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tensorflow/tensor2tensor
|
tensor2tensor/utils/data_reader.py
|
hparams_to_batching_scheme
|
def hparams_to_batching_scheme(hparams,
drop_long_sequences=False,
shard_multiplier=1,
length_multiplier=1):
"""Wrapper around _batching_scheme with hparams."""
return batching_scheme(
batch_size=hparams.batch_size,
min_length=hparams.min_length,
max_length=hparams.max_length,
min_length_bucket=hparams.min_length_bucket,
length_bucket_step=hparams.length_bucket_step,
drop_long_sequences=drop_long_sequences,
shard_multiplier=shard_multiplier,
length_multiplier=length_multiplier)
|
python
|
def hparams_to_batching_scheme(hparams,
drop_long_sequences=False,
shard_multiplier=1,
length_multiplier=1):
"""Wrapper around _batching_scheme with hparams."""
return batching_scheme(
batch_size=hparams.batch_size,
min_length=hparams.min_length,
max_length=hparams.max_length,
min_length_bucket=hparams.min_length_bucket,
length_bucket_step=hparams.length_bucket_step,
drop_long_sequences=drop_long_sequences,
shard_multiplier=shard_multiplier,
length_multiplier=length_multiplier)
|
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Wrapper around _batching_scheme with hparams.
|
[
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/data_reader.py#L167-L180
|
train
|
Wrapper around _batching_scheme with hparams.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b1101100 + 0o3) + chr(49) + chr(49) + '\x34', 60528 - 60520), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1321 - 1270) + chr(2737 - 2683) + chr(66 - 16), ord("\x08")), ehT0Px3KOsy9(chr(575 - 527) + chr(0b1101111) + chr(0b0 + 0o63) + chr(0b100000 + 0o24) + '\064', 0o10), ehT0Px3KOsy9(chr(0b100110 + 0o12) + '\x6f' + chr(51) + chr(51) + chr(52), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + chr(48) + chr(54), 49004 - 48996), ehT0Px3KOsy9('\060' + chr(3293 - 3182) + '\x34' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x34' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(0b11010 + 0o32) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + chr(0b1011 + 0o52) + chr(0b11000 + 0o33), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(49) + '\060' + chr(0b101011 + 0o12), 0o10), ehT0Px3KOsy9(chr(518 - 470) + chr(0b1101111) + chr(0b101110 + 0o4) + chr(48) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\061' + chr(285 - 237) + '\060', 0o10), ehT0Px3KOsy9(chr(1460 - 1412) + '\157' + chr(51) + chr(0b111 + 0o51) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(421 - 373) + chr(0b1101111) + '\x31' + chr(0b110010) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(1340 - 1292) + chr(10225 - 10114) + '\066' + chr(312 - 260), ord("\x08")), ehT0Px3KOsy9(chr(2226 - 2178) + chr(5149 - 5038) + '\x33' + '\x35' + chr(2676 - 2622), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + chr(702 - 653) + chr(0b101100 + 0o10), 32980 - 32972), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(2132 - 2082) + chr(0b11011 + 0o25) + chr(1927 - 1877), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + chr(55) + chr(48), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1100110 + 0o11) + '\x31' + chr(0b1 + 0o63) + chr(0b1101 + 0o44), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x34' + '\063', 30105 - 30097), ehT0Px3KOsy9('\060' + chr(0b1011111 + 0o20) + chr(50) + chr(1469 - 1415) + chr(1506 - 1451), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\063' + '\x31' + '\x30', 0o10), ehT0Px3KOsy9(chr(1676 - 1628) + chr(111) + chr(1601 - 1550) + '\x36' + '\063', 0o10), ehT0Px3KOsy9(chr(1953 - 1905) + chr(7832 - 7721) + chr(49) + chr(0b1001 + 0o50) + chr(49), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1101 + 0o52) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(0b1101111) + '\063' + chr(609 - 560) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\157' + '\x32' + chr(51) + chr(54), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + chr(0b100000 + 0o23) + chr(1002 - 953), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + '\x37' + chr(52), 13430 - 13422), ehT0Px3KOsy9('\x30' + '\157' + '\x32' + chr(1976 - 1924), 26025 - 26017), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + chr(0b110010) + chr(0b1101 + 0o47), 0b1000), ehT0Px3KOsy9(chr(1952 - 1904) + chr(0b1101111) + chr(2011 - 1962) + chr(0b10 + 0o60), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(0b110001) + chr(49), 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\061' + chr(0b110011) + '\061', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(54) + chr(0b110101), 30308 - 30300), ehT0Px3KOsy9(chr(0b110000) + chr(5423 - 5312) + chr(0b101101 + 0o4) + chr(2079 - 2024) + chr(2257 - 2209), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(2478 - 2427) + '\x33' + chr(1393 - 1344), 8), ehT0Px3KOsy9(chr(84 - 36) + chr(7426 - 7315) + '\x34' + chr(0b100 + 0o54), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + '\064' + '\067', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x35' + chr(48), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'b'), '\144' + chr(0b1100101) + chr(99) + '\x6f' + chr(9988 - 9888) + chr(0b1010001 + 0o24))(chr(0b1110101) + chr(116) + '\146' + chr(0b101101) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def E1u26WzGPIXY(n4ljua2gi1Pr, IEeQFspKnx61=ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110000), ord("\x08")), Bm1NEEhi0X9x=ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(1863 - 1814), ord("\x08")), aDkRd93pNhGr=ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49), 8)):
return JGwSmyHKQnp6(batch_size=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'%\x8a\xdd\xb8\x1c_@\xa0\x06\x10\xf8\x19'), chr(0b1100100) + '\x65' + chr(0b1100011) + chr(0b1101111) + '\144' + chr(101))(chr(0b1100101 + 0o20) + chr(0b1110100) + chr(102) + chr(0b10000 + 0o35) + '\x38')), min_length=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'!\x9b\x8a\x83*CK\x86\x1f-'), '\144' + chr(0b1100101) + chr(0b1100011) + chr(0b1011110 + 0o21) + chr(7045 - 6945) + chr(4572 - 4471))('\x75' + '\x74' + chr(102) + '\x2d' + chr(56))), max_length=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x13\x9d\xd3\xac\x10~d\x85$\x06\xd29'), chr(5232 - 5132) + chr(0b1100101) + '\143' + chr(0b1011001 + 0o26) + chr(0b1100100) + chr(5380 - 5279))('\x75' + chr(116) + chr(102) + chr(0b11101 + 0o20) + chr(56))), min_length_bucket=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b' \x9a\xae\xb1r|\x16\xd3!)\xcdr'), chr(2530 - 2430) + '\145' + '\143' + '\x6f' + chr(0b1100100) + chr(0b1100000 + 0o5))(chr(0b1110101) + chr(116) + '\x66' + chr(45) + '\070')), length_bucket_step=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b' \x97\x8a\xbb2Nz\x83\x1e&\xeb%\xb2\nG\x9a\xe9\xf2'), chr(100) + chr(7665 - 7564) + '\143' + chr(0b1101111) + chr(100) + '\x65')(chr(0b1110101) + chr(0b1000111 + 0o55) + '\x66' + chr(45) + '\x38')), drop_long_sequences=IEeQFspKnx61, shard_multiplier=Bm1NEEhi0X9x, length_multiplier=aDkRd93pNhGr)
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/data_reader.py
|
pad_for_tpu
|
def pad_for_tpu(shapes_dict, hparams, max_length):
"""Pads unknown features' dimensions for TPU."""
padded_shapes = {}
def get_filler(specified_max_length):
if not specified_max_length:
return max_length
return min(specified_max_length, max_length)
inputs_none_filler = get_filler(hparams.max_input_seq_length)
targets_none_filler = get_filler(hparams.max_target_seq_length)
def pad_one_shape(shape, none_filler):
return [
(dim if dim is not None else none_filler) for dim in shape.as_list()
]
for key, shape in six.iteritems(shapes_dict):
if key == "inputs":
padded_shapes[key] = pad_one_shape(shape, inputs_none_filler)
elif key == "targets":
padded_shapes[key] = pad_one_shape(shape, targets_none_filler)
else:
padded_shapes[key] = pad_one_shape(shape, max_length)
return padded_shapes
|
python
|
def pad_for_tpu(shapes_dict, hparams, max_length):
"""Pads unknown features' dimensions for TPU."""
padded_shapes = {}
def get_filler(specified_max_length):
if not specified_max_length:
return max_length
return min(specified_max_length, max_length)
inputs_none_filler = get_filler(hparams.max_input_seq_length)
targets_none_filler = get_filler(hparams.max_target_seq_length)
def pad_one_shape(shape, none_filler):
return [
(dim if dim is not None else none_filler) for dim in shape.as_list()
]
for key, shape in six.iteritems(shapes_dict):
if key == "inputs":
padded_shapes[key] = pad_one_shape(shape, inputs_none_filler)
elif key == "targets":
padded_shapes[key] = pad_one_shape(shape, targets_none_filler)
else:
padded_shapes[key] = pad_one_shape(shape, max_length)
return padded_shapes
|
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] |
Pads unknown features' dimensions for TPU.
|
[
"Pads",
"unknown",
"features",
"dimensions",
"for",
"TPU",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/data_reader.py#L194-L218
|
train
|
Pads unknown features dimensions for TPU.
|
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) + '\x31' + '\066' + chr(2185 - 2136), 0b1000), ehT0Px3KOsy9(chr(0b100 + 0o54) + '\157' + chr(631 - 578) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\157' + chr(0b10110 + 0o34) + chr(0b110111) + '\x30', 0o10), ehT0Px3KOsy9('\060' + chr(0b1001000 + 0o47) + '\x37' + chr(54), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x31' + '\x35', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(49) + chr(48) + chr(516 - 465), 4239 - 4231), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + chr(0b110111) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b110101 + 0o72) + chr(2293 - 2244), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(53) + chr(0b110011), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + '\x30' + chr(52), 0o10), ehT0Px3KOsy9(chr(1964 - 1916) + chr(0b111011 + 0o64) + '\x32' + '\x31' + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b110000 + 0o77) + chr(0b11011 + 0o30) + chr(0b110000) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001) + chr(0b110110) + chr(51), 35962 - 35954), ehT0Px3KOsy9(chr(48) + chr(166 - 55) + chr(0b11010 + 0o27) + chr(0b11100 + 0o24), 0o10), ehT0Px3KOsy9(chr(1778 - 1730) + chr(0b1101111) + chr(0b110010) + chr(1822 - 1772) + '\060', 40644 - 40636), ehT0Px3KOsy9(chr(1376 - 1328) + chr(0b1101111) + chr(51) + '\x36' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(917 - 869) + chr(0b100001 + 0o116) + '\066' + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110 + 0o52) + '\157' + chr(597 - 546) + '\x32' + chr(2947 - 2892), 0o10), ehT0Px3KOsy9(chr(1628 - 1580) + chr(4430 - 4319) + '\x33' + chr(2526 - 2472), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\067', 63286 - 63278), ehT0Px3KOsy9(chr(48) + chr(0b1101100 + 0o3) + '\x34' + '\066', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + chr(55) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1953 - 1903) + chr(49) + '\062', 23921 - 23913), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(0b1101111) + '\062' + '\063' + '\x33', 20211 - 20203), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110011) + chr(0b101001 + 0o14) + chr(48), 0o10), ehT0Px3KOsy9(chr(519 - 471) + chr(0b1000101 + 0o52) + chr(1546 - 1495) + chr(51) + '\x33', 0o10), ehT0Px3KOsy9(chr(1087 - 1039) + '\157' + '\062' + '\062', 63043 - 63035), ehT0Px3KOsy9(chr(1658 - 1610) + '\157' + chr(0b110010) + chr(0b11 + 0o61) + '\x33', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(733 - 683) + chr(0b101100 + 0o10) + chr(305 - 250), 12308 - 12300), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + chr(2095 - 2044) + chr(48), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\061' + chr(0b1111 + 0o42) + chr(2294 - 2243), 0b1000), ehT0Px3KOsy9(chr(1817 - 1769) + chr(111) + chr(0b110011) + chr(0b110011) + chr(48), 8), ehT0Px3KOsy9('\060' + '\157' + '\x33' + '\x33' + chr(0b101011 + 0o10), 8), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11111 + 0o24) + '\065' + '\061', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(1944 - 1889) + chr(0b100100 + 0o16), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001) + chr(54) + '\x33', 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + '\x30' + chr(54), 2528 - 2520), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + chr(0b101111 + 0o1) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b11001 + 0o30) + chr(48), 8), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1101111) + chr(50) + '\063' + '\x30', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(8498 - 8387) + chr(0b110101) + chr(0b100010 + 0o16), 44414 - 44406)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'_'), chr(0b10101 + 0o117) + chr(0b1010000 + 0o25) + chr(2944 - 2845) + chr(0b1101111) + chr(0b1000101 + 0o37) + chr(5671 - 5570))(chr(0b110101 + 0o100) + '\164' + '\x66' + chr(1061 - 1016) + chr(0b110000 + 0o10)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def JegpSfmGUFal(QxYCzzCIWGil, n4ljua2gi1Pr, _o7pVXAdOCRy):
HI4hZPL6gW9O = {}
def YadhPQsp4aIT(hPHwW1WG9_Nm):
if not hPHwW1WG9_Nm:
return _o7pVXAdOCRy
return Dx22bkKPdt5d(hPHwW1WG9_Nm, _o7pVXAdOCRy)
FlZab99xhC9o = YadhPQsp4aIT(n4ljua2gi1Pr.xa50HGLsAIaS)
i6wUdhiELKtk = YadhPQsp4aIT(n4ljua2gi1Pr.uJutLB5DfPmB)
def Kww9GScKGgtI(nauYfLglTpcb, Z4Wv_2Q8fbIr):
return [Nl_JhL3qUwSN if Nl_JhL3qUwSN is not None else Z4Wv_2Q8fbIr for Nl_JhL3qUwSN in xafqLlk3kkUe(nauYfLglTpcb, xafqLlk3kkUe(SXOLrMavuUCe(b'\x10X\xe7Rd0\x8c'), chr(0b1100100) + chr(2235 - 2134) + chr(99) + chr(111) + chr(100) + '\145')(chr(0b1101000 + 0o15) + '\164' + '\146' + chr(45) + chr(0b111000)))()]
for (K3J4ZwSlE0sT, nauYfLglTpcb) in xafqLlk3kkUe(sYby0kpfssd4, xafqLlk3kkUe(SXOLrMavuUCe(b'\x18_\xddLd7\x9dlX'), chr(0b1100100) + chr(8081 - 7980) + chr(0b101010 + 0o71) + '\x6f' + chr(0b1100100) + chr(101))(chr(0b1000000 + 0o65) + chr(0b1110100) + '\146' + chr(0b11101 + 0o20) + '\070'))(QxYCzzCIWGil):
if K3J4ZwSlE0sT == xafqLlk3kkUe(SXOLrMavuUCe(b'\x18E\xc8Ky0'), chr(0b1100100) + chr(1374 - 1273) + chr(0b1100011) + '\157' + chr(0b111101 + 0o47) + '\x65')('\x75' + chr(116) + chr(0b1000100 + 0o42) + chr(45) + chr(0b111000)):
HI4hZPL6gW9O[K3J4ZwSlE0sT] = Kww9GScKGgtI(nauYfLglTpcb, FlZab99xhC9o)
elif K3J4ZwSlE0sT == xafqLlk3kkUe(SXOLrMavuUCe(b'\x05J\xcaYh7\x8b'), chr(100) + chr(0b1100101) + '\x63' + chr(3263 - 3152) + '\144' + chr(0b1100010 + 0o3))(chr(117) + chr(0b1010100 + 0o40) + '\146' + chr(45) + '\070'):
HI4hZPL6gW9O[K3J4ZwSlE0sT] = Kww9GScKGgtI(nauYfLglTpcb, i6wUdhiELKtk)
else:
HI4hZPL6gW9O[K3J4ZwSlE0sT] = Kww9GScKGgtI(nauYfLglTpcb, _o7pVXAdOCRy)
return HI4hZPL6gW9O
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/data_reader.py
|
standardize_shapes
|
def standardize_shapes(features, batch_size=None):
"""Set the right shapes for the features."""
for fname in ["inputs", "targets"]:
if fname not in features:
continue
f = features[fname]
while len(f.get_shape()) < 4:
f = tf.expand_dims(f, axis=-1)
features[fname] = f
if batch_size:
# Ensure batch size is set on all features
for _, t in six.iteritems(features):
shape = t.get_shape().as_list()
shape[0] = batch_size
t.set_shape(t.get_shape().merge_with(shape))
# Assert shapes are fully known
t.get_shape().assert_is_fully_defined()
return features
|
python
|
def standardize_shapes(features, batch_size=None):
"""Set the right shapes for the features."""
for fname in ["inputs", "targets"]:
if fname not in features:
continue
f = features[fname]
while len(f.get_shape()) < 4:
f = tf.expand_dims(f, axis=-1)
features[fname] = f
if batch_size:
# Ensure batch size is set on all features
for _, t in six.iteritems(features):
shape = t.get_shape().as_list()
shape[0] = batch_size
t.set_shape(t.get_shape().merge_with(shape))
# Assert shapes are fully known
t.get_shape().assert_is_fully_defined()
return features
|
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] |
Set the right shapes for the features.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/data_reader.py#L240-L259
|
train
|
Set the right shapes for the features.
|
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(2033 - 1985) + chr(111) + '\x33' + '\063' + chr(48), 0o10), ehT0Px3KOsy9(chr(48) + chr(5578 - 5467) + '\x31' + chr(49) + chr(0b10101 + 0o41), 16667 - 16659), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + chr(1132 - 1083) + '\064', 0b1000), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(6112 - 6001) + chr(49) + chr(0b110110) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001) + chr(2194 - 2140) + chr(1410 - 1359), 8), ehT0Px3KOsy9('\060' + '\157' + chr(0b110010) + chr(49) + '\x36', 17146 - 17138), ehT0Px3KOsy9(chr(1608 - 1560) + chr(111) + chr(401 - 351) + '\x32' + chr(50), 25872 - 25864), ehT0Px3KOsy9(chr(48) + chr(10126 - 10015) + '\x32' + chr(2121 - 2069) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\067', 14198 - 14190), ehT0Px3KOsy9(chr(362 - 314) + chr(0b1001100 + 0o43) + '\x33' + chr(0b10000 + 0o43) + chr(0b110011), 3220 - 3212), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + chr(50) + '\060', 6136 - 6128), ehT0Px3KOsy9('\x30' + '\157' + chr(0b100110 + 0o13) + chr(53) + '\x33', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + '\067' + chr(165 - 116), 0o10), ehT0Px3KOsy9(chr(1983 - 1935) + '\x6f' + '\062' + chr(0b100000 + 0o23) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(805 - 757) + chr(111) + '\x33' + chr(0b110011) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + '\x32', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b100101 + 0o20) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(111) + '\063' + chr(721 - 668) + chr(910 - 857), 27204 - 27196), ehT0Px3KOsy9(chr(0b110000) + chr(4341 - 4230) + '\063' + '\x31' + '\067', ord("\x08")), ehT0Px3KOsy9(chr(816 - 768) + chr(111) + chr(2490 - 2439) + '\063' + chr(0b100010 + 0o24), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(119 - 66) + chr(0b11110 + 0o25), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + chr(0b101111 + 0o2) + chr(0b100011 + 0o16), 31481 - 31473), ehT0Px3KOsy9('\060' + '\157' + chr(531 - 482) + chr(0b110010) + chr(0b110 + 0o52), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1100110 + 0o11) + '\x33' + '\061' + chr(0b11110 + 0o31), 8), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(0b1101111) + chr(0b10101 + 0o35) + '\063' + chr(0b110111), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + '\067', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\062' + '\x32' + chr(0b110110), 24273 - 24265), ehT0Px3KOsy9('\x30' + chr(8156 - 8045) + '\063' + '\063' + '\x35', 53244 - 53236), ehT0Px3KOsy9('\x30' + chr(0b100011 + 0o114) + chr(0b11100 + 0o25) + '\064' + chr(1177 - 1129), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b111010 + 0o65) + chr(51) + '\061' + chr(0b110011), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(2021 - 1971) + '\060' + '\060', 22346 - 22338), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1785 - 1735) + '\x31' + chr(0b10101 + 0o36), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(1857 - 1804), 38310 - 38302), ehT0Px3KOsy9(chr(0b10 + 0o56) + '\157' + chr(0b110001) + chr(0b11010 + 0o27), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101011 + 0o4) + chr(1282 - 1233) + '\064', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b10000 + 0o137) + chr(0b110011) + '\060' + chr(636 - 582), 39127 - 39119), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011) + '\x35' + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + '\x33' + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + chr(0b1011 + 0o45) + '\064', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(2389 - 2335), 55874 - 55866)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(662 - 614) + chr(4394 - 4283) + chr(0b110101) + chr(0b110 + 0o52), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf6'), chr(2836 - 2736) + chr(0b11 + 0o142) + '\x63' + chr(0b1101111) + '\144' + '\x65')(chr(0b1110101) + '\164' + chr(0b110101 + 0o61) + '\x2d' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def czGIkBlXHzVz(EEf4r9nUvta_, ix9dZyeAmUxY=None):
for t3WbF0Ae42Pu in [xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1 \xbc\x06\x07\xfd'), chr(2702 - 2602) + '\145' + chr(0b1100011) + chr(0b1101111) + chr(0b1100100) + '\145')(chr(0b1110101) + chr(10877 - 10761) + chr(0b101110 + 0o70) + chr(45) + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xac/\xbe\x14\x16\xfa\xe1'), chr(7513 - 7413) + '\145' + '\x63' + '\157' + chr(0b100010 + 0o102) + chr(0b100100 + 0o101))(chr(0b100111 + 0o116) + chr(0b100100 + 0o120) + '\146' + chr(45) + chr(1538 - 1482))]:
if t3WbF0Ae42Pu not in EEf4r9nUvta_:
continue
EGyt1xfPT1P6 = EEf4r9nUvta_[t3WbF0Ae42Pu]
while c2A0yzQpDQB3(xafqLlk3kkUe(EGyt1xfPT1P6, xafqLlk3kkUe(SXOLrMavuUCe(b'\xbf+\xb8,\x00\xe6\xf3\xd0b'), '\x64' + '\x65' + chr(7552 - 7453) + '\x6f' + '\144' + '\x65')(chr(0b1110101) + chr(0b1110100) + chr(6032 - 5930) + chr(0b101101) + '\070'))()) < ehT0Px3KOsy9(chr(1088 - 1040) + chr(111) + chr(1296 - 1244), 0b1000):
EGyt1xfPT1P6 = IDJ2eXGCBCDu.expand_dims(EGyt1xfPT1P6, axis=-ehT0Px3KOsy9('\060' + chr(0b1101110 + 0o1) + chr(49), 0b1000))
EEf4r9nUvta_[t3WbF0Ae42Pu] = EGyt1xfPT1P6
if ix9dZyeAmUxY:
for (VNGQdHSFPrso, YeT3l7JgTbWR) in xafqLlk3kkUe(sYby0kpfssd4, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1:\xa9\x01\x1a\xfa\xf7\xcdt'), '\144' + chr(0b1000010 + 0o43) + chr(99) + '\157' + '\144' + chr(0b1100101))(chr(117) + chr(0b1110100) + chr(0b1000010 + 0o44) + '\055' + '\070'))(EEf4r9nUvta_):
nauYfLglTpcb = YeT3l7JgTbWR.get_shape().as_list()
nauYfLglTpcb[ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(0b1001100 + 0o43) + chr(0b110000), 30957 - 30949)] = ix9dZyeAmUxY
xafqLlk3kkUe(YeT3l7JgTbWR, xafqLlk3kkUe(SXOLrMavuUCe(b'\xab+\xb8,\x00\xe6\xf3\xd0b'), chr(7526 - 7426) + '\145' + chr(0b1001011 + 0o30) + chr(480 - 369) + chr(5825 - 5725) + chr(101))('\165' + chr(2941 - 2825) + chr(9991 - 9889) + chr(719 - 674) + chr(2126 - 2070)))(xafqLlk3kkUe(YeT3l7JgTbWR.get_shape(), xafqLlk3kkUe(SXOLrMavuUCe(b'\xb5+\xbe\x14\x16\xd1\xe5\xc9s\xb3'), '\x64' + chr(3598 - 3497) + chr(0b1110 + 0o125) + '\157' + chr(0b1100100) + '\145')(chr(0b1100 + 0o151) + chr(10000 - 9884) + chr(0b1100110) + chr(659 - 614) + chr(0b111000)))(nauYfLglTpcb))
xafqLlk3kkUe(YeT3l7JgTbWR.get_shape(), xafqLlk3kkUe(SXOLrMavuUCe(b'\xb9=\xbf\x16\x01\xfa\xcd\xc9t\x84\xf6\x1e\x15\xf3\xa6MJ\x88\xa9\xb7E\xac4'), chr(100) + chr(0b1010010 + 0o23) + chr(1582 - 1483) + chr(10228 - 10117) + chr(0b1011100 + 0o10) + '\x65')(chr(9896 - 9779) + '\164' + chr(0b1001100 + 0o32) + chr(0b101101) + '\x38'))()
return EEf4r9nUvta_
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/data_reader.py
|
_file_num_records_cached
|
def _file_num_records_cached(filename):
"""Return the number of TFRecords in a file."""
# Cache the result, as this is expensive to compute
if filename in _file_num_records_cache:
return _file_num_records_cache[filename]
ret = 0
for _ in tf.python_io.tf_record_iterator(filename):
ret += 1
_file_num_records_cache[filename] = ret
return ret
|
python
|
def _file_num_records_cached(filename):
"""Return the number of TFRecords in a file."""
# Cache the result, as this is expensive to compute
if filename in _file_num_records_cache:
return _file_num_records_cache[filename]
ret = 0
for _ in tf.python_io.tf_record_iterator(filename):
ret += 1
_file_num_records_cache[filename] = ret
return ret
|
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Return the number of TFRecords in a file.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/data_reader.py#L269-L278
|
train
|
Return the number of TFRecords in a 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(0b110000) + chr(0b1101111) + '\x32' + chr(0b110011) + chr(0b101111 + 0o1), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + '\x36', 16135 - 16127), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + '\067' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(74 - 25) + chr(0b10001 + 0o44), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(4543 - 4432) + chr(49) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(1450 - 1402) + chr(0b1101111) + chr(0b110011) + chr(0b10 + 0o60) + chr(0b110010), 46570 - 46562), ehT0Px3KOsy9(chr(48) + chr(3776 - 3665) + chr(0b110001) + chr(1463 - 1411) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(111) + chr(50) + chr(1910 - 1862) + chr(1229 - 1180), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + '\x32' + chr(1845 - 1791), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1010 + 0o50) + '\x32' + chr(0b110110), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(1585 - 1534) + chr(0b110000), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(2115 - 2067), ord("\x08")), ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\x6f' + chr(0b110011) + chr(0b1 + 0o66) + chr(48), 0b1000), ehT0Px3KOsy9(chr(1299 - 1251) + chr(5125 - 5014) + chr(0b110010) + chr(0b101110 + 0o10) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(6507 - 6396) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(11336 - 11225) + chr(0b10111 + 0o33) + '\x30' + '\x32', 25823 - 25815), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + '\x34' + chr(439 - 386), 0b1000), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\157' + chr(0b110001) + '\x36' + chr(0b11101 + 0o26), 63608 - 63600), ehT0Px3KOsy9('\x30' + chr(6997 - 6886) + '\x32' + chr(0b11100 + 0o25) + chr(54), 64622 - 64614), ehT0Px3KOsy9(chr(1052 - 1004) + chr(0b1001001 + 0o46) + chr(53) + chr(0b101110 + 0o2), 44715 - 44707), ehT0Px3KOsy9(chr(1881 - 1833) + '\x6f' + chr(1521 - 1467) + '\x30', 59910 - 59902), ehT0Px3KOsy9(chr(693 - 645) + chr(111) + chr(51) + chr(52) + chr(51), 8652 - 8644), ehT0Px3KOsy9('\060' + chr(111) + '\062' + chr(1554 - 1501) + chr(0b110110), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + '\062' + '\067', 0b1000), ehT0Px3KOsy9(chr(697 - 649) + chr(2545 - 2434) + '\061' + chr(0b110111) + chr(150 - 97), 23072 - 23064), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\x6f' + chr(51) + chr(52) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101000 + 0o7) + chr(0b110011) + chr(0b11111 + 0o22) + '\065', 0o10), ehT0Px3KOsy9(chr(884 - 836) + chr(111) + chr(51) + chr(683 - 629) + chr(0b101 + 0o54), 49632 - 49624), ehT0Px3KOsy9(chr(48) + chr(0b1001 + 0o146) + '\063' + '\064' + chr(0b101010 + 0o11), 8), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1005 - 954) + chr(885 - 836) + chr(0b1100 + 0o53), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b100010 + 0o115) + '\063' + chr(50) + chr(0b110010), 8), ehT0Px3KOsy9('\x30' + '\157' + '\063' + chr(0b110100) + chr(0b11110 + 0o30), 8), ehT0Px3KOsy9(chr(0b110000) + chr(3570 - 3459) + '\067' + chr(51), 0o10), ehT0Px3KOsy9(chr(1889 - 1841) + chr(4920 - 4809) + chr(0b1001 + 0o51) + chr(1698 - 1644) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(2004 - 1954) + chr(0b110011) + chr(0b101 + 0o61), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x31' + '\067' + '\x31', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b11001 + 0o126) + '\061' + chr(1567 - 1514) + chr(0b101011 + 0o12), 6476 - 6468), ehT0Px3KOsy9(chr(0b110000) + chr(1014 - 903) + '\x31' + '\x37' + '\065', 8), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1000011 + 0o54) + chr(2754 - 2700), 48644 - 48636), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(2829 - 2718) + '\x32' + '\x33' + chr(50), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(1837 - 1726) + chr(1101 - 1048) + chr(0b10000 + 0o40), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb6'), '\144' + chr(101) + '\x63' + '\x6f' + '\x64' + chr(0b1100101))('\x75' + chr(0b1110010 + 0o2) + chr(0b101000 + 0o76) + chr(0b101000 + 0o5) + chr(2717 - 2661)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ALh_uQTY0ezU(xw4DsBfIJ22E):
if xw4DsBfIJ22E in VhKjy9xuoJ8C:
return VhKjy9xuoJ8C[xw4DsBfIJ22E]
VHn4CV4Ymrei = ehT0Px3KOsy9('\060' + chr(343 - 232) + chr(0b110000), 0b1000)
for VNGQdHSFPrso in xafqLlk3kkUe(IDJ2eXGCBCDu.python_io, xafqLlk3kkUe(SXOLrMavuUCe(b'\xecx\xa1\x7fn\xb1\x0c\xf32\xc91d\x9d\xc7c\xf6\n\x01'), chr(0b1100100) + chr(101) + chr(0b11111 + 0o104) + chr(0b100100 + 0o113) + chr(100) + chr(0b1100101))(chr(674 - 557) + chr(116) + '\x66' + chr(1997 - 1952) + chr(0b111000)))(xw4DsBfIJ22E):
VHn4CV4Ymrei += ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001), 5291 - 5283)
VhKjy9xuoJ8C[xw4DsBfIJ22E] = VHn4CV4Ymrei
return VHn4CV4Ymrei
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/data_reader.py
|
pad_batch
|
def pad_batch(features, batch_multiple):
"""Pad batch dim of features to nearest multiple of batch_multiple."""
