110000), 8), postprocess=ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110000), 8))
xafqLlk3kkUe(IDJ2eXGCBCDu.contrib.summary, xafqLlk3kkUe(SXOLrMavuUCe(b'?\xab2\x1f\xac\x7f'), '\x64' + chr(8640 - 8539) + chr(0b1100011) + chr(11145 - 11034) + '\x64' + '\145')(chr(0b111001 + 0o74) + '\x74' + '\146' + '\055' + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b" \xbb'\x1e\x92dt\xef\xa4\x94\xa6\xcf\xae\x1c\xb9"), chr(100) + '\x65' + chr(99) + chr(0b1101111) + chr(3654 - 3554) + chr(0b10111 + 0o116))(chr(10996 - 10879) + '\x74' + chr(0b1100110) + chr(1891 - 1846) + chr(0b1101 + 0o53)), xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'>\xad7\x06\xaehE\xf2\xb4\x81\x97'), chr(0b1100100 + 0o0) + '\x65' + '\143' + '\x6f' + chr(6769 - 6669) + chr(1646 - 1545))(chr(0b1100111 + 0o16) + '\x74' + chr(0b1100110) + '\055' + '\x38'))(fXFfMsSsKLGa))
JQUaTC8egnhs = TlcH9M_VkXCB([hmthMC4Pao6T, KKFQISrGeiAm], n4ljua2gi1Pr, name=xafqLlk3kkUe(SXOLrMavuUCe(b'*\xa7!\x14\xa8y'), '\x64' + chr(101) + '\143' + chr(3201 - 3090) + '\144' + '\145')(chr(0b1110101) + chr(116) + chr(555 - 453) + '\055' + chr(2331 - 2275)), bias_initializer=IDJ2eXGCBCDu.zeros_initializer(), activation=None, pad_remover=bLDzE_zU4vXa, preprocess=ehT0Px3KOsy9('\060' + chr(4992 - 4881) + chr(0b100100 + 0o14), 8), postprocess=ehT0Px3KOsy9('\x30' + chr(5314 - 5203) + '\x30', 8))
gPCJnad2dwhs = IDJ2eXGCBCDu.constant(n4ljua2gi1Pr.lstm_forget_bias)
JQUaTC8egnhs = IDJ2eXGCBCDu.sigmoid(JQUaTC8egnhs + gPCJnad2dwhs)
xafqLlk3kkUe(IDJ2eXGCBCDu.contrib.summary, xafqLlk3kkUe(SXOLrMavuUCe(b'?\xab2\x1f\xac\x7f'), '\x64' + chr(0b11010 + 0o113) + chr(287 - 188) + chr(9841 - 9730) + chr(100) + chr(0b1100101))(chr(11033 - 10916) + '\x74' + chr(0b1100110) + chr(45) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b" \xbb'\x1e\x92ku\xed\xb6\x85\x8d\xf7\xa8\t\xa8s"), chr(100) + chr(5087 - 4986) + chr(6375 - 6276) + '\x6f' + chr(100) + chr(0b1100101))(chr(0b1110101) + chr(0b100011 + 0o121) + chr(102) + chr(0b101101) + '\070'), xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'>\xad7\x06\xaehE\xf2\xb4\x81\x97'), chr(0b11101 + 0o107) + '\145' + chr(0b1010010 + 0o21) + chr(0b1101001 + 0o6) + chr(0b100110 + 0o76) + chr(0b1100101))(chr(0b1011110 + 0o27) + chr(6279 - 6163) + chr(9666 - 9564) + chr(45) + '\x38'))(JQUaTC8egnhs))
Ck8DbliOap_l = TlcH9M_VkXCB([hmthMC4Pao6T, KKFQISrGeiAm], n4ljua2gi1Pr, name=xafqLlk3kkUe(SXOLrMavuUCe(b"#\xbd'\x03\xb8y"), chr(0b1000100 + 0o40) + '\x65' + chr(0b110111 + 0o54) + '\x6f' + '\144' + chr(0b100001 + 0o104))(chr(117) + '\164' + chr(0b1100010 + 0o4) + '\055' + '\x38'), bias_initializer=IDJ2eXGCBCDu.zeros_initializer(), activation=IDJ2eXGCBCDu.sigmoid, pad_remover=bLDzE_zU4vXa, preprocess=ehT0Px3KOsy9(chr(1724 - 1676) + chr(0b1101111) + '\060', 8), postprocess=ehT0Px3KOsy9(chr(0b110000) + chr(9830 - 9719) + chr(0b110000), 8))
xafqLlk3kkUe(IDJ2eXGCBCDu.contrib.summary, xafqLlk3kkUe(SXOLrMavuUCe(b'?\xab2\x1f\xac\x7f'), chr(1196 - 1096) + chr(101) + chr(1393 - 1294) + '\157' + chr(0b1100100) + '\145')(chr(0b1110101) + chr(116) + chr(2638 - 2536) + chr(1861 - 1816) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b" \xbb'\x1e\x92bo\xeb\xa1\x95\x8d\xf7\xa8\t\xa8s"), '\144' + chr(0b1100101) + chr(0b1100011) + chr(5675 - 5564) + chr(100) + chr(0b1100101))(chr(3411 - 3294) + '\164' + chr(4074 - 3972) + chr(0b101101) + '\070'), xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'>\xad7\x06\xaehE\xf2\xb4\x81\x97'), chr(100) + chr(0b1010110 + 0o17) + '\x63' + chr(111) + chr(100) + '\145')(chr(0b1110101) + chr(2779 - 2663) + chr(9461 - 9359) + '\x2d' + chr(1377 - 1321)))(Ck8DbliOap_l))
d19zseEoeoz_ = TlcH9M_VkXCB([hmthMC4Pao6T, KKFQISrGeiAm], n4ljua2gi1Pr, name=xafqLlk3kkUe(SXOLrMavuUCe(b'%\xa6#\x06\xb9Rw\xf0\xb5\x95\x95\xc9\xbb\x01\xb3x'), chr(100) + '\145' + '\x63' + '\x6f' + chr(8576 - 8476) + '\x65')('\x75' + chr(116) + '\x66' + '\x2d' + chr(0b100101 + 0o23)), bias_initializer=IDJ2eXGCBCDu.zeros_initializer(), activation=IDJ2eXGCBCDu.tanh, pad_remover=bLDzE_zU4vXa, preprocess=ehT0Px3KOsy9('\x30' + '\157' + '\060', 8), postprocess=ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110000), 8))
HeFK7vS9Z76S = KcR7WgfLppqF * JQUaTC8egnhs + fXFfMsSsKLGa * d19zseEoeoz_
G4J1HOKlqSFw = IDJ2eXGCBCDu.tanh(HeFK7vS9Z76S) * Ck8DbliOap_l
G4J1HOKlqSFw = jSKPaHwSAfVv.layer_preprocess(G4J1HOKlqSFw, n4ljua2gi1Pr)
return (G4J1HOKlqSFw, nwxKmaSu5BSm, HeFK7vS9Z76S)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
universal_transformer_act
|
def universal_transformer_act(x, hparams, ffn_unit, attention_unit):
"""ACT based models.
Implementations of all act models are based on craffel@'s cl/160711592.
(1) Basic AUT based on remainder-distribution ACT (position-wise).
(2) AUT with global halting probability (not position-wise).
(3) AUT with random halting probability (not position-wise).
(4) AUT with final state as accumulation of all states.
Args:
x: input
hparams: model hyper-parameters
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
Returns:
the output tensor, (ponder_times, remainders)
Raises:
ValueError: Unknown act type
"""
if hparams.act_type not in ["basic", "global", "random", "accumulated"]:
raise ValueError("Unknown act type: %s" % hparams.act_type)
state = x
act_max_steps = hparams.act_max_steps
threshold = 1.0 - hparams.act_epsilon
state_shape_static = state.get_shape()
state_slice = slice(0, 2)
if hparams.act_type == "global":
state_slice = slice(0, 1)
# Dynamic shape for update tensors below
update_shape = tf.shape(state)[state_slice]
# Halting probabilities (p_t^n in the paper)
halting_probability = tf.zeros(update_shape, name="halting_probability")
# Remainders (R(t) in the paper)
remainders = tf.zeros(update_shape, name="remainder")
# Number of updates performed (N(t) in the paper)
n_updates = tf.zeros(update_shape, name="n_updates")
# Previous cell states (s_t in the paper)
previous_state = tf.zeros_like(state, name="previous_state")
step = tf.constant(0, dtype=tf.int32)
def ut_function(state, step, halting_probability, remainders, n_updates,
previous_state):
"""implements act (position-wise halting).
Args:
state: 3-D Tensor: [batch_size, length, channel]
step: indicates number of steps taken so far
halting_probability: halting probability
remainders: act remainders
n_updates: act n_updates
previous_state: previous state
Returns:
transformed_state: transformed state
step: step+1
halting_probability: halting probability
remainders: act remainders
n_updates: act n_updates
new_state: new state
"""
state = step_preprocess(state, step, hparams)
if hparams.act_type == "random":
# random as halting probability
p = tf.random_uniform(
shape=common_layers.shape_list(halting_probability))
else:
with tf.variable_scope("sigmoid_activation_for_pondering"):
p = common_layers.dense(
state,
1,
activation=tf.nn.sigmoid,
use_bias=True,
bias_initializer=tf.constant_initializer(
hparams.act_halting_bias_init))
if hparams.act_type == "global":
# average over all positions (as a global halting prob)
p = tf.reduce_mean(p, axis=1)
p = tf.squeeze(p)
else:
# maintain position-wise probabilities
p = tf.squeeze(p, axis=-1)
# Mask for inputs which have not halted yet
still_running = tf.cast(tf.less(halting_probability, 1.0), tf.float32)
# Mask of inputs which halted at this step
new_halted = tf.cast(
tf.greater(halting_probability + p * still_running, threshold),
tf.float32) * still_running
# Mask of inputs which haven't halted, and didn't halt this step
still_running = tf.cast(
tf.less_equal(halting_probability + p * still_running, threshold),
tf.float32) * still_running
# Add the halting probability for this step to the halting
# probabilities for those input which haven't halted yet
halting_probability += p * still_running
# Compute remainders for the inputs which halted at this step
remainders += new_halted * (1 - halting_probability)
# Add the remainders to those inputs which halted at this step
halting_probability += new_halted * remainders
# Increment n_updates for all inputs which are still running
n_updates += still_running + new_halted
# Compute the weight to be applied to the new state and output
# 0 when the input has already halted
# p when the input hasn't halted yet
# the remainders when it halted this step
update_weights = tf.expand_dims(
p * still_running + new_halted * remainders, -1)
if hparams.act_type == "global":
update_weights = tf.expand_dims(update_weights, -1)
# apply transformation on the state
transformed_state = state
for i in range(hparams.num_inrecurrence_layers):
with tf.variable_scope("rec_layer_%d" % i):
transformed_state = ffn_unit(attention_unit(transformed_state))
# update running part in the weighted state and keep the rest
new_state = ((transformed_state * update_weights) +
(previous_state * (1 - update_weights)))
if hparams.act_type == "accumulated":
# Add in the weighted state
new_state = (transformed_state * update_weights) + previous_state
# remind TensorFlow of everything's shape
transformed_state.set_shape(state_shape_static)
for x in [halting_probability, remainders, n_updates]:
x.set_shape(state_shape_static[state_slice])
new_state.set_shape(state_shape_static)
step += 1
return (transformed_state, step, halting_probability, remainders, n_updates,
new_state)
# While loop stops when this predicate is FALSE.
# Ie all (probability < 1-eps AND counter < N) are false.
def should_continue(u0, u1, halting_probability, u2, n_updates, u3):
del u0, u1, u2, u3
return tf.reduce_any(
tf.logical_and(
tf.less(halting_probability, threshold),
tf.less(n_updates, act_max_steps)))
# Do while loop iterations until predicate above is false.
(_, _, _, remainder, n_updates, new_state) = tf.while_loop(
should_continue, ut_function,
(state, step, halting_probability, remainders, n_updates, previous_state),
maximum_iterations=act_max_steps + 1)
ponder_times = n_updates
remainders = remainder
tf.contrib.summary.scalar("ponder_times", tf.reduce_mean(ponder_times))
return new_state, (ponder_times, remainders)
|
python
|
def universal_transformer_act(x, hparams, ffn_unit, attention_unit):
"""ACT based models.
Implementations of all act models are based on craffel@'s cl/160711592.
(1) Basic AUT based on remainder-distribution ACT (position-wise).
(2) AUT with global halting probability (not position-wise).
(3) AUT with random halting probability (not position-wise).
(4) AUT with final state as accumulation of all states.
Args:
x: input
hparams: model hyper-parameters
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
Returns:
the output tensor, (ponder_times, remainders)
Raises:
ValueError: Unknown act type
"""
if hparams.act_type not in ["basic", "global", "random", "accumulated"]:
raise ValueError("Unknown act type: %s" % hparams.act_type)
state = x
act_max_steps = hparams.act_max_steps
threshold = 1.0 - hparams.act_epsilon
state_shape_static = state.get_shape()
state_slice = slice(0, 2)
if hparams.act_type == "global":
state_slice = slice(0, 1)
# Dynamic shape for update tensors below
update_shape = tf.shape(state)[state_slice]
# Halting probabilities (p_t^n in the paper)
halting_probability = tf.zeros(update_shape, name="halting_probability")
# Remainders (R(t) in the paper)
remainders = tf.zeros(update_shape, name="remainder")
# Number of updates performed (N(t) in the paper)
n_updates = tf.zeros(update_shape, name="n_updates")
# Previous cell states (s_t in the paper)
previous_state = tf.zeros_like(state, name="previous_state")
step = tf.constant(0, dtype=tf.int32)
def ut_function(state, step, halting_probability, remainders, n_updates,
previous_state):
"""implements act (position-wise halting).
Args:
state: 3-D Tensor: [batch_size, length, channel]
step: indicates number of steps taken so far
halting_probability: halting probability
remainders: act remainders
n_updates: act n_updates
previous_state: previous state
Returns:
transformed_state: transformed state
step: step+1
halting_probability: halting probability
remainders: act remainders
n_updates: act n_updates
new_state: new state
"""
state = step_preprocess(state, step, hparams)
if hparams.act_type == "random":
# random as halting probability
p = tf.random_uniform(
shape=common_layers.shape_list(halting_probability))
else:
with tf.variable_scope("sigmoid_activation_for_pondering"):
p = common_layers.dense(
state,
1,
activation=tf.nn.sigmoid,
use_bias=True,
bias_initializer=tf.constant_initializer(
hparams.act_halting_bias_init))
if hparams.act_type == "global":
# average over all positions (as a global halting prob)
p = tf.reduce_mean(p, axis=1)
p = tf.squeeze(p)
else:
# maintain position-wise probabilities
p = tf.squeeze(p, axis=-1)
# Mask for inputs which have not halted yet
still_running = tf.cast(tf.less(halting_probability, 1.0), tf.float32)
# Mask of inputs which halted at this step
new_halted = tf.cast(
tf.greater(halting_probability + p * still_running, threshold),
tf.float32) * still_running
# Mask of inputs which haven't halted, and didn't halt this step
still_running = tf.cast(
tf.less_equal(halting_probability + p * still_running, threshold),
tf.float32) * still_running
# Add the halting probability for this step to the halting
# probabilities for those input which haven't halted yet
halting_probability += p * still_running
# Compute remainders for the inputs which halted at this step
remainders += new_halted * (1 - halting_probability)
# Add the remainders to those inputs which halted at this step
halting_probability += new_halted * remainders
# Increment n_updates for all inputs which are still running
n_updates += still_running + new_halted
# Compute the weight to be applied to the new state and output
# 0 when the input has already halted
# p when the input hasn't halted yet
# the remainders when it halted this step
update_weights = tf.expand_dims(
p * still_running + new_halted * remainders, -1)
if hparams.act_type == "global":
update_weights = tf.expand_dims(update_weights, -1)
# apply transformation on the state
transformed_state = state
for i in range(hparams.num_inrecurrence_layers):
with tf.variable_scope("rec_layer_%d" % i):
transformed_state = ffn_unit(attention_unit(transformed_state))
# update running part in the weighted state and keep the rest
new_state = ((transformed_state * update_weights) +
(previous_state * (1 - update_weights)))
if hparams.act_type == "accumulated":
# Add in the weighted state
new_state = (transformed_state * update_weights) + previous_state
# remind TensorFlow of everything's shape
transformed_state.set_shape(state_shape_static)
for x in [halting_probability, remainders, n_updates]:
x.set_shape(state_shape_static[state_slice])
new_state.set_shape(state_shape_static)
step += 1
return (transformed_state, step, halting_probability, remainders, n_updates,
new_state)
# While loop stops when this predicate is FALSE.
# Ie all (probability < 1-eps AND counter < N) are false.
def should_continue(u0, u1, halting_probability, u2, n_updates, u3):
del u0, u1, u2, u3
return tf.reduce_any(
tf.logical_and(
tf.less(halting_probability, threshold),
tf.less(n_updates, act_max_steps)))
# Do while loop iterations until predicate above is false.
(_, _, _, remainder, n_updates, new_state) = tf.while_loop(
should_continue, ut_function,
(state, step, halting_probability, remainders, n_updates, previous_state),
maximum_iterations=act_max_steps + 1)
ponder_times = n_updates
remainders = remainder
tf.contrib.summary.scalar("ponder_times", tf.reduce_mean(ponder_times))
return new_state, (ponder_times, remainders)
|
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] |
ACT based models.
Implementations of all act models are based on craffel@'s cl/160711592.
(1) Basic AUT based on remainder-distribution ACT (position-wise).
(2) AUT with global halting probability (not position-wise).
(3) AUT with random halting probability (not position-wise).
(4) AUT with final state as accumulation of all states.
Args:
x: input
hparams: model hyper-parameters
ffn_unit: feed-forward unit
attention_unit: multi-head attention unit
Returns:
the output tensor, (ponder_times, remainders)
Raises:
ValueError: Unknown act type
|
[
"ACT",
"based",
"models",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L1040-L1212
|
train
|
Universal Transformer for act based models.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1029 - 981) + chr(0b100101 + 0o112) + '\x33' + '\x34' + chr(1698 - 1650), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001) + '\x35' + chr(0b11001 + 0o35), 36674 - 36666), ehT0Px3KOsy9('\x30' + chr(111) + chr(2158 - 2106), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(2469 - 2419) + '\x36' + chr(49), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101011 + 0o4) + chr(0b110001) + '\x36' + chr(50), 0o10), ehT0Px3KOsy9(chr(0b110 + 0o52) + '\157' + '\x37' + '\x36', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51) + chr(52) + chr(1893 - 1842), 7831 - 7823), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + chr(0b1000 + 0o54) + '\x31', 15250 - 15242), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(6081 - 5970) + '\x31' + chr(0b1100 + 0o45) + '\x30', 0b1000), ehT0Px3KOsy9(chr(195 - 147) + chr(0b1011 + 0o144) + chr(0b110010) + chr(55) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010101 + 0o32) + chr(0b110010) + chr(0b110000) + chr(52), 38115 - 38107), ehT0Px3KOsy9(chr(652 - 604) + chr(111) + '\062' + '\x34' + '\x33', 22117 - 22109), ehT0Px3KOsy9(chr(1372 - 1324) + chr(0b1101111) + chr(0b110001) + '\066' + chr(51), 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\064' + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b100100 + 0o113) + '\063' + '\060' + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010101 + 0o32) + chr(0b100110 + 0o13) + chr(53), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b10100 + 0o37) + '\x32' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(83 - 34) + chr(2076 - 2027) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(5466 - 5355) + '\x35' + chr(2631 - 2577), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b101101 + 0o6) + chr(0b110110) + chr(313 - 265), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + chr(0b110110) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(51) + '\x34' + chr(2573 - 2521), 0b1000), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b110101 + 0o72) + '\x31' + chr(212 - 159) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(0b1101111) + '\x31' + '\067' + chr(50), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(1840 - 1789) + '\x32' + chr(0b101100 + 0o13), 8), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\x6f' + chr(0b1111 + 0o43) + chr(0b110001) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(1283 - 1235) + chr(0b1101111) + '\x31' + chr(0b110000) + chr(0b10 + 0o57), ord("\x08")), ehT0Px3KOsy9(chr(0b0 + 0o60) + '\x6f' + '\x33' + chr(593 - 543) + '\061', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(2074 - 2023) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(111) + chr(1311 - 1261) + chr(2103 - 2052) + chr(2156 - 2104), 0b1000), ehT0Px3KOsy9(chr(48) + chr(10622 - 10511) + chr(53) + chr(861 - 813), 34424 - 34416), ehT0Px3KOsy9(chr(0b110000) + chr(813 - 702) + chr(1732 - 1682) + '\x35' + '\x37', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1000001 + 0o56) + chr(768 - 717) + chr(0b1010 + 0o54) + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + '\x32' + chr(0b101010 + 0o12), ord("\x08")), ehT0Px3KOsy9(chr(927 - 879) + '\157' + chr(0b110011) + '\x32' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(546 - 498) + '\157' + '\063' + '\065' + chr(54), 29403 - 29395), ehT0Px3KOsy9(chr(791 - 743) + chr(0b1101111) + chr(0b101 + 0o56) + chr(48) + chr(0b110110), 51426 - 51418), ehT0Px3KOsy9(chr(48) + '\157' + '\061' + chr(417 - 363) + chr(0b10100 + 0o42), ord("\x08")), ehT0Px3KOsy9(chr(1284 - 1236) + chr(0b1100110 + 0o11) + '\x32' + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110111) + chr(0b110011), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(111) + '\065' + chr(48), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xce'), '\x64' + chr(101) + chr(0b100100 + 0o77) + '\157' + chr(0b11 + 0o141) + chr(0b1100101))(chr(117) + chr(0b1110100) + chr(102) + chr(0b11001 + 0o24) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def kLAnEEMTVVI2(OeWW0F1dBPRQ, n4ljua2gi1Pr, SHRtjNoPzosY, ek3fs6JEXh0d):
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x81\rp\xee\x06G\x93\x84'), '\144' + chr(0b11101 + 0o110) + chr(99) + chr(11074 - 10963) + chr(0b1101 + 0o127) + '\x65')(chr(0b101101 + 0o110) + chr(0b11 + 0o161) + chr(0b1100110) + '\055' + chr(1476 - 1420))) not in [xafqLlk3kkUe(SXOLrMavuUCe(b'\x82\x0fw\xd8\x11'), chr(0b1000001 + 0o43) + '\x65' + chr(0b1000 + 0o133) + chr(814 - 703) + chr(5355 - 5255) + chr(3070 - 2969))('\x75' + chr(0b1110100) + chr(0b1100110) + '\055' + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\x87\x02k\xd3\x13R'), chr(100) + chr(6839 - 6738) + chr(0b1011000 + 0o13) + chr(111) + chr(0b11100 + 0o110) + chr(0b1100101))('\x75' + chr(0b110110 + 0o76) + chr(0b10000 + 0o126) + chr(45) + chr(1541 - 1485)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\x0fj\xd5\x1dS'), chr(100) + '\145' + chr(0b10 + 0o141) + chr(0b1011 + 0o144) + chr(100) + '\x65')(chr(0b1101011 + 0o12) + chr(11686 - 11570) + '\146' + chr(0b101101) + chr(2821 - 2765)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x81\rg\xc4\x1fK\x8f\x80<\xdb\xe0'), chr(100) + chr(0b1100101) + chr(0b1100011) + chr(1945 - 1834) + '\x64' + '\145')(chr(12755 - 12638) + '\164' + chr(0b1100110) + '\x2d' + chr(0b1 + 0o67))]:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\xb5\x00o\xdf\x1dI\x8d\xc1)\xdd\xf0\x83\x07[\xb0h\xedj\x0b\x83'), chr(0b1000111 + 0o35) + '\145' + '\143' + '\157' + chr(1231 - 1131) + chr(1176 - 1075))(chr(117) + '\x74' + chr(102) + '\x2d' + '\070') % xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x81\rp\xee\x06G\x93\x84'), chr(0b101011 + 0o71) + chr(0b1100101) + chr(0b1100011) + chr(9395 - 9284) + '\x64' + chr(0b1100101))(chr(117) + chr(0b101011 + 0o111) + chr(102) + chr(172 - 127) + chr(56))))
KKFQISrGeiAm = OeWW0F1dBPRQ
kBCT8GcwBJOF = n4ljua2gi1Pr.act_max_steps
DhxlYT5nN5Hu = 1.0 - n4ljua2gi1Pr.act_epsilon
sjybvrljgW8H = KKFQISrGeiAm.get_shape()
uLy2dxCaqQZ_ = W3g84rNiEdDQ(ehT0Px3KOsy9(chr(48) + '\157' + '\060', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(50), 52516 - 52508))
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x81\rp\xee\x06G\x93\x84'), chr(0b1001011 + 0o31) + chr(288 - 187) + '\x63' + chr(111) + chr(100) + chr(101))(chr(6727 - 6610) + chr(0b1110100 + 0o0) + '\146' + '\055' + chr(0b111000))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x87\x02k\xd3\x13R'), chr(0b1100100) + '\145' + chr(99) + chr(0b1001010 + 0o45) + chr(100) + chr(101))(chr(117) + chr(0b100100 + 0o120) + chr(0b1000100 + 0o42) + '\x2d' + '\070'):
uLy2dxCaqQZ_ = W3g84rNiEdDQ(ehT0Px3KOsy9(chr(48) + '\x6f' + '\060', 8), ehT0Px3KOsy9(chr(48) + chr(0b111111 + 0o60) + chr(1545 - 1496), 45551 - 45543))
gYvQryVj6mrj = IDJ2eXGCBCDu.nauYfLglTpcb(KKFQISrGeiAm)[uLy2dxCaqQZ_]
KrRiV9wIruZH = IDJ2eXGCBCDu.zeros(gYvQryVj6mrj, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x88\x0fh\xc5\x1bP\x84\xbe8\xcc\xeb\xc1\x12@\xa9a\xbe>W'), chr(0b1010011 + 0o21) + chr(653 - 552) + chr(99) + '\157' + chr(0b10100 + 0o120) + chr(7712 - 7611))(chr(0b1001110 + 0o47) + '\164' + chr(5222 - 5120) + chr(0b110 + 0o47) + '\070'))
zNcnStGroZVg = IDJ2eXGCBCDu.zeros(gYvQryVj6mrj, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\x0bi\xd0\x1bP\x87\x84:'), chr(0b1100100) + chr(0b1000110 + 0o37) + '\143' + '\157' + chr(100) + '\145')(chr(0b1011111 + 0o26) + '\164' + '\x66' + '\x2d' + '\x38'))
ciVXtTlQKiCh = IDJ2eXGCBCDu.zeros(gYvQryVj6mrj, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e1q\xc1\x16_\x97\x84;'), '\x64' + '\145' + chr(1212 - 1113) + '\157' + chr(0b1000010 + 0o42) + '\x65')(chr(0b1010110 + 0o37) + '\164' + '\x66' + chr(442 - 397) + chr(0b111000)))
RNFyM8qCdMT2 = IDJ2eXGCBCDu.zeros_like(KKFQISrGeiAm, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x90\x1ca\xc7\x1bQ\x96\x92\x17\xcd\xf0\xc2\x07G'), '\x64' + '\145' + chr(99) + '\x6f' + '\144' + chr(7353 - 7252))(chr(5256 - 5139) + '\164' + '\146' + chr(45) + chr(56)))
kDuFsAhEatcU = IDJ2eXGCBCDu.constant(ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(48), 8), dtype=IDJ2eXGCBCDu.int32)
def bJ8teQTW0l5A(KKFQISrGeiAm, kDuFsAhEatcU, KrRiV9wIruZH, zNcnStGroZVg, ciVXtTlQKiCh, RNFyM8qCdMT2):
KKFQISrGeiAm = A2EO56BplgPh(KKFQISrGeiAm, kDuFsAhEatcU, n4ljua2gi1Pr)
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x81\rp\xee\x06G\x93\x84'), '\x64' + '\x65' + chr(5171 - 5072) + chr(0b1101111) + '\144' + chr(3705 - 3604))('\165' + chr(0b1110100) + '\x66' + chr(45) + chr(0b111000))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\x0fj\xd5\x1dS'), '\x64' + '\x65' + chr(8007 - 7908) + chr(0b100001 + 0o116) + chr(0b1001000 + 0o34) + chr(0b1011001 + 0o14))('\165' + '\164' + '\146' + '\x2d' + '\070'):
UyakMW2IMFEj = IDJ2eXGCBCDu.random_uniform(shape=jSKPaHwSAfVv.shape_list(KrRiV9wIruZH))
else:
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x96\x0fv\xd8\x13\\\x8f\x84\x17\xcd\xe7\xcc\x03G'), chr(0b101011 + 0o71) + chr(101) + chr(1084 - 985) + '\157' + chr(3455 - 3355) + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + '\146' + chr(45) + chr(0b111 + 0o61)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x93\x07c\xdc\x1dW\x87\xbe)\xdd\xf0\xca\x05C\xb4d\xb8$q\x96\x99\x964\n\xb8\xe3%\xb4\xef\xf5F\xc8'), chr(0b10011 + 0o121) + '\x65' + '\143' + '\x6f' + '\x64' + chr(0b101011 + 0o72))(chr(0b1110101) + chr(0b111111 + 0o65) + '\146' + chr(0b100011 + 0o12) + chr(56))):
UyakMW2IMFEj = jSKPaHwSAfVv.dense(KKFQISrGeiAm, ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001), 8), activation=IDJ2eXGCBCDu.nn.sigmoid, use_bias=ehT0Px3KOsy9(chr(48) + chr(0b1101100 + 0o3) + '\x31', 8), bias_initializer=IDJ2eXGCBCDu.constant_initializer(n4ljua2gi1Pr.act_halting_bias_init))
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x81\rp\xee\x06G\x93\x84'), chr(0b1000011 + 0o41) + chr(0b1010010 + 0o23) + chr(2565 - 2466) + '\x6f' + chr(8158 - 8058) + chr(146 - 45))(chr(117) + '\x74' + chr(7757 - 7655) + chr(0b101101) + chr(0b111000))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x87\x02k\xd3\x13R'), '\x64' + '\x65' + chr(2261 - 2162) + '\x6f' + chr(0b111011 + 0o51) + chr(0b1100101))(chr(117) + chr(0b11001 + 0o133) + '\146' + '\x2d' + chr(0b100000 + 0o30)):
UyakMW2IMFEj = IDJ2eXGCBCDu.reduce_mean(UyakMW2IMFEj, axis=ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x31', 8))
UyakMW2IMFEj = IDJ2eXGCBCDu.squeeze(UyakMW2IMFEj)
else:
UyakMW2IMFEj = IDJ2eXGCBCDu.squeeze(UyakMW2IMFEj, axis=-ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061', 8))
i06TFlWNuxU9 = IDJ2eXGCBCDu.cast(IDJ2eXGCBCDu.less(KrRiV9wIruZH, 1.0), IDJ2eXGCBCDu.float32)
nkqvWf45OJQF = IDJ2eXGCBCDu.cast(IDJ2eXGCBCDu.greater(KrRiV9wIruZH + UyakMW2IMFEj * i06TFlWNuxU9, DhxlYT5nN5Hu), IDJ2eXGCBCDu.float32) * i06TFlWNuxU9
i06TFlWNuxU9 = IDJ2eXGCBCDu.cast(IDJ2eXGCBCDu.less_equal(KrRiV9wIruZH + UyakMW2IMFEj * i06TFlWNuxU9, DhxlYT5nN5Hu), IDJ2eXGCBCDu.float32) * i06TFlWNuxU9
KrRiV9wIruZH += UyakMW2IMFEj * i06TFlWNuxU9
zNcnStGroZVg += nkqvWf45OJQF * (ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\x6f' + chr(0b10101 + 0o34), 8) - KrRiV9wIruZH)
KrRiV9wIruZH += nkqvWf45OJQF * zNcnStGroZVg
ciVXtTlQKiCh += i06TFlWNuxU9 + nkqvWf45OJQF
nNHiwD3mJDBn = IDJ2eXGCBCDu.expand_dims(UyakMW2IMFEj * i06TFlWNuxU9 + nkqvWf45OJQF * zNcnStGroZVg, -ehT0Px3KOsy9(chr(48) + chr(0b1001001 + 0o46) + '\x31', 8))
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x81\rp\xee\x06G\x93\x84'), chr(0b1100001 + 0o3) + chr(101) + chr(0b1010100 + 0o17) + chr(111) + chr(0b1100100 + 0o0) + '\x65')(chr(117) + chr(0b1110100) + chr(102) + chr(0b101101) + chr(2108 - 2052))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x87\x02k\xd3\x13R'), chr(8105 - 8005) + chr(0b110100 + 0o61) + '\143' + chr(5897 - 5786) + '\x64' + chr(101))('\x75' + '\x74' + '\x66' + chr(1816 - 1771) + chr(56)):
nNHiwD3mJDBn = IDJ2eXGCBCDu.expand_dims(nNHiwD3mJDBn, -ehT0Px3KOsy9(chr(48) + '\x6f' + '\061', 8))
mOMnObBgvPkH = KKFQISrGeiAm
for WVxHKyX45z_L in vQr8gNKaIaWE(xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e\x1bi\xee\x1bP\x91\x84+\xcb\xf6\xd1\x16L\xa3h\x88&O\x89\x93\x96\x18'), chr(0b1100100) + chr(101) + '\x63' + chr(0b1001000 + 0o47) + chr(2419 - 2319) + chr(101))(chr(0b1110101) + '\164' + '\146' + '\x2d' + chr(56)))):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x96\x0fv\xd8\x13\\\x8f\x84\x17\xcd\xe7\xcc\x03G'), chr(1565 - 1465) + chr(0b1001 + 0o134) + '\143' + chr(111) + chr(0b100010 + 0o102) + chr(0b10001 + 0o124))(chr(5646 - 5529) + '\164' + chr(102) + chr(0b1111 + 0o36) + chr(2798 - 2742)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\x0bg\xee\x1e_\x9a\x84:\xe1\xa1\xc7'), chr(100) + '\x65' + chr(0b1110 + 0o125) + '\157' + '\144' + chr(0b10110 + 0o117))(chr(0b101001 + 0o114) + chr(0b110011 + 0o101) + '\x66' + chr(0b101101) + chr(86 - 30)) % WVxHKyX45z_L):
mOMnObBgvPkH = SHRtjNoPzosY(ek3fs6JEXh0d(mOMnObBgvPkH))
bzRb0v_p_rjD = mOMnObBgvPkH * nNHiwD3mJDBn + RNFyM8qCdMT2 * (ehT0Px3KOsy9(chr(1023 - 975) + '\157' + chr(0b110001), 8) - nNHiwD3mJDBn)
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x81\rp\xee\x06G\x93\x84'), '\x64' + chr(0b1110 + 0o127) + chr(0b11000 + 0o113) + '\x6f' + chr(100) + chr(101))(chr(0b1110101) + chr(0b10111 + 0o135) + chr(102) + '\055' + chr(0b111000))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x81\rg\xc4\x1fK\x8f\x80<\xdb\xe0'), '\144' + chr(5040 - 4939) + chr(4403 - 4304) + chr(0b10011 + 0o134) + '\144' + chr(0b100011 + 0o102))(chr(0b1110101) + '\x74' + chr(0b1100110) + chr(45) + chr(56)):
bzRb0v_p_rjD = mOMnObBgvPkH * nNHiwD3mJDBn + RNFyM8qCdMT2
xafqLlk3kkUe(mOMnObBgvPkH, xafqLlk3kkUe(SXOLrMavuUCe(b'\x93\x0bp\xee\x01V\x82\x91-'), '\144' + chr(101) + chr(6408 - 6309) + chr(2263 - 2152) + chr(2496 - 2396) + chr(101))('\165' + chr(4070 - 3954) + chr(0b101001 + 0o75) + chr(45) + chr(0b111000)))(sjybvrljgW8H)
for OeWW0F1dBPRQ in [KrRiV9wIruZH, zNcnStGroZVg, ciVXtTlQKiCh]:
xafqLlk3kkUe(OeWW0F1dBPRQ, xafqLlk3kkUe(SXOLrMavuUCe(b'\x93\x0bp\xee\x01V\x82\x91-'), chr(0b1100100) + chr(0b1100101) + chr(99) + '\x6f' + '\x64' + chr(639 - 538))('\x75' + '\164' + chr(0b1100110) + chr(0b11100 + 0o21) + '\x38'))(sjybvrljgW8H[uLy2dxCaqQZ_])
xafqLlk3kkUe(bzRb0v_p_rjD, xafqLlk3kkUe(SXOLrMavuUCe(b'\x93\x0bp\xee\x01V\x82\x91-'), chr(0b1100100) + chr(101) + chr(0b1011 + 0o130) + '\157' + chr(100) + chr(0b110111 + 0o56))(chr(117) + chr(11447 - 11331) + chr(0b110000 + 0o66) + chr(0b101101) + '\x38'))(sjybvrljgW8H)
kDuFsAhEatcU += ehT0Px3KOsy9('\060' + '\157' + chr(0b110001), 8)
return (mOMnObBgvPkH, kDuFsAhEatcU, KrRiV9wIruZH, zNcnStGroZVg, ciVXtTlQKiCh, bzRb0v_p_rjD)
def tOBPNOooISnR(TNEh1h_BSh_h, MjSQsoYK9ZqB, KrRiV9wIruZH, Qcg0qw7RcLH_, ciVXtTlQKiCh, jHGWjahKiPq4):
del TNEh1h_BSh_h, MjSQsoYK9ZqB, Qcg0qw7RcLH_, jHGWjahKiPq4
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\x0b`\xc4\x11[\xbc\x80&\xc7'), chr(0b1011101 + 0o7) + chr(0b1100101) + '\x63' + chr(6735 - 6624) + '\144' + chr(0b1100101))(chr(117) + chr(116) + chr(0b1100011 + 0o3) + chr(45) + '\070'))(xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c\x01c\xd8\x11_\x8f\xbe)\xd0\xe0'), chr(100) + chr(0b1111 + 0o126) + chr(0b1100011) + chr(1097 - 986) + chr(100) + chr(0b1011100 + 0o11))(chr(0b100000 + 0o125) + chr(0b111100 + 0o70) + chr(0b1100110) + '\x2d' + '\x38'))(xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c\x0bw\xc2'), '\144' + chr(8728 - 8627) + chr(99) + chr(0b1101111) + '\144' + chr(0b1100101))('\165' + chr(116) + chr(0b1010100 + 0o22) + chr(0b101101) + '\x38'))(KrRiV9wIruZH, DhxlYT5nN5Hu), xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c\x0bw\xc2'), chr(2502 - 2402) + chr(9694 - 9593) + chr(99) + '\157' + '\x64' + '\145')(chr(3209 - 3092) + chr(116) + '\146' + '\x2d' + chr(1772 - 1716)))(ciVXtTlQKiCh, kBCT8GcwBJOF)))
(VNGQdHSFPrso, VNGQdHSFPrso, VNGQdHSFPrso, H4A5NixHRl2l, ciVXtTlQKiCh, bzRb0v_p_rjD) = IDJ2eXGCBCDu.while_loop(tOBPNOooISnR, bJ8teQTW0l5A, (KKFQISrGeiAm, kDuFsAhEatcU, KrRiV9wIruZH, zNcnStGroZVg, ciVXtTlQKiCh, RNFyM8qCdMT2), maximum_iterations=kBCT8GcwBJOF + ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31', 8))
W7tAPUZdP4qE = ciVXtTlQKiCh
zNcnStGroZVg = H4A5NixHRl2l
xafqLlk3kkUe(IDJ2eXGCBCDu.contrib.summary, xafqLlk3kkUe(SXOLrMavuUCe(b'\x93\re\xdd\x13L'), chr(299 - 199) + chr(0b1100101) + '\143' + '\157' + chr(100) + chr(0b1100101))('\x75' + '\164' + chr(0b1100110) + chr(0b10000 + 0o35) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x90\x01j\xd5\x17L\xbc\x95!\xd3\xe1\xd0'), '\x64' + '\x65' + chr(1040 - 941) + chr(111) + chr(100) + '\145')('\165' + chr(116) + chr(8318 - 8216) + '\x2d' + chr(0b11110 + 0o32)), xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\x0b`\xc4\x11[\xbc\x8c-\xdf\xea'), chr(1505 - 1405) + chr(0b110110 + 0o57) + '\x63' + chr(8768 - 8657) + '\144' + chr(0b1100101))(chr(0b1000111 + 0o56) + '\164' + chr(0b1100110) + '\055' + chr(0b1011 + 0o55)))(W7tAPUZdP4qE))
return (bzRb0v_p_rjD, (W7tAPUZdP4qE, zNcnStGroZVg))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
_ffn_layer_multi_inputs
|
def _ffn_layer_multi_inputs(inputs_list,
hparams,
ffn_layer_type="dense",
name="ffn",
kernel_initializer=None,
bias_initializer=None,
activation=None,
pad_remover=None,
preprocess=False,
postprocess=False):
"""Implements a Feed-forward layer with multiple inputs, pad-removing, etc.
Args:
inputs_list: list of input tensors
hparams: hyper-parameters
ffn_layer_type: dense / dense_dropconnect/ dense_relu_dense
name: name
kernel_initializer: kernel initializer
bias_initializer: bias initializer
activation: activation function
pad_remover: pad remover
preprocess: if preprocess the input
postprocess: if postprocess the output
Returns:
a tensor
Raises:
ValueError: Unknown ffn_layer type.
"""
# need at least one inputs
num_inputs = len(inputs_list)
assert num_inputs > 0
if preprocess and num_inputs == 1:
inputs_list[0] = common_layers.layer_preprocess(inputs_list[0], hparams)
if postprocess:
original_inputs = inputs_list[0]
# the output size is the hidden size of the main inputs
main_input = inputs_list[0]
original_shape = common_layers.shape_list(main_input)
assert hparams.hidden_size == common_layers.shape_list(main_input)[-1]
# all the inputs are in the same shape with main inputs
for inputs in inputs_list:
main_input.get_shape().assert_is_compatible_with(inputs.get_shape())
def remove_pads(x):
original_shape = common_layers.shape_list(x)
# Collapse `x` across examples, and remove padding positions.
x = tf.reshape(x, tf.concat([[-1], original_shape[2:]], axis=0))
x = tf.expand_dims(pad_remover.remove(x), axis=0)
return x
if pad_remover:
for i, inputs in enumerate(inputs_list):
inputs_list[i] = remove_pads(inputs)
ffn_inputs = inputs_list[0]
if len(inputs_list) != 1:
ffn_inputs = tf.concat(inputs_list, axis=-1)
if ffn_layer_type == "dense":
output = common_layers.dense(
ffn_inputs,
hparams.hidden_size,
name=name,
activation=activation,
use_bias=True,
kernel_initializer=kernel_initializer,
bias_initializer=bias_initializer)
elif ffn_layer_type == "dense_dropconnect":
output = common_layers.dense_dropconnect(
ffn_inputs,
hparams.hidden_size,
name=name,
dropconnect_dropout=hparams.dropconnect_dropout,
output_activation=activation)
postprocess = False # no dropout on the output unit
elif ffn_layer_type == "dense_relu_dense":
output = common_layers.dense_relu_dense(
ffn_inputs,
hparams.filter_size,
hparams.hidden_size,
name=name,
dropout=hparams.relu_dropout,
output_activation=activation,
)
else:
raise ValueError("Unknown ffn_layer type: %s" % ffn_layer_type)
if pad_remover:
# Restore `output` to the original shape of `x`, including padding.
output = tf.reshape(
pad_remover.restore(tf.squeeze(output, axis=0)), original_shape)
if postprocess:
if num_inputs == 1:
output = common_layers.layer_postprocess(original_inputs, output, hparams)
else: # only dropout (no residual)x
hp = copy.copy(hparams)
hp.layer_postprocess_sequence = hp.layer_postprocess_sequence.replace(
"a", "")
output = common_layers.layer_postprocess(original_inputs, output, hp)
return output
|
python
|
def _ffn_layer_multi_inputs(inputs_list,
hparams,
ffn_layer_type="dense",
name="ffn",
kernel_initializer=None,
bias_initializer=None,
activation=None,
pad_remover=None,
preprocess=False,
postprocess=False):
"""Implements a Feed-forward layer with multiple inputs, pad-removing, etc.
Args:
inputs_list: list of input tensors
hparams: hyper-parameters
ffn_layer_type: dense / dense_dropconnect/ dense_relu_dense
name: name
kernel_initializer: kernel initializer
bias_initializer: bias initializer
activation: activation function
pad_remover: pad remover
preprocess: if preprocess the input
postprocess: if postprocess the output
Returns:
a tensor
Raises:
ValueError: Unknown ffn_layer type.
"""
# need at least one inputs
num_inputs = len(inputs_list)
assert num_inputs > 0
if preprocess and num_inputs == 1:
inputs_list[0] = common_layers.layer_preprocess(inputs_list[0], hparams)
if postprocess:
original_inputs = inputs_list[0]
# the output size is the hidden size of the main inputs
main_input = inputs_list[0]
original_shape = common_layers.shape_list(main_input)
assert hparams.hidden_size == common_layers.shape_list(main_input)[-1]
# all the inputs are in the same shape with main inputs
for inputs in inputs_list:
main_input.get_shape().assert_is_compatible_with(inputs.get_shape())
def remove_pads(x):
original_shape = common_layers.shape_list(x)
# Collapse `x` across examples, and remove padding positions.
x = tf.reshape(x, tf.concat([[-1], original_shape[2:]], axis=0))
x = tf.expand_dims(pad_remover.remove(x), axis=0)
return x
if pad_remover:
for i, inputs in enumerate(inputs_list):
inputs_list[i] = remove_pads(inputs)
ffn_inputs = inputs_list[0]
if len(inputs_list) != 1:
ffn_inputs = tf.concat(inputs_list, axis=-1)
if ffn_layer_type == "dense":
output = common_layers.dense(
ffn_inputs,
hparams.hidden_size,
name=name,
activation=activation,
use_bias=True,
kernel_initializer=kernel_initializer,
bias_initializer=bias_initializer)
elif ffn_layer_type == "dense_dropconnect":
output = common_layers.dense_dropconnect(
ffn_inputs,
hparams.hidden_size,
name=name,
dropconnect_dropout=hparams.dropconnect_dropout,
output_activation=activation)
postprocess = False # no dropout on the output unit
elif ffn_layer_type == "dense_relu_dense":
output = common_layers.dense_relu_dense(
ffn_inputs,
hparams.filter_size,
hparams.hidden_size,
name=name,
dropout=hparams.relu_dropout,
output_activation=activation,
)
else:
raise ValueError("Unknown ffn_layer type: %s" % ffn_layer_type)
if pad_remover:
# Restore `output` to the original shape of `x`, including padding.
output = tf.reshape(
pad_remover.restore(tf.squeeze(output, axis=0)), original_shape)
if postprocess:
if num_inputs == 1:
output = common_layers.layer_postprocess(original_inputs, output, hparams)
else: # only dropout (no residual)x
hp = copy.copy(hparams)
hp.layer_postprocess_sequence = hp.layer_postprocess_sequence.replace(
"a", "")
output = common_layers.layer_postprocess(original_inputs, output, hp)
return output
|
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] |
Implements a Feed-forward layer with multiple inputs, pad-removing, etc.
Args:
inputs_list: list of input tensors
hparams: hyper-parameters
ffn_layer_type: dense / dense_dropconnect/ dense_relu_dense
name: name
kernel_initializer: kernel initializer
bias_initializer: bias initializer
activation: activation function
pad_remover: pad remover
preprocess: if preprocess the input
postprocess: if postprocess the output
Returns:
a tensor
Raises:
ValueError: Unknown ffn_layer type.
|
[
"Implements",
"a",
"Feed",
"-",
"forward",
"layer",
"with",
"multiple",
"inputs",
"pad",
"-",
"removing",
"etc",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L1215-L1326
|
train
|
Implements a Feed - forward layer with multiple inputs.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b1001 + 0o50) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(366 - 318) + '\x6f' + chr(0b1000 + 0o52) + chr(0b11101 + 0o32) + chr(1829 - 1779), 0o10), ehT0Px3KOsy9('\060' + chr(0b11001 + 0o126) + chr(0b11100 + 0o30) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(1504 - 1456) + '\157' + chr(0b110011) + chr(0b110010) + chr(53), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100111 + 0o14) + '\065' + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\x36' + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b100000 + 0o20) + '\x6f' + chr(0b110011), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + chr(0b101010 + 0o10), ord("\x08")), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\157' + '\x32' + chr(51) + '\062', 39169 - 39161), ehT0Px3KOsy9('\060' + chr(111) + '\x32' + chr(0b110110) + chr(48), 21303 - 21295), ehT0Px3KOsy9(chr(2150 - 2102) + '\157' + chr(0b101011 + 0o10) + chr(0b11011 + 0o27) + chr(50), 0b1000), ehT0Px3KOsy9(chr(2190 - 2142) + chr(0b1101111) + '\x33' + chr(0b11011 + 0o31) + '\x33', 0b1000), ehT0Px3KOsy9(chr(218 - 170) + '\157' + '\x33' + chr(52), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b11100 + 0o27) + chr(0b110001) + '\063', 50969 - 50961), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101110 + 0o4) + '\x34' + chr(525 - 471), 0o10), ehT0Px3KOsy9(chr(1507 - 1459) + chr(12105 - 11994) + chr(0b110010) + chr(425 - 373), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\062' + chr(53) + chr(1319 - 1265), 0b1000), ehT0Px3KOsy9(chr(1860 - 1812) + chr(0b1101111) + '\x33' + chr(2340 - 2288) + chr(0b101101 + 0o12), 0b1000), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(111) + '\x32' + chr(0b110110) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(10836 - 10725) + chr(0b1000 + 0o52) + '\063' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + chr(0b110010 + 0o1) + '\x36' + chr(55), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + chr(0b11011 + 0o30) + chr(2351 - 2300), 0o10), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(111) + chr(0b110010) + chr(0b1110 + 0o45) + '\x35', 8), ehT0Px3KOsy9(chr(655 - 607) + chr(0b1011011 + 0o24) + '\x33' + chr(55) + chr(54), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + '\x35' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\157' + '\061' + '\064' + chr(51), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x32' + '\x36' + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1010011 + 0o34) + chr(0b110011 + 0o0) + '\x32' + chr(0b110011), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(50) + chr(51) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010000 + 0o37) + chr(50) + chr(54) + chr(0b100111 + 0o16), 0b1000), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(0b11101 + 0o122) + chr(49) + '\061' + chr(550 - 496), 15449 - 15441), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + chr(0b100101 + 0o13) + chr(0b10 + 0o64), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + chr(51) + chr(0b110010), 8), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(0b1001111 + 0o40) + '\061' + '\066' + chr(0b11010 + 0o30), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49) + '\065' + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + chr(921 - 871) + chr(1765 - 1717), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + '\060' + chr(0b100000 + 0o27), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + chr(50) + chr(50), 8), ehT0Px3KOsy9('\x30' + '\157' + chr(51) + '\062' + chr(0b110101), 8), ehT0Px3KOsy9('\060' + chr(10087 - 9976) + '\063' + '\062' + chr(2650 - 2597), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(267 - 219) + chr(1966 - 1855) + chr(0b100 + 0o61) + chr(0b11010 + 0o26), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'&'), chr(0b1100100) + chr(0b1100101) + chr(99) + chr(0b1011 + 0o144) + chr(0b1111 + 0o125) + chr(0b1000 + 0o135))(chr(11343 - 11226) + '\x74' + chr(10079 - 9977) + chr(0b110 + 0o47) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def TlcH9M_VkXCB(z4VZIwhw1Vpr, n4ljua2gi1Pr, GSba7y4QrBxX=xafqLlk3kkUe(SXOLrMavuUCe(b'l\xdfK\xa6\x8c'), chr(8365 - 8265) + chr(7131 - 7030) + chr(99) + chr(0b1101100 + 0o3) + '\x64' + '\x65')(chr(0b1110101) + chr(12213 - 12097) + chr(102) + chr(45) + '\x38'), AIvJRzLdDfgF=xafqLlk3kkUe(SXOLrMavuUCe(b'n\xdcK'), chr(0b101010 + 0o72) + chr(101) + '\143' + chr(11483 - 11372) + '\144' + chr(0b1100101))(chr(0b1110101) + chr(116) + '\x66' + chr(1475 - 1430) + '\070'), yTYoQGLIQD0u=None, qV2vQknHOrdL=None, _GyOifGFZyk1=None, bLDzE_zU4vXa=None, n8IJXbSueTJV=ehT0Px3KOsy9(chr(0b110000) + chr(9712 - 9601) + '\060', 0o10), wwNuyCSLWczo=ehT0Px3KOsy9(chr(2264 - 2216) + '\x6f' + chr(0b110000), 8)):
gjMqORDCm2Cl = c2A0yzQpDQB3(z4VZIwhw1Vpr)
assert gjMqORDCm2Cl > ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\x6f' + '\x30', 8)
if n8IJXbSueTJV and gjMqORDCm2Cl == ehT0Px3KOsy9(chr(0b111 + 0o51) + '\x6f' + chr(1067 - 1018), 0b1000):
z4VZIwhw1Vpr[ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(651 - 603), 8)] = jSKPaHwSAfVv.layer_preprocess(z4VZIwhw1Vpr[ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(111) + '\060', 8)], n4ljua2gi1Pr)
if wwNuyCSLWczo:
L153lFEVelnH = z4VZIwhw1Vpr[ehT0Px3KOsy9(chr(189 - 141) + chr(6722 - 6611) + chr(48), 8)]
z1x_o_9HT_Vk = z4VZIwhw1Vpr[ehT0Px3KOsy9(chr(48) + '\157' + chr(48), 8)]
uoX0EqIBJxTx = jSKPaHwSAfVv.shape_list(z1x_o_9HT_Vk)
assert xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'y\xc0J\xac\xb1\x7f0a\xfe\xd8\x96\xaf'), chr(100) + '\x65' + chr(0b1100011) + '\157' + chr(7899 - 7799) + chr(2255 - 2154))(chr(11205 - 11088) + chr(0b1110100) + chr(0b1010000 + 0o26) + chr(0b1101 + 0o40) + chr(2079 - 2023))) == xafqLlk3kkUe(jSKPaHwSAfVv, xafqLlk3kkUe(SXOLrMavuUCe(b'{\xd2D\xa5\x8cnoc\xe9\xc4'), chr(3872 - 3772) + chr(0b1100101) + chr(0b11 + 0o140) + '\157' + chr(0b1100100) + chr(101))('\x75' + chr(116) + chr(0b1100110) + chr(0b101 + 0o50) + '\x38'))(z1x_o_9HT_Vk)[-ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b1101111) + chr(2170 - 2121), 8)]
for vXoupepMtCXU in z4VZIwhw1Vpr:
xafqLlk3kkUe(z1x_o_9HT_Vk.get_shape(), xafqLlk3kkUe(SXOLrMavuUCe(b'i\xc9V\xb0\x9bE\\c\xe9\xef\xb1\x8cq\xbb\xc7`\xc7\x85\xde\xf8\xa8,\xf4\x8a\x06'), chr(0b101101 + 0o67) + chr(0b1100101) + '\143' + '\x6f' + chr(100) + chr(0b1100101))(chr(0b1000010 + 0o63) + chr(0b1110100) + chr(102) + chr(0b1110 + 0o37) + chr(0b111000)))(xafqLlk3kkUe(vXoupepMtCXU, xafqLlk3kkUe(SXOLrMavuUCe(b'o\xdfQ\x8a\x9aYbz\xff'), chr(100) + '\x65' + chr(0b1100011) + chr(0b1101111) + chr(0b100001 + 0o103) + chr(101))(chr(0b1110101) + chr(12074 - 11958) + '\146' + chr(0b10011 + 0o32) + chr(0b111000)))())
def YOycpWPbDi8a(OeWW0F1dBPRQ):
uoX0EqIBJxTx = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
OeWW0F1dBPRQ = IDJ2eXGCBCDu.reshape(OeWW0F1dBPRQ, IDJ2eXGCBCDu.concat([[-ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x31', 8)], uoX0EqIBJxTx[ehT0Px3KOsy9('\x30' + chr(6779 - 6668) + '\062', ord("\x08")):]], axis=ehT0Px3KOsy9('\x30' + '\157' + '\x30', 8)))
OeWW0F1dBPRQ = IDJ2eXGCBCDu.expand_dims(bLDzE_zU4vXa.remove(OeWW0F1dBPRQ), axis=ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\060', 8))
return OeWW0F1dBPRQ
if bLDzE_zU4vXa:
for (WVxHKyX45z_L, vXoupepMtCXU) in YlkZvXL8qwsX(z4VZIwhw1Vpr):
z4VZIwhw1Vpr[WVxHKyX45z_L] = YOycpWPbDi8a(vXoupepMtCXU)
fQSXbmkTcp72 = z4VZIwhw1Vpr[ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\157' + chr(0b101101 + 0o3), 8)]
if c2A0yzQpDQB3(z4VZIwhw1Vpr) != ehT0Px3KOsy9('\060' + chr(111) + chr(302 - 253), 8):
fQSXbmkTcp72 = IDJ2eXGCBCDu.concat(z4VZIwhw1Vpr, axis=-ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1570 - 1521), 8))
if GSba7y4QrBxX == xafqLlk3kkUe(SXOLrMavuUCe(b'l\xdfK\xa6\x8c'), chr(7506 - 7406) + '\145' + '\143' + '\x6f' + chr(8282 - 8182) + chr(101))(chr(0b1110101) + chr(0b111 + 0o155) + chr(102) + chr(1477 - 1432) + '\x38'):
e1jVqMSBZ01Y = jSKPaHwSAfVv.dense(fQSXbmkTcp72, n4ljua2gi1Pr.qzoyXN3kdhDL, name=AIvJRzLdDfgF, activation=_GyOifGFZyk1, use_bias=ehT0Px3KOsy9(chr(0b110000) + chr(0b1101010 + 0o5) + chr(0b110001), 8), kernel_initializer=yTYoQGLIQD0u, bias_initializer=qV2vQknHOrdL)
elif GSba7y4QrBxX == xafqLlk3kkUe(SXOLrMavuUCe(b'l\xdfK\xa6\x8cngx\xf5\xc0\xb1\x8cr\xa5\xc3w\xda'), chr(0b1011001 + 0o13) + chr(0b1100101) + '\x63' + '\157' + chr(0b1010010 + 0o22) + chr(101))(chr(0b1110101) + chr(116) + chr(0b11010 + 0o114) + chr(45) + chr(0b111000)):
e1jVqMSBZ01Y = jSKPaHwSAfVv.dense_dropconnect(fQSXbmkTcp72, n4ljua2gi1Pr.qzoyXN3kdhDL, name=AIvJRzLdDfgF, dropconnect_dropout=n4ljua2gi1Pr.dropconnect_dropout, output_activation=_GyOifGFZyk1)
wwNuyCSLWczo = ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(111) + chr(1985 - 1937), 8)
elif GSba7y4QrBxX == xafqLlk3kkUe(SXOLrMavuUCe(b'l\xdfK\xa6\x8cnqo\xf6\xc5\x8d\x87y\xa5\xd5q'), chr(0b1011100 + 0o10) + '\x65' + chr(0b1100011) + chr(0b1101111) + '\x64' + chr(101))(chr(4274 - 4157) + chr(0b1110001 + 0o3) + chr(0b1001000 + 0o36) + '\x2d' + chr(601 - 545)):
e1jVqMSBZ01Y = jSKPaHwSAfVv.dense_relu_dense(fQSXbmkTcp72, n4ljua2gi1Pr.deybX8NJ0oEI, n4ljua2gi1Pr.qzoyXN3kdhDL, name=AIvJRzLdDfgF, dropout=n4ljua2gi1Pr.PJc0PNdBnSag, output_activation=_GyOifGFZyk1)
else:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b']\xd4N\xbb\x86Fm*\xfc\xd6\xbc\xbcp\xaa\xdfq\xdc\xc7\xc6\xe4\x87>\xa7\xdeK\x10'), chr(100) + chr(101) + '\x63' + chr(111) + chr(2730 - 2630) + chr(101))(chr(0b1110101) + chr(0b1110100) + chr(724 - 622) + '\055' + chr(493 - 437)) % GSba7y4QrBxX)
if bLDzE_zU4vXa:
e1jVqMSBZ01Y = IDJ2eXGCBCDu.reshape(bLDzE_zU4vXa.restore(IDJ2eXGCBCDu.squeeze(e1jVqMSBZ01Y, axis=ehT0Px3KOsy9('\060' + '\x6f' + '\060', 8))), uoX0EqIBJxTx)
if wwNuyCSLWczo:
if gjMqORDCm2Cl == ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49), 8):
e1jVqMSBZ01Y = jSKPaHwSAfVv.layer_postprocess(L153lFEVelnH, e1jVqMSBZ01Y, n4ljua2gi1Pr)
else:
ny6shRSJO9Wm = igThHS4jwVsa.igThHS4jwVsa(n4ljua2gi1Pr)
ny6shRSJO9Wm.s6T_PoakASTI = ny6shRSJO9Wm.layer_postprocess_sequence.replace(xafqLlk3kkUe(SXOLrMavuUCe(b'i'), chr(100) + chr(0b1100101) + '\x63' + '\x6f' + chr(0b1100100) + '\x65')(chr(0b1110101) + chr(0b1110100) + '\146' + chr(1620 - 1575) + chr(0b100010 + 0o26)), xafqLlk3kkUe(SXOLrMavuUCe(b''), chr(5008 - 4908) + chr(0b1100101) + chr(99) + chr(0b10111 + 0o130) + chr(0b111101 + 0o47) + chr(0b1100101))('\165' + '\x74' + '\146' + chr(1488 - 1443) + chr(56)))
e1jVqMSBZ01Y = jSKPaHwSAfVv.layer_postprocess(L153lFEVelnH, e1jVqMSBZ01Y, ny6shRSJO9Wm)
return e1jVqMSBZ01Y
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
fill_memory_slot
|
def fill_memory_slot(memory, value, index):
"""Fills the memory slot at a particular index with the given value.
Args:
memory: a 4-d tensor [memory_size, batch, length, channel] containing
the state of all steps
value: a 3-d tensor [batch, length, channel] as the sate
index: integer in [0, memory_size)
Returns:
filled memory
"""
mask = tf.to_float(
tf.one_hot(index,
tf.shape(memory)[0])[:, None, None, None])
fill_memory = (1 - mask) * memory + mask * value[None, ...]
return fill_memory
|
python
|
def fill_memory_slot(memory, value, index):
"""Fills the memory slot at a particular index with the given value.
Args:
memory: a 4-d tensor [memory_size, batch, length, channel] containing
the state of all steps
value: a 3-d tensor [batch, length, channel] as the sate
index: integer in [0, memory_size)
Returns:
filled memory
"""
mask = tf.to_float(
tf.one_hot(index,
tf.shape(memory)[0])[:, None, None, None])
fill_memory = (1 - mask) * memory + mask * value[None, ...]
return fill_memory
|
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"*",
"value",
"[",
"None",
",",
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"]",
"return",
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] |
Fills the memory slot at a particular index with the given value.
Args:
memory: a 4-d tensor [memory_size, batch, length, channel] containing
the state of all steps
value: a 3-d tensor [batch, length, channel] as the sate
index: integer in [0, memory_size)
Returns:
filled memory
|
[
"Fills",
"the",
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"slot",
"at",
"a",
"particular",
"index",
"with",
"the",
"given",
"value",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L1329-L1346
|
train
|
Fills the memory at a particular index with the given value.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + '\157' + chr(1148 - 1097) + chr(134 - 83) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + chr(0b110111) + chr(54), 17344 - 17336), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(2146 - 2096) + '\061' + '\061', 40821 - 40813), ehT0Px3KOsy9('\060' + '\157' + '\063' + chr(0b100000 + 0o22) + chr(0b10 + 0o56), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1100101 + 0o12) + '\063' + chr(0b110001) + '\060', 0b1000), ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\x6f' + chr(0b110010) + chr(0b11001 + 0o30) + chr(0b110111), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\x37' + chr(0b110011), 36010 - 36002), ehT0Px3KOsy9(chr(48) + chr(111) + '\063' + '\066' + chr(0b110100 + 0o0), 21800 - 21792), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110111) + chr(1368 - 1313), 38743 - 38735), ehT0Px3KOsy9(chr(0b110000) + chr(2904 - 2793) + chr(1629 - 1580) + '\065' + chr(0b1010 + 0o47), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(604 - 554) + '\064' + chr(101 - 53), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\x32' + chr(0b100110 + 0o16) + chr(49), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101 + 0o142) + chr(0b100100 + 0o16) + chr(52) + '\x32', 16795 - 16787), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x32' + '\x31' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(625 - 514) + '\x33' + '\065' + '\062', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + '\061', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(1311 - 1260) + chr(0b110100) + chr(0b10000 + 0o44), 0o10), ehT0Px3KOsy9(chr(150 - 102) + '\x6f' + chr(55) + chr(55), 8), ehT0Px3KOsy9('\x30' + chr(0b1101100 + 0o3) + chr(0b100011 + 0o17) + chr(0b110001) + '\x32', 12506 - 12498), ehT0Px3KOsy9('\x30' + chr(111) + chr(2543 - 2490) + chr(0b111 + 0o54), 0b1000), ehT0Px3KOsy9('\x30' + chr(5216 - 5105) + chr(49) + chr(1922 - 1873) + chr(0b101011 + 0o7), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\063' + chr(2477 - 2423) + chr(0b1011 + 0o53), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b111111 + 0o60) + chr(1333 - 1283) + chr(698 - 648) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(335 - 287) + '\157' + chr(0b110011) + chr(1895 - 1847) + chr(0b1101 + 0o51), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110100) + chr(55), 3669 - 3661), ehT0Px3KOsy9('\x30' + chr(0b10111 + 0o130) + chr(0b110011) + chr(0b110111) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(4756 - 4645) + '\x32' + '\x33' + chr(1366 - 1318), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + '\x33' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(1616 - 1568) + '\157' + '\x36' + '\x35', 0b1000), ehT0Px3KOsy9(chr(1371 - 1323) + '\x6f' + '\061' + chr(0b110110) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(10731 - 10620) + chr(0b110001) + chr(0b110111) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011 + 0o144) + chr(0b110011) + chr(0b110110) + chr(0b110000), 0o10), ehT0Px3KOsy9('\060' + chr(0b11111 + 0o120) + '\x31' + chr(2187 - 2133) + '\066', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001) + chr(0b110000) + chr(55), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(333 - 283) + chr(1728 - 1677) + chr(0b11111 + 0o30), 58443 - 58435), ehT0Px3KOsy9(chr(441 - 393) + chr(0b1101111) + chr(0b110111) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(1731 - 1683) + chr(111) + chr(0b101011 + 0o6) + chr(0b110000 + 0o3) + chr(50), 44138 - 44130), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061' + '\x33' + '\065', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + '\x32' + chr(2740 - 2685), 0o10), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(1426 - 1315) + '\065' + chr(48), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(10403 - 10292) + chr(0b100011 + 0o22) + chr(1749 - 1701), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf3'), '\144' + '\145' + chr(0b100000 + 0o103) + chr(111) + '\144' + chr(101))(chr(0b1110101) + '\164' + chr(559 - 457) + '\x2d' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def nWMmlaB9bcqE(KcR7WgfLppqF, QmmgWUB13VCJ, XdowRbJKZWL9):
Iz1jSgUKZDvt = IDJ2eXGCBCDu.to_float(IDJ2eXGCBCDu.Hq3fv4Yp0EhD(XdowRbJKZWL9, IDJ2eXGCBCDu.nauYfLglTpcb(KcR7WgfLppqF)[ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(9350 - 9239) + '\060', 0o10)])[:, None, None, None])
hLS6T4p3Y6sI = (ehT0Px3KOsy9('\x30' + '\x6f' + '\x31', 0b1000) - Iz1jSgUKZDvt) * KcR7WgfLppqF + Iz1jSgUKZDvt * QmmgWUB13VCJ[None, ...]
return hLS6T4p3Y6sI
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
add_depth_embedding
|
def add_depth_embedding(x):
"""Add n-dimensional embedding as the depth embedding (timing signal).
Adds embeddings to represent the position of the step in the recurrent
tower.
Args:
x: a tensor with shape [max_step, batch, length, depth]
Returns:
a Tensor the same shape as x.
"""
x_shape = common_layers.shape_list(x)
depth = x_shape[-1]
num_steps = x_shape[0]
shape = [num_steps, 1, 1, depth]
depth_embedding = (
tf.get_variable(
"depth_embedding",
shape,
initializer=tf.random_normal_initializer(0, depth**-0.5)) * (depth**
0.5))
x += depth_embedding
return x
|
python
|
def add_depth_embedding(x):
"""Add n-dimensional embedding as the depth embedding (timing signal).
Adds embeddings to represent the position of the step in the recurrent
tower.
Args:
x: a tensor with shape [max_step, batch, length, depth]
Returns:
a Tensor the same shape as x.
"""
x_shape = common_layers.shape_list(x)
depth = x_shape[-1]
num_steps = x_shape[0]
shape = [num_steps, 1, 1, depth]
depth_embedding = (
tf.get_variable(
"depth_embedding",
shape,
initializer=tf.random_normal_initializer(0, depth**-0.5)) * (depth**
0.5))
x += depth_embedding
return x
|
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Add n-dimensional embedding as the depth embedding (timing signal).
Adds embeddings to represent the position of the step in the recurrent
tower.
Args:
x: a tensor with shape [max_step, batch, length, depth]
Returns:
a Tensor the same shape as x.
|
[
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"embedding",
"(",
"timing",
"signal",
")",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L1349-L1373
|
train
|
Adds n - dimensional embedding as the depth embedding.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(0b110100), 5412 - 5404), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b10110 + 0o35) + '\x35' + '\x32', 742 - 734), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(10414 - 10303) + chr(0b10111 + 0o40) + chr(0b110111), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + '\x30' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + chr(52), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x32' + chr(0b110000) + chr(0b110110), 32974 - 32966), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + '\x31' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b100000 + 0o20) + '\x6f' + '\062' + chr(0b11000 + 0o36) + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\x35' + chr(712 - 662), 0o10), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(111) + chr(49) + '\x30' + chr(786 - 734), 35963 - 35955), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(1289 - 1237) + chr(0b11010 + 0o35), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b101100 + 0o10) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(330 - 282) + chr(0b1101111) + '\x37' + chr(491 - 437), ord("\x08")), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(7000 - 6889) + chr(0b110001) + '\067' + '\061', 24633 - 24625), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1355 - 1305) + '\066' + '\061', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b100100 + 0o113) + '\x31' + '\x37' + '\063', 0o10), ehT0Px3KOsy9(chr(1508 - 1460) + '\x6f' + chr(1043 - 994) + chr(2311 - 2260) + chr(2200 - 2150), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + chr(0b110010) + '\x32', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b10001 + 0o40), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1100011 + 0o14) + chr(50) + chr(48) + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\157' + '\061' + '\x36' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b110001 + 0o76) + chr(0b110011) + '\x34' + '\x35', 33326 - 33318), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(53) + chr(52), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(2250 - 2196) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + chr(10069 - 9958) + chr(0b110010) + chr(0b11000 + 0o34) + chr(0b11100 + 0o27), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b10011 + 0o36) + chr(0b101010 + 0o13) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(1365 - 1317) + chr(0b11101 + 0o122) + chr(1260 - 1211) + '\061' + '\066', 54001 - 53993), ehT0Px3KOsy9('\060' + chr(11653 - 11542) + chr(0b110011) + chr(0b101010 + 0o11) + chr(0b101101 + 0o10), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b11010 + 0o27) + chr(0b110000) + '\065', 5411 - 5403), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1620 - 1571) + chr(0b101111 + 0o5) + '\x33', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1010011 + 0o34) + chr(0b11011 + 0o27) + '\x35' + chr(0b10001 + 0o44), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1000000 + 0o57) + chr(0b110011) + chr(0b110011) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b1101111) + chr(0b11100 + 0o26), ord("\x08")), ehT0Px3KOsy9(chr(1163 - 1115) + '\157' + '\x31', 8), ehT0Px3KOsy9('\x30' + chr(0b10011 + 0o134) + '\x32' + '\x36' + chr(1666 - 1616), 37761 - 37753), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + '\064' + chr(0b11 + 0o56), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + chr(51) + chr(2243 - 2192), ord("\x08")), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\x6f' + '\063' + '\062' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(0b110110) + chr(48), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b100000 + 0o24) + '\x30', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b101111 + 0o100) + chr(53) + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'"'), '\x64' + '\145' + chr(0b1100011) + chr(5982 - 5871) + chr(6854 - 6754) + chr(0b1000010 + 0o43))(chr(0b1110000 + 0o5) + chr(0b1110011 + 0o1) + '\146' + chr(593 - 548) + chr(0b1111 + 0o51)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def B4mMKRG89s7X(OeWW0F1dBPRQ):
QQEXXbdZyz6m = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
UEys4_lSwsID = QQEXXbdZyz6m[-ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061', 8)]
UQsgPnJC3jY0 = QQEXXbdZyz6m[ehT0Px3KOsy9('\x30' + chr(0b1100111 + 0o10) + chr(235 - 187), 7139 - 7131)]
nauYfLglTpcb = [UQsgPnJC3jY0, ehT0Px3KOsy9(chr(48) + '\157' + chr(0b11001 + 0o30), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061', 8), UEys4_lSwsID]
poJpvc2aOMRU = IDJ2eXGCBCDu.get_variable(xafqLlk3kkUe(SXOLrMavuUCe(b'h\x8fO\xb2|\xd9\xab\xdaH!\xc3BW\x17\xd6'), '\144' + chr(0b1100101) + '\x63' + '\157' + chr(100) + chr(0b1011001 + 0o14))(chr(0b1110101) + chr(0b1001 + 0o153) + chr(0b1100110) + chr(45) + chr(0b111000)), nauYfLglTpcb, initializer=IDJ2eXGCBCDu.random_normal_initializer(ehT0Px3KOsy9(chr(48) + chr(111) + '\060', 8), UEys4_lSwsID ** (-0.5))) * UEys4_lSwsID ** 0.5
OeWW0F1dBPRQ += poJpvc2aOMRU
return OeWW0F1dBPRQ
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
step_preprocess
|
def step_preprocess(x, step, hparams):
"""Preprocess the input at the beginning of each step.
Args:
x: input tensor
step: step
hparams: model hyper-parameters
Returns:
preprocessed input.
"""
original_channel_size = common_layers.shape_list(x)[-1]
if hparams.add_position_timing_signal:
x = add_position_timing_signal(x, step, hparams)
if hparams.add_step_timing_signal:
x = add_step_timing_signal(x, step, hparams)
if ((hparams.add_position_timing_signal or hparams.add_position_timing_signal)
and hparams.add_or_concat_timing_signal == "concat"):
# linear projection to the original dimension of x
x = common_layers.dense(
x, original_channel_size, activation=None, use_bias=False)
if hparams.add_sru:
x = common_layers.sru(x)
return x
|
python
|
def step_preprocess(x, step, hparams):
"""Preprocess the input at the beginning of each step.
Args:
x: input tensor
step: step
hparams: model hyper-parameters
Returns:
preprocessed input.
"""
original_channel_size = common_layers.shape_list(x)[-1]
if hparams.add_position_timing_signal:
x = add_position_timing_signal(x, step, hparams)
if hparams.add_step_timing_signal:
x = add_step_timing_signal(x, step, hparams)
if ((hparams.add_position_timing_signal or hparams.add_position_timing_signal)
and hparams.add_or_concat_timing_signal == "concat"):
# linear projection to the original dimension of x
x = common_layers.dense(
x, original_channel_size, activation=None, use_bias=False)
if hparams.add_sru:
x = common_layers.sru(x)
return x
|
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] |
Preprocess the input at the beginning of each step.
Args:
x: input tensor
step: step
hparams: model hyper-parameters
Returns:
preprocessed input.
|
[
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L1376-L1405
|
train
|
Preprocess the input at the beginning of each step.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(4645 - 4534) + chr(0b11010 + 0o30) + chr(51) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\061' + chr(0b1 + 0o61) + chr(0b100110 + 0o13), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + '\x37' + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + chr(0b110100) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(1213 - 1165) + chr(4520 - 4409) + '\063' + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + '\063' + chr(0b10111 + 0o32), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + '\x36' + '\066', 0o10), ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\157' + chr(51) + '\x32' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\x6f' + '\062' + chr(55) + chr(2525 - 2473), 0b1000), ehT0Px3KOsy9(chr(648 - 600) + chr(111) + chr(0b110001) + chr(0b110100 + 0o3) + '\067', 29508 - 29500), ehT0Px3KOsy9('\x30' + chr(111) + '\066', 0b1000), ehT0Px3KOsy9(chr(2183 - 2135) + chr(7331 - 7220) + chr(50) + chr(0b1100 + 0o47) + '\060', 8), ehT0Px3KOsy9(chr(0b110000) + chr(5853 - 5742) + chr(0b101010 + 0o11) + '\064' + chr(0b1000 + 0o53), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + '\x35' + '\067', 0o10), ehT0Px3KOsy9('\060' + chr(0b100010 + 0o115) + chr(0b10011 + 0o37) + '\x35' + chr(0b101100 + 0o6), ord("\x08")), ehT0Px3KOsy9(chr(2164 - 2116) + chr(10684 - 10573) + '\x35' + chr(0b1110 + 0o47), 16407 - 16399), ehT0Px3KOsy9('\060' + '\157' + chr(793 - 744) + chr(50) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(1573 - 1525) + '\x6f' + '\061' + chr(0b110001) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\x31' + chr(0b110010) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\x6f' + '\x34' + '\x33', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(198 - 148) + chr(0b10111 + 0o36) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + chr(0b10100 + 0o34) + chr(2241 - 2193), 0b1000), ehT0Px3KOsy9(chr(0b100111 + 0o11) + '\157' + chr(0b100101 + 0o14) + '\060' + chr(0b10 + 0o61), 26544 - 26536), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1550 - 1500) + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(333 - 284) + '\x30' + chr(0b110011), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + chr(0b101101 + 0o3) + '\x34', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(1596 - 1547) + '\x34' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(0b1101111) + chr(0b100101 + 0o15) + chr(1066 - 1017) + chr(0b101000 + 0o10), 0b1000), ehT0Px3KOsy9(chr(366 - 318) + '\157' + chr(0b1 + 0o60) + chr(829 - 781) + chr(0b101000 + 0o11), 27538 - 27530), ehT0Px3KOsy9(chr(2032 - 1984) + chr(3640 - 3529) + chr(49) + chr(1613 - 1560) + chr(0b111 + 0o52), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1796 - 1745) + '\067' + '\x37', 0b1000), ehT0Px3KOsy9(chr(1368 - 1320) + chr(0b1101111) + chr(49) + '\066' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1010110 + 0o31) + '\061' + chr(0b110100) + '\064', 34309 - 34301), ehT0Px3KOsy9(chr(1202 - 1154) + '\157' + chr(49) + '\065' + chr(933 - 880), 46897 - 46889), ehT0Px3KOsy9(chr(0b101 + 0o53) + '\x6f' + '\x31' + chr(1794 - 1742) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b1101110 + 0o1) + chr(2351 - 2300) + chr(475 - 423) + chr(296 - 246), 24714 - 24706), ehT0Px3KOsy9(chr(0b110000) + chr(8887 - 8776) + chr(51) + chr(0b1010 + 0o51), 60554 - 60546), ehT0Px3KOsy9(chr(0b100 + 0o54) + '\157' + chr(0b110011) + chr(932 - 880) + chr(0b110010), 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32' + chr(0b110010 + 0o0) + chr(52), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b101010 + 0o7) + chr(54), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(1477 - 1429) + chr(0b1101111) + '\065' + '\x30', 18822 - 18814)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb6'), chr(0b1100100) + chr(356 - 255) + chr(0b1000000 + 0o43) + chr(0b1101111) + chr(0b1100100) + '\x65')(chr(117) + chr(4661 - 4545) + '\146' + chr(0b10010 + 0o33) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def A2EO56BplgPh(OeWW0F1dBPRQ, kDuFsAhEatcU, n4ljua2gi1Pr):
telKTe0dti2J = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)[-ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(202 - 153), ord("\x08"))]
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf95\xdb\xbfi\xb6\x85\xbf\xc8\x16i\xf6\xbc\x1b\xc3@>"1|\xde\xe9$y"\xa8'), chr(8837 - 8737) + chr(101) + chr(0b111110 + 0o45) + chr(0b1101111) + chr(0b1010111 + 0o15) + '\x65')('\165' + '\x74' + chr(102) + chr(782 - 737) + chr(1090 - 1034))):
OeWW0F1dBPRQ = OmImHhkMEG3R(OeWW0F1dBPRQ, kDuFsAhEatcU, n4ljua2gi1Pr)
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf95\xdb\xbfj\xad\x93\xa6\xe3\x0bo\xf5\x8a\x01\xcdr$%1M\xcc\xec'), chr(3669 - 3569) + '\x65' + '\143' + '\x6f' + '\144' + '\x65')(chr(0b1110101) + chr(116) + '\146' + chr(45) + chr(0b100001 + 0o27))):
OeWW0F1dBPRQ = W3WXOJx9HFnq(OeWW0F1dBPRQ, kDuFsAhEatcU, n4ljua2gi1Pr)
if (xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf95\xdb\xbfi\xb6\x85\xbf\xc8\x16i\xf6\xbc\x1b\xc3@>"1|\xde\xe9$y"\xa8'), chr(100) + chr(0b101001 + 0o74) + chr(7652 - 7553) + chr(5485 - 5374) + '\144' + '\145')('\165' + chr(116) + chr(102) + chr(108 - 63) + '\x38')) or xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf95\xdb\xbfi\xb6\x85\xbf\xc8\x16i\xf6\xbc\x1b\xc3@>"1|\xde\xe9$y"\xa8'), chr(0b1000101 + 0o37) + chr(8909 - 8808) + chr(0b1001110 + 0o25) + chr(0b1101111) + chr(0b110 + 0o136) + '\x65')(chr(0b100 + 0o161) + chr(10304 - 10188) + chr(102) + '\x2d' + '\070'))) and xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf95\xdb\xbfv\xab\xa9\xb5\xd3\x11e\xf9\x970\xdeD:%8D\xf2\xf3*p-\xa5\x0e'), '\144' + '\x65' + '\x63' + chr(0b1111 + 0o140) + '\x64' + chr(0b1100101))(chr(3643 - 3526) + '\x74' + chr(102) + chr(45) + chr(1816 - 1760))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\xfb>\xd1\x83x\xad'), '\144' + '\145' + chr(3542 - 3443) + chr(0b1001001 + 0o46) + chr(100) + '\145')('\x75' + chr(0b1001111 + 0o45) + chr(0b1000011 + 0o43) + chr(0b101000 + 0o5) + chr(0b11000 + 0o40)):
OeWW0F1dBPRQ = jSKPaHwSAfVv.dense(OeWW0F1dBPRQ, telKTe0dti2J, activation=None, use_bias=ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x30', 40321 - 40313))
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf95\xdb\xbfj\xab\x83'), '\x64' + '\x65' + chr(0b11011 + 0o110) + chr(111) + chr(0b100000 + 0o104) + chr(101))(chr(2682 - 2565) + '\164' + chr(1335 - 1233) + chr(45) + '\070')):
OeWW0F1dBPRQ = jSKPaHwSAfVv.sru(OeWW0F1dBPRQ)
return OeWW0F1dBPRQ
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
add_position_timing_signal
|
def add_position_timing_signal(x, step, hparams):
"""Add n-dimensional embedding as the position (horizontal) timing signal.
Args:
x: a tensor with shape [batch, length, depth]
step: step
hparams: model hyper parameters
Returns:
a Tensor with the same shape as x.
"""
if not hparams.position_start_index:
index = 0
elif hparams.position_start_index == "random":
# Shift all positions randomly
# TODO(dehghani): What would be reasonable for max number of shift?
index = tf.random_uniform(
[], maxval=common_layers.shape_list(x)[1], dtype=tf.int32)
elif hparams.position_start_index == "step":
# Shift positions based on the step
if hparams.recurrence_type == "act":
num_steps = hparams.act_max_steps
else:
num_steps = hparams.num_rec_steps
index = tf.cast(
common_layers.shape_list(x)[1] * step / num_steps, dtype=tf.int32)
# No need for the timing signal in the encoder/decoder input preparation
assert hparams.pos is None
length = common_layers.shape_list(x)[1]
channels = common_layers.shape_list(x)[2]
signal = common_attention.get_timing_signal_1d(
length, channels, start_index=index)
if hparams.add_or_concat_timing_signal == "add":
x_with_timing = x + common_layers.cast_like(signal, x)
elif hparams.add_or_concat_timing_signal == "concat":
batch_size = common_layers.shape_list(x)[0]
signal_tiled = tf.tile(signal, [batch_size, 1, 1])
x_with_timing = tf.concat((x, signal_tiled), axis=-1)
return x_with_timing
|
python
|
def add_position_timing_signal(x, step, hparams):
"""Add n-dimensional embedding as the position (horizontal) timing signal.
Args:
x: a tensor with shape [batch, length, depth]
step: step
hparams: model hyper parameters
Returns:
a Tensor with the same shape as x.
"""
if not hparams.position_start_index:
index = 0
elif hparams.position_start_index == "random":
# Shift all positions randomly
# TODO(dehghani): What would be reasonable for max number of shift?
index = tf.random_uniform(
[], maxval=common_layers.shape_list(x)[1], dtype=tf.int32)
elif hparams.position_start_index == "step":
# Shift positions based on the step
if hparams.recurrence_type == "act":
num_steps = hparams.act_max_steps
else:
num_steps = hparams.num_rec_steps
index = tf.cast(
common_layers.shape_list(x)[1] * step / num_steps, dtype=tf.int32)
# No need for the timing signal in the encoder/decoder input preparation
assert hparams.pos is None
length = common_layers.shape_list(x)[1]
channels = common_layers.shape_list(x)[2]
signal = common_attention.get_timing_signal_1d(
length, channels, start_index=index)
if hparams.add_or_concat_timing_signal == "add":
x_with_timing = x + common_layers.cast_like(signal, x)
elif hparams.add_or_concat_timing_signal == "concat":
batch_size = common_layers.shape_list(x)[0]
signal_tiled = tf.tile(signal, [batch_size, 1, 1])
x_with_timing = tf.concat((x, signal_tiled), axis=-1)
return x_with_timing
|
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",",
"axis",
"=",
"-",
"1",
")",
"return",
"x_with_timing"
] |
Add n-dimensional embedding as the position (horizontal) timing signal.
Args:
x: a tensor with shape [batch, length, depth]
step: step
hparams: model hyper parameters
Returns:
a Tensor with the same shape as x.
|
[
"Add",
"n",
"-",
"dimensional",
"embedding",
"as",
"the",
"position",
"(",
"horizontal",
")",
"timing",
"signal",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L1408-L1455
|
train
|
Add n - dimensional embedding as the position timing signal.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(0b1101111 + 0o0) + '\061' + '\x32' + '\062', 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(815 - 767) + chr(617 - 506) + chr(0b110001) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + '\x36' + chr(0b10110 + 0o41), 14035 - 14027), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100111 + 0o10) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(828 - 717) + '\x33' + chr(0b1 + 0o61), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + chr(0b110110) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061' + chr(609 - 559) + '\061', 0b1000), ehT0Px3KOsy9(chr(1555 - 1507) + '\157' + chr(107 - 57) + chr(2518 - 2466) + '\062', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b101110 + 0o5) + '\065' + '\067', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b1011 + 0o50) + '\064' + chr(53), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(9360 - 9249) + '\x33' + chr(0b110111), 42591 - 42583), ehT0Px3KOsy9('\x30' + chr(0b111 + 0o150) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061' + '\066' + '\066', 0o10), ehT0Px3KOsy9('\060' + chr(2944 - 2833) + '\062' + chr(55) + chr(0b1 + 0o60), 22487 - 22479), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(0b1100 + 0o46), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b110010 + 0o75) + '\062' + chr(278 - 227) + '\065', 41165 - 41157), ehT0Px3KOsy9(chr(0b1100 + 0o44) + '\x6f' + chr(117 - 62) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000110 + 0o51) + chr(0b110010) + '\063' + chr(451 - 403), 0b1000), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(0b1101111) + chr(51) + chr(50) + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b11001 + 0o31) + chr(470 - 422) + chr(0b101111 + 0o3), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1010101 + 0o32) + chr(50) + chr(0b110100) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\x31' + '\x34' + '\065', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + '\x37' + chr(1607 - 1554), 0b1000), ehT0Px3KOsy9('\060' + chr(0b100010 + 0o115) + chr(0b101100 + 0o6) + chr(0b110010) + chr(0b1011 + 0o51), 34020 - 34012), ehT0Px3KOsy9(chr(1289 - 1241) + '\157' + chr(0b110011) + chr(0b110000 + 0o0) + chr(0b10110 + 0o41), 0b1000), ehT0Px3KOsy9(chr(48) + chr(11760 - 11649) + chr(0b101 + 0o54) + '\x35' + chr(0b100111 + 0o11), 0o10), ehT0Px3KOsy9('\x30' + chr(919 - 808) + chr(0b110101) + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(111) + chr(0b110011) + chr(0b1001 + 0o55) + chr(0b11000 + 0o34), 0b1000), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\x6f' + chr(0b110010) + chr(0b110101) + chr(779 - 729), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b111 + 0o150) + chr(51) + '\x33' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(862 - 814) + chr(111) + '\063' + chr(0b11010 + 0o35) + '\067', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b111110 + 0o61) + chr(49) + chr(1147 - 1098), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(51) + chr(0b100100 + 0o23) + chr(0b110001), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101001 + 0o6) + '\062' + chr(881 - 833) + chr(0b100111 + 0o12), 31358 - 31350), ehT0Px3KOsy9('\x30' + chr(608 - 497) + chr(175 - 125) + '\x30' + '\065', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\066' + chr(1150 - 1100), 0o10), ehT0Px3KOsy9(chr(1118 - 1070) + chr(0b1101111) + chr(0b110001) + chr(53) + chr(0b101011 + 0o6), 2505 - 2497), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(55 - 5) + '\061' + '\x34', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(0b1001000 + 0o47) + chr(0b110101) + chr(1783 - 1735), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'|'), chr(100) + '\145' + chr(0b1100011) + '\x6f' + chr(0b1100100) + '\x65')(chr(2332 - 2215) + chr(0b110100 + 0o100) + chr(4434 - 4332) + '\x2d' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def OmImHhkMEG3R(OeWW0F1dBPRQ, kDuFsAhEatcU, n4ljua2gi1Pr):
if not xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'"x~\x1ets\x1b?\xfd\x9c\x91~v\x02\xe6{\xf3Z\xfd\xad'), chr(0b1100100) + chr(0b1100101) + chr(0b1100011) + chr(0b1101111) + '\x64' + '\145')(chr(0b1101101 + 0o10) + '\164' + chr(2161 - 2059) + '\x2d' + chr(1600 - 1544))):
XdowRbJKZWL9 = ehT0Px3KOsy9('\060' + chr(4115 - 4004) + '\060', 8)
elif xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'"x~\x1ets\x1b?\xfd\x9c\x91~v\x02\xe6{\xf3Z\xfd\xad'), chr(0b100001 + 0o103) + '\145' + chr(99) + '\x6f' + chr(2545 - 2445) + '\x65')(chr(117) + chr(0b1011101 + 0o27) + chr(0b1 + 0o145) + chr(0b11 + 0o52) + chr(0b11101 + 0o33))) == xafqLlk3kkUe(SXOLrMavuUCe(b' vc\x13ow'), '\x64' + '\x65' + '\143' + chr(0b1101111) + '\x64' + chr(581 - 480))('\x75' + '\164' + chr(102) + chr(45) + '\070'):
XdowRbJKZWL9 = IDJ2eXGCBCDu.random_uniform([], maxval=jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)[ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(0b10100 + 0o133) + '\x31', 0o10)], dtype=IDJ2eXGCBCDu.int32)
elif xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'"x~\x1ets\x1b?\xfd\x9c\x91~v\x02\xe6{\xf3Z\xfd\xad'), '\x64' + chr(101) + chr(9280 - 9181) + '\157' + chr(0b10000 + 0o124) + chr(8741 - 8640))('\x75' + chr(116) + chr(4598 - 4496) + '\x2d' + '\x38')) == xafqLlk3kkUe(SXOLrMavuUCe(b'!ch\x07'), chr(3820 - 3720) + '\x65' + '\x63' + '\x6f' + chr(0b1100100) + chr(5859 - 5758))(chr(9985 - 9868) + chr(0b1110100) + chr(102) + chr(45) + chr(0b111000)):
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b' rn\x02rh\x11?\xc1\x8a\xbak}\x06\xdc'), chr(100) + chr(5267 - 5166) + chr(99) + chr(0b1001010 + 0o45) + '\x64' + '\x65')('\x75' + '\164' + chr(0b1100110) + chr(0b10110 + 0o27) + chr(0b111000))) == xafqLlk3kkUe(SXOLrMavuUCe(b'3ty'), chr(0b10001 + 0o123) + chr(101) + chr(0b1100011) + chr(0b100100 + 0o113) + chr(100) + chr(0b1100101 + 0o0))('\x75' + chr(116) + chr(102) + chr(45) + chr(0b100101 + 0o23)):
UQsgPnJC3jY0 = n4ljua2gi1Pr.act_max_steps
else:
UQsgPnJC3jY0 = n4ljua2gi1Pr.num_rec_steps
XdowRbJKZWL9 = IDJ2eXGCBCDu.cast(jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)[ehT0Px3KOsy9(chr(660 - 612) + chr(0b11000 + 0o127) + '\x31', 8)] * kDuFsAhEatcU / UQsgPnJC3jY0, dtype=IDJ2eXGCBCDu.int32)
assert xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x1cOiGak-\x1b\xc6\xdb\x89T'), chr(0b1100100) + chr(0b1100101) + chr(4255 - 4156) + chr(0b1001111 + 0o40) + chr(1864 - 1764) + '\x65')('\x75' + '\x74' + chr(102) + chr(45) + chr(1216 - 1160))) is None
CHAOgk5VCHH_ = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)[ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001), 8)]
H2MQqAZeamNo = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)[ehT0Px3KOsy9(chr(1107 - 1059) + '\x6f' + chr(50), 0b1000)]
ZDvW02DvHNUc = WOnrfm4dlYcf.get_timing_signal_1d(CHAOgk5VCHH_, H2MQqAZeamNo, start_index=XdowRbJKZWL9)
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'3si(oh+2\xcd\x81\x86~p)\xcd{\xf0W\xf6\xb2S\xf1\xcd\x02\xd3\xf5\xab'), chr(1152 - 1052) + chr(101) + chr(99) + chr(0b1101111) + chr(0b1010110 + 0o16) + '\145')('\x75' + '\x74' + chr(4850 - 4748) + chr(45) + chr(56))) == xafqLlk3kkUe(SXOLrMavuUCe(b'3si'), '\144' + chr(101) + chr(0b1100000 + 0o3) + chr(0b1101111) + '\x64' + chr(0b101010 + 0o73))(chr(12107 - 11990) + chr(792 - 676) + '\146' + chr(0b101101) + '\070'):
GsL9drPPYrKD = OeWW0F1dBPRQ + jSKPaHwSAfVv.cast_like(ZDvW02DvHNUc, OeWW0F1dBPRQ)
elif xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'3si(oh+2\xcd\x81\x86~p)\xcd{\xf0W\xf6\xb2S\xf1\xcd\x02\xd3\xf5\xab'), chr(100) + '\x65' + chr(0b1100011) + chr(7980 - 7869) + '\144' + '\x65')('\x75' + chr(451 - 335) + chr(0b1100110) + chr(0b101101) + '\x38')) == xafqLlk3kkUe(SXOLrMavuUCe(b'1xc\x14an'), '\x64' + chr(0b1110 + 0o127) + chr(5549 - 5450) + chr(0b1101111) + chr(8409 - 8309) + '\x65')(chr(0b1110101) + chr(0b1110100) + '\x66' + chr(0b101101) + chr(2214 - 2158)):
ix9dZyeAmUxY = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)[ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1062 - 1014), 8)]
ToGpUKWrm5_c = IDJ2eXGCBCDu.tile(ZDvW02DvHNUc, [ix9dZyeAmUxY, ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1101111) + chr(49), 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b100100 + 0o15), 8)])
GsL9drPPYrKD = IDJ2eXGCBCDu.concat((OeWW0F1dBPRQ, ToGpUKWrm5_c), axis=-ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001), 8))
return GsL9drPPYrKD
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/universal_transformer_util.py
|
add_step_timing_signal
|
def add_step_timing_signal(x, step, hparams):
"""Add n-dimensional embedding as the step (vertical) timing signal.