feature = list(features.items())[0][1]
batch_size = tf.shape(feature)[0]
mod = batch_size % batch_multiple
has_mod = tf.cast(tf.cast(mod, tf.bool), tf.int32)
batch_padding = batch_multiple * has_mod - mod
padded_features = {}
for k, feature in features.items():
rank = len(feature.shape)
paddings = [[0, 0] for _ in range(rank)]
paddings[0][1] = batch_padding
padded_feature = tf.pad(feature, paddings)
padded_features[k] = padded_feature
return padded_features
|
python
|
def pad_batch(features, batch_multiple):
"""Pad batch dim of features to nearest multiple of batch_multiple."""
feature = list(features.items())[0][1]
batch_size = tf.shape(feature)[0]
mod = batch_size % batch_multiple
has_mod = tf.cast(tf.cast(mod, tf.bool), tf.int32)
batch_padding = batch_multiple * has_mod - mod
padded_features = {}
for k, feature in features.items():
rank = len(feature.shape)
paddings = [[0, 0] for _ in range(rank)]
paddings[0][1] = batch_padding
padded_feature = tf.pad(feature, paddings)
padded_features[k] = padded_feature
return padded_features
|
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] |
Pad batch dim of features to nearest multiple of batch_multiple.
|
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/data_reader.py#L292-L307
|
train
|
Pad batch dim of features to nearest multiple of batch_multiple.
|
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(1728 - 1680) + '\x6f' + chr(49) + '\064', 51014 - 51006), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(504 - 453) + '\x30' + chr(0b1010 + 0o54), 54548 - 54540), ehT0Px3KOsy9(chr(1701 - 1653) + '\x6f' + chr(0b1010 + 0o53) + chr(542 - 488), 0o10), ehT0Px3KOsy9(chr(0b10000 + 0o40) + '\x6f' + '\061' + chr(0b110001 + 0o1) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\157' + chr(49) + chr(600 - 550) + chr(1375 - 1326), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011) + chr(55) + chr(0b110010), 5506 - 5498), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\062' + chr(103 - 49) + chr(0b101010 + 0o6), 42834 - 42826), ehT0Px3KOsy9('\060' + chr(0b101001 + 0o106) + '\x33' + '\065', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + '\060' + chr(52), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\065' + chr(48), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1151 - 1100) + chr(1479 - 1431), 0b1000), ehT0Px3KOsy9(chr(0b101000 + 0o10) + '\x6f' + chr(50) + chr(0b1100 + 0o44) + chr(0b101011 + 0o10), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1001011 + 0o44) + chr(0b110010) + '\x33' + chr(0b101011 + 0o13), 65419 - 65411), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(52) + '\065', 0b1000), ehT0Px3KOsy9(chr(329 - 281) + chr(0b1101111) + chr(0b101011 + 0o7) + chr(2094 - 2045) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(2285 - 2237) + chr(0b1001011 + 0o44) + chr(54) + chr(0b101011 + 0o11), ord("\x08")), ehT0Px3KOsy9(chr(1382 - 1334) + chr(0b1101111) + '\062' + chr(0b100000 + 0o27) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + '\065' + chr(0b100 + 0o54), 59950 - 59942), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(54) + chr(211 - 162), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51) + chr(0b110011), 16230 - 16222), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + chr(1295 - 1245) + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b11101 + 0o24) + chr(0b110000 + 0o5) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(0b110101) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(9407 - 9296) + '\063' + chr(1641 - 1593) + chr(0b101000 + 0o13), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(289 - 237) + chr(1267 - 1212), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + chr(1124 - 1073) + chr(1188 - 1134), 8), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1000001 + 0o56) + chr(1974 - 1925) + '\x32' + '\063', 45758 - 45750), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(0b110100) + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x36' + chr(0b110000), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010 + 0o5) + chr(1684 - 1636), 38235 - 38227), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001001 + 0o46) + chr(0b10100 + 0o40) + '\x33', 0o10), ehT0Px3KOsy9(chr(658 - 610) + '\157' + '\x32' + chr(55), 51878 - 51870), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\063' + chr(1535 - 1485) + chr(0b100101 + 0o14), 0o10), ehT0Px3KOsy9(chr(499 - 451) + '\157' + chr(0b110011 + 0o3), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(6203 - 6092) + chr(51) + '\064' + '\060', 0b1000), ehT0Px3KOsy9(chr(0b100010 + 0o16) + '\x6f' + '\x33' + '\x31' + chr(49), 0b1000), ehT0Px3KOsy9(chr(48) + chr(4758 - 4647) + '\062' + '\062', 0b1000), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(2348 - 2237) + chr(0b110011) + chr(55) + chr(1001 - 953), 0b1000), ehT0Px3KOsy9(chr(0b100 + 0o54) + '\157' + chr(2019 - 1969) + chr(48) + chr(0b110001), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(53) + chr(0b110000 + 0o0), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'"'), '\144' + '\145' + chr(0b1100011) + '\x6f' + '\x64' + chr(0b1010101 + 0o20))(chr(11519 - 11402) + chr(0b1100011 + 0o21) + chr(5510 - 5408) + '\x2d' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def _D58k8QjRlpJ(EEf4r9nUvta_, _i4P3dl8fCMX):
fVxZREPfp9Oo = YyaZ4tpXu4lf(EEf4r9nUvta_.NzveIZ3IlSH9())[ehT0Px3KOsy9(chr(48) + chr(6090 - 5979) + chr(0b100001 + 0o17), 8)][ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(111) + chr(0b110001), 0b1000)]
ix9dZyeAmUxY = IDJ2eXGCBCDu.nauYfLglTpcb(fVxZREPfp9Oo)[ehT0Px3KOsy9(chr(0b0 + 0o60) + '\x6f' + '\060', 8)]
JHJR37KvkQhF = ix9dZyeAmUxY % _i4P3dl8fCMX
DAGPKkEPUaCM = IDJ2eXGCBCDu.cast(IDJ2eXGCBCDu.cast(JHJR37KvkQhF, IDJ2eXGCBCDu.bool), IDJ2eXGCBCDu.int32)
Ck85PxId4V0k = _i4P3dl8fCMX * DAGPKkEPUaCM - JHJR37KvkQhF
nySK1Ft8Mcii = {}
for (OolUPRJhRaJd, fVxZREPfp9Oo) in xafqLlk3kkUe(EEf4r9nUvta_, xafqLlk3kkUe(SXOLrMavuUCe(b'B\xbcX3\x18\xa0\x83T({P\xba'), chr(0b1010111 + 0o15) + '\145' + '\143' + chr(0b101110 + 0o101) + '\144' + chr(0b1000110 + 0o37))(chr(0b1110101) + chr(0b1110100) + '\x66' + chr(45) + '\070'))():
SIkZeGCA53HL = c2A0yzQpDQB3(fVxZREPfp9Oo.nauYfLglTpcb)
rWQRL0c0130o = [[ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\060', 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(329 - 281), 8)] for VNGQdHSFPrso in vQr8gNKaIaWE(SIkZeGCA53HL)]
rWQRL0c0130o[ehT0Px3KOsy9(chr(0b10011 + 0o35) + '\157' + '\x30', 8)][ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(151 - 102), 8)] = Ck85PxId4V0k
P6TF3ndUvKJP = IDJ2eXGCBCDu.pad(fVxZREPfp9Oo, rWQRL0c0130o)
nySK1Ft8Mcii[OolUPRJhRaJd] = P6TF3ndUvKJP
return nySK1Ft8Mcii
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/data_reader.py
|
input_fn
|
def input_fn(dataset,
filepattern,
skip_random_fraction_when_training,
batch_size_means_tokens_param,
batch_size_multiplier,
max_length,
mode,
hparams,
data_dir=None,
params=None,
config=None,
force_repeat=False,
prevent_repeat=False):
"""Builds input pipeline for problem.
Args:
dataset: the dataset to make input function from.
filepattern: the pattern of files to read from.
skip_random_fraction_when_training: whether to skip randomly when training.
batch_size_means_tokens_param: whether batch size should mean tokens.
batch_size_multiplier: how to multiply batch size when bucketing.
max_length: maximum length,
mode: tf.estimator.ModeKeys
hparams: HParams, model hparams
data_dir: str, data directory; if None, will use hparams.data_dir
params: dict, may include "batch_size"
config: RunConfig; should have the data_parallelism attribute if not using
TPU
force_repeat: bool, whether to repeat the data even if not training
prevent_repeat: bool, whether to not repeat when in training mode.
Overrides force_repeat.
Returns:
(features_dict<str name, Tensor feature>, Tensor targets)
"""
is_training = mode == tf.estimator.ModeKeys.TRAIN
if config and config.use_tpu:
num_threads = 64
else:
num_threads = cpu_count() if is_training else 1
if config and hasattr(config,
"data_parallelism") and config.data_parallelism:
num_shards = config.data_parallelism.n
else:
num_shards = 1
mlperf_log.transformer_print(
key=mlperf_log.INPUT_MAX_LENGTH, value=max_length)
def tpu_valid_size(example):
return example_valid_size(example, hparams.min_length, max_length)
def gpu_valid_size(example):
drop_long_sequences = is_training or hparams.eval_drop_long_sequences
max_validate_length = max_length if drop_long_sequences else 10**9
return example_valid_size(example, hparams.min_length, max_validate_length)
def define_shapes(example):
batch_size = config and config.use_tpu and params["batch_size"]
return standardize_shapes(example, batch_size=batch_size)
# Read and preprocess
data_dir = data_dir or (hasattr(hparams, "data_dir") and hparams.data_dir)
if (force_repeat or is_training) and not prevent_repeat:
# Repeat and skip a random number of records
dataset = dataset.repeat()
if is_training and skip_random_fraction_when_training:
data_files = tf.contrib.slim.parallel_reader.get_data_files(filepattern)
# In continuous_train_and_eval when switching between train and
# eval, this input_fn method gets called multiple times and it
# would give you the exact same samples from the last call
# (because the Graph seed is set). So this skip gives you some
# shuffling.
dataset = skip_random_fraction(dataset, data_files[0])
dataset = dataset.map(cast_ints_to_int32, num_parallel_calls=num_threads)
if batch_size_means_tokens_param:
batch_size_means_tokens = True
else:
if _are_shapes_fully_defined(dataset.output_shapes):
batch_size_means_tokens = False
else:
tf.logging.warning(
"Shapes are not fully defined. Assuming batch_size means tokens.")
batch_size_means_tokens = True
# Batching
if not batch_size_means_tokens:
# Batch size means examples per datashard.
if config and config.use_tpu:
# on TPU, we use params["batch_size"], which specifies the number of
# examples across all datashards
batch_size = params["batch_size"]
dataset = dataset.batch(batch_size, drop_remainder=True)
else:
batch_size = hparams.batch_size * num_shards
dataset = dataset.batch(batch_size)
else:
# batch_size means tokens per datashard
if config and config.use_tpu:
dataset = dataset.filter(tpu_valid_size)
padded_shapes = pad_for_tpu(dataset.output_shapes, hparams, max_length)
# on TPU, we use params["batch_size"], which specifies the number of
# examples across all datashards
batch_size = params["batch_size"]
if hparams.pad_batch:
tf.logging.warn(
"Padding the batch to ensure that remainder eval batches are "
"processed. This may lead to incorrect metrics for "
"non-zero-padded features, e.g. images. Use a smaller batch "
"size that has no remainder in that case.")
dataset = dataset.padded_batch(
batch_size, padded_shapes, drop_remainder=False)
dataset = dataset.map(
functools.partial(pad_batch, batch_multiple=batch_size),
num_parallel_calls=num_threads)
else:
dataset = dataset.padded_batch(
batch_size, padded_shapes, drop_remainder=True)
else:
# On GPU, bucket by length
dataset = dataset.filter(gpu_valid_size)
cur_batching_scheme = hparams_to_batching_scheme(
hparams,
shard_multiplier=num_shards,
length_multiplier=batch_size_multiplier)
if hparams.use_fixed_batch_size:
# Here batch_size really means examples per datashard.
cur_batching_scheme["batch_sizes"] = [hparams.batch_size]
cur_batching_scheme["boundaries"] = []
dataset = dataset.apply(
tf.data.experimental.bucket_by_sequence_length(
example_length, cur_batching_scheme["boundaries"],
cur_batching_scheme["batch_sizes"]))
if not is_training:
batch_multiple = num_shards
if hparams.use_fixed_batch_size:
# Make sure the last batch has the same fixed size as the rest.
batch_multiple *= hparams.batch_size
if batch_multiple > 1:
tf.logging.warn(
"Padding the batch to ensure that remainder eval batches have "
"a batch size divisible by the number of data shards. This may "
"lead to incorrect metrics for non-zero-padded features, e.g. "
"images. Use a single datashard (i.e. 1 GPU) in that case.")
dataset = dataset.map(
functools.partial(pad_batch, batch_multiple=batch_multiple),
num_parallel_calls=num_threads)
dataset = dataset.map(define_shapes, num_parallel_calls=num_threads)
# Add shuffling for training batches. This is necessary along with record
# level shuffling in the dataset generation. Record shuffling will shuffle
# the examples. However, in some cases, it's possible that the shuffle
# buffer size for record shuffling is smaller than the batch size. In such
# cases, adding batch shuffling ensures that the data is in random order
# during training
if (is_training and hasattr(hparams, "batch_shuffle_size") and
hparams.batch_shuffle_size):
dataset = dataset.shuffle(hparams.batch_shuffle_size)
# Split batches into chunks if targets are too long.
# The new "chunk_number" feature is 0 for the first chunk and goes up then.
# Chunks are reversed so the 0th chunk comes first, then the 1st and so on,
# so models can attend to them in the order they arrive. The last chunk is
# usually the one containing the end of the target sentence (EOS).
chunk_length = hparams.get("split_targets_chunk_length", 0)
max_chunks = hparams.get("split_targets_max_chunks", 100)
if chunk_length > 0:
def is_nonzero_chunk(example):
"""A chunk is zero if all targets are 0s."""
return tf.less(0, tf.reduce_sum(tf.abs(example["targets"])))
def split_on_length(example):
"""Split a batch of ditcs on length."""
x = example["targets"]
# TODO(kitaev): This code breaks if chunk_length * max_chunks < batch_size
length_diff = chunk_length * max_chunks - tf.shape(x)[1]
padded_x = tf.pad(x, [(0, 0), (0, length_diff), (0, 0), (0, 0)])
chunks = [padded_x[:, i*chunk_length:(i+1)*chunk_length, :, :]
for i in range(max_chunks - 1)]
chunks.append(padded_x[:, (max_chunks - 1)*chunk_length:, :, :])
new_example = {}
# Setting chunk_number to be tf.range(max_chunks) is incompatible with TPU
new_example["chunk_number"] = tf.concat([
tf.expand_dims(tf.ones_like(c) * n, axis=0)
for n, c in enumerate(chunks)
],
axis=0)
new_example["targets"] = tf.concat(
[tf.expand_dims(c, axis=0) for c in chunks], axis=0)
for k in example:
if k != "targets":
assert k != "chunk_number", (
"Chunking code expects the chunk_number feature name to be "
"available"
)
new_example[k] = tf.concat(
[tf.expand_dims(example[k], axis=0) for _ in range(max_chunks)],
axis=0)
return tf.data.Dataset.from_tensor_slices(new_example)
dataset = dataset.flat_map(split_on_length)
dataset = dataset.filter(is_nonzero_chunk)
# The chunking data pipeline thus far creates batches of examples where all
# of the examples have the same chunk number. This can lead to periodic
# fluctuations in the loss; for example, when all examples in the batch have
# chunk number 0 the loss may be higher than midway through a sequence.
# Enabling split_targets_strided_training adjusts the data so that each
# batch includes examples at various points within a sequence.
if is_training and hparams.split_targets_strided_training:
# TODO(kitaev): make sure that shape inference works on GPU, not just TPU.
inferred_batch_size = dataset.output_shapes["targets"].as_list()[0]
if inferred_batch_size is None:
raise ValueError(
"Strided training is only implemented when the batch size can be "
"inferred statically, for example when training on TPU."
)
chunk_stride = inferred_batch_size * max(
1, max_chunks // inferred_batch_size) + 1
def collapse_nested_datasets(example):
"""Converts a dataset of datasets to a dataset of tensor features."""
new_example = {}
for k, v in example.items():
v = tf.data.experimental.get_single_element(
v.batch(inferred_batch_size, drop_remainder=True))
new_example[k] = v
return tf.data.Dataset.from_tensor_slices(new_example)
dataset = dataset.apply(tf.data.experimental.unbatch())
dataset = dataset.window(inferred_batch_size, inferred_batch_size,
chunk_stride)
dataset = dataset.flat_map(collapse_nested_datasets)
dataset = dataset.batch(inferred_batch_size, drop_remainder=True)
def prepare_for_output(example):
if not config or not config.use_tpu:
_summarize_features(example, num_shards)
if mode == tf.estimator.ModeKeys.PREDICT:
example["infer_targets"] = example.pop("targets")
return example
else:
return example, example["targets"]
dataset = dataset.map(prepare_for_output, num_parallel_calls=num_threads)
dataset = dataset.prefetch(2)
if mode == tf.estimator.ModeKeys.PREDICT:
# This is because of a bug in the Estimator that short-circuits prediction
# if it doesn't see a QueueRunner. DummyQueueRunner implements the
# minimal expected interface but does nothing.
tf.add_to_collection(tf.GraphKeys.QUEUE_RUNNERS, DummyQueueRunner())
return dataset
|
python
|
def input_fn(dataset,
filepattern,
skip_random_fraction_when_training,
batch_size_means_tokens_param,
batch_size_multiplier,
max_length,
mode,
hparams,
data_dir=None,
params=None,
config=None,
force_repeat=False,
prevent_repeat=False):
"""Builds input pipeline for problem.
Args:
dataset: the dataset to make input function from.
filepattern: the pattern of files to read from.
skip_random_fraction_when_training: whether to skip randomly when training.
batch_size_means_tokens_param: whether batch size should mean tokens.
batch_size_multiplier: how to multiply batch size when bucketing.
max_length: maximum length,
mode: tf.estimator.ModeKeys
hparams: HParams, model hparams
data_dir: str, data directory; if None, will use hparams.data_dir
params: dict, may include "batch_size"
config: RunConfig; should have the data_parallelism attribute if not using
TPU
force_repeat: bool, whether to repeat the data even if not training
prevent_repeat: bool, whether to not repeat when in training mode.
Overrides force_repeat.
Returns:
(features_dict<str name, Tensor feature>, Tensor targets)
"""
is_training = mode == tf.estimator.ModeKeys.TRAIN
if config and config.use_tpu:
num_threads = 64
else:
num_threads = cpu_count() if is_training else 1
if config and hasattr(config,
"data_parallelism") and config.data_parallelism:
num_shards = config.data_parallelism.n
else:
num_shards = 1
mlperf_log.transformer_print(
key=mlperf_log.INPUT_MAX_LENGTH, value=max_length)
def tpu_valid_size(example):
return example_valid_size(example, hparams.min_length, max_length)
def gpu_valid_size(example):
drop_long_sequences = is_training or hparams.eval_drop_long_sequences
max_validate_length = max_length if drop_long_sequences else 10**9
return example_valid_size(example, hparams.min_length, max_validate_length)
def define_shapes(example):
batch_size = config and config.use_tpu and params["batch_size"]
return standardize_shapes(example, batch_size=batch_size)
# Read and preprocess
data_dir = data_dir or (hasattr(hparams, "data_dir") and hparams.data_dir)
if (force_repeat or is_training) and not prevent_repeat:
# Repeat and skip a random number of records
dataset = dataset.repeat()
if is_training and skip_random_fraction_when_training:
data_files = tf.contrib.slim.parallel_reader.get_data_files(filepattern)
# In continuous_train_and_eval when switching between train and
# eval, this input_fn method gets called multiple times and it
# would give you the exact same samples from the last call
# (because the Graph seed is set). So this skip gives you some
# shuffling.
dataset = skip_random_fraction(dataset, data_files[0])
dataset = dataset.map(cast_ints_to_int32, num_parallel_calls=num_threads)
if batch_size_means_tokens_param:
batch_size_means_tokens = True
else:
if _are_shapes_fully_defined(dataset.output_shapes):
batch_size_means_tokens = False
else:
tf.logging.warning(
"Shapes are not fully defined. Assuming batch_size means tokens.")
batch_size_means_tokens = True
# Batching
if not batch_size_means_tokens:
# Batch size means examples per datashard.
if config and config.use_tpu:
# on TPU, we use params["batch_size"], which specifies the number of
# examples across all datashards
batch_size = params["batch_size"]
dataset = dataset.batch(batch_size, drop_remainder=True)
else:
batch_size = hparams.batch_size * num_shards
dataset = dataset.batch(batch_size)
else:
# batch_size means tokens per datashard
if config and config.use_tpu:
dataset = dataset.filter(tpu_valid_size)
padded_shapes = pad_for_tpu(dataset.output_shapes, hparams, max_length)
# on TPU, we use params["batch_size"], which specifies the number of
# examples across all datashards
batch_size = params["batch_size"]
if hparams.pad_batch:
tf.logging.warn(
"Padding the batch to ensure that remainder eval batches are "
"processed. This may lead to incorrect metrics for "
"non-zero-padded features, e.g. images. Use a smaller batch "
"size that has no remainder in that case.")
dataset = dataset.padded_batch(
batch_size, padded_shapes, drop_remainder=False)
dataset = dataset.map(
functools.partial(pad_batch, batch_multiple=batch_size),
num_parallel_calls=num_threads)
else:
dataset = dataset.padded_batch(
batch_size, padded_shapes, drop_remainder=True)
else:
# On GPU, bucket by length
dataset = dataset.filter(gpu_valid_size)
cur_batching_scheme = hparams_to_batching_scheme(
hparams,
shard_multiplier=num_shards,
length_multiplier=batch_size_multiplier)
if hparams.use_fixed_batch_size:
# Here batch_size really means examples per datashard.
cur_batching_scheme["batch_sizes"] = [hparams.batch_size]
cur_batching_scheme["boundaries"] = []
dataset = dataset.apply(
tf.data.experimental.bucket_by_sequence_length(
example_length, cur_batching_scheme["boundaries"],
cur_batching_scheme["batch_sizes"]))
if not is_training:
batch_multiple = num_shards
if hparams.use_fixed_batch_size:
# Make sure the last batch has the same fixed size as the rest.
batch_multiple *= hparams.batch_size
if batch_multiple > 1:
tf.logging.warn(
"Padding the batch to ensure that remainder eval batches have "
"a batch size divisible by the number of data shards. This may "
"lead to incorrect metrics for non-zero-padded features, e.g. "
"images. Use a single datashard (i.e. 1 GPU) in that case.")
dataset = dataset.map(
functools.partial(pad_batch, batch_multiple=batch_multiple),
num_parallel_calls=num_threads)
dataset = dataset.map(define_shapes, num_parallel_calls=num_threads)
# Add shuffling for training batches. This is necessary along with record
# level shuffling in the dataset generation. Record shuffling will shuffle
# the examples. However, in some cases, it's possible that the shuffle
# buffer size for record shuffling is smaller than the batch size. In such
# cases, adding batch shuffling ensures that the data is in random order
# during training
if (is_training and hasattr(hparams, "batch_shuffle_size") and
hparams.batch_shuffle_size):
dataset = dataset.shuffle(hparams.batch_shuffle_size)
# Split batches into chunks if targets are too long.
# The new "chunk_number" feature is 0 for the first chunk and goes up then.
# Chunks are reversed so the 0th chunk comes first, then the 1st and so on,
# so models can attend to them in the order they arrive. The last chunk is
# usually the one containing the end of the target sentence (EOS).
chunk_length = hparams.get("split_targets_chunk_length", 0)
max_chunks = hparams.get("split_targets_max_chunks", 100)
if chunk_length > 0:
def is_nonzero_chunk(example):
"""A chunk is zero if all targets are 0s."""
return tf.less(0, tf.reduce_sum(tf.abs(example["targets"])))
def split_on_length(example):
"""Split a batch of ditcs on length."""
x = example["targets"]
# TODO(kitaev): This code breaks if chunk_length * max_chunks < batch_size
length_diff = chunk_length * max_chunks - tf.shape(x)[1]
padded_x = tf.pad(x, [(0, 0), (0, length_diff), (0, 0), (0, 0)])
chunks = [padded_x[:, i*chunk_length:(i+1)*chunk_length, :, :]
for i in range(max_chunks - 1)]
chunks.append(padded_x[:, (max_chunks - 1)*chunk_length:, :, :])
new_example = {}
# Setting chunk_number to be tf.range(max_chunks) is incompatible with TPU
new_example["chunk_number"] = tf.concat([
tf.expand_dims(tf.ones_like(c) * n, axis=0)
for n, c in enumerate(chunks)
],
axis=0)
new_example["targets"] = tf.concat(
[tf.expand_dims(c, axis=0) for c in chunks], axis=0)
for k in example:
if k != "targets":
assert k != "chunk_number", (
"Chunking code expects the chunk_number feature name to be "
"available"
)
new_example[k] = tf.concat(
[tf.expand_dims(example[k], axis=0) for _ in range(max_chunks)],
axis=0)
return tf.data.Dataset.from_tensor_slices(new_example)
dataset = dataset.flat_map(split_on_length)
dataset = dataset.filter(is_nonzero_chunk)
# The chunking data pipeline thus far creates batches of examples where all
# of the examples have the same chunk number. This can lead to periodic
# fluctuations in the loss; for example, when all examples in the batch have
# chunk number 0 the loss may be higher than midway through a sequence.
# Enabling split_targets_strided_training adjusts the data so that each
# batch includes examples at various points within a sequence.
if is_training and hparams.split_targets_strided_training:
# TODO(kitaev): make sure that shape inference works on GPU, not just TPU.
inferred_batch_size = dataset.output_shapes["targets"].as_list()[0]
if inferred_batch_size is None:
raise ValueError(
"Strided training is only implemented when the batch size can be "
"inferred statically, for example when training on TPU."
)
chunk_stride = inferred_batch_size * max(
1, max_chunks // inferred_batch_size) + 1
def collapse_nested_datasets(example):
"""Converts a dataset of datasets to a dataset of tensor features."""
new_example = {}
for k, v in example.items():
v = tf.data.experimental.get_single_element(
v.batch(inferred_batch_size, drop_remainder=True))
new_example[k] = v
return tf.data.Dataset.from_tensor_slices(new_example)
dataset = dataset.apply(tf.data.experimental.unbatch())
dataset = dataset.window(inferred_batch_size, inferred_batch_size,
chunk_stride)
dataset = dataset.flat_map(collapse_nested_datasets)
dataset = dataset.batch(inferred_batch_size, drop_remainder=True)
def prepare_for_output(example):
if not config or not config.use_tpu:
_summarize_features(example, num_shards)
if mode == tf.estimator.ModeKeys.PREDICT:
example["infer_targets"] = example.pop("targets")
return example
else:
return example, example["targets"]
dataset = dataset.map(prepare_for_output, num_parallel_calls=num_threads)
dataset = dataset.prefetch(2)
if mode == tf.estimator.ModeKeys.PREDICT:
# This is because of a bug in the Estimator that short-circuits prediction
# if it doesn't see a QueueRunner. DummyQueueRunner implements the
# minimal expected interface but does nothing.
tf.add_to_collection(tf.GraphKeys.QUEUE_RUNNERS, DummyQueueRunner())
return dataset
|
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] |
Builds input pipeline for problem.
Args:
dataset: the dataset to make input function from.
filepattern: the pattern of files to read from.
skip_random_fraction_when_training: whether to skip randomly when training.
batch_size_means_tokens_param: whether batch size should mean tokens.
batch_size_multiplier: how to multiply batch size when bucketing.
max_length: maximum length,
mode: tf.estimator.ModeKeys
hparams: HParams, model hparams
data_dir: str, data directory; if None, will use hparams.data_dir
params: dict, may include "batch_size"
config: RunConfig; should have the data_parallelism attribute if not using
TPU
force_repeat: bool, whether to repeat the data even if not training
prevent_repeat: bool, whether to not repeat when in training mode.
Overrides force_repeat.