Args:
x: a tensor with shape [batch, length, depth]
step: step
hparams: model hyper parameters
Returns:
a Tensor with the same shape as x.
"""
if hparams.recurrence_type == "act":
num_steps = hparams.act_max_steps
else:
num_steps = hparams.num_rec_steps
channels = common_layers.shape_list(x)[-1]
if hparams.step_timing_signal_type == "learned":
signal = common_attention.get_layer_timing_signal_learned_1d(
channels, step, num_steps)
elif hparams.step_timing_signal_type == "sinusoid":
signal = common_attention.get_layer_timing_signal_sinusoid_1d(
channels, step, num_steps)
if hparams.add_or_concat_timing_signal == "add":
x_with_timing = x + common_layers.cast_like(signal, x)
elif hparams.add_or_concat_timing_signal == "concat":
batch_size = common_layers.shape_list(x)[0]
length = common_layers.shape_list(x)[1]
signal_tiled = tf.tile(signal, [batch_size, length, 1])
x_with_timing = tf.concat((x, signal_tiled), axis=-1)
return x_with_timing
|
python
|
def add_step_timing_signal(x, step, hparams):
"""Add n-dimensional embedding as the step (vertical) timing signal.
Args:
x: a tensor with shape [batch, length, depth]
step: step
hparams: model hyper parameters
Returns:
a Tensor with the same shape as x.
"""
if hparams.recurrence_type == "act":
num_steps = hparams.act_max_steps
else:
num_steps = hparams.num_rec_steps
channels = common_layers.shape_list(x)[-1]
if hparams.step_timing_signal_type == "learned":
signal = common_attention.get_layer_timing_signal_learned_1d(
channels, step, num_steps)
elif hparams.step_timing_signal_type == "sinusoid":
signal = common_attention.get_layer_timing_signal_sinusoid_1d(
channels, step, num_steps)
if hparams.add_or_concat_timing_signal == "add":
x_with_timing = x + common_layers.cast_like(signal, x)
elif hparams.add_or_concat_timing_signal == "concat":
batch_size = common_layers.shape_list(x)[0]
length = common_layers.shape_list(x)[1]
signal_tiled = tf.tile(signal, [batch_size, length, 1])
x_with_timing = tf.concat((x, signal_tiled), axis=-1)
return x_with_timing
|
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] |
Add n-dimensional embedding as the step (vertical) timing signal.
Args:
x: a tensor with shape [batch, length, depth]
step: step
hparams: model hyper parameters
Returns:
a Tensor with the same shape as x.
|
[
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/universal_transformer_util.py#L1458-L1493
|
train
|
Adds a n - dimensional embedding as the step ( vertical ) timing signal.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(438 - 390) + '\157' + chr(0b1111 + 0o42) + chr(0b11010 + 0o33) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\061' + chr(252 - 202) + '\x34', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b11100 + 0o26) + '\x35' + chr(1715 - 1666), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + chr(0b1000 + 0o53) + chr(557 - 507), 12765 - 12757), ehT0Px3KOsy9(chr(1383 - 1335) + chr(111) + '\062' + chr(54) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b0 + 0o63) + chr(0b101101 + 0o11) + '\065', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(689 - 638) + chr(0b10000 + 0o45) + '\x32', 59064 - 59056), ehT0Px3KOsy9(chr(1567 - 1519) + chr(111) + chr(0b110010) + chr(0b110010) + chr(0b11100 + 0o32), 25442 - 25434), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1101 + 0o44) + '\066' + chr(0b1100 + 0o46), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + '\062' + '\061', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b10000 + 0o43) + chr(52) + chr(0b111 + 0o57), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1011101 + 0o22) + chr(0b10 + 0o57) + '\x37' + chr(0b110000), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + '\x34' + chr(0b101 + 0o62), 6403 - 6395), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b1101111) + chr(54) + chr(434 - 379), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + '\063' + '\060', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b10011 + 0o40) + chr(2223 - 2174), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + '\061' + chr(0b110001 + 0o2), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + '\x32' + '\x30', 45631 - 45623), ehT0Px3KOsy9(chr(200 - 152) + chr(0b1101111) + '\x31' + '\x33' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(4035 - 3924) + chr(0b110100) + chr(1885 - 1837), 0b1000), ehT0Px3KOsy9(chr(1443 - 1395) + chr(111) + '\061' + chr(0b0 + 0o62) + chr(1561 - 1509), 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + '\060' + chr(0b101011 + 0o11), 2674 - 2666), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + '\063' + chr(336 - 283), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(1541 - 1491) + '\061' + chr(0b11101 + 0o27), 0b1000), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(0b110101 + 0o72) + chr(0b110010) + chr(51) + chr(909 - 861), ord("\x08")), ehT0Px3KOsy9(chr(1176 - 1128) + '\157' + chr(0b110011) + chr(54) + chr(54), 15306 - 15298), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + '\x34' + '\x37', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + '\062' + chr(0b100111 + 0o11), 8), ehT0Px3KOsy9('\060' + chr(0b1011 + 0o144) + chr(2247 - 2197) + chr(1031 - 980) + chr(0b100010 + 0o23), ord("\x08")), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(0b1101111) + chr(49) + chr(0b110000) + chr(1820 - 1766), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1199 - 1150) + chr(0b110001) + chr(55), 0o10), ehT0Px3KOsy9('\x30' + chr(0b111101 + 0o62) + chr(51) + chr(0b110000) + '\066', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101100 + 0o3) + '\063' + chr(0b110011), 53352 - 53344), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b11110 + 0o23) + chr(51) + chr(48), 8), ehT0Px3KOsy9('\060' + chr(12157 - 12046) + '\066' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b1011 + 0o45) + '\x6f' + chr(0b110010) + chr(2412 - 2357) + '\060', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b11 + 0o60), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1010100 + 0o33) + chr(49) + chr(0b11101 + 0o24) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + '\066' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(1543 - 1495) + chr(111) + '\062' + '\x30' + chr(948 - 896), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x35' + chr(48), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'F'), '\144' + chr(101) + chr(99) + chr(0b1000011 + 0o54) + '\144' + '\145')(chr(117) + chr(0b1100111 + 0o15) + '\146' + '\x2d' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def W3WXOJx9HFnq(OeWW0F1dBPRQ, kDuFsAhEatcU, n4ljua2gi1Pr):
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x1a1\xca\xef\xc0\x87\x8f\xf8\x11\xb4\xb9\x0c\xdeG='), '\144' + '\145' + '\143' + chr(0b1101111) + '\x64' + chr(0b1100101))(chr(0b1000110 + 0o57) + '\x74' + chr(0b1100110) + '\x2d' + chr(56))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\t7\xdd'), chr(0b1100100) + chr(5852 - 5751) + chr(0b1100011) + '\157' + chr(1918 - 1818) + chr(101))(chr(117) + chr(1384 - 1268) + '\146' + chr(0b1001 + 0o44) + '\070'):
UQsgPnJC3jY0 = n4ljua2gi1Pr.act_max_steps
else:
UQsgPnJC3jY0 = n4ljua2gi1Pr.num_rec_steps
H2MQqAZeamNo = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)[-ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(0b110000 + 0o77) + '\x31', 48700 - 48692)]
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b"\x1b \xcc\xea\xed\x81\x83\xfb\x1b\xbf\x81'\xd4^?w\xea\xbc\x01T-48"), chr(0b110101 + 0o57) + chr(0b1100101) + '\143' + chr(9903 - 9792) + chr(920 - 820) + chr(0b1100101))(chr(7781 - 7664) + chr(0b11011 + 0o131) + '\x66' + chr(1064 - 1019) + '\x38')) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x041\xc8\xe8\xdc\x90\x8e'), '\144' + '\x65' + '\x63' + '\x6f' + chr(0b1100100) + chr(4907 - 4806))(chr(8776 - 8659) + chr(116) + chr(102) + chr(1532 - 1487) + chr(0b110000 + 0o10)):
ZDvW02DvHNUc = WOnrfm4dlYcf.get_layer_timing_signal_learned_1d(H2MQqAZeamNo, kDuFsAhEatcU, UQsgPnJC3jY0)
elif xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b"\x1b \xcc\xea\xed\x81\x83\xfb\x1b\xbf\x81'\xd4^?w\xea\xbc\x01T-48"), chr(0b1100100) + chr(101) + chr(3033 - 2934) + '\157' + chr(0b1100100) + chr(101))('\x75' + chr(0b1110100) + chr(0b1100110) + '\x2d' + chr(56))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x1b=\xc7\xef\xc1\x9a\x83\xf2'), '\x64' + chr(101) + chr(1811 - 1712) + chr(111) + '\144' + '\x65')(chr(117) + '\164' + chr(8264 - 8162) + '\x2d' + chr(1340 - 1284)):
ZDvW02DvHNUc = WOnrfm4dlYcf.get_layer_timing_signal_sinusoid_1d(H2MQqAZeamNo, kDuFsAhEatcU, UQsgPnJC3jY0)
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\t0\xcd\xc5\xdd\x87\xb5\xf5\x1d\xbf\x85\x19\xd3h,p\xe6\xb90G\x0b74\xeb\xf6\x97\x8b'), chr(0b1100100) + chr(0b1100101) + chr(99) + '\x6f' + chr(0b1100100) + chr(0b1100101))(chr(117) + '\164' + chr(0b1100110) + chr(0b11101 + 0o20) + '\070')) == xafqLlk3kkUe(SXOLrMavuUCe(b'\t0\xcd'), chr(4647 - 4547) + chr(9947 - 9846) + chr(2580 - 2481) + chr(111) + chr(6983 - 6883) + '\x65')(chr(0b101101 + 0o110) + chr(0b110010 + 0o102) + chr(6563 - 6461) + chr(45) + chr(1062 - 1006)):
GsL9drPPYrKD = OeWW0F1dBPRQ + jSKPaHwSAfVv.cast_like(ZDvW02DvHNUc, OeWW0F1dBPRQ)
elif xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\t0\xcd\xc5\xdd\x87\xb5\xf5\x1d\xbf\x85\x19\xd3h,p\xe6\xb90G\x0b74\xeb\xf6\x97\x8b'), chr(0b1100100) + '\145' + chr(0b1011000 + 0o13) + chr(3267 - 3156) + chr(0b1010100 + 0o20) + chr(101))('\x75' + chr(0b10101 + 0o137) + chr(102) + '\055' + chr(0b111 + 0o61))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x0b;\xc7\xf9\xd3\x81'), chr(0b111100 + 0o50) + chr(0b1100101) + chr(0b1001111 + 0o24) + chr(0b1101111) + '\x64' + '\x65')('\165' + chr(0b110111 + 0o75) + chr(102) + '\055' + '\x38'):
ix9dZyeAmUxY = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)[ehT0Px3KOsy9('\x30' + '\x6f' + '\x30', 0b1000)]
CHAOgk5VCHH_ = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)[ehT0Px3KOsy9(chr(1351 - 1303) + chr(0b1000001 + 0o56) + chr(0b110001), 8)]
ToGpUKWrm5_c = IDJ2eXGCBCDu.tile(ZDvW02DvHNUc, [ix9dZyeAmUxY, CHAOgk5VCHH_, ehT0Px3KOsy9('\x30' + '\x6f' + chr(2311 - 2262), 8)])
GsL9drPPYrKD = IDJ2eXGCBCDu.concat((OeWW0F1dBPRQ, ToGpUKWrm5_c), axis=-ehT0Px3KOsy9('\x30' + chr(0b10 + 0o155) + chr(0b110001), 8))
return GsL9drPPYrKD
|
tensorflow/tensor2tensor
|
tensor2tensor/data_generators/wikisum/utils.py
|
wet_records_from_file_obj
|
def wet_records_from_file_obj(f, take_ownership=False):
"""Iterate through records in WET file object."""
while True:
record = WETRecord.read(f)
if record is None:
break
if not record.url:
continue
yield record
if take_ownership:
f.close()
|
python
|
def wet_records_from_file_obj(f, take_ownership=False):
"""Iterate through records in WET file object."""
while True:
record = WETRecord.read(f)
if record is None:
break
if not record.url:
continue
yield record
if take_ownership:
f.close()
|
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Iterate through records in WET file object.
|
[
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"WET",
"file",
"object",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/data_generators/wikisum/utils.py#L101-L115
|
train
|
Iterate through records in WET file object.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b11001 + 0o32) + chr(0b10 + 0o56), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + chr(0b100000 + 0o25) + '\066', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(5314 - 5203) + chr(0b10101 + 0o36) + chr(0b1101 + 0o43) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(49) + chr(50), 44623 - 44615), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(111) + chr(0b110001) + '\065' + chr(108 - 58), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + '\066' + chr(0b10000 + 0o40), 0o10), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(136 - 25) + chr(0b110011) + chr(0b110001) + chr(53), 47134 - 47126), ehT0Px3KOsy9('\060' + chr(0b1000110 + 0o51) + chr(0b10000 + 0o44) + chr(303 - 249), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(2480 - 2427) + chr(0b110000), 3994 - 3986), ehT0Px3KOsy9(chr(2302 - 2254) + chr(0b100111 + 0o110) + '\063' + chr(48) + '\x35', 45215 - 45207), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\062' + '\x35', 0o10), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(0b1000110 + 0o51) + chr(0b100001 + 0o20) + chr(0b110101) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(11580 - 11469) + chr(51) + '\061' + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b110 + 0o151) + chr(761 - 706) + '\x37', 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x33' + chr(1367 - 1313) + '\061', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + '\x36' + '\066', 28585 - 28577), ehT0Px3KOsy9(chr(0b110000) + chr(8046 - 7935) + chr(1046 - 997) + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b1100 + 0o45) + '\061', 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + '\x35' + '\062', 8), ehT0Px3KOsy9('\x30' + chr(0b1101100 + 0o3) + '\062' + '\061', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110000 + 0o1) + chr(0b110001) + chr(0b11010 + 0o26), 9920 - 9912), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + '\062' + chr(0b110000), 0o10), ehT0Px3KOsy9('\x30' + chr(5332 - 5221) + chr(0b1 + 0o62) + '\x30' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(3080 - 2969) + chr(0b110001) + chr(53) + chr(0b100010 + 0o23), 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\062' + chr(1782 - 1727) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\060' + chr(12169 - 12058) + chr(0b110010) + chr(0b110010) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(677 - 624) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\x30' + chr(9263 - 9152) + chr(0b110011) + '\x32' + chr(0b110000), 38091 - 38083), ehT0Px3KOsy9(chr(1914 - 1866) + chr(111) + chr(1323 - 1274) + chr(0b110001) + '\x30', 8), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + '\x33' + chr(50), 8209 - 8201), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061' + chr(1145 - 1092) + chr(0b11 + 0o57), 8), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(6129 - 6018) + chr(0b10110 + 0o33) + chr(49), 8), ehT0Px3KOsy9('\x30' + chr(0b111111 + 0o60) + chr(49) + '\x33' + chr(0b11011 + 0o30), 61756 - 61748), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + '\x36' + '\x35', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + chr(932 - 879) + chr(0b100011 + 0o21), 0b1000), ehT0Px3KOsy9('\060' + chr(2206 - 2095) + chr(50) + chr(0b110000) + chr(0b110100), 0o10), ehT0Px3KOsy9('\x30' + chr(0b110100 + 0o73) + '\x33' + chr(0b1110 + 0o47) + chr(2244 - 2192), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(52) + chr(0b101001 + 0o12), 0b1000), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(4720 - 4609) + chr(0b110010) + '\067', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + chr(0b11111 + 0o23) + chr(0b110010 + 0o0), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(1396 - 1348) + '\x6f' + chr(0b110101) + '\060', 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'6'), '\x64' + '\x65' + chr(0b1010 + 0o131) + chr(111) + '\144' + '\x65')(chr(5359 - 5242) + '\x74' + chr(0b1100110) + '\055' + chr(0b100111 + 0o21)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def POZ43ZcEzoJR(EGyt1xfPT1P6, bkDIsMO0Ppn0=ehT0Px3KOsy9('\060' + '\157' + chr(48), ord("\x08"))):
while ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31', 51651 - 51643):
SIWbn6wzltxD = rqmvjHLwnCYS.U6MiWrhuCi2Y(EGyt1xfPT1P6)
if SIWbn6wzltxD is None:
break
if not xafqLlk3kkUe(SIWbn6wzltxD, xafqLlk3kkUe(SXOLrMavuUCe(b'm\x9c\xad'), chr(100) + chr(0b1100101) + '\143' + chr(6356 - 6245) + chr(8552 - 8452) + chr(0b1100101))('\x75' + chr(141 - 25) + chr(0b1100110) + chr(0b1 + 0o54) + chr(961 - 905))):
continue
yield SIWbn6wzltxD
if bkDIsMO0Ppn0:
xafqLlk3kkUe(EGyt1xfPT1P6, xafqLlk3kkUe(SXOLrMavuUCe(b'{\x82\xaey\x0f'), chr(0b1100100) + '\145' + chr(8445 - 8346) + chr(0b1011011 + 0o24) + chr(5747 - 5647) + chr(8335 - 8234))(chr(0b1000 + 0o155) + chr(2315 - 2199) + '\146' + chr(45) + chr(0b101000 + 0o20)))()
|
tensorflow/tensor2tensor
|
tensor2tensor/data_generators/wikisum/utils.py
|
wet_records
|
def wet_records(wet_filepath):
"""Generate WETRecords from filepath."""
if wet_filepath.endswith('.gz'):
fopen = gzip.open
else:
fopen = tf.gfile.GFile
with fopen(wet_filepath) as f:
for record in wet_records_from_file_obj(f):
yield record
|
python
|
def wet_records(wet_filepath):
"""Generate WETRecords from filepath."""
if wet_filepath.endswith('.gz'):
fopen = gzip.open
else:
fopen = tf.gfile.GFile
with fopen(wet_filepath) as f:
for record in wet_records_from_file_obj(f):
yield record
|
[
"def",
"wet_records",
"(",
"wet_filepath",
")",
":",
"if",
"wet_filepath",
".",
"endswith",
"(",
"'.gz'",
")",
":",
"fopen",
"=",
"gzip",
".",
"open",
"else",
":",
"fopen",
"=",
"tf",
".",
"gfile",
".",
"GFile",
"with",
"fopen",
"(",
"wet_filepath",
")",
"as",
"f",
":",
"for",
"record",
"in",
"wet_records_from_file_obj",
"(",
"f",
")",
":",
"yield",
"record"
] |
Generate WETRecords from filepath.
|
[
"Generate",
"WETRecords",
"from",
"filepath",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/data_generators/wikisum/utils.py#L118-L127
|
train
|
Generate WETRecords from filepath.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b1100 + 0o47) + '\x36' + '\x36', 40114 - 40106), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101111) + chr(0b1110 + 0o46) + '\063', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(2071 - 2022) + chr(0b110111) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(1417 - 1369) + chr(111) + chr(0b110011) + chr(0b110101) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(10096 - 9985) + '\x31' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + chr(54) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + '\x36' + chr(52), 0b1000), ehT0Px3KOsy9(chr(1505 - 1457) + chr(111) + chr(51) + '\x33' + chr(627 - 574), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + '\065' + chr(0b100100 + 0o17), 2769 - 2761), ehT0Px3KOsy9(chr(48) + chr(111) + '\x34' + chr(50), 0o10), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(111) + chr(53) + '\x36', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(54) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(0b101110 + 0o101) + chr(49) + chr(0b10011 + 0o44), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10100 + 0o36) + chr(1818 - 1765), 0b1000), ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\x6f' + chr(0b11111 + 0o22) + chr(0b110111) + chr(691 - 636), ord("\x08")), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(1974 - 1863) + chr(0b10001 + 0o42) + chr(1810 - 1761) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(898 - 850) + chr(5297 - 5186) + chr(2000 - 1951) + chr(0b110001) + chr(0b1011 + 0o54), 0b1000), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(111) + chr(54) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\060' + chr(329 - 218) + '\067' + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\061' + '\060' + chr(0b11110 + 0o30), 51460 - 51452), ehT0Px3KOsy9(chr(0b110000) + chr(9293 - 9182) + '\061' + chr(0b10 + 0o65) + chr(53), 58082 - 58074), ehT0Px3KOsy9('\060' + '\157' + chr(0b100000 + 0o24) + chr(0b101110 + 0o5), 8), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(12263 - 12152) + chr(0b10111 + 0o40) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(5733 - 5622) + chr(1701 - 1651) + chr(1943 - 1895), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b100111 + 0o110) + chr(2560 - 2509) + chr(55) + chr(1013 - 964), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(0b110111) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(0b1101111) + '\062' + chr(0b110000) + chr(0b10010 + 0o40), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b110111 + 0o70) + chr(0b11101 + 0o26) + chr(51) + '\060', 0b1000), ehT0Px3KOsy9(chr(1077 - 1029) + chr(0b1101100 + 0o3) + '\066' + chr(1700 - 1651), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + '\x32' + chr(558 - 505), 0o10), ehT0Px3KOsy9(chr(1302 - 1254) + '\x6f' + chr(0b10001 + 0o42) + '\x34' + chr(48), 0b1000), ehT0Px3KOsy9(chr(48) + chr(5356 - 5245) + chr(0b110011) + chr(2320 - 2268) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1001111 + 0o40) + chr(2064 - 2013) + '\x32' + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + '\063' + chr(158 - 108), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011) + chr(383 - 329) + chr(52), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b101101 + 0o4) + chr(0b101011 + 0o7) + chr(49), 0o10), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b1001101 + 0o42) + chr(0b101011 + 0o10) + chr(1306 - 1257) + chr(2478 - 2427), ord("\x08")), ehT0Px3KOsy9(chr(1518 - 1470) + '\x6f' + chr(0b1101 + 0o44) + '\x37' + chr(0b11100 + 0o32), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + chr(704 - 649) + chr(0b110100), 8), ehT0Px3KOsy9('\x30' + '\157' + chr(0b1010 + 0o47), 19920 - 19912)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + '\x6f' + chr(53) + chr(0b11011 + 0o25), 7131 - 7123)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd8'), chr(0b101011 + 0o71) + chr(101) + chr(0b1100011) + chr(0b1101111) + chr(100) + chr(7273 - 7172))(chr(117) + '\x74' + chr(0b1100110) + '\x2d' + chr(0b11111 + 0o31)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def eR17SWf8jTix(r0P33gIutBM5):
if xafqLlk3kkUe(r0P33gIutBM5, xafqLlk3kkUe(SXOLrMavuUCe(b'\x93M\x1e\x9cz\xdb\xc0\xb5'), chr(0b1001000 + 0o34) + chr(0b101000 + 0o75) + chr(4916 - 4817) + '\157' + chr(3773 - 3673) + chr(101))(chr(117) + chr(0b1110100) + '\146' + chr(45) + chr(0b10000 + 0o50)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xd8D\x00'), '\x64' + chr(101) + chr(0b1100011) + '\x6f' + '\x64' + chr(0b1100101))('\165' + chr(116) + '\146' + chr(45) + chr(56))):
aPfXNVMhLl76 = Sl9BQg7umixy.open
else:
aPfXNVMhLl76 = IDJ2eXGCBCDu.gfile.GFile
with aPfXNVMhLl76(r0P33gIutBM5) as EGyt1xfPT1P6:
for SIWbn6wzltxD in POZ43ZcEzoJR(EGyt1xfPT1P6):
yield SIWbn6wzltxD
|
tensorflow/tensor2tensor
|
tensor2tensor/data_generators/wikisum/utils.py
|
filter_paragraph
|
def filter_paragraph(p):
"""Simple filter to remove obviously bad paragraphs (bad text extraction).
Note this needs to run very quickly as it is applied to every paragraph
in the corpus, so nothing fancy! This whole method should be linear
expected time in len(p).
Args:
p: string, paragraph
Returns:
True if we should remove the paragraph.
"""
# Expect a minimum number of words.
tokens = p.split()
if len(tokens) < 6:
return True
# Require some letters.
if not re.search(_SOME_ALPHA_RE, p):
return True
# Keep this one at the end, probably the most complicated logic.
# We try to detect sentences, which should have a minimum of 3 tokens
# with only alphabetic characters.
last = 0
found_sentence = False
num_alpha = 0
for i, x in enumerate(tokens):
if x == '.':
if i - last > 3 and num_alpha >= 3:
found_sentence = True
break
last = i
num_alpha = 0
if re.match(_ONLY_ALPHA_RE, x):
num_alpha += 1
if not found_sentence:
return True
return False
|
python
|
def filter_paragraph(p):
"""Simple filter to remove obviously bad paragraphs (bad text extraction).
Note this needs to run very quickly as it is applied to every paragraph
in the corpus, so nothing fancy! This whole method should be linear
expected time in len(p).
Args:
p: string, paragraph
Returns:
True if we should remove the paragraph.
"""
# Expect a minimum number of words.
tokens = p.split()
if len(tokens) < 6:
return True
# Require some letters.
if not re.search(_SOME_ALPHA_RE, p):
return True
# Keep this one at the end, probably the most complicated logic.
# We try to detect sentences, which should have a minimum of 3 tokens
# with only alphabetic characters.
last = 0
found_sentence = False
num_alpha = 0
for i, x in enumerate(tokens):
if x == '.':
if i - last > 3 and num_alpha >= 3:
found_sentence = True
break
last = i
num_alpha = 0
if re.match(_ONLY_ALPHA_RE, x):
num_alpha += 1
if not found_sentence:
return True
return False
|
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"_SOME_ALPHA_RE",
",",
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"return",
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"# Keep this one at the end, probably the most complicated logic.",
"# We try to detect sentences, which should have a minimum of 3 tokens",
"# with only alphabetic characters.",
"last",
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"0",
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"_ONLY_ALPHA_RE",
",",
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":",
"num_alpha",
"+=",
"1",
"if",
"not",
"found_sentence",
":",
"return",
"True",
"return",
"False"
] |
Simple filter to remove obviously bad paragraphs (bad text extraction).
Note this needs to run very quickly as it is applied to every paragraph
in the corpus, so nothing fancy! This whole method should be linear
expected time in len(p).
Args:
p: string, paragraph
Returns:
True if we should remove the paragraph.
|
[
"Simple",
"filter",
"to",
"remove",
"obviously",
"bad",
"paragraphs",
"(",
"bad",
"text",
"extraction",
")",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/data_generators/wikisum/utils.py#L214-L254
|
train
|
Simple filter to remove obviously bad paragraphs.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(250 - 202) + chr(111) + chr(0b101010 + 0o10) + '\061' + '\061', 0o10), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(111) + chr(2159 - 2109) + chr(51) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(2174 - 2126) + '\x6f' + '\x31' + chr(2696 - 2644) + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(9403 - 9292) + chr(0b110001) + chr(0b10100 + 0o43) + chr(987 - 935), 35694 - 35686), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + chr(0b11 + 0o57) + chr(0b10110 + 0o37), 19282 - 19274), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31' + chr(53) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(333 - 285) + chr(2491 - 2380) + '\x31' + chr(688 - 634) + chr(1440 - 1392), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(238 - 127) + '\x33' + chr(0b110000) + chr(67 - 17), 11580 - 11572), ehT0Px3KOsy9(chr(1286 - 1238) + chr(2204 - 2093) + chr(50) + chr(0b1001 + 0o54) + chr(50), 4353 - 4345), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000011 + 0o54) + chr(1253 - 1204) + chr(0b110111) + chr(1553 - 1505), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110111) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(824 - 774) + chr(54), 50503 - 50495), ehT0Px3KOsy9(chr(1186 - 1138) + chr(0b1101111) + chr(0b110001) + '\066', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061' + '\x30' + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + chr(0b101111 + 0o7) + '\064', 0b1000), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b1101111) + '\x31' + '\064' + chr(1008 - 960), 10927 - 10919), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b1101111) + chr(1859 - 1810) + '\x36' + chr(1363 - 1311), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + chr(0b1011 + 0o51) + '\x32', 54849 - 54841), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + '\060' + chr(928 - 873), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b100111 + 0o16) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + chr(0b110100) + '\061', 44349 - 44341), ehT0Px3KOsy9('\x30' + chr(453 - 342) + chr(1413 - 1364) + '\061' + chr(48), 31203 - 31195), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1010 + 0o50) + chr(0b110001) + '\061', 8), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b1101111) + '\063' + chr(52) + chr(0b11101 + 0o27), 0o10), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\157' + '\x32' + '\x30' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101111) + chr(0b110010) + chr(48), 62274 - 62266), ehT0Px3KOsy9('\060' + '\157' + '\061' + '\x35' + '\x35', 55444 - 55436), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + chr(1200 - 1151) + chr(2303 - 2251), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(6203 - 6092) + '\066' + chr(0b110001), 25101 - 25093), ehT0Px3KOsy9('\x30' + chr(0b1011001 + 0o26) + chr(428 - 379) + chr(55) + chr(0b11111 + 0o21), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(749 - 699) + chr(0b111 + 0o53) + chr(0b1001 + 0o50), 0o10), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\x6f' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b10111 + 0o130) + chr(0b11010 + 0o31) + chr(0b101001 + 0o11), 26513 - 26505), ehT0Px3KOsy9(chr(48) + chr(0b1101010 + 0o5) + chr(325 - 274) + chr(52), 26857 - 26849), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(2212 - 2160) + chr(0b110010), 0b1000), ehT0Px3KOsy9('\x30' + chr(6782 - 6671) + '\062' + chr(55) + '\062', 0o10), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b1100101 + 0o12) + chr(1055 - 1006) + chr(0b110110) + chr(49), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1100000 + 0o17) + '\062' + chr(0b100101 + 0o16) + chr(2439 - 2387), 0b1000), ehT0Px3KOsy9('\x30' + chr(679 - 568) + chr(0b101001 + 0o12) + chr(54) + chr(53), 1851 - 1843), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + chr(0b101001 + 0o11) + '\x33', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110101) + chr(0b110 + 0o52), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xa7'), chr(2617 - 2517) + '\x65' + '\143' + '\157' + chr(100) + chr(3070 - 2969))(chr(0b1110101) + chr(0b1011101 + 0o27) + chr(102) + chr(0b101101) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def s2rXJw_HOBNv(UyakMW2IMFEj):
Sz7tXxaCGqJ1 = UyakMW2IMFEj.split()
if c2A0yzQpDQB3(Sz7tXxaCGqJ1) < ehT0Px3KOsy9(chr(2094 - 2046) + '\157' + chr(0b110110), 0b1000):
return ehT0Px3KOsy9(chr(1676 - 1628) + chr(0b110 + 0o151) + '\061', ord("\x08"))
if not xafqLlk3kkUe(_7u55U49WwX2, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfa\xfb\x04\x0e6\x02'), chr(0b10101 + 0o117) + chr(9724 - 9623) + '\x63' + '\x6f' + chr(9603 - 9503) + chr(9435 - 9334))(chr(0b1110101) + '\164' + chr(0b1100110) + chr(1828 - 1783) + '\070'))(yxd832aSFC9T, UyakMW2IMFEj):
return ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(49), 8)
Z6Ub1MQPX1kA = ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\x6f' + chr(1954 - 1906), 8)
ALmPsCUAbB5E = ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110 + 0o52), 8)
gE69P5OivSkz = ehT0Px3KOsy9(chr(1478 - 1430) + chr(111) + chr(0b110000), 8)
for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(Sz7tXxaCGqJ1):
if OeWW0F1dBPRQ == xafqLlk3kkUe(SXOLrMavuUCe(b'\xa7'), chr(100) + '\145' + chr(0b100 + 0o137) + chr(0b1101100 + 0o3) + chr(100) + chr(0b1100101))(chr(0b110 + 0o157) + chr(0b1001001 + 0o53) + chr(9624 - 9522) + chr(0b101101) + chr(1405 - 1349)):
if WVxHKyX45z_L - Z6Ub1MQPX1kA > ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(6219 - 6108) + chr(51), 0o10) and gE69P5OivSkz >= ehT0Px3KOsy9(chr(1905 - 1857) + chr(3359 - 3248) + '\x33', 8):
ALmPsCUAbB5E = ehT0Px3KOsy9(chr(1507 - 1459) + chr(111) + chr(689 - 640), 8)
break
Z6Ub1MQPX1kA = WVxHKyX45z_L
gE69P5OivSkz = ehT0Px3KOsy9(chr(1795 - 1747) + chr(0b11011 + 0o124) + chr(48), 8)
if xafqLlk3kkUe(_7u55U49WwX2, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe4\xff\x11\x1f='), chr(0b1100 + 0o130) + '\x65' + chr(0b1100011) + chr(0b1101111) + chr(100) + '\x65')('\165' + '\164' + '\x66' + chr(45) + chr(0b111000)))(KrV5KOC3C4X3, OeWW0F1dBPRQ):
gE69P5OivSkz += ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061', 8)
if not ALmPsCUAbB5E:
return ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\x6f' + chr(49), 8)
return ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1111 + 0o41), 8)
|
tensorflow/tensor2tensor
|
tensor2tensor/data_generators/wikisum/utils.py
|
timing
|
def timing(name=''):
"""Log start, end, and duration."""
start = datetime.datetime.now()
timestamp = start.strftime('%H:%M')
tf.logging.info('Starting job [%s] at %s', name, timestamp)
yield
end = datetime.datetime.now()
timestamp = end.strftime('%H:%M')
tf.logging.info('Finished job [%s] at %s', name, timestamp)
duration = end - start
duration_mins = duration.total_seconds() / 60
tf.logging.info('Total time [%s] (m): %d', name, int(duration_mins))
|
python
|
def timing(name=''):
"""Log start, end, and duration."""
start = datetime.datetime.now()
timestamp = start.strftime('%H:%M')
tf.logging.info('Starting job [%s] at %s', name, timestamp)
yield
end = datetime.datetime.now()
timestamp = end.strftime('%H:%M')
tf.logging.info('Finished job [%s] at %s', name, timestamp)
duration = end - start
duration_mins = duration.total_seconds() / 60
tf.logging.info('Total time [%s] (m): %d', name, int(duration_mins))
|
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",",
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")",
")"
] |
Log start, end, and duration.
|
[
"Log",
"start",
"end",
"and",
"duration",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/data_generators/wikisum/utils.py#L258-L269
|
train
|
Log start end and duration.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(8656 - 8545) + '\063' + chr(0b100010 + 0o21) + '\067', 42685 - 42677), ehT0Px3KOsy9(chr(0b110000) + chr(0b101 + 0o152) + '\x34' + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + '\x37' + chr(54), 0o10), ehT0Px3KOsy9('\060' + chr(6142 - 6031) + '\061' + '\061', 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x31' + '\060' + '\065', 21531 - 21523), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + '\x33', 5528 - 5520), ehT0Px3KOsy9(chr(0b110000) + chr(11633 - 11522) + '\x33' + chr(51) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + '\067' + chr(1698 - 1650), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + chr(452 - 397) + '\065', 0o10), ehT0Px3KOsy9(chr(2298 - 2250) + '\x6f' + chr(0b110010) + chr(48) + '\061', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + chr(49) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(8387 - 8276) + '\065' + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b110100 + 0o73) + chr(54), 0o10), ehT0Px3KOsy9('\060' + chr(0b100100 + 0o113) + chr(49) + chr(0b100110 + 0o21) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(552 - 504) + chr(1924 - 1813) + '\061' + '\067' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32' + chr(0b1100 + 0o47) + '\x33', 0b1000), ehT0Px3KOsy9(chr(1005 - 957) + chr(111) + chr(1251 - 1202) + chr(51) + chr(0b100010 + 0o24), ord("\x08")), ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\x6f' + '\061' + chr(1409 - 1359), 61493 - 61485), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(54) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(2264 - 2216) + chr(0b1101111) + chr(51) + chr(0b1100 + 0o51) + '\067', 17926 - 17918), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(1757 - 1705) + chr(1998 - 1947), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + chr(55) + chr(0b11110 + 0o31), 8), ehT0Px3KOsy9(chr(1891 - 1843) + chr(9927 - 9816) + chr(0b110011) + '\x34' + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x31' + chr(0b110001) + chr(51), 0b1000), ehT0Px3KOsy9(chr(1093 - 1045) + chr(0b100000 + 0o117) + chr(445 - 396) + chr(0b110110) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(49) + '\x35', 13921 - 13913), ehT0Px3KOsy9(chr(48) + chr(0b1010100 + 0o33) + chr(49) + '\x33' + chr(0b110010 + 0o4), 8), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(111) + chr(0b10111 + 0o33) + chr(52) + '\067', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + chr(459 - 405) + chr(0b110011), 4904 - 4896), ehT0Px3KOsy9(chr(595 - 547) + '\157' + chr(0b10111 + 0o33) + '\066' + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(1554 - 1506) + '\157' + '\062' + '\060' + chr(0b110100), 12204 - 12196), ehT0Px3KOsy9('\x30' + chr(8729 - 8618) + chr(0b11000 + 0o31) + '\x36', 0o10), ehT0Px3KOsy9(chr(2130 - 2082) + chr(11515 - 11404) + chr(0b110001) + '\x33' + '\x36', 8), ehT0Px3KOsy9('\x30' + '\157' + '\063' + chr(667 - 616) + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(5884 - 5773) + chr(610 - 559) + chr(0b110101) + '\x30', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000000 + 0o57) + chr(0b1010 + 0o46), 36503 - 36495), ehT0Px3KOsy9('\060' + chr(11248 - 11137) + chr(51) + chr(54) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + '\x6f' + chr(50) + '\067' + chr(0b110000), 8), ehT0Px3KOsy9(chr(48) + '\157' + chr(530 - 475) + chr(575 - 521), 40020 - 40012), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(567 - 517) + chr(2567 - 2513), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1101111) + '\065' + chr(0b110000), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf1'), chr(0b1011110 + 0o6) + '\145' + '\x63' + chr(3530 - 3419) + chr(0b1100100) + chr(0b1100101))(chr(2952 - 2835) + chr(0b1110100) + chr(1528 - 1426) + chr(45) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def PNtjUKZX1RB0(AIvJRzLdDfgF=xafqLlk3kkUe(SXOLrMavuUCe(b''), chr(0b111000 + 0o54) + chr(0b1100100 + 0o1) + chr(99) + '\157' + chr(100) + chr(7809 - 7708))(chr(0b11010 + 0o133) + '\x74' + chr(102) + chr(0b101101) + '\x38')):
avRbFsnfJxQj = zKdiQFzuryNR.datetime.now()
SgRbwnqVfFz7 = avRbFsnfJxQj.strftime(xafqLlk3kkUe(SXOLrMavuUCe(b'\xfao\xc4,\x08'), chr(1555 - 1455) + chr(0b1100101) + chr(0b1100011) + chr(111) + chr(0b1100100) + chr(3698 - 3597))(chr(0b1110101) + '\164' + chr(102) + chr(0b101101) + chr(619 - 563)))
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c\x10\xb6q0p\xbe\x8f\x97\xed\xd0@'), chr(0b1100100) + chr(0b110000 + 0o65) + '\143' + chr(715 - 604) + '\144' + '\145')('\x75' + '\164' + chr(4999 - 4897) + '\055' + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x8cS\x9f{1z\xb7\xdf\xdd\xeb\xe5I&"Z\xe8\x03*\x17\x9b\x03Z\x93'), chr(0b110110 + 0o56) + chr(0b1100101) + chr(99) + chr(0b1101111) + '\144' + chr(5141 - 5040))('\165' + '\x74' + chr(0b101110 + 0o70) + '\x2d' + chr(0b111000)), AIvJRzLdDfgF, SgRbwnqVfFz7)
yield
whWDZq5_lP01 = zKdiQFzuryNR.datetime.now()
SgRbwnqVfFz7 = whWDZq5_lP01.strftime(xafqLlk3kkUe(SXOLrMavuUCe(b'\xfao\xc4,\x08'), chr(0b1100100) + chr(101) + '\143' + '\157' + chr(0b1010101 + 0o17) + '\x65')('\165' + chr(0b110101 + 0o77) + chr(0b10110 + 0o120) + chr(0b101101) + chr(0b11010 + 0o36)))
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c\x10\xb6q0p\xbe\x8f\x97\xed\xd0@'), chr(0b110011 + 0o61) + chr(0b1100101) + chr(0b1100011) + '\x6f' + '\x64' + chr(101))(chr(117) + '\164' + chr(0b1100110) + chr(1680 - 1635) + chr(386 - 330)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x99N\x90`6{\xbc\xdc\xdd\xeb\xe5I&"Z\xe8\x03*\x17\x9b\x03Z\x93'), chr(0b1010110 + 0o16) + chr(0b10100 + 0o121) + '\x63' + '\x6f' + chr(0b1100100) + '\145')(chr(5996 - 5879) + chr(0b1110100) + '\x66' + chr(0b101011 + 0o2) + chr(0b111000)), AIvJRzLdDfgF, SgRbwnqVfFz7)
AW3Z20f3DKFA = whWDZq5_lP01 - avRbFsnfJxQj
enkGjPU3mPOc = AW3Z20f3DKFA.total_seconds() / ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1877 - 1822) + chr(0b110100), 0b1000)
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c\x10\xb6q0p\xbe\x8f\x97\xed\xd0@'), chr(0b1100100) + chr(0b10000 + 0o125) + chr(0b110010 + 0o61) + chr(0b1101111) + '\144' + '\x65')(chr(117) + chr(0b1110100) + chr(102) + chr(0b101101) + chr(2871 - 2815)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x8bH\x8ah)3\xad\xd1\x90\xe4\xaap#\n"\xbbvg_\xd5\x03Z\x84'), chr(0b1011111 + 0o5) + '\x65' + chr(99) + chr(5631 - 5520) + '\x64' + chr(0b1111 + 0o126))(chr(0b1000010 + 0o63) + '\x74' + chr(2471 - 2369) + chr(45) + '\070'), AIvJRzLdDfgF, ehT0Px3KOsy9(enkGjPU3mPOc))
|
tensorflow/tensor2tensor
|
tensor2tensor/data_generators/wikisum/utils.py
|
WETHeader.read
|
def read(cls, f):
"""Read header from file. Headers end with length and then 1 blank line."""
url = None
line = f.readline()
if not line:
# EOF
return None
while not line.startswith(cls.LENGTH_HEADER):
if line.startswith(cls.URI_HEADER):
url = line[len(cls.URI_HEADER):].strip()
line = f.readline()
# Consume empty separator
f.readline()
# Read content
length = int(line.split(':')[1])
return cls(url, length)
|
python
|
def read(cls, f):
"""Read header from file. Headers end with length and then 1 blank line."""
url = None
line = f.readline()
if not line:
# EOF
return None
while not line.startswith(cls.LENGTH_HEADER):
if line.startswith(cls.URI_HEADER):
url = line[len(cls.URI_HEADER):].strip()
line = f.readline()
# Consume empty separator
f.readline()
# Read content
length = int(line.split(':')[1])
return cls(url, length)
|
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] |
Read header from file. Headers end with length and then 1 blank line.