Returns:
(features_dict<str name, Tensor feature>, Tensor targets)
|
[
"Builds",
"input",
"pipeline",
"for",
"problem",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/data_reader.py#L312-L572
|
train
|
Builds input function for the input problem.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(251 - 203) + chr(11203 - 11092) + '\063' + chr(0b110111), 12577 - 12569), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + chr(54) + chr(48), 27545 - 27537), ehT0Px3KOsy9(chr(48) + chr(0b1101011 + 0o4) + '\063' + '\x31' + '\x35', 13191 - 13183), ehT0Px3KOsy9(chr(524 - 476) + '\157' + '\061', 39945 - 39937), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(53), 0b1000), ehT0Px3KOsy9(chr(269 - 221) + chr(4689 - 4578) + '\x33' + chr(330 - 275) + chr(0b1011 + 0o50), 0o10), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(111) + chr(0b100011 + 0o17) + chr(48) + '\x32', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(3074 - 2963) + chr(2454 - 2403) + '\065' + chr(52), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1640 - 1590) + chr(0b110001) + chr(0b101100 + 0o4), 0o10), ehT0Px3KOsy9('\060' + chr(0b1001101 + 0o42) + '\063' + '\x31' + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(1649 - 1601) + '\157' + '\x33' + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b11010 + 0o125) + chr(142 - 93) + '\062', 62794 - 62786), ehT0Px3KOsy9('\060' + chr(0b110 + 0o151) + chr(49) + chr(0b101 + 0o60) + '\060', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + chr(0b100 + 0o56) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b11100 + 0o30) + chr(2161 - 2110), ord("\x08")), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b10010 + 0o135) + chr(1975 - 1925) + chr(0b110101) + chr(0b11001 + 0o34), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x32' + chr(55) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + '\065' + chr(2814 - 2760), 33565 - 33557), ehT0Px3KOsy9(chr(48) + chr(111) + '\x32' + chr(54) + chr(1930 - 1882), 0b1000), ehT0Px3KOsy9(chr(1459 - 1411) + chr(7082 - 6971) + chr(1186 - 1137) + '\061' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\157' + chr(0b110010) + chr(54) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b1 + 0o57) + '\x6f' + chr(0b101010 + 0o7) + chr(0b110000) + chr(1084 - 1029), ord("\x08")), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b1101111) + chr(51) + chr(54) + '\x30', 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(384 - 335) + chr(1300 - 1247) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061' + chr(0b101000 + 0o10) + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + chr(3642 - 3531) + chr(0b101001 + 0o11) + chr(0b101111 + 0o6), 8), ehT0Px3KOsy9(chr(1240 - 1192) + chr(0b1101111) + '\061' + chr(2850 - 2796) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(48) + chr(2343 - 2232) + chr(50) + chr(48) + chr(0b110010), 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1001 + 0o50) + '\062' + chr(696 - 647), 41658 - 41650), ehT0Px3KOsy9('\x30' + chr(111) + '\062', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\060', 0b1000), ehT0Px3KOsy9('\x30' + chr(7534 - 7423) + chr(51) + chr(50) + chr(55), 10573 - 10565), ehT0Px3KOsy9('\x30' + chr(0b1101 + 0o142) + chr(0b110111) + chr(1675 - 1620), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(5409 - 5298) + chr(0b100100 + 0o15) + '\x31' + chr(0b10001 + 0o43), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010100 + 0o33) + chr(51) + chr(0b110111) + chr(0b1110 + 0o50), 0o10), ehT0Px3KOsy9(chr(579 - 531) + chr(0b101001 + 0o106) + chr(0b100010 + 0o25) + chr(53), 53714 - 53706), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062' + chr(190 - 140) + chr(0b111 + 0o54), 47298 - 47290), ehT0Px3KOsy9(chr(2142 - 2094) + '\x6f' + chr(0b11011 + 0o30) + chr(55) + chr(0b10 + 0o60), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b101100 + 0o103) + chr(0b110010) + chr(0b101111 + 0o6), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(2161 - 2113) + chr(0b1101111) + chr(53) + chr(1071 - 1023), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'1'), chr(9348 - 9248) + chr(5468 - 5367) + chr(99) + chr(0b1101111) + chr(100) + chr(8127 - 8026))('\x75' + chr(8729 - 8613) + chr(0b110110 + 0o60) + chr(45) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def MVwQV4Upte2X(xQt6gV9VfTO3, mnAeTPQPQgT_, biaXPfiCgoGt, aTCys8DWJnZ2, Gb0tZM0PV2pD, _o7pVXAdOCRy, holLFgwB7vsP, n4ljua2gi1Pr, kVFRD544hi_1=None, nEbJZ4wfte2w=None, jAj7S20Ct06o=None, Q5HlHwWjWXJy=ehT0Px3KOsy9(chr(0b110000) + chr(11566 - 11455) + chr(539 - 491), 8), kcD5_yICCeDt=ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(0b1101111) + '\060', 8)):
XQJVi3cQFN5l = holLFgwB7vsP == IDJ2eXGCBCDu.estimator.ModeKeys.TRAIN
if jAj7S20Ct06o and xafqLlk3kkUe(jAj7S20Ct06o, xafqLlk3kkUe(SXOLrMavuUCe(b'j\x83\xa8^a\x8b\xf7'), chr(0b1100100) + '\145' + chr(0b1100011) + chr(4061 - 3950) + chr(100) + '\145')(chr(0b1 + 0o164) + chr(10123 - 10007) + chr(5432 - 5330) + chr(0b1110 + 0o37) + chr(0b100111 + 0o21))):
pCw22JJnmDr0 = ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + chr(0b110000) + chr(235 - 187), 8)
else:
pCw22JJnmDr0 = l4Wa6ItFurHt() if XQJVi3cQFN5l else ehT0Px3KOsy9(chr(0b110000) + chr(10277 - 10166) + chr(0b11000 + 0o31), 8)
if jAj7S20Ct06o and lot1PSoAwYhj(jAj7S20Ct06o, xafqLlk3kkUe(SXOLrMavuUCe(b'{\x91\xb9`J\x8b\xe3}\x8d\xe4\xa2}f\x01#N'), '\x64' + chr(5330 - 5229) + chr(128 - 29) + chr(5936 - 5825) + chr(0b1010010 + 0o22) + chr(101))(chr(7507 - 7390) + chr(0b100111 + 0o115) + chr(0b110001 + 0o65) + '\055' + chr(0b100001 + 0o27))) and xafqLlk3kkUe(jAj7S20Ct06o, xafqLlk3kkUe(SXOLrMavuUCe(b'{\x91\xb9`J\x8b\xe3}\x8d\xe4\xa2}f\x01#N'), chr(7152 - 7052) + chr(0b1100101) + chr(2520 - 2421) + '\157' + '\144' + chr(0b1100101))(chr(0b10000 + 0o145) + chr(0b1000101 + 0o57) + chr(102) + '\x2d' + chr(2692 - 2636))):
WJU3qUPk_Uro = jAj7S20Ct06o.data_parallelism.m1NkCryOw9Bx
else:
WJU3qUPk_Uro = ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1450 - 1401), 8)
xafqLlk3kkUe(mcP9wB7s3wV8, xafqLlk3kkUe(SXOLrMavuUCe(b'k\x82\xacof\x9d\xed}\x81\xed\xbcGz\x1a9M\xd9'), '\x64' + chr(101) + chr(9003 - 8904) + '\157' + '\x64' + chr(0b1100101))('\165' + '\x74' + chr(0b1100110) + chr(0b101101) + chr(2035 - 1979)))(key=xafqLlk3kkUe(mcP9wB7s3wV8, xafqLlk3kkUe(SXOLrMavuUCe(b'V\xbe\x9dTA\xa4\xcfN\xb4\xd7\x82]D/\x04k'), '\144' + chr(101) + chr(0b1100011) + chr(0b11001 + 0o126) + chr(1210 - 1110) + chr(0b101000 + 0o75))('\x75' + '\164' + chr(102) + chr(45) + chr(1506 - 1450))), value=_o7pVXAdOCRy)
def C2P0oiwMxhBS(kP4qaKv0ZkGv):
return tK2cBvmV9fXh(kP4qaKv0ZkGv, xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'r\x99\xa3^y\x9e\xech\x98\xe0'), chr(0b1010011 + 0o21) + '\145' + chr(6261 - 6162) + '\x6f' + '\144' + chr(101))('\x75' + chr(0b1110100) + chr(102) + chr(0b101101) + '\x38')), _o7pVXAdOCRy)
def DVLWrG0Dr425(kP4qaKv0ZkGv):
IEeQFspKnx61 = XQJVi3cQFN5l or n4ljua2gi1Pr.n5sZSNr92T7V
EjEWxHCxzOtT = _o7pVXAdOCRy if IEeQFspKnx61 else ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(576 - 527) + chr(0b110010), 8) ** ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + '\061', 0b1000)
return tK2cBvmV9fXh(kP4qaKv0ZkGv, xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'r\x99\xa3^y\x9e\xech\x98\xe0'), chr(100) + chr(101) + chr(0b1100011) + chr(111) + '\144' + chr(0b1100101))(chr(6280 - 6163) + '\164' + chr(102) + chr(0b101101) + chr(0b1010 + 0o56))), EjEWxHCxzOtT)
def bQLp9myA_ckF(kP4qaKv0ZkGv):
ix9dZyeAmUxY = jAj7S20Ct06o and jAj7S20Ct06o.use_tpu and nEbJZ4wfte2w[xafqLlk3kkUe(SXOLrMavuUCe(b'}\x91\xb9b}\xa4\xf1f\x96\xed'), chr(0b1100100) + '\145' + chr(99) + chr(0b110011 + 0o74) + '\144' + chr(7115 - 7014))(chr(11791 - 11674) + chr(0b1101100 + 0o10) + chr(0b1100110) + '\055' + chr(2054 - 1998))]
return czGIkBlXHzVz(kP4qaKv0ZkGv, batch_size=ix9dZyeAmUxY)
kVFRD544hi_1 = kVFRD544hi_1 or (lot1PSoAwYhj(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'{\x91\xb9`J\x9f\xeb}'), '\x64' + '\145' + chr(0b100 + 0o137) + chr(0b1101111) + chr(100) + '\x65')(chr(117) + chr(116) + '\146' + chr(240 - 195) + chr(1671 - 1615))) and n4ljua2gi1Pr.kVFRD544hi_1)
if (Q5HlHwWjWXJy or XQJVi3cQFN5l) and (not kcD5_yICCeDt):
xQt6gV9VfTO3 = xQt6gV9VfTO3.repeat()
if XQJVi3cQFN5l and biaXPfiCgoGt:
KAyZjSEftgFC = IDJ2eXGCBCDu.contrib.slim.parallel_reader.get_data_files(mnAeTPQPQgT_)
xQt6gV9VfTO3 = nP2HOJnm70hw(xQt6gV9VfTO3, KAyZjSEftgFC[ehT0Px3KOsy9(chr(0b101000 + 0o10) + '\x6f' + '\x30', 8)])
xQt6gV9VfTO3 = xQt6gV9VfTO3.map(MtG_mwI9f3vG, num_parallel_calls=pCw22JJnmDr0)
if aTCys8DWJnZ2:
soKesuPT7Gdi = ehT0Px3KOsy9('\060' + chr(0b111110 + 0o61) + '\061', 8)
elif rp_oyM2vnbYa(xafqLlk3kkUe(xQt6gV9VfTO3, xafqLlk3kkUe(SXOLrMavuUCe(b'p\x85\xb9q`\x8f\xdd|\x84\xe9\xbe}y'), '\x64' + chr(0b10 + 0o143) + '\x63' + chr(0b1101111) + '\x64' + '\145')('\x75' + chr(0b1011110 + 0o26) + chr(102) + '\x2d' + chr(0b111000)))):
soKesuPT7Gdi = ehT0Px3KOsy9(chr(760 - 712) + '\x6f' + chr(0b110000), 8)
else:
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'h\x91\xbfo|\x95\xe5'), chr(0b1100100) + chr(101) + chr(0b1100011) + '\157' + '\144' + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + '\x66' + chr(0b101101) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'L\x98\xacqp\x88\xa2n\x9e\xed\xeeve\x1cpE\xd8\xd1\x02\xc9o\xd0"\x96\x03.p\x11\xacqCs\xa4J!\x97S\xf4\xdaw~\x84\xaeiJ\x88\xebu\x89\xa8\xa3}k\x06#\x03\xd9\xd2\x05\xd5!\xc7i'), chr(0b1100100) + chr(101) + '\143' + '\x6f' + chr(0b110000 + 0o64) + chr(0b1100101))(chr(117) + '\164' + chr(102) + '\x2d' + chr(309 - 253)))
soKesuPT7Gdi = ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(11883 - 11772) + '\x31', 8)
if not soKesuPT7Gdi:
if jAj7S20Ct06o and xafqLlk3kkUe(jAj7S20Ct06o, xafqLlk3kkUe(SXOLrMavuUCe(b'j\x83\xa8^a\x8b\xf7'), chr(0b101 + 0o137) + '\x65' + '\x63' + chr(111) + chr(100) + chr(0b1100101))(chr(0b1110101) + '\x74' + '\146' + chr(0b101101) + chr(56))):
ix9dZyeAmUxY = nEbJZ4wfte2w[xafqLlk3kkUe(SXOLrMavuUCe(b'}\x91\xb9b}\xa4\xf1f\x96\xed'), chr(4987 - 4887) + chr(101) + chr(0b1100011) + chr(0b1101111) + chr(100) + '\145')(chr(117) + chr(0b100000 + 0o124) + chr(102) + '\055' + '\070')]
xQt6gV9VfTO3 = xQt6gV9VfTO3.dNwAahu8tvoY(ix9dZyeAmUxY, drop_remainder=ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001), 8))
else:
ix9dZyeAmUxY = n4ljua2gi1Pr.ix9dZyeAmUxY * WJU3qUPk_Uro
xQt6gV9VfTO3 = xQt6gV9VfTO3.dNwAahu8tvoY(ix9dZyeAmUxY)
elif jAj7S20Ct06o and xafqLlk3kkUe(jAj7S20Ct06o, xafqLlk3kkUe(SXOLrMavuUCe(b'j\x83\xa8^a\x8b\xf7'), '\144' + '\x65' + chr(99) + '\157' + chr(2409 - 2309) + chr(0b1000011 + 0o42))('\x75' + '\x74' + chr(102) + chr(0b10110 + 0o27) + chr(56))):
xQt6gV9VfTO3 = xQt6gV9VfTO3.hi1V0ySZcNds(C2P0oiwMxhBS)
HI4hZPL6gW9O = JegpSfmGUFal(xQt6gV9VfTO3.output_shapes, n4ljua2gi1Pr, _o7pVXAdOCRy)
ix9dZyeAmUxY = nEbJZ4wfte2w[xafqLlk3kkUe(SXOLrMavuUCe(b'}\x91\xb9b}\xa4\xf1f\x96\xed'), '\144' + '\145' + chr(5278 - 5179) + chr(0b100011 + 0o114) + chr(0b1100100) + chr(1835 - 1734))(chr(0b1110101) + chr(0b1110100) + '\x66' + '\055' + chr(2711 - 2655))]
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'o\x91\xa9^w\x9a\xf6l\x84'), chr(7894 - 7794) + '\145' + chr(0b1100011) + chr(0b1101111) + chr(0b10100 + 0o120) + chr(0b110111 + 0o56))(chr(0b1110101) + '\x74' + '\x66' + '\055' + chr(0b111000))):
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'q\xb4\x88o[\xb9\xe3m\xaa\xc6\x85u'), chr(968 - 868) + '\145' + '\143' + '\x6f' + chr(0b1000 + 0o134) + chr(0b1100101))('\165' + '\164' + chr(0b1010 + 0o134) + '\055' + chr(0b11011 + 0o35)))(xafqLlk3kkUe(SXOLrMavuUCe(b'O\x91\xa9e|\x95\xe5/\x98\xe0\xab8h\t$@\xc5\x9d\x1a\xdfo\xd1)\x83\x1f2pU\xf69ct\xf7M)\x93\\\xfa\x94qz\x82\xeddc\x9a\xee/\x8e\xe9\xba{b\r#\x03\xcc\xcf\x0b\x90?\xc6(\x93\x0f3f\x10\xe6\x7f"T\xbfV?\xdeP\xf2\x835s\x95\xace5\x8f\xed/\x85\xe6\xadwx\x1a5@\xd9\x9d\x03\xd5;\xc6.\x93\x19`s\x1a\xf0qlo\xb9\x126\x9bO\xfc\xd7e~\x94\xa9dq\xdb\xe4j\x8d\xfc\xbbjo\x1b|\x03\xc8\x93\t\x9eo\xdd*\x91\r%f[\xa2\x04qe\xf7^l\x8dP\xf2\x96yz\x82\xedct\x8f\xe1g\xcc\xfb\xa7boH$K\xcc\xc9N\xd8.\xc7g\x9e\x05`g\x10\xef0kn\xb3Z>\xdeT\xfd\xdaaw\x91\xb9!v\x9a\xf1j\xc2'), '\x64' + chr(101) + chr(99) + chr(12143 - 12032) + chr(4628 - 4528) + chr(101))(chr(0b11100 + 0o131) + chr(0b1011 + 0o151) + chr(3521 - 3419) + '\055' + chr(56)))
xQt6gV9VfTO3 = xQt6gV9VfTO3.padded_batch(ix9dZyeAmUxY, HI4hZPL6gW9O, drop_remainder=ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(57 - 9), 8))
xQt6gV9VfTO3 = xQt6gV9VfTO3.map(E6ula8_Zv1yl.partial(_D58k8QjRlpJ, batch_multiple=ix9dZyeAmUxY), num_parallel_calls=pCw22JJnmDr0)
else:
xQt6gV9VfTO3 = xQt6gV9VfTO3.padded_batch(ix9dZyeAmUxY, HI4hZPL6gW9O, drop_remainder=ehT0Px3KOsy9(chr(1353 - 1305) + chr(8577 - 8466) + '\x31', 8))
else:
xQt6gV9VfTO3 = xQt6gV9VfTO3.hi1V0ySZcNds(DVLWrG0Dr425)
XqrOVA_5adqI = E1u26WzGPIXY(n4ljua2gi1Pr, shard_multiplier=WJU3qUPk_Uro, length_multiplier=Gb0tZM0PV2pD)
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'I\xc9\x94v}\xbf\xf1I\xa3\xe4\x89S'), '\144' + chr(0b101 + 0o140) + '\x63' + chr(7724 - 7613) + chr(0b1100100) + '\145')(chr(8741 - 8624) + '\x74' + chr(0b1100100 + 0o2) + chr(1485 - 1440) + chr(56))):
XqrOVA_5adqI[xafqLlk3kkUe(SXOLrMavuUCe(b'}\x91\xb9b}\xa4\xf1f\x96\xed\xbd'), chr(0b1011101 + 0o7) + '\145' + chr(0b1110 + 0o125) + chr(8758 - 8647) + chr(0b1 + 0o143) + chr(0b1100001 + 0o4))(chr(0b1110101) + '\x74' + '\x66' + chr(45) + chr(2768 - 2712))] = [n4ljua2gi1Pr.ix9dZyeAmUxY]
XqrOVA_5adqI[xafqLlk3kkUe(SXOLrMavuUCe(b'}\x9f\xb8oq\x9a\xf0f\x89\xfb'), chr(0b1001001 + 0o33) + chr(0b1100101) + chr(8889 - 8790) + chr(111) + '\144' + '\x65')(chr(117) + chr(0b1001111 + 0o45) + '\146' + chr(45) + chr(0b110100 + 0o4))] = []
xQt6gV9VfTO3 = xQt6gV9VfTO3.apply(IDJ2eXGCBCDu.data.experimental.bucket_by_sequence_length(fEAdJgn5yxLX, XqrOVA_5adqI[xafqLlk3kkUe(SXOLrMavuUCe(b'}\x9f\xb8oq\x9a\xf0f\x89\xfb'), '\x64' + chr(0b1100101) + chr(99) + chr(0b1101100 + 0o3) + chr(100) + chr(1498 - 1397))(chr(0b101 + 0o160) + chr(0b1 + 0o163) + '\x66' + chr(510 - 465) + chr(56))], XqrOVA_5adqI[xafqLlk3kkUe(SXOLrMavuUCe(b'}\x91\xb9b}\xa4\xf1f\x96\xed\xbd'), chr(0b1100100) + chr(8547 - 8446) + chr(0b1100011) + chr(6404 - 6293) + chr(100) + chr(101))(chr(117) + chr(0b1001010 + 0o52) + chr(0b1100110) + chr(0b11010 + 0o23) + '\070')]))
if not XQJVi3cQFN5l:
_i4P3dl8fCMX = WJU3qUPk_Uro
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'I\xc9\x94v}\xbf\xf1I\xa3\xe4\x89S'), '\144' + '\x65' + '\x63' + chr(0b1011011 + 0o24) + '\144' + chr(0b1100101))(chr(117) + chr(0b1110100) + chr(0b1100110) + chr(45) + chr(0b111000))):
_i4P3dl8fCMX *= n4ljua2gi1Pr.ix9dZyeAmUxY
if _i4P3dl8fCMX > ehT0Px3KOsy9('\060' + '\157' + chr(0b0 + 0o61), 8):
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'q\xb4\x88o[\xb9\xe3m\xaa\xc6\x85u'), '\144' + '\x65' + chr(0b101010 + 0o71) + chr(0b111110 + 0o61) + chr(5415 - 5315) + chr(0b1100101))(chr(5615 - 5498) + chr(116) + chr(0b1110 + 0o130) + chr(0b101101) + chr(2800 - 2744)))(xafqLlk3kkUe(SXOLrMavuUCe(b'O\x91\xa9e|\x95\xe5/\x98\xe0\xab8h\t$@\xc5\x9d\x1a\xdfo\xd1)\x83\x1f2pU\xf69ct\xf7M)\x93\\\xfa\x94qz\x82\xeddc\x9a\xee/\x8e\xe9\xba{b\r#\x03\xc5\xdc\x18\xd5o\xd5g\x92\x0b4v\x1d\xa2"kz\xb2\x1f(\x97K\xfa\x89|}\x9c\xa8!w\x82\xa2{\x84\xed\xeev\x7f\x052F\xdf\x9d\x01\xd6o\xd0&\x84\x0b`f\x1d\xe3#fs\xf9\x1f\x18\x96T\xe0\xdax~\x89\xedmp\x9a\xe6/\x98\xe7\xeeqd\x0b?Q\xdf\xd8\r\xc4o\xd9"\x84\x18)v\x06\xa27mr\xf7Q#\x90\x10\xe9\x9fgp\xdd\xbd`q\x9f\xe7k\xcc\xee\xaby~\x1d"F\xde\x91N\xd5a\xd3i\xd0\x03-t\x12\xe7", \x82L)\xde\\\xb3\x89|q\x97\xa1d5\x9f\xe3{\x8d\xfb\xa6yx\x0cp\x0b\xc4\x93\x0b\x9eo\x85g\xb7:\x15<U\xeb?"t\xbf^8\xde^\xf2\x89p1'), chr(0b1100100) + '\145' + '\143' + chr(0b1101111) + chr(0b111111 + 0o45) + chr(0b1000111 + 0o36))(chr(680 - 563) + '\x74' + chr(0b1001 + 0o135) + chr(0b101000 + 0o5) + chr(0b111000)))
xQt6gV9VfTO3 = xQt6gV9VfTO3.map(E6ula8_Zv1yl.partial(_D58k8QjRlpJ, batch_multiple=_i4P3dl8fCMX), num_parallel_calls=pCw22JJnmDr0)
xQt6gV9VfTO3 = xQt6gV9VfTO3.map(bQLp9myA_ckF, num_parallel_calls=pCw22JJnmDr0)
if XQJVi3cQFN5l and lot1PSoAwYhj(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'}\x91\xb9b}\xa4\xf1g\x99\xee\xa8to7#J\xd7\xd8'), chr(0b1100100) + '\x65' + chr(99) + chr(1067 - 956) + '\x64' + '\x65')(chr(0b111001 + 0o74) + chr(0b1011001 + 0o33) + chr(0b111001 + 0o55) + chr(789 - 744) + chr(0b111000))) and xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'}\x91\xb9b}\xa4\xf1g\x99\xee\xa8to7#J\xd7\xd8'), '\144' + '\145' + '\143' + chr(111) + chr(0b1100100) + '\145')('\x75' + chr(116) + '\146' + chr(0b101101) + '\070')):
xQt6gV9VfTO3 = xQt6gV9VfTO3.shuffle(n4ljua2gi1Pr.batch_shuffle_size)
U20n43DzQduo = n4ljua2gi1Pr.get(xafqLlk3kkUe(SXOLrMavuUCe(b'l\x80\xa1ha\xa4\xf6n\x9e\xef\xably73K\xd8\xd3\x05\xef#\xd1)\x97\x1e('), chr(406 - 306) + '\x65' + chr(0b1100 + 0o127) + chr(111) + chr(0b101 + 0o137) + chr(101))('\x75' + '\164' + chr(0b1100110) + chr(45) + chr(0b101 + 0o63)), ehT0Px3KOsy9(chr(817 - 769) + '\157' + chr(0b101001 + 0o7), 8))
Dfo4F1zszySM = n4ljua2gi1Pr.get(xafqLlk3kkUe(SXOLrMavuUCe(b'l\x80\xa1ha\xa4\xf6n\x9e\xef\xably7=B\xd5\xe2\r\xd8:\xda,\x83'), chr(7621 - 7521) + chr(3386 - 3285) + '\x63' + chr(0b1101111) + chr(8752 - 8652) + '\145')('\x75' + chr(0b1110100) + '\146' + '\x2d' + chr(1685 - 1629)), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + chr(286 - 234) + '\064', ord("\x08")))
if U20n43DzQduo > ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1110 + 0o42), 8):
def faCPipjYxuys(kP4qaKv0ZkGv):
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b's\x95\xber'), chr(0b101001 + 0o73) + chr(641 - 540) + chr(0b1001000 + 0o33) + '\157' + '\x64' + chr(8958 - 8857))('\165' + '\164' + '\146' + chr(0b101101) + '\070'))(ehT0Px3KOsy9(chr(48) + '\157' + '\x30', 8), xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'm\x95\xa9tv\x9e\xdd|\x99\xe5'), chr(100) + chr(0b11 + 0o142) + chr(2896 - 2797) + chr(0b100010 + 0o115) + '\144' + chr(347 - 246))('\x75' + chr(2493 - 2377) + chr(102) + chr(45) + chr(0b10100 + 0o44)))(xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'~\x92\xbe'), chr(100) + chr(9478 - 9377) + chr(0b1000 + 0o133) + chr(0b1101111) + chr(0b1010111 + 0o15) + chr(0b1100101))(chr(0b1100011 + 0o22) + chr(0b1110100) + chr(0b1100110) + chr(0b101101) + chr(0b10001 + 0o47)))(kP4qaKv0ZkGv[xafqLlk3kkUe(SXOLrMavuUCe(b'k\x91\xbffp\x8f\xf1'), chr(100) + chr(101) + '\x63' + '\x6f' + '\x64' + chr(4844 - 4743))(chr(0b1110011 + 0o2) + chr(0b1110100) + '\146' + '\x2d' + chr(0b111000))])))
def fYrvFzAhW6_L(kP4qaKv0ZkGv):
OeWW0F1dBPRQ = kP4qaKv0ZkGv[xafqLlk3kkUe(SXOLrMavuUCe(b'k\x91\xbffp\x8f\xf1'), chr(0b1101 + 0o127) + chr(0b1100011 + 0o2) + chr(99) + '\157' + chr(8156 - 8056) + '\x65')('\165' + '\164' + chr(7279 - 7177) + '\x2d' + chr(1577 - 1521))]
JOXBBW_AsDvh = U20n43DzQduo * Dfo4F1zszySM - IDJ2eXGCBCDu.nauYfLglTpcb(OeWW0F1dBPRQ)[ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100100 + 0o15), 8)]
UQa66kHr4Iwu = IDJ2eXGCBCDu.pad(OeWW0F1dBPRQ, [(ehT0Px3KOsy9('\060' + '\x6f' + '\060', 8), ehT0Px3KOsy9('\x30' + '\x6f' + '\060', 8)), (ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x30', 8), JOXBBW_AsDvh), (ehT0Px3KOsy9(chr(48) + chr(6415 - 6304) + chr(48), 8), ehT0Px3KOsy9(chr(1382 - 1334) + chr(0b111100 + 0o63) + chr(1016 - 968), 8)), (ehT0Px3KOsy9(chr(48) + chr(0b1100 + 0o143) + chr(0b10111 + 0o31), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\060', 8))])
XVRfrZhsDVHr = [UQa66kHr4Iwu[:, WVxHKyX45z_L * U20n43DzQduo:(WVxHKyX45z_L + ehT0Px3KOsy9(chr(48) + '\x6f' + chr(49), 8)) * U20n43DzQduo, :, :] for WVxHKyX45z_L in vQr8gNKaIaWE(Dfo4F1zszySM - ehT0Px3KOsy9(chr(892 - 844) + chr(111) + chr(49), 8))]
xafqLlk3kkUe(XVRfrZhsDVHr, xafqLlk3kkUe(SXOLrMavuUCe(b'~\x80\xbdd{\x9f'), chr(100) + '\x65' + '\143' + '\157' + chr(0b11111 + 0o105) + '\145')(chr(12747 - 12630) + chr(11146 - 11030) + chr(0b110110 + 0o60) + chr(0b1110 + 0o37) + chr(0b10011 + 0o45)))(UQa66kHr4Iwu[:, (Dfo4F1zszySM - ehT0Px3KOsy9('\060' + '\157' + '\061', 8)) * U20n43DzQduo:, :, :])
PTHa4fKFxPzV = {}
PTHa4fKFxPzV[xafqLlk3kkUe(SXOLrMavuUCe(b'|\x98\xb8o~\xa4\xecz\x81\xea\xabj'), '\144' + chr(0b1000001 + 0o44) + chr(99) + chr(0b11 + 0o154) + chr(4726 - 4626) + '\x65')('\165' + '\x74' + chr(102) + chr(0b101101) + chr(0b10001 + 0o47))] = IDJ2eXGCBCDu.concat([IDJ2eXGCBCDu.expand_dims(IDJ2eXGCBCDu.ones_like(qzn1Ctg9WgNh) * m1NkCryOw9Bx, axis=ehT0Px3KOsy9('\x30' + chr(10595 - 10484) + chr(48), 8)) for (m1NkCryOw9Bx, qzn1Ctg9WgNh) in YlkZvXL8qwsX(XVRfrZhsDVHr)], axis=ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b1101010 + 0o5) + chr(0b100110 + 0o12), 8))
PTHa4fKFxPzV[xafqLlk3kkUe(SXOLrMavuUCe(b'k\x91\xbffp\x8f\xf1'), chr(0b1100100) + chr(0b100011 + 0o102) + '\143' + chr(0b1001 + 0o146) + '\144' + chr(5748 - 5647))('\x75' + chr(0b100001 + 0o123) + '\x66' + '\x2d' + '\070')] = IDJ2eXGCBCDu.concat([IDJ2eXGCBCDu.expand_dims(qzn1Ctg9WgNh, axis=ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1011111 + 0o20) + '\060', 8)) for qzn1Ctg9WgNh in XVRfrZhsDVHr], axis=ehT0Px3KOsy9('\060' + '\x6f' + chr(0b1 + 0o57), 8))
for OolUPRJhRaJd in kP4qaKv0ZkGv:
if OolUPRJhRaJd != xafqLlk3kkUe(SXOLrMavuUCe(b'k\x91\xbffp\x8f\xf1'), chr(0b11010 + 0o112) + chr(0b1100101) + chr(0b1001011 + 0o30) + '\157' + chr(7577 - 7477) + '\x65')(chr(0b1110101) + '\x74' + chr(0b1100001 + 0o5) + '\055' + '\x38'):
assert OolUPRJhRaJd != xafqLlk3kkUe(SXOLrMavuUCe(b'|\x98\xb8o~\xa4\xecz\x81\xea\xabj'), '\144' + '\x65' + '\143' + chr(0b1011 + 0o144) + '\144' + chr(0b110011 + 0o62))(chr(117) + '\x74' + chr(0b1100110) + chr(45) + chr(1186 - 1130)), xafqLlk3kkUe(SXOLrMavuUCe(b'\\\x98\xb8o~\x92\xech\xcc\xeb\xa1|oH5[\xdd\xd8\r\xc4<\x943\x98\x0f`v\x1d\xf7?i_\xb9J!\x9cX\xe1\xdasz\x91\xb9tg\x9e\xa2a\x8d\xe5\xab8~\x07pA\xc8\x9d\x0f\xc6.\xdd+\x91\x08,p'), chr(100) + '\x65' + chr(0b1010110 + 0o15) + '\x6f' + '\144' + '\145')(chr(0b1110101) + '\164' + '\146' + '\x2d' + '\070')
PTHa4fKFxPzV[OolUPRJhRaJd] = IDJ2eXGCBCDu.concat([IDJ2eXGCBCDu.expand_dims(kP4qaKv0ZkGv[OolUPRJhRaJd], axis=ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100101 + 0o13), 8)) for VNGQdHSFPrso in vQr8gNKaIaWE(Dfo4F1zszySM)], axis=ehT0Px3KOsy9('\x30' + '\x6f' + '\060', 8))
return xafqLlk3kkUe(IDJ2eXGCBCDu.data.Dataset, xafqLlk3kkUe(SXOLrMavuUCe(b'y\x82\xa2lJ\x8f\xe7a\x9f\xe7\xbcGy\x049@\xc8\xce'), '\144' + chr(0b1100101) + '\x63' + chr(0b100011 + 0o114) + '\144' + chr(101))(chr(0b100001 + 0o124) + chr(116) + chr(7818 - 7716) + '\x2d' + '\070'))(PTHa4fKFxPzV)
xQt6gV9VfTO3 = xQt6gV9VfTO3.flat_map(fYrvFzAhW6_L)
xQt6gV9VfTO3 = xQt6gV9VfTO3.hi1V0ySZcNds(faCPipjYxuys)
if XQJVi3cQFN5l and xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'l\x80\xa1ha\xa4\xf6n\x9e\xef\xably7#W\xdf\xd4\n\xd5+\xeb3\x82\x0b){\x1c\xec6'), '\x64' + '\145' + '\x63' + chr(1760 - 1649) + '\144' + '\x65')('\x75' + '\164' + chr(102) + chr(1245 - 1200) + chr(56))):
DvvoTxuoRCMY = xQt6gV9VfTO3.output_shapes[xafqLlk3kkUe(SXOLrMavuUCe(b'k\x91\xbffp\x8f\xf1'), chr(4930 - 4830) + chr(0b100101 + 0o100) + chr(0b1100011) + '\157' + '\x64' + chr(101))('\x75' + chr(0b10011 + 0o141) + chr(0b1100110) + '\055' + chr(56))].as_list()[ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\157' + '\060', 8)]
if DvvoTxuoRCMY is None:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'L\x84\xbfhq\x9e\xe6/\x98\xfa\xafqd\x01>D\x8d\xd4\x1d\x90 \xda+\x89J)x\x05\xee4oe\xb9K)\x9a\x1d\xe4\x92pq\xd0\xb9ip\xdb\xe0n\x98\xeb\xa68y\x01*F\x8d\xde\x0f\xdeo\xd6"\xd0\x03.s\x10\xf0#gd\xf7L8\x9fI\xfa\x99ts\x9c\xb4-5\x9d\xed}\xcc\xed\xb6yg\x18<F\x8d\xca\x06\xd5!\x943\x82\x0b){\x1c\xec6"o\xb9\x1f\x18\xaeh\xbd'), '\x64' + '\145' + chr(0b1100011) + '\157' + chr(0b1100100) + chr(101))(chr(7232 - 7115) + '\164' + chr(0b1100110) + chr(0b101101) + chr(0b100 + 0o64)))
ARR4_kBXtaaZ = DvvoTxuoRCMY * tsdjvlgh9gDP(ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(896 - 785) + chr(1316 - 1267), 8), Dfo4F1zszySM // DvvoTxuoRCMY) + ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001), 8)
def cfGk5yRT7MF5(kP4qaKv0ZkGv):
PTHa4fKFxPzV = {}
for (OolUPRJhRaJd, cMbll0QYhULo) in xafqLlk3kkUe(kP4qaKv0ZkGv, xafqLlk3kkUe(SXOLrMavuUCe(b'Q\x8a\xbbd\\\xa1\xb1F\x80\xdb\x86!'), chr(0b1100100) + chr(1898 - 1797) + chr(0b1100011) + '\x6f' + chr(0b1001001 + 0o33) + chr(0b111001 + 0o54))(chr(0b1110101) + chr(0b100011 + 0o121) + '\x66' + chr(876 - 831) + '\070'))():
cMbll0QYhULo = IDJ2eXGCBCDu.data.experimental.get_single_element(cMbll0QYhULo.dNwAahu8tvoY(DvvoTxuoRCMY, drop_remainder=ehT0Px3KOsy9(chr(2282 - 2234) + chr(0b1101111) + chr(2222 - 2173), 8)))
PTHa4fKFxPzV[OolUPRJhRaJd] = cMbll0QYhULo
return xafqLlk3kkUe(IDJ2eXGCBCDu.data.Dataset, xafqLlk3kkUe(SXOLrMavuUCe(b'y\x82\xa2lJ\x8f\xe7a\x9f\xe7\xbcGy\x049@\xc8\xce'), '\x64' + chr(101) + '\143' + '\x6f' + chr(100) + chr(8927 - 8826))(chr(0b1110101) + chr(0b110 + 0o156) + chr(102) + chr(45) + chr(56)))(PTHa4fKFxPzV)
xQt6gV9VfTO3 = xQt6gV9VfTO3.apply(IDJ2eXGCBCDu.data.experimental.unbatch())
xQt6gV9VfTO3 = xQt6gV9VfTO3.window(DvvoTxuoRCMY, DvvoTxuoRCMY, ARR4_kBXtaaZ)
xQt6gV9VfTO3 = xQt6gV9VfTO3.flat_map(cfGk5yRT7MF5)
xQt6gV9VfTO3 = xQt6gV9VfTO3.dNwAahu8tvoY(DvvoTxuoRCMY, drop_remainder=ehT0Px3KOsy9(chr(48) + chr(0b1010010 + 0o35) + '\061', 8))
def iG6KGTHt0ZGt(kP4qaKv0ZkGv):
if not jAj7S20Ct06o or not xafqLlk3kkUe(jAj7S20Ct06o, xafqLlk3kkUe(SXOLrMavuUCe(b'j\x83\xa8^a\x8b\xf7'), chr(5250 - 5150) + chr(0b1010100 + 0o21) + chr(99) + chr(0b10001 + 0o136) + chr(0b1100100) + chr(101))(chr(0b1110101) + chr(0b1110100) + chr(0b1000111 + 0o37) + '\x2d' + chr(0b110101 + 0o3))):
cwjwmKAFjKmm(kP4qaKv0ZkGv, WJU3qUPk_Uro)
if holLFgwB7vsP == xafqLlk3kkUe(IDJ2eXGCBCDu.estimator.ModeKeys, xafqLlk3kkUe(SXOLrMavuUCe(b'O\xa2\x88E\\\xb8\xd6'), '\x64' + '\x65' + chr(0b1011111 + 0o4) + chr(135 - 24) + chr(100) + chr(9857 - 9756))(chr(0b1110101) + chr(116) + chr(0b101101 + 0o71) + '\x2d' + '\x38')):
kP4qaKv0ZkGv[xafqLlk3kkUe(SXOLrMavuUCe(b'v\x9e\xabdg\xa4\xf6n\x9e\xef\xably'), '\144' + '\145' + chr(0b1010101 + 0o16) + chr(11473 - 11362) + '\x64' + '\x65')(chr(0b1110011 + 0o2) + chr(5262 - 5146) + '\146' + '\x2d' + chr(56))] = kP4qaKv0ZkGv.pop(xafqLlk3kkUe(SXOLrMavuUCe(b'k\x91\xbffp\x8f\xf1'), chr(100) + '\x65' + '\143' + chr(0b1101111) + chr(0b1100100) + '\145')('\x75' + chr(0b1110010 + 0o2) + chr(0b11010 + 0o114) + '\055' + chr(56)))
return kP4qaKv0ZkGv
else:
return (kP4qaKv0ZkGv, kP4qaKv0ZkGv[xafqLlk3kkUe(SXOLrMavuUCe(b'k\x91\xbffp\x8f\xf1'), chr(100) + chr(2926 - 2825) + chr(99) + chr(0b1 + 0o156) + chr(0b11000 + 0o114) + '\x65')(chr(2282 - 2165) + chr(8320 - 8204) + '\146' + '\055' + chr(56))])
xQt6gV9VfTO3 = xQt6gV9VfTO3.map(iG6KGTHt0ZGt, num_parallel_calls=pCw22JJnmDr0)
xQt6gV9VfTO3 = xQt6gV9VfTO3.prefetch(ehT0Px3KOsy9(chr(48) + '\x6f' + chr(393 - 343), 8))
if holLFgwB7vsP == xafqLlk3kkUe(IDJ2eXGCBCDu.estimator.ModeKeys, xafqLlk3kkUe(SXOLrMavuUCe(b'O\xa2\x88E\\\xb8\xd6'), chr(0b1100100) + chr(101) + '\x63' + chr(8853 - 8742) + chr(5059 - 4959) + '\x65')(chr(117) + chr(4259 - 4143) + '\146' + chr(0b101101) + '\070')):
xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'~\x94\xa9^a\x94\xddl\x83\xe4\xa2}i\x1c9L\xc3'), chr(100) + '\145' + '\x63' + chr(0b1101111) + chr(0b1100100) + chr(129 - 28))(chr(247 - 130) + '\164' + chr(102) + chr(45) + chr(0b11111 + 0o31)))(xafqLlk3kkUe(IDJ2eXGCBCDu.GraphKeys, xafqLlk3kkUe(SXOLrMavuUCe(b'N\xa5\x88TP\xa4\xd0Z\xa2\xc6\x8bJY'), '\x64' + '\x65' + chr(5753 - 5654) + '\x6f' + '\x64' + '\145')(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + '\x2d' + chr(0b111000))), nwq3PKVegcl5())
return xQt6gV9VfTO3
|
tensorflow/tensor2tensor
|
tensor2tensor/data_generators/gene_expression.py
|
generate_shard_args
|
def generate_shard_args(outfiles, num_examples):
"""Generate start and end indices per outfile."""
num_shards = len(outfiles)
num_examples_per_shard = num_examples // num_shards
start_idxs = [i * num_examples_per_shard for i in range(num_shards)]
end_idxs = list(start_idxs)
end_idxs.pop(0)
end_idxs.append(num_examples)
return zip(start_idxs, end_idxs, outfiles)
|
python
|
def generate_shard_args(outfiles, num_examples):
"""Generate start and end indices per outfile."""
num_shards = len(outfiles)
num_examples_per_shard = num_examples // num_shards
start_idxs = [i * num_examples_per_shard for i in range(num_shards)]
end_idxs = list(start_idxs)
end_idxs.pop(0)
end_idxs.append(num_examples)
return zip(start_idxs, end_idxs, outfiles)
|
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] |
Generate start and end indices per outfile.
|
[
"Generate",
"start",
"and",
"end",
"indices",
"per",
"outfile",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/data_generators/gene_expression.py#L208-L216
|
train
|
Generate start and end indices per outfile.
|
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(9663 - 9552) + chr(0b100101 + 0o16) + chr(0b110010) + chr(55), 50493 - 50485), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(0b1101100 + 0o3) + '\063' + chr(0b1101 + 0o50) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x36' + chr(0b11100 + 0o27), 9506 - 9498), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b0 + 0o157) + chr(0b110011) + chr(2557 - 2506) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + '\060' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b110101 + 0o72) + '\x32' + chr(1144 - 1091) + chr(0b110010), 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\065' + '\063', 0b1000), ehT0Px3KOsy9('\060' + chr(6053 - 5942) + chr(51) + chr(54) + chr(0b101 + 0o62), 0b1000), ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\157' + chr(1805 - 1755) + '\067' + '\x36', 0o10), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(11153 - 11042) + chr(335 - 286) + chr(50) + '\x35', 24692 - 24684), ehT0Px3KOsy9(chr(281 - 233) + chr(111) + chr(0b110 + 0o55) + chr(1122 - 1073) + '\x32', 62824 - 62816), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110010) + '\062' + chr(0b11010 + 0o26), 8730 - 8722), ehT0Px3KOsy9(chr(48) + '\157' + chr(2209 - 2159) + chr(2329 - 2277) + chr(0b10110 + 0o37), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\064' + '\064', 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\061' + chr(1582 - 1534), 0b1000), ehT0Px3KOsy9(chr(758 - 710) + '\x6f' + chr(51) + chr(53) + chr(0b110001), 8071 - 8063), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(1554 - 1503) + chr(54) + '\x36', 30620 - 30612), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\157' + chr(49) + '\x37' + '\061', 59072 - 59064), ehT0Px3KOsy9('\x30' + chr(111) + '\066', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(0b11010 + 0o33) + '\x35', 34005 - 33997), ehT0Px3KOsy9(chr(0b110000) + chr(8472 - 8361) + chr(0b10011 + 0o36) + chr(1126 - 1075) + chr(55), 0o10), ehT0Px3KOsy9(chr(448 - 400) + '\x6f' + chr(0b11010 + 0o27) + '\x32' + '\060', 60410 - 60402), ehT0Px3KOsy9(chr(950 - 902) + '\157' + chr(548 - 497) + chr(0b110010), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + '\063' + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b1100 + 0o47) + chr(0b101010 + 0o14) + chr(55), 8), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + chr(0b110100) + chr(55), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\x31' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50) + chr(0b100011 + 0o15) + '\060', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1397 - 1345) + chr(0b101100 + 0o4), 64703 - 64695), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(0b1101111) + chr(0b110001) + chr(0b1010 + 0o55) + chr(1800 - 1746), 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\x6f' + chr(0b1000 + 0o51) + chr(0b1110 + 0o45) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(8682 - 8571) + '\x32' + '\066' + '\x36', 60165 - 60157), ehT0Px3KOsy9(chr(850 - 802) + chr(0b1011011 + 0o24) + chr(469 - 418) + chr(0b110101) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b0 + 0o60) + '\157' + chr(0b10000 + 0o47) + chr(54), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1100001 + 0o16) + '\x31' + chr(0b110001) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + chr(52) + chr(50), 15345 - 15337), ehT0Px3KOsy9(chr(1894 - 1846) + '\x6f' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(464 - 414) + chr(120 - 68) + '\x35', 8), ehT0Px3KOsy9('\060' + chr(111) + '\064' + chr(1977 - 1928), 7101 - 7093), ehT0Px3KOsy9('\x30' + chr(0b1010011 + 0o34) + chr(49) + '\065' + chr(0b110010), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(8976 - 8865) + '\x35' + chr(1982 - 1934), 12328 - 12320)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf9'), '\x64' + '\145' + '\143' + chr(0b11111 + 0o120) + '\144' + chr(101))(chr(4910 - 4793) + chr(0b10011 + 0o141) + '\x66' + chr(0b101101) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def _QEAJAzVjgJC(b07LITKzBXVw, reL9qOBFFFyj):
WJU3qUPk_Uro = c2A0yzQpDQB3(b07LITKzBXVw)
xsGObqSEqc3j = reL9qOBFFFyj // WJU3qUPk_Uro
Y3j5zT2uNsa_ = [WVxHKyX45z_L * xsGObqSEqc3j for WVxHKyX45z_L in vQr8gNKaIaWE(WJU3qUPk_Uro)]
KJ9biy1ys_4y = YyaZ4tpXu4lf(Y3j5zT2uNsa_)
xafqLlk3kkUe(KJ9biy1ys_4y, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa7\x81C'), '\x64' + chr(0b1100101) + chr(99) + '\157' + chr(0b1010100 + 0o20) + '\x65')(chr(10147 - 10030) + chr(0b1110100) + '\146' + chr(0b100010 + 0o13) + chr(56)))(ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10110 + 0o32), 8))
xafqLlk3kkUe(KJ9biy1ys_4y, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb6\x9eC\xbf*\xce'), '\144' + '\145' + '\x63' + chr(0b1011110 + 0o21) + chr(0b1100100) + chr(101))('\x75' + chr(0b0 + 0o164) + chr(0b1100101 + 0o1) + '\x2d' + chr(0b111000)))(reL9qOBFFFyj)
return pZ0NK2y6HRbn(Y3j5zT2uNsa_, KJ9biy1ys_4y, b07LITKzBXVw)
|
tensorflow/tensor2tensor
|
tensor2tensor/data_generators/gene_expression.py
|
dataset_generator
|
def dataset_generator(filepath,
dataset,
chunk_size=1,
start_idx=None,
end_idx=None):
"""Generate example dicts."""
encoder = dna_encoder.DNAEncoder(chunk_size=chunk_size)
with h5py.File(filepath, "r") as h5_file:
# Get input keys from h5_file
src_keys = [s % dataset for s in ["%s_in", "%s_na", "%s_out"]]
src_values = [h5_file[k] for k in src_keys]
inp_data, mask_data, out_data = src_values
assert len(set([v.len() for v in src_values])) == 1
if start_idx is None:
start_idx = 0
if end_idx is None:
end_idx = inp_data.len()
for i in range(start_idx, end_idx):
if i % 100 == 0:
print("Generating example %d for %s" % (i, dataset))
inputs, mask, outputs = inp_data[i], mask_data[i], out_data[i]
ex_dict = to_example_dict(encoder, inputs, mask, outputs)
# Original data has one output for every 128 input bases. Ensure that the
# ratio has been maintained given the chunk size and removing EOS.
assert (len(ex_dict["inputs"]) - 1) == ((
128 // chunk_size) * ex_dict["targets_shape"][0])
yield ex_dict
|
python
|
def dataset_generator(filepath,
dataset,
chunk_size=1,
start_idx=None,
end_idx=None):
"""Generate example dicts."""
encoder = dna_encoder.DNAEncoder(chunk_size=chunk_size)
with h5py.File(filepath, "r") as h5_file:
# Get input keys from h5_file
src_keys = [s % dataset for s in ["%s_in", "%s_na", "%s_out"]]
src_values = [h5_file[k] for k in src_keys]
inp_data, mask_data, out_data = src_values
assert len(set([v.len() for v in src_values])) == 1
if start_idx is None:
start_idx = 0
if end_idx is None:
end_idx = inp_data.len()
for i in range(start_idx, end_idx):
if i % 100 == 0:
print("Generating example %d for %s" % (i, dataset))
inputs, mask, outputs = inp_data[i], mask_data[i], out_data[i]
ex_dict = to_example_dict(encoder, inputs, mask, outputs)
# Original data has one output for every 128 input bases. Ensure that the
# ratio has been maintained given the chunk size and removing EOS.
assert (len(ex_dict["inputs"]) - 1) == ((
128 // chunk_size) * ex_dict["targets_shape"][0])
yield ex_dict
|
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] |
Generate example dicts.
|
[
"Generate",
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/data_generators/gene_expression.py#L232-L260
|
train
|
Generate example dicts for a dataset.
|
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) + chr(50) + chr(0b10001 + 0o37) + chr(0b0 + 0o62), ord("\x08")), ehT0Px3KOsy9(chr(2086 - 2038) + chr(4995 - 4884) + chr(51) + chr(0b110001) + chr(0b110101 + 0o2), 0o10), ehT0Px3KOsy9(chr(0b101000 + 0o10) + '\x6f' + chr(51) + chr(53) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b10001 + 0o136) + '\x31' + chr(0b110010 + 0o0), ord("\x08")), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(6127 - 6016) + chr(0b110110) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\157' + chr(0b11010 + 0o30) + '\061' + chr(88 - 34), 0o10), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b1000 + 0o147) + chr(50) + chr(0b110101) + chr(0b100110 + 0o17), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110110) + chr(53), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110100) + chr(1767 - 1716), 0b1000), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b1001110 + 0o41) + chr(767 - 716) + chr(48) + chr(0b100101 + 0o15), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + chr(2248 - 2195) + '\x32', 0b1000), ehT0Px3KOsy9('\060' + chr(10658 - 10547) + '\x33' + '\064' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(9382 - 9271) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(0b1110 + 0o141) + chr(0b110101) + chr(2669 - 2616), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b10001 + 0o42) + chr(0b110000) + '\x34', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b11111 + 0o120) + chr(0b11001 + 0o32) + chr(0b11000 + 0o33) + '\065', 7298 - 7290), ehT0Px3KOsy9('\060' + chr(10876 - 10765) + chr(0b110010) + '\064' + chr(342 - 292), 54094 - 54086), ehT0Px3KOsy9(chr(1957 - 1909) + '\157' + '\x31' + '\064' + chr(50), 33436 - 33428), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + '\x31' + chr(0b0 + 0o63), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b100101 + 0o112) + '\062' + chr(0b110111) + chr(51), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110101) + chr(53), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b1010 + 0o50) + chr(0b110010) + chr(52), 0o10), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(111) + chr(2051 - 2000) + chr(2850 - 2795) + chr(0b10101 + 0o37), 37215 - 37207), ehT0Px3KOsy9(chr(952 - 904) + chr(111) + '\061' + '\065' + chr(0b110010), 28354 - 28346), ehT0Px3KOsy9('\x30' + '\157' + '\061' + chr(0b110111) + chr(48), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + chr(52) + '\062', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011100 + 0o23) + chr(0b101101 + 0o5) + '\x30' + chr(0b100001 + 0o24), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + chr(1701 - 1647) + chr(0b110101 + 0o0), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(53) + chr(54), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(1621 - 1570) + '\062' + '\060', 16854 - 16846), ehT0Px3KOsy9(chr(0b110000) + chr(1650 - 1539) + '\064' + chr(52), 26935 - 26927), ehT0Px3KOsy9(chr(48) + chr(1056 - 945) + '\061' + '\x34' + '\067', 39576 - 39568), ehT0Px3KOsy9(chr(0b10101 + 0o33) + '\x6f' + chr(669 - 620) + chr(0b110101) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000 + 0o147) + '\x32' + '\x37' + chr(0b110110), 36626 - 36618), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2379 - 2329) + chr(49) + chr(94 - 40), 8), ehT0Px3KOsy9('\060' + chr(0b11110 + 0o121) + chr(0b110001) + chr(228 - 177) + chr(0b101110 + 0o11), 0o10), ehT0Px3KOsy9(chr(1613 - 1565) + chr(0b1101100 + 0o3) + '\061' + '\x31' + '\063', 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + '\060' + chr(837 - 788), 59809 - 59801), ehT0Px3KOsy9(chr(533 - 485) + chr(9020 - 8909) + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(10136 - 10025) + '\x32' + '\x34' + chr(0b1010 + 0o51), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\065' + chr(386 - 338), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xac'), chr(4807 - 4707) + chr(0b1100101) + '\143' + chr(4003 - 3892) + '\x64' + chr(0b1100101))(chr(0b1110101) + chr(11277 - 11161) + '\146' + chr(0b0 + 0o55) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def EAQXlCVVOzTV(D3zslhgxMHWQ, xQt6gV9VfTO3, ha7Qr2IqbXbY=ehT0Px3KOsy9('\060' + '\x6f' + '\x31', 0b1000), NOt5Gkf5z9g4=None, p6zNIQAtD3F5=None):
hoK3K1TwFlkr = bf8f7F8oE9rk.DNAEncoder(chunk_size=ha7Qr2IqbXbY)
with xafqLlk3kkUe(aKlwkq0m2IdK, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc4\xa6\x85o'), chr(0b1100100) + '\x65' + chr(0b1001000 + 0o33) + chr(111) + chr(4855 - 4755) + chr(101))(chr(0b1001010 + 0o53) + '\x74' + '\146' + '\x2d' + chr(0b110110 + 0o2)))(D3zslhgxMHWQ, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf0'), '\144' + '\x65' + chr(0b1100011) + chr(0b1010010 + 0o35) + chr(0b10100 + 0o120) + chr(0b11101 + 0o110))(chr(0b100000 + 0o125) + chr(8454 - 8338) + '\146' + '\x2d' + chr(0b11 + 0o65))) as pQUW2um5i6vi:
YC_xc9XCQvUL = [vGrByMSYMp9h % xQt6gV9VfTO3 for vGrByMSYMp9h in [xafqLlk3kkUe(SXOLrMavuUCe(b'\xa7\xbc\xb6c['), chr(7628 - 7528) + '\145' + chr(99) + chr(0b111101 + 0o62) + '\144' + chr(2780 - 2679))('\165' + chr(3179 - 3063) + chr(7182 - 7080) + chr(45) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xa7\xbc\xb6dT'), chr(6811 - 6711) + '\x65' + '\143' + '\x6f' + '\x64' + '\x65')(chr(117) + '\x74' + chr(0b1000001 + 0o45) + '\055' + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xa7\xbc\xb6e@\xfa'), '\144' + '\145' + '\143' + '\x6f' + chr(0b1 + 0o143) + '\145')(chr(0b1110101) + chr(0b1110100) + chr(0b100010 + 0o104) + chr(45) + chr(0b1 + 0o67))]]
WCxSgSefH9Hg = [pQUW2um5i6vi[OolUPRJhRaJd] for OolUPRJhRaJd in YC_xc9XCQvUL]
(o0TKzTLatylE, Moqgi9p5eaLY, oYrSIQieWlfI) = WCxSgSefH9Hg
assert c2A0yzQpDQB3(MVEN8G6CxlvR([xafqLlk3kkUe(cMbll0QYhULo, xafqLlk3kkUe(SXOLrMavuUCe(b'\xee\xaa\x87'), chr(100) + chr(0b1100101) + chr(0b1100011) + chr(12132 - 12021) + '\x64' + chr(0b1001010 + 0o33))('\165' + chr(116) + '\146' + '\x2d' + '\070'))() for cMbll0QYhULo in WCxSgSefH9Hg])) == ehT0Px3KOsy9('\x30' + chr(7709 - 7598) + chr(49), 8)
if NOt5Gkf5z9g4 is None:
NOt5Gkf5z9g4 = ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(48), ord("\x08"))
if p6zNIQAtD3F5 is None:
p6zNIQAtD3F5 = o0TKzTLatylE.len()
for WVxHKyX45z_L in vQr8gNKaIaWE(NOt5Gkf5z9g4, p6zNIQAtD3F5):
if WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\157' + chr(0b11111 + 0o22) + '\064' + '\064', 0o10) == ehT0Px3KOsy9(chr(0b1000 + 0o50) + '\x6f' + chr(266 - 218), 8):
zLUzGokYBM2Z(xafqLlk3kkUe(SXOLrMavuUCe(b'\xc5\xaa\x87oG\xef\xd9\\M\xa5\xca\x83zL\xa9\xad\xce\x07k\x9eI\xb4\x9a\x05\n\x82\xa0\x06'), '\144' + '\x65' + '\143' + chr(9323 - 9212) + '\x64' + chr(0b1100101))(chr(0b1010011 + 0o42) + '\164' + chr(3964 - 3862) + '\055' + '\070') % (WVxHKyX45z_L, xQt6gV9VfTO3))
(vXoupepMtCXU, Iz1jSgUKZDvt, Dx_DllZ8uCko) = (o0TKzTLatylE[WVxHKyX45z_L], Moqgi9p5eaLY[WVxHKyX45z_L], oYrSIQieWlfI[WVxHKyX45z_L])
WgDbEGQpjqHN = pvR7OHwGHmRQ(hoK3K1TwFlkr, vXoupepMtCXU, Iz1jSgUKZDvt, Dx_DllZ8uCko)
assert c2A0yzQpDQB3(WgDbEGQpjqHN[xafqLlk3kkUe(SXOLrMavuUCe(b'\xeb\xa1\x99\x7fA\xfd'), chr(0b1001111 + 0o25) + chr(0b1100101) + '\143' + '\157' + chr(100) + chr(0b1000100 + 0o41))(chr(117) + chr(116) + chr(8134 - 8032) + chr(0b10100 + 0o31) + chr(0b10010 + 0o46))]) - ehT0Px3KOsy9('\060' + '\157' + chr(49), 8) == ehT0Px3KOsy9('\x30' + '\157' + chr(50) + chr(0b101010 + 0o6) + chr(0b110000), 14742 - 14734) // ha7Qr2IqbXbY * WgDbEGQpjqHN[xafqLlk3kkUe(SXOLrMavuUCe(b'\xf6\xae\x9bmP\xfa\xdejP\xaa\x8b\x96g'), chr(9149 - 9049) + chr(7993 - 7892) + chr(1706 - 1607) + chr(0b101100 + 0o103) + '\x64' + chr(0b1100101))(chr(8635 - 8518) + chr(0b1110100) + chr(7904 - 7802) + '\055' + chr(0b11 + 0o65))][ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\060', 8)]
yield WgDbEGQpjqHN
|
tensorflow/tensor2tensor
|
tensor2tensor/data_generators/gene_expression.py
|
to_example_dict
|
def to_example_dict(encoder, inputs, mask, outputs):
"""Convert single h5 record to an example dict."""
# Inputs
bases = []
input_ids = []
last_idx = -1
for row in np.argwhere(inputs):
idx, base_id = row
idx, base_id = int(idx), int(base_id)
assert idx > last_idx # if not, means 2 True values in 1 row
# Some rows are all False. Those rows are mapped to UNK_ID.
while idx != last_idx + 1:
bases.append(encoder.UNK)
last_idx += 1
bases.append(encoder.BASES[base_id])
last_idx = idx
assert len(inputs) == len(bases)
input_ids = encoder.encode(bases)
input_ids.append(text_encoder.EOS_ID)
# Targets: mask and output
targets_mask = [float(v) for v in mask]
# The output is (n, m); store targets_shape so that it can be reshaped
# properly on the other end.
targets = [float(v) for v in outputs.flatten()]
targets_shape = [int(dim) for dim in outputs.shape]
assert mask.shape[0] == outputs.shape[0]
example_keys = ["inputs", "targets_mask", "targets", "targets_shape"]
ex_dict = dict(
zip(example_keys, [input_ids, targets_mask, targets, targets_shape]))
return ex_dict
|
python
|
def to_example_dict(encoder, inputs, mask, outputs):
"""Convert single h5 record to an example dict."""
# Inputs
bases = []
input_ids = []
last_idx = -1
for row in np.argwhere(inputs):
idx, base_id = row
idx, base_id = int(idx), int(base_id)
assert idx > last_idx # if not, means 2 True values in 1 row
# Some rows are all False. Those rows are mapped to UNK_ID.
while idx != last_idx + 1:
bases.append(encoder.UNK)
last_idx += 1
bases.append(encoder.BASES[base_id])
last_idx = idx
assert len(inputs) == len(bases)
input_ids = encoder.encode(bases)
input_ids.append(text_encoder.EOS_ID)
# Targets: mask and output
targets_mask = [float(v) for v in mask]
# The output is (n, m); store targets_shape so that it can be reshaped
# properly on the other end.
targets = [float(v) for v in outputs.flatten()]
targets_shape = [int(dim) for dim in outputs.shape]
assert mask.shape[0] == outputs.shape[0]
example_keys = ["inputs", "targets_mask", "targets", "targets_shape"]
ex_dict = dict(
zip(example_keys, [input_ids, targets_mask, targets, targets_shape]))
return ex_dict
|
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Convert single h5 record to an example dict.
|
[
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"record",
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/data_generators/gene_expression.py#L263-L295
|
train
|
Convert a single h5 record to an example dict.