|
[
"Read",
"header",
"from",
"file",
".",
"Headers",
"end",
"with",
"length",
"and",
"then",
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"blank",
"line",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/data_generators/wikisum/utils.py#L61-L80
|
train
|
Read header from file. Headers end with length and then 1 blank line.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(111) + '\061' + chr(49) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2519 - 2468) + '\x36' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2706 - 2652) + '\x35', 0o10), ehT0Px3KOsy9(chr(1703 - 1655) + chr(0b100010 + 0o115) + chr(0b110010) + chr(0b10100 + 0o35) + chr(51), 0o10), ehT0Px3KOsy9('\x30' + chr(10442 - 10331) + chr(0b11110 + 0o23) + chr(55) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\x6f' + '\x31' + '\x37' + chr(0b10001 + 0o42), 5009 - 5001), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(10191 - 10080) + chr(393 - 343) + '\064' + '\060', 0o10), ehT0Px3KOsy9('\x30' + chr(312 - 201) + '\062' + '\066', 0o10), ehT0Px3KOsy9(chr(0b110 + 0o52) + '\157' + chr(551 - 500) + chr(498 - 445) + chr(1999 - 1945), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10111 + 0o34) + chr(67 - 13) + chr(0b10101 + 0o41), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100 + 0o61) + chr(53), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2034 - 1985) + chr(743 - 695) + chr(0b110100), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\061' + chr(1679 - 1630) + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(9826 - 9715) + '\x33' + '\060' + chr(675 - 627), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(51) + chr(51) + chr(0b101011 + 0o7), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b111011 + 0o64) + chr(0b110010) + chr(0b1100 + 0o53) + chr(1768 - 1719), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(49) + chr(0b110111) + '\x37', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\x32' + '\x32', 58084 - 58076), ehT0Px3KOsy9('\060' + chr(10212 - 10101) + '\x34' + chr(465 - 414), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + '\061' + '\065', 0b1000), ehT0Px3KOsy9(chr(48) + chr(12244 - 12133) + '\061' + '\060' + chr(0b10111 + 0o34), 0o10), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(11390 - 11279) + chr(0b110001) + '\x36' + chr(1646 - 1592), 0b1000), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b1101111) + chr(184 - 133) + chr(833 - 781), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(0b101111 + 0o7) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b1 + 0o57) + '\157' + chr(50) + '\x35' + '\x35', 0o10), ehT0Px3KOsy9(chr(926 - 878) + chr(0b1011011 + 0o24) + chr(1225 - 1175) + chr(0b110100 + 0o3) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100100 + 0o20) + chr(0b100011 + 0o22), 0o10), ehT0Px3KOsy9(chr(0b100 + 0o54) + '\157' + '\x32' + chr(53) + chr(0b100101 + 0o21), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111 + 0o0) + '\062' + chr(0b1100 + 0o44) + '\x36', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1257 - 1203), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + '\x36' + '\060', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51) + '\060' + chr(54), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + '\065' + chr(2304 - 2251), 0o10), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\157' + chr(51) + chr(0b11 + 0o61) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(622 - 574) + '\x6f' + chr(1060 - 1007) + '\063', 38317 - 38309), ehT0Px3KOsy9(chr(1587 - 1539) + '\x6f' + '\x33' + chr(49), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\063' + chr(0b110011) + '\064', 0b1000), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(5298 - 5187) + '\063' + chr(55) + chr(901 - 852), 41239 - 41231), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + chr(0b110000) + '\x34', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(2568 - 2457) + chr(49) + chr(51), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(111) + chr(0b110101) + '\x30', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'd'), chr(4030 - 3930) + chr(2997 - 2896) + '\143' + chr(0b110110 + 0o71) + '\x64' + '\145')(chr(117) + chr(10968 - 10852) + chr(0b1100110) + '\x2d' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def U6MiWrhuCi2Y(NSstowUUZlxS, EGyt1xfPT1P6):
CYCr3xzMHl4K = None
LycYkDpyelF6 = EGyt1xfPT1P6.readline()
if not LycYkDpyelF6:
return None
while not xafqLlk3kkUe(LycYkDpyelF6, xafqLlk3kkUe(SXOLrMavuUCe(b'9\x86T\xf9\n\x08\xd7\x7f\x9a\x9e'), '\144' + '\145' + chr(318 - 219) + chr(0b1101111) + chr(100) + '\x65')('\165' + chr(0b11000 + 0o134) + chr(0b1100000 + 0o6) + chr(45) + chr(179 - 123)))(xafqLlk3kkUe(NSstowUUZlxS, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb7{\xcc*3\xff^\xab\xb7i\x01\x1c'), '\x64' + chr(101) + chr(99) + chr(111) + chr(0b110111 + 0o55) + chr(0b1001100 + 0o31))('\x75' + chr(116) + '\x66' + '\x2d' + '\070'))):
if xafqLlk3kkUe(LycYkDpyelF6, xafqLlk3kkUe(SXOLrMavuUCe(b'9\x86T\xf9\n\x08\xd7\x7f\x9a\x9e'), '\144' + chr(0b1100101) + chr(0b1100011) + chr(0b1101111) + chr(100) + chr(10147 - 10046))(chr(117) + chr(0b110100 + 0o100) + chr(102) + chr(508 - 463) + chr(0b1011 + 0o55)))(xafqLlk3kkUe(NSstowUUZlxS, xafqLlk3kkUe(SXOLrMavuUCe(b'\x1f\xa0|\xd46>\xe1R\xab\xa4'), chr(0b1100100) + chr(101) + chr(130 - 31) + chr(0b1101111) + chr(0b1100011 + 0o1) + chr(2980 - 2879))('\x75' + '\164' + chr(0b10011 + 0o123) + '\x2d' + '\x38'))):
CYCr3xzMHl4K = LycYkDpyelF6[c2A0yzQpDQB3(NSstowUUZlxS.URI_HEADER):].strip()
LycYkDpyelF6 = EGyt1xfPT1P6.readline()
xafqLlk3kkUe(EGyt1xfPT1P6, xafqLlk3kkUe(SXOLrMavuUCe(b'8\x97T\xef\x12\x12\xces'), chr(0b1100100) + chr(0b1100101) + '\143' + chr(0b1000 + 0o147) + chr(100) + chr(0b1100101))('\x75' + chr(116) + '\146' + chr(2025 - 1980) + '\x38'))()
CHAOgk5VCHH_ = ehT0Px3KOsy9(LycYkDpyelF6.split(xafqLlk3kkUe(SXOLrMavuUCe(b'p'), chr(0b1100100) + chr(6631 - 6530) + chr(0b1100011) + chr(0b10111 + 0o130) + chr(8932 - 8832) + chr(3443 - 3342))(chr(117) + chr(0b1010 + 0o152) + chr(8399 - 8297) + '\055' + chr(0b111000)))[ehT0Px3KOsy9(chr(48) + chr(4041 - 3930) + chr(874 - 825), 20841 - 20833)])
return NSstowUUZlxS(CYCr3xzMHl4K, CHAOgk5VCHH_)
|
tensorflow/tensor2tensor
|
tensor2tensor/data_generators/wikisum/utils.py
|
WETRecord.read
|
def read(cls, f):
"""Read WETRecord from file. Records end with 2 blank lines."""
header = WETHeader.read(f)
if header is None:
# EOF
return None
content = f.read(header.length)
# Consume empty separators
f.readline()
f.readline()
return cls(header.url, content)
|
python
|
def read(cls, f):
"""Read WETRecord from file. Records end with 2 blank lines."""
header = WETHeader.read(f)
if header is None:
# EOF
return None
content = f.read(header.length)
# Consume empty separators
f.readline()
f.readline()
return cls(header.url, content)
|
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"(",
")",
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"readline",
"(",
")",
"return",
"cls",
"(",
"header",
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"url",
",",
"content",
")"
] |
Read WETRecord from file. Records end with 2 blank lines.
|
[
"Read",
"WETRecord",
"from",
"file",
".",
"Records",
"end",
"with",
"2",
"blank",
"lines",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/data_generators/wikisum/utils.py#L86-L98
|
train
|
Read WETRecord from file.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\157' + '\x32' + chr(2148 - 2093) + chr(55), 0o10), ehT0Px3KOsy9(chr(1908 - 1860) + chr(0b1010101 + 0o32) + chr(0b110011) + chr(0b110000) + '\064', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101101 + 0o2) + chr(49) + chr(0b110010) + chr(52), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(6645 - 6534) + '\062' + chr(142 - 91), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b111110 + 0o61) + chr(0b101101 + 0o4) + '\x31' + chr(105 - 54), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b111 + 0o150) + '\066' + '\x30', 0o10), ehT0Px3KOsy9(chr(396 - 348) + chr(0b10110 + 0o131) + '\063' + chr(0b110100) + '\x35', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100011 + 0o14) + chr(0b110001) + chr(48) + '\064', 24869 - 24861), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(0b101010 + 0o10) + chr(857 - 809), 53948 - 53940), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(51) + '\x30', 50180 - 50172), ehT0Px3KOsy9(chr(0b110000) + chr(0b10001 + 0o136) + chr(0b110001) + chr(0b110000) + chr(50), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + chr(49) + chr(785 - 731), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(1275 - 1225) + '\067' + chr(2371 - 2317), ord("\x08")), ehT0Px3KOsy9(chr(172 - 124) + '\x6f' + chr(671 - 620) + chr(0b11101 + 0o24) + chr(0b101100 + 0o4), 0o10), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(111) + chr(51) + chr(0b10001 + 0o40) + chr(54), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061' + chr(0b110001 + 0o0), 31236 - 31228), ehT0Px3KOsy9(chr(166 - 118) + '\x6f' + chr(51) + chr(0b10100 + 0o34) + chr(0b10110 + 0o36), 8), ehT0Px3KOsy9(chr(1817 - 1769) + chr(0b101100 + 0o103) + '\063' + chr(0b1111 + 0o46) + chr(55), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + chr(0b10111 + 0o34) + chr(1500 - 1446), 37241 - 37233), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(49) + chr(443 - 388) + chr(316 - 265), 27383 - 27375), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + '\067' + chr(1030 - 976), 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(50) + chr(0b101110 + 0o6) + '\066', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(1752 - 1701) + chr(0b10101 + 0o40) + '\x31', 52435 - 52427), ehT0Px3KOsy9(chr(1228 - 1180) + chr(111) + chr(50) + chr(0b110100) + chr(201 - 146), 0o10), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b1001111 + 0o40) + '\x31' + chr(50) + chr(0b110100), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49) + chr(0b110010) + '\061', 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\061' + chr(0b110001) + chr(1891 - 1840), 8), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(8921 - 8810) + '\x32' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\x6f' + '\x33' + chr(54) + chr(0b1110 + 0o42), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b100000 + 0o21) + chr(0b110111) + chr(828 - 777), 8), ehT0Px3KOsy9('\060' + chr(8569 - 8458) + chr(0b11000 + 0o33) + '\x32' + '\063', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011) + chr(0b110000) + chr(2229 - 2179), 0o10), ehT0Px3KOsy9('\060' + chr(0b1011000 + 0o27) + chr(49) + '\x33' + chr(0b110101), 34424 - 34416), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\062' + chr(482 - 433) + chr(0b100011 + 0o23), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(49) + chr(54) + chr(0b111 + 0o53), ord("\x08")), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(111) + chr(51) + chr(1758 - 1707) + chr(51), 12501 - 12493), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011110 + 0o21) + chr(0b10000 + 0o41) + '\067' + '\x37', 41090 - 41082), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110010) + '\060' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + '\061' + '\062', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(1637 - 1586) + chr(50) + chr(1853 - 1798), 54781 - 54773)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(3765 - 3654) + chr(1845 - 1792) + '\x30', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x91'), '\144' + '\x65' + '\143' + chr(0b100001 + 0o116) + chr(100) + chr(0b1000000 + 0o45))(chr(0b100010 + 0o123) + '\164' + '\x66' + chr(0b111 + 0o46) + chr(2558 - 2502)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def U6MiWrhuCi2Y(NSstowUUZlxS, EGyt1xfPT1P6):
ZmHK8Erhdn3m = A1Jlm2jaVVSG.U6MiWrhuCi2Y(EGyt1xfPT1P6)
if ZmHK8Erhdn3m is None:
return None
VjgGQlDzfDa9 = EGyt1xfPT1P6.U6MiWrhuCi2Y(ZmHK8Erhdn3m.length)
xafqLlk3kkUe(EGyt1xfPT1P6, xafqLlk3kkUe(SXOLrMavuUCe(b"\xcd\xa15w'Y\x8b!"), '\144' + chr(101) + chr(0b100 + 0o137) + '\157' + chr(3881 - 3781) + chr(6838 - 6737))(chr(117) + chr(116) + chr(0b1010000 + 0o26) + '\x2d' + chr(0b111000)))()
xafqLlk3kkUe(EGyt1xfPT1P6, xafqLlk3kkUe(SXOLrMavuUCe(b"\xcd\xa15w'Y\x8b!"), chr(0b1100100) + chr(0b1001 + 0o134) + chr(4426 - 4327) + chr(111) + '\144' + chr(101))(chr(0b1010110 + 0o37) + chr(0b1110100) + chr(6840 - 6738) + '\055' + '\x38'))()
return NSstowUUZlxS(xafqLlk3kkUe(ZmHK8Erhdn3m, xafqLlk3kkUe(SXOLrMavuUCe(b'\xca\xb68'), chr(100) + chr(101) + chr(0b1100011) + chr(111) + chr(0b1011001 + 0o13) + '\x65')(chr(8858 - 8741) + chr(0b1000110 + 0o56) + '\x66' + '\055' + '\x38')), VjgGQlDzfDa9)
|
tensorflow/tensor2tensor
|
tensor2tensor/trax/models/mlp.py
|
MLP
|
def MLP(num_hidden_layers=2,
hidden_size=512,
activation_fn=layers.Relu,
num_output_classes=10,
mode="train"):
"""Multi-layer feed-forward neural network with non-linear activations."""
del mode
cur_layers = [layers.Flatten()]
for _ in range(num_hidden_layers):
cur_layers += [layers.Dense(hidden_size), activation_fn()]
cur_layers += [layers.Dense(num_output_classes), layers.LogSoftmax()]
return layers.Serial(*cur_layers)
|
python
|
def MLP(num_hidden_layers=2,
hidden_size=512,
activation_fn=layers.Relu,
num_output_classes=10,
mode="train"):
"""Multi-layer feed-forward neural network with non-linear activations."""
del mode
cur_layers = [layers.Flatten()]
for _ in range(num_hidden_layers):
cur_layers += [layers.Dense(hidden_size), activation_fn()]
cur_layers += [layers.Dense(num_output_classes), layers.LogSoftmax()]
return layers.Serial(*cur_layers)
|
[
"def",
"MLP",
"(",
"num_hidden_layers",
"=",
"2",
",",
"hidden_size",
"=",
"512",
",",
"activation_fn",
"=",
"layers",
".",
"Relu",
",",
"num_output_classes",
"=",
"10",
",",
"mode",
"=",
"\"train\"",
")",
":",
"del",
"mode",
"cur_layers",
"=",
"[",
"layers",
".",
"Flatten",
"(",
")",
"]",
"for",
"_",
"in",
"range",
"(",
"num_hidden_layers",
")",
":",
"cur_layers",
"+=",
"[",
"layers",
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"Dense",
"(",
"hidden_size",
")",
",",
"activation_fn",
"(",
")",
"]",
"cur_layers",
"+=",
"[",
"layers",
".",
"Dense",
"(",
"num_output_classes",
")",
",",
"layers",
".",
"LogSoftmax",
"(",
")",
"]",
"return",
"layers",
".",
"Serial",
"(",
"*",
"cur_layers",
")"
] |
Multi-layer feed-forward neural network with non-linear activations.
|
[
"Multi",
"-",
"layer",
"feed",
"-",
"forward",
"neural",
"network",
"with",
"non",
"-",
"linear",
"activations",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/trax/models/mlp.py#L25-L36
|
train
|
Multi - layer feed - forward neural network with non - linear activations.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1700 - 1652) + chr(0b1101111) + '\x36', 0o10), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\x6f' + chr(51) + chr(48) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(0b1101111) + '\064' + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\x6f' + '\x32' + chr(126 - 71) + '\066', 3636 - 3628), ehT0Px3KOsy9(chr(48) + '\157' + '\x33' + chr(0b110010) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + '\x34' + chr(640 - 589), 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b1101111) + chr(1705 - 1652) + chr(2529 - 2477), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000101 + 0o52) + chr(0b110010) + chr(53) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(0b1101111) + '\x32' + chr(48) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(5854 - 5743) + chr(0b10010 + 0o40) + '\067' + chr(53), 59450 - 59442), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(2484 - 2430) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b101 + 0o152) + '\x31' + '\x33', 49729 - 49721), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(8067 - 7956) + chr(0b10 + 0o57) + '\x35' + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b101000 + 0o107) + chr(0b110010) + chr(447 - 393) + chr(2349 - 2297), ord("\x08")), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\157' + chr(0b110010) + chr(1650 - 1599) + chr(0b11110 + 0o25), 0o10), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1001101 + 0o42) + chr(50) + chr(0b10111 + 0o34) + chr(0b11111 + 0o24), 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(816 - 762) + '\x34', 51474 - 51466), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b100 + 0o153) + chr(2352 - 2297) + chr(0b110101), 49994 - 49986), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\063' + '\x34' + '\x31', 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\157' + chr(0b110001) + chr(0b1110 + 0o45) + chr(0b10 + 0o64), 59339 - 59331), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x31' + chr(62 - 8) + chr(0b110010), 2017 - 2009), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + chr(279 - 231) + chr(0b11 + 0o62), 0b1000), ehT0Px3KOsy9(chr(931 - 883) + chr(111) + chr(49) + chr(53) + chr(0b100110 + 0o17), 38725 - 38717), ehT0Px3KOsy9(chr(820 - 772) + '\157' + chr(0b110011) + chr(0b110011) + chr(1383 - 1330), 53552 - 53544), ehT0Px3KOsy9(chr(730 - 682) + chr(111) + chr(0b110011) + chr(0b10110 + 0o40) + '\061', 0o10), ehT0Px3KOsy9(chr(1866 - 1818) + '\x6f' + chr(51) + chr(0b1000 + 0o57) + chr(0b110110), 64323 - 64315), ehT0Px3KOsy9(chr(1865 - 1817) + '\157' + '\062' + chr(0b1110 + 0o50) + chr(0b110010), 50574 - 50566), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1091 - 1038) + '\x32', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(2460 - 2409) + chr(54) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(50), 0o10), ehT0Px3KOsy9(chr(1499 - 1451) + chr(0b1000110 + 0o51) + '\063' + '\067' + '\060', 25989 - 25981), ehT0Px3KOsy9(chr(1518 - 1470) + chr(111) + '\x34' + '\x35', 3457 - 3449), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110101) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101100 + 0o3) + chr(0b110011) + '\x30' + '\064', 0b1000), ehT0Px3KOsy9(chr(1234 - 1186) + '\x6f' + '\x32' + chr(719 - 665) + chr(2195 - 2144), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(0b110011), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011) + chr(50) + '\065', 0b1000), ehT0Px3KOsy9(chr(1307 - 1259) + '\157' + chr(49) + chr(0b110101) + chr(0b1111 + 0o44), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110000 + 0o2) + chr(0b1 + 0o62), 0o10), ehT0Px3KOsy9(chr(1011 - 963) + chr(0b1101111) + chr(0b110010) + chr(0b110111) + '\x36', 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(1814 - 1766) + chr(0b1101111) + '\065' + '\060', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'('), chr(100) + '\x65' + chr(99) + chr(0b1101111) + chr(0b111 + 0o135) + '\145')(chr(117) + '\x74' + chr(102) + chr(45) + chr(2770 - 2714)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def YTtX6EdqFOK1(jZh5_pLUoOoZ=ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b110111 + 0o70) + chr(50), 8), qzoyXN3kdhDL=ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + chr(48) + chr(0b1101 + 0o43) + '\060', ord("\x08")), csxIq5qGbfRm=xafqLlk3kkUe(sGi5Aql23May, xafqLlk3kkUe(SXOLrMavuUCe(b'T\xa3N\xcb'), chr(2610 - 2510) + '\x65' + '\143' + chr(111) + chr(0b1100100) + chr(0b1100101))('\x75' + '\164' + '\x66' + chr(45) + chr(56))), o1MPieaI0OA6=ehT0Px3KOsy9(chr(48) + chr(111) + chr(49) + chr(0b110010), 0o10), holLFgwB7vsP=xafqLlk3kkUe(SXOLrMavuUCe(b'r\xb4C\xd7\xbe'), chr(100) + chr(0b1001111 + 0o26) + chr(6057 - 5958) + chr(8332 - 8221) + chr(5385 - 5285) + chr(0b100000 + 0o105))(chr(0b111011 + 0o72) + chr(8837 - 8721) + chr(102) + chr(0b1100 + 0o41) + '\x38')):
del holLFgwB7vsP
yiNy3ydwXJ5_ = [sGi5Aql23May.Flatten()]
for VNGQdHSFPrso in vQr8gNKaIaWE(jZh5_pLUoOoZ):
yiNy3ydwXJ5_ += [sGi5Aql23May.Dense(qzoyXN3kdhDL), csxIq5qGbfRm()]
yiNy3ydwXJ5_ += [sGi5Aql23May.Dense(o1MPieaI0OA6), sGi5Aql23May.LogSoftmax()]
return xafqLlk3kkUe(sGi5Aql23May, xafqLlk3kkUe(SXOLrMavuUCe(b'U\xa3P\xd7\xb1\x0f'), chr(8573 - 8473) + chr(101) + chr(0b1100011) + chr(0b11010 + 0o125) + chr(0b1010011 + 0o21) + chr(0b1100101))('\x75' + chr(6906 - 6790) + chr(0b1100110) + chr(45) + chr(56)))(*yiNy3ydwXJ5_)
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/env_problem.py
|
EnvProblem._verify_same_spaces
|
def _verify_same_spaces(self):
"""Verifies that all the envs have the same observation and action space."""
# Pre-conditions: self._envs is initialized.
if self._envs is None:
raise ValueError("Environments not initialized.")
if not isinstance(self._envs, list):
tf.logging.warning("Not checking observation and action space "
"compatibility across envs, since there is just one.")
return
# NOTE: We compare string representations of observation_space and
# action_space because compositional classes like space.Tuple don't return
# true on object comparison.
if not all(
str(env.observation_space) == str(self.observation_space)
for env in self._envs):
err_str = ("All environments should have the same observation space, but "
"don't.")
tf.logging.error(err_str)
# Log all observation spaces.
for i, env in enumerate(self._envs):
tf.logging.error("Env[%d] has observation space [%s]", i,
env.observation_space)
raise ValueError(err_str)
if not all(
str(env.action_space) == str(self.action_space) for env in self._envs):
err_str = "All environments should have the same action space, but don't."
tf.logging.error(err_str)
# Log all action spaces.
for i, env in enumerate(self._envs):
tf.logging.error("Env[%d] has action space [%s]", i, env.action_space)
raise ValueError(err_str)
|
python
|
def _verify_same_spaces(self):
"""Verifies that all the envs have the same observation and action space."""
# Pre-conditions: self._envs is initialized.
if self._envs is None:
raise ValueError("Environments not initialized.")
if not isinstance(self._envs, list):
tf.logging.warning("Not checking observation and action space "
"compatibility across envs, since there is just one.")
return
# NOTE: We compare string representations of observation_space and
# action_space because compositional classes like space.Tuple don't return
# true on object comparison.
if not all(
str(env.observation_space) == str(self.observation_space)
for env in self._envs):
err_str = ("All environments should have the same observation space, but "
"don't.")
tf.logging.error(err_str)
# Log all observation spaces.
for i, env in enumerate(self._envs):
tf.logging.error("Env[%d] has observation space [%s]", i,
env.observation_space)
raise ValueError(err_str)
if not all(
str(env.action_space) == str(self.action_space) for env in self._envs):
err_str = "All environments should have the same action space, but don't."
tf.logging.error(err_str)
# Log all action spaces.
for i, env in enumerate(self._envs):
tf.logging.error("Env[%d] has action space [%s]", i, env.action_space)
raise ValueError(err_str)
|
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] |
Verifies that all the envs have the same observation and action space.
|
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/env_problem.py#L199-L235
|
train
|
Verifies that all the envs have the same observation and action space.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1100 + 0o51) + chr(0b10001 + 0o44), ord("\x08")), ehT0Px3KOsy9(chr(314 - 266) + chr(4395 - 4284) + '\063' + '\x34', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1001000 + 0o47) + chr(0b11111 + 0o24) + chr(0b110101) + chr(0b1111 + 0o46), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b100110 + 0o14) + chr(0b110100) + chr(2593 - 2542), 3368 - 3360), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(111) + '\x33' + chr(54), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + '\062' + '\x31', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062' + chr(280 - 232) + chr(2173 - 2122), 7336 - 7328), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49) + chr(0b110100), 0b1000), ehT0Px3KOsy9('\x30' + chr(11275 - 11164) + chr(0b110010) + chr(50) + chr(51), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(49) + '\x37' + chr(0b110110), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1836 - 1786) + chr(0b110000) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1001010 + 0o45) + chr(0b110111) + '\060', 8848 - 8840), ehT0Px3KOsy9('\x30' + '\157' + chr(51) + '\x30' + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(1471 - 1360) + '\067', 45278 - 45270), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + chr(2277 - 2222) + chr(0b110001), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b101100 + 0o103) + chr(0b110001) + chr(55) + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b11000 + 0o32) + chr(0b1110 + 0o45) + chr(49), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(425 - 376) + chr(0b110101) + chr(0b111 + 0o55), 52587 - 52579), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + '\x33', 0o10), ehT0Px3KOsy9(chr(1270 - 1222) + '\157' + '\062' + '\x31' + chr(0b110111), 33147 - 33139), ehT0Px3KOsy9('\060' + chr(111) + '\062' + '\064' + chr(0b100 + 0o55), 43894 - 43886), ehT0Px3KOsy9(chr(334 - 286) + chr(7159 - 7048) + '\x33' + '\x34' + chr(1415 - 1363), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + chr(0b110010) + '\x31', 8), ehT0Px3KOsy9('\060' + chr(3112 - 3001) + chr(0b110010) + chr(48) + '\x33', 8), ehT0Px3KOsy9('\060' + chr(111) + chr(49) + chr(230 - 179) + chr(55), 0o10), ehT0Px3KOsy9('\060' + chr(4488 - 4377) + chr(54) + chr(0b11011 + 0o31), 45484 - 45476), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b100100 + 0o17) + '\x35' + chr(51), 10839 - 10831), ehT0Px3KOsy9(chr(687 - 639) + '\157' + '\x31' + '\x33' + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\063' + '\x36' + chr(1637 - 1586), ord("\x08")), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b10101 + 0o132) + chr(0b110001 + 0o2) + chr(0b110111) + '\065', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\x33' + chr(0b110111) + chr(48), 62403 - 62395), ehT0Px3KOsy9(chr(48) + chr(1806 - 1695) + chr(1579 - 1528) + chr(1140 - 1087) + chr(0b10110 + 0o35), 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110111) + chr(842 - 791), 11306 - 11298), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(9256 - 9145) + '\x32' + chr(52) + chr(0b111 + 0o55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(5201 - 5090) + chr(49) + '\065' + chr(0b1110 + 0o43), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(1233 - 1184) + chr(54) + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + chr(50) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(2378 - 2328) + chr(0b110110) + '\067', 0b1000), ehT0Px3KOsy9('\x30' + chr(3272 - 3161) + '\x31' + chr(0b100010 + 0o20), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b1100 + 0o53) + chr(0b1010 + 0o46), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1101111) + chr(53) + chr(0b110000), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x03'), chr(100) + '\x65' + '\143' + chr(2720 - 2609) + chr(100) + chr(101))('\165' + '\x74' + chr(0b1100110) + chr(0b101101) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def kk05nZGgf2xD(oVre8I6UXc3b):
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'ry\x83\xd5m'), chr(100) + '\x65' + '\x63' + chr(111) + '\144' + '\x65')('\165' + chr(0b1110001 + 0o3) + chr(0b1100011 + 0o3) + '\x2d' + chr(1729 - 1673))) is None:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'hr\x9b\xcal\xbe\xeda\xf6\x10\xf1K\xe3i\x16\t\xb9\x05}\xe6\xd5\x8d\xb0\xef6N\x8e<\xdd'), chr(9258 - 9158) + '\x65' + chr(0b1100011) + chr(111) + '\144' + '\145')(chr(117) + chr(116) + chr(8850 - 8748) + chr(645 - 600) + chr(0b1101 + 0o53)))
if not PlSM16l2KDPD(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'ry\x83\xd5m'), chr(100) + chr(785 - 684) + chr(0b111011 + 0o50) + chr(0b1101111) + chr(3248 - 3148) + chr(101))(chr(117) + '\x74' + chr(0b1100110) + chr(1168 - 1123) + chr(1147 - 1091))), YyaZ4tpXu4lf):
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'Z}\x9f\xcdw\xbf\xe4'), chr(2510 - 2410) + '\145' + chr(0b1011100 + 0o7) + '\157' + chr(2640 - 2540) + '\145')(chr(0b1 + 0o164) + '\x74' + chr(102) + chr(0b101101) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'cs\x99\x83}\xb9\xe6o\xf8\x17\xeb_\xe3h\x1b\x0e\xfc\x1ee\xee\xd5\x8d\xbe\xed\x7fU\x85<\xd3\x9c\x9b\x9fR\xcb\x07S\xa7\xc7k[H<\x8e\xccs\xa1\xe2x\xfa\x1c\xecT\xaas\x00]\xf8\x0fa\xe0\xd2\x97\xf1\xe61B\x98t\xd3\x8e\x91\x85X\xc1I\x07\xbc\xd2x]\ru\x9e\x83t\xa4\xf0x\xb3\x11\xeb]\xed'), '\144' + '\145' + chr(0b101000 + 0o73) + chr(2575 - 2464) + chr(0b1100100) + chr(0b11101 + 0o110))(chr(117) + '\164' + chr(102) + '\x2d' + chr(1538 - 1482)))
return
if not Dl48nj1rbi23((M8_cKLkHVB2V(xafqLlk3kkUe(xzsHIGfR8Ip5, xafqLlk3kkUe(SXOLrMavuUCe(b'B~\x9e\xc6l\xa7\xe2x\xfa\x11\xebg\xb0w\x18\x1e\xfc'), chr(100) + chr(0b1010101 + 0o20) + chr(0b1010101 + 0o16) + chr(111) + chr(4318 - 4218) + chr(0b1000 + 0o135))(chr(3257 - 3140) + chr(116) + '\x66' + chr(45) + chr(0b100000 + 0o30)))) == M8_cKLkHVB2V(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'B~\x9e\xc6l\xa7\xe2x\xfa\x11\xebg\xb0w\x18\x1e\xfc'), '\144' + '\x65' + '\x63' + chr(111) + '\144' + chr(0b110000 + 0o65))('\165' + chr(0b1110100) + chr(331 - 229) + chr(0b100010 + 0o13) + '\x38'))) for xzsHIGfR8Ip5 in xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'ry\x83\xd5m'), '\144' + chr(0b1100101) + '\x63' + chr(0b101000 + 0o107) + chr(100) + '\x65')(chr(0b110101 + 0o100) + '\x74' + '\x66' + chr(45) + chr(1050 - 994))))):
OyFE_HVWONDE = xafqLlk3kkUe(SXOLrMavuUCe(b'lp\x81\x83{\xbf\xf5e\xe1\x11\xebU\xa6i\r\x0e\xb9\x1f{\xe0\xd4\x88\xb5\xa37U\x9d=\xd3\x89\x90\x8e\x1b\xd7\x08\x1e\xb1\x97eZ^y\x9f\xd5\x7f\xa5\xeac\xfd^\xf6H\xa2d\x1cQ\xb9\x0ef\xfb\x81\x80\xbe\xedx@\xc5'), '\144' + chr(0b1100101) + chr(0b1010 + 0o131) + chr(0b1101111) + chr(0b10111 + 0o115) + '\x65')(chr(0b1110101) + chr(3855 - 3739) + '\146' + chr(45) + chr(0b111000))
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'hI\x89\xf3\x7f\xa5\xcc_\xa2\t\xfd\x08'), chr(0b1100100) + chr(0b1100101) + chr(4101 - 4002) + chr(3032 - 2921) + '\x64' + chr(4267 - 4166))(chr(117) + chr(2422 - 2306) + '\x66' + '\055' + chr(184 - 128)))(OyFE_HVWONDE)
for (WVxHKyX45z_L, xzsHIGfR8Ip5) in YlkZvXL8qwsX(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'ry\x83\xd5m'), '\x64' + chr(0b1100101) + '\x63' + chr(1233 - 1122) + chr(100) + '\145')(chr(10791 - 10674) + chr(0b1000110 + 0o56) + chr(102) + chr(45) + '\070'))):
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'hI\x89\xf3\x7f\xa5\xcc_\xa2\t\xfd\x08'), chr(0b1100100) + chr(4314 - 4213) + chr(99) + '\x6f' + chr(0b111111 + 0o45) + chr(2407 - 2306))(chr(0b111001 + 0o74) + chr(116) + chr(0b1100110) + chr(0b1001 + 0o44) + chr(0b110100 + 0o4)))(xafqLlk3kkUe(SXOLrMavuUCe(b'hr\x9b\xf8;\xb5\xde,\xfb\x1f\xf6\x18\xace\n\x18\xeb\x1ar\xfb\xc8\x8b\xbf\xa3,D\x8a;\x96\xdd\xa3\xceH\xf9'), chr(0b1100100) + '\x65' + '\143' + '\x6f' + chr(0b1100100) + '\145')(chr(0b100101 + 0o120) + '\164' + chr(9979 - 9877) + chr(0b101101) + chr(56)), WVxHKyX45z_L, xafqLlk3kkUe(xzsHIGfR8Ip5, xafqLlk3kkUe(SXOLrMavuUCe(b'B~\x9e\xc6l\xa7\xe2x\xfa\x11\xebg\xb0w\x18\x1e\xfc'), chr(912 - 812) + '\145' + chr(99) + chr(0b1101111) + chr(9496 - 9396) + chr(7158 - 7057))(chr(6421 - 6304) + chr(116) + chr(5846 - 5744) + chr(0b101101) + chr(1925 - 1869))))
raise q1QCh3W88sgk(OyFE_HVWONDE)
if not Dl48nj1rbi23((M8_cKLkHVB2V(xafqLlk3kkUe(xzsHIGfR8Ip5, xafqLlk3kkUe(SXOLrMavuUCe(b'L\x7f\x99\xcaq\xbf\xdc\x7f\xe3\x1f\xe6]'), chr(0b1011101 + 0o7) + chr(0b1010100 + 0o21) + '\x63' + chr(111) + chr(100) + '\x65')('\x75' + chr(0b1110100) + chr(0b1011101 + 0o11) + chr(1962 - 1917) + chr(56)))) == M8_cKLkHVB2V(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'L\x7f\x99\xcaq\xbf\xdc\x7f\xe3\x1f\xe6]'), '\144' + '\x65' + '\x63' + '\157' + '\144' + chr(0b1001001 + 0o34))(chr(0b1110101) + '\164' + chr(0b1001011 + 0o33) + '\x2d' + chr(0b11001 + 0o37)))) for xzsHIGfR8Ip5 in xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'ry\x83\xd5m'), chr(2487 - 2387) + chr(0b1100101) + chr(0b100110 + 0o75) + '\157' + chr(0b1100100) + chr(0b1010100 + 0o21))('\x75' + '\164' + '\x66' + '\x2d' + chr(56))))):
OyFE_HVWONDE = xafqLlk3kkUe(SXOLrMavuUCe(b'lp\x81\x83{\xbf\xf5e\xe1\x11\xebU\xa6i\r\x0e\xb9\x1f{\xe0\xd4\x88\xb5\xa37U\x9d=\xd3\x89\x90\x8e\x1b\xd7\x08\x1e\xb1\x97k[Yu\x82\xcd>\xa2\xf3m\xf0\x1b\xa9\x18\xa1r\r]\xfd\x03}\xa8\xd5\xca'), '\144' + chr(7895 - 7794) + '\x63' + chr(0b1010000 + 0o37) + chr(0b1100100) + chr(5431 - 5330))('\165' + chr(0b1010110 + 0o36) + chr(0b1010110 + 0o20) + chr(1313 - 1268) + chr(2565 - 2509))
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'hI\x89\xf3\x7f\xa5\xcc_\xa2\t\xfd\x08'), '\x64' + chr(0b1100101) + chr(99) + chr(111) + chr(0b1000 + 0o134) + chr(101))(chr(0b10010 + 0o143) + '\164' + chr(521 - 419) + chr(361 - 316) + '\x38'))(OyFE_HVWONDE)
for (WVxHKyX45z_L, xzsHIGfR8Ip5) in YlkZvXL8qwsX(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'ry\x83\xd5m'), chr(1815 - 1715) + chr(101) + chr(0b0 + 0o143) + '\x6f' + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + chr(455 - 339) + chr(9804 - 9702) + '\x2d' + '\070'))):
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'hI\x89\xf3\x7f\xa5\xcc_\xa2\t\xfd\x08'), chr(310 - 210) + '\145' + chr(99) + '\x6f' + chr(2325 - 2225) + '\145')('\x75' + chr(0b1100001 + 0o23) + chr(0b1010101 + 0o21) + chr(0b101101) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'hr\x9b\xf8;\xb5\xde,\xfb\x1f\xf6\x18\xa2d\r\x14\xf6\x023\xfc\xd1\x85\xb2\xe6\x7fo\xce+\xae'), '\x64' + '\x65' + chr(0b110 + 0o135) + '\x6f' + '\144' + chr(0b1100101))(chr(0b100111 + 0o116) + '\164' + chr(0b100010 + 0o104) + chr(0b100001 + 0o14) + '\070'), WVxHKyX45z_L, xafqLlk3kkUe(xzsHIGfR8Ip5, xafqLlk3kkUe(SXOLrMavuUCe(b'L\x7f\x99\xcaq\xbf\xdc\x7f\xe3\x1f\xe6]'), chr(0b1010110 + 0o16) + chr(101) + chr(2158 - 2059) + chr(5028 - 4917) + chr(3496 - 3396) + chr(101))(chr(4803 - 4686) + chr(0b1001001 + 0o53) + chr(7265 - 7163) + chr(0b1 + 0o54) + '\070')))
raise q1QCh3W88sgk(OyFE_HVWONDE)
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/env_problem.py
|
EnvProblem.initialize_environments
|
def initialize_environments(self, batch_size=1):
"""Initializes the environments and trajectories.
Subclasses can override this if they don't want a default implementation
which initializes `batch_size` environments, but must take care to
initialize self._trajectories (this is checked in __init__ anyways).
Args:
batch_size: (int) Number of `self.base_env_name` envs to initialize.
"""
assert batch_size >= 1
self._batch_size = batch_size
self._envs = [gym.make(self.base_env_name) for _ in range(batch_size)]
if self._env_wrapper_fn is not None:
self._envs = list(map(self._env_wrapper_fn, self._envs))
# If self.observation_space and self.action_space aren't None, then it means
# that this is a re-initialization of this class, in that case make sure
# that this matches our previous behaviour.
if self._observation_space:
assert str(self._observation_space) == str(
self._envs[0].observation_space)
else:
# This means that we are initializing this class for the first time.
#
# We set this equal to the first env's observation space, later on we'll
# verify that all envs have the same observation space.
self._observation_space = self._envs[0].observation_space
# Similarly for action_space
if self._action_space:
assert str(self._action_space) == str(self._envs[0].action_space)
else:
self._action_space = self._envs[0].action_space
self._verify_same_spaces()
# If self.reward_range is None, i.e. this means that we should take the
# reward range of the env.
if self.reward_range is None:
self._reward_range = self._envs[0].reward_range
# This data structure stores the history of each env.
#
# NOTE: Even if the env is a NN and can step in all batches concurrently, it
# is still valuable to store the trajectories separately.
self._trajectories = trajectory.BatchTrajectory(batch_size=batch_size)
|
python
|
def initialize_environments(self, batch_size=1):
"""Initializes the environments and trajectories.
Subclasses can override this if they don't want a default implementation
which initializes `batch_size` environments, but must take care to
initialize self._trajectories (this is checked in __init__ anyways).
Args:
batch_size: (int) Number of `self.base_env_name` envs to initialize.
"""
assert batch_size >= 1
self._batch_size = batch_size
self._envs = [gym.make(self.base_env_name) for _ in range(batch_size)]
if self._env_wrapper_fn is not None:
self._envs = list(map(self._env_wrapper_fn, self._envs))
# If self.observation_space and self.action_space aren't None, then it means
# that this is a re-initialization of this class, in that case make sure
# that this matches our previous behaviour.
if self._observation_space:
assert str(self._observation_space) == str(
self._envs[0].observation_space)
else:
# This means that we are initializing this class for the first time.
#
# We set this equal to the first env's observation space, later on we'll
# verify that all envs have the same observation space.
self._observation_space = self._envs[0].observation_space
# Similarly for action_space
if self._action_space:
assert str(self._action_space) == str(self._envs[0].action_space)
else:
self._action_space = self._envs[0].action_space
self._verify_same_spaces()
# If self.reward_range is None, i.e. this means that we should take the
# reward range of the env.
if self.reward_range is None:
self._reward_range = self._envs[0].reward_range
# This data structure stores the history of each env.
#
# NOTE: Even if the env is a NN and can step in all batches concurrently, it
# is still valuable to store the trajectories separately.
self._trajectories = trajectory.BatchTrajectory(batch_size=batch_size)
|
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] |
Initializes the environments and trajectories.
Subclasses can override this if they don't want a default implementation
which initializes `batch_size` environments, but must take care to
initialize self._trajectories (this is checked in __init__ anyways).
Args:
batch_size: (int) Number of `self.base_env_name` envs to initialize.
|
[
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/env_problem.py#L248-L295
|
train
|
Initializes the environments and trajectories.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b10100 + 0o37) + '\060' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b111010 + 0o65) + chr(51) + chr(353 - 299) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(1122 - 1074) + chr(0b1101111) + chr(1006 - 955) + chr(1701 - 1648) + '\x37', 0o10), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(1107 - 996) + chr(51) + chr(0b110110) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(0b110001 + 0o76) + chr(50) + chr(2270 - 2219) + chr(0b1110 + 0o46), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b100 + 0o153) + chr(0b100101 + 0o15) + '\066' + chr(1101 - 1048), ord("\x08")), ehT0Px3KOsy9(chr(191 - 143) + '\x6f' + '\x31' + chr(55) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(1469 - 1421) + chr(111) + chr(0b111 + 0o54) + '\x33' + '\063', 0o10), ehT0Px3KOsy9('\x30' + chr(700 - 589) + chr(0b101101 + 0o6) + chr(1715 - 1666) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(304 - 253) + chr(51) + '\066', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + chr(0b110001) + chr(1638 - 1587), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1 + 0o156) + chr(0b110010) + chr(50) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b1 + 0o57) + '\x6f' + chr(0b110010) + chr(1326 - 1277) + chr(0b11010 + 0o35), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + chr(0b110000) + '\x37', 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\066', 0b1000), ehT0Px3KOsy9(chr(1992 - 1944) + '\157' + '\062' + '\064' + chr(0b1111 + 0o44), 8338 - 8330), ehT0Px3KOsy9('\x30' + chr(111) + '\063' + chr(55) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b1100011 + 0o14) + chr(50) + chr(51) + chr(1225 - 1176), 0b1000), ehT0Px3KOsy9(chr(1187 - 1139) + '\x6f' + chr(0b101001 + 0o10) + chr(0b1100 + 0o45) + chr(0b1010 + 0o46), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(5364 - 5253) + '\x32' + '\x33' + chr(53), 27123 - 27115), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b1111 + 0o43) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(76 - 27) + '\x30' + chr(2255 - 2205), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(1890 - 1779) + chr(0b110010) + chr(1160 - 1107) + chr(0b101100 + 0o13), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(11136 - 11025) + chr(0b11110 + 0o23) + '\x30' + chr(0b110111), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b10101 + 0o35) + '\062' + chr(54), 0b1000), ehT0Px3KOsy9(chr(1574 - 1526) + chr(10573 - 10462) + '\061' + '\065' + chr(0b110000), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(51) + '\066' + '\066', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b11100 + 0o123) + chr(0b110100) + chr(0b110001), 0b1000), ehT0Px3KOsy9('\060' + chr(3627 - 3516) + chr(2136 - 2086) + '\066' + chr(1530 - 1478), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + chr(53) + '\061', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + chr(0b100101 + 0o17) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(985 - 931) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b101 + 0o54) + chr(1026 - 972) + chr(0b110100 + 0o3), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x32' + '\x32' + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(111) + chr(909 - 860) + chr(432 - 381) + chr(49), 0o10), ehT0Px3KOsy9('\060' + chr(2297 - 2186) + chr(0b100000 + 0o24) + chr(0b10000 + 0o45), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1855 - 1805) + chr(0b110111), 12948 - 12940), ehT0Px3KOsy9('\x30' + '\x6f' + chr(51) + chr(53) + chr(0b101110 + 0o4), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + chr(0b110101 + 0o1) + '\x36', 8), ehT0Px3KOsy9(chr(1770 - 1722) + chr(111) + '\x31' + chr(54) + '\067', 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110101) + chr(0b1110 + 0o42), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xe8'), '\x64' + chr(0b1100010 + 0o3) + '\143' + chr(0b1000100 + 0o53) + chr(100) + chr(10096 - 9995))('\165' + chr(2523 - 2407) + chr(0b1100110) + chr(0b101101) + chr(2691 - 2635)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Y4ovMe5LEuOj(oVre8I6UXc3b, ix9dZyeAmUxY=ehT0Px3KOsy9(chr(0b110000) + chr(627 - 516) + chr(506 - 457), 22148 - 22140)):
assert ix9dZyeAmUxY >= ehT0Px3KOsy9(chr(0b110000) + chr(0b10101 + 0o132) + chr(2365 - 2316), 8)
oVre8I6UXc3b.JgJJHskwetFL = ix9dZyeAmUxY
oVre8I6UXc3b.f3hkKxEoUkuU = [mZyhk1NGHEBF.make(oVre8I6UXc3b.base_env_name) for VNGQdHSFPrso in vQr8gNKaIaWE(ix9dZyeAmUxY)]
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x99\x91\x81\x84\xc3\xc2\r\xba\xb9\xae\xae\xe2\xd0!h'), chr(0b100 + 0o140) + chr(0b100011 + 0o102) + chr(371 - 272) + chr(111) + '\144' + chr(1438 - 1337))(chr(8092 - 7975) + chr(116) + chr(0b1100110) + chr(1179 - 1134) + chr(0b1001 + 0o57))) is not None:
oVre8I6UXc3b.f3hkKxEoUkuU = YyaZ4tpXu4lf(abA97kOQKaLo(oVre8I6UXc3b._env_wrapper_fn, oVre8I6UXc3b.f3hkKxEoUkuU))
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x99\x9b\x8d\x81\xf9\xc7\t\xba\xbd\xb7\xa4\xfe\xd04v\xc2\x9a\xfc'), '\144' + chr(0b110011 + 0o62) + '\143' + '\157' + chr(100) + '\x65')('\x75' + '\x74' + '\146' + chr(0b10001 + 0o34) + chr(56))):
assert M8_cKLkHVB2V(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x99\x9b\x8d\x81\xf9\xc7\t\xba\xbd\xb7\xa4\xfe\xd04v\xc2\x9a\xfc'), chr(0b1100100) + chr(0b10100 + 0o121) + chr(99) + '\157' + chr(0b1100100) + chr(0b10110 + 0o117))(chr(0b100100 + 0o121) + '\x74' + chr(10225 - 10123) + '\x2d' + '\x38'))) == M8_cKLkHVB2V(xafqLlk3kkUe(oVre8I6UXc3b._envs[ehT0Px3KOsy9(chr(2153 - 2105) + '\x6f' + chr(0b1111 + 0o41), 0b1000)], xafqLlk3kkUe(SXOLrMavuUCe(b'\xa9\x96\x9c\x97\xee\xc3\x1e\xaf\xa0\xb1\xa5\xcf\xfc7g\xc0\x9c'), chr(5746 - 5646) + '\x65' + '\x63' + '\157' + chr(100) + '\145')('\x75' + chr(0b1011 + 0o151) + chr(0b1100110) + chr(0b101101) + chr(944 - 888))))
else:
oVre8I6UXc3b.CBxpEJqBX_3Z = oVre8I6UXc3b._envs[ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\060', 8)].observation_space
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x99\x95\x8c\x86\xf5\xda\x11\x84\xba\xae\xaa\xf3\xea'), chr(0b100110 + 0o76) + chr(0b1100101) + chr(99) + '\157' + chr(0b1100100) + chr(101))('\165' + '\x74' + chr(2948 - 2846) + chr(277 - 232) + chr(0b1 + 0o67))):
assert M8_cKLkHVB2V(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x99\x95\x8c\x86\xf5\xda\x11\x84\xba\xae\xaa\xf3\xea'), chr(0b1100100) + '\x65' + chr(99) + '\x6f' + chr(100) + chr(0b1000011 + 0o42))('\x75' + chr(116) + '\146' + chr(1972 - 1927) + chr(2895 - 2839)))) == M8_cKLkHVB2V(xafqLlk3kkUe(oVre8I6UXc3b._envs[ehT0Px3KOsy9('\060' + chr(0b1011011 + 0o24) + '\060', 8)], xafqLlk3kkUe(SXOLrMavuUCe(b'\xa7\x97\x9b\x9b\xf3\xdb \xa8\xb9\xbf\xa8\xf5'), '\144' + chr(0b1100101) + chr(2767 - 2668) + chr(6447 - 6336) + chr(690 - 590) + '\145')(chr(0b1110101) + '\164' + chr(102) + chr(0b1011 + 0o42) + chr(0b101011 + 0o15))))
else:
oVre8I6UXc3b.y7tPe6mHiF9X = oVre8I6UXc3b._envs[ehT0Px3KOsy9(chr(527 - 479) + '\157' + '\x30', 8)].action_space
xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x99\x82\x8a\x80\xf5\xd3\x06\x84\xba\xbf\xa6\xf5\xd04v\xc2\x9a\xfc;'), chr(0b1100100) + chr(8484 - 8383) + '\143' + chr(111) + chr(100) + chr(0b11110 + 0o107))(chr(0b1010001 + 0o44) + chr(5984 - 5868) + chr(0b1 + 0o145) + chr(1558 - 1513) + chr(0b10101 + 0o43)))()
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb4\x91\x98\x93\xee\xd1 \xa9\xa8\xb0\xac\xf5'), '\144' + chr(101) + chr(0b1100011) + chr(0b1101111) + chr(3643 - 3543) + chr(0b10010 + 0o123))(chr(117) + chr(0b1100 + 0o150) + '\146' + chr(0b11 + 0o52) + chr(0b101 + 0o63))) is None:
oVre8I6UXc3b.DwwPkrpADL9M = oVre8I6UXc3b._envs[ehT0Px3KOsy9(chr(0b110000) + chr(0b100101 + 0o112) + chr(0b10010 + 0o36), 8)].reward_range
oVre8I6UXc3b.V73mUfYH1QkS = Mzq2fr56UhXf.BatchTrajectory(batch_size=ix9dZyeAmUxY)
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/env_problem.py
|
EnvProblem.process_rewards
|
def process_rewards(self, rewards):
"""Clips, rounds, and changes to integer type.