|
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(0b101 + 0o54) + chr(0b110001) + chr(1678 - 1625), 0b1000), ehT0Px3KOsy9(chr(0b101000 + 0o10) + '\157' + chr(0b10110 + 0o34) + chr(0b100111 + 0o12) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(8512 - 8401) + chr(0b110010) + chr(0b100000 + 0o25) + chr(1465 - 1417), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + chr(0b110011) + '\065', 51641 - 51633), ehT0Px3KOsy9('\x30' + chr(6951 - 6840) + chr(49) + chr(2541 - 2489) + chr(0b0 + 0o62), 0b1000), ehT0Px3KOsy9('\x30' + chr(612 - 501) + chr(0b110010) + chr(0b110001) + chr(0b110001 + 0o2), ord("\x08")), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b1101000 + 0o7) + chr(2339 - 2289) + '\060' + '\065', 61272 - 61264), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + '\x34' + chr(144 - 96), 24206 - 24198), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b1101110 + 0o1) + '\062' + chr(52) + chr(0b100000 + 0o20), 0b1000), ehT0Px3KOsy9(chr(1960 - 1912) + '\x6f' + '\064' + chr(0b10011 + 0o40), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1001011 + 0o44) + '\063' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + '\061' + '\x34', 0b1000), ehT0Px3KOsy9(chr(1905 - 1857) + '\157' + chr(2951 - 2896), 49239 - 49231), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(111) + chr(0b1110 + 0o45) + '\x34', 8015 - 8007), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + '\x37' + '\065', 45016 - 45008), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + chr(0b110010 + 0o0) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1001011 + 0o44) + chr(441 - 391), 0o10), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(111) + chr(0b110100) + chr(0b101101 + 0o7), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1000001 + 0o56) + '\061' + chr(0b110101) + chr(0b10100 + 0o36), 38569 - 38561), ehT0Px3KOsy9(chr(397 - 349) + chr(111) + chr(2237 - 2188) + '\062' + chr(107 - 56), 57553 - 57545), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + chr(0b110101) + chr(0b1101 + 0o46), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11011 + 0o34) + chr(52), 0o10), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1101111) + '\x31' + chr(0b110000) + chr(48), 56764 - 56756), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(0b1101111) + chr(1411 - 1362) + '\062' + chr(54), 19964 - 19956), ehT0Px3KOsy9('\x30' + '\x6f' + chr(911 - 860) + '\065', 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(7552 - 7441) + chr(49) + chr(2364 - 2313) + chr(51), 35568 - 35560), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + '\067' + '\x31', 751 - 743), ehT0Px3KOsy9('\060' + chr(0b1010010 + 0o35) + '\063' + chr(0b10100 + 0o40) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(65 - 17) + '\157' + chr(0b110011) + chr(55) + '\064', 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(7229 - 7118) + '\063' + '\x34' + chr(1838 - 1783), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x31' + '\061' + chr(55), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\062' + chr(0b110110) + chr(0b1101 + 0o52), 35904 - 35896), ehT0Px3KOsy9('\060' + chr(10561 - 10450) + '\x37' + '\060', 4179 - 4171), ehT0Px3KOsy9('\x30' + '\157' + '\063' + chr(0b11010 + 0o31) + '\x32', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\064', 0b1000), ehT0Px3KOsy9(chr(2100 - 2052) + chr(7751 - 7640) + '\061' + chr(424 - 376) + chr(55), 54393 - 54385), ehT0Px3KOsy9(chr(1901 - 1853) + chr(11227 - 11116) + '\x31' + '\063' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(1533 - 1485) + chr(0b1101111) + chr(0b11101 + 0o26) + '\x30' + chr(0b10101 + 0o40), ord("\x08")), ehT0Px3KOsy9(chr(1579 - 1531) + chr(0b1101111) + '\063' + chr(0b1000 + 0o56) + chr(53), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(111) + chr(2216 - 2163) + chr(0b110000), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'c'), chr(0b1100100) + chr(101) + '\143' + '\x6f' + chr(0b1100100) + chr(7124 - 7023))(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + chr(0b101101) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def pvR7OHwGHmRQ(hoK3K1TwFlkr, vXoupepMtCXU, Iz1jSgUKZDvt, Dx_DllZ8uCko):
TeVqVbGfVXKA = []
CyiZkgWrlgA9 = []
aCoHNt9Gd6OJ = -ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061', 0b1000)
for TAK9K32TkBdA in xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b',\xfd\xcf\xea\n\xee\xf7\x05'), '\x64' + '\x65' + '\143' + '\157' + chr(1100 - 1000) + chr(0b1100101))(chr(117) + chr(0b1010101 + 0o37) + chr(0b11001 + 0o115) + '\055' + chr(0b11001 + 0o37)))(vXoupepMtCXU):
(YlqusYB6InkM, QGblK_IVy2Ip) = TAK9K32TkBdA
(YlqusYB6InkM, QGblK_IVy2Ip) = (ehT0Px3KOsy9(YlqusYB6InkM), ehT0Px3KOsy9(QGblK_IVy2Ip))
assert YlqusYB6InkM > aCoHNt9Gd6OJ
while YlqusYB6InkM != aCoHNt9Gd6OJ + ehT0Px3KOsy9(chr(0b1000 + 0o50) + '\157' + '\x31', 8):
xafqLlk3kkUe(TeVqVbGfVXKA, xafqLlk3kkUe(SXOLrMavuUCe(b',\xff\xd8\xf8\x0c\xef'), chr(0b1100100) + '\x65' + chr(0b1001000 + 0o33) + '\157' + '\x64' + chr(0b1100 + 0o131))('\x75' + chr(116) + '\x66' + chr(1874 - 1829) + chr(56)))(xafqLlk3kkUe(hoK3K1TwFlkr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x18\xc1\xe3'), chr(0b10100 + 0o120) + chr(4266 - 4165) + chr(0b1100011) + '\x6f' + '\x64' + chr(0b1100101))(chr(0b11101 + 0o130) + '\164' + chr(102) + chr(1307 - 1262) + chr(56))))
aCoHNt9Gd6OJ += ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(11397 - 11286) + chr(49), 8)
xafqLlk3kkUe(TeVqVbGfVXKA, xafqLlk3kkUe(SXOLrMavuUCe(b',\xff\xd8\xf8\x0c\xef'), '\x64' + '\x65' + chr(0b1100011) + '\x6f' + '\144' + chr(0b100000 + 0o105))(chr(11850 - 11733) + chr(116) + '\x66' + chr(45) + chr(56)))(xafqLlk3kkUe(hoK3K1TwFlkr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0f\xce\xfb\xd81'), '\144' + '\145' + chr(7992 - 7893) + chr(0b1000101 + 0o52) + chr(100) + '\145')(chr(7213 - 7096) + chr(0b1011100 + 0o30) + chr(0b10000 + 0o126) + '\x2d' + chr(2018 - 1962)))[QGblK_IVy2Ip])
aCoHNt9Gd6OJ = YlqusYB6InkM
assert c2A0yzQpDQB3(vXoupepMtCXU) == c2A0yzQpDQB3(TeVqVbGfVXKA)
CyiZkgWrlgA9 = hoK3K1TwFlkr.encode(TeVqVbGfVXKA)
xafqLlk3kkUe(CyiZkgWrlgA9, xafqLlk3kkUe(SXOLrMavuUCe(b',\xff\xd8\xf8\x0c\xef'), chr(0b1011001 + 0o13) + '\x65' + '\143' + '\157' + chr(0b100000 + 0o104) + '\145')(chr(0b101100 + 0o111) + chr(0b1110100) + chr(10068 - 9966) + chr(45) + chr(2003 - 1947)))(xafqLlk3kkUe(nCRDzZ_Is9fz, xafqLlk3kkUe(SXOLrMavuUCe(b'\x08\xc0\xfb\xc2+\xcf'), chr(100) + chr(0b1010101 + 0o20) + chr(237 - 138) + '\x6f' + '\x64' + chr(2926 - 2825))(chr(117) + chr(0b1110100) + '\146' + chr(1751 - 1706) + chr(56))))
BHw9bGdZny4p = [kkSX4ccExqw4(cMbll0QYhULo) for cMbll0QYhULo in Iz1jSgUKZDvt]
xIEmRseySp3z = [kkSX4ccExqw4(cMbll0QYhULo) for cMbll0QYhULo in Dx_DllZ8uCko.flatten()]
qGCVeFvxIRjf = [ehT0Px3KOsy9(Nl_JhL3qUwSN) for Nl_JhL3qUwSN in Dx_DllZ8uCko.nauYfLglTpcb]
assert xafqLlk3kkUe(Iz1jSgUKZDvt, xafqLlk3kkUe(SXOLrMavuUCe(b'#\xee\xdd\xc4\x04\xc7\xe2\x0c\xf4Sy\xee'), chr(0b111001 + 0o53) + '\x65' + chr(0b1100011) + chr(0b110100 + 0o73) + chr(0b101100 + 0o70) + chr(0b1000 + 0o135))(chr(10271 - 10154) + chr(8416 - 8300) + '\x66' + chr(45) + '\070'))[ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(6672 - 6561) + chr(215 - 167), ord("\x08"))] == xafqLlk3kkUe(Dx_DllZ8uCko, xafqLlk3kkUe(SXOLrMavuUCe(b'#\xee\xdd\xc4\x04\xc7\xe2\x0c\xf4Sy\xee'), chr(100) + '\145' + chr(99) + chr(4363 - 4252) + '\x64' + chr(0b1100101))(chr(13648 - 13531) + chr(0b110101 + 0o77) + '\146' + '\055' + chr(56)))[ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b1101111) + chr(0b11000 + 0o30), 8)]
LJ6uS3pgieAj = [xafqLlk3kkUe(SXOLrMavuUCe(b'$\xe1\xd8\xe8\x16\xf8'), chr(100) + '\x65' + chr(726 - 627) + chr(0b1100110 + 0o11) + chr(100) + '\x65')(chr(0b1110101) + chr(116) + chr(0b11000 + 0o116) + chr(45) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'9\xee\xda\xfa\x07\xff\xf6?\xcdBi\xe7'), '\x64' + chr(101) + chr(8631 - 8532) + '\x6f' + chr(100) + '\145')(chr(0b11000 + 0o135) + chr(0b1101000 + 0o14) + chr(1447 - 1345) + chr(1737 - 1692) + chr(1555 - 1499)), xafqLlk3kkUe(SXOLrMavuUCe(b'9\xee\xda\xfa\x07\xff\xf6'), chr(8369 - 8269) + '\145' + chr(0b10 + 0o141) + '\x6f' + chr(0b1100100) + chr(101))('\x75' + '\x74' + chr(663 - 561) + '\055' + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'9\xee\xda\xfa\x07\xff\xf6?\xd3K{\xfcb'), chr(0b1100000 + 0o4) + chr(101) + chr(4118 - 4019) + chr(111) + chr(100) + '\x65')(chr(117) + chr(0b1010101 + 0o37) + '\x66' + '\055' + chr(0b1110 + 0o52))]
WgDbEGQpjqHN = wLqBDw8l0eIm(pZ0NK2y6HRbn(LJ6uS3pgieAj, [CyiZkgWrlgA9, BHw9bGdZny4p, xIEmRseySp3z, qGCVeFvxIRjf]))
return WgDbEGQpjqHN
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
linear_interpolate
|
def linear_interpolate(tensor1, tensor2, coeffs):
"""Linearly interpolate between two tensors at coeff.
Args:
tensor1: 4-D Tensor, shape=(NHWC)
tensor2: 4-D Tensor, shape=(NHWC)
coeffs: list of floats.
Returns:
interp_latents: 5-D Tensor, with interp_latents[i] representing
interpolations at coeffs[i].
shape=(len(coeffs), NHWC)
"""
interp_tensors = []
for coeff in coeffs:
interp_tensor = tensor1 + coeff * (tensor2 - tensor1)
interp_tensors.append(interp_tensor)
return tf.concat(interp_tensors, axis=0)
|
python
|
def linear_interpolate(tensor1, tensor2, coeffs):
"""Linearly interpolate between two tensors at coeff.
Args:
tensor1: 4-D Tensor, shape=(NHWC)
tensor2: 4-D Tensor, shape=(NHWC)
coeffs: list of floats.
Returns:
interp_latents: 5-D Tensor, with interp_latents[i] representing
interpolations at coeffs[i].
shape=(len(coeffs), NHWC)
"""
interp_tensors = []
for coeff in coeffs:
interp_tensor = tensor1 + coeff * (tensor2 - tensor1)
interp_tensors.append(interp_tensor)
return tf.concat(interp_tensors, axis=0)
|
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"tf",
".",
"concat",
"(",
"interp_tensors",
",",
"axis",
"=",
"0",
")"
] |
Linearly interpolate between two tensors at coeff.
Args:
tensor1: 4-D Tensor, shape=(NHWC)
tensor2: 4-D Tensor, shape=(NHWC)
coeffs: list of floats.
Returns:
interp_latents: 5-D Tensor, with interp_latents[i] representing
interpolations at coeffs[i].
shape=(len(coeffs), NHWC)
|
[
"Linearly",
"interpolate",
"between",
"two",
"tensors",
"at",
"coeff",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L34-L50
|
train
|
Linearly interpolate between two tensors at coeff.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(824 - 776) + '\157' + '\x31' + chr(0b110001) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1011000 + 0o27) + chr(0b110001) + chr(685 - 632) + chr(0b101000 + 0o16), 0o10), ehT0Px3KOsy9(chr(750 - 702) + chr(10787 - 10676) + chr(0b110010) + '\x32' + chr(48), 0o10), ehT0Px3KOsy9('\060' + chr(12250 - 12139) + '\x32' + '\062' + chr(326 - 274), 53825 - 53817), ehT0Px3KOsy9('\060' + chr(111) + chr(462 - 413) + chr(0b100100 + 0o22) + '\067', 21709 - 21701), ehT0Px3KOsy9('\x30' + '\x6f' + chr(51) + chr(2437 - 2384) + chr(0b10000 + 0o41), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\063' + '\x37' + chr(2410 - 2359), 0b1000), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(8913 - 8802) + chr(0b110110 + 0o1) + chr(0b11110 + 0o31), 37347 - 37339), ehT0Px3KOsy9('\060' + chr(111) + chr(0b101000 + 0o11) + chr(0b101010 + 0o14) + chr(907 - 852), 8), ehT0Px3KOsy9('\060' + chr(0b11011 + 0o124) + chr(0b110001) + chr(878 - 823), 0o10), ehT0Px3KOsy9(chr(0b10 + 0o56) + '\157' + '\x31' + chr(0b1111 + 0o45) + chr(54), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + chr(2247 - 2195) + chr(0b1011 + 0o45), ord("\x08")), ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\x6f' + chr(50) + chr(495 - 447) + '\x34', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + chr(0b11110 + 0o22) + chr(0b101011 + 0o11), 8), ehT0Px3KOsy9('\x30' + chr(9615 - 9504) + chr(0b1001 + 0o52) + chr(0b110000) + '\060', ord("\x08")), ehT0Px3KOsy9('\060' + chr(7864 - 7753) + '\063' + '\067' + chr(2402 - 2351), 8), ehT0Px3KOsy9(chr(294 - 246) + chr(282 - 171) + chr(0b10000 + 0o41) + '\x35' + chr(0b10010 + 0o44), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b10010 + 0o41) + chr(623 - 570) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1976 - 1927) + chr(0b101000 + 0o13) + chr(2024 - 1971), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1000 + 0o147) + chr(0b1010 + 0o47) + chr(52) + chr(49), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b10110 + 0o33) + chr(1502 - 1447) + chr(0b11001 + 0o34), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + '\x32' + chr(1045 - 996), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + chr(51), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\061' + chr(0b100000 + 0o21), 33703 - 33695), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\x6f' + chr(0b11000 + 0o35) + chr(2115 - 2060), ord("\x08")), ehT0Px3KOsy9('\060' + chr(1202 - 1091) + chr(0b10001 + 0o41) + chr(0b110100) + chr(387 - 335), 0o10), ehT0Px3KOsy9(chr(2210 - 2162) + '\x6f' + '\062' + '\060' + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(365 - 317) + chr(0b1101101 + 0o2) + chr(0b110010) + chr(48) + '\064', 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + '\x30' + chr(1657 - 1604), 33114 - 33106), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + chr(50) + chr(0b1100 + 0o50), 8), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\x6f' + chr(51) + chr(0b10001 + 0o43) + '\067', 52172 - 52164), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + '\064' + '\x34', 0o10), ehT0Px3KOsy9(chr(1440 - 1392) + chr(0b1000111 + 0o50) + chr(53) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(2227 - 2176) + chr(0b10110 + 0o32) + '\065', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b110110 + 0o71) + chr(0b110011) + '\x30' + chr(0b110101), 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + '\x31' + chr(0b10110 + 0o32), 62641 - 62633), ehT0Px3KOsy9('\060' + '\157' + chr(436 - 386) + '\063' + chr(404 - 355), 32443 - 32435), ehT0Px3KOsy9('\x30' + '\157' + chr(55) + chr(49), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\063' + chr(0b100110 + 0o15), 901 - 893), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\063' + '\x33' + '\x32', 62456 - 62448)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(0b1001001 + 0o46) + chr(0b110101) + chr(479 - 431), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'd'), chr(6613 - 6513) + '\145' + chr(5009 - 4910) + chr(10549 - 10438) + '\144' + chr(101))(chr(0b1110101) + '\164' + '\x66' + '\x2d' + chr(0b1 + 0o67)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def EGCvNjfl2iz3(_GoaLGZ5U6xS, H6fJ9QOZaJmh, Mq2X4hHIvLYE):
hpt8yJLmdtZP = []
for reNPK3PqEOpR in Mq2X4hHIvLYE:
tgH570glvJIv = _GoaLGZ5U6xS + reNPK3PqEOpR * (H6fJ9QOZaJmh - _GoaLGZ5U6xS)
xafqLlk3kkUe(hpt8yJLmdtZP, xafqLlk3kkUe(SXOLrMavuUCe(b'+\x1e\xe0\xf1\x19\x8d'), chr(0b1100100) + chr(0b1100101) + chr(9161 - 9062) + chr(111) + '\144' + chr(0b11111 + 0o106))('\x75' + chr(116) + chr(3434 - 3332) + '\x2d' + '\x38'))(tgH570glvJIv)
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b')\x01\xfe\xf7\x16\x9d'), chr(9235 - 9135) + chr(0b1100101) + '\x63' + chr(0b1101111) + chr(100) + chr(0b110101 + 0o60))(chr(0b1110011 + 0o2) + chr(116) + chr(102) + chr(45) + '\x38'))(hpt8yJLmdtZP, axis=ehT0Px3KOsy9(chr(0b100101 + 0o13) + '\157' + chr(0b110000), 0o10))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
linear_interpolate_rank
|
def linear_interpolate_rank(tensor1, tensor2, coeffs, rank=1):
"""Linearly interpolate channel at "rank" between two tensors.
The channels are ranked according to their L2 norm between tensor1[channel]
and tensor2[channel].
Args:
tensor1: 4-D Tensor, NHWC
tensor2: 4-D Tensor, NHWC
coeffs: list of floats.
rank: integer.
Returns:
interp_latents: list of interpolated 4-D Tensors, shape=(NHWC)
"""
# sum across space, max across channels.
_, _, _, num_channels = common_layers.shape_list(tensor1)
diff_sq_sum = tf.reduce_sum((tensor1 - tensor2)**2, axis=(0, 1, 2))
_, feature_ranks = tf.math.top_k(diff_sq_sum, k=rank)
feature_rank = feature_ranks[-1]
channel_inds = tf.range(num_channels, dtype=tf.int32)
channel_mask = tf.equal(channel_inds, feature_rank)
ones_t = tf.ones(num_channels, dtype=tf.float32)
zeros_t = tf.zeros(num_channels, dtype=tf.float32)
interp_tensors = []
for coeff in coeffs:
curr_coeff = tf.where(channel_mask, coeff * ones_t, zeros_t)
interp_tensor = tensor1 + curr_coeff * (tensor2 - tensor1)
interp_tensors.append(interp_tensor)
return tf.concat(interp_tensors, axis=0)
|
python
|
def linear_interpolate_rank(tensor1, tensor2, coeffs, rank=1):
"""Linearly interpolate channel at "rank" between two tensors.
The channels are ranked according to their L2 norm between tensor1[channel]
and tensor2[channel].
Args:
tensor1: 4-D Tensor, NHWC
tensor2: 4-D Tensor, NHWC
coeffs: list of floats.
rank: integer.
Returns:
interp_latents: list of interpolated 4-D Tensors, shape=(NHWC)
"""
# sum across space, max across channels.
_, _, _, num_channels = common_layers.shape_list(tensor1)
diff_sq_sum = tf.reduce_sum((tensor1 - tensor2)**2, axis=(0, 1, 2))
_, feature_ranks = tf.math.top_k(diff_sq_sum, k=rank)
feature_rank = feature_ranks[-1]
channel_inds = tf.range(num_channels, dtype=tf.int32)
channel_mask = tf.equal(channel_inds, feature_rank)
ones_t = tf.ones(num_channels, dtype=tf.float32)
zeros_t = tf.zeros(num_channels, dtype=tf.float32)
interp_tensors = []
for coeff in coeffs:
curr_coeff = tf.where(channel_mask, coeff * ones_t, zeros_t)
interp_tensor = tensor1 + curr_coeff * (tensor2 - tensor1)
interp_tensors.append(interp_tensor)
return tf.concat(interp_tensors, axis=0)
|
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Linearly interpolate channel at "rank" between two tensors.
The channels are ranked according to their L2 norm between tensor1[channel]
and tensor2[channel].
Args:
tensor1: 4-D Tensor, NHWC
tensor2: 4-D Tensor, NHWC
coeffs: list of floats.
rank: integer.
Returns:
interp_latents: list of interpolated 4-D Tensors, shape=(NHWC)
|
[
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L53-L82
|
train
|
Linearly interpolate channel at rank between two tensors.
|
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) + '\x32' + chr(0b110000 + 0o2) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(1241 - 1190) + chr(48), 27610 - 27602), ehT0Px3KOsy9('\x30' + chr(0b110001 + 0o76) + chr(0b110001) + chr(48) + chr(1675 - 1620), 0b1000), ehT0Px3KOsy9(chr(760 - 712) + chr(111) + chr(0b110011) + chr(188 - 137) + chr(49), 0o10), ehT0Px3KOsy9(chr(48) + chr(2846 - 2735) + chr(49) + '\065', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(0b110 + 0o60), 0b1000), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b1101111) + '\x33' + chr(0b110011) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(111) + chr(49) + chr(0b1011 + 0o45) + chr(51), 0b1000), ehT0Px3KOsy9('\060' + chr(8098 - 7987) + '\x33' + chr(0b100011 + 0o22) + '\x36', 0o10), ehT0Px3KOsy9('\060' + chr(0b1010011 + 0o34) + '\065' + chr(0b110110), 37651 - 37643), ehT0Px3KOsy9(chr(0b100110 + 0o12) + '\157' + '\062' + chr(53) + '\x37', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1010 + 0o145) + chr(2248 - 2197) + chr(53) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x33' + '\x34' + chr(0b101010 + 0o12), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b101011 + 0o7) + chr(1696 - 1641) + '\x36', 16471 - 16463), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b11110 + 0o24) + chr(0b11100 + 0o33) + '\066', 8), ehT0Px3KOsy9(chr(568 - 520) + chr(0b1101111) + chr(457 - 405) + chr(511 - 459), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10100 + 0o35) + chr(50) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\x6f' + chr(49) + '\x37' + chr(49), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(53) + '\063', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110001) + chr(0b1110 + 0o47) + chr(1324 - 1272), 0b1000), ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\157' + chr(857 - 807) + '\063' + chr(2295 - 2242), 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + '\x33' + chr(0b11100 + 0o24), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x32', 11587 - 11579), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110000 + 0o3) + chr(0b110001 + 0o4) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(48) + chr(5179 - 5068) + '\x32' + chr(2905 - 2851) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(111) + '\x32' + chr(54) + '\064', 0o10), ehT0Px3KOsy9(chr(1630 - 1582) + '\x6f' + chr(0b11110 + 0o25) + chr(0b11110 + 0o30) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101101 + 0o2) + chr(1966 - 1917) + '\060' + chr(675 - 622), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1011010 + 0o25) + '\x31' + chr(0b110110) + '\066', 40126 - 40118), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110010) + chr(1797 - 1746) + chr(0b100011 + 0o20), 0b1000), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(4390 - 4279) + chr(49) + '\062' + chr(1325 - 1272), 0o10), ehT0Px3KOsy9('\060' + chr(0b1111 + 0o140) + chr(365 - 314) + chr(0b110000) + '\x32', 21934 - 21926), ehT0Px3KOsy9(chr(0b110000) + chr(2034 - 1923) + '\061' + chr(1970 - 1918) + chr(0b10001 + 0o37), 17898 - 17890), ehT0Px3KOsy9(chr(48) + chr(0b1010011 + 0o34) + chr(1222 - 1173) + chr(0b11011 + 0o34) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1010 + 0o145) + chr(0b110001) + '\x35' + '\x33', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1241 - 1191) + chr(1221 - 1168) + '\x31', 17598 - 17590), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + chr(0b110001) + chr(55), 2354 - 2346), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(1534 - 1483) + chr(0b110100) + '\063', 44265 - 44257), ehT0Px3KOsy9(chr(48) + chr(4467 - 4356) + chr(1842 - 1791) + chr(0b110110) + chr(2377 - 2325), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b100 + 0o153) + chr(0b11110 + 0o24) + '\061' + '\x33', 41914 - 41906)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x35' + chr(0b101011 + 0o5), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xba'), chr(9083 - 8983) + chr(0b110001 + 0o64) + chr(0b1100011) + chr(0b1101111) + '\144' + '\x65')('\x75' + chr(0b1001011 + 0o51) + '\x66' + chr(0b101101) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Hr4HqTvG2HzO(_GoaLGZ5U6xS, H6fJ9QOZaJmh, Mq2X4hHIvLYE, SIkZeGCA53HL=ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b101101 + 0o4), 54256 - 54248)):
(VNGQdHSFPrso, VNGQdHSFPrso, VNGQdHSFPrso, X1ZpHSxyKbHn) = jSKPaHwSAfVv.shape_list(_GoaLGZ5U6xS)
OiQSFE0MLnas = IDJ2eXGCBCDu.reduce_sum((_GoaLGZ5U6xS - H6fJ9QOZaJmh) ** ehT0Px3KOsy9(chr(955 - 907) + chr(111) + '\x32', 8), axis=(ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b11001 + 0o30), 8), ehT0Px3KOsy9(chr(145 - 97) + chr(9291 - 9180) + '\062', 8)))
(VNGQdHSFPrso, yOlTRI3A1piB) = IDJ2eXGCBCDu.math.top_k(OiQSFE0MLnas, k=SIkZeGCA53HL)
X2brqcqt18pK = yOlTRI3A1piB[-ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11100 + 0o25), 8)]
hwzeWlciR85H = IDJ2eXGCBCDu.range(X1ZpHSxyKbHn, dtype=IDJ2eXGCBCDu.int32)
D2q_YosqiMF7 = IDJ2eXGCBCDu.equal(hwzeWlciR85H, X2brqcqt18pK)
mxhUxfENiwcN = IDJ2eXGCBCDu.ones(X1ZpHSxyKbHn, dtype=IDJ2eXGCBCDu.float32)
y5C5CgZRtfVA = IDJ2eXGCBCDu.zeros(X1ZpHSxyKbHn, dtype=IDJ2eXGCBCDu.float32)
hpt8yJLmdtZP = []
for reNPK3PqEOpR in Mq2X4hHIvLYE:
w_j09XzADGYr = IDJ2eXGCBCDu.dRFAC59yQBm_(D2q_YosqiMF7, reNPK3PqEOpR * mxhUxfENiwcN, y5C5CgZRtfVA)
tgH570glvJIv = _GoaLGZ5U6xS + w_j09XzADGYr * (H6fJ9QOZaJmh - _GoaLGZ5U6xS)
xafqLlk3kkUe(hpt8yJLmdtZP, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf5\xe87\xbccr'), chr(0b10100 + 0o120) + chr(4374 - 4273) + chr(2770 - 2671) + chr(0b1010001 + 0o36) + chr(0b10010 + 0o122) + chr(101))('\x75' + chr(0b1110100) + chr(2660 - 2558) + chr(0b101101) + '\070'))(tgH570glvJIv)
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf7\xf7)\xbalb'), chr(1535 - 1435) + '\145' + '\x63' + chr(0b1000000 + 0o57) + chr(100) + chr(101))('\165' + chr(10410 - 10294) + chr(0b1100110) + chr(45) + '\070'))(hpt8yJLmdtZP, axis=ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b1101111) + chr(0b10111 + 0o31), 8))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
postprocess
|
def postprocess(x, n_bits_x=8):
"""Converts x from [-0.5, 0.5], to [0, 255].
Args:
x: 3-D or 4-D Tensor normalized between [-0.5, 0.5]
n_bits_x: Number of bits representing each pixel of the output.
Defaults to 8, to default to 256 possible values.
Returns:
x: 3-D or 4-D Tensor representing images or videos.
"""
x = tf.where(tf.is_finite(x), x, tf.ones_like(x))
x = tf.clip_by_value(x, -0.5, 0.5)
x += 0.5
x = x * 2**n_bits_x
return tf.cast(tf.clip_by_value(x, 0, 255), dtype=tf.uint8)
|
python
|
def postprocess(x, n_bits_x=8):
"""Converts x from [-0.5, 0.5], to [0, 255].
Args:
x: 3-D or 4-D Tensor normalized between [-0.5, 0.5]
n_bits_x: Number of bits representing each pixel of the output.
Defaults to 8, to default to 256 possible values.
Returns:
x: 3-D or 4-D Tensor representing images or videos.
"""
x = tf.where(tf.is_finite(x), x, tf.ones_like(x))
x = tf.clip_by_value(x, -0.5, 0.5)
x += 0.5
x = x * 2**n_bits_x
return tf.cast(tf.clip_by_value(x, 0, 255), dtype=tf.uint8)
|
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Converts x from [-0.5, 0.5], to [0, 255].
Args:
x: 3-D or 4-D Tensor normalized between [-0.5, 0.5]
n_bits_x: Number of bits representing each pixel of the output.
Defaults to 8, to default to 256 possible values.
Returns:
x: 3-D or 4-D Tensor representing images or videos.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L85-L99
|
train
|
Converts x from 0. 5 0. 5 to 255.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + '\061' + chr(0b11000 + 0o30), 42978 - 42970), ehT0Px3KOsy9(chr(1211 - 1163) + chr(10591 - 10480) + chr(49) + chr(999 - 951) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(1969 - 1921) + chr(111) + chr(50) + chr(0b10001 + 0o43) + chr(0b10000 + 0o47), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + '\x31' + chr(2459 - 2405), 20985 - 20977), ehT0Px3KOsy9('\060' + chr(111) + '\x33' + chr(0b110100) + '\064', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(53) + chr(1396 - 1345), 0b1000), ehT0Px3KOsy9(chr(1290 - 1242) + chr(111) + chr(1350 - 1300) + '\x31' + chr(54), 8), ehT0Px3KOsy9('\060' + chr(2811 - 2700) + chr(1837 - 1787) + '\067' + chr(0b11010 + 0o30), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(1952 - 1902) + '\x32' + chr(50), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b1110 + 0o43) + chr(0b110110) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x37' + chr(0b101 + 0o55), 0b1000), ehT0Px3KOsy9(chr(0b111 + 0o51) + '\x6f' + chr(681 - 631) + chr(0b1011 + 0o50) + chr(1836 - 1786), 0b1000), ehT0Px3KOsy9(chr(1526 - 1478) + chr(0b1101111) + chr(531 - 481) + chr(1803 - 1754) + chr(0b101010 + 0o6), 15705 - 15697), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + '\x31' + '\062', 0b1000), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(111) + chr(0b100110 + 0o13) + chr(0b101 + 0o56) + chr(2219 - 2168), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(1485 - 1435) + chr(222 - 172) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(740 - 692) + '\x6f' + chr(0b10110 + 0o35) + chr(54), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + chr(0b11111 + 0o26) + chr(1402 - 1349), 16247 - 16239), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(111) + chr(0b1001 + 0o51) + chr(0b110100 + 0o0) + chr(0b101011 + 0o5), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + chr(0b101000 + 0o10) + chr(2458 - 2403), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b1101 + 0o45) + chr(2333 - 2279) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001) + chr(1809 - 1760) + chr(55), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010 + 0o1) + chr(2034 - 1984) + '\066', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010 + 0o4) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + '\x31' + chr(55), 0o10), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(2329 - 2218) + chr(450 - 400) + chr(0b110000) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(1819 - 1771) + chr(0b1011110 + 0o21) + chr(1708 - 1657) + chr(0b110001) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(1137 - 1089) + '\157' + chr(0b10011 + 0o40) + chr(1780 - 1732) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(1641 - 1593) + chr(10813 - 10702) + '\063' + chr(0b100010 + 0o20) + chr(0b101 + 0o60), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\x32' + chr(0b10001 + 0o42) + chr(1093 - 1039), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + '\x34' + '\x33', 40331 - 40323), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011 + 0o144) + '\062' + '\x33' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\157' + '\x32' + chr(2336 - 2285), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(51) + chr(0b110011) + chr(0b10111 + 0o34), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(167 - 119) + chr(111) + '\063' + chr(2248 - 2195) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + chr(48) + chr(53), 0o10), ehT0Px3KOsy9('\x30' + chr(4792 - 4681) + '\x33' + chr(2013 - 1959) + chr(1983 - 1932), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + chr(50) + chr(0b100011 + 0o15), 0o10), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(0b10101 + 0o132) + '\x32' + chr(0b101001 + 0o10) + chr(0b110011), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(3350 - 3239) + '\x35' + '\x30', 36442 - 36434)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'f'), chr(0b111110 + 0o46) + chr(0b10011 + 0o122) + chr(99) + '\x6f' + '\144' + '\x65')(chr(0b110101 + 0o100) + '\164' + '\x66' + chr(651 - 606) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def wwNuyCSLWczo(OeWW0F1dBPRQ, VyJxzgIHrPL2=ehT0Px3KOsy9(chr(0b110000) + chr(4623 - 4512) + chr(0b110001) + chr(48), 21063 - 21055)):
OeWW0F1dBPRQ = IDJ2eXGCBCDu.dRFAC59yQBm_(IDJ2eXGCBCDu.is_finite(OeWW0F1dBPRQ), OeWW0F1dBPRQ, IDJ2eXGCBCDu.ones_like(OeWW0F1dBPRQ))
OeWW0F1dBPRQ = IDJ2eXGCBCDu.clip_by_value(OeWW0F1dBPRQ, -0.5, 0.5)
OeWW0F1dBPRQ += 0.5
OeWW0F1dBPRQ = OeWW0F1dBPRQ * ehT0Px3KOsy9(chr(1534 - 1486) + chr(111) + chr(0b110010), ord("\x08")) ** VyJxzgIHrPL2
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'+ \xd4\xfa'), chr(100) + chr(7894 - 7793) + chr(99) + chr(0b1101111) + chr(5892 - 5792) + chr(0b1100101))(chr(7888 - 7771) + chr(116) + chr(102) + '\055' + chr(0b111000)))(xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'+-\xce\xfe\xbbI\xf7\xe5\xe4\x13V\xef\xed'), chr(0b1100100) + chr(4699 - 4598) + chr(99) + chr(3260 - 3149) + chr(0b1000011 + 0o41) + '\x65')(chr(117) + '\164' + '\x66' + '\x2d' + chr(56)))(OeWW0F1dBPRQ, ehT0Px3KOsy9('\x30' + '\157' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b100011 + 0o114) + chr(0b1110 + 0o45) + chr(1038 - 983) + chr(0b110111), 34733 - 34725)), dtype=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'=(\xc9\xfa\xdc'), '\144' + chr(101) + chr(99) + '\x6f' + chr(0b1010111 + 0o15) + chr(0b1100101))('\x75' + chr(0b1011010 + 0o32) + '\x66' + chr(132 - 87) + chr(0b10011 + 0o45))))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
get_cond_latents_at_level
|
def get_cond_latents_at_level(cond_latents, level, hparams):
"""Returns a single or list of conditional latents at level 'level'."""
if cond_latents:
if hparams.latent_dist_encoder in ["conv_net", "conv3d_net"]:
return [cond_latent[level] for cond_latent in cond_latents]
elif hparams.latent_dist_encoder in ["pointwise", "conv_lstm"]:
return cond_latents[level]
|
python
|
def get_cond_latents_at_level(cond_latents, level, hparams):
"""Returns a single or list of conditional latents at level 'level'."""
if cond_latents:
if hparams.latent_dist_encoder in ["conv_net", "conv3d_net"]:
return [cond_latent[level] for cond_latent in cond_latents]
elif hparams.latent_dist_encoder in ["pointwise", "conv_lstm"]:
return cond_latents[level]
|
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Returns a single or list of conditional latents at level 'level'.
|
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272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L141-L147
|
train
|
Returns a single or list of conditional latents at level level.
|
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(0b110001 + 0o76) + chr(0b1100 + 0o45) + chr(49) + chr(50), 60286 - 60278), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(0b1001000 + 0o47) + chr(2729 - 2674) + chr(0b100111 + 0o14), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11010 + 0o27) + '\067' + chr(49), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(975 - 864) + '\061' + '\x34' + chr(50), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(51) + chr(0b101110 + 0o4) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(2157 - 2109) + chr(111) + '\061' + chr(0b1010 + 0o54) + chr(0b11001 + 0o30), 29366 - 29358), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\062' + chr(48) + chr(0b110001), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(50) + '\x30' + chr(0b11100 + 0o33), 46929 - 46921), ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\157' + '\061' + chr(0b110 + 0o57) + chr(941 - 892), ord("\x08")), ehT0Px3KOsy9(chr(726 - 678) + chr(111) + chr(0b1110 + 0o44) + chr(0b110000) + chr(54), 27338 - 27330), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b11110 + 0o121) + chr(0b1111 + 0o44) + chr(154 - 101) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(111) + '\062' + chr(0b110100) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(448 - 400) + '\x6f' + chr(0b110011) + chr(0b110110) + '\x35', 0o10), ehT0Px3KOsy9(chr(471 - 423) + chr(0b1010011 + 0o34) + chr(0b110010 + 0o4), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1265 - 1215) + '\x34' + chr(0b110 + 0o61), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100110 + 0o13) + chr(54), 0b1000), ehT0Px3KOsy9(chr(2275 - 2227) + chr(0b1100011 + 0o14) + chr(2038 - 1989) + chr(2577 - 2522) + '\061', 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11000 + 0o36), 8), ehT0Px3KOsy9('\060' + chr(111) + '\x37' + chr(0b110011), 8), ehT0Px3KOsy9('\x30' + '\157' + '\x31' + '\x35', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + chr(0b0 + 0o64) + '\065', 8), ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\x6f' + chr(2469 - 2419) + chr(50) + '\065', 0o10), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\x6f' + chr(0b100110 + 0o13) + chr(0b1011 + 0o47) + chr(0b110 + 0o60), 0o10), ehT0Px3KOsy9(chr(1214 - 1166) + chr(0b1101111) + chr(0b110001) + '\062' + chr(0b110001), 51085 - 51077), ehT0Px3KOsy9(chr(1974 - 1926) + chr(0b1101111) + chr(51) + chr(0b101010 + 0o12) + chr(139 - 90), ord("\x08")), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(9231 - 9120) + chr(0b110010) + chr(0b11011 + 0o32) + chr(0b100100 + 0o23), 0o10), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\x6f' + chr(2223 - 2168) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b111110 + 0o61) + chr(0b110011) + chr(0b110100) + '\066', 0o10), ehT0Px3KOsy9(chr(0b10000 + 0o40) + '\x6f' + chr(0b110001) + chr(55) + chr(0b111 + 0o55), 0b1000), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(111) + chr(1612 - 1563) + chr(0b110011) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b101000 + 0o107) + chr(0b110011) + chr(53) + chr(187 - 138), 39692 - 39684), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1153 - 1103) + '\x35' + chr(0b100001 + 0o17), 0o10), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(6492 - 6381) + '\067' + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + chr(10275 - 10164) + '\x31' + chr(0b1101 + 0o47) + chr(0b1010 + 0o55), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + '\061' + '\065', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110011) + '\x31' + chr(0b110000 + 0o6), 6908 - 6900), ehT0Px3KOsy9('\x30' + chr(9683 - 9572) + chr(49) + '\063' + chr(638 - 587), 0b1000), ehT0Px3KOsy9(chr(48) + chr(2363 - 2252) + chr(48), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1010110 + 0o31) + chr(50) + '\x30' + chr(59 - 9), 0b1000), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(0b10000 + 0o137) + chr(0b110011) + chr(48) + chr(50), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\x6f' + '\x35' + chr(48), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'd'), chr(100) + chr(1523 - 1422) + chr(7088 - 6989) + '\157' + chr(9529 - 9429) + chr(0b1100101))('\x75' + chr(0b1110100) + chr(102) + chr(45) + chr(0b10 + 0o66)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def zZWeegG44oB_(EJNyt2wVt1N7, K3VjCQe_lvJZ, n4ljua2gi1Pr):
if EJNyt2wVt1N7:
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'&Z\r\x07\xb8\x05\xde\xe3\x00\xf5\x9e\xfa\x90h\xc4a\x1dcI'), chr(100) + chr(0b111011 + 0o52) + chr(99) + '\157' + chr(0b1100100) + '\145')(chr(0b1000101 + 0o60) + chr(0b1110100) + '\146' + chr(231 - 186) + chr(56))) in [xafqLlk3kkUe(SXOLrMavuUCe(b')T\x17\x14\x89\x1f\xe4\xf3'), chr(100) + '\x65' + '\x63' + '\x6f' + chr(100) + chr(0b1011001 + 0o14))(chr(0b101100 + 0o111) + chr(116) + chr(102) + '\x2d' + chr(1983 - 1927)), xafqLlk3kkUe(SXOLrMavuUCe(b')T\x17\x14\xe5\x15\xde\xe9\x0c\xf2'), '\144' + '\x65' + '\143' + '\x6f' + chr(0b1000100 + 0o40) + chr(101))('\165' + chr(1788 - 1672) + chr(0b1100110) + chr(0b11001 + 0o24) + '\070')]:
return [ylK7t6C1JoJn[K3VjCQe_lvJZ] for ylK7t6C1JoJn in EJNyt2wVt1N7]
elif xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'&Z\r\x07\xb8\x05\xde\xe3\x00\xf5\x9e\xfa\x90h\xc4a\x1dcI'), '\144' + chr(160 - 59) + chr(99) + chr(0b100011 + 0o114) + chr(0b1100100) + chr(0b1001111 + 0o26))('\165' + chr(11597 - 11481) + chr(102) + chr(0b101101) + '\070')) in [xafqLlk3kkUe(SXOLrMavuUCe(b':T\x10\x0c\xa2\x06\xe8\xf4\x0c'), '\x64' + chr(0b11 + 0o142) + chr(0b110001 + 0o62) + chr(111) + '\144' + chr(0b1100011 + 0o2))(chr(2287 - 2170) + '\x74' + '\146' + chr(0b101100 + 0o1) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b')T\x17\x14\x89\x1d\xf2\xf3\x04'), chr(0b1100100) + chr(0b11101 + 0o110) + '\143' + '\157' + '\x64' + '\x65')(chr(6853 - 6736) + '\x74' + chr(0b1100110) + chr(0b101101) + chr(0b111000))]:
return EJNyt2wVt1N7[K3VjCQe_lvJZ]
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
check_cond_latents
|
def check_cond_latents(cond_latents, hparams):
"""Shape checking for cond_latents."""
if cond_latents is None:
return
if not isinstance(cond_latents[0], list):
cond_latents = [cond_latents]
exp_num_latents = hparams.num_cond_latents
if hparams.latent_dist_encoder == "conv_net":
exp_num_latents += int(hparams.cond_first_frame)
if len(cond_latents) != exp_num_latents:
raise ValueError("Expected number of cond_latents: %d, got %d" %
(exp_num_latents, len(cond_latents)))
for cond_latent in cond_latents:
if len(cond_latent) != hparams.n_levels - 1:
raise ValueError("Expected level_latents to be %d, got %d" %
(hparams.n_levels - 1, len(cond_latent)))
|
python
|
def check_cond_latents(cond_latents, hparams):
"""Shape checking for cond_latents."""
if cond_latents is None:
return
if not isinstance(cond_latents[0], list):
cond_latents = [cond_latents]
exp_num_latents = hparams.num_cond_latents
if hparams.latent_dist_encoder == "conv_net":
exp_num_latents += int(hparams.cond_first_frame)
if len(cond_latents) != exp_num_latents:
raise ValueError("Expected number of cond_latents: %d, got %d" %
(exp_num_latents, len(cond_latents)))
for cond_latent in cond_latents:
if len(cond_latent) != hparams.n_levels - 1:
raise ValueError("Expected level_latents to be %d, got %d" %
(hparams.n_levels - 1, len(cond_latent)))
|
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] |
Shape checking for cond_latents.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L150-L165
|
train
|
Shape checking for cond_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' + chr(111) + chr(0b110001) + chr(0b100010 + 0o21) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(9093 - 8982) + chr(49) + chr(0b1001 + 0o54) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + chr(50), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b101101 + 0o102) + '\061' + chr(0b110010) + chr(0b110001), 51219 - 51211), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(52) + chr(0b100110 + 0o13), ord("\x08")), ehT0Px3KOsy9(chr(1756 - 1708) + chr(0b1101111) + chr(0b100110 + 0o17) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + '\x32' + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b1101111) + chr(49) + chr(1817 - 1765) + chr(973 - 922), 0b1000), ehT0Px3KOsy9(chr(357 - 309) + '\x6f' + chr(1561 - 1507) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011111 + 0o20) + chr(49) + '\060' + chr(0b110101 + 0o2), 42843 - 42835), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1011101 + 0o22) + chr(49) + chr(0b1 + 0o64) + '\x36', 39941 - 39933), ehT0Px3KOsy9(chr(1565 - 1517) + '\157' + chr(325 - 275) + '\061' + chr(48), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b111110 + 0o61) + '\061' + chr(0b10110 + 0o33) + chr(0b110010), 50366 - 50358), ehT0Px3KOsy9(chr(1395 - 1347) + '\x6f' + chr(0b110011) + chr(0b100010 + 0o25) + '\x35', 2639 - 2631), ehT0Px3KOsy9(chr(1921 - 1873) + chr(111) + chr(49) + '\060' + chr(0b101100 + 0o5), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\x6f' + chr(51) + chr(53) + chr(58 - 10), 0o10), ehT0Px3KOsy9(chr(75 - 27) + '\x6f' + '\065' + chr(1331 - 1276), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + '\061', 61538 - 61530), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50) + '\067' + '\063', 0b1000), ehT0Px3KOsy9(chr(267 - 219) + chr(111) + chr(0b110010) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(577 - 529) + chr(111) + '\x35' + chr(2155 - 2100), 8), ehT0Px3KOsy9('\060' + chr(111) + '\061' + chr(53) + chr(53), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b101110 + 0o101) + '\x31' + chr(2142 - 2093) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(775 - 727) + chr(0b1010100 + 0o33) + chr(0b110001) + '\x37' + chr(54), 53478 - 53470), ehT0Px3KOsy9('\x30' + chr(9330 - 9219) + chr(0b101010 + 0o10) + chr(52), 37421 - 37413), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(51) + chr(0b101011 + 0o12), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(2149 - 2100) + chr(0b110010) + chr(53), 4896 - 4888), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + '\064' + '\x30', 49876 - 49868), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + chr(0b110100) + chr(51), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1302 - 1251) + '\x30' + chr(1153 - 1100), 0b1000), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(122 - 11) + '\x37' + chr(1604 - 1553), 0b1000), ehT0Px3KOsy9(chr(1825 - 1777) + chr(0b1001000 + 0o47) + '\062' + chr(1888 - 1839) + chr(0b110 + 0o55), 0o10), ehT0Px3KOsy9('\060' + chr(9685 - 9574) + '\x33' + chr(0b10110 + 0o36) + chr(0b101010 + 0o13), 31301 - 31293), ehT0Px3KOsy9('\060' + chr(111) + '\063' + '\x34' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + '\061' + chr(0b1001 + 0o47), 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2389 - 2338) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110101) + chr(0b100111 + 0o11), 0b1000), ehT0Px3KOsy9(chr(48) + chr(558 - 447) + chr(50) + chr(0b110000) + chr(484 - 429), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063' + '\x30' + chr(0b10010 + 0o41), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b1000 + 0o50) + '\157' + chr(0b100101 + 0o20) + chr(0b110000), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'w'), chr(0b101111 + 0o65) + '\145' + chr(99) + chr(0b100 + 0o153) + chr(0b11 + 0o141) + '\x65')(chr(11994 - 11877) + chr(0b1001111 + 0o45) + chr(102) + '\x2d' + chr(502 - 446)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def VAs_1jgFBuYm(EJNyt2wVt1N7, n4ljua2gi1Pr):
if EJNyt2wVt1N7 is None:
return
if not PlSM16l2KDPD(EJNyt2wVt1N7[ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110000), 0b1000)], YyaZ4tpXu4lf):
EJNyt2wVt1N7 = [EJNyt2wVt1N7]
vcIh4XSKzob1 = n4ljua2gi1Pr.num_cond_latents
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'5\t~4OY\xcc\x07^4\x1a\xd7/\x93"m\x8cJk'), chr(0b1100 + 0o130) + chr(101) + '\x63' + chr(0b1100000 + 0o17) + chr(0b1100100) + '\x65')('\x75' + '\x74' + chr(0b1100110) + chr(1791 - 1746) + chr(578 - 522))) == xafqLlk3kkUe(SXOLrMavuUCe(b":\x07d'~C\xf6\x17"), '\x64' + chr(0b1100101) + chr(0b111 + 0o134) + '\x6f' + chr(0b1100100) + chr(0b1100101))('\x75' + chr(3856 - 3740) + '\x66' + chr(1389 - 1344) + '\x38'):
vcIh4XSKzob1 += ehT0Px3KOsy9(n4ljua2gi1Pr.cond_first_frame)
if c2A0yzQpDQB3(EJNyt2wVt1N7) != vcIh4XSKzob1:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\x1c\x10z4BY\xf6\x07\x17)\x1b\xe5(\x983"\x87I9\xd8\x7fA\t\x11\x12u\xe90\x0e\x17\xb6\x01\xab\xc0\x82\xa48O\xe8\xb7yMn'), chr(0b1100100) + '\x65' + '\143' + '\157' + '\x64' + chr(0b10010 + 0o123))('\165' + chr(0b1110100) + '\x66' + chr(0b101101) + '\070') % (vcIh4XSKzob1, c2A0yzQpDQB3(EJNyt2wVt1N7)))
for ylK7t6C1JoJn in EJNyt2wVt1N7:
if c2A0yzQpDQB3(ylK7t6C1JoJn) != xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'77f4WH\xff\x10'), chr(0b11111 + 0o105) + chr(0b1001110 + 0o27) + '\143' + chr(0b10011 + 0o134) + '\x64' + chr(0b1100101))(chr(0b1010001 + 0o44) + chr(116) + chr(102) + chr(45) + chr(971 - 915))) - ehT0Px3KOsy9(chr(0b1 + 0o57) + '\157' + chr(0b1100 + 0o45), 49725 - 49717):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\x1c\x10z4BY\xf6\x07\x17+\x0b\xfe/\x91\x1en\x89[|\xd5d\\M:\x114\xff0@F\xa1\x17\xab\x82\x89\xfc8\r\xe3'), '\144' + chr(0b1100101) + '\x63' + chr(0b100100 + 0o113) + chr(0b1100100) + chr(3173 - 3072))('\x75' + chr(0b1110100) + chr(102) + chr(0b101101) + chr(549 - 493)) % (xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'77f4WH\xff\x10'), chr(9345 - 9245) + chr(0b1100101) + chr(0b1100011) + chr(0b1101111) + chr(0b1100100) + chr(4478 - 4377))(chr(117) + chr(116) + '\146' + '\055' + '\x38')) - ehT0Px3KOsy9('\x30' + '\x6f' + chr(49), 8), c2A0yzQpDQB3(ylK7t6C1JoJn)))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
get_variable_ddi
|
def get_variable_ddi(name, shape, initial_value, dtype=tf.float32, init=False,
trainable=True):
"""Wrapper for data-dependent initialization."""
# If init is a tf bool: w is assigned dynamically at runtime.
# If init is a python bool: then w is determined during graph construction.
w = tf.get_variable(name, shape, dtype, None, trainable=trainable)
if isinstance(init, bool):
if init:
return assign(w, initial_value)
return w
else:
return tf.cond(init, lambda: assign(w, initial_value), lambda: w)
|
python
|
def get_variable_ddi(name, shape, initial_value, dtype=tf.float32, init=False,
trainable=True):
"""Wrapper for data-dependent initialization."""
# If init is a tf bool: w is assigned dynamically at runtime.
# If init is a python bool: then w is determined during graph construction.
w = tf.get_variable(name, shape, dtype, None, trainable=trainable)
if isinstance(init, bool):
if init:
return assign(w, initial_value)
return w
else:
return tf.cond(init, lambda: assign(w, initial_value), lambda: w)
|
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Wrapper for data-dependent initialization.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L169-L180
|
train
|
Wrapper for data - dependent initialization.
|
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(0b11110 + 0o22) + '\157' + chr(0b10010 + 0o40) + chr(0b110101) + chr(0b1011 + 0o51), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(629 - 579) + '\x35' + '\x37', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\063' + chr(0b110000) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b10110 + 0o32) + '\157' + '\063' + chr(1276 - 1227), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + '\x33' + '\060', 21818 - 21810), ehT0Px3KOsy9('\060' + chr(0b1001110 + 0o41) + '\063' + '\x35' + '\x34', 51089 - 51081), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1011110 + 0o21) + chr(51) + chr(0b110011) + chr(1742 - 1687), 0b1000), ehT0Px3KOsy9(chr(389 - 341) + '\x6f' + chr(0b110010) + chr(0b110101) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(1788 - 1740) + '\x6f' + '\061' + '\x30' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(124 - 76) + chr(10779 - 10668) + chr(0b110001) + '\x31' + chr(1191 - 1137), 0o10), ehT0Px3KOsy9('\060' + chr(0b11011 + 0o124) + '\063' + chr(1444 - 1394), ord("\x08")), ehT0Px3KOsy9('\060' + chr(10228 - 10117) + chr(1656 - 1605) + chr(0b110111) + chr(55), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(54) + chr(0b101 + 0o55), 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(111) + chr(0b10010 + 0o41) + '\x34' + chr(1619 - 1566), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(51) + chr(0b110011) + chr(0b110001), 36390 - 36382), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000011 + 0o54) + chr(0b110001) + '\x30' + chr(54), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(0b110110), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x36', 0o10), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b1101111) + chr(941 - 890) + chr(0b100111 + 0o12) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + '\x37' + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(971 - 923) + '\157' + '\x31' + chr(0b110100) + chr(50 - 2), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(49) + '\x30' + chr(0b110000 + 0o3), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062' + chr(49) + '\066', 52922 - 52914), ehT0Px3KOsy9(chr(1146 - 1098) + '\157' + chr(1289 - 1239) + '\062' + '\x35', 62429 - 62421), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + chr(0b10101 + 0o33) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + chr(53), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(2188 - 2138) + '\x35' + chr(0b110001), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + chr(0b100111 + 0o14) + chr(971 - 916), 8), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b1 + 0o62) + chr(0b1000 + 0o55) + '\x35', 0o10), ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\x6f' + chr(1722 - 1669), 34120 - 34112), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + chr(52) + '\x37', 551 - 543), ehT0Px3KOsy9(chr(449 - 401) + chr(6879 - 6768) + chr(0b100111 + 0o12) + '\x33' + chr(368 - 314), 0o10), ehT0Px3KOsy9(chr(48) + chr(997 - 886) + chr(0b101111 + 0o7) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(951 - 903) + '\157' + '\x31' + chr(0b1010 + 0o55) + '\063', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1882 - 1833) + chr(2013 - 1960) + chr(0b110110), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + '\x37' + chr(0b101100 + 0o12), 0o10), ehT0Px3KOsy9(chr(2265 - 2217) + chr(0b1010000 + 0o37) + '\061' + '\x35' + '\x35', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + chr(1253 - 1205) + '\063', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(54) + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b0 + 0o157) + chr(80 - 25) + chr(1633 - 1581), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(0b1101111) + '\x35' + '\060', 20515 - 20507)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x82'), '\144' + '\145' + chr(99) + chr(6778 - 6667) + chr(100) + chr(0b1100101))('\x75' + '\164' + chr(5223 - 5121) + '\055' + chr(1504 - 1448)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def hYTzLkEA06YI(AIvJRzLdDfgF, nauYfLglTpcb, rgrqUMxfRll6, jSV9IKnemH7K=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xca\xc3\xaex,\xdf\xed'), chr(0b1000110 + 0o36) + chr(0b10111 + 0o116) + chr(99) + chr(0b1100001 + 0o16) + '\x64' + chr(101))(chr(3298 - 3181) + chr(0b110101 + 0o77) + chr(102) + '\055' + chr(892 - 836))), A5GIpkDsgP4U=ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(1960 - 1849) + chr(0b1111 + 0o41), 62132 - 62124), blO62vIs9J6u=ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31', 3650 - 3642)):
AOfzRywRzEXp = IDJ2eXGCBCDu.get_variable(AIvJRzLdDfgF, nauYfLglTpcb, jSV9IKnemH7K, None, trainable=blO62vIs9J6u)
if PlSM16l2KDPD(A5GIpkDsgP4U, WbBjf8Y7v9VN):
if A5GIpkDsgP4U:
return XH9bAgNQ2txV(AOfzRywRzEXp, rgrqUMxfRll6)
return AOfzRywRzEXp
else:
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xcf\xc0\xaf}'), chr(100) + '\145' + chr(9576 - 9477) + chr(0b1101111) + '\144' + '\x65')(chr(0b1110101) + chr(0b110001 + 0o103) + chr(0b1100110) + '\055' + chr(2357 - 2301)))(A5GIpkDsgP4U, lambda : XH9bAgNQ2txV(AOfzRywRzEXp, rgrqUMxfRll6), lambda : AOfzRywRzEXp)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
get_dropout
|
def get_dropout(x, rate=0.0, init=True):
"""Dropout x with dropout_rate = rate.
Apply zero dropout during init or prediction time.
Args:
x: 4-D Tensor, shape=(NHWC).
rate: Dropout rate.
init: Initialization.
Returns:
x: activations after dropout.
"""
if init or rate == 0:
return x
return tf.layers.dropout(x, rate=rate, training=True)
|
python
|
def get_dropout(x, rate=0.0, init=True):
"""Dropout x with dropout_rate = rate.
Apply zero dropout during init or prediction time.
Args:
x: 4-D Tensor, shape=(NHWC).
rate: Dropout rate.
init: Initialization.
Returns:
x: activations after dropout.
"""
if init or rate == 0:
return x
return tf.layers.dropout(x, rate=rate, training=True)
|
[
"def",
"get_dropout",
"(",
"x",
",",
"rate",
"=",
"0.0",
",",
"init",
"=",
"True",
")",
":",
"if",
"init",
"or",
"rate",
"==",
"0",
":",
"return",
"x",
"return",
"tf",
".",
"layers",
".",
"dropout",
"(",
"x",
",",
"rate",
"=",
"rate",
",",
"training",
"=",
"True",
")"
] |
Dropout x with dropout_rate = rate.
Apply zero dropout during init or prediction time.
Args:
x: 4-D Tensor, shape=(NHWC).
rate: Dropout rate.
init: Initialization.
Returns:
x: activations after dropout.
|
[
"Dropout",
"x",
"with",
"dropout_rate",
"=",
"rate",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L184-L198
|
train
|
Dropout x with dropout_rate = rate.
|
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) + '\x32' + chr(0b110100) + chr(0b110111), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(0b110000) + '\x31', 9336 - 9328), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + chr(0b110111) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + '\x33' + chr(132 - 82), 54604 - 54596), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x35', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(599 - 488) + '\x32' + chr(0b101100 + 0o5) + chr(599 - 549), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + '\065', 60050 - 60042), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(432 - 379) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(1657 - 1609) + chr(11790 - 11679) + chr(0b110010) + chr(53) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b0 + 0o60) + '\x6f' + chr(0b110010) + '\x37' + chr(0b10011 + 0o44), 41634 - 41626), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + chr(1205 - 1154) + chr(0b110000), 37451 - 37443), ehT0Px3KOsy9(chr(2297 - 2249) + chr(0b11000 + 0o127) + chr(1260 - 1210) + '\062' + chr(0b1111 + 0o47), 31495 - 31487), ehT0Px3KOsy9(chr(1073 - 1025) + chr(0b1101111) + chr(0b11010 + 0o31) + chr(48) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(6522 - 6411) + '\063' + chr(0b110001) + chr(52), 33372 - 33364), ehT0Px3KOsy9('\060' + chr(0b1010 + 0o145) + chr(200 - 150) + chr(53) + chr(0b110001), 18320 - 18312), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110010) + chr(2060 - 2011) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(54 - 5) + chr(52) + '\060', 0o10), ehT0Px3KOsy9(chr(683 - 635) + '\x6f' + chr(0b110001) + chr(0b110010) + chr(48), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\065' + chr(48), 0o10), ehT0Px3KOsy9(chr(192 - 144) + '\157' + '\x33' + '\065' + chr(1103 - 1054), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(923 - 873) + chr(0b110010) + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061' + '\062' + '\061', 0b1000), ehT0Px3KOsy9(chr(1485 - 1437) + '\x6f' + chr(0b110010 + 0o0) + chr(0b10011 + 0o41) + chr(1507 - 1459), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(2139 - 2088), 0o10), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(111) + '\x32' + '\x37' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\x6f' + '\063' + '\x34' + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + chr(730 - 678), 58405 - 58397), ehT0Px3KOsy9('\060' + '\x6f' + '\061' + '\063' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b0 + 0o62) + chr(0b101011 + 0o13) + chr(1508 - 1460), 0o10), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(111) + '\061' + '\066' + chr(48), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(2455 - 2405) + chr(0b100101 + 0o17) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(10376 - 10265) + '\x32' + chr(50) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(0b110011) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(2451 - 2340) + chr(166 - 117) + chr(51) + chr(0b11000 + 0o37), 8), ehT0Px3KOsy9('\x30' + chr(1383 - 1272) + chr(49) + chr(2600 - 2546) + chr(0b1011 + 0o52), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x31' + chr(2456 - 2402) + '\062', 0b1000), ehT0Px3KOsy9(chr(1487 - 1439) + chr(111) + '\x32' + chr(55) + chr(1836 - 1786), 12574 - 12566), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b1 + 0o60) + chr(0b110000) + chr(0b100010 + 0o17), 0o10), ehT0Px3KOsy9(chr(644 - 596) + '\157' + chr(1620 - 1570) + chr(0b110000) + chr(2650 - 2595), 0b1000), ehT0Px3KOsy9(chr(48) + chr(3688 - 3577) + chr(419 - 370) + chr(0b100110 + 0o12) + '\067', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(6504 - 6393) + chr(0b10101 + 0o40) + chr(0b110000), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x89'), chr(0b100010 + 0o102) + chr(0b1100101) + '\x63' + chr(0b111101 + 0o62) + chr(6293 - 6193) + chr(101))('\165' + chr(0b11110 + 0o126) + chr(102) + '\x2d' + chr(0b100010 + 0o26)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def hyYiFcSqOLyL(OeWW0F1dBPRQ, YygZh57sDDVX=0.0, A5GIpkDsgP4U=ehT0Px3KOsy9(chr(0b100101 + 0o13) + '\157' + chr(2074 - 2025), 32839 - 32831)):
if A5GIpkDsgP4U or YygZh57sDDVX == ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\157' + chr(48), 55759 - 55751):
return OeWW0F1dBPRQ
return xafqLlk3kkUe(IDJ2eXGCBCDu.layers, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc6\xe6N7r\xcfj}\xd2\xd5\xc1\xe0'), '\x64' + chr(0b1100101) + '\x63' + chr(0b1101111) + chr(100) + chr(0b1100101))(chr(117) + chr(4233 - 4117) + chr(102) + '\055' + chr(0b1010 + 0o56)))(OeWW0F1dBPRQ, rate=YygZh57sDDVX, training=ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111 + 0o0) + '\061', 8))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
actnorm_3d
|
def actnorm_3d(name, x, logscale_factor=3.):
"""Applies actnorm to each time-step independently.
There are a total of 2*n_channels*n_steps parameters learnt.
Args:
name: variable scope.
x: 5-D Tensor, (NTHWC)
logscale_factor: Increases the learning rate of the scale by
logscale_factor.
Returns:
x: 5-D Tensor, (NTHWC) with the per-timestep, per-channel normalization.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
x = tf.unstack(x, axis=1)
x_normed = []
for ind, x_step in enumerate(x):
x_step, _ = actnorm("actnorm_%d" % ind, x_step,
logscale_factor=logscale_factor)
x_normed.append(x_step)
return tf.stack(x_normed, axis=1), None
|
python
|
def actnorm_3d(name, x, logscale_factor=3.):
"""Applies actnorm to each time-step independently.
There are a total of 2*n_channels*n_steps parameters learnt.
Args:
name: variable scope.
x: 5-D Tensor, (NTHWC)
logscale_factor: Increases the learning rate of the scale by
logscale_factor.
Returns:
x: 5-D Tensor, (NTHWC) with the per-timestep, per-channel normalization.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
x = tf.unstack(x, axis=1)
x_normed = []
for ind, x_step in enumerate(x):
x_step, _ = actnorm("actnorm_%d" % ind, x_step,
logscale_factor=logscale_factor)
x_normed.append(x_step)
return tf.stack(x_normed, axis=1), None
|
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] |
Applies actnorm to each time-step independently.
There are a total of 2*n_channels*n_steps parameters learnt.
Args:
name: variable scope.
x: 5-D Tensor, (NTHWC)
logscale_factor: Increases the learning rate of the scale by
logscale_factor.