Args:
rewards: numpy array of raw (float) rewards.
Returns:
processed_rewards: numpy array of np.int64
"""
min_reward, max_reward = self.reward_range
# Clips at min and max reward.
rewards = np.clip(rewards, min_reward, max_reward)
# Round to (nearest) int and convert to integral type.
rewards = np.around(rewards, decimals=0).astype(np.int64)
return rewards
|
python
|
def process_rewards(self, rewards):
"""Clips, rounds, and changes to integer type.
Args:
rewards: numpy array of raw (float) rewards.
Returns:
processed_rewards: numpy array of np.int64
"""
min_reward, max_reward = self.reward_range
# Clips at min and max reward.
rewards = np.clip(rewards, min_reward, max_reward)
# Round to (nearest) int and convert to integral type.
rewards = np.around(rewards, decimals=0).astype(np.int64)
return rewards
|
[
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"# Clips at min and max reward.",
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"(",
"rewards",
",",
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",",
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"# Round to (nearest) int and convert to integral type.",
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"=",
"0",
")",
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"astype",
"(",
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"int64",
")",
"return",
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] |
Clips, rounds, and changes to integer type.
Args:
rewards: numpy array of raw (float) rewards.
Returns:
processed_rewards: numpy array of np.int64
|
[
"Clips",
"rounds",
"and",
"changes",
"to",
"integer",
"type",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/env_problem.py#L352-L368
|
train
|
Clips rounds and changes to integer type.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(12035 - 11924) + '\x32' + chr(569 - 518) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(3891 - 3780) + chr(2480 - 2426), ord("\x08")), ehT0Px3KOsy9(chr(925 - 877) + '\157' + chr(0b0 + 0o63) + '\x30' + chr(622 - 573), 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\063' + '\060' + '\060', 51537 - 51529), ehT0Px3KOsy9(chr(0b110000) + chr(0b101010 + 0o105) + '\x31' + '\063' + chr(0b110001), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1000000 + 0o57) + chr(0b11001 + 0o33) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(11290 - 11179) + chr(51) + chr(0b110100) + '\x31', 0o10), ehT0Px3KOsy9('\x30' + chr(0b110 + 0o151) + chr(0b110010 + 0o1) + chr(50) + '\x34', 0o10), ehT0Px3KOsy9(chr(2300 - 2252) + '\x6f' + chr(498 - 449) + '\063' + '\x31', 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1278 - 1226) + '\062', 28329 - 28321), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(11902 - 11791) + '\063' + chr(49) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(52) + chr(0b110000 + 0o1), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + chr(913 - 865) + chr(0b110011), 22116 - 22108), ehT0Px3KOsy9('\060' + '\157' + chr(1625 - 1576) + chr(0b11111 + 0o24) + chr(51), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + '\060', 61780 - 61772), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(7192 - 7081) + chr(0b110001) + '\x37' + '\x35', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b11110 + 0o25) + '\x36' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(1831 - 1783) + chr(111) + chr(0b110011) + '\065' + '\064', 33824 - 33816), ehT0Px3KOsy9(chr(1066 - 1018) + '\x6f' + chr(55) + '\062', 0o10), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\x6f' + '\061' + chr(0b10000 + 0o41) + '\064', 0o10), ehT0Px3KOsy9('\x30' + chr(5968 - 5857) + chr(0b110011) + chr(602 - 549) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + chr(53) + chr(48), 8), ehT0Px3KOsy9(chr(1807 - 1759) + chr(0b1101111) + chr(0b10011 + 0o36) + '\064' + '\x30', 0o10), ehT0Px3KOsy9('\060' + chr(0b1010010 + 0o35) + chr(780 - 730) + chr(49), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1093 - 1042) + chr(410 - 362) + '\x35', 258 - 250), ehT0Px3KOsy9(chr(64 - 16) + chr(4119 - 4008) + chr(0b1 + 0o60) + chr(0b11011 + 0o32) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b101010 + 0o12) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b1101111) + '\061' + chr(0b10011 + 0o42) + chr(55), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b10000 + 0o43) + chr(0b110000) + '\x31', 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(54) + '\065', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + '\067' + chr(50), 45951 - 45943), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(925 - 875) + chr(51) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(6479 - 6368) + chr(1465 - 1416), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(11488 - 11377) + '\x33' + '\062' + chr(0b110101 + 0o1), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(742 - 691) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(427 - 379) + '\157' + chr(0b110001) + '\x33' + '\063', 8), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(111) + chr(2569 - 2518) + '\060' + chr(51), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + '\x31' + '\x33', 8), ehT0Px3KOsy9(chr(2268 - 2220) + chr(0b1101111) + chr(1330 - 1280) + chr(1893 - 1838), ord("\x08")), ehT0Px3KOsy9(chr(0b100000 + 0o20) + '\x6f' + chr(51) + chr(728 - 674) + '\x31', 17992 - 17984)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100000 + 0o25) + chr(0b110000), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1'), chr(0b1100100) + chr(0b110101 + 0o60) + '\143' + chr(0b1101101 + 0o2) + chr(100) + chr(101))(chr(0b1110101) + chr(0b1101001 + 0o13) + chr(0b111100 + 0o52) + chr(0b101101 + 0o0) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def bOL4RsWe32Ht(oVre8I6UXc3b, yrDfr6ll4Ijz):
(V3tTGLj6OXEA, ZKyWwD02HWSB) = oVre8I6UXc3b.reward_range
yrDfr6ll4Ijz = WqUC3KWvYVup.H8HUQmIerer7(yrDfr6ll4Ijz, V3tTGLj6OXEA, ZKyWwD02HWSB)
yrDfr6ll4Ijz = WqUC3KWvYVup.around(yrDfr6ll4Ijz, decimals=ehT0Px3KOsy9('\060' + '\x6f' + chr(48), ord("\x08"))).astype(WqUC3KWvYVup.int64)
return yrDfr6ll4Ijz
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/env_problem.py
|
EnvProblem.num_rewards
|
def num_rewards(self):
"""Returns the number of distinct rewards.
Returns:
Returns None if the reward range is infinite or the processed rewards
aren't discrete, otherwise returns the number of distinct rewards.
"""
# Pre-conditions: reward range is finite.
# : processed rewards are discrete.
if not self.is_reward_range_finite:
tf.logging.error("Infinite reward range, `num_rewards returning None`")
return None
if not self.is_processed_rewards_discrete:
tf.logging.error(
"Processed rewards are not discrete, `num_rewards` returning None")
return None
min_reward, max_reward = self.reward_range
return max_reward - min_reward + 1
|
python
|
def num_rewards(self):
"""Returns the number of distinct rewards.
Returns:
Returns None if the reward range is infinite or the processed rewards
aren't discrete, otherwise returns the number of distinct rewards.
"""
# Pre-conditions: reward range is finite.
# : processed rewards are discrete.
if not self.is_reward_range_finite:
tf.logging.error("Infinite reward range, `num_rewards returning None`")
return None
if not self.is_processed_rewards_discrete:
tf.logging.error(
"Processed rewards are not discrete, `num_rewards` returning None")
return None
min_reward, max_reward = self.reward_range
return max_reward - min_reward + 1
|
[
"def",
"num_rewards",
"(",
"self",
")",
":",
"# Pre-conditions: reward range is finite.",
"# : processed rewards are discrete.",
"if",
"not",
"self",
".",
"is_reward_range_finite",
":",
"tf",
".",
"logging",
".",
"error",
"(",
"\"Infinite reward range, `num_rewards returning None`\"",
")",
"return",
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"logging",
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"\"Processed rewards are not discrete, `num_rewards` returning None\"",
")",
"return",
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",",
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"self",
".",
"reward_range",
"return",
"max_reward",
"-",
"min_reward",
"+",
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] |
Returns the number of distinct rewards.
Returns:
Returns None if the reward range is infinite or the processed rewards
aren't discrete, otherwise returns the number of distinct rewards.
|
[
"Returns",
"the",
"number",
"of",
"distinct",
"rewards",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/env_problem.py#L380-L399
|
train
|
Returns the number of distinct rewards.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110100 + 0o1) + chr(0b11111 + 0o24), 0b1000), ehT0Px3KOsy9('\060' + chr(0b110100 + 0o73) + chr(50) + chr(0b110000 + 0o6) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\063' + chr(48) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\061' + '\x32' + chr(834 - 780), 0o10), ehT0Px3KOsy9('\060' + chr(0b1000011 + 0o54) + '\061' + '\062' + chr(0b110010 + 0o1), 376 - 368), ehT0Px3KOsy9('\x30' + chr(2624 - 2513) + chr(0b110110) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + chr(0b1011 + 0o50) + chr(1621 - 1573), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\x33', 43845 - 43837), ehT0Px3KOsy9('\x30' + chr(0b1011 + 0o144) + '\067' + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(51) + chr(0b110010) + chr(2716 - 2663), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + chr(48) + chr(521 - 469), 0b1000), ehT0Px3KOsy9(chr(1568 - 1520) + chr(0b1101111) + chr(0b11100 + 0o31) + chr(0b10100 + 0o43), 0o10), ehT0Px3KOsy9('\x30' + chr(2086 - 1975) + chr(2503 - 2452) + chr(0b110101) + chr(0b101010 + 0o12), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\063' + chr(0b110010) + '\067', 0o10), ehT0Px3KOsy9(chr(1157 - 1109) + chr(111) + chr(0b110010) + '\060' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\062' + '\x30' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x32' + chr(0b11000 + 0o32) + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b11 + 0o154) + chr(844 - 795) + chr(0b110111) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b101010 + 0o6) + '\157' + chr(0b110010) + chr(53) + chr(0b110010), 54259 - 54251), ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\x6f' + '\x33' + chr(51) + '\x33', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110101 + 0o0), 1686 - 1678), ehT0Px3KOsy9(chr(349 - 301) + '\157' + chr(0b110001) + chr(50) + chr(49), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1010110 + 0o31) + chr(74 - 24) + chr(0b110101) + '\x37', 0o10), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1101111) + chr(1589 - 1539) + chr(54), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + '\065' + chr(51), 33773 - 33765), ehT0Px3KOsy9(chr(411 - 363) + chr(0b1000011 + 0o54) + chr(52) + chr(0b100 + 0o54), 0o10), ehT0Px3KOsy9(chr(323 - 275) + chr(111) + chr(0b110010) + chr(50) + chr(0b11110 + 0o26), 8), ehT0Px3KOsy9(chr(0b110000) + chr(9108 - 8997) + chr(51) + '\x37' + chr(0b10010 + 0o45), 0o10), ehT0Px3KOsy9(chr(503 - 455) + chr(0b1101111) + '\x32' + chr(53), 45490 - 45482), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + chr(0b110 + 0o53) + '\x33', 0o10), ehT0Px3KOsy9(chr(1636 - 1588) + chr(570 - 459) + '\061' + chr(0b1011 + 0o47) + chr(1592 - 1543), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b10 + 0o61) + '\x32' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1101111) + chr(50) + '\x37', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110 + 0o55) + '\067' + chr(0b110111), 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\062' + chr(0b1100 + 0o44) + chr(53), 8), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + '\x37' + '\066', 0o10), ehT0Px3KOsy9('\x30' + chr(9494 - 9383) + '\062' + chr(1025 - 977) + chr(1036 - 982), 0b1000), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b1101111) + '\061' + chr(54) + chr(2844 - 2789), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b11111 + 0o24) + chr(0b110110) + chr(486 - 438), 0o10), ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\x6f' + '\x33' + chr(50) + '\067', 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(111) + chr(2172 - 2119) + chr(1005 - 957), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x05'), chr(1816 - 1716) + '\145' + chr(99) + chr(0b1101001 + 0o6) + '\144' + chr(0b1100101))(chr(3689 - 3572) + chr(0b1110100) + '\x66' + chr(45) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def pqGosRmKnEPv(oVre8I6UXc3b):
if not xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'B\xc5\x9f$6E\xf9q\\\x8a6N\x82\xb0\xe6\xda\xf2\x15\xc4\xb2q4'), '\x64' + '\145' + '\x63' + chr(111) + chr(0b100 + 0o140) + chr(0b1100101))('\x75' + '\164' + chr(0b111010 + 0o54) + chr(0b101 + 0o50) + '\x38')):
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'n\xe3\xa4\x062F\xd7P\t\xa2<\x1f'), chr(100) + '\145' + chr(0b100000 + 0o103) + chr(111) + '\x64' + '\x65')(chr(117) + '\164' + chr(0b1110 + 0o130) + chr(0b101101) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'b\xd8\xa6?=[\xecf\x18\xa7!X\x8d\xa5\xe7\xa5\xe6\x1d\xc4\xbc`}\x8fv\xc5U\xf9\xa0g\xae&\xb7e\x9b\xf6\xde\xf4\x12\x84\xa2Y\xd8\xa984\x12\xd6lV\xb0$'), chr(5679 - 5579) + chr(0b11001 + 0o114) + '\143' + '\157' + chr(0b1001011 + 0o31) + chr(0b1100101))('\x75' + '\x74' + chr(0b1011100 + 0o12) + chr(0b101101) + chr(0b10111 + 0o41)))
return None
if not xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'B\xc5\x9f&!]\xfbfK\xa6!K\xb3\xa5\xe6\xf2\xf5\x0e\xce\xa8Z5\xc6e\xc8R\xf1\x8bp'), chr(0b1100100) + '\x65' + '\143' + chr(7334 - 7223) + chr(0b11110 + 0o106) + chr(101))(chr(669 - 552) + '\164' + chr(1995 - 1893) + chr(0b100111 + 0o6) + chr(1193 - 1137))):
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'n\xe3\xa4\x062F\xd7P\t\xa2<\x1f'), chr(0b1100100) + chr(1287 - 1186) + chr(0b1100011) + chr(0b1101111) + chr(6289 - 6189) + '\x65')(chr(0b1110101) + chr(116) + chr(0b1000111 + 0o37) + chr(45) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'{\xc4\xaf56A\xebf\\\xf56J\x9b\xb6\xf1\xe1\xe7\\\xcb\xa9`q\xc1y\xdf\x00\xf0\x96f\xa8#\xb3c\x9a\xa9\xde\xe6\x19\x85\xbat\xc4\xa5!2@\xfcpX\xf56J\x98\xa2\xf1\xeb\xfd\x12\xcd\xfbK>\xc1s'), chr(0b1100100) + chr(0b1010110 + 0o17) + '\143' + '\157' + '\144' + '\145')(chr(0b1101011 + 0o12) + chr(6647 - 6531) + chr(0b1100100 + 0o2) + chr(45) + '\070'))
return None
(V3tTGLj6OXEA, ZKyWwD02HWSB) = oVre8I6UXc3b.reward_range
return ZKyWwD02HWSB - V3tTGLj6OXEA + ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001), 0o10)
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/env_problem.py
|
EnvProblem._reset
|
def _reset(self, indices):
"""Resets environments at indices shouldn't pre-process or record.
Subclasses should override this to do the actual reset if something other
than the default implementation is desired.
Args:
indices: list of indices of underlying envs to call reset on.
Returns:
np.ndarray of stacked observations from the reset-ed envs.
"""
# Pre-conditions: common_preconditions, see `assert_common_preconditions`.
self.assert_common_preconditions()
# This returns a numpy array with first dimension `len(indices)` and the
# rest being the dimensionality of the observation.
return np.stack([self._envs[index].reset() for index in indices])
|
python
|
def _reset(self, indices):
"""Resets environments at indices shouldn't pre-process or record.
Subclasses should override this to do the actual reset if something other
than the default implementation is desired.
Args:
indices: list of indices of underlying envs to call reset on.
Returns:
np.ndarray of stacked observations from the reset-ed envs.
"""
# Pre-conditions: common_preconditions, see `assert_common_preconditions`.
self.assert_common_preconditions()
# This returns a numpy array with first dimension `len(indices)` and the
# rest being the dimensionality of the observation.
return np.stack([self._envs[index].reset() for index in indices])
|
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"reset",
"(",
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"]",
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] |
Resets environments at indices shouldn't pre-process or record.
Subclasses should override this to do the actual reset if something other
than the default implementation is desired.
Args:
indices: list of indices of underlying envs to call reset on.
Returns:
np.ndarray of stacked observations from the reset-ed envs.
|
[
"Resets",
"environments",
"at",
"indices",
"shouldn",
"t",
"pre",
"-",
"process",
"or",
"record",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/env_problem.py#L454-L472
|
train
|
Resets the environments at indices should not pre - process or record.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + '\157' + chr(677 - 628) + chr(49) + chr(54), 16471 - 16463), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\x6f' + chr(0b110111) + chr(2052 - 2001), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(55) + '\x31', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(1255 - 1206) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(2183 - 2135) + '\157' + chr(51) + chr(0b100010 + 0o22) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(301 - 253) + chr(0b1101111) + chr(50) + '\067' + chr(55), 50339 - 50331), ehT0Px3KOsy9(chr(48) + chr(1009 - 898) + chr(1839 - 1788) + '\061' + chr(52), 8), ehT0Px3KOsy9(chr(182 - 134) + chr(0b1001101 + 0o42) + chr(52) + chr(1590 - 1535), 0o10), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(1033 - 922) + '\x33' + chr(0b110100) + chr(2080 - 2027), 0b1000), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\x6f' + '\x37' + chr(51), 8), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(2868 - 2757) + '\x32' + '\060' + chr(720 - 671), 38659 - 38651), ehT0Px3KOsy9('\060' + chr(111) + chr(0b11111 + 0o30) + '\x36', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100110 + 0o13) + chr(578 - 525) + chr(50), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + chr(0b110101) + chr(1015 - 967), 0b1000), ehT0Px3KOsy9(chr(206 - 158) + '\157' + chr(1832 - 1781) + chr(2646 - 2594) + chr(0b11100 + 0o31), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2150 - 2099) + '\066' + chr(0b110011), 48086 - 48078), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110 + 0o53) + '\065' + '\x33', 59145 - 59137), ehT0Px3KOsy9(chr(48) + chr(9964 - 9853) + chr(50) + '\x36' + chr(0b110011), 57787 - 57779), ehT0Px3KOsy9(chr(48) + chr(0b1000011 + 0o54) + chr(0b101111 + 0o3) + chr(0b110110) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + chr(0b110001 + 0o2) + '\x36', ord("\x08")), ehT0Px3KOsy9('\060' + chr(5770 - 5659) + '\063' + chr(55) + chr(266 - 215), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2119 - 2069) + chr(0b1001 + 0o54) + chr(55), 54947 - 54939), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b10111 + 0o33) + chr(0b110110) + chr(2289 - 2235), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(52) + chr(0b110100), 8), ehT0Px3KOsy9(chr(48) + chr(0b1001000 + 0o47) + chr(49) + chr(49) + '\063', 0o10), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b11000 + 0o127) + chr(967 - 916) + chr(0b110101) + chr(0b101100 + 0o4), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1101111) + chr(0b110010) + '\064' + chr(882 - 834), 45787 - 45779), ehT0Px3KOsy9(chr(1758 - 1710) + chr(0b1011001 + 0o26) + chr(0b10100 + 0o36) + chr(0b1010 + 0o46) + '\x33', 29582 - 29574), ehT0Px3KOsy9(chr(48) + chr(844 - 733) + '\061' + chr(0b100111 + 0o11) + '\x32', 0o10), ehT0Px3KOsy9(chr(1945 - 1897) + chr(0b110001 + 0o76) + chr(0b110001) + chr(0b110011) + chr(54), 0o10), ehT0Px3KOsy9(chr(1993 - 1945) + '\x6f' + '\x31' + chr(944 - 896) + chr(53), 16996 - 16988), ehT0Px3KOsy9(chr(1886 - 1838) + '\157' + chr(54) + '\062', 2084 - 2076), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + chr(55), 0o10), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\157' + '\x35' + '\066', 0b1000), ehT0Px3KOsy9(chr(1202 - 1154) + chr(0b1010 + 0o145) + '\062' + '\x36' + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b10011 + 0o35) + '\157' + '\x32' + '\067' + chr(0b10101 + 0o35), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + chr(52) + chr(621 - 569), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + chr(0b110011) + '\061', 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(2388 - 2277) + chr(49) + '\064' + chr(1390 - 1339), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b111000 + 0o67) + chr(53) + '\060', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'`'), chr(0b1100011 + 0o1) + chr(0b1100101) + '\x63' + '\x6f' + '\144' + '\x65')(chr(10783 - 10666) + chr(0b1110100) + chr(102) + '\x2d' + chr(2089 - 2033)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def m60wwhCWdMHS(oVre8I6UXc3b, pIcoaXENl5Pw):
xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'/HJ\xa9\x96\xcb\x93D\x8aV\xecQ\x04\xb7\x95\x81\x0e\xd0\xda\xb0\x9f\xc6\xc2\x8d$\x86p'), chr(100) + chr(4819 - 4718) + chr(0b1100011) + '\157' + '\144' + '\x65')(chr(3830 - 3713) + chr(10592 - 10476) + '\146' + '\055' + '\070'))()
return xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'=OX\xaf\x8f'), chr(100) + '\x65' + chr(0b1010100 + 0o17) + chr(111) + chr(100) + chr(1986 - 1885))(chr(0b10101 + 0o140) + chr(8064 - 7948) + '\146' + '\055' + chr(787 - 731)))([xafqLlk3kkUe(oVre8I6UXc3b._envs[XdowRbJKZWL9], xafqLlk3kkUe(SXOLrMavuUCe(b'<^J\xa9\x90'), chr(2861 - 2761) + '\x65' + chr(0b1100011) + chr(0b1101111) + '\x64' + chr(101))(chr(0b1110101) + '\x74' + chr(102) + '\x2d' + chr(0b111000)))() for XdowRbJKZWL9 in pIcoaXENl5Pw])
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/env_problem.py
|
EnvProblem.reset
|
def reset(self, indices=None):
"""Resets environments at given indices.
Subclasses should override _reset to do the actual reset if something other
than the default implementation is desired.
Args:
indices: Indices of environments to reset. If None all envs are reset.
Returns:
Batch of initial observations of reset environments.
"""
if indices is None:
indices = np.arange(self.trajectories.batch_size)
# If this is empty (not None) then don't do anything, no env was done.
if indices.size == 0:
tf.logging.warning(
"`reset` called with empty indices array, this is a no-op.")
return None
observations = self._reset(indices)
processed_observations = self.process_observations(observations)
# Record history.
self.trajectories.reset(indices, observations)
return processed_observations
|
python
|
def reset(self, indices=None):
"""Resets environments at given indices.
Subclasses should override _reset to do the actual reset if something other
than the default implementation is desired.
Args:
indices: Indices of environments to reset. If None all envs are reset.
Returns:
Batch of initial observations of reset environments.
"""
if indices is None:
indices = np.arange(self.trajectories.batch_size)
# If this is empty (not None) then don't do anything, no env was done.
if indices.size == 0:
tf.logging.warning(
"`reset` called with empty indices array, this is a no-op.")
return None
observations = self._reset(indices)
processed_observations = self.process_observations(observations)
# Record history.
self.trajectories.reset(indices, observations)
return processed_observations
|
[
"def",
"reset",
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"self",
",",
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"=",
"None",
")",
":",
"if",
"indices",
"is",
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":",
"indices",
"=",
"np",
".",
"arange",
"(",
"self",
".",
"trajectories",
".",
"batch_size",
")",
"# If this is empty (not None) then don't do anything, no env was done.",
"if",
"indices",
".",
"size",
"==",
"0",
":",
"tf",
".",
"logging",
".",
"warning",
"(",
"\"`reset` called with empty indices array, this is a no-op.\"",
")",
"return",
"None",
"observations",
"=",
"self",
".",
"_reset",
"(",
"indices",
")",
"processed_observations",
"=",
"self",
".",
"process_observations",
"(",
"observations",
")",
"# Record history.",
"self",
".",
"trajectories",
".",
"reset",
"(",
"indices",
",",
"observations",
")",
"return",
"processed_observations"
] |
Resets environments at given indices.
Subclasses should override _reset to do the actual reset if something other
than the default implementation is desired.
Args:
indices: Indices of environments to reset. If None all envs are reset.
Returns:
Batch of initial observations of reset environments.
|
[
"Resets",
"environments",
"at",
"given",
"indices",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/env_problem.py#L474-L502
|
train
|
Resets the environment at given indices.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(618 - 570) + '\x6f' + chr(652 - 602) + chr(0b110100) + chr(0b1100 + 0o50), 25919 - 25911), ehT0Px3KOsy9('\060' + chr(111) + chr(0b100110 + 0o14) + '\x34' + '\063', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(0b10101 + 0o40) + '\067', 0o10), ehT0Px3KOsy9(chr(1935 - 1887) + chr(8989 - 8878) + '\x33' + chr(0b110001), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + chr(0b101001 + 0o16) + chr(0b110101), 42177 - 42169), ehT0Px3KOsy9('\x30' + '\157' + chr(1570 - 1519) + chr(53) + chr(0b11101 + 0o24), ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(11312 - 11201) + '\061' + chr(55), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x34' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + chr(52) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(8989 - 8878) + chr(50) + chr(2126 - 2077) + '\066', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1343 - 1292) + chr(1489 - 1435) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11001 + 0o30) + chr(0b11010 + 0o35) + chr(51), 11480 - 11472), ehT0Px3KOsy9(chr(48) + chr(0b1101101 + 0o2) + '\063' + '\x36' + chr(0b10101 + 0o41), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b101000 + 0o107) + chr(0b110101 + 0o0) + chr(0b10111 + 0o34), ord("\x08")), ehT0Px3KOsy9(chr(859 - 811) + '\157' + chr(0b100 + 0o60), 60609 - 60601), ehT0Px3KOsy9(chr(977 - 929) + chr(111) + chr(1525 - 1475) + '\060' + '\061', 817 - 809), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + chr(1921 - 1870) + '\066', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b101110 + 0o5) + chr(0b11010 + 0o32) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b11011 + 0o124) + chr(0b110010) + '\x37' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(146 - 98) + chr(0b111010 + 0o65) + '\063' + chr(0b11000 + 0o35) + '\062', 0o10), ehT0Px3KOsy9('\060' + chr(10653 - 10542) + chr(0b100101 + 0o15) + chr(0b100111 + 0o16) + chr(118 - 68), 38719 - 38711), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + '\x30' + chr(395 - 342), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + chr(0b110011 + 0o0) + chr(54), 8), ehT0Px3KOsy9(chr(2265 - 2217) + chr(111) + '\x33' + '\x34' + chr(55), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(747 - 697) + chr(0b1011 + 0o50) + chr(100 - 52), 38591 - 38583), ehT0Px3KOsy9('\060' + '\x6f' + chr(1291 - 1242) + '\064' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b100100 + 0o16) + chr(2616 - 2563) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b1101111) + chr(0b110011) + chr(0b110011) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(231 - 181) + chr(50) + chr(2477 - 2426), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + chr(0b110001) + chr(1236 - 1184), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(822 - 773) + chr(51), 17763 - 17755), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110011) + chr(2593 - 2538) + chr(0b1000 + 0o52), 24082 - 24074), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(0b1101111) + chr(0b110000 + 0o3) + chr(55) + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011110 + 0o21) + '\062' + chr(0b110110) + chr(2936 - 2881), 58502 - 58494), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b1101111) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b111101 + 0o62) + chr(51) + chr(51) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\x31' + chr(51) + chr(1850 - 1801), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50) + chr(0b100101 + 0o14), 35570 - 35562), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b110010 + 0o75) + chr(0b10001 + 0o42) + chr(54) + chr(49), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(54) + chr(53), 26932 - 26924)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(1285 - 1237) + '\157' + chr(0b10001 + 0o44) + chr(432 - 384), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x8a'), '\144' + chr(0b1001110 + 0o27) + chr(6173 - 6074) + chr(0b1101111) + chr(0b110011 + 0o61) + chr(101))(chr(0b1110101) + '\x74' + chr(0b1000100 + 0o42) + '\x2d' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def G0V856pwkJmZ(oVre8I6UXc3b, pIcoaXENl5Pw=None):
if pIcoaXENl5Pw is None:
pIcoaXENl5Pw = WqUC3KWvYVup.arange(oVre8I6UXc3b.trajectories.ix9dZyeAmUxY)
if xafqLlk3kkUe(pIcoaXENl5Pw, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\xef\x0cz\x8e\xabLm\xcb\xdf\x98\x1a'), chr(100) + chr(0b111100 + 0o51) + '\x63' + '\x6f' + chr(0b1100100) + chr(0b110111 + 0o56))(chr(4030 - 3913) + chr(116) + chr(0b1100110) + chr(0b11111 + 0o16) + '\x38')) == ehT0Px3KOsy9('\x30' + chr(0b1010100 + 0o33) + chr(1146 - 1098), 44714 - 44706):
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd3\xc2\x1dw\xd4\x87h'), '\144' + chr(101) + chr(99) + '\157' + chr(4111 - 4011) + '\145')(chr(13018 - 12901) + chr(0b101011 + 0o111) + chr(6294 - 6192) + '\x2d' + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xc4\xd1\nj\xd8\x9do\x07\xc6\xef\x9f\x17\x93O$\xf6\xf7\x90\xd0\xca\xcf\xe8\xee\x93\xe1E\xc6\xb7\xf7\xa5h\x9f\x8b\x97b\xae+p\x88\x19\x84\xd7\x07p\xce\xc9fT\x85\xef\xd3\x15\x99\x06k\xf1\xb0'), chr(100) + chr(0b1110 + 0o127) + chr(0b1100011) + '\157' + chr(0b111111 + 0o45) + '\x65')(chr(3004 - 2887) + chr(116) + chr(0b1100001 + 0o5) + chr(1129 - 1084) + '\070'))
return None
uswa0rn3Tb4L = oVre8I6UXc3b._reset(pIcoaXENl5Pw)
tIs7Yi3rFcFO = oVre8I6UXc3b.process_observations(uswa0rn3Tb4L)
xafqLlk3kkUe(oVre8I6UXc3b.trajectories, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd6\xc6\x1c|\xc9'), chr(0b1100100) + '\x65' + chr(99) + '\x6f' + '\x64' + '\145')(chr(0b1010011 + 0o42) + '\164' + chr(102) + chr(45) + '\x38'))(pIcoaXENl5Pw, uswa0rn3Tb4L)
return tIs7Yi3rFcFO
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/env_problem.py
|
EnvProblem._step
|
def _step(self, actions):
"""Takes a step in all environments, shouldn't pre-process or record.
Subclasses should override this to do the actual step if something other
than the default implementation is desired.
Args:
actions: (np.ndarray) with first dimension equal to the batch size.
Returns:
a tuple of stacked raw observations, raw rewards, dones and infos.
"""
# Pre-conditions: common_preconditions, see `assert_common_preconditions`.
# : len(actions) == len(self._envs)
self.assert_common_preconditions()
assert len(actions) == len(self._envs)
observations = []
rewards = []
dones = []
infos = []
# Take steps in all environments.
for env, action in zip(self._envs, actions):
observation, reward, done, info = env.step(action)
observations.append(observation)
rewards.append(reward)
dones.append(done)
infos.append(info)
# Convert each list (observations, rewards, ...) into np.array and return a
# tuple.
return tuple(map(np.stack, [observations, rewards, dones, infos]))
|
python
|
def _step(self, actions):
"""Takes a step in all environments, shouldn't pre-process or record.
Subclasses should override this to do the actual step if something other
than the default implementation is desired.
Args:
actions: (np.ndarray) with first dimension equal to the batch size.
Returns:
a tuple of stacked raw observations, raw rewards, dones and infos.
"""
# Pre-conditions: common_preconditions, see `assert_common_preconditions`.
# : len(actions) == len(self._envs)
self.assert_common_preconditions()
assert len(actions) == len(self._envs)
observations = []
rewards = []
dones = []
infos = []
# Take steps in all environments.
for env, action in zip(self._envs, actions):
observation, reward, done, info = env.step(action)
observations.append(observation)
rewards.append(reward)
dones.append(done)
infos.append(info)
# Convert each list (observations, rewards, ...) into np.array and return a
# tuple.
return tuple(map(np.stack, [observations, rewards, dones, infos]))
|
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] |
Takes a step in all environments, shouldn't pre-process or record.
Subclasses should override this to do the actual step if something other
than the default implementation is desired.
Args:
actions: (np.ndarray) with first dimension equal to the batch size.
Returns:
a tuple of stacked raw observations, raw rewards, dones and infos.
|
[
"Takes",
"a",
"step",
"in",
"all",
"environments",
"shouldn",
"t",
"pre",
"-",
"process",
"or",
"record",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/env_problem.py#L504-L538
|
train
|
Takes a step in all environments should not pre - process or record.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(10268 - 10157) + chr(0b10101 + 0o36) + '\x35' + chr(0b110111), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(423 - 374) + chr(55) + chr(0b110000 + 0o2), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(2001 - 1952) + chr(1739 - 1684) + '\x32', 8), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100100 + 0o16) + chr(0b110100) + '\x31', 39970 - 39962), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1417 - 1366) + '\x34' + chr(0b110000), 46356 - 46348), ehT0Px3KOsy9('\x30' + '\x6f' + chr(623 - 574) + chr(53) + chr(1532 - 1484), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(11598 - 11487) + chr(0b10011 + 0o43) + chr(0b110101 + 0o2), 54447 - 54439), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001000 + 0o47) + chr(0b101111 + 0o7) + chr(2036 - 1986), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + '\x30' + '\x33', 23454 - 23446), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100001 + 0o16) + chr(0b110001) + chr(54) + '\x34', 45704 - 45696), ehT0Px3KOsy9('\x30' + chr(10221 - 10110) + '\x31' + '\061' + chr(0b1 + 0o61), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + '\067', 0b1000), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\157' + chr(0b110011) + chr(54) + chr(0b10100 + 0o40), 0b1000), ehT0Px3KOsy9(chr(2269 - 2221) + chr(111) + chr(49) + '\x30', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1000110 + 0o51) + chr(0b110010) + chr(0b1100 + 0o50) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b11011 + 0o25) + '\x6f' + '\x33' + chr(2085 - 2030) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b101010 + 0o6) + '\x6f' + chr(1573 - 1524) + '\x33' + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1 + 0o156) + chr(0b110010) + '\x32' + chr(564 - 513), 45641 - 45633), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(2632 - 2579) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(6672 - 6561) + chr(50) + chr(52) + chr(54), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\x31' + chr(0b10100 + 0o40) + '\066', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b10010 + 0o37) + chr(0b11100 + 0o31) + '\065', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\x31' + chr(0b101101 + 0o5) + chr(54), 0o10), ehT0Px3KOsy9('\x30' + chr(5557 - 5446) + '\062' + '\063' + '\x30', 4407 - 4399), ehT0Px3KOsy9('\060' + chr(111) + chr(54) + chr(48), 61927 - 61919), ehT0Px3KOsy9('\060' + chr(0b1000001 + 0o56) + chr(828 - 773) + chr(0b100110 + 0o15), 0b1000), ehT0Px3KOsy9(chr(1530 - 1482) + chr(0b1101111) + '\x37' + chr(52), 0o10), ehT0Px3KOsy9(chr(48) + chr(4776 - 4665) + '\062' + '\x37' + chr(286 - 238), 513 - 505), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + '\x31' + chr(0b10111 + 0o33), 0b1000), ehT0Px3KOsy9('\x30' + chr(8763 - 8652) + chr(0b11011 + 0o26) + chr(0b110000 + 0o2) + '\x32', ord("\x08")), ehT0Px3KOsy9('\060' + chr(3911 - 3800) + chr(972 - 921) + chr(0b110010) + '\x36', 6371 - 6363), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100101 + 0o12) + chr(0b110010) + '\x36' + chr(2346 - 2295), 40550 - 40542), ehT0Px3KOsy9(chr(0b110000) + chr(7973 - 7862) + chr(0b110010) + chr(0b110011) + chr(55), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + chr(357 - 304) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + chr(696 - 644) + '\x30', 8), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b11001 + 0o126) + '\x32' + chr(0b10001 + 0o37), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x31' + chr(54) + '\x37', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100000 + 0o17) + chr(0b110011) + chr(0b1101 + 0o52) + chr(0b110100), 8), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(3571 - 3460) + chr(0b110011) + chr(53), 0o10), ehT0Px3KOsy9(chr(1583 - 1535) + chr(111) + chr(49) + chr(1871 - 1822), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(111) + chr(108 - 55) + chr(48), 38791 - 38783)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xc1'), chr(100) + chr(101) + '\143' + chr(10115 - 10004) + '\x64' + '\x65')(chr(117) + chr(0b1011100 + 0o30) + chr(9202 - 9100) + '\055' + chr(0b101110 + 0o12)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def TqJNIV_7POBe(oVre8I6UXc3b, WCl6VUkME_8I):
xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e\t\t\xc4\x92\x1chQ,\x19\'`\x9aW\xd5\x8e9\xf0\xc2\xc8\x02\x04"\xf1_UO'), chr(100) + chr(0b1011111 + 0o6) + chr(0b1001010 + 0o31) + '\x6f' + chr(0b1100100) + '\x65')(chr(0b1110101) + chr(0b111110 + 0o66) + chr(102) + chr(666 - 621) + chr(56)))()
assert c2A0yzQpDQB3(WCl6VUkME_8I) == c2A0yzQpDQB3(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x89I\x12\xca\xab\x10r]\x16\x1f?Z'), chr(0b1100100) + chr(101) + '\x63' + chr(0b100110 + 0o111) + chr(100) + '\145')('\165' + chr(12388 - 12272) + '\146' + '\055' + '\x38')))
uswa0rn3Tb4L = []
yrDfr6ll4Ijz = []
ijPEVpFpIejc = []
IxpfLxpjkLkf = []
for (xzsHIGfR8Ip5, vyskHDXig6uT) in pZ0NK2y6HRbn(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x89I\x12\xca\xab\x10r]\x16\x1f?Z'), chr(8642 - 8542) + chr(7646 - 7545) + '\143' + chr(0b1010101 + 0o32) + '\144' + chr(101))('\x75' + '\x74' + chr(0b1100110) + '\x2d' + chr(56))), WCl6VUkME_8I):
(mKQm526a9xSD, jEXsEsgeguP4, Ki86oC9WfglU, S7Hxucg7jlZk) = xzsHIGfR8Ip5.kDuFsAhEatcU(vyskHDXig6uT)
xafqLlk3kkUe(uswa0rn3Tb4L, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e\n\n\xc4\x8e\x0c'), '\144' + chr(0b10110 + 0o117) + chr(0b1010001 + 0o22) + '\157' + chr(0b1100100) + chr(0b1111 + 0o126))(chr(0b1110101) + chr(0b110101 + 0o77) + chr(0b111001 + 0o55) + '\x2d' + '\x38'))(mKQm526a9xSD)
xafqLlk3kkUe(yrDfr6ll4Ijz, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e\n\n\xc4\x8e\x0c'), chr(100) + '\x65' + '\143' + chr(0b1101111) + '\x64' + chr(101))(chr(0b101100 + 0o111) + chr(8622 - 8506) + chr(0b1100110) + '\055' + chr(56)))(jEXsEsgeguP4)
xafqLlk3kkUe(ijPEVpFpIejc, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e\n\n\xc4\x8e\x0c'), '\x64' + chr(101) + '\x63' + chr(0b1010010 + 0o35) + chr(0b1100100) + chr(101))(chr(0b1001010 + 0o53) + '\164' + '\146' + chr(45) + chr(56)))(Ki86oC9WfglU)
xafqLlk3kkUe(IxpfLxpjkLkf, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e\n\n\xc4\x8e\x0c'), '\x64' + chr(2098 - 1997) + chr(0b10010 + 0o121) + chr(1500 - 1389) + chr(100) + chr(0b1100101))(chr(0b1101001 + 0o14) + chr(116) + '\146' + '\055' + '\x38'))(S7Hxucg7jlZk)
return KNyTy8rYcwji(abA97kOQKaLo(xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9c\x0e\x1b\xc2\x8b'), chr(0b1100100) + chr(101) + chr(99) + chr(0b1001 + 0o146) + chr(100) + chr(0b11 + 0o142))(chr(0b1110101) + chr(116) + '\146' + chr(0b101101) + '\070')), [uswa0rn3Tb4L, yrDfr6ll4Ijz, ijPEVpFpIejc, IxpfLxpjkLkf]))
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/env_problem.py
|
EnvProblem.step
|
def step(self, actions):
"""Takes a step in all environments.
Subclasses should override _step to do the actual reset if something other
than the default implementation is desired.
Args:
actions: Batch of actions.
Returns:
(preprocessed_observations, processed_rewards, dones, infos).
"""
observations, raw_rewards, dones, infos = self._step(actions)
# Process rewards.
raw_rewards = raw_rewards.astype(np.float32)
processed_rewards = self.process_rewards(raw_rewards)
# Process observations.
processed_observations = self.process_observations(observations)
# Record history.
self.trajectories.step(processed_observations, raw_rewards,
processed_rewards, dones, actions)
return processed_observations, processed_rewards, dones, infos
|
python
|
def step(self, actions):
"""Takes a step in all environments.
Subclasses should override _step to do the actual reset if something other
than the default implementation is desired.
Args:
actions: Batch of actions.
Returns:
(preprocessed_observations, processed_rewards, dones, infos).
"""
observations, raw_rewards, dones, infos = self._step(actions)
# Process rewards.
raw_rewards = raw_rewards.astype(np.float32)
processed_rewards = self.process_rewards(raw_rewards)
# Process observations.
processed_observations = self.process_observations(observations)
# Record history.
self.trajectories.step(processed_observations, raw_rewards,
processed_rewards, dones, actions)
return processed_observations, processed_rewards, dones, infos
|
[
"def",
"step",
"(",
"self",
",",
"actions",
")",
":",
"observations",
",",
"raw_rewards",
",",
"dones",
",",
"infos",
"=",
"self",
".",
"_step",
"(",
"actions",
")",
"# Process rewards.",
"raw_rewards",
"=",
"raw_rewards",
".",
"astype",
"(",
"np",
".",
"float32",
")",
"processed_rewards",
"=",
"self",
".",
"process_rewards",
"(",
"raw_rewards",
")",
"# Process observations.",
"processed_observations",
"=",
"self",
".",
"process_observations",
"(",
"observations",
")",
"# Record history.",
"self",
".",
"trajectories",
".",
"step",
"(",
"processed_observations",
",",
"raw_rewards",
",",
"processed_rewards",
",",
"dones",
",",
"actions",
")",
"return",
"processed_observations",
",",
"processed_rewards",
",",
"dones",
",",
"infos"
] |
Takes a step in all environments.
Subclasses should override _step to do the actual reset if something other
than the default implementation is desired.
Args:
actions: Batch of actions.
Returns:
(preprocessed_observations, processed_rewards, dones, infos).
|
[
"Takes",
"a",
"step",
"in",
"all",
"environments",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/env_problem.py#L540-L566
|
train
|
Takes a step in all environments and processes rewards and record history.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(111) + chr(49) + chr(0b100100 + 0o23), 53251 - 53243), ehT0Px3KOsy9('\x30' + chr(0b10100 + 0o133) + chr(50) + '\x37' + chr(0b11101 + 0o23), 0b1000), ehT0Px3KOsy9(chr(48) + chr(538 - 427) + chr(0b100111 + 0o13) + chr(49) + chr(2355 - 2303), 24427 - 24419), ehT0Px3KOsy9('\060' + chr(4691 - 4580) + chr(223 - 174) + chr(0b110111) + chr(0b100010 + 0o16), 58970 - 58962), ehT0Px3KOsy9('\x30' + chr(1783 - 1672) + chr(0b100 + 0o56) + chr(0b110101) + chr(0b110110), 50566 - 50558), ehT0Px3KOsy9('\060' + '\157' + '\x33', 59851 - 59843), ehT0Px3KOsy9(chr(1175 - 1127) + chr(1087 - 976) + chr(2569 - 2515) + chr(1685 - 1633), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(9723 - 9612) + chr(0b110 + 0o53) + '\061' + chr(699 - 644), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(50) + chr(1279 - 1229) + chr(0b101101 + 0o7), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1 + 0o62), 8), ehT0Px3KOsy9('\x30' + '\157' + '\062' + chr(54) + chr(0b101000 + 0o16), 6361 - 6353), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + chr(0b11000 + 0o31) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(0b110110) + chr(0b101010 + 0o7), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(8441 - 8330) + chr(0b110010) + chr(0b110101 + 0o2) + '\066', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + chr(0b100000 + 0o27) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(0b1010 + 0o145) + '\x34' + chr(0b110100), 47566 - 47558), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\157' + chr(0b110101) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(5460 - 5349) + '\063' + '\065' + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(0b1000110 + 0o51) + chr(49) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(53), 0o10), ehT0Px3KOsy9('\060' + chr(4282 - 4171) + chr(2252 - 2201) + chr(0b101100 + 0o12) + '\x31', 0o10), ehT0Px3KOsy9(chr(48) + chr(3277 - 3166) + chr(0b100111 + 0o14) + chr(0b101010 + 0o13) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b1101111) + chr(0b11100 + 0o25) + chr(0b110110) + chr(0b101000 + 0o13), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + '\063' + chr(50), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + chr(0b1110 + 0o51) + '\x32', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\061' + chr(1308 - 1260) + chr(0b1101 + 0o44), 63725 - 63717), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001) + chr(51) + '\061', 0b1000), ehT0Px3KOsy9('\060' + chr(2369 - 2258) + chr(412 - 363) + chr(0b11000 + 0o35) + '\x36', 1321 - 1313), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31' + chr(0b110010), 35926 - 35918), ehT0Px3KOsy9(chr(927 - 879) + chr(0b1100000 + 0o17) + chr(0b10111 + 0o34) + chr(1959 - 1907) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2010 - 1955) + chr(0b110001), 41103 - 41095), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + '\065' + chr(0b110010), 8), ehT0Px3KOsy9(chr(359 - 311) + '\157' + chr(0b100 + 0o56) + chr(0b11010 + 0o33) + '\061', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(6914 - 6803) + chr(0b110011) + chr(2790 - 2736) + '\060', 53270 - 53262), ehT0Px3KOsy9(chr(164 - 116) + chr(0b1101111) + '\061' + '\067' + chr(50), 8), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(4558 - 4447) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + chr(1457 - 1402) + '\x37', 39685 - 39677), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + chr(902 - 854) + '\x30', 27163 - 27155), ehT0Px3KOsy9(chr(1178 - 1130) + chr(0b1100101 + 0o12) + chr(49) + '\066' + chr(1647 - 1597), 18886 - 18878), ehT0Px3KOsy9(chr(1172 - 1124) + '\x6f' + chr(0b110100) + chr(0b110001), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\157' + chr(0b100100 + 0o21) + '\x30', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'!'), chr(2826 - 2726) + chr(5958 - 5857) + chr(0b1100011) + chr(11288 - 11177) + chr(0b1010110 + 0o16) + chr(0b1100101))(chr(0b1110101) + '\164' + chr(102) + chr(625 - 580) + chr(1461 - 1405)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def kDuFsAhEatcU(oVre8I6UXc3b, WCl6VUkME_8I):
(uswa0rn3Tb4L, Q6_1NAs64aKe, ijPEVpFpIejc, IxpfLxpjkLkf) = oVre8I6UXc3b._step(WCl6VUkME_8I)
Q6_1NAs64aKe = Q6_1NAs64aKe.astype(WqUC3KWvYVup.float32)
KmO4a71nY2SN = oVre8I6UXc3b.process_rewards(Q6_1NAs64aKe)
tIs7Yi3rFcFO = oVre8I6UXc3b.process_observations(uswa0rn3Tb4L)
xafqLlk3kkUe(oVre8I6UXc3b.trajectories, xafqLlk3kkUe(SXOLrMavuUCe(b'd\xfc\xf9>\xddB\\\n\xf5w\xd5\x9b'), '\144' + chr(8817 - 8716) + chr(0b1100011) + chr(0b110101 + 0o72) + '\144' + chr(4287 - 4186))('\165' + '\x74' + '\x66' + chr(1582 - 1537) + '\070'))(tIs7Yi3rFcFO, Q6_1NAs64aKe, KmO4a71nY2SN, ijPEVpFpIejc, WCl6VUkME_8I)
return (tIs7Yi3rFcFO, KmO4a71nY2SN, ijPEVpFpIejc, IxpfLxpjkLkf)
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/env_problem.py
|
EnvProblem.example_reading_spec
|
def example_reading_spec(self):
"""Data fields to store on disk and their decoders."""