Returns:
x: 5-D Tensor, (NTHWC) with the per-timestep, per-channel normalization.
|
[
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"-",
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"independently",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L202-L222
|
train
|
Applies actnorm to each time - step independently.
|
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(12212 - 12101) + chr(0b101011 + 0o10) + '\x33' + '\065', 0b1000), ehT0Px3KOsy9(chr(497 - 449) + '\x6f' + '\x32' + chr(263 - 213), 41838 - 41830), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110100) + chr(52), 0o10), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(10355 - 10244) + '\061' + chr(53) + '\063', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(1359 - 1310), ord("\x08")), ehT0Px3KOsy9(chr(242 - 194) + '\157' + '\063' + chr(49) + chr(0b110000), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + '\x31' + chr(48), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + chr(1973 - 1922) + chr(0b101110 + 0o4), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50) + chr(1001 - 953) + chr(0b110000), 18356 - 18348), ehT0Px3KOsy9('\x30' + chr(0b1001001 + 0o46) + '\061' + chr(0b100001 + 0o17) + chr(0b101111 + 0o10), 0b1000), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1100100 + 0o13) + chr(49) + '\063', 0o10), ehT0Px3KOsy9(chr(48) + chr(5672 - 5561) + chr(49) + '\x35', 16393 - 16385), ehT0Px3KOsy9('\x30' + chr(6024 - 5913) + '\x34' + chr(435 - 382), ord("\x08")), ehT0Px3KOsy9(chr(752 - 704) + chr(0b1101111) + chr(0b110001) + chr(924 - 872) + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b11111 + 0o120) + '\062' + chr(0b110010) + chr(0b110001), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001) + chr(48) + chr(0b110101), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + '\x36', ord("\x08")), ehT0Px3KOsy9('\060' + chr(5060 - 4949) + '\062' + chr(0b110101) + chr(0b101100 + 0o4), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + '\x35' + chr(0b110000 + 0o5), 10456 - 10448), ehT0Px3KOsy9(chr(198 - 150) + '\x6f' + chr(0b110001) + chr(53) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(49), 29764 - 29756), ehT0Px3KOsy9(chr(0b1 + 0o57) + '\x6f' + chr(50) + '\060' + '\x30', 8), ehT0Px3KOsy9(chr(1222 - 1174) + '\157' + chr(51) + chr(0b11010 + 0o30) + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11111 + 0o22) + chr(0b110101), 8), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + '\x30' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b11100 + 0o27) + chr(55) + chr(0b10101 + 0o34), 0b1000), ehT0Px3KOsy9(chr(153 - 105) + chr(0b1001 + 0o146) + '\x31' + chr(477 - 423) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(394 - 346) + chr(0b1101111) + chr(0b110111) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\x6f' + '\x32' + chr(116 - 63) + chr(51), 0o10), ehT0Px3KOsy9(chr(1968 - 1920) + '\x6f' + chr(0b110011) + chr(2181 - 2128) + '\x36', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b11101 + 0o26) + chr(1429 - 1380) + chr(52), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + '\x31' + chr(55), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110 + 0o54) + chr(0b100010 + 0o16) + '\x37', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + chr(0b110000) + chr(1576 - 1526), 0b1000), ehT0Px3KOsy9(chr(94 - 46) + chr(9921 - 9810) + '\x33' + chr(0b110111) + chr(788 - 734), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110111) + chr(1330 - 1277), 8), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + chr(0b1101 + 0o52) + '\x33', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b100011 + 0o20) + '\x33' + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(315 - 267) + chr(111) + '\x32' + chr(0b110110) + chr(55), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(8879 - 8768) + chr(0b110010) + chr(48) + '\064', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(111) + chr(0b110101) + chr(0b11001 + 0o27), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf3'), '\144' + chr(7718 - 7617) + chr(7291 - 7192) + chr(11157 - 11046) + '\144' + '\x65')(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + '\x2d' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def fp02jnf93ZnE(AIvJRzLdDfgF, OeWW0F1dBPRQ, pTH4H_nQFAXy=3.0):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xabsV\x02p\xaa\xa4\xff\xdf4hbU\x06'), chr(100) + chr(0b1100101) + '\x63' + '\x6f' + chr(0b1100100) + chr(101))('\x75' + chr(116) + chr(0b1000001 + 0o45) + chr(0b101101) + chr(0b101001 + 0o17)))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9cGp$N\x9a\x8d\xcf\xd3\x02'), chr(0b1100100) + chr(101) + chr(0b1001111 + 0o24) + chr(3259 - 3148) + chr(3056 - 2956) + chr(0b1100101))('\x75' + chr(0b1110100) + chr(0b1000011 + 0o43) + chr(0b101101) + chr(56)))):
OeWW0F1dBPRQ = IDJ2eXGCBCDu.unstack(OeWW0F1dBPRQ, axis=ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061', ord("\x08")))
fzNt0GNDlk4j = []
for (r3s_x88rHjuC, HP33FfGoFL47) in YlkZvXL8qwsX(OeWW0F1dBPRQ):
(HP33FfGoFL47, VNGQdHSFPrso) = QuPLNjEzN1in(xafqLlk3kkUe(SXOLrMavuUCe(b'\xbcqP\x05~\xba\xa5\xc5\xa5#'), '\144' + chr(0b110101 + 0o60) + chr(0b1100011) + chr(10636 - 10525) + chr(100) + '\x65')(chr(9709 - 9592) + chr(0b1110100) + chr(4242 - 4140) + chr(1743 - 1698) + '\070') % r3s_x88rHjuC, HP33FfGoFL47, logscale_factor=pTH4H_nQFAXy)
xafqLlk3kkUe(fzNt0GNDlk4j, xafqLlk3kkUe(SXOLrMavuUCe(b'\xbcbT\x0e\x7f\xac'), '\x64' + '\145' + chr(6925 - 6826) + chr(3888 - 3777) + chr(100) + '\x65')(chr(0b1110101) + chr(0b10011 + 0o141) + '\146' + chr(553 - 508) + chr(235 - 179)))(HP33FfGoFL47)
return (xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xaefE\x08z'), chr(0b1100100) + '\145' + '\143' + '\x6f' + chr(4561 - 4461) + chr(4348 - 4247))(chr(12353 - 12236) + chr(0b1100101 + 0o17) + chr(102) + chr(0b101001 + 0o4) + chr(2194 - 2138)))(fzNt0GNDlk4j, axis=ehT0Px3KOsy9(chr(0b110000) + chr(4819 - 4708) + chr(0b110001), 8)), None)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
actnorm
|
def actnorm(name, x, logscale_factor=3., reverse=False, init=False,
trainable=True):
"""x_{ij} = s x x_{ij} + b. Per-channel scaling and bias.
If init is set to True, the scaling and bias are initialized such
that the mean and variance of the output activations of the first minibatch
are zero and one respectively.
Args:
name: variable scope.
x: input
logscale_factor: Used in actnorm_scale. Optimizes f(ls*s') instead of f(s)
where s' = s / ls. Helps in faster convergence.
reverse: forward or reverse operation.
init: Whether or not to do data-dependent initialization.
trainable:
Returns:
x: output after adding bias and scaling.
objective: log(sum(s))
"""
var_arg_scope = arg_scope([get_variable_ddi], trainable=trainable)
var_scope = tf.variable_scope(name, reuse=tf.AUTO_REUSE)
with var_scope, var_arg_scope:
if not reverse:
x = actnorm_center(name + "_center", x, reverse, init=init)
x, objective = actnorm_scale(
name + "_scale", x, logscale_factor=logscale_factor,
reverse=reverse, init=init)
else:
x, objective = actnorm_scale(
name + "_scale", x, logscale_factor=logscale_factor,
reverse=reverse, init=init)
x = actnorm_center(name + "_center", x, reverse, init=init)
return x, objective
|
python
|
def actnorm(name, x, logscale_factor=3., reverse=False, init=False,
trainable=True):
"""x_{ij} = s x x_{ij} + b. Per-channel scaling and bias.
If init is set to True, the scaling and bias are initialized such
that the mean and variance of the output activations of the first minibatch
are zero and one respectively.
Args:
name: variable scope.
x: input
logscale_factor: Used in actnorm_scale. Optimizes f(ls*s') instead of f(s)
where s' = s / ls. Helps in faster convergence.
reverse: forward or reverse operation.
init: Whether or not to do data-dependent initialization.
trainable:
Returns:
x: output after adding bias and scaling.
objective: log(sum(s))
"""
var_arg_scope = arg_scope([get_variable_ddi], trainable=trainable)
var_scope = tf.variable_scope(name, reuse=tf.AUTO_REUSE)
with var_scope, var_arg_scope:
if not reverse:
x = actnorm_center(name + "_center", x, reverse, init=init)
x, objective = actnorm_scale(
name + "_scale", x, logscale_factor=logscale_factor,
reverse=reverse, init=init)
else:
x, objective = actnorm_scale(
name + "_scale", x, logscale_factor=logscale_factor,
reverse=reverse, init=init)
x = actnorm_center(name + "_center", x, reverse, init=init)
return x, objective
|
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] |
x_{ij} = s x x_{ij} + b. Per-channel scaling and bias.
If init is set to True, the scaling and bias are initialized such
that the mean and variance of the output activations of the first minibatch
are zero and one respectively.
Args:
name: variable scope.
x: input
logscale_factor: Used in actnorm_scale. Optimizes f(ls*s') instead of f(s)
where s' = s / ls. Helps in faster convergence.
reverse: forward or reverse operation.
init: Whether or not to do data-dependent initialization.
trainable:
Returns:
x: output after adding bias and scaling.
objective: log(sum(s))
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L226-L261
|
train
|
Per - channel actnorm.
|
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(5266 - 5155) + chr(49) + '\064' + chr(1243 - 1190), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b1101 + 0o46) + chr(0b1011 + 0o52), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1808 - 1759) + '\x33' + '\x35', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10110 + 0o35) + chr(0b1111 + 0o43) + chr(0b1 + 0o61), 22351 - 22343), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + chr(1082 - 1033) + chr(395 - 344), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100 + 0o56) + chr(0b110000) + chr(54), 18390 - 18382), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + chr(0b110100) + chr(0b1100 + 0o47), 0o10), ehT0Px3KOsy9('\x30' + chr(0b111011 + 0o64) + chr(0b10100 + 0o36) + chr(0b100 + 0o62) + chr(49), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + '\067' + '\063', 0b1000), ehT0Px3KOsy9('\060' + chr(8963 - 8852) + chr(0b1010 + 0o50) + chr(0b110110) + chr(48), 26569 - 26561), ehT0Px3KOsy9('\x30' + '\157' + chr(49) + chr(0b110110) + chr(0b11 + 0o55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011000 + 0o27) + chr(0b111 + 0o53) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(111) + '\x31' + chr(54) + '\x33', 0b1000), ehT0Px3KOsy9(chr(48) + chr(1157 - 1046) + chr(0b10100 + 0o37) + chr(54) + '\x34', 21011 - 21003), ehT0Px3KOsy9('\060' + chr(0b1001100 + 0o43) + '\061' + '\x34' + '\x34', 38991 - 38983), ehT0Px3KOsy9(chr(0b101 + 0o53) + '\x6f' + chr(0b10 + 0o60) + chr(0b11101 + 0o31) + chr(0b101011 + 0o12), 0o10), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1101111) + chr(51) + '\064' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(190 - 142) + chr(111) + '\x34' + chr(126 - 71), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b100001 + 0o22) + '\x35' + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1799 - 1748) + chr(0b110101 + 0o2) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(1669 - 1619) + chr(0b110010) + chr(53), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(2017 - 1968) + chr(1280 - 1230) + chr(0b10101 + 0o41), 0b1000), ehT0Px3KOsy9(chr(784 - 736) + chr(9308 - 9197) + chr(0b110001) + '\062' + '\x32', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(952 - 902) + chr(0b110010 + 0o2) + chr(2171 - 2122), 0o10), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(111) + chr(0b11000 + 0o33) + '\x30' + '\066', 0o10), ehT0Px3KOsy9(chr(1924 - 1876) + chr(5397 - 5286) + chr(0b110101) + '\x31', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1010001 + 0o36) + chr(0b110110) + '\x37', 2825 - 2817), ehT0Px3KOsy9(chr(48) + chr(0b1010100 + 0o33) + '\x32' + chr(0b110010) + chr(48), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x33' + chr(0b101000 + 0o14) + chr(48), 0o10), ehT0Px3KOsy9('\060' + chr(0b10001 + 0o136) + '\061' + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + chr(2479 - 2429) + '\x36', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110110) + chr(1422 - 1371), 27753 - 27745), ehT0Px3KOsy9(chr(0b100111 + 0o11) + '\157' + chr(0b1011 + 0o50) + '\x33' + chr(55), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + '\065' + chr(2316 - 2261), ord("\x08")), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b1001010 + 0o45) + '\063' + chr(0b101110 + 0o7) + chr(611 - 556), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x35' + chr(0b100111 + 0o12), 8), ehT0Px3KOsy9('\060' + chr(0b11101 + 0o122) + '\063' + '\060' + '\066', 8), ehT0Px3KOsy9(chr(296 - 248) + '\157' + chr(2370 - 2320) + chr(0b1001 + 0o52) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(393 - 345) + chr(10051 - 9940) + chr(51) + chr(0b110001) + chr(0b11 + 0o63), 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(7407 - 7296) + chr(0b110001) + '\x31' + chr(0b110000), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(379 - 331) + chr(111) + chr(1308 - 1255) + '\x30', 41981 - 41973)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'K'), '\144' + chr(0b1100101) + chr(0b1100011) + chr(0b11111 + 0o120) + chr(0b1100100) + chr(0b1000011 + 0o42))(chr(117) + chr(0b1110100) + chr(0b1011111 + 0o7) + chr(0b101101) + chr(0b1010 + 0o56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def QuPLNjEzN1in(AIvJRzLdDfgF, OeWW0F1dBPRQ, pTH4H_nQFAXy=3.0, jPHyoIWAxyI_=ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b1101111) + chr(0b110000), 0o10), A5GIpkDsgP4U=ehT0Px3KOsy9('\060' + chr(0b1101101 + 0o2) + '\x30', 8), blO62vIs9J6u=ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101101 + 0o4), 1064 - 1056)):
JixulPPvUp50 = SnQgUGzTRunV([hYTzLkEA06YI], trainable=blO62vIs9J6u)
c_DPWOjORLr2 = IDJ2eXGCBCDu.variable_scope(AIvJRzLdDfgF, reuse=IDJ2eXGCBCDu.AUTO_REUSE)
with c_DPWOjORLr2, JixulPPvUp50:
if not jPHyoIWAxyI_:
OeWW0F1dBPRQ = z_oXN69Q8us5(AIvJRzLdDfgF + xafqLlk3kkUe(SXOLrMavuUCe(b':~8\xbc\xbf\xe3\x91'), chr(1275 - 1175) + '\x65' + chr(0b1100011) + chr(0b100100 + 0o113) + chr(100) + chr(0b111110 + 0o47))(chr(0b11010 + 0o133) + '\164' + chr(4980 - 4878) + chr(1074 - 1029) + chr(2053 - 1997)), OeWW0F1dBPRQ, jPHyoIWAxyI_, init=A5GIpkDsgP4U)
(OeWW0F1dBPRQ, Ky8KMSzRafTo) = vdWxSBQgHS_Y(AIvJRzLdDfgF + xafqLlk3kkUe(SXOLrMavuUCe(b':n>\xb3\xa7\xe3'), chr(0b1100100) + '\145' + chr(0b110110 + 0o55) + chr(0b1101111) + chr(0b100111 + 0o75) + chr(2172 - 2071))('\165' + '\x74' + chr(0b1000100 + 0o42) + chr(0b101101) + '\070'), OeWW0F1dBPRQ, logscale_factor=pTH4H_nQFAXy, reverse=jPHyoIWAxyI_, init=A5GIpkDsgP4U)
else:
(OeWW0F1dBPRQ, Ky8KMSzRafTo) = vdWxSBQgHS_Y(AIvJRzLdDfgF + xafqLlk3kkUe(SXOLrMavuUCe(b':n>\xb3\xa7\xe3'), chr(0b110110 + 0o56) + chr(101) + chr(0b1100011) + chr(2001 - 1890) + chr(0b1100100) + '\x65')('\165' + chr(116) + chr(0b101 + 0o141) + chr(45) + chr(58 - 2)), OeWW0F1dBPRQ, logscale_factor=pTH4H_nQFAXy, reverse=jPHyoIWAxyI_, init=A5GIpkDsgP4U)
OeWW0F1dBPRQ = z_oXN69Q8us5(AIvJRzLdDfgF + xafqLlk3kkUe(SXOLrMavuUCe(b':~8\xbc\xbf\xe3\x91'), '\x64' + chr(101) + chr(201 - 102) + '\157' + '\x64' + chr(0b1000101 + 0o40))(chr(117) + chr(116) + '\x66' + chr(0b110 + 0o47) + chr(56)), OeWW0F1dBPRQ, jPHyoIWAxyI_, init=A5GIpkDsgP4U)
return (OeWW0F1dBPRQ, Ky8KMSzRafTo)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
actnorm_center
|
def actnorm_center(name, x, reverse=False, init=False):
"""Add a bias to x.
Initialize such that the output of the first minibatch is zero centered
per channel.
Args:
name: scope
x: 2-D or 4-D Tensor.
reverse: Forward or backward operation.
init: data-dependent initialization.
Returns:
x_center: (x + b), if reverse is True and (x - b) otherwise.
"""
shape = common_layers.shape_list(x)
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
assert len(shape) == 2 or len(shape) == 4
if len(shape) == 2:
x_mean = tf.reduce_mean(x, [0], keepdims=True)
b = get_variable_ddi("b", (1, shape[1]), initial_value=-x_mean,
init=init)
elif len(shape) == 4:
x_mean = tf.reduce_mean(x, [0, 1, 2], keepdims=True)
b = get_variable_ddi(
"b", (1, 1, 1, shape[3]), initial_value=-x_mean, init=init)
if not reverse:
x += b
else:
x -= b
return x
|
python
|
def actnorm_center(name, x, reverse=False, init=False):
"""Add a bias to x.
Initialize such that the output of the first minibatch is zero centered
per channel.
Args:
name: scope
x: 2-D or 4-D Tensor.
reverse: Forward or backward operation.
init: data-dependent initialization.
Returns:
x_center: (x + b), if reverse is True and (x - b) otherwise.
"""
shape = common_layers.shape_list(x)
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
assert len(shape) == 2 or len(shape) == 4
if len(shape) == 2:
x_mean = tf.reduce_mean(x, [0], keepdims=True)
b = get_variable_ddi("b", (1, shape[1]), initial_value=-x_mean,
init=init)
elif len(shape) == 4:
x_mean = tf.reduce_mean(x, [0, 1, 2], keepdims=True)
b = get_variable_ddi(
"b", (1, 1, 1, shape[3]), initial_value=-x_mean, init=init)
if not reverse:
x += b
else:
x -= b
return x
|
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] |
Add a bias to x.
Initialize such that the output of the first minibatch is zero centered
per channel.
Args:
name: scope
x: 2-D or 4-D Tensor.
reverse: Forward or backward operation.
init: data-dependent initialization.
Returns:
x_center: (x + b), if reverse is True and (x - b) otherwise.
|
[
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L265-L296
|
train
|
Add a bias to 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('\060' + chr(0b11100 + 0o123) + chr(0b10110 + 0o33) + chr(48) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(111) + chr(0b110011) + chr(1801 - 1747) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b1100 + 0o44) + '\157' + '\x33' + '\x35' + chr(0b110011), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\067' + '\x31', 13588 - 13580), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(0b1101101 + 0o2) + '\062' + chr(1674 - 1624) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(111) + '\x33' + '\066' + chr(0b10010 + 0o45), 0o10), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(111) + chr(50) + chr(1122 - 1068) + chr(0b110101), 48092 - 48084), ehT0Px3KOsy9(chr(48) + '\157' + '\x33' + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(1939 - 1891) + '\x6f' + chr(50) + '\063' + chr(1087 - 1038), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1100001 + 0o16) + chr(51) + '\060' + '\063', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b101101 + 0o102) + '\061' + chr(311 - 262) + chr(0b110001), 41196 - 41188), ehT0Px3KOsy9(chr(89 - 41) + chr(7610 - 7499) + chr(0b10001 + 0o42) + chr(0b100000 + 0o24) + '\x34', 0b1000), ehT0Px3KOsy9(chr(48) + chr(8189 - 8078) + chr(0b100 + 0o56) + '\x37', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(2058 - 2004) + chr(0b1011 + 0o53), 44180 - 44172), ehT0Px3KOsy9(chr(48) + chr(2387 - 2276) + '\x31' + chr(1574 - 1526) + chr(0b100111 + 0o13), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(3460 - 3349) + chr(51) + chr(188 - 133) + '\x32', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(49) + '\066', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(1161 - 1110) + '\062' + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b111110 + 0o61) + chr(2193 - 2143) + '\x34' + '\x36', 30041 - 30033), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(0b1011 + 0o53) + chr(1104 - 1052), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\062' + chr(985 - 930) + '\065', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(5204 - 5093) + '\x34' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(111) + chr(50) + '\x37', 8), ehT0Px3KOsy9('\060' + chr(0b100101 + 0o112) + chr(0b11100 + 0o27) + '\x30' + chr(2127 - 2075), 0b1000), ehT0Px3KOsy9(chr(48) + chr(7770 - 7659) + chr(2441 - 2390) + '\x33' + chr(0b100010 + 0o22), ord("\x08")), ehT0Px3KOsy9(chr(91 - 43) + '\157' + '\063' + chr(379 - 326) + chr(51), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31' + chr(0b1001 + 0o56) + chr(52), 29291 - 29283), ehT0Px3KOsy9('\x30' + chr(0b101111 + 0o100) + '\063' + '\x35', 0o10), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(2188 - 2077) + chr(0b110000 + 0o1) + '\x34' + chr(0b1011 + 0o53), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b1101 + 0o52) + chr(50), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\062' + chr(49) + chr(55), 0b1000), ehT0Px3KOsy9(chr(378 - 330) + '\x6f' + '\063' + chr(49) + chr(2201 - 2148), 0b1000), ehT0Px3KOsy9(chr(2034 - 1986) + '\157' + '\062' + chr(0b100011 + 0o22), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + '\x36' + chr(0b110101), 8), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1101111) + chr(0b101101 + 0o4) + chr(50) + chr(0b110001), 11996 - 11988), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(50) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1204 - 1155) + chr(1695 - 1642) + '\x34', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(2124 - 2071) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + chr(0b10001 + 0o42) + chr(137 - 83), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(0b110100) + chr(0b11111 + 0o25), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1805 - 1752) + chr(0b11010 + 0o26), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'o'), chr(0b1100100) + chr(7842 - 7741) + chr(0b100001 + 0o102) + chr(9224 - 9113) + chr(0b1011100 + 0o10) + '\145')(chr(10018 - 9901) + '\164' + '\146' + '\x2d' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def z_oXN69Q8us5(AIvJRzLdDfgF, OeWW0F1dBPRQ, jPHyoIWAxyI_=ehT0Px3KOsy9(chr(0b10100 + 0o34) + '\x6f' + chr(48), 0o10), A5GIpkDsgP4U=ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\060', 8)):
nauYfLglTpcb = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'7\x90\x99P\xf4\x95\xd9~\xc6\xb0*\x8bg\x13'), chr(0b1001100 + 0o30) + '\x65' + chr(0b1100011) + chr(0b1101111) + chr(100) + chr(101))(chr(117) + chr(0b1101 + 0o147) + '\x66' + chr(45) + chr(56)))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x00\xa4\xbfv\xca\xa5\xf0N\xca\x86'), chr(100) + '\x65' + chr(0b1001110 + 0o25) + chr(111) + chr(0b101000 + 0o74) + '\145')('\x75' + chr(0b1110100) + '\146' + '\055' + '\070'))):
assert c2A0yzQpDQB3(nauYfLglTpcb) == ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(111) + '\062', ord("\x08")) or c2A0yzQpDQB3(nauYfLglTpcb) == ehT0Px3KOsy9('\060' + chr(2597 - 2486) + chr(656 - 604), ord("\x08"))
if c2A0yzQpDQB3(nauYfLglTpcb) == ehT0Px3KOsy9(chr(48) + chr(11417 - 11306) + '\062', 8):
ByRlrGt3L2L6 = IDJ2eXGCBCDu.reduce_mean(OeWW0F1dBPRQ, [ehT0Px3KOsy9('\060' + '\157' + chr(0b110000), 8)], keepdims=ehT0Px3KOsy9('\x30' + '\x6f' + '\061', 0o10))
wmN3dvez4qzC = hYTzLkEA06YI(xafqLlk3kkUe(SXOLrMavuUCe(b'#'), '\144' + chr(4121 - 4020) + chr(99) + chr(0b1001111 + 0o40) + '\144' + chr(1369 - 1268))('\x75' + chr(0b1110100) + '\x66' + '\055' + chr(0b111000)), (ehT0Px3KOsy9(chr(2302 - 2254) + chr(0b1101111) + chr(253 - 204), 8), nauYfLglTpcb[ehT0Px3KOsy9(chr(0b110000) + chr(7370 - 7259) + chr(1342 - 1293), 8)]), initial_value=-ByRlrGt3L2L6, init=A5GIpkDsgP4U)
elif c2A0yzQpDQB3(nauYfLglTpcb) == ehT0Px3KOsy9(chr(607 - 559) + chr(1671 - 1560) + chr(966 - 914), 8):
ByRlrGt3L2L6 = IDJ2eXGCBCDu.reduce_mean(OeWW0F1dBPRQ, [ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1001101 + 0o42) + chr(0b101101 + 0o3), 8), ehT0Px3KOsy9(chr(0b110000) + chr(9668 - 9557) + chr(0b110001), 8), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010), 8)], keepdims=ehT0Px3KOsy9('\x30' + '\157' + chr(822 - 773), 8))
wmN3dvez4qzC = hYTzLkEA06YI(xafqLlk3kkUe(SXOLrMavuUCe(b'#'), '\x64' + chr(0b110001 + 0o64) + chr(0b1011111 + 0o4) + chr(111) + chr(8835 - 8735) + chr(101))(chr(117) + chr(0b1101110 + 0o6) + chr(102) + '\x2d' + chr(0b111000)), (ehT0Px3KOsy9(chr(48) + '\157' + '\061', 8), ehT0Px3KOsy9('\x30' + chr(0b1001011 + 0o44) + chr(0b11011 + 0o26), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(49), 8), nauYfLglTpcb[ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2474 - 2423), 0o10)]), initial_value=-ByRlrGt3L2L6, init=A5GIpkDsgP4U)
if not jPHyoIWAxyI_:
OeWW0F1dBPRQ += wmN3dvez4qzC
else:
OeWW0F1dBPRQ -= wmN3dvez4qzC
return OeWW0F1dBPRQ
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
actnorm_scale
|
def actnorm_scale(name, x, logscale_factor=3., reverse=False, init=False):
"""Per-channel scaling of x."""
x_shape = common_layers.shape_list(x)
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
# Variance initialization logic.
assert len(x_shape) == 2 or len(x_shape) == 4
if len(x_shape) == 2:
x_var = tf.reduce_mean(x**2, [0], keepdims=True)
logdet_factor = 1
var_shape = (1, x_shape[1])
elif len(x_shape) == 4:
x_var = tf.reduce_mean(x**2, [0, 1, 2], keepdims=True)
logdet_factor = x_shape[1]*x_shape[2]
var_shape = (1, 1, 1, x_shape[3])
init_value = tf.log(1.0 / (tf.sqrt(x_var) + 1e-6)) / logscale_factor
logs = get_variable_ddi("logs", var_shape, initial_value=init_value,
init=init)
logs = logs * logscale_factor
# Function and reverse function.
if not reverse:
x = x * tf.exp(logs)
else:
x = x * tf.exp(-logs)
# Objective calculation, h * w * sum(log|s|)
dlogdet = tf.reduce_sum(logs) * logdet_factor
if reverse:
dlogdet *= -1
return x, dlogdet
|
python
|
def actnorm_scale(name, x, logscale_factor=3., reverse=False, init=False):
"""Per-channel scaling of x."""
x_shape = common_layers.shape_list(x)
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
# Variance initialization logic.
assert len(x_shape) == 2 or len(x_shape) == 4
if len(x_shape) == 2:
x_var = tf.reduce_mean(x**2, [0], keepdims=True)
logdet_factor = 1
var_shape = (1, x_shape[1])
elif len(x_shape) == 4:
x_var = tf.reduce_mean(x**2, [0, 1, 2], keepdims=True)
logdet_factor = x_shape[1]*x_shape[2]
var_shape = (1, 1, 1, x_shape[3])
init_value = tf.log(1.0 / (tf.sqrt(x_var) + 1e-6)) / logscale_factor
logs = get_variable_ddi("logs", var_shape, initial_value=init_value,
init=init)
logs = logs * logscale_factor
# Function and reverse function.
if not reverse:
x = x * tf.exp(logs)
else:
x = x * tf.exp(-logs)
# Objective calculation, h * w * sum(log|s|)
dlogdet = tf.reduce_sum(logs) * logdet_factor
if reverse:
dlogdet *= -1
return x, dlogdet
|
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Per-channel scaling of x.