# Subclasses can override and/or extend.
processed_reward_type = tf.float32
if self.is_processed_rewards_discrete:
processed_reward_type = tf.int64
data_fields = {
TIMESTEP_FIELD: tf.FixedLenFeature((1,), tf.int64),
RAW_REWARD_FIELD: tf.FixedLenFeature((1,), tf.float32),
PROCESSED_REWARD_FIELD: tf.FixedLenFeature((1,), processed_reward_type),
DONE_FIELD: tf.FixedLenFeature((1,), tf.int64), # we wrote this as int.
# Special treatment because we need to determine type and shape, also
# enables classes to override.
OBSERVATION_FIELD: self.observation_spec,
ACTION_FIELD: self.action_spec,
}
data_items_to_decoders = {
field: tf.contrib.slim.tfexample_decoder.Tensor(field)
for field in data_fields
}
return data_fields, data_items_to_decoders
|
python
|
def example_reading_spec(self):
"""Data fields to store on disk and their decoders."""
# Subclasses can override and/or extend.
processed_reward_type = tf.float32
if self.is_processed_rewards_discrete:
processed_reward_type = tf.int64
data_fields = {
TIMESTEP_FIELD: tf.FixedLenFeature((1,), tf.int64),
RAW_REWARD_FIELD: tf.FixedLenFeature((1,), tf.float32),
PROCESSED_REWARD_FIELD: tf.FixedLenFeature((1,), processed_reward_type),
DONE_FIELD: tf.FixedLenFeature((1,), tf.int64), # we wrote this as int.
# Special treatment because we need to determine type and shape, also
# enables classes to override.
OBSERVATION_FIELD: self.observation_spec,
ACTION_FIELD: self.action_spec,
}
data_items_to_decoders = {
field: tf.contrib.slim.tfexample_decoder.Tensor(field)
for field in data_fields
}
return data_fields, data_items_to_decoders
|
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] |
Data fields to store on disk and their decoders.
|
[
"Data",
"fields",
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/env_problem.py#L568-L594
|
train
|
Returns a tuple of data fields and data items to decoders.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(0b110011 + 0o4) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\x6f' + '\061' + '\063' + chr(0b110000), 65432 - 65424), ehT0Px3KOsy9(chr(1665 - 1617) + chr(163 - 52) + chr(0b110 + 0o53) + chr(0b110001) + '\064', 0o10), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(0b1101111) + '\062' + '\061' + chr(50), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000000 + 0o57) + chr(1276 - 1224) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b11110 + 0o24) + chr(0b11110 + 0o25) + chr(179 - 125), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(48) + chr(2175 - 2123), 0o10), ehT0Px3KOsy9(chr(1748 - 1700) + chr(111) + chr(0b1101 + 0o44) + chr(48) + chr(53), 3488 - 3480), ehT0Px3KOsy9(chr(48) + chr(3206 - 3095) + chr(0b110001) + chr(0b110001) + '\x31', 0b1000), ehT0Px3KOsy9(chr(657 - 609) + '\157' + '\x33' + chr(54) + chr(290 - 241), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011101 + 0o22) + chr(0b110001) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110100) + chr(0b10110 + 0o33), ord("\x08")), ehT0Px3KOsy9('\060' + chr(4619 - 4508) + chr(0b110001) + chr(559 - 506) + chr(0b1100 + 0o52), 56832 - 56824), ehT0Px3KOsy9(chr(193 - 145) + chr(111) + chr(0b110001) + '\x30', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1946 - 1895) + '\066' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b1011 + 0o45) + '\x6f' + chr(0b110001) + '\061', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101101 + 0o2) + chr(0b10010 + 0o44), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\065' + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110111) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b1101111) + '\x31' + chr(0b11000 + 0o30) + chr(2060 - 2010), 0b1000), ehT0Px3KOsy9('\x30' + chr(939 - 828) + chr(50) + chr(52) + chr(2009 - 1961), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1136 - 1085) + chr(49), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(2201 - 2153) + chr(111) + chr(0b110110) + '\x36', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + chr(2339 - 2288) + chr(55), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(52) + chr(0b100 + 0o62), 0b1000), ehT0Px3KOsy9('\060' + chr(2444 - 2333) + chr(0b110011) + chr(980 - 927), 8), ehT0Px3KOsy9(chr(2043 - 1995) + '\x6f' + '\x35' + '\x32', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + '\x33' + '\x35', 0b1000), ehT0Px3KOsy9(chr(412 - 364) + chr(111) + chr(2206 - 2157) + '\x32' + '\x34', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b100001 + 0o21) + chr(52) + chr(2335 - 2282), 0b1000), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(0b101000 + 0o107) + chr(49) + chr(0b10011 + 0o44) + chr(2082 - 2030), 0o10), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b110000 + 0o77) + '\061' + chr(0b110111) + chr(0b110110), 0o10), ehT0Px3KOsy9('\060' + chr(0b1100000 + 0o17) + chr(0b110011) + chr(0b110110) + chr(0b110001 + 0o5), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(0b100111 + 0o12), 8), ehT0Px3KOsy9(chr(341 - 293) + '\x6f' + chr(1420 - 1369) + chr(51) + chr(0b111 + 0o54), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1000001 + 0o56) + chr(53) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(11473 - 11362) + chr(0b101100 + 0o5) + '\x37' + '\x31', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x36' + chr(1041 - 993), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(2497 - 2444) + '\060', 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'S'), chr(100) + '\145' + chr(99) + chr(3122 - 3011) + chr(938 - 838) + '\x65')(chr(117) + chr(116) + chr(102) + chr(0b101001 + 0o4) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def aQvXV6y6L2zO(oVre8I6UXc3b):
qnMq015wv2_4 = IDJ2eXGCBCDu.float32
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x14+\x13\xfaRr\xfd\xa16:\x94n~\x1cm\x85htOI\x1d\xc4ppU-CiO'), '\144' + '\x65' + '\x63' + chr(0b1101111) + '\x64' + '\x65')(chr(3560 - 3443) + chr(5138 - 5022) + '\146' + '\055' + chr(1385 - 1329))):
qnMq015wv2_4 = IDJ2eXGCBCDu.int64
NcaloodHmi5p = {q5WOw1_M50mt: IDJ2eXGCBCDu.FixedLenFeature((ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1001 - 952), 21758 - 21750),), IDJ2eXGCBCDu.int64), pKVmEWIBpO3r: IDJ2eXGCBCDu.FixedLenFeature((ehT0Px3KOsy9(chr(0b10101 + 0o33) + '\157' + chr(49), 8),), IDJ2eXGCBCDu.float32), YoZofS38WR2o: IDJ2eXGCBCDu.FixedLenFeature((ehT0Px3KOsy9('\060' + chr(111) + '\061', 8),), qnMq015wv2_4), XKMPSL5bwuzk: IDJ2eXGCBCDu.FixedLenFeature((ehT0Px3KOsy9(chr(1872 - 1824) + '\157' + '\061', 8),), IDJ2eXGCBCDu.int64), BcCHeLwc1dak: oVre8I6UXc3b.observation_spec, ETs7TddM391F: oVre8I6UXc3b.action_spec}
IU0p0SPK4Dei = {fEcfxx4smAdS: IDJ2eXGCBCDu.contrib.slim.tfexample_decoder.Tensor(fEcfxx4smAdS) for fEcfxx4smAdS in NcaloodHmi5p}
return (NcaloodHmi5p, IU0p0SPK4Dei)
|
tensorflow/tensor2tensor
|
tensor2tensor/envs/env_problem.py
|
EnvProblem._generate_time_steps
|
def _generate_time_steps(self, trajectory_list):
"""A generator to yield single time-steps from a list of trajectories."""
for single_trajectory in trajectory_list:
assert isinstance(single_trajectory, trajectory.Trajectory)
# Skip writing trajectories that have only a single time-step -- this
# could just be a repeated reset.
if single_trajectory.num_time_steps <= 1:
continue
for index, time_step in enumerate(single_trajectory.time_steps):
# The first time-step doesn't have reward/processed_reward, if so, just
# setting it to 0.0 / 0 should be OK.
raw_reward = time_step.raw_reward
if not raw_reward:
raw_reward = 0.0
processed_reward = time_step.processed_reward
if not processed_reward:
processed_reward = 0
action = time_step.action
if action is None:
# The last time-step doesn't have action, and this action shouldn't be
# used, gym's spaces have a `sample` function, so let's just sample an
# action and use that.
action = self.action_space.sample()
action = gym_spaces_utils.gym_space_encode(self.action_space, action)
if six.PY3:
# py3 complains that, to_example cannot handle np.int64 !
action_dtype = self.action_space.dtype
if action_dtype in [np.int64, np.int32]:
action = list(map(int, action))
elif action_dtype in [np.float64, np.float32]:
action = list(map(float, action))
# same with processed_reward.
processed_reward = int(processed_reward)
assert time_step.observation is not None
yield {
TIMESTEP_FIELD: [index],
ACTION_FIELD:
action,
# to_example errors on np.float32
RAW_REWARD_FIELD: [float(raw_reward)],
PROCESSED_REWARD_FIELD: [processed_reward],
# to_example doesn't know bools
DONE_FIELD: [int(time_step.done)],
OBSERVATION_FIELD:
gym_spaces_utils.gym_space_encode(self.observation_space,
time_step.observation),
}
|
python
|
def _generate_time_steps(self, trajectory_list):
"""A generator to yield single time-steps from a list of trajectories."""
for single_trajectory in trajectory_list:
assert isinstance(single_trajectory, trajectory.Trajectory)
# Skip writing trajectories that have only a single time-step -- this
# could just be a repeated reset.
if single_trajectory.num_time_steps <= 1:
continue
for index, time_step in enumerate(single_trajectory.time_steps):
# The first time-step doesn't have reward/processed_reward, if so, just
# setting it to 0.0 / 0 should be OK.
raw_reward = time_step.raw_reward
if not raw_reward:
raw_reward = 0.0
processed_reward = time_step.processed_reward
if not processed_reward:
processed_reward = 0
action = time_step.action
if action is None:
# The last time-step doesn't have action, and this action shouldn't be
# used, gym's spaces have a `sample` function, so let's just sample an
# action and use that.
action = self.action_space.sample()
action = gym_spaces_utils.gym_space_encode(self.action_space, action)
if six.PY3:
# py3 complains that, to_example cannot handle np.int64 !
action_dtype = self.action_space.dtype
if action_dtype in [np.int64, np.int32]:
action = list(map(int, action))
elif action_dtype in [np.float64, np.float32]:
action = list(map(float, action))
# same with processed_reward.
processed_reward = int(processed_reward)
assert time_step.observation is not None
yield {
TIMESTEP_FIELD: [index],
ACTION_FIELD:
action,
# to_example errors on np.float32
RAW_REWARD_FIELD: [float(raw_reward)],
PROCESSED_REWARD_FIELD: [processed_reward],
# to_example doesn't know bools
DONE_FIELD: [int(time_step.done)],
OBSERVATION_FIELD:
gym_spaces_utils.gym_space_encode(self.observation_space,
time_step.observation),
}
|
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] |
A generator to yield single time-steps from a list of trajectories.
|
[
"A",
"generator",
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"yield",
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"time",
"-",
"steps",
"from",
"a",
"list",
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/envs/env_problem.py#L656-L713
|
train
|
A generator to yield single time - steps from a list of trajectories.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49) + chr(0b101001 + 0o16) + '\067', 65147 - 65139), ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\157' + chr(1873 - 1822) + chr(0b110101) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b110010 + 0o75) + '\064' + '\066', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + chr(0b1010 + 0o53) + chr(0b1100 + 0o50), 8), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(0b100110 + 0o111) + '\x31' + '\064' + chr(0b11011 + 0o33), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1000 + 0o147) + chr(2436 - 2386) + chr(0b100001 + 0o23) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(1507 - 1459) + '\x6f' + chr(52), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063' + chr(798 - 748), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b10111 + 0o130) + chr(0b101010 + 0o11) + chr(2287 - 2235) + chr(0b110100), 35398 - 35390), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + chr(52) + '\060', 0b1000), ehT0Px3KOsy9(chr(1512 - 1464) + chr(11397 - 11286) + chr(1280 - 1230) + chr(0b11011 + 0o32) + chr(0b10000 + 0o46), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(10459 - 10348) + '\x33' + chr(52), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x36' + '\066', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(348 - 299) + chr(390 - 338) + chr(0b111 + 0o57), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b101 + 0o54) + chr(0b10101 + 0o35) + '\x30', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\063' + chr(1462 - 1409) + '\062', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1000000 + 0o57) + chr(119 - 68) + chr(0b101100 + 0o12) + chr(0b101111 + 0o10), 30329 - 30321), ehT0Px3KOsy9('\x30' + chr(2875 - 2764) + '\065', 43877 - 43869), ehT0Px3KOsy9(chr(1916 - 1868) + chr(0b1101111) + '\x32' + chr(0b101000 + 0o11), 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\157' + chr(2070 - 2020) + chr(50) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(2118 - 2069) + chr(49) + chr(51), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110 + 0o60), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(91 - 41), 0o10), ehT0Px3KOsy9('\x30' + chr(0b10111 + 0o130) + chr(49) + chr(55) + chr(0b1100 + 0o52), 0b1000), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + '\062' + chr(54) + '\066', 60590 - 60582), ehT0Px3KOsy9('\x30' + chr(11372 - 11261) + chr(49) + chr(0b110011) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(5705 - 5594) + '\062' + '\064' + chr(1106 - 1054), 50812 - 50804), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001 + 0o5) + chr(51), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110100) + chr(2221 - 2172), 0b1000), ehT0Px3KOsy9(chr(704 - 656) + '\157' + '\x33' + chr(0b1101 + 0o43) + chr(0b110100), 1397 - 1389), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + chr(54) + '\062', 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\061' + chr(1471 - 1419) + '\x36', 8), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\157' + chr(2118 - 2063) + chr(52), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1000000 + 0o57) + '\x37' + chr(0b101001 + 0o12), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + '\x33' + chr(1410 - 1357), 0o10), ehT0Px3KOsy9(chr(1294 - 1246) + chr(0b1101111) + chr(51) + chr(0b110000) + '\x34', 8), ehT0Px3KOsy9('\x30' + chr(0b100001 + 0o116) + chr(1136 - 1086) + chr(1336 - 1283) + chr(0b110110 + 0o0), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(2535 - 2482) + chr(116 - 64), 24411 - 24403), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + chr(0b11000 + 0o34) + chr(650 - 599), 0b1000), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b1101111) + chr(0b110111) + '\x35', 33200 - 33192)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(7531 - 7420) + chr(1712 - 1659) + '\x30', 27136 - 27128)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'Q'), '\x64' + chr(0b1100101) + chr(99) + '\x6f' + chr(100) + chr(0b1100101))(chr(0b1100001 + 0o24) + chr(116) + '\146' + '\055' + chr(1764 - 1708)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def KjRRMz75iZjo(oVre8I6UXc3b, pbil2iYlib4a):
for ZYxwK1E_v5uK in pbil2iYlib4a:
assert PlSM16l2KDPD(ZYxwK1E_v5uK, xafqLlk3kkUe(Mzq2fr56UhXf, xafqLlk3kkUe(SXOLrMavuUCe(b'+\x9eG\x86\x03\xc5pu\x96\xd9'), '\x64' + '\145' + chr(0b1100011) + chr(111) + chr(0b0 + 0o144) + chr(0b1100101))(chr(2682 - 2565) + chr(0b1101001 + 0o13) + chr(10305 - 10203) + '\x2d' + chr(0b111000))))
if xafqLlk3kkUe(ZYxwK1E_v5uK, xafqLlk3kkUe(SXOLrMavuUCe(b'\x11\x99K\xb3\x12\xcfi\x7f\xbb\xd3\xdayF\x15'), chr(0b101111 + 0o65) + chr(101) + '\x63' + chr(10297 - 10186) + chr(4740 - 4640) + '\x65')(chr(0b100001 + 0o124) + chr(116) + '\x66' + '\055' + chr(0b101010 + 0o16))) <= ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101111) + chr(0b1010 + 0o47), 0o10):
continue
for (XdowRbJKZWL9, zVXIFxIBf7Io) in YlkZvXL8qwsX(xafqLlk3kkUe(ZYxwK1E_v5uK, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0b\x85K\x899\xd5p\x7f\x94\xd3'), chr(0b100110 + 0o76) + chr(0b1100101) + '\143' + chr(9451 - 9340) + '\144' + '\145')(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + chr(0b101101) + chr(992 - 936)))):
DvXIgH6NMV3Z = zVXIFxIBf7Io.raw_reward
if not DvXIgH6NMV3Z:
DvXIgH6NMV3Z = 0.0
eMNMcKhPnkSX = zVXIFxIBf7Io.processed_reward
if not eMNMcKhPnkSX:
eMNMcKhPnkSX = ehT0Px3KOsy9(chr(48) + chr(569 - 458) + chr(0b10000 + 0o40), 13949 - 13941)
vyskHDXig6uT = zVXIFxIBf7Io.action
if vyskHDXig6uT is None:
vyskHDXig6uT = oVre8I6UXc3b.action_space.sample()
vyskHDXig6uT = R3UdsNmwvq6a.gym_space_encode(oVre8I6UXc3b.action_space, vyskHDXig6uT)
if xafqLlk3kkUe(sYby0kpfssd4, xafqLlk3kkUe(SXOLrMavuUCe(b'/\xb5\x15'), chr(0b1110 + 0o126) + '\145' + chr(0b101000 + 0o73) + '\157' + chr(8602 - 8502) + chr(0b1100101))(chr(117) + chr(0b1110100) + '\x66' + chr(0b111 + 0o46) + '\x38')):
lfkTERiDpFAA = oVre8I6UXc3b.action_space.jSV9IKnemH7K
if lfkTERiDpFAA in [xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x16\x82R\xdaR'), chr(0b1100100) + '\x65' + chr(6917 - 6818) + chr(0b1101111) + '\144' + '\145')(chr(117) + chr(116) + '\x66' + chr(589 - 544) + chr(0b10100 + 0o44))), xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x16\x82R\xdfT'), chr(0b1011010 + 0o12) + chr(0b1100101) + '\143' + '\157' + chr(0b11110 + 0o106) + chr(4412 - 4311))(chr(0b1110101) + chr(116) + chr(0b1100101 + 0o1) + chr(45) + chr(0b101 + 0o63)))]:
vyskHDXig6uT = YyaZ4tpXu4lf(abA97kOQKaLo(ehT0Px3KOsy9, vyskHDXig6uT))
elif lfkTERiDpFAA in [xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x19\x80I\x8d\x12\x900'), '\144' + chr(0b1100101) + chr(0b1100011) + chr(0b1101111) + chr(100) + chr(0b111011 + 0o52))(chr(0b1001110 + 0o47) + chr(7067 - 6951) + chr(0b1000100 + 0o42) + chr(824 - 779) + '\070')), xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x19\x80I\x8d\x12\x956'), chr(100) + chr(0b1100101) + '\143' + '\x6f' + '\x64' + chr(0b1100101))('\165' + '\x74' + chr(0b1100110) + chr(2000 - 1955) + chr(2066 - 2010)))]:
vyskHDXig6uT = YyaZ4tpXu4lf(abA97kOQKaLo(kkSX4ccExqw4, vyskHDXig6uT))
eMNMcKhPnkSX = ehT0Px3KOsy9(eMNMcKhPnkSX)
assert xafqLlk3kkUe(zVXIFxIBf7Io, xafqLlk3kkUe(SXOLrMavuUCe(b'\x10\x8eU\x89\x14\xd0en\x8d\xcf\xc0'), chr(0b111101 + 0o47) + chr(0b1100101) + chr(2072 - 1973) + '\x6f' + chr(0b10100 + 0o120) + chr(101))(chr(0b1110101) + chr(8311 - 8195) + '\x66' + chr(1345 - 1300) + chr(887 - 831))) is not None
yield {q5WOw1_M50mt: [XdowRbJKZWL9], ETs7TddM391F: vyskHDXig6uT, pKVmEWIBpO3r: [kkSX4ccExqw4(DvXIgH6NMV3Z)], YoZofS38WR2o: [eMNMcKhPnkSX], XKMPSL5bwuzk: [ehT0Px3KOsy9(xafqLlk3kkUe(zVXIFxIBf7Io, xafqLlk3kkUe(SXOLrMavuUCe(b'\x1b\x83H\x89'), chr(0b1001111 + 0o25) + chr(9453 - 9352) + chr(99) + chr(0b111011 + 0o64) + chr(0b1100100) + '\145')(chr(10531 - 10414) + chr(0b1110100) + chr(0b1100110) + chr(0b101101) + chr(2696 - 2640))))], BcCHeLwc1dak: xafqLlk3kkUe(R3UdsNmwvq6a, xafqLlk3kkUe(SXOLrMavuUCe(b'\x18\x95K\xb3\x15\xd6ey\x81\xff\xcbrU\t4\x8f'), '\144' + chr(0b10111 + 0o116) + chr(2780 - 2681) + chr(6224 - 6113) + '\x64' + chr(0b110011 + 0o62))(chr(117) + chr(0b100111 + 0o115) + '\x66' + '\x2d' + chr(0b100010 + 0o26)))(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x10\x8eU\x89\x14\xd0en\x8d\xcf\xc0CE\x161\x89\x92'), chr(0b101101 + 0o67) + chr(101) + '\143' + '\157' + chr(100) + '\145')('\165' + '\x74' + chr(0b1001 + 0o135) + '\x2d' + '\070')), xafqLlk3kkUe(zVXIFxIBf7Io, xafqLlk3kkUe(SXOLrMavuUCe(b'\x10\x8eU\x89\x14\xd0en\x8d\xcf\xc0'), chr(0b1100100) + '\x65' + chr(99) + chr(0b1101111) + chr(7575 - 7475) + '\145')('\165' + chr(13096 - 12980) + chr(8062 - 7960) + chr(0b10110 + 0o27) + chr(321 - 265))))}
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/transformer_nat.py
|
init_vq_bottleneck
|
def init_vq_bottleneck(bottleneck_size, hidden_size):
"""Get lookup table for VQ bottleneck."""
means = tf.get_variable(
name="means",
shape=[bottleneck_size, hidden_size],
initializer=tf.uniform_unit_scaling_initializer())
ema_count = tf.get_variable(
name="ema_count",
shape=[bottleneck_size],
initializer=tf.constant_initializer(0),
trainable=False)
with tf.colocate_with(means):
ema_means = tf.get_variable(
name="ema_means",
initializer=means.initialized_value(),
trainable=False)
return means, ema_means, ema_count
|
python
|
def init_vq_bottleneck(bottleneck_size, hidden_size):
"""Get lookup table for VQ bottleneck."""
means = tf.get_variable(
name="means",
shape=[bottleneck_size, hidden_size],
initializer=tf.uniform_unit_scaling_initializer())
ema_count = tf.get_variable(
name="ema_count",
shape=[bottleneck_size],
initializer=tf.constant_initializer(0),
trainable=False)
with tf.colocate_with(means):
ema_means = tf.get_variable(
name="ema_means",
initializer=means.initialized_value(),
trainable=False)
return means, ema_means, ema_count
|
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] |
Get lookup table for VQ bottleneck.
|
[
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"table",
"for",
"VQ",
"bottleneck",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/transformer_nat.py#L31-L48
|
train
|
Initialize the lookup table for VQ bottleneck.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110100) + chr(0b100111 + 0o20), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1795 - 1745) + chr(0b110001) + chr(970 - 916), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + '\063' + '\x31', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x37', 17428 - 17420), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b10100 + 0o37) + chr(0b110100) + chr(0b110001), 14135 - 14127), ehT0Px3KOsy9(chr(0b10101 + 0o33) + '\x6f' + '\x32' + chr(55), 8411 - 8403), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b101001 + 0o11) + chr(197 - 146) + '\065', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\062' + chr(48) + chr(48), 0b1000), ehT0Px3KOsy9(chr(1896 - 1848) + chr(6543 - 6432) + '\x32' + chr(0b1111 + 0o42) + chr(54), 8), ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\157' + chr(2846 - 2791), 8), ehT0Px3KOsy9(chr(0b111 + 0o51) + '\157' + '\063' + '\x30' + '\060', 0b1000), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1001000 + 0o47) + chr(0b110011) + '\067' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(51) + chr(0b100110 + 0o12), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b100001 + 0o116) + chr(0b110 + 0o55) + '\061' + '\x37', 0o10), ehT0Px3KOsy9('\060' + '\157' + '\062' + chr(0b110110) + '\066', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\066' + '\x31', 4515 - 4507), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + '\x31' + chr(0b110011), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + chr(48) + '\060', 8), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\157' + chr(0b110010) + '\060' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(7791 - 7680) + '\x31' + chr(0b110010) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(1426 - 1378) + chr(0b110 + 0o151) + chr(0b110100) + chr(52), 0b1000), ehT0Px3KOsy9(chr(404 - 356) + '\x6f' + chr(2219 - 2171), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b1111 + 0o42) + '\067' + chr(54), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + chr(0b110110) + '\x36', 8581 - 8573), ehT0Px3KOsy9(chr(48) + '\157' + '\x33' + chr(762 - 711) + '\x31', 0o10), ehT0Px3KOsy9(chr(968 - 920) + '\x6f' + chr(0b1101 + 0o46) + chr(2246 - 2197), 10076 - 10068), ehT0Px3KOsy9('\x30' + chr(0b1010100 + 0o33) + '\x31' + chr(0b110001) + chr(1674 - 1622), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + chr(0b101 + 0o62) + chr(0b110111), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + chr(0b110011) + chr(1482 - 1429), 0b1000), ehT0Px3KOsy9(chr(0b101010 + 0o6) + '\157' + chr(0b10101 + 0o34) + chr(0b1100 + 0o44) + chr(1448 - 1399), ord("\x08")), ehT0Px3KOsy9('\060' + chr(5472 - 5361) + '\x31' + chr(1625 - 1575) + chr(0b1000 + 0o53), 54324 - 54316), ehT0Px3KOsy9(chr(246 - 198) + '\157' + chr(0b1001 + 0o50) + chr(49) + chr(0b110001), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + '\x37' + '\067', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b101110 + 0o3) + chr(976 - 924) + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1662 - 1608) + '\x33', 26135 - 26127), ehT0Px3KOsy9(chr(48) + chr(879 - 768) + chr(0b110011) + '\065' + '\x33', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101100 + 0o3) + chr(50) + '\x37' + chr(1060 - 1005), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(116 - 66) + chr(981 - 927), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(3004 - 2893) + chr(0b101001 + 0o11) + chr(1716 - 1667) + '\x35', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(53) + '\060', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\t'), '\144' + '\x65' + '\143' + '\157' + chr(0b11 + 0o141) + chr(101))(chr(117) + chr(0b1011001 + 0o33) + chr(102) + chr(1698 - 1653) + chr(0b10110 + 0o42)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def su8SG215ouBf(MyjCWd_3JWq1, qzoyXN3kdhDL):
XCAIkNRdiX0I = IDJ2eXGCBCDu.get_variable(name=xafqLlk3kkUe(SXOLrMavuUCe(b'J\xebo7t'), chr(0b111000 + 0o54) + chr(0b1100101) + '\143' + chr(0b101001 + 0o106) + chr(0b1100100) + '\145')('\165' + '\x74' + chr(0b10101 + 0o121) + '\055' + chr(0b111000)), shape=[MyjCWd_3JWq1, qzoyXN3kdhDL], initializer=IDJ2eXGCBCDu.uniform_unit_scaling_initializer())
ALokVh6YPLgI = IDJ2eXGCBCDu.get_variable(name=xafqLlk3kkUe(SXOLrMavuUCe(b'B\xe3o\x06d\x8eb\xf3\xf4'), chr(100) + chr(4047 - 3946) + '\143' + chr(0b1011100 + 0o23) + chr(100) + chr(0b1001110 + 0o27))(chr(0b100010 + 0o123) + chr(0b1110100) + chr(0b1010010 + 0o24) + '\x2d' + chr(280 - 224)), shape=[MyjCWd_3JWq1], initializer=IDJ2eXGCBCDu.constant_initializer(ehT0Px3KOsy9(chr(725 - 677) + '\157' + '\x30', 8)), trainable=ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110000), 8))
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'D\xe1b6d\x80c\xf8\xdf\xf9n\xb4\x97'), chr(6272 - 6172) + '\x65' + chr(0b1100011) + chr(0b1010001 + 0o36) + chr(0b1100100) + chr(0b1100101))('\x75' + '\x74' + chr(102) + chr(0b1010 + 0o43) + chr(56)))(XCAIkNRdiX0I):
vx6LjadlTfNA = IDJ2eXGCBCDu.get_variable(name=xafqLlk3kkUe(SXOLrMavuUCe(b'B\xe3o\x06j\x84v\xf3\xf3'), '\144' + chr(101) + chr(0b1100011) + chr(0b101011 + 0o104) + chr(0b11101 + 0o107) + chr(10012 - 9911))(chr(0b1110101) + '\164' + '\146' + chr(45) + chr(56)), initializer=XCAIkNRdiX0I.initialized_value(), trainable=ehT0Px3KOsy9(chr(0b110000) + chr(4265 - 4154) + '\x30', 8))
return (XCAIkNRdiX0I, vx6LjadlTfNA, ALokVh6YPLgI)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/transformer_nat.py
|
vq_nearest_neighbor
|
def vq_nearest_neighbor(x, hparams):
"""Find the nearest element in means to elements in x."""
bottleneck_size = 2**hparams.bottleneck_bits
means = hparams.means
x_norm_sq = tf.reduce_sum(tf.square(x), axis=-1, keepdims=True)
means_norm_sq = tf.reduce_sum(tf.square(means), axis=-1, keepdims=True)
scalar_prod = tf.matmul(x, means, transpose_b=True)
dist = x_norm_sq + tf.transpose(means_norm_sq) - 2 * scalar_prod
if hparams.bottleneck_kind == "em":
x_means_idx = tf.multinomial(-dist, num_samples=hparams.num_samples)
x_means_hot = tf.one_hot(
x_means_idx, depth=bottleneck_size)
x_means_hot = tf.reduce_mean(x_means_hot, axis=1)
else:
x_means_idx = tf.argmax(-dist, axis=-1)
x_means_hot = tf.one_hot(x_means_idx, depth=bottleneck_size)
x_means = tf.matmul(x_means_hot, means)
e_loss = tf.reduce_mean(tf.squared_difference(x, tf.stop_gradient(x_means)))
return x_means_hot, e_loss
|
python
|
def vq_nearest_neighbor(x, hparams):
"""Find the nearest element in means to elements in x."""
bottleneck_size = 2**hparams.bottleneck_bits
means = hparams.means
x_norm_sq = tf.reduce_sum(tf.square(x), axis=-1, keepdims=True)
means_norm_sq = tf.reduce_sum(tf.square(means), axis=-1, keepdims=True)
scalar_prod = tf.matmul(x, means, transpose_b=True)
dist = x_norm_sq + tf.transpose(means_norm_sq) - 2 * scalar_prod
if hparams.bottleneck_kind == "em":
x_means_idx = tf.multinomial(-dist, num_samples=hparams.num_samples)
x_means_hot = tf.one_hot(
x_means_idx, depth=bottleneck_size)
x_means_hot = tf.reduce_mean(x_means_hot, axis=1)
else:
x_means_idx = tf.argmax(-dist, axis=-1)
x_means_hot = tf.one_hot(x_means_idx, depth=bottleneck_size)
x_means = tf.matmul(x_means_hot, means)
e_loss = tf.reduce_mean(tf.squared_difference(x, tf.stop_gradient(x_means)))
return x_means_hot, e_loss
|
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] |
Find the nearest element in means to elements in x.
|
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272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/transformer_nat.py#L51-L69
|
train
|
Find the nearest element in means to elements in x.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(111) + '\x32' + chr(0b1111 + 0o41) + chr(0b110110), 58330 - 58322), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\x6f' + chr(2470 - 2419) + chr(507 - 458) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(1743 - 1695) + '\157' + '\x31' + chr(53) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(840 - 791) + '\064' + chr(53), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110 + 0o55) + chr(0b110101) + chr(0b101 + 0o53), 0o10), ehT0Px3KOsy9(chr(2006 - 1958) + '\157' + chr(387 - 336) + chr(0b110010) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + '\x32' + chr(0b101110 + 0o6), 17881 - 17873), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\157' + chr(49) + chr(0b100111 + 0o15) + chr(50), 0b1000), ehT0Px3KOsy9(chr(191 - 143) + chr(0b1101111) + '\x33' + chr(2296 - 2244) + '\066', 56667 - 56659), ehT0Px3KOsy9(chr(1983 - 1935) + chr(0b1101111) + chr(0b110011) + chr(52) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b101000 + 0o107) + chr(555 - 506) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b1101111) + '\061' + chr(1838 - 1787) + '\x36', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + chr(2669 - 2615) + chr(0b1010 + 0o52), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000110 + 0o51) + chr(0b100110 + 0o21), ord("\x08")), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b11000 + 0o127) + chr(191 - 142) + chr(652 - 598) + chr(2397 - 2346), 0b1000), ehT0Px3KOsy9(chr(48) + chr(10419 - 10308) + chr(0b110001) + chr(0b100010 + 0o21) + chr(0b110011), 0b1000), ehT0Px3KOsy9('\060' + chr(1977 - 1866) + chr(0b10101 + 0o36) + chr(0b110100), 50989 - 50981), ehT0Px3KOsy9(chr(48) + chr(111) + '\062' + '\061' + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + chr(0b1100 + 0o52) + '\x30', 59781 - 59773), ehT0Px3KOsy9('\x30' + chr(5698 - 5587) + chr(0b1000 + 0o53) + chr(0b110101) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + chr(0b110111) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\063' + '\066', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + chr(0b110111) + chr(0b101011 + 0o5), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(83 - 34) + chr(50) + '\x36', 47414 - 47406), ehT0Px3KOsy9('\060' + chr(111) + chr(386 - 336) + chr(1810 - 1758) + chr(2023 - 1974), 65037 - 65029), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b1000 + 0o147) + chr(51) + '\064', 8), ehT0Px3KOsy9('\060' + chr(111) + '\x33' + '\x32' + chr(0b1100 + 0o44), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49), 46766 - 46758), ehT0Px3KOsy9(chr(48) + chr(7533 - 7422) + chr(2008 - 1957) + '\x36' + chr(1141 - 1091), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(91 - 42) + chr(0b110011) + chr(0b110110), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b101010 + 0o7) + chr(2192 - 2137) + chr(0b110011), 8), ehT0Px3KOsy9('\060' + chr(111) + '\x32' + '\066' + chr(1139 - 1085), ord("\x08")), ehT0Px3KOsy9(chr(134 - 86) + '\x6f' + '\061' + chr(0b11101 + 0o26) + chr(55), 61221 - 61213), ehT0Px3KOsy9('\060' + '\157' + '\x31' + chr(612 - 559) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(464 - 416) + '\x6f' + chr(0b11101 + 0o24) + chr(0b110011) + '\064', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100010 + 0o15) + '\x31' + chr(0b110010) + chr(0b110000 + 0o7), 0b1000), ehT0Px3KOsy9(chr(553 - 505) + '\x6f' + chr(0b110101) + '\x32', 33047 - 33039), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1100011 + 0o14) + '\x31' + chr(290 - 237) + chr(0b110100), 8), ehT0Px3KOsy9('\x30' + '\157' + chr(185 - 134) + '\x33', 57413 - 57405), ehT0Px3KOsy9(chr(48) + chr(468 - 357) + chr(51) + chr(0b110101) + '\x33', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110101) + chr(0b11000 + 0o30), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xa8'), '\x64' + chr(101) + '\x63' + chr(0b1001100 + 0o43) + '\x64' + chr(101))('\x75' + chr(0b1110100) + chr(102) + '\x2d' + chr(0b110000 + 0o10)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def _BIEDn8fJw4t(OeWW0F1dBPRQ, n4ljua2gi1Pr):
MyjCWd_3JWq1 = ehT0Px3KOsy9(chr(0b1100 + 0o44) + '\x6f' + chr(2325 - 2275), 0b1000) ** n4ljua2gi1Pr.bottleneck_bits
XCAIkNRdiX0I = n4ljua2gi1Pr.XCAIkNRdiX0I
fGB238pT2MDS = IDJ2eXGCBCDu.reduce_sum(IDJ2eXGCBCDu.square(OeWW0F1dBPRQ), axis=-ehT0Px3KOsy9('\x30' + chr(10433 - 10322) + chr(0b1011 + 0o46), 8), keepdims=ehT0Px3KOsy9('\060' + '\x6f' + chr(1071 - 1022), 8))
VKkOWR9YyfoZ = IDJ2eXGCBCDu.reduce_sum(IDJ2eXGCBCDu.square(XCAIkNRdiX0I), axis=-ehT0Px3KOsy9(chr(0b110000) + chr(0b1101101 + 0o2) + chr(49), 8), keepdims=ehT0Px3KOsy9(chr(1711 - 1663) + chr(111) + '\x31', 8))
OsEVnTBapoxv = IDJ2eXGCBCDu.matmul(OeWW0F1dBPRQ, XCAIkNRdiX0I, transpose_b=ehT0Px3KOsy9(chr(0b110000) + chr(0b1000000 + 0o57) + chr(0b110001), 8))
ydho_1U2EnKK = fGB238pT2MDS + IDJ2eXGCBCDu.transpose(VKkOWR9YyfoZ) - ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b101101 + 0o5), 8) * OsEVnTBapoxv
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe4\xa6\x18\x11\x84\xb4\xfa\x07\x85\x89S5\xddi\x17'), '\144' + chr(8757 - 8656) + '\143' + chr(111) + chr(359 - 259) + '\x65')(chr(0b1110101) + chr(0b111001 + 0o73) + chr(0b1000010 + 0o44) + chr(0b11 + 0o52) + '\070')) == xafqLlk3kkUe(SXOLrMavuUCe(b'\xe3\xa4'), chr(0b100 + 0o140) + chr(0b1100101) + chr(0b1100011) + '\157' + '\144' + chr(0b10100 + 0o121))('\165' + '\x74' + '\x66' + '\055' + chr(0b10010 + 0o46)):
T8BdHeA1BjOx = IDJ2eXGCBCDu.multinomial(-ydho_1U2EnKK, num_samples=n4ljua2gi1Pr.num_samples)
fu_DLUnq0Rui = IDJ2eXGCBCDu.Hq3fv4Yp0EhD(T8BdHeA1BjOx, depth=MyjCWd_3JWq1)
fu_DLUnq0Rui = IDJ2eXGCBCDu.reduce_mean(fu_DLUnq0Rui, axis=ehT0Px3KOsy9(chr(48) + chr(0b10011 + 0o134) + chr(0b110001), 8))
else:
T8BdHeA1BjOx = IDJ2eXGCBCDu.argmax(-ydho_1U2EnKK, axis=-ehT0Px3KOsy9('\060' + chr(1659 - 1548) + chr(49), 8))
fu_DLUnq0Rui = IDJ2eXGCBCDu.Hq3fv4Yp0EhD(T8BdHeA1BjOx, depth=MyjCWd_3JWq1)
xPgmXL9DQrWF = IDJ2eXGCBCDu.matmul(fu_DLUnq0Rui, XCAIkNRdiX0I)
bGSDGpa5hkiT = IDJ2eXGCBCDu.reduce_mean(IDJ2eXGCBCDu.squared_difference(OeWW0F1dBPRQ, IDJ2eXGCBCDu.stop_gradient(xPgmXL9DQrWF)))
return (fu_DLUnq0Rui, bGSDGpa5hkiT)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/transformer_nat.py
|
vq_discrete_bottleneck
|
def vq_discrete_bottleneck(x, hparams):
"""Simple vector quantized discrete bottleneck."""
tf.logging.info("Using EMA with beta = {}".format(hparams.beta))
bottleneck_size = 2**hparams.bottleneck_bits
x_shape = common_layers.shape_list(x)
x = tf.reshape(x, [-1, hparams.hidden_size])
x_means_hot, e_loss = vq_nearest_neighbor(
x, hparams)
means, ema_means, ema_count = (hparams.means, hparams.ema_means,
hparams.ema_count)
# Update the ema variables
updated_ema_count = moving_averages.assign_moving_average(
ema_count,
tf.reduce_sum(x_means_hot, axis=0),
hparams.decay,
zero_debias=False)
dw = tf.matmul(x_means_hot, x, transpose_a=True)
updated_ema_means = moving_averages.assign_moving_average(
ema_means, dw, hparams.decay, zero_debias=False)
n = tf.reduce_sum(updated_ema_count, axis=-1, keepdims=True)
updated_ema_count = (
(updated_ema_count + hparams.epsilon) /
(n + bottleneck_size * hparams.epsilon) * n)
# pylint: disable=g-no-augmented-assignment
updated_ema_means = updated_ema_means / tf.expand_dims(
updated_ema_count, axis=-1)
# pylint: enable=g-no-augmented-assignment
with tf.control_dependencies([e_loss]):
update_means = tf.assign(means, updated_ema_means)
with tf.control_dependencies([update_means]):
loss = hparams.beta * e_loss
discrete = tf.reshape(x_means_hot, x_shape[:-1] + [bottleneck_size])
return discrete, loss
|
python
|
def vq_discrete_bottleneck(x, hparams):
"""Simple vector quantized discrete bottleneck."""
tf.logging.info("Using EMA with beta = {}".format(hparams.beta))
bottleneck_size = 2**hparams.bottleneck_bits
x_shape = common_layers.shape_list(x)
x = tf.reshape(x, [-1, hparams.hidden_size])
x_means_hot, e_loss = vq_nearest_neighbor(
x, hparams)
means, ema_means, ema_count = (hparams.means, hparams.ema_means,
hparams.ema_count)
# Update the ema variables
updated_ema_count = moving_averages.assign_moving_average(
ema_count,
tf.reduce_sum(x_means_hot, axis=0),
hparams.decay,
zero_debias=False)
dw = tf.matmul(x_means_hot, x, transpose_a=True)
updated_ema_means = moving_averages.assign_moving_average(
ema_means, dw, hparams.decay, zero_debias=False)
n = tf.reduce_sum(updated_ema_count, axis=-1, keepdims=True)
updated_ema_count = (
(updated_ema_count + hparams.epsilon) /
(n + bottleneck_size * hparams.epsilon) * n)
# pylint: disable=g-no-augmented-assignment
updated_ema_means = updated_ema_means / tf.expand_dims(
updated_ema_count, axis=-1)
# pylint: enable=g-no-augmented-assignment
with tf.control_dependencies([e_loss]):
update_means = tf.assign(means, updated_ema_means)
with tf.control_dependencies([update_means]):
loss = hparams.beta * e_loss
discrete = tf.reshape(x_means_hot, x_shape[:-1] + [bottleneck_size])
return discrete, loss
|
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"]",
")",
"return",
"discrete",
",",
"loss"
] |
Simple vector quantized discrete bottleneck.
|
[
"Simple",
"vector",
"quantized",
"discrete",
"bottleneck",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/transformer_nat.py#L72-L107
|
train
|
Simple vector quantized discrete bottleneck.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x32' + '\062' + chr(371 - 321), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(51), 25281 - 25273), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1058 - 1009) + chr(50) + '\x37', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + '\x31' + chr(54), 8366 - 8358), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x32' + chr(0b110011) + chr(2567 - 2516), ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b1101111) + chr(0b110011) + '\x37' + chr(586 - 537), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + '\x30' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(3615 - 3504) + '\x32' + chr(0b110000) + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b1100111 + 0o10) + chr(51) + '\061' + chr(50), 0o10), ehT0Px3KOsy9(chr(1122 - 1074) + '\157' + chr(131 - 80) + '\066' + chr(0b10101 + 0o41), 0b1000), ehT0Px3KOsy9(chr(48) + chr(859 - 748) + chr(0b101011 + 0o10) + chr(49) + chr(0b11101 + 0o30), 0o10), ehT0Px3KOsy9(chr(1347 - 1299) + '\157' + chr(1993 - 1944) + chr(1032 - 978) + '\x32', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\x31' + chr(479 - 428) + '\061', 44453 - 44445), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1453 - 1403) + chr(249 - 198) + '\x32', 0o10), ehT0Px3KOsy9(chr(419 - 371) + chr(2522 - 2411) + '\x33' + chr(1179 - 1130) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(703 - 649), 58505 - 58497), ehT0Px3KOsy9(chr(48) + chr(7213 - 7102) + chr(729 - 680) + '\065' + chr(0b10100 + 0o37), 0o10), ehT0Px3KOsy9(chr(847 - 799) + chr(0b100110 + 0o111) + '\x31' + chr(0b100111 + 0o12) + chr(0b100101 + 0o20), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(977 - 927) + chr(0b110010) + chr(0b110100), 56030 - 56022), ehT0Px3KOsy9(chr(0b10100 + 0o34) + '\157' + '\x32' + chr(0b110111) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(3017 - 2906) + chr(0b10001 + 0o40) + '\x31' + chr(0b11000 + 0o33), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + chr(0b101111 + 0o7) + '\x31', 20828 - 20820), ehT0Px3KOsy9(chr(175 - 127) + '\157' + '\062' + chr(53) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\x6f' + '\063' + '\x36' + '\x36', 8), ehT0Px3KOsy9(chr(1122 - 1074) + chr(0b1101111) + chr(51) + chr(51) + '\063', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + '\065' + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(111) + chr(51) + chr(48) + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(8458 - 8347) + chr(0b110010) + '\063' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(49) + chr(527 - 479) + '\064', 46125 - 46117), ehT0Px3KOsy9(chr(1871 - 1823) + '\157' + '\062' + '\x31' + chr(2320 - 2265), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + chr(441 - 390) + chr(2338 - 2284), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + '\x36' + '\x33', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(8645 - 8534) + chr(0b110110) + '\065', 34846 - 34838), ehT0Px3KOsy9(chr(1632 - 1584) + chr(0b1010001 + 0o36) + chr(0b11011 + 0o27) + '\x31' + chr(472 - 423), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(325 - 272), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(1949 - 1896), 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(11038 - 10927) + chr(0b110001) + '\067' + chr(0b1110 + 0o46), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1011000 + 0o27) + chr(51) + chr(54) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(111) + chr(50) + chr(0b110111) + '\064', 0b1000), ehT0Px3KOsy9(chr(638 - 590) + chr(0b1101111) + '\x32' + chr(53) + '\x34', 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b0 + 0o157) + chr(1224 - 1171) + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xbc'), chr(7483 - 7383) + chr(0b1100101) + chr(0b1100011) + chr(0b1101111) + chr(0b1100100) + chr(101))('\x75' + chr(0b10100 + 0o140) + '\146' + chr(45) + chr(0b110001 + 0o7)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def AA7HUoEwKt_Y(OeWW0F1dBPRQ, n4ljua2gi1Pr):
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc14\x1f6\xee\x9a\xe3\xb5\xa0\x9a\x97\x19'), chr(2921 - 2821) + '\145' + '\143' + '\x6f' + '\x64' + '\x65')(chr(0b111010 + 0o73) + chr(0b110010 + 0o102) + chr(0b1100110) + '\055' + chr(0b111000)))(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b'\xc7p> \xfc\xd9\xc1\xcf\x8b\xd6\xba\x1b-\xf2\xebd\x0e9\xf5\x9fv\xd1\xd7\x8b'), chr(2442 - 2342) + chr(0b111101 + 0o50) + chr(99) + chr(0b1100001 + 0o16) + '\144' + chr(101))(chr(0b100001 + 0o124) + chr(0b1110100) + '\146' + '\055' + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xc47%!\xd3\x98\xd7\xb1\x9a\x86\xa8\x18'), '\144' + chr(0b1100101) + '\x63' + chr(7891 - 7780) + '\144' + '\145')(chr(117) + chr(0b111000 + 0o74) + chr(0b1100110) + chr(0b101101) + '\x38'))(xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd4i4!\xed\x9e\xeb\xca\x87\xc7\x815'), '\144' + chr(5991 - 5890) + chr(99) + chr(584 - 473) + '\144' + chr(0b1000 + 0o135))(chr(0b1110101) + '\x74' + chr(0b1001 + 0o135) + chr(0b10001 + 0o34) + '\x38'))))
MyjCWd_3JWq1 = ehT0Px3KOsy9('\x30' + chr(111) + chr(683 - 633), 0b1000) ** n4ljua2gi1Pr.bottleneck_bits
QQEXXbdZyz6m = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
OeWW0F1dBPRQ = IDJ2eXGCBCDu.reshape(OeWW0F1dBPRQ, [-ehT0Px3KOsy9(chr(0b110000) + chr(0b1101 + 0o142) + chr(0b100 + 0o55), 0o10), n4ljua2gi1Pr.qzoyXN3kdhDL])
(fu_DLUnq0Rui, bGSDGpa5hkiT) = _BIEDn8fJw4t(OeWW0F1dBPRQ, n4ljua2gi1Pr)
(XCAIkNRdiX0I, vx6LjadlTfNA, ALokVh6YPLgI) = (n4ljua2gi1Pr.XCAIkNRdiX0I, n4ljua2gi1Pr.ema_means, n4ljua2gi1Pr.ema_count)
FuqutXPYitL0 = nDgFXrDqtELR.assign_moving_average(ALokVh6YPLgI, IDJ2eXGCBCDu.reduce_sum(fu_DLUnq0Rui, axis=ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110000), 0o10)), n4ljua2gi1Pr.decay, zero_debias=ehT0Px3KOsy9(chr(1528 - 1480) + chr(111) + chr(48), 8))
UVJMTi_S70Uf = IDJ2eXGCBCDu.matmul(fu_DLUnq0Rui, OeWW0F1dBPRQ, transpose_a=ehT0Px3KOsy9(chr(213 - 165) + '\157' + chr(194 - 145), 8))
RVkrIbasqS0L = nDgFXrDqtELR.assign_moving_average(vx6LjadlTfNA, UVJMTi_S70Uf, n4ljua2gi1Pr.decay, zero_debias=ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\x6f' + chr(0b11 + 0o55), 8))
m1NkCryOw9Bx = IDJ2eXGCBCDu.reduce_sum(FuqutXPYitL0, axis=-ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\157' + chr(2166 - 2117), 8), keepdims=ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31', 8))
FuqutXPYitL0 = (FuqutXPYitL0 + n4ljua2gi1Pr.Xtig2zAKpR0T) / (m1NkCryOw9Bx + MyjCWd_3JWq1 * n4ljua2gi1Pr.Xtig2zAKpR0T) * m1NkCryOw9Bx
RVkrIbasqS0L = RVkrIbasqS0L / IDJ2eXGCBCDu.expand_dims(FuqutXPYitL0, axis=-ehT0Px3KOsy9(chr(48) + chr(0b11110 + 0o121) + chr(49), 8))
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf1l9:\xe9\x96\xe8\xdd\xae\x93\xbd\x177\xfe\xaeh\x08$\xf1\xcc'), '\x64' + '\145' + chr(0b101011 + 0o70) + '\157' + chr(6843 - 6743) + '\x65')(chr(117) + '\164' + chr(3307 - 3205) + chr(0b111 + 0o46) + chr(0b1100 + 0o54)))([bGSDGpa5hkiT]):
lMKniTbgIhg2 = IDJ2eXGCBCDu.assign(XCAIkNRdiX0I, RVkrIbasqS0L)
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf1l9:\xe9\x96\xe8\xdd\xae\x93\xbd\x177\xfe\xaeh\x08$\xf1\xcc'), chr(100) + chr(895 - 794) + chr(0b1100011) + chr(0b1101011 + 0o4) + chr(100) + '\145')(chr(0b10001 + 0o144) + chr(116) + chr(0b1100110) + chr(1296 - 1251) + chr(0b101010 + 0o16)))([lMKniTbgIhg2]):
YpO0BcZ6fMsf = n4ljua2gi1Pr.FjcovgoHM1LG * bGSDGpa5hkiT
_imQq3p9CjTh = IDJ2eXGCBCDu.reshape(fu_DLUnq0Rui, QQEXXbdZyz6m[:-ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49), 8)] + [MyjCWd_3JWq1])
return (_imQq3p9CjTh, YpO0BcZ6fMsf)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/transformer_nat.py
|
vq_discrete_unbottleneck
|
def vq_discrete_unbottleneck(x, hparams):
"""Simple undiscretization from vector quantized representation."""
x_shape = common_layers.shape_list(x)
bottleneck_size = 2**hparams.bottleneck_bits
means = hparams.means
x_flat = tf.reshape(x, [-1, bottleneck_size])
result = tf.matmul(x_flat, means)
result = tf.reshape(result, x_shape[:-1] + [hparams.hidden_size])
return result
|
python
|
def vq_discrete_unbottleneck(x, hparams):
"""Simple undiscretization from vector quantized representation."""
x_shape = common_layers.shape_list(x)
bottleneck_size = 2**hparams.bottleneck_bits
means = hparams.means
x_flat = tf.reshape(x, [-1, bottleneck_size])
result = tf.matmul(x_flat, means)
result = tf.reshape(result, x_shape[:-1] + [hparams.hidden_size])
return result
|
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Simple undiscretization from vector quantized representation.
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/transformer_nat.py#L110-L118
|
train
|
Simple undiscretization from vector quantized representation.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101110 + 0o1) + '\063' + chr(0b110001) + chr(870 - 818), 0o10), ehT0Px3KOsy9(chr(389 - 341) + chr(0b110110 + 0o71) + chr(51) + chr(49) + '\062', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b100011 + 0o114) + chr(0b110010) + chr(0b1101 + 0o50) + chr(49), 19041 - 19033), ehT0Px3KOsy9('\060' + chr(111) + '\063' + chr(0b10111 + 0o37) + chr(54), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(7391 - 7280) + chr(498 - 448) + chr(535 - 483) + '\x30', 0o10), ehT0Px3KOsy9(chr(886 - 838) + chr(0b1100010 + 0o15) + chr(50) + chr(0b110011) + chr(0b10001 + 0o43), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001 + 0o0) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\064' + '\x36', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101101 + 0o6) + chr(688 - 635) + '\x34', ord("\x08")), ehT0Px3KOsy9('\060' + chr(9682 - 9571) + '\x33' + chr(48) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + chr(11938 - 11827) + chr(0b10011 + 0o42) + '\x33', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\065', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(1855 - 1805) + chr(0b11101 + 0o31) + '\066', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + chr(0b110000) + chr(0b100001 + 0o21), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(1217 - 1168) + chr(0b110010) + chr(874 - 820), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + '\061' + chr(53), 42891 - 42883), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(0b1101101 + 0o2) + chr(1696 - 1645) + '\064' + chr(51), 0o10), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(111) + chr(0b110001) + '\066' + chr(50), 2765 - 2757), ehT0Px3KOsy9(chr(1015 - 967) + chr(111) + chr(335 - 285) + '\x37' + chr(0b100 + 0o57), 0b1000), ehT0Px3KOsy9(chr(48) + chr(9594 - 9483) + '\x33' + chr(0b11010 + 0o31), 0o10), ehT0Px3KOsy9(chr(448 - 400) + chr(0b1101111) + '\x37' + chr(2890 - 2835), 0o10), ehT0Px3KOsy9('\x30' + chr(9118 - 9007) + chr(51) + chr(53) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100010 + 0o15) + chr(0b110001) + '\x33' + '\061', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101011 + 0o4) + chr(302 - 251) + chr(0b110100) + '\064', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + '\066' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + '\062' + chr(49), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b101111 + 0o10) + chr(0b1001 + 0o52), 0b1000), ehT0Px3KOsy9(chr(929 - 881) + chr(111) + chr(1395 - 1345) + chr(0b101101 + 0o7) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50) + chr(0b101 + 0o56) + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110010) + '\x32' + '\060', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(4788 - 4677) + chr(0b110001 + 0o1) + chr(51) + '\x32', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + '\x31' + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(111) + chr(54) + chr(377 - 329), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + chr(52) + chr(49), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(55) + chr(0b110000), 24129 - 24121), ehT0Px3KOsy9('\060' + chr(0b110101 + 0o72) + chr(0b10001 + 0o41) + chr(0b110010) + chr(0b110000), 8), ehT0Px3KOsy9('\060' + '\157' + chr(49) + '\x36' + chr(49), 46025 - 46017), ehT0Px3KOsy9('\060' + chr(4072 - 3961) + chr(0b110011) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + '\x32' + chr(0b10000 + 0o45), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b100101 + 0o112) + chr(51) + '\x37' + chr(548 - 493), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100000 + 0o25) + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xe2'), chr(6882 - 6782) + chr(101) + chr(0b1100011) + chr(111) + '\144' + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + '\146' + '\x2d' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ix49FQPz8XkJ(OeWW0F1dBPRQ, n4ljua2gi1Pr):
QQEXXbdZyz6m = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
MyjCWd_3JWq1 = ehT0Px3KOsy9(chr(48) + chr(111) + '\x32', 0o10) ** n4ljua2gi1Pr.bottleneck_bits
XCAIkNRdiX0I = n4ljua2gi1Pr.XCAIkNRdiX0I
mstS6zVd22Jf = IDJ2eXGCBCDu.reshape(OeWW0F1dBPRQ, [-ehT0Px3KOsy9(chr(2242 - 2194) + chr(111) + chr(415 - 366), ord("\x08")), MyjCWd_3JWq1])
ShZmEKfTkAOZ = IDJ2eXGCBCDu.matmul(mstS6zVd22Jf, XCAIkNRdiX0I)
ShZmEKfTkAOZ = IDJ2eXGCBCDu.reshape(ShZmEKfTkAOZ, QQEXXbdZyz6m[:-ehT0Px3KOsy9(chr(48) + '\157' + '\x31', 8)] + [n4ljua2gi1Pr.qzoyXN3kdhDL])
return ShZmEKfTkAOZ
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/transformer_nat.py
|
residual_conv
|
def residual_conv(x, repeat, k, hparams, name, reuse=None):
"""A stack of convolution blocks with residual connections."""
with tf.variable_scope(name, reuse=reuse):
dilations_and_kernels = [((1, 1), k) for _ in range(3)]
for i in range(repeat):
with tf.variable_scope("repeat_%d" % i):
y = common_layers.conv_block(
common_layers.layer_norm(x, hparams.hidden_size, name="lnorm"),
hparams.hidden_size,
dilations_and_kernels,
padding="SAME",
name="residual_conv")
y = tf.nn.dropout(y, 1.0 - hparams.dropout)
x += y
return x
|
python
|
def residual_conv(x, repeat, k, hparams, name, reuse=None):
"""A stack of convolution blocks with residual connections."""
with tf.variable_scope(name, reuse=reuse):
dilations_and_kernels = [((1, 1), k) for _ in range(3)]
for i in range(repeat):
with tf.variable_scope("repeat_%d" % i):
y = common_layers.conv_block(
common_layers.layer_norm(x, hparams.hidden_size, name="lnorm"),
hparams.hidden_size,
dilations_and_kernels,
padding="SAME",
name="residual_conv")
y = tf.nn.dropout(y, 1.0 - hparams.dropout)
x += y
return x
|
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A stack of convolution blocks with residual connections.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/transformer_nat.py#L121-L135
|
train
|
A stack of convolution blocks with residual connections.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(4353 - 4242) + chr(219 - 166) + '\x35', 1842 - 1834), ehT0Px3KOsy9('\060' + chr(0b1001010 + 0o45) + '\x31' + '\064' + '\x34', 0b1000), ehT0Px3KOsy9(chr(329 - 281) + chr(0b1 + 0o156) + chr(403 - 354) + chr(50) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b11101 + 0o25) + chr(0b110000) + '\065', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + chr(0b11100 + 0o27) + '\x36', 0o10), ehT0Px3KOsy9(chr(1316 - 1268) + chr(10848 - 10737) + chr(0b110011) + chr(0b110001) + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(1552 - 1500) + chr(0b110000), 1871 - 1863), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(7494 - 7383) + chr(0b11101 + 0o26) + '\x30' + '\063', 3966 - 3958), ehT0Px3KOsy9(chr(48) + chr(2935 - 2824) + chr(51) + chr(236 - 181), 64288 - 64280), ehT0Px3KOsy9('\x30' + chr(0b1100011 + 0o14) + chr(48), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b10110 + 0o33) + chr(0b100011 + 0o23) + chr(0b110110), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b100000 + 0o25) + chr(2527 - 2476), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(646 - 597) + chr(1369 - 1315) + chr(0b110000), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + chr(1726 - 1671) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(724 - 676) + chr(0b1101111) + '\062' + chr(830 - 778) + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1011111 + 0o20) + chr(1183 - 1133) + '\x33' + '\064', 0o10), ehT0Px3KOsy9(chr(478 - 430) + chr(111) + chr(51) + '\x34' + '\x30', 56059 - 56051), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(49) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(0b1101111) + chr(0b110100) + chr(0b111 + 0o52), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1393 - 1342) + '\060' + '\062', 13059 - 13051), ehT0Px3KOsy9(chr(2161 - 2113) + '\157' + chr(0b11010 + 0o30) + chr(2740 - 2687), 0o10), ehT0Px3KOsy9(chr(1531 - 1483) + chr(111) + chr(51) + chr(48) + '\x32', 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1152 - 1097) + '\x33', 35959 - 35951), ehT0Px3KOsy9(chr(1262 - 1214) + chr(3854 - 3743) + chr(0b110011) + chr(52) + chr(222 - 170), 0b1000), ehT0Px3KOsy9(chr(853 - 805) + '\157' + chr(0b101001 + 0o12) + chr(48) + chr(1047 - 996), 8), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + '\062' + chr(0b10011 + 0o41), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001) + '\x36' + '\065', 0o10), ehT0Px3KOsy9(chr(1700 - 1652) + chr(0b1100010 + 0o15) + chr(50) + chr(55) + '\x33', 0o10), ehT0Px3KOsy9('\x30' + chr(6212 - 6101) + chr(0b100100 + 0o17) + chr(49), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\067' + chr(51), 8), ehT0Px3KOsy9(chr(0b110000) + chr(6885 - 6774) + '\062' + chr(0b11011 + 0o30) + chr(0b101000 + 0o13), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + chr(0b110101) + chr(55), 19850 - 19842), ehT0Px3KOsy9(chr(2118 - 2070) + chr(0b1000111 + 0o50) + chr(537 - 487) + '\063' + chr(0b100111 + 0o12), 40817 - 40809), ehT0Px3KOsy9(chr(0b110000) + chr(7284 - 7173) + chr(0b110001) + '\065' + chr(48), 0o10), ehT0Px3KOsy9(chr(2101 - 2053) + chr(0b101 + 0o152) + chr(49) + chr(0b11000 + 0o35), 0b1000), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b111011 + 0o64) + chr(0b10101 + 0o34) + '\061', 22112 - 22104), ehT0Px3KOsy9(chr(1752 - 1704) + chr(0b1101000 + 0o7) + chr(0b110001) + '\x33' + chr(49), 0o10), ehT0Px3KOsy9(chr(1930 - 1882) + chr(0b1101111) + chr(0b100101 + 0o16) + chr(53) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b1010 + 0o46) + '\157' + '\062' + chr(0b10011 + 0o40) + chr(49), 8), ehT0Px3KOsy9(chr(48) + chr(0b1011001 + 0o26) + chr(49) + '\063' + '\061', 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b1000 + 0o50) + '\x6f' + chr(1415 - 1362) + chr(0b101011 + 0o5), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x03'), '\x64' + '\x65' + '\143' + chr(111) + '\x64' + '\x65')(chr(2943 - 2826) + chr(0b1100101 + 0o17) + '\x66' + '\055' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def c7tmxGI2JxIE(OeWW0F1dBPRQ, hpyK9c505LBh, OolUPRJhRaJd, n4ljua2gi1Pr, AIvJRzLdDfgF, pmC5wdSFgdFj=None):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'[\x05"\xec\xbf\xac\xcc\xa6@s\x15D\x00\x1b'), '\144' + '\x65' + chr(0b10011 + 0o120) + chr(0b111111 + 0o60) + chr(0b1010011 + 0o21) + chr(0b1000110 + 0o37))(chr(117) + chr(116) + '\146' + '\055' + chr(584 - 528)))(AIvJRzLdDfgF, reuse=pmC5wdSFgdFj):
HfyTWMMIvuNz = [((ehT0Px3KOsy9(chr(1143 - 1095) + '\157' + chr(0b110001), 21406 - 21398), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(111) + chr(0b1110 + 0o43), 8)), OolUPRJhRaJd) for VNGQdHSFPrso in vQr8gNKaIaWE(ehT0Px3KOsy9(chr(1372 - 1324) + chr(111) + chr(1479 - 1428), 7380 - 7372))]
for WVxHKyX45z_L in vQr8gNKaIaWE(hpyK9c505LBh):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'[\x05"\xec\xbf\xac\xcc\xa6@s\x15D\x00\x1b'), '\x64' + '\145' + '\143' + chr(0b1101111) + '\x64' + chr(0b1100101))(chr(8644 - 8527) + '\x74' + chr(102) + '\055' + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'_\x01 \xe0\xbf\xba\xff\xe6{'), chr(7172 - 7072) + chr(101) + chr(0b11110 + 0o105) + chr(111) + '\144' + chr(10193 - 10092))(chr(117) + '\164' + '\x66' + chr(45) + chr(0b100101 + 0o23)) % WVxHKyX45z_L):
SqiSOtYOqOJH = jSKPaHwSAfVv.conv_block(jSKPaHwSAfVv.layer_norm(OeWW0F1dBPRQ, n4ljua2gi1Pr.qzoyXN3kdhDL, name=xafqLlk3kkUe(SXOLrMavuUCe(b'A\n?\xf7\xb3'), chr(0b1100100) + '\145' + chr(99) + chr(0b1101111) + chr(6701 - 6601) + '\145')(chr(0b100001 + 0o124) + chr(0b1010111 + 0o35) + '\x66' + chr(45) + chr(56))), n4ljua2gi1Pr.qzoyXN3kdhDL, HfyTWMMIvuNz, padding=xafqLlk3kkUe(SXOLrMavuUCe(b'~%\x1d\xc0'), '\144' + chr(0b1100101) + '\x63' + '\x6f' + chr(3514 - 3414) + '\x65')('\165' + chr(0b1110100) + chr(0b1100110) + chr(0b11010 + 0o23) + '\x38'), name=xafqLlk3kkUe(SXOLrMavuUCe(b'_\x01#\xec\xba\xbb\xc1\xaf@c\x19E\x06'), '\x64' + '\145' + chr(2074 - 1975) + chr(0b101101 + 0o102) + chr(0b111 + 0o135) + chr(0b110010 + 0o63))(chr(0b1110101) + chr(11660 - 11544) + chr(5468 - 5366) + chr(0b101101) + chr(1141 - 1085)))
SqiSOtYOqOJH = IDJ2eXGCBCDu.nn.ag0mwEgWzjYv(SqiSOtYOqOJH, 1.0 - n4ljua2gi1Pr.ag0mwEgWzjYv)
OeWW0F1dBPRQ += SqiSOtYOqOJH
return OeWW0F1dBPRQ
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/transformer_nat.py
|
decompress_step
|
def decompress_step(source, hparams, first_relu, name):
"""Decompression function."""
with tf.variable_scope(name):
shape = common_layers.shape_list(source)
multiplier = 2
kernel = (1, 1)
thicker = common_layers.conv_block(
source,
hparams.hidden_size * multiplier, [((1, 1), kernel)],
first_relu=first_relu,
name="decompress_conv")
return tf.reshape(thicker, [shape[0], shape[1] * 2, 1, hparams.hidden_size])
|
python
|
def decompress_step(source, hparams, first_relu, name):
"""Decompression function."""
with tf.variable_scope(name):
shape = common_layers.shape_list(source)
multiplier = 2
kernel = (1, 1)
thicker = common_layers.conv_block(
source,
hparams.hidden_size * multiplier, [((1, 1), kernel)],
first_relu=first_relu,
name="decompress_conv")
return tf.reshape(thicker, [shape[0], shape[1] * 2, 1, hparams.hidden_size])
|
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] |
Decompression function.
|
[
"Decompression",
"function",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/transformer_nat.py#L138-L149
|
train
|
Decompression function.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(3992 - 3881) + '\x33' + '\x33' + chr(232 - 184), 0b1000), ehT0Px3KOsy9(chr(319 - 271) + chr(0b1011110 + 0o21) + '\063' + chr(1045 - 996) + chr(54), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b100000 + 0o22) + '\x37' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(0b1100 + 0o45) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + chr(2331 - 2281) + '\063', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + chr(328 - 274) + '\x32', 4611 - 4603), ehT0Px3KOsy9('\060' + chr(111) + '\x32' + chr(0b100000 + 0o23) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b10011 + 0o134) + chr(2340 - 2290) + chr(0b110101) + chr(0b1 + 0o63), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101101 + 0o2) + '\x33' + '\x32' + '\x33', 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + chr(0b110110), 0o10), ehT0Px3KOsy9('\x30' + chr(11232 - 11121) + '\x33' + '\062' + chr(52), 38042 - 38034), ehT0Px3KOsy9(chr(48) + chr(10120 - 10009) + chr(0b110101) + '\067', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001) + chr(0b110110) + '\x34', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(1495 - 1446) + chr(52) + chr(1582 - 1534), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(664 - 613) + '\066' + chr(301 - 246), ord("\x08")), ehT0Px3KOsy9(chr(0b100000 + 0o20) + '\x6f' + '\064' + chr(1011 - 962), 8501 - 8493), ehT0Px3KOsy9(chr(48) + chr(7904 - 7793) + '\x36', 0b1000), ehT0Px3KOsy9(chr(1493 - 1445) + chr(0b1101111 + 0o0) + chr(0b110010) + chr(0b11100 + 0o30) + '\x36', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1100000 + 0o17) + chr(0b110001) + '\x36' + '\x33', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100000 + 0o22) + '\x33' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1101111) + chr(54) + chr(65 - 10), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b10 + 0o60) + '\062', 5384 - 5376), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\062' + chr(0b110 + 0o56) + '\062', 0b1000), ehT0Px3KOsy9('\x30' + chr(2107 - 1996) + chr(0b110011) + '\x33' + chr(2025 - 1973), 0o10), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(111) + chr(603 - 551) + chr(0b100000 + 0o22), 27101 - 27093), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(111) + chr(0b10101 + 0o34) + chr(651 - 597) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(269 - 221) + chr(111) + chr(53) + chr(52), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + chr(50), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(897 - 846) + chr(0b110000) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(3802 - 3691) + chr(0b1101 + 0o45) + '\067' + '\063', 56091 - 56083), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + chr(50) + '\067' + chr(52), 0b1000), ehT0Px3KOsy9(chr(48) + chr(2403 - 2292) + '\063', 0o10), ehT0Px3KOsy9(chr(0b10001 + 0o37) + '\157' + '\067' + chr(0b11011 + 0o34), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x31' + '\060' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1540 - 1491) + chr(0b101110 + 0o5) + chr(2177 - 2124), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b11110 + 0o30), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + chr(0b110110) + '\067', 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011) + '\062' + chr(0b11110 + 0o31), 15177 - 15169), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(0b110001) + '\065', 0o10), ehT0Px3KOsy9(chr(1260 - 1212) + chr(0b1101111) + chr(190 - 140) + chr(0b10000 + 0o41) + chr(2090 - 2038), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1011 + 0o144) + '\x35' + chr(1067 - 1019), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf6'), chr(0b1100100) + chr(1162 - 1061) + chr(0b1100011) + '\x6f' + '\x64' + chr(776 - 675))(chr(0b1110101) + '\x74' + chr(0b11101 + 0o111) + '\x2d' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def EI3e3IdP4nk0(Qas9W3D0Xbzi, n4ljua2gi1Pr, B5W4NvHB8_yU, AIvJRzLdDfgF):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xae\xaf\xcb\xa1\xb2\xd0\xf5\xc9\x8c}\xb7@\x04\x05'), chr(9128 - 9028) + chr(101) + '\143' + chr(0b111010 + 0o65) + chr(100) + '\145')(chr(0b1111 + 0o146) + '\x74' + '\x66' + chr(45) + chr(436 - 380)))(AIvJRzLdDfgF):
nauYfLglTpcb = jSKPaHwSAfVv.shape_list(Qas9W3D0Xbzi)
S0Mp0SOoXply = ehT0Px3KOsy9(chr(621 - 573) + '\x6f' + chr(0b110010), 64191 - 64183)
iaILEoszmqXb = (ehT0Px3KOsy9('\x30' + chr(0b1001 + 0o146) + chr(1743 - 1694), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b1 + 0o60), 8))
NbjBQHAjtBee = jSKPaHwSAfVv.conv_block(Qas9W3D0Xbzi, n4ljua2gi1Pr.qzoyXN3kdhDL * S0Mp0SOoXply, [((ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x31', 8), ehT0Px3KOsy9(chr(129 - 81) + chr(0b100101 + 0o112) + '\061', 8)), iaILEoszmqXb)], first_relu=B5W4NvHB8_yU, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\xbc\xab\xda\xa7\xbe\xc2\xeb\xc9\xa0}\x8bL\x1b\x0e\x81'), chr(0b1100100) + '\x65' + '\x63' + '\157' + '\x64' + chr(101))(chr(0b111011 + 0o72) + chr(8357 - 8241) + chr(3644 - 3542) + chr(1102 - 1057) + chr(2478 - 2422)))
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xaa\xab\xca\xa0\xb2\xc2\xfc'), chr(455 - 355) + '\145' + chr(99) + '\x6f' + chr(6577 - 6477) + chr(0b11011 + 0o112))('\165' + '\164' + '\146' + '\055' + '\070'))(NbjBQHAjtBee, [nauYfLglTpcb[ehT0Px3KOsy9(chr(1396 - 1348) + chr(0b1101111) + chr(1903 - 1855), 0o10)], nauYfLglTpcb[ehT0Px3KOsy9('\060' + chr(4955 - 4844) + '\x31', 8)] * ehT0Px3KOsy9(chr(48) + '\157' + chr(50), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001 + 0o0), 8), xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa9\xb4\xd6\xb1\x8b\xfc\xaa\xc7\xb7f\x90c'), chr(0b1000000 + 0o44) + '\145' + chr(0b1001111 + 0o24) + chr(12089 - 11978) + '\144' + chr(2851 - 2750))('\x75' + chr(13446 - 13330) + chr(102) + chr(1704 - 1659) + chr(0b100011 + 0o25)))])
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/transformer_nat.py
|
compress
|
def compress(x, hparams, name):
"""Compress."""
with tf.variable_scope(name):
# Run compression by strided convs.
cur = x
k1 = (3, 1)
k2 = (2, 1)
cur = residual_conv(cur, hparams.num_compress_steps, k1, hparams, "rc")
for i in range(hparams.num_compress_steps):
cur = common_layers.conv_block(
cur,
hparams.hidden_size, [((1, 1), k2)],
strides=k2,
name="compress_%d" % i)
return cur
|
python
|
def compress(x, hparams, name):
"""Compress."""
with tf.variable_scope(name):
# Run compression by strided convs.
cur = x
k1 = (3, 1)
k2 = (2, 1)
cur = residual_conv(cur, hparams.num_compress_steps, k1, hparams, "rc")
for i in range(hparams.num_compress_steps):
cur = common_layers.conv_block(
cur,
hparams.hidden_size, [((1, 1), k2)],
strides=k2,
name="compress_%d" % i)
return cur
|
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] |
Compress.
|
[
"Compress",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/transformer_nat.py#L152-L166
|
train
|
Compress the input tensor x using strided convs.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + chr(54) + chr(0b110010), 705 - 697), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(0b101001 + 0o7), ord("\x08")), ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\157' + chr(53) + chr(975 - 925), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b11011 + 0o31) + chr(50), 1650 - 1642), ehT0Px3KOsy9(chr(48) + chr(11212 - 11101) + chr(51) + chr(0b100101 + 0o21) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x33' + '\060' + '\063', 0o10), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b100011 + 0o114) + '\x32' + chr(0b10 + 0o64) + chr(0b101111 + 0o5), 0o10), ehT0Px3KOsy9(chr(210 - 162) + '\157' + '\x37' + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b11 + 0o154) + chr(0b110011) + chr(52) + chr(0b110010), 0b1000), ehT0Px3KOsy9('\060' + chr(0b110110 + 0o71) + chr(769 - 720) + '\066' + '\x30', 34707 - 34699), ehT0Px3KOsy9(chr(0b110000) + chr(8835 - 8724) + chr(1491 - 1440) + '\x35', 0o10), ehT0Px3KOsy9(chr(1472 - 1424) + '\157' + chr(2567 - 2516) + '\x30' + chr(0b110100), 53851 - 53843), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\063' + chr(0b110101) + chr(50), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(2056 - 2007) + chr(2368 - 2316) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101010 + 0o10) + chr(0b100111 + 0o12) + '\060', 27216 - 27208), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b1100 + 0o47) + chr(510 - 458) + chr(0b10001 + 0o37), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x33' + '\x36' + chr(54 - 6), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b1001 + 0o50) + '\063' + '\061', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\x32' + '\065' + chr(0b101111 + 0o6), 1165 - 1157), ehT0Px3KOsy9(chr(524 - 476) + '\157' + chr(50) + chr(0b110011) + chr(0b110001 + 0o4), 36951 - 36943), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061' + chr(0b101100 + 0o6) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b1101111) + '\061' + chr(51) + chr(852 - 804), 17563 - 17555), ehT0Px3KOsy9(chr(0b10011 + 0o35) + '\x6f' + chr(0b110001) + chr(0b110010) + chr(0b110001), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1001101 + 0o42) + '\061' + chr(0b110011) + '\065', 9406 - 9398), ehT0Px3KOsy9(chr(48) + chr(0b101011 + 0o104) + chr(0b110011) + chr(1604 - 1552), 0b1000), ehT0Px3KOsy9(chr(1472 - 1424) + '\157' + chr(0b110011) + '\x37' + chr(53), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + '\066' + chr(0b110001), 26996 - 26988), ehT0Px3KOsy9(chr(0b110000) + chr(10527 - 10416) + chr(50) + '\066' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(1880 - 1832) + '\x6f' + chr(51) + chr(52) + '\063', 11379 - 11371), ehT0Px3KOsy9('\x30' + '\157' + '\061' + chr(0b110001) + chr(55), 60373 - 60365), ehT0Px3KOsy9('\x30' + chr(111) + '\x31' + '\x37' + chr(0b100101 + 0o17), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1010000 + 0o37) + chr(983 - 934) + chr(0b101100 + 0o13) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b10010 + 0o135) + chr(0b101001 + 0o12) + chr(0b101 + 0o57) + '\067', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001) + chr(0b10010 + 0o36) + '\x34', 0b1000), ehT0Px3KOsy9(chr(1029 - 981) + '\157' + chr(51) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + '\x30', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b100101 + 0o112) + chr(49) + chr(0b1010 + 0o50), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1100010 + 0o15) + '\x31' + chr(52) + chr(0b0 + 0o65), 7269 - 7261), ehT0Px3KOsy9('\060' + chr(0b100110 + 0o111) + chr(1291 - 1240) + chr(0b110001) + '\x34', 0o10), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\x6f' + chr(50) + chr(0b100001 + 0o20) + '\x30', 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001 + 0o4) + chr(48), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xdc'), chr(0b100 + 0o140) + '\145' + chr(4664 - 4565) + chr(111) + chr(8920 - 8820) + chr(101))(chr(0b1110000 + 0o5) + chr(116) + chr(0b1100110) + '\055' + chr(0b11 + 0o65)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def xNrsUM6GazDP(OeWW0F1dBPRQ, n4ljua2gi1Pr, AIvJRzLdDfgF):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x84yXK\x95\xa1\xd8]\xbd\x03~\xab\x9a\x04'), '\x64' + chr(8957 - 8856) + chr(7664 - 7565) + '\x6f' + chr(0b1001 + 0o133) + chr(2682 - 2581))(chr(0b1110101) + chr(0b100001 + 0o123) + chr(0b1010010 + 0o24) + chr(0b101101) + chr(0b111000)))(AIvJRzLdDfgF):
wL6S4kgnTowq = OeWW0F1dBPRQ
GSzKJmkSuLTa = (ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b1101111) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b11111 + 0o22), 0o10))
b_VHuxu0okoq = (ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(1393 - 1282) + chr(50), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b10011 + 0o36), 8))
wL6S4kgnTowq = c7tmxGI2JxIE(wL6S4kgnTowq, n4ljua2gi1Pr._y1Py7UE3OKS, GSzKJmkSuLTa, n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x80{'), chr(0b1100100) + '\145' + chr(0b1100011 + 0o0) + '\x6f' + '\144' + chr(101))('\x75' + chr(6302 - 6186) + chr(8581 - 8479) + chr(0b11010 + 0o23) + '\070'))
for WVxHKyX45z_L in vQr8gNKaIaWE(xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xada\x1br\x8d\xf4\xe1}\xd1?V\x97'), chr(7303 - 7203) + '\145' + chr(99) + '\157' + chr(8944 - 8844) + chr(5687 - 5586))(chr(117) + chr(9956 - 9840) + '\x66' + '\055' + chr(56)))):
wL6S4kgnTowq = jSKPaHwSAfVv.conv_block(wL6S4kgnTowq, n4ljua2gi1Pr.qzoyXN3kdhDL, [((ehT0Px3KOsy9(chr(48) + chr(0b101011 + 0o104) + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b1000 + 0o50) + '\x6f' + chr(0b1111 + 0o42), 8)), b_VHuxu0okoq)], strides=b_VHuxu0okoq, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x91wGR\x86\xa6\xc7K\xbdUy'), chr(0b1100100) + '\x65' + chr(8646 - 8547) + '\x6f' + chr(100) + '\x65')(chr(12555 - 12438) + chr(0b1110100) + chr(102) + '\x2d' + chr(1113 - 1057)) % WVxHKyX45z_L)
return wL6S4kgnTowq
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/transformer_nat.py
|
encode
|
def encode(x, x_space, hparams, name):
"""Transformer preparations and encoder."""
with tf.variable_scope(name):
(encoder_input, encoder_self_attention_bias,
ed) = transformer.transformer_prepare_encoder(x, x_space, hparams)
encoder_input = tf.nn.dropout(encoder_input, 1.0 - hparams.dropout)
return transformer.transformer_encoder(
encoder_input, encoder_self_attention_bias, hparams), ed
|
python
|
def encode(x, x_space, hparams, name):
"""Transformer preparations and encoder."""
with tf.variable_scope(name):
(encoder_input, encoder_self_attention_bias,
ed) = transformer.transformer_prepare_encoder(x, x_space, hparams)
encoder_input = tf.nn.dropout(encoder_input, 1.0 - hparams.dropout)
return transformer.transformer_encoder(
encoder_input, encoder_self_attention_bias, hparams), ed
|
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] |
Transformer preparations and encoder.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/transformer_nat.py#L169-L176
|
train
|
Transformer preparations and encoder.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + chr(0b110111) + chr(1703 - 1653), ord("\x08")), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(111) + chr(0b101000 + 0o13) + chr(0b110101) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\065' + chr(139 - 85), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b11011 + 0o30) + chr(0b1010 + 0o55) + chr(1637 - 1586), 0o10), ehT0Px3KOsy9('\060' + chr(7860 - 7749) + '\061' + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(10147 - 10036) + chr(0b1010 + 0o51) + chr(0b11 + 0o57) + chr(0b110000 + 0o6), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(952 - 841) + '\063' + '\062' + chr(53), 0o10), ehT0Px3KOsy9(chr(48) + chr(7515 - 7404) + chr(0b110011) + chr(575 - 521) + chr(1774 - 1726), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\061' + chr(0b110010) + '\061', 38390 - 38382), ehT0Px3KOsy9(chr(1018 - 970) + chr(6137 - 6026) + chr(1168 - 1118) + '\065' + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b1001 + 0o146) + chr(0b110011) + chr(48) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\x6f' + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + '\066' + chr(790 - 738), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011101 + 0o22) + '\x32' + '\064' + chr(53), 45451 - 45443), ehT0Px3KOsy9(chr(48) + chr(10057 - 9946) + chr(0b111 + 0o53) + '\x37' + chr(387 - 333), 0b1000), ehT0Px3KOsy9(chr(48) + chr(2127 - 2016) + chr(49) + chr(720 - 668) + '\060', 7218 - 7210), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011) + '\x30' + chr(0b111 + 0o55), ord("\x08")), ehT0Px3KOsy9(chr(1777 - 1729) + chr(0b101110 + 0o101) + '\x33' + '\063' + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(1430 - 1319) + '\063' + '\064' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b1101111) + chr(573 - 524) + chr(1361 - 1312) + '\060', 32473 - 32465), ehT0Px3KOsy9(chr(1601 - 1553) + chr(0b100110 + 0o111) + chr(0b110010) + chr(0b11 + 0o56) + chr(258 - 210), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b11001 + 0o33) + chr(2357 - 2303), 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\061' + chr(0b110001) + '\064', 28839 - 28831), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + chr(506 - 456) + chr(831 - 783), 0b1000), ehT0Px3KOsy9('\060' + chr(3250 - 3139) + chr(0b1 + 0o61) + chr(51) + chr(49), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(2562 - 2511) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + chr(716 - 666) + chr(0b110111), 35309 - 35301), ehT0Px3KOsy9(chr(0b110000) + chr(2300 - 2189) + chr(0b1110 + 0o46), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(52) + chr(1494 - 1439), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\062' + chr(0b110000 + 0o5) + '\x37', 59135 - 59127), ehT0Px3KOsy9(chr(1692 - 1644) + '\x6f' + '\x31' + chr(83 - 29) + '\061', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1011111 + 0o20) + '\062' + chr(0b100000 + 0o22), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b10110 + 0o131) + '\063' + chr(0b110011) + chr(0b10 + 0o60), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\063' + chr(0b110001) + chr(0b10101 + 0o37), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + '\063' + chr(54), 64115 - 64107), ehT0Px3KOsy9('\060' + chr(111) + '\061' + chr(561 - 510) + '\x36', 44234 - 44226), ehT0Px3KOsy9('\060' + chr(10262 - 10151) + chr(2387 - 2338) + chr(0b110111) + '\063', 57256 - 57248), ehT0Px3KOsy9(chr(551 - 503) + '\157' + chr(51) + chr(51) + '\061', 0b1000), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\157' + chr(0b110011) + chr(2142 - 2094) + chr(831 - 781), 0b1000), ehT0Px3KOsy9(chr(1223 - 1175) + '\x6f' + chr(49) + chr(2313 - 2258) + '\x36', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\157' + chr(53) + chr(0b100011 + 0o15), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'T'), chr(0b100000 + 0o104) + chr(0b1011111 + 0o6) + chr(99) + chr(111) + chr(6945 - 6845) + '\145')('\165' + chr(116) + chr(0b1000000 + 0o46) + '\x2d' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def WZINe7poqZfF(OeWW0F1dBPRQ, FcffmIwkFiZu, n4ljua2gi1Pr, AIvJRzLdDfgF):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0c\x8b\\\x92i\xb4\xb9\x95\x0e\xd8\xa4h\x84\xc0'), chr(3310 - 3210) + '\x65' + chr(0b1100011) + chr(0b1101111) + chr(6228 - 6128) + '\145')('\165' + chr(0b1101011 + 0o11) + '\146' + chr(1236 - 1191) + chr(2111 - 2055)))(AIvJRzLdDfgF):
(LDEM1Zag9l0P, cMrr2bkEBgTQ, dTXqLuPC2FBQ) = Nk9m9eKr4iuF.transformer_prepare_encoder(OeWW0F1dBPRQ, FcffmIwkFiZu, n4ljua2gi1Pr)
LDEM1Zag9l0P = IDJ2eXGCBCDu.nn.ag0mwEgWzjYv(LDEM1Zag9l0P, 1.0 - n4ljua2gi1Pr.ag0mwEgWzjYv)
return (xafqLlk3kkUe(Nk9m9eKr4iuF, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0e\x98O\x95{\xb0\xba\x82<\xce\xb5X\x91\xcb\xdd\x0f\xa0\xbd\x95'), chr(0b110 + 0o136) + chr(6692 - 6591) + chr(8975 - 8876) + chr(111) + chr(100) + chr(0b1000110 + 0o37))('\165' + chr(0b1110100) + '\x66' + '\x2d' + chr(3023 - 2967)))(LDEM1Zag9l0P, cMrr2bkEBgTQ, n4ljua2gi1Pr), dTXqLuPC2FBQ)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/transformer_nat.py
|
decode_transformer
|
def decode_transformer(encoder_output, encoder_decoder_attention_bias, targets,
hparams, name):
"""Original Transformer decoder."""
with tf.variable_scope(name):
targets = common_layers.flatten4d3d(targets)
decoder_input, decoder_self_bias = (
transformer.transformer_prepare_decoder(targets, hparams))
decoder_input = tf.nn.dropout(decoder_input,
1.0 - hparams.layer_prepostprocess_dropout)
decoder_output = transformer.transformer_decoder(
decoder_input, encoder_output, decoder_self_bias,
encoder_decoder_attention_bias, hparams)
decoder_output = tf.expand_dims(decoder_output, axis=2)
decoder_output_shape = common_layers.shape_list(decoder_output)
decoder_output = tf.reshape(
decoder_output, [decoder_output_shape[0], -1, 1, hparams.hidden_size])
# Expand since t2t expects 4d tensors.
return decoder_output
|
python
|
def decode_transformer(encoder_output, encoder_decoder_attention_bias, targets,
hparams, name):
"""Original Transformer decoder."""
with tf.variable_scope(name):
targets = common_layers.flatten4d3d(targets)
decoder_input, decoder_self_bias = (
transformer.transformer_prepare_decoder(targets, hparams))
decoder_input = tf.nn.dropout(decoder_input,
1.0 - hparams.layer_prepostprocess_dropout)
decoder_output = transformer.transformer_decoder(
decoder_input, encoder_output, decoder_self_bias,
encoder_decoder_attention_bias, hparams)
decoder_output = tf.expand_dims(decoder_output, axis=2)
decoder_output_shape = common_layers.shape_list(decoder_output)
decoder_output = tf.reshape(
decoder_output, [decoder_output_shape[0], -1, 1, hparams.hidden_size])
# Expand since t2t expects 4d tensors.
return decoder_output
|
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] |
Original Transformer decoder.
|
[
"Original",
"Transformer",
"decoder",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/transformer_nat.py#L179-L199
|
train
|
Original Transformer decoder.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b1101111) + '\061' + '\x32' + '\x30', 0o10), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(111) + chr(1669 - 1618) + '\065' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + chr(0b110011) + chr(0b1001 + 0o56), 0o10), ehT0Px3KOsy9(chr(330 - 282) + chr(0b1101111) + '\x33' + chr(0b11111 + 0o27) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b110110 + 0o71) + '\x33' + chr(0b101 + 0o62) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(1873 - 1825) + chr(0b1101111) + '\x31' + '\062' + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(873 - 825) + chr(0b111000 + 0o67) + '\061' + chr(0b100100 + 0o16) + '\x32', 43550 - 43542), ehT0Px3KOsy9(chr(1290 - 1242) + chr(0b110011 + 0o74) + '\062' + chr(1444 - 1389) + '\066', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + chr(1700 - 1648) + chr(49), 38979 - 38971), ehT0Px3KOsy9(chr(232 - 184) + chr(0b1010010 + 0o35) + chr(1767 - 1718) + '\066' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(936 - 888) + '\x6f' + chr(2451 - 2401) + '\x36' + chr(1287 - 1235), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b10000 + 0o137) + '\063' + chr(52) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(1064 - 1016) + chr(0b1100000 + 0o17) + chr(0b100011 + 0o20) + chr(0b110000 + 0o3) + chr(928 - 878), 0b1000), ehT0Px3KOsy9(chr(1123 - 1075) + '\x6f' + chr(317 - 266) + chr(0b101110 + 0o7) + chr(50), 0o10), ehT0Px3KOsy9(chr(1014 - 966) + '\157' + chr(0b10000 + 0o43) + chr(0b110101) + '\x30', 10228 - 10220), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + chr(0b100010 + 0o25), 30902 - 30894), ehT0Px3KOsy9('\x30' + chr(0b11110 + 0o121) + '\061' + chr(52) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + '\067', 0b1000), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(0b1101111) + chr(50) + chr(48) + chr(0b110110), 64470 - 64462), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + chr(0b101110 + 0o7) + chr(50), 54546 - 54538), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x32' + chr(0b1000 + 0o57) + '\063', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100010 + 0o21) + chr(559 - 508) + chr(0b11 + 0o61), 44097 - 44089), ehT0Px3KOsy9(chr(1702 - 1654) + chr(11223 - 11112) + chr(356 - 305) + chr(0b110100) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(930 - 880) + chr(0b10010 + 0o45), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + chr(52) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(111) + chr(54) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b1101111) + chr(0b110001) + chr(139 - 89) + '\x34', 550 - 542), ehT0Px3KOsy9('\x30' + chr(1692 - 1581) + '\062' + '\x32' + chr(0b100111 + 0o13), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + '\064' + chr(359 - 310), 8), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + chr(55), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1776 - 1726) + chr(2080 - 2028) + chr(52), 11623 - 11615), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110011) + chr(1697 - 1644) + '\x30', 8), ehT0Px3KOsy9(chr(1465 - 1417) + '\x6f' + chr(49) + chr(2198 - 2147) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1101111) + chr(49) + chr(1877 - 1823) + chr(0b100111 + 0o15), ord("\x08")), ehT0Px3KOsy9(chr(1279 - 1231) + '\157' + '\062' + chr(0b110000) + chr(2299 - 2249), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + chr(0b110011) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(554 - 506) + chr(111) + chr(55) + chr(0b101011 + 0o6), 0b1000), ehT0Px3KOsy9(chr(48) + chr(9705 - 9594) + chr(48), 28839 - 28831), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b11110 + 0o23) + chr(0b100010 + 0o21) + chr(50), 51268 - 51260), ehT0Px3KOsy9('\x30' + chr(111) + chr(50) + '\x34', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b11100 + 0o123) + chr(587 - 534) + '\060', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'~'), '\144' + '\x65' + chr(0b1100011) + '\x6f' + '\144' + '\x65')('\165' + '\x74' + chr(470 - 368) + '\x2d' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def LYaPq_spmQOb(NE_S2zAzN4PI, iuvkQfeRHfn5, xIEmRseySp3z, n4ljua2gi1Pr, AIvJRzLdDfgF):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'&\x8f\xad\x98\x993>\xdb\xfe\x05\xd7\x8a\xaa\x8f'), '\x64' + '\x65' + chr(99) + '\157' + chr(100) + '\145')(chr(0b1110101) + chr(116) + chr(0b1100110) + chr(0b10111 + 0o26) + '\x38'))(AIvJRzLdDfgF):
xIEmRseySp3z = jSKPaHwSAfVv.flatten4d3d(xIEmRseySp3z)
(t5Jz9byuSQ65, kBP2FfG4SUrK) = Nk9m9eKr4iuF.transformer_prepare_decoder(xIEmRseySp3z, n4ljua2gi1Pr)
t5Jz9byuSQ65 = IDJ2eXGCBCDu.nn.ag0mwEgWzjYv(t5Jz9byuSQ65, 1.0 - n4ljua2gi1Pr.RW_xSzp18UeS)
JU9Bzy7FPp94 = Nk9m9eKr4iuF.transformer_decoder(t5Jz9byuSQ65, NE_S2zAzN4PI, kBP2FfG4SUrK, iuvkQfeRHfn5, n4ljua2gi1Pr)
JU9Bzy7FPp94 = IDJ2eXGCBCDu.expand_dims(JU9Bzy7FPp94, axis=ehT0Px3KOsy9('\x30' + chr(7116 - 7005) + chr(50), ord("\x08")))
GWrLUmWe_CNL = jSKPaHwSAfVv.shape_list(JU9Bzy7FPp94)
JU9Bzy7FPp94 = IDJ2eXGCBCDu.reshape(JU9Bzy7FPp94, [GWrLUmWe_CNL[ehT0Px3KOsy9('\060' + chr(0b1011 + 0o144) + chr(48), 8)], -ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31', 6312 - 6304), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10000 + 0o41), 8), n4ljua2gi1Pr.qzoyXN3kdhDL])
return JU9Bzy7FPp94
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/transformer_nat.py
|
get_latent_pred_loss
|
def get_latent_pred_loss(latents_pred, latents_discrete_hot, hparams):
"""Latent prediction and loss."""
latents_logits = tf.layers.dense(
latents_pred, 2**hparams.bottleneck_bits, name="extra_logits")
loss = tf.nn.softmax_cross_entropy_with_logits_v2(
labels=tf.stop_gradient(latents_discrete_hot), logits=latents_logits)
return loss
|
python
|
def get_latent_pred_loss(latents_pred, latents_discrete_hot, hparams):
"""Latent prediction and loss."""
latents_logits = tf.layers.dense(
latents_pred, 2**hparams.bottleneck_bits, name="extra_logits")
loss = tf.nn.softmax_cross_entropy_with_logits_v2(
labels=tf.stop_gradient(latents_discrete_hot), logits=latents_logits)
return loss
|
[
"def",
"get_latent_pred_loss",
"(",
"latents_pred",
",",
"latents_discrete_hot",
",",
"hparams",
")",
":",
"latents_logits",
"=",
"tf",
".",
"layers",
".",
"dense",
"(",
"latents_pred",
",",
"2",
"**",
"hparams",
".",
"bottleneck_bits",
",",
"name",
"=",
"\"extra_logits\"",
")",
"loss",
"=",
"tf",
".",
"nn",
".",
"softmax_cross_entropy_with_logits_v2",
"(",
"labels",
"=",
"tf",
".",
"stop_gradient",
"(",
"latents_discrete_hot",
")",
",",
"logits",
"=",
"latents_logits",
")",
"return",
"loss"
] |
Latent prediction and loss.
|
[
"Latent",
"prediction",
"and",
"loss",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/transformer_nat.py#L202-L208
|
train
|
Get the loss for a given set of latents.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + '\157' + chr(0b101010 + 0o10) + chr(49) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(111) + '\x31' + chr(0b110011) + chr(1686 - 1635), 0o10), ehT0Px3KOsy9('\060' + chr(8442 - 8331) + chr(481 - 431) + '\x33' + '\x37', 54025 - 54017), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + chr(0b11001 + 0o36) + chr(53), 0b1000), ehT0Px3KOsy9(chr(888 - 840) + '\157' + chr(49) + '\x30' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(111) + '\067' + chr(0b110100), 2090 - 2082), ehT0Px3KOsy9(chr(1558 - 1510) + chr(111) + chr(174 - 124) + chr(0b1110 + 0o43), 35680 - 35672), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b1101111) + '\063' + chr(0b110000 + 0o6) + chr(0b110100 + 0o3), 0o10), ehT0Px3KOsy9('\060' + chr(5115 - 5004) + chr(835 - 785) + chr(49) + '\x35', 8), ehT0Px3KOsy9('\x30' + chr(9003 - 8892) + chr(0b110010) + chr(0b100101 + 0o17) + chr(49), 38967 - 38959), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51) + chr(0b100001 + 0o23) + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(189 - 138) + '\x32' + chr(0b1111 + 0o45), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + '\060' + chr(49), 0b1000), ehT0Px3KOsy9('\060' + chr(10450 - 10339) + chr(2460 - 2406) + '\x36', 0o10), ehT0Px3KOsy9(chr(2114 - 2066) + chr(11737 - 11626) + '\063' + chr(0b110100) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b1011110 + 0o21) + chr(187 - 137) + '\060' + chr(0b110100), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1140 - 1090) + chr(2260 - 2205), 63676 - 63668), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + '\x34' + '\061', 62689 - 62681), ehT0Px3KOsy9(chr(1461 - 1413) + chr(8577 - 8466) + chr(0b110011) + '\x34' + chr(1041 - 992), 8), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(3865 - 3754) + '\x30', 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\063' + chr(52) + '\x33', 6951 - 6943), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(2244 - 2195) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + chr(0b11 + 0o64), 39970 - 39962), ehT0Px3KOsy9('\060' + chr(111) + '\067' + chr(0b11011 + 0o33), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31' + chr(49) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(1647 - 1536) + chr(0b110010) + chr(509 - 456), 62077 - 62069), ehT0Px3KOsy9(chr(467 - 419) + chr(6302 - 6191) + chr(0b100111 + 0o12) + chr(1528 - 1480) + chr(1376 - 1328), 0o10), ehT0Px3KOsy9(chr(1387 - 1339) + '\157' + '\065' + '\x32', 2806 - 2798), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + chr(0b110010) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + '\064' + chr(0b101110 + 0o7), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(445 - 393) + '\067', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001) + chr(49), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063' + '\062' + '\x34', 8), ehT0Px3KOsy9(chr(0b110000) + chr(8541 - 8430) + chr(0b11111 + 0o23) + chr(2573 - 2521) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\x6f' + chr(0b10011 + 0o36) + chr(0b10100 + 0o42) + chr(0b110001), 6065 - 6057), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + '\062' + chr(50), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(54) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(1094 - 1046) + '\x6f' + chr(50) + chr(48), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(1235 - 1183) + chr(0b110111), 8), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b1101111) + chr(0b11 + 0o60) + chr(0b110101) + chr(525 - 474), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(9722 - 9611) + chr(0b110101) + chr(48), 4529 - 4521)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xa3'), chr(6585 - 6485) + '\145' + chr(6843 - 6744) + chr(111) + '\144' + chr(0b1100101 + 0o0))('\165' + chr(0b1110100) + chr(0b1100110) + chr(0b1111 + 0o36) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def As5pL7vyvA80(CGc8shFbWMSf, YsQ4jOHTeRvG, n4ljua2gi1Pr):
HljACvRa5la1 = IDJ2eXGCBCDu.layers.dense(CGc8shFbWMSf, ehT0Px3KOsy9('\060' + '\157' + '\x32', 0b1000) ** n4ljua2gi1Pr.bottleneck_bits, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\xe8#\xeb\xcf#c}\x98\xea\xc8\x94\xa7'), chr(694 - 594) + chr(101) + '\143' + chr(0b1101111) + chr(4636 - 4536) + '\x65')('\165' + '\x74' + chr(0b10010 + 0o124) + chr(0b101101) + chr(906 - 850)))
YpO0BcZ6fMsf = IDJ2eXGCBCDu.nn.softmax_cross_entropy_with_logits_v2(labels=IDJ2eXGCBCDu.stop_gradient(YsQ4jOHTeRvG), logits=HljACvRa5la1)
return YpO0BcZ6fMsf
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/transformer_nat.py
|
ae_transformer_internal
|
def ae_transformer_internal(inputs, targets, target_space, hparams, cache=None):
"""Main step used for training."""
# Encoder.
inputs = common_layers.flatten4d3d(inputs)
inputs, ed = encode(inputs, target_space, hparams, "input_enc")
# Autoencoding.
losses = {"extra": tf.constant(0.0), "latent_pred": tf.constant(0.0)}
max_targets_len_from_inputs = tf.concat([inputs, inputs], axis=1)
targets, _ = common_layers.pad_to_same_length(
targets,
max_targets_len_from_inputs,
final_length_divisible_by=2**hparams.num_compress_steps)
targets_c = compress(targets, hparams, "compress")
if hparams.mode != tf.estimator.ModeKeys.PREDICT:
# Compress and bottleneck.
latents_discrete_hot, extra_loss = vq_discrete_bottleneck(
x=targets_c, hparams=hparams)
latents_dense = vq_discrete_unbottleneck(
latents_discrete_hot, hparams=hparams)
latents_dense = targets_c + tf.stop_gradient(latents_dense - targets_c)
latents_discrete = tf.argmax(latents_discrete_hot, axis=-1)
tf.summary.histogram("codes", tf.reshape(latents_discrete[:, 0, :], [-1]))
losses["extra"] = extra_loss
# Extra loss predicting latent code from input.
latents_pred = decode_transformer(inputs, ed, latents_dense, hparams,
"extra")
latent_pred_loss = get_latent_pred_loss(latents_pred, latents_discrete_hot,
hparams)
losses["latent_pred"] = tf.reduce_mean(latent_pred_loss)
else:
latent_len = common_layers.shape_list(targets_c)[1]
embed = functools.partial(vq_discrete_unbottleneck, hparams=hparams)
latents_dense = tf.zeros_like(targets_c[:, :latent_len, :, :])
if cache is None:
cache = ae_latent_sample_beam(latents_dense, inputs, ed, embed,
hparams)
cache_hot = tf.one_hot(cache, depth=2**hparams.bottleneck_bits)
latents_dense = embed(cache_hot)
# Postprocess.
d = latents_dense
pos = tf.get_variable("pos", [1, 1000, 1, hparams.hidden_size])
pos = pos[:, :common_layers.shape_list(latents_dense)[1] + 1, :, :]
latents_dense = tf.pad(latents_dense, [[0, 0], [1, 0], [0, 0], [0, 0]]) + pos
# Decompressing the dense latents
for i in range(hparams.num_compress_steps):
j = hparams.num_compress_steps - i - 1
d = residual_conv(d, 1, (3, 1), hparams, "decompress_rc_%d" % j)
d = decompress_step(d, hparams, i > 0, "decompress_%d" % j)
masking = common_layers.inverse_lin_decay(hparams.mask_startup_steps)
masking *= common_layers.inverse_exp_decay(
hparams.mask_startup_steps // 4) # Not much at start.
masking = tf.minimum(tf.maximum(masking, 0.0), 1.0)
if hparams.mode == tf.estimator.ModeKeys.PREDICT:
masking = 1.0
mask = tf.less(masking,
tf.random_uniform(common_layers.shape_list(targets)[:-1]))
mask = tf.expand_dims(tf.to_float(mask), 3)
# targets is always [batch, length, 1, depth]
targets = mask * targets + (1.0 - mask) * d
res = decode_transformer(inputs, ed, targets, hparams, "decoder")
latent_time = tf.less(hparams.mask_startup_steps,
tf.to_int32(tf.train.get_global_step()))
losses["latent_pred"] *= tf.to_float(latent_time)
return res, losses, cache
|
python
|
def ae_transformer_internal(inputs, targets, target_space, hparams, cache=None):
"""Main step used for training."""
# Encoder.
inputs = common_layers.flatten4d3d(inputs)
inputs, ed = encode(inputs, target_space, hparams, "input_enc")
# Autoencoding.
losses = {"extra": tf.constant(0.0), "latent_pred": tf.constant(0.0)}
max_targets_len_from_inputs = tf.concat([inputs, inputs], axis=1)
targets, _ = common_layers.pad_to_same_length(
targets,
max_targets_len_from_inputs,
final_length_divisible_by=2**hparams.num_compress_steps)
targets_c = compress(targets, hparams, "compress")
if hparams.mode != tf.estimator.ModeKeys.PREDICT:
# Compress and bottleneck.
latents_discrete_hot, extra_loss = vq_discrete_bottleneck(
x=targets_c, hparams=hparams)
latents_dense = vq_discrete_unbottleneck(
latents_discrete_hot, hparams=hparams)
latents_dense = targets_c + tf.stop_gradient(latents_dense - targets_c)
latents_discrete = tf.argmax(latents_discrete_hot, axis=-1)
tf.summary.histogram("codes", tf.reshape(latents_discrete[:, 0, :], [-1]))
losses["extra"] = extra_loss
# Extra loss predicting latent code from input.
latents_pred = decode_transformer(inputs, ed, latents_dense, hparams,
"extra")
latent_pred_loss = get_latent_pred_loss(latents_pred, latents_discrete_hot,
hparams)
losses["latent_pred"] = tf.reduce_mean(latent_pred_loss)
else:
latent_len = common_layers.shape_list(targets_c)[1]
embed = functools.partial(vq_discrete_unbottleneck, hparams=hparams)
latents_dense = tf.zeros_like(targets_c[:, :latent_len, :, :])
if cache is None:
cache = ae_latent_sample_beam(latents_dense, inputs, ed, embed,
hparams)
cache_hot = tf.one_hot(cache, depth=2**hparams.bottleneck_bits)
latents_dense = embed(cache_hot)
# Postprocess.
d = latents_dense
pos = tf.get_variable("pos", [1, 1000, 1, hparams.hidden_size])
pos = pos[:, :common_layers.shape_list(latents_dense)[1] + 1, :, :]
latents_dense = tf.pad(latents_dense, [[0, 0], [1, 0], [0, 0], [0, 0]]) + pos
# Decompressing the dense latents
for i in range(hparams.num_compress_steps):
j = hparams.num_compress_steps - i - 1
d = residual_conv(d, 1, (3, 1), hparams, "decompress_rc_%d" % j)
d = decompress_step(d, hparams, i > 0, "decompress_%d" % j)
masking = common_layers.inverse_lin_decay(hparams.mask_startup_steps)
masking *= common_layers.inverse_exp_decay(
hparams.mask_startup_steps // 4) # Not much at start.
masking = tf.minimum(tf.maximum(masking, 0.0), 1.0)
if hparams.mode == tf.estimator.ModeKeys.PREDICT:
masking = 1.0
mask = tf.less(masking,
tf.random_uniform(common_layers.shape_list(targets)[:-1]))
mask = tf.expand_dims(tf.to_float(mask), 3)
# targets is always [batch, length, 1, depth]
targets = mask * targets + (1.0 - mask) * d
res = decode_transformer(inputs, ed, targets, hparams, "decoder")
latent_time = tf.less(hparams.mask_startup_steps,
tf.to_int32(tf.train.get_global_step()))
losses["latent_pred"] *= tf.to_float(latent_time)
return res, losses, cache
|
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] |
Main step used for training.
|
[
"Main",
"step",
"used",
"for",
"training",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/transformer_nat.py#L245-L316
|
train
|
Main step used for training.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + '\157' + chr(2326 - 2275) + chr(0b110110) + chr(0b110011 + 0o2), 39333 - 39325), ehT0Px3KOsy9(chr(1022 - 974) + chr(111) + chr(0b110011) + chr(0b110101) + '\065', 4691 - 4683), ehT0Px3KOsy9(chr(0b101010 + 0o6) + '\157' + chr(0b110011) + chr(0b110101), 64693 - 64685), ehT0Px3KOsy9(chr(615 - 567) + chr(11587 - 11476) + chr(49) + '\062' + '\060', 34658 - 34650), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + chr(2629 - 2574) + '\065', 40853 - 40845), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + '\x32' + '\065', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x34' + chr(1669 - 1615), 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b1101111) + '\067' + chr(406 - 356), 0b1000), ehT0Px3KOsy9('\x30' + chr(5697 - 5586) + chr(2354 - 2304) + chr(0b111 + 0o54) + chr(851 - 797), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(4915 - 4804) + chr(0b110010) + '\066' + chr(0b110101 + 0o1), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + '\x31' + chr(52), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10010 + 0o40) + chr(0b110111) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(1713 - 1665) + chr(111) + '\063' + '\063' + chr(0b111 + 0o60), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + chr(67 - 13) + chr(51), 2428 - 2420), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b101001 + 0o12) + chr(54) + '\x36', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b10111 + 0o130) + chr(0b11010 + 0o32) + chr(0b100001 + 0o25), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51) + '\062' + chr(194 - 144), 0o10), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(2105 - 1994) + chr(0b110011) + chr(0b10000 + 0o41) + chr(49), 38704 - 38696), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b101101 + 0o5) + '\x32' + '\062', 30004 - 29996), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + chr(48), 0o10), ehT0Px3KOsy9('\060' + chr(0b100110 + 0o111) + chr(0b110001) + chr(49) + '\063', 25195 - 25187), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(111) + chr(0b110001) + chr(1343 - 1293) + '\065', 8), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(48) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(111) + chr(2203 - 2153) + chr(51), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + '\x35' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(1342 - 1294) + chr(0b1101111) + '\x34' + chr(726 - 672), 8), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(8203 - 8092) + chr(49) + '\x34' + chr(0b100001 + 0o17), 0b1000), ehT0Px3KOsy9(chr(851 - 803) + chr(0b1011111 + 0o20) + '\062' + chr(68 - 18) + chr(1118 - 1064), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1001111 + 0o40) + '\x32' + '\065' + chr(48), 0b1000), ehT0Px3KOsy9(chr(1910 - 1862) + chr(10345 - 10234) + chr(0b10 + 0o64), ord("\x08")), ehT0Px3KOsy9(chr(577 - 529) + chr(0b1101111) + chr(50) + '\x37' + '\x32', 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(1892 - 1842) + chr(2221 - 2172) + chr(52), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b110110) + chr(0b1101 + 0o46), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061' + chr(0b110001) + chr(52), 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(50) + chr(2025 - 1971) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(0b1101111) + chr(227 - 177) + '\x33', 8), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1101111) + chr(51) + chr(0b111 + 0o60) + chr(0b110010), 22237 - 22229), ehT0Px3KOsy9('\060' + chr(0b1011100 + 0o23) + chr(51) + chr(0b110101) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b101000 + 0o107) + chr(55) + chr(0b10001 + 0o41), 8), ehT0Px3KOsy9(chr(1088 - 1040) + '\x6f' + chr(1997 - 1947) + '\061' + '\067', 16392 - 16384)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b1001101 + 0o42) + '\065' + chr(1344 - 1296), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xdb'), chr(5530 - 5430) + chr(0b1100101) + chr(99) + chr(111) + chr(0b1100100) + chr(0b1010111 + 0o16))('\165' + chr(116) + chr(102) + chr(0b11001 + 0o24) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def IxhIKnhOVf_A(vXoupepMtCXU, xIEmRseySp3z, uFIGUtii6RGG, n4ljua2gi1Pr, j1lPDdxcDbRB=None):
vXoupepMtCXU = jSKPaHwSAfVv.flatten4d3d(vXoupepMtCXU)
(vXoupepMtCXU, dTXqLuPC2FBQ) = WZINe7poqZfF(vXoupepMtCXU, uFIGUtii6RGG, n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9c\x83m%\t\nCT\xfd'), chr(0b1100100) + chr(0b1100101) + chr(3525 - 3426) + chr(0b110001 + 0o76) + chr(5432 - 5332) + chr(0b100111 + 0o76))(chr(0b1110101) + chr(0b1101110 + 0o6) + '\x66' + chr(1590 - 1545) + '\x38'))
eJKWkHA7qzlZ = {xafqLlk3kkUe(SXOLrMavuUCe(b'\x90\x95i"\x1c'), chr(100) + chr(0b1100101) + chr(0b1100011) + chr(248 - 137) + '\x64' + '\145')('\x75' + chr(0b1110100) + chr(0b1100110) + chr(0b100011 + 0o12) + '\x38'): IDJ2eXGCBCDu.constant(0.0), xafqLlk3kkUe(SXOLrMavuUCe(b'\x99\x8ci5\x13!yJ\xec\xd3('), chr(0b101001 + 0o73) + chr(0b1100101) + chr(0b1100011) + '\157' + '\144' + chr(0b1100101))(chr(9379 - 9262) + chr(0b10110 + 0o136) + '\x66' + chr(45) + chr(2900 - 2844)): IDJ2eXGCBCDu.constant(0.0)}
P17OAtyVwBhU = IDJ2eXGCBCDu.concat([vXoupepMtCXU, vXoupepMtCXU], axis=ehT0Px3KOsy9(chr(1788 - 1740) + chr(111) + chr(0b10111 + 0o32), 4360 - 4352))
(xIEmRseySp3z, VNGQdHSFPrso) = jSKPaHwSAfVv.pad_to_same_length(xIEmRseySp3z, P17OAtyVwBhU, final_length_divisible_by=ehT0Px3KOsy9('\x30' + chr(111) + '\x32', 0o10) ** n4ljua2gi1Pr._y1Py7UE3OKS)
i6WtNO7U6Bue = xNrsUM6GazDP(xIEmRseySp3z, n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x96\x82p \x0f0UI'), '\144' + '\145' + chr(0b1010 + 0o131) + chr(0b1101111) + '\144' + chr(0b1100101))(chr(0b1110101) + chr(0b1100101 + 0o17) + chr(0b1100110) + chr(507 - 462) + chr(0b111000)))
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x98\x82y5'), chr(8985 - 8885) + chr(101) + chr(0b1100011) + chr(0b110001 + 0o76) + '\144' + '\145')(chr(10091 - 9974) + '\x74' + '\146' + chr(0b101101) + chr(231 - 175))) != xafqLlk3kkUe(IDJ2eXGCBCDu.estimator.ModeKeys, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa5\xbfX\x144\x16r'), '\x64' + chr(746 - 645) + chr(0b110011 + 0o60) + chr(4871 - 4760) + chr(0b1100100) + chr(0b111110 + 0o47))(chr(0b1110101) + '\x74' + '\146' + chr(0b11010 + 0o23) + chr(1969 - 1913))):
(YsQ4jOHTeRvG, OyYXdGmcLv7F) = AA7HUoEwKt_Y(x=i6WtNO7U6Bue, hparams=n4ljua2gi1Pr)
dyezpTDvdVyF = ix49FQPz8XkJ(YsQ4jOHTeRvG, hparams=n4ljua2gi1Pr)
dyezpTDvdVyF = i6WtNO7U6Bue + IDJ2eXGCBCDu.stop_gradient(dyezpTDvdVyF - i6WtNO7U6Bue)
z2Exq_eUlctN = IDJ2eXGCBCDu.argmax(YsQ4jOHTeRvG, axis=-ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b101010 + 0o105) + chr(0b110001), 8))
xafqLlk3kkUe(IDJ2eXGCBCDu.summary, xafqLlk3kkUe(SXOLrMavuUCe(b'\xaa\xa9)\n\nlDN\xcb\xe29\xeb'), '\144' + chr(0b100 + 0o141) + chr(8932 - 8833) + chr(111) + chr(0b110010 + 0o62) + chr(3872 - 3771))('\x75' + chr(116) + chr(102) + chr(0b100100 + 0o11) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x96\x82y5\x0e'), '\144' + chr(0b101111 + 0o66) + chr(0b11100 + 0o107) + '\157' + '\144' + chr(1649 - 1548))(chr(0b110000 + 0o105) + chr(0b1110100) + '\x66' + chr(1277 - 1232) + '\x38'), xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x87\x88n8\x1c%C'), chr(8233 - 8133) + chr(101) + chr(99) + chr(0b0 + 0o157) + chr(100) + chr(101))(chr(0b1110101) + '\x74' + chr(2574 - 2472) + '\x2d' + chr(0b101010 + 0o16)))(z2Exq_eUlctN[:, ehT0Px3KOsy9(chr(48) + chr(12215 - 12104) + chr(48), ord("\x08")), :], [-ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061', 8)]))
eJKWkHA7qzlZ[xafqLlk3kkUe(SXOLrMavuUCe(b'\x90\x95i"\x1c'), '\x64' + chr(2454 - 2353) + '\x63' + chr(111) + chr(0b1010011 + 0o21) + chr(0b1010001 + 0o24))(chr(811 - 694) + '\x74' + chr(0b1100001 + 0o5) + chr(45) + '\x38')] = OyYXdGmcLv7F
CGc8shFbWMSf = LYaPq_spmQOb(vXoupepMtCXU, dTXqLuPC2FBQ, dyezpTDvdVyF, n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x90\x95i"\x1c'), chr(0b1010101 + 0o17) + chr(4733 - 4632) + '\143' + '\157' + '\x64' + '\x65')('\165' + chr(116) + chr(0b10001 + 0o125) + chr(0b11100 + 0o21) + chr(0b1101 + 0o53)))
tywY_VUe399r = As5pL7vyvA80(CGc8shFbWMSf, YsQ4jOHTeRvG, n4ljua2gi1Pr)
eJKWkHA7qzlZ[xafqLlk3kkUe(SXOLrMavuUCe(b'\x99\x8ci5\x13!yJ\xec\xd3('), chr(7813 - 7713) + chr(101) + chr(0b101 + 0o136) + chr(6522 - 6411) + chr(0b1100100) + chr(0b10011 + 0o122))(chr(0b1110101) + '\164' + chr(102) + chr(1604 - 1559) + '\070')] = IDJ2eXGCBCDu.reduce_mean(tywY_VUe399r)
else:
WH1RhWxChep0 = jSKPaHwSAfVv.shape_list(i6WtNO7U6Bue)[ehT0Px3KOsy9(chr(0b110000) + chr(11792 - 11681) + chr(0b1010 + 0o47), 8)]
DSKhI6I667G0 = E6ula8_Zv1yl.partial(ix49FQPz8XkJ, hparams=n4ljua2gi1Pr)
dyezpTDvdVyF = IDJ2eXGCBCDu.zeros_like(i6WtNO7U6Bue[:, :WH1RhWxChep0, :, :])
if j1lPDdxcDbRB is None:
j1lPDdxcDbRB = Qh4xGcOn2HHI(dyezpTDvdVyF, vXoupepMtCXU, dTXqLuPC2FBQ, DSKhI6I667G0, n4ljua2gi1Pr)
WiV1WrireP9_ = IDJ2eXGCBCDu.Hq3fv4Yp0EhD(j1lPDdxcDbRB, depth=ehT0Px3KOsy9('\060' + chr(8877 - 8766) + chr(1297 - 1247), 8) ** n4ljua2gi1Pr.bottleneck_bits)
dyezpTDvdVyF = DSKhI6I667G0(WiV1WrireP9_)
pd3lxn9vqWxp = dyezpTDvdVyF
NXd0aqYJd4lK = IDJ2eXGCBCDu.get_variable(xafqLlk3kkUe(SXOLrMavuUCe(b'\x85\x82n'), '\144' + '\145' + chr(99) + chr(111) + '\x64' + chr(6784 - 6683))(chr(0b11101 + 0o130) + '\x74' + chr(0b1100 + 0o132) + chr(1494 - 1449) + chr(392 - 336)), [ehT0Px3KOsy9(chr(0b110000) + chr(4085 - 3974) + '\061', 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1398 - 1349) + chr(1858 - 1803) + '\065' + chr(937 - 889), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(5724 - 5613) + chr(0b110001), 8), n4ljua2gi1Pr.qzoyXN3kdhDL])
NXd0aqYJd4lK = NXd0aqYJd4lK[:, :jSKPaHwSAfVv.shape_list(dyezpTDvdVyF)[ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49), 8)] + ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(1244 - 1133) + chr(49), 8), :, :]
dyezpTDvdVyF = IDJ2eXGCBCDu.pad(dyezpTDvdVyF, [[ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(488 - 440), 8), ehT0Px3KOsy9(chr(1526 - 1478) + chr(4038 - 3927) + chr(0b110000), 8)], [ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1101111) + chr(0b110000), 8)], [ehT0Px3KOsy9(chr(2223 - 2175) + '\x6f' + chr(103 - 55), 8), ehT0Px3KOsy9(chr(440 - 392) + chr(0b1101111) + chr(48), 8)], [ehT0Px3KOsy9(chr(1333 - 1285) + chr(0b1111 + 0o140) + '\x30', 8), ehT0Px3KOsy9(chr(0b110000) + chr(10438 - 10327) + '\x30', 8)]]) + NXd0aqYJd4lK
for WVxHKyX45z_L in vQr8gNKaIaWE(xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xaa\x94,\x00\x04bs\x7f\xad\xf9\x07\xe9'), chr(0b1100100) + chr(733 - 632) + '\x63' + chr(0b1101111) + chr(100) + chr(0b111100 + 0o51))('\x75' + '\x74' + chr(5341 - 5239) + chr(0b101101) + chr(56)))):
tlORBuYsiw3X = n4ljua2gi1Pr._y1Py7UE3OKS - WVxHKyX45z_L - ehT0Px3KOsy9('\x30' + chr(7837 - 7726) + chr(1580 - 1531), 8)
pd3lxn9vqWxp = c7tmxGI2JxIE(pd3lxn9vqWxp, ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(9618 - 9507) + chr(0b100 + 0o55), 8), (ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b100101 + 0o16), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(2017 - 1906) + chr(1065 - 1016), 8)), n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x91\x88~?\x10%T_\xed\xc5\x13\xc8\xbc,\xd3B'), '\144' + chr(10158 - 10057) + chr(99) + '\157' + '\144' + chr(101))(chr(322 - 205) + '\164' + chr(0b1011001 + 0o15) + chr(0b101000 + 0o5) + '\x38') % tlORBuYsiw3X)
pd3lxn9vqWxp = EI3e3IdP4nk0(pd3lxn9vqWxp, n4ljua2gi1Pr, WVxHKyX45z_L > ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\060', 8), xafqLlk3kkUe(SXOLrMavuUCe(b'\x91\x88~?\x10%T_\xed\xc5\x13\x9f\xbb'), chr(100) + '\x65' + chr(99) + chr(0b1101111) + '\144' + '\x65')(chr(117) + '\x74' + chr(102) + chr(0b101101) + chr(0b111000)) % tlORBuYsiw3X)
Xc6mmmn54jv8 = jSKPaHwSAfVv.inverse_lin_decay(n4ljua2gi1Pr.mask_startup_steps)
Xc6mmmn54jv8 *= jSKPaHwSAfVv.inverse_exp_decay(n4ljua2gi1Pr.mask_startup_steps // ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110100), ord("\x08")))
Xc6mmmn54jv8 = IDJ2eXGCBCDu.minimum(IDJ2eXGCBCDu.maximum(Xc6mmmn54jv8, 0.0), 1.0)
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x98\x82y5'), chr(0b1100100) + chr(101) + '\x63' + '\x6f' + chr(0b1100100) + chr(444 - 343))('\165' + chr(12159 - 12043) + chr(0b101000 + 0o76) + '\055' + '\x38')) == xafqLlk3kkUe(IDJ2eXGCBCDu.estimator.ModeKeys, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa5\xbfX\x144\x16r'), chr(0b1001 + 0o133) + '\145' + chr(0b111110 + 0o45) + chr(10319 - 10208) + '\144' + chr(2830 - 2729))(chr(0b1000000 + 0o65) + chr(116) + '\x66' + chr(45) + chr(0b110101 + 0o3))):
Xc6mmmn54jv8 = 1.0
Iz1jSgUKZDvt = IDJ2eXGCBCDu.less(Xc6mmmn54jv8, IDJ2eXGCBCDu.random_uniform(jSKPaHwSAfVv.shape_list(xIEmRseySp3z)[:-ehT0Px3KOsy9(chr(1019 - 971) + '\157' + chr(0b110001), 8)]))
Iz1jSgUKZDvt = IDJ2eXGCBCDu.expand_dims(IDJ2eXGCBCDu.to_float(Iz1jSgUKZDvt), ehT0Px3KOsy9(chr(972 - 924) + '\157' + '\x33', 8))
xIEmRseySp3z = Iz1jSgUKZDvt * xIEmRseySp3z + (1.0 - Iz1jSgUKZDvt) * pd3lxn9vqWxp
MsbwfslwLjRO = LYaPq_spmQOb(vXoupepMtCXU, dTXqLuPC2FBQ, xIEmRseySp3z, n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x91\x88~?\x190T'), chr(100) + chr(0b1100101) + chr(3960 - 3861) + '\x6f' + chr(8463 - 8363) + '\x65')(chr(0b1110101) + chr(0b10100 + 0o140) + '\x66' + chr(455 - 410) + chr(0b111000)))
flxufY_4QFGJ = IDJ2eXGCBCDu.less(n4ljua2gi1Pr.mask_startup_steps, IDJ2eXGCBCDu.to_int32(IDJ2eXGCBCDu.train.get_global_step()))
eJKWkHA7qzlZ[xafqLlk3kkUe(SXOLrMavuUCe(b'\x99\x8ci5\x13!yJ\xec\xd3('), '\144' + '\x65' + chr(0b1100011) + '\x6f' + chr(7273 - 7173) + chr(0b1011001 + 0o14))(chr(638 - 521) + '\x74' + '\146' + chr(45) + chr(0b111000 + 0o0))] *= IDJ2eXGCBCDu.to_float(flxufY_4QFGJ)
return (MsbwfslwLjRO, eJKWkHA7qzlZ, j1lPDdxcDbRB)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/transformer_nat.py
|
transformer_nat_small
|
def transformer_nat_small():
"""Set of hyperparameters."""
hparams = transformer.transformer_small()
hparams.batch_size = 2048
hparams.learning_rate = 0.2
hparams.learning_rate_warmup_steps = 4000
hparams.num_hidden_layers = 3
hparams.hidden_size = 384
hparams.filter_size = 2048
hparams.label_smoothing = 0.0
hparams.force_full_predict = True
hparams.optimizer = "adam"
hparams.optimizer_adam_epsilon = 1e-9
hparams.optimizer_adam_beta1 = 0.9
hparams.optimizer_adam_beta2 = 0.997
hparams.add_hparam("bottleneck_kind", "vq")
hparams.add_hparam("bottleneck_bits", 12)
hparams.add_hparam("num_compress_steps", 3)
hparams.add_hparam("beta", 0.25)
hparams.add_hparam("epsilon", 1e-5)
hparams.add_hparam("decay", 0.999)
hparams.add_hparam("num_samples", 10)
hparams.add_hparam("mask_startup_steps", 50000)
return hparams
|
python
|
def transformer_nat_small():
"""Set of hyperparameters."""
hparams = transformer.transformer_small()
hparams.batch_size = 2048
hparams.learning_rate = 0.2
hparams.learning_rate_warmup_steps = 4000
hparams.num_hidden_layers = 3
hparams.hidden_size = 384
hparams.filter_size = 2048
hparams.label_smoothing = 0.0
hparams.force_full_predict = True
hparams.optimizer = "adam"
hparams.optimizer_adam_epsilon = 1e-9
hparams.optimizer_adam_beta1 = 0.9
hparams.optimizer_adam_beta2 = 0.997
hparams.add_hparam("bottleneck_kind", "vq")
hparams.add_hparam("bottleneck_bits", 12)
hparams.add_hparam("num_compress_steps", 3)
hparams.add_hparam("beta", 0.25)
hparams.add_hparam("epsilon", 1e-5)
hparams.add_hparam("decay", 0.999)
hparams.add_hparam("num_samples", 10)
hparams.add_hparam("mask_startup_steps", 50000)
return hparams
|
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Set of hyperparameters.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/transformer_nat.py#L384-L407
|
train
|
Set of hyperparameters for transformer_nat_big.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(231 - 183) + '\x6f' + chr(723 - 672) + '\060', 0o10), ehT0Px3KOsy9('\060' + chr(7670 - 7559) + '\063' + chr(2879 - 2824) + chr(0b110010), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + chr(241 - 191) + chr(2108 - 2056), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + chr(1460 - 1408) + chr(2450 - 2396), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b11011 + 0o26) + '\060' + chr(52), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(2476 - 2426) + '\x32', 33086 - 33078), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(0b1000011 + 0o54) + chr(0b110001) + chr(0b11110 + 0o31), ord("\x08")), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b10011 + 0o134) + chr(54) + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1933 - 1881) + chr(0b110010), 22590 - 22582), ehT0Px3KOsy9('\x30' + chr(0b1000110 + 0o51) + chr(0b110011) + '\060' + chr(0b101110 + 0o6), 10590 - 10582), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + chr(0b110011) + chr(51) + chr(2120 - 2070), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(50) + '\065' + chr(54), 0o10), ehT0Px3KOsy9(chr(708 - 660) + '\x6f' + '\065' + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(0b101101 + 0o5) + '\066', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b101000 + 0o12) + chr(1738 - 1688) + chr(0b11100 + 0o24), 19457 - 19449), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1899 - 1850) + chr(334 - 285) + chr(51), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001 + 0o146) + chr(0b110011) + chr(0b100100 + 0o23) + '\064', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(2032 - 1921) + chr(51) + chr(0b110001) + chr(0b110010), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\067' + chr(0b110110), 8540 - 8532), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + chr(0b110000) + chr(0b100111 + 0o17), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\062' + chr(53) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(2436 - 2385) + chr(877 - 828), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(1417 - 1367) + chr(2304 - 2249) + chr(50), 0o10), ehT0Px3KOsy9(chr(402 - 354) + chr(0b1101111) + '\x32' + '\x33' + chr(2768 - 2713), 0o10), ehT0Px3KOsy9(chr(300 - 252) + chr(111) + chr(51) + chr(0b110011) + chr(0b11100 + 0o26), 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + '\060' + chr(0b101110 + 0o6), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\066' + '\x33', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(52) + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010011 + 0o34) + '\063' + '\065' + chr(0b100001 + 0o22), 0o10), ehT0Px3KOsy9(chr(847 - 799) + chr(0b1101111) + chr(49) + '\x33' + chr(884 - 834), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b11101 + 0o26) + chr(49) + '\062', 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001 + 0o2) + '\067' + '\061', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(49) + chr(1997 - 1943) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b1001 + 0o146) + '\061' + '\x32' + '\x31', 19076 - 19068), ehT0Px3KOsy9(chr(0b110000) + chr(4367 - 4256) + chr(0b100110 + 0o14) + chr(48) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(3894 - 3783) + '\x32' + '\x37' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(662 - 614) + chr(0b1101111) + chr(0b1000 + 0o51) + chr(1028 - 974) + '\067', 64501 - 64493), ehT0Px3KOsy9(chr(48) + chr(111) + '\x31' + chr(0b11010 + 0o30) + chr(2853 - 2799), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\063' + chr(0b101100 + 0o5), 8), ehT0Px3KOsy9(chr(1091 - 1043) + '\x6f' + chr(0b1000 + 0o53) + chr(0b110111) + '\x35', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(397 - 349) + chr(0b1101111) + '\x35' + '\060', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'6'), '\144' + '\x65' + '\x63' + chr(111) + chr(0b1111 + 0o125) + chr(3000 - 2899))('\165' + chr(2525 - 2409) + chr(0b1100110) + chr(0b101101) + chr(198 - 142)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def AcmCerhucwGr():
n4ljua2gi1Pr = Nk9m9eKr4iuF.transformer_small()
n4ljua2gi1Pr.ix9dZyeAmUxY = ehT0Px3KOsy9(chr(48) + '\157' + chr(52) + chr(0b100111 + 0o11) + chr(0b110000) + chr(0b110000), ord("\x08"))
n4ljua2gi1Pr.QGSIpd_yUNzU = 0.2
n4ljua2gi1Pr.fHyhoyGmdvM9 = ehT0Px3KOsy9('\x30' + '\x6f' + '\067' + chr(1652 - 1598) + '\x34' + '\060', ord("\x08"))
n4ljua2gi1Pr.jZh5_pLUoOoZ = ehT0Px3KOsy9(chr(0b11 + 0o55) + '\157' + '\x33', 0o10)
n4ljua2gi1Pr.qzoyXN3kdhDL = ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b111100 + 0o63) + chr(802 - 748) + '\060' + '\060', 1328 - 1320)
n4ljua2gi1Pr.deybX8NJ0oEI = ehT0Px3KOsy9(chr(48) + '\157' + '\064' + chr(48) + chr(0b1111 + 0o41) + '\x30', 8)
n4ljua2gi1Pr.FSjUgdaczzRk = 0.0
n4ljua2gi1Pr.FmdIbDrE7jNj = ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(0b1001000 + 0o47) + chr(49), 12303 - 12295)
n4ljua2gi1Pr.XdKNcYRObPK3 = xafqLlk3kkUe(SXOLrMavuUCe(b'y\x9e5\xcb'), '\x64' + chr(101) + chr(0b1010001 + 0o22) + '\157' + chr(0b1100100) + chr(0b1100101))(chr(13613 - 13496) + '\x74' + chr(0b1001001 + 0o35) + '\055' + chr(56))
n4ljua2gi1Pr.o17O_bIptWdl = 1e-09
n4ljua2gi1Pr.GcOjyd7zcDH8 = 0.9
n4ljua2gi1Pr.CBOVKNT0M9cG = 0.997
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'y\x9e0\xf9,bnEC\xa9'), chr(0b1100100) + '\x65' + chr(0b1100011) + chr(0b1100011 + 0o14) + '\x64' + '\145')(chr(12150 - 12033) + '\x74' + chr(0b1100110) + chr(733 - 688) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'z\x95 \xd2(waRA\xaf\x85\xc5D\xb8\xf4'), '\144' + '\145' + chr(0b101111 + 0o64) + chr(7226 - 7115) + chr(100) + chr(101))('\x75' + chr(116) + '\x66' + '\055' + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'n\x8b'), chr(0b111000 + 0o54) + '\x65' + chr(99) + chr(9089 - 8978) + '\x64' + chr(0b1110 + 0o127))(chr(0b11 + 0o162) + chr(0b1110100) + chr(3524 - 3422) + '\x2d' + '\070'))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'y\x9e0\xf9,bnEC\xa9'), chr(100) + chr(9510 - 9409) + chr(0b10 + 0o141) + '\x6f' + chr(100) + chr(101))(chr(1238 - 1121) + chr(6886 - 6770) + '\146' + '\055' + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'z\x95 \xd2(waRA\xaf\x85\xccD\xa2\xe3'), chr(0b101011 + 0o71) + chr(101) + chr(0b100010 + 0o101) + chr(111) + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + chr(116) + chr(8000 - 7898) + chr(0b101101) + chr(0b1100 + 0o54)), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + '\x34', 0b1000))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'y\x9e0\xf9,bnEC\xa9'), chr(0b1100100) + '\145' + chr(99) + chr(0b101001 + 0o106) + '\x64' + '\145')(chr(1453 - 1336) + chr(116) + chr(0b1100010 + 0o4) + '\055' + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b"v\x8f9\xf9'}bGP\xa1\xa9\xddr\xa5\xe4.\x8c\xb9"), chr(0b1100100) + chr(0b1100101) + '\143' + chr(0b1101111) + chr(0b100111 + 0o75) + chr(101))('\x75' + chr(116) + '\x66' + chr(0b1100 + 0o41) + chr(0b111000)), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b110101 + 0o72) + '\x33', 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'y\x9e0\xf9,bnEC\xa9'), chr(100) + '\x65' + chr(99) + chr(0b1101111) + chr(100) + chr(101))(chr(3468 - 3351) + '\x74' + chr(0b1010 + 0o134) + '\055' + chr(1002 - 946)))(xafqLlk3kkUe(SXOLrMavuUCe(b'z\x9f \xc7'), chr(100) + chr(0b1011110 + 0o7) + chr(5137 - 5038) + chr(5822 - 5711) + '\144' + chr(101))('\165' + '\x74' + chr(102) + '\055' + chr(226 - 170)), 0.25)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'y\x9e0\xf9,bnEC\xa9'), chr(0b1100100) + '\145' + chr(99) + chr(532 - 421) + '\144' + chr(0b10000 + 0o125))('\165' + chr(0b110001 + 0o103) + chr(0b1100110) + '\x2d' + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b"}\x8a'\xcf(}a"), chr(100) + chr(101) + chr(0b1100011) + chr(0b1101111) + chr(100) + '\145')(chr(117) + '\164' + chr(0b0 + 0o146) + '\055' + chr(56)), 1e-05)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'y\x9e0\xf9,bnEC\xa9'), '\144' + '\145' + chr(0b1100011) + chr(0b1101111) + chr(0b10111 + 0o115) + chr(0b100011 + 0o102))(chr(0b111111 + 0o66) + '\x74' + chr(0b1100110) + chr(45) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'|\x9f7\xc7='), chr(0b110000 + 0o64) + '\145' + chr(4397 - 4298) + '\x6f' + '\x64' + chr(101))('\165' + chr(116) + chr(0b1001100 + 0o32) + '\055' + '\x38'), 0.999)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'y\x9e0\xf9,bnEC\xa9'), chr(100) + '\145' + chr(8542 - 8443) + chr(0b11100 + 0o123) + chr(1698 - 1598) + '\145')(chr(0b1110101) + chr(0b1110100) + '\x66' + '\x2d' + chr(0b10111 + 0o41)))(xafqLlk3kkUe(SXOLrMavuUCe(b'v\x8f9\xf97sbGN\xa1\xa9'), chr(0b1100 + 0o130) + '\x65' + '\x63' + chr(2793 - 2682) + chr(100) + chr(0b11001 + 0o114))(chr(117) + chr(0b1010100 + 0o40) + chr(0b11001 + 0o115) + '\x2d' + chr(2972 - 2916)), ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\157' + chr(49) + chr(1951 - 1901), 0o10))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'y\x9e0\xf9,bnEC\xa9'), chr(2699 - 2599) + '\145' + chr(99) + chr(111) + '\144' + '\145')(chr(3789 - 3672) + chr(0b1110100) + '\146' + '\055' + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b"u\x9b'\xcd\x1ba{VP\xb0\xaf\xder\xa5\xe4.\x8c\xb9"), '\144' + '\x65' + chr(0b1100011) + '\x6f' + '\144' + chr(0b1100101))('\x75' + '\x74' + chr(102) + chr(973 - 928) + '\070'), ehT0Px3KOsy9(chr(0b110000) + chr(0b110001 + 0o76) + '\x31' + chr(0b110100) + chr(0b110001) + chr(0b110101) + '\062' + '\x30', ord("\x08")))
return n4ljua2gi1Pr
|
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