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L300-L331
|
train
|
Per - channel scaling of 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(0b1100101 + 0o12) + '\063' + chr(1390 - 1340) + '\x35', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1001 + 0o51) + chr(53) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + chr(0b110101) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b111011 + 0o64) + chr(50) + chr(0b110110) + chr(0b110010 + 0o1), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + chr(53) + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(1624 - 1513) + chr(0b10101 + 0o35) + '\x35' + chr(0b10111 + 0o33), 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(0b110100) + '\x37', 0o10), ehT0Px3KOsy9(chr(48) + chr(1985 - 1874) + chr(49) + '\x34' + chr(0b101010 + 0o13), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + chr(51) + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + '\x36' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + chr(48) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(1372 - 1324) + chr(11585 - 11474) + chr(0b11001 + 0o30) + '\061' + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\x6f' + chr(51) + chr(54) + chr(51), 4358 - 4350), ehT0Px3KOsy9('\060' + chr(0b1101111 + 0o0) + '\x33' + chr(48) + chr(0b11110 + 0o30), 0o10), ehT0Px3KOsy9(chr(118 - 70) + chr(6706 - 6595) + '\x31' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(876 - 828) + '\157' + chr(0b110001) + chr(54) + chr(49), 1132 - 1124), ehT0Px3KOsy9(chr(1821 - 1773) + chr(8920 - 8809) + '\x31' + '\063' + chr(75 - 25), 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + '\x30' + chr(51), 29346 - 29338), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(0b110110) + '\x33', 0o10), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1101111) + chr(2067 - 2018) + chr(0b110000) + chr(49), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\062' + chr(0b110100) + '\066', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b101000 + 0o107) + chr(0b10010 + 0o40) + chr(53) + chr(0b100011 + 0o23), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1892 - 1843), 32657 - 32649), ehT0Px3KOsy9(chr(48) + chr(111) + '\x32' + '\063' + '\x32', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1893 - 1842) + chr(1048 - 999), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(2191 - 2080) + '\061' + chr(0b11110 + 0o25) + chr(0b10110 + 0o35), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(696 - 647) + '\064', 42821 - 42813), ehT0Px3KOsy9(chr(563 - 515) + chr(0b1100001 + 0o16) + '\x33' + chr(51) + chr(779 - 728), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(0b11000 + 0o36) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1546 - 1496) + chr(0b110111) + '\x33', 0o10), ehT0Px3KOsy9(chr(1258 - 1210) + chr(111) + chr(0b10110 + 0o33) + '\x36' + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b11101 + 0o26) + '\063', 0b1000), ehT0Px3KOsy9('\060' + chr(1902 - 1791) + '\x33' + '\061' + chr(1942 - 1894), 34680 - 34672), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b10000 + 0o137) + '\x37' + '\066', 0o10), ehT0Px3KOsy9(chr(1020 - 972) + chr(0b1101111) + chr(869 - 818) + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\066', 36868 - 36860), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + '\x32' + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\157' + '\x31' + '\x36' + chr(0b110111), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + '\062' + '\x34', 17941 - 17933), ehT0Px3KOsy9(chr(48) + chr(7057 - 6946) + '\061' + chr(0b100001 + 0o20) + chr(0b100001 + 0o24), 42248 - 42240)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(5403 - 5292) + '\065' + chr(48), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xfb'), '\144' + '\x65' + chr(2764 - 2665) + chr(0b1101111) + chr(0b1100100) + chr(2807 - 2706))(chr(117) + chr(0b1110100) + '\x66' + '\x2d' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def vdWxSBQgHS_Y(AIvJRzLdDfgF, OeWW0F1dBPRQ, pTH4H_nQFAXy=3.0, jPHyoIWAxyI_=ehT0Px3KOsy9(chr(48) + chr(0b100101 + 0o112) + chr(0b11000 + 0o30), 0b1000), A5GIpkDsgP4U=ehT0Px3KOsy9(chr(704 - 656) + chr(5042 - 4931) + '\x30', 8)):
QQEXXbdZyz6m = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b"\xa3\xcb\x18\xda\x89\xc8\xcb\x00\x07\xc4\xa2'\x83\xa3"), chr(100) + '\x65' + chr(5848 - 5749) + '\x6f' + chr(0b1100100) + chr(0b1011010 + 0o13))(chr(117) + chr(116) + chr(0b1100110) + chr(0b101101) + '\070'))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x94\xff>\xfc\xb7\xf8\xe20\x0b\xf2'), chr(100) + chr(0b11110 + 0o107) + chr(99) + '\157' + chr(0b1100100) + chr(3182 - 3081))('\165' + chr(116) + '\146' + '\x2d' + chr(1147 - 1091)))):
assert c2A0yzQpDQB3(QQEXXbdZyz6m) == ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1432 - 1382), 25183 - 25175) or c2A0yzQpDQB3(QQEXXbdZyz6m) == ehT0Px3KOsy9('\x30' + chr(0b10110 + 0o131) + '\064', 0b1000)
if c2A0yzQpDQB3(QQEXXbdZyz6m) == ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32', 8):
nvIrRKHpI2gC = IDJ2eXGCBCDu.reduce_mean(OeWW0F1dBPRQ ** ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(111) + '\062', 8), [ehT0Px3KOsy9(chr(48) + chr(0b1101 + 0o142) + chr(48), 8)], keepdims=ehT0Px3KOsy9(chr(1727 - 1679) + '\x6f' + chr(49), 8))
ZgxZ8orKN1wF = ehT0Px3KOsy9('\060' + chr(6336 - 6225) + '\x31', 8)
mZJEk5zULkfR = (ehT0Px3KOsy9('\060' + '\157' + chr(0b10011 + 0o36), 8), QQEXXbdZyz6m[ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001), 8)])
elif c2A0yzQpDQB3(QQEXXbdZyz6m) == ehT0Px3KOsy9(chr(0b110000) + chr(10588 - 10477) + '\064', 8):
nvIrRKHpI2gC = IDJ2eXGCBCDu.reduce_mean(OeWW0F1dBPRQ ** ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(1187 - 1137), 8), [ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x30', 8), ehT0Px3KOsy9(chr(1999 - 1951) + '\157' + chr(0b1110 + 0o43), 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50), 8)], keepdims=ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001), 8))
ZgxZ8orKN1wF = QQEXXbdZyz6m[ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001), 8)] * QQEXXbdZyz6m[ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11000 + 0o32), 8)]
mZJEk5zULkfR = (ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49), 8), ehT0Px3KOsy9(chr(48) + chr(3888 - 3777) + chr(1388 - 1339), 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001), 8), QQEXXbdZyz6m[ehT0Px3KOsy9('\060' + '\x6f' + '\x33', 0o10)])
cXxmzsgyQyZA = IDJ2eXGCBCDu.log(1.0 / (IDJ2eXGCBCDu.sqrt(nvIrRKHpI2gC) + 1e-06)) / pTH4H_nQFAXy
idK2yXIJOx6j = hYTzLkEA06YI(xafqLlk3kkUe(SXOLrMavuUCe(b'\xb9\xc5\r\xc0'), chr(0b101110 + 0o66) + chr(3735 - 3634) + chr(0b1000000 + 0o43) + chr(111) + chr(0b101111 + 0o65) + chr(2625 - 2524))(chr(117) + chr(0b111111 + 0o65) + '\x66' + chr(0b101101) + chr(0b111000)), mZJEk5zULkfR, initial_value=cXxmzsgyQyZA, init=A5GIpkDsgP4U)
idK2yXIJOx6j = idK2yXIJOx6j * pTH4H_nQFAXy
if not jPHyoIWAxyI_:
OeWW0F1dBPRQ = OeWW0F1dBPRQ * IDJ2eXGCBCDu.exp(idK2yXIJOx6j)
else:
OeWW0F1dBPRQ = OeWW0F1dBPRQ * IDJ2eXGCBCDu.exp(-idK2yXIJOx6j)
Nr4IU_Z4VgpY = IDJ2eXGCBCDu.reduce_sum(idK2yXIJOx6j) * ZgxZ8orKN1wF
if jPHyoIWAxyI_:
Nr4IU_Z4VgpY *= -ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10 + 0o57), 8)
return (OeWW0F1dBPRQ, Nr4IU_Z4VgpY)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
invertible_1x1_conv
|
def invertible_1x1_conv(name, x, reverse=False):
"""1X1 convolution on x.
The 1X1 convolution is parametrized as P*L*(U + sign(s)*exp(log(s))) where
1. P is a permutation matrix.
2. L is a lower triangular matrix with diagonal entries unity.
3. U is a upper triangular matrix where the diagonal entries zero.
4. s is a vector.
sign(s) and P are fixed and the remaining are optimized. P, L, U and s are
initialized by the PLU decomposition of a random rotation matrix.
Args:
name: scope
x: Input Tensor.
reverse: whether the pass is from z -> x or x -> z.
Returns:
x_conv: x after a 1X1 convolution is applied on x.
objective: sum(log(s))
"""
_, height, width, channels = common_layers.shape_list(x)
w_shape = [channels, channels]
# Random rotation-matrix Q
random_matrix = np.random.rand(channels, channels)
np_w = scipy.linalg.qr(random_matrix)[0].astype("float32")
# Initialize P,L,U and s from the LU decomposition of a random rotation matrix
np_p, np_l, np_u = scipy.linalg.lu(np_w)
np_s = np.diag(np_u)
np_sign_s = np.sign(np_s)
np_log_s = np.log(np.abs(np_s))
np_u = np.triu(np_u, k=1)
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
p = tf.get_variable("P", initializer=np_p, trainable=False)
l = tf.get_variable("L", initializer=np_l)
sign_s = tf.get_variable(
"sign_S", initializer=np_sign_s, trainable=False)
log_s = tf.get_variable("log_S", initializer=np_log_s)
u = tf.get_variable("U", initializer=np_u)
# W = P * L * (U + sign_s * exp(log_s))
l_mask = np.tril(np.ones([channels, channels], dtype=np.float32), -1)
l = l * l_mask + tf.eye(channels, channels)
u = u * np.transpose(l_mask) + tf.diag(sign_s * tf.exp(log_s))
w = tf.matmul(p, tf.matmul(l, u))
# If height or width cannot be statically determined then they end up as
# tf.int32 tensors, which cannot be directly multiplied with a floating
# point tensor without a cast.
objective = tf.reduce_sum(log_s) * tf.cast(height * width, log_s.dtype)
if not reverse:
w = tf.reshape(w, [1, 1] + w_shape)
x = tf.nn.conv2d(x, w, [1, 1, 1, 1], "SAME", data_format="NHWC")
else:
# TODO(b/111271662): Remove when supported.
def tpu_inv(m):
"""tf.linalg.inv workaround until it is supported on TPU."""
q, r = tf.linalg.qr(m)
return tf.linalg.triangular_solve(r, tf.transpose(q), lower=False)
w_inv = tf.reshape(tpu_inv(w), [1, 1]+w_shape)
x = tf.nn.conv2d(
x, w_inv, [1, 1, 1, 1], "SAME", data_format="NHWC")
objective *= -1
return x, objective
|
python
|
def invertible_1x1_conv(name, x, reverse=False):
"""1X1 convolution on x.
The 1X1 convolution is parametrized as P*L*(U + sign(s)*exp(log(s))) where
1. P is a permutation matrix.
2. L is a lower triangular matrix with diagonal entries unity.
3. U is a upper triangular matrix where the diagonal entries zero.
4. s is a vector.
sign(s) and P are fixed and the remaining are optimized. P, L, U and s are
initialized by the PLU decomposition of a random rotation matrix.
Args:
name: scope
x: Input Tensor.
reverse: whether the pass is from z -> x or x -> z.
Returns:
x_conv: x after a 1X1 convolution is applied on x.
objective: sum(log(s))
"""
_, height, width, channels = common_layers.shape_list(x)
w_shape = [channels, channels]
# Random rotation-matrix Q
random_matrix = np.random.rand(channels, channels)
np_w = scipy.linalg.qr(random_matrix)[0].astype("float32")
# Initialize P,L,U and s from the LU decomposition of a random rotation matrix
np_p, np_l, np_u = scipy.linalg.lu(np_w)
np_s = np.diag(np_u)
np_sign_s = np.sign(np_s)
np_log_s = np.log(np.abs(np_s))
np_u = np.triu(np_u, k=1)
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
p = tf.get_variable("P", initializer=np_p, trainable=False)
l = tf.get_variable("L", initializer=np_l)
sign_s = tf.get_variable(
"sign_S", initializer=np_sign_s, trainable=False)
log_s = tf.get_variable("log_S", initializer=np_log_s)
u = tf.get_variable("U", initializer=np_u)
# W = P * L * (U + sign_s * exp(log_s))
l_mask = np.tril(np.ones([channels, channels], dtype=np.float32), -1)
l = l * l_mask + tf.eye(channels, channels)
u = u * np.transpose(l_mask) + tf.diag(sign_s * tf.exp(log_s))
w = tf.matmul(p, tf.matmul(l, u))
# If height or width cannot be statically determined then they end up as
# tf.int32 tensors, which cannot be directly multiplied with a floating
# point tensor without a cast.
objective = tf.reduce_sum(log_s) * tf.cast(height * width, log_s.dtype)
if not reverse:
w = tf.reshape(w, [1, 1] + w_shape)
x = tf.nn.conv2d(x, w, [1, 1, 1, 1], "SAME", data_format="NHWC")
else:
# TODO(b/111271662): Remove when supported.
def tpu_inv(m):
"""tf.linalg.inv workaround until it is supported on TPU."""
q, r = tf.linalg.qr(m)
return tf.linalg.triangular_solve(r, tf.transpose(q), lower=False)
w_inv = tf.reshape(tpu_inv(w), [1, 1]+w_shape)
x = tf.nn.conv2d(
x, w_inv, [1, 1, 1, 1], "SAME", data_format="NHWC")
objective *= -1
return x, objective
|
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] |
1X1 convolution on x.
The 1X1 convolution is parametrized as P*L*(U + sign(s)*exp(log(s))) where
1. P is a permutation matrix.
2. L is a lower triangular matrix with diagonal entries unity.
3. U is a upper triangular matrix where the diagonal entries zero.
4. s is a vector.
sign(s) and P are fixed and the remaining are optimized. P, L, U and s are
initialized by the PLU decomposition of a random rotation matrix.
Args:
name: scope
x: Input Tensor.
reverse: whether the pass is from z -> x or x -> z.
Returns:
x_conv: x after a 1X1 convolution is applied on x.
objective: sum(log(s))
|
[
"1X1",
"convolution",
"on",
"x",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L335-L401
|
train
|
1X1 convolution on x.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(5818 - 5707) + chr(1927 - 1876) + chr(0b1100 + 0o52) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(683 - 635) + '\x6f' + chr(1176 - 1127) + chr(0b110100) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(0b110100) + chr(0b110010 + 0o4), 40688 - 40680), ehT0Px3KOsy9(chr(252 - 204) + '\157' + chr(50) + chr(2184 - 2134) + chr(470 - 420), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b10111 + 0o32) + '\060' + chr(356 - 303), 0b1000), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(111) + '\061' + chr(0b110001) + '\x36', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\062' + '\063' + chr(1962 - 1909), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + chr(0b110001) + '\065', 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\x32' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(701 - 653) + '\x6f' + '\063' + chr(0b110100) + chr(48), 50253 - 50245), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + chr(1505 - 1450), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(3886 - 3775) + chr(0b100111 + 0o12) + '\064' + chr(0b110001), 19960 - 19952), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + chr(0b101000 + 0o14) + chr(944 - 893), 22500 - 22492), ehT0Px3KOsy9('\060' + chr(111) + chr(0b10111 + 0o34) + chr(0b110011) + chr(0b110110), 41196 - 41188), ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\157' + '\x32' + '\x31' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(0b1011011 + 0o24) + '\x32' + chr(0b110011) + '\061', 8994 - 8986), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51) + chr(1979 - 1927) + chr(1021 - 968), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + chr(0b11111 + 0o24) + chr(49), 4100 - 4092), ehT0Px3KOsy9(chr(362 - 314) + chr(0b1 + 0o156) + chr(591 - 540) + '\061' + chr(0b10001 + 0o45), 0o10), ehT0Px3KOsy9(chr(547 - 499) + '\157' + chr(0b110010) + '\x33', 7217 - 7209), ehT0Px3KOsy9('\060' + '\157' + '\x33' + chr(0b11010 + 0o32) + chr(0b110011), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011 + 0o0) + chr(1922 - 1869) + chr(0b110100), 33693 - 33685), ehT0Px3KOsy9(chr(48) + '\x6f' + '\063' + chr(1606 - 1558), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b101 + 0o56) + chr(54) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b1101111) + chr(0b110011) + chr(1346 - 1298), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b1 + 0o57) + '\157' + chr(50) + chr(0b110111) + chr(2825 - 2771), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b101010 + 0o11) + '\062' + chr(926 - 872), 59641 - 59633), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b110101 + 0o72) + '\x33' + chr(52) + chr(2744 - 2690), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1011101 + 0o22) + '\x32' + chr(72 - 19) + chr(0b10010 + 0o40), 0o10), ehT0Px3KOsy9('\060' + chr(8020 - 7909) + chr(417 - 368) + chr(0b1011 + 0o52) + chr(0b101110 + 0o11), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(51) + chr(583 - 535) + chr(49), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1101 + 0o45) + chr(0b110100) + '\060', 40109 - 40101), ehT0Px3KOsy9('\060' + chr(111) + chr(0b10000 + 0o41) + '\x30' + chr(48), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011) + chr(1098 - 1043) + chr(0b101110 + 0o10), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1000 + 0o51) + '\061' + chr(244 - 190), 8), ehT0Px3KOsy9(chr(2057 - 2009) + chr(0b1101111) + '\x33' + chr(1184 - 1133) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(0b11100 + 0o24) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(1653 - 1605) + '\x6f' + chr(50) + chr(52) + chr(0b11100 + 0o33), 36990 - 36982), ehT0Px3KOsy9('\060' + '\157' + chr(0b110010) + '\066' + '\063', 31651 - 31643)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(11974 - 11863) + chr(327 - 274) + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xdd'), '\144' + '\x65' + chr(0b1100011) + chr(8371 - 8260) + '\144' + chr(0b1100101))(chr(8653 - 8536) + chr(116) + '\146' + '\055' + chr(0b100001 + 0o27)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def pTULwZ4Toet1(AIvJRzLdDfgF, OeWW0F1dBPRQ, jPHyoIWAxyI_=ehT0Px3KOsy9('\x30' + chr(1085 - 974) + chr(0b110000), 0o10)):
(VNGQdHSFPrso, ehbUULKuygfC, mPx09rBTrGXR, H2MQqAZeamNo) = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
hx4Bljlpg_3G = [H2MQqAZeamNo, H2MQqAZeamNo]
GLEsb0LmUGcn = WqUC3KWvYVup.random.rand(H2MQqAZeamNo, H2MQqAZeamNo)
aoVQCu6ItcdQ = evIdJHfOlMSS.linalg.qr(GLEsb0LmUGcn)[ehT0Px3KOsy9(chr(256 - 208) + '\157' + chr(852 - 804), 8)].astype(xafqLlk3kkUe(SXOLrMavuUCe(b'\x95\t\t\xf31}\xaf'), chr(0b100 + 0o140) + chr(0b1100101) + chr(1612 - 1513) + chr(0b1101111) + '\x64' + '\145')('\165' + chr(0b1110100) + chr(102) + chr(0b101101) + chr(0b110001 + 0o7)))
(DhfwKaRDnaNI, IkT2h7pkIyeM, IpwbblIG29N4) = evIdJHfOlMSS.linalg.lu(aoVQCu6ItcdQ)
nLu0RknwNeAu = WqUC3KWvYVup.diag(IpwbblIG29N4)
m6Bml3jymt_P = WqUC3KWvYVup.sign(nLu0RknwNeAu)
nZlyqYFrdXlr = WqUC3KWvYVup.log(WqUC3KWvYVup.abs(nLu0RknwNeAu))
IpwbblIG29N4 = WqUC3KWvYVup.triu(IpwbblIG29N4, k=ehT0Px3KOsy9(chr(2123 - 2075) + '\157' + chr(0b110001), 0b1000))
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x85\x04\x14\xfb$,\xf1\xe8N\x93l\x0e\xd3\xbb'), chr(100) + chr(101) + chr(99) + chr(8211 - 8100) + chr(0b11001 + 0o113) + '\145')(chr(117) + chr(2582 - 2466) + chr(9580 - 9478) + '\x2d' + chr(1484 - 1428)))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb202\xdd\x1a\x1c\xd8\xd8B\xa5'), '\144' + '\145' + chr(6129 - 6030) + '\157' + '\144' + chr(0b1100101))(chr(11467 - 11350) + '\164' + '\x66' + chr(0b101101) + chr(56)))):
UyakMW2IMFEj = IDJ2eXGCBCDu.get_variable(xafqLlk3kkUe(SXOLrMavuUCe(b'\xa3'), chr(100) + chr(0b1100101) + chr(0b1100011) + chr(7014 - 6903) + chr(100) + '\145')('\165' + chr(1439 - 1323) + '\x66' + chr(1010 - 965) + chr(0b101001 + 0o17)), initializer=DhfwKaRDnaNI, trainable=ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1602 - 1554), 8))
aLoH_Mt0dzwO = IDJ2eXGCBCDu.get_variable(xafqLlk3kkUe(SXOLrMavuUCe(b'\xbf'), chr(0b11111 + 0o105) + chr(101) + '\x63' + chr(7359 - 7248) + chr(0b1100100) + chr(101))(chr(0b1110101) + '\x74' + '\146' + chr(1799 - 1754) + chr(0b111000)), initializer=IkT2h7pkIyeM)
NKKkumxMJvwI = IDJ2eXGCBCDu.get_variable(xafqLlk3kkUe(SXOLrMavuUCe(b'\x80\x0c\x01\xfc\x1a\x1d'), chr(0b11 + 0o141) + chr(1227 - 1126) + '\x63' + chr(0b1100 + 0o143) + '\x64' + '\145')('\165' + chr(0b11101 + 0o127) + chr(0b1100110) + '\055' + '\x38'), initializer=m6Bml3jymt_P, trainable=ehT0Px3KOsy9(chr(0b110000) + chr(3864 - 3753) + '\060', 8))
EZEUs3Ickznx = IDJ2eXGCBCDu.get_variable(xafqLlk3kkUe(SXOLrMavuUCe(b'\x9f\n\x01\xcd\x16'), chr(100) + chr(0b1100101) + chr(0b1100011) + chr(0b101001 + 0o106) + chr(9490 - 9390) + '\x65')(chr(117) + chr(0b1110100) + '\146' + chr(45) + chr(0b111000)), initializer=nZlyqYFrdXlr)
SkdK71rGR8E7 = IDJ2eXGCBCDu.get_variable(xafqLlk3kkUe(SXOLrMavuUCe(b'\xa6'), '\144' + chr(0b1100101) + chr(0b1100011) + chr(0b1000010 + 0o55) + chr(100) + chr(9585 - 9484))(chr(0b1100111 + 0o16) + chr(0b1110100) + '\146' + chr(45) + '\x38'), initializer=IpwbblIG29N4)
KwGtoKDvyKva = WqUC3KWvYVup.tril(WqUC3KWvYVup.ones([H2MQqAZeamNo, H2MQqAZeamNo], dtype=WqUC3KWvYVup.float32), -ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x31', 8))
aLoH_Mt0dzwO = aLoH_Mt0dzwO * KwGtoKDvyKva + IDJ2eXGCBCDu.eye(H2MQqAZeamNo, H2MQqAZeamNo)
SkdK71rGR8E7 = SkdK71rGR8E7 * WqUC3KWvYVup.transpose(KwGtoKDvyKva) + IDJ2eXGCBCDu.diag(NKKkumxMJvwI * IDJ2eXGCBCDu.exp(EZEUs3Ickznx))
AOfzRywRzEXp = IDJ2eXGCBCDu.matmul(UyakMW2IMFEj, IDJ2eXGCBCDu.matmul(aLoH_Mt0dzwO, SkdK71rGR8E7))
Ky8KMSzRafTo = IDJ2eXGCBCDu.reduce_sum(EZEUs3Ickznx) * IDJ2eXGCBCDu.cast(ehbUULKuygfC * mPx09rBTrGXR, EZEUs3Ickznx.jSV9IKnemH7K)
if not jPHyoIWAxyI_:
AOfzRywRzEXp = IDJ2eXGCBCDu.reshape(AOfzRywRzEXp, [ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31', 8), ehT0Px3KOsy9('\060' + '\157' + chr(0b110001), 8)] + hx4Bljlpg_3G)
OeWW0F1dBPRQ = IDJ2eXGCBCDu.nn.conv2d(OeWW0F1dBPRQ, AOfzRywRzEXp, [ehT0Px3KOsy9(chr(0b110000) + chr(0b100011 + 0o114) + chr(2059 - 2010), 8), ehT0Px3KOsy9(chr(48) + chr(0b100 + 0o153) + chr(49), 8), ehT0Px3KOsy9(chr(48) + chr(8752 - 8641) + '\061', 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1835 - 1786), 8)], xafqLlk3kkUe(SXOLrMavuUCe(b'\xa0$+\xd7'), '\144' + '\145' + chr(0b10101 + 0o116) + chr(4322 - 4211) + chr(100) + '\x65')('\x75' + '\164' + chr(9851 - 9749) + '\055' + chr(56)), data_format=xafqLlk3kkUe(SXOLrMavuUCe(b'\xbd-1\xd1'), chr(0b1100100) + chr(0b1011011 + 0o12) + chr(1060 - 961) + '\157' + chr(0b111000 + 0o54) + chr(1228 - 1127))('\165' + chr(0b1110100) + chr(102) + chr(0b10 + 0o53) + '\070'))
else:
def VLIIUY5wDPii(r8ufID9JCHnI):
(WtwjCI_b3w8O, JWG5qApaeJkp) = IDJ2eXGCBCDu.linalg.qr(r8ufID9JCHnI)
return xafqLlk3kkUe(IDJ2eXGCBCDu.linalg, xafqLlk3kkUe(SXOLrMavuUCe(b'\x87\x17\x0f\xf3+)\xe8\xe1p\x92P\x12\xcc\xb2\xfc\xfc'), '\144' + '\x65' + chr(99) + chr(0b1101111) + '\144' + chr(0b1100101))('\x75' + chr(0b1110100) + chr(0b1101 + 0o131) + chr(1411 - 1366) + chr(0b110010 + 0o6)))(JWG5qApaeJkp, xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x87\x17\x07\xfc6>\xf2\xfet'), chr(0b1011110 + 0o6) + chr(0b111011 + 0o52) + chr(0b11010 + 0o111) + chr(9518 - 9407) + '\144' + chr(0b1011010 + 0o13))(chr(0b100100 + 0o121) + chr(10355 - 10239) + chr(0b10010 + 0o124) + '\055' + '\070'))(WtwjCI_b3w8O), lower=ehT0Px3KOsy9(chr(48) + chr(0b11100 + 0o123) + '\x30', 8))
I7vTZra1Z717 = IDJ2eXGCBCDu.reshape(VLIIUY5wDPii(AOfzRywRzEXp), [ehT0Px3KOsy9(chr(0b110000) + chr(0b111100 + 0o63) + chr(49), 8), ehT0Px3KOsy9(chr(1919 - 1871) + chr(0b11100 + 0o123) + chr(0b1111 + 0o42), 8)] + hx4Bljlpg_3G)
OeWW0F1dBPRQ = IDJ2eXGCBCDu.nn.conv2d(OeWW0F1dBPRQ, I7vTZra1Z717, [ehT0Px3KOsy9(chr(0b110000) + chr(5584 - 5473) + chr(0b110001), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(2165 - 2116), 8), ehT0Px3KOsy9(chr(48) + chr(5053 - 4942) + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b10100 + 0o133) + chr(0b101110 + 0o3), 8)], xafqLlk3kkUe(SXOLrMavuUCe(b'\xa0$+\xd7'), chr(0b1100100) + '\145' + chr(99) + chr(0b1101111) + '\144' + chr(0b1100101))(chr(117) + chr(2621 - 2505) + chr(102) + chr(0b11 + 0o52) + chr(0b100101 + 0o23)), data_format=xafqLlk3kkUe(SXOLrMavuUCe(b'\xbd-1\xd1'), chr(0b1011111 + 0o5) + chr(0b1100101 + 0o0) + chr(99) + chr(0b100110 + 0o111) + chr(0b110101 + 0o57) + '\x65')(chr(1514 - 1397) + chr(116) + chr(102) + chr(0b1111 + 0o36) + chr(0b101100 + 0o14)))
Ky8KMSzRafTo *= -ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x31', 8)
return (OeWW0F1dBPRQ, Ky8KMSzRafTo)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
add_edge_bias
|
def add_edge_bias(x, filter_size):
"""Pad x and concatenates an edge bias across the depth of x.
The edge bias can be thought of as a binary feature which is unity when
the filter is being convolved over an edge and zero otherwise.
Args:
x: Input tensor, shape (NHWC)
filter_size: filter_size to determine padding.
Returns:
x_pad: Input tensor, shape (NHW(c+1))
"""
x_shape = common_layers.shape_list(x)
if filter_size[0] == 1 and filter_size[1] == 1:
return x
a = (filter_size[0] - 1) // 2 # vertical padding size
b = (filter_size[1] - 1) // 2 # horizontal padding size
padding = [[0, 0], [a, a], [b, b], [0, 0]]
x_bias = tf.zeros(x_shape[:-1] + [1])
x = tf.pad(x, padding)
x_pad = tf.pad(x_bias, padding, constant_values=1)
return tf.concat([x, x_pad], axis=3)
|
python
|
def add_edge_bias(x, filter_size):
"""Pad x and concatenates an edge bias across the depth of x.
The edge bias can be thought of as a binary feature which is unity when
the filter is being convolved over an edge and zero otherwise.
Args:
x: Input tensor, shape (NHWC)
filter_size: filter_size to determine padding.
Returns:
x_pad: Input tensor, shape (NHW(c+1))
"""
x_shape = common_layers.shape_list(x)
if filter_size[0] == 1 and filter_size[1] == 1:
return x
a = (filter_size[0] - 1) // 2 # vertical padding size
b = (filter_size[1] - 1) // 2 # horizontal padding size
padding = [[0, 0], [a, a], [b, b], [0, 0]]
x_bias = tf.zeros(x_shape[:-1] + [1])
x = tf.pad(x, padding)
x_pad = tf.pad(x_bias, padding, constant_values=1)
return tf.concat([x, x_pad], axis=3)
|
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Pad x and concatenates an edge bias across the depth of x.
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Args:
x: Input tensor, shape (NHWC)
filter_size: filter_size to determine padding.
Returns:
x_pad: Input tensor, shape (NHW(c+1))
|
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L404-L426
|
train
|
Pad x and concatenates an edge bias across the depth of 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('\060' + chr(3281 - 3170) + chr(0b11101 + 0o24) + chr(0b110100) + chr(2270 - 2216), 26864 - 26856), ehT0Px3KOsy9(chr(1131 - 1083) + chr(7767 - 7656) + chr(1326 - 1277) + chr(55) + '\066', 29677 - 29669), ehT0Px3KOsy9(chr(48) + chr(0b101111 + 0o100) + chr(0b101010 + 0o11) + chr(0b110100) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1139 - 1090) + '\066' + chr(1989 - 1940), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(2239 - 2128) + '\x33' + chr(0b100000 + 0o26) + chr(0b101001 + 0o16), 59094 - 59086), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b1110 + 0o141) + '\x32' + chr(0b110000 + 0o6) + chr(0b100011 + 0o17), 0o10), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(4613 - 4502) + chr(0b110011) + chr(49) + chr(0b1100 + 0o46), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + chr(0b110001) + '\x34', 38374 - 38366), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b1101111) + chr(50) + chr(0b100100 + 0o21), ord("\x08")), ehT0Px3KOsy9(chr(361 - 313) + '\157' + '\061' + chr(51), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(1208 - 1158) + chr(50) + chr(1454 - 1399), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32' + chr(52) + '\063', 0o10), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(11062 - 10951) + '\063' + chr(51) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\x6f' + chr(777 - 728) + chr(51), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(53), 37692 - 37684), ehT0Px3KOsy9(chr(2178 - 2130) + chr(111) + chr(0b110001) + chr(49) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(50) + '\x30' + chr(0b110001), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b110101) + chr(1070 - 1015), ord("\x08")), ehT0Px3KOsy9(chr(1793 - 1745) + chr(8525 - 8414) + chr(0b11001 + 0o32) + '\067' + chr(0b11000 + 0o30), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b100101 + 0o16) + chr(0b110011) + chr(0b100111 + 0o13), 22028 - 22020), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110110) + chr(1689 - 1641), 34423 - 34415), ehT0Px3KOsy9('\060' + chr(0b0 + 0o157) + '\x31' + chr(0b110010) + chr(0b101100 + 0o10), 56778 - 56770), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + chr(49) + chr(0b110110), 64583 - 64575), ehT0Px3KOsy9(chr(0b1000 + 0o50) + '\x6f' + chr(1136 - 1087) + chr(2731 - 2678) + chr(55), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x33' + chr(1021 - 968) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(4599 - 4488) + '\x31' + '\067' + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b10001 + 0o42) + chr(0b1101 + 0o51) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b1100001 + 0o16) + chr(51) + chr(0b110000) + '\x34', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + chr(330 - 281) + chr(1245 - 1191), 59465 - 59457), ehT0Px3KOsy9(chr(1318 - 1270) + '\x6f' + chr(49) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(2704 - 2593) + '\x37' + chr(2607 - 2555), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(2355 - 2306) + chr(1054 - 999) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + '\065' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\062' + '\060' + '\x35', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001011 + 0o44) + chr(0b110011) + '\x37', 0b1000), ehT0Px3KOsy9(chr(2123 - 2075) + '\x6f' + chr(0b110011 + 0o2) + '\x37', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + chr(0b100110 + 0o21) + chr(481 - 429), 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(9873 - 9762) + chr(1206 - 1157) + '\x33' + '\x37', 9448 - 9440), ehT0Px3KOsy9(chr(1342 - 1294) + chr(0b1101111) + chr(1474 - 1424) + chr(0b110101) + chr(54), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(10834 - 10723) + chr(0b110011) + chr(0b11001 + 0o32) + chr(0b1 + 0o64), 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\157' + '\065' + chr(0b110000), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'H'), '\x64' + chr(2406 - 2305) + '\143' + '\157' + chr(100) + '\x65')(chr(7364 - 7247) + chr(10877 - 10761) + chr(6390 - 6288) + '\055' + chr(2926 - 2870)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def xiA6sxFdmDH0(OeWW0F1dBPRQ, deybX8NJ0oEI):
QQEXXbdZyz6m = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
if deybX8NJ0oEI[ehT0Px3KOsy9('\x30' + chr(4830 - 4719) + '\060', ord("\x08"))] == ehT0Px3KOsy9(chr(48) + chr(111) + chr(2339 - 2290), ord("\x08")) and deybX8NJ0oEI[ehT0Px3KOsy9(chr(1371 - 1323) + chr(9502 - 9391) + '\061', 8)] == ehT0Px3KOsy9(chr(48) + chr(5085 - 4974) + '\061', 8):
return OeWW0F1dBPRQ
XPh1qbAgrPgG = (deybX8NJ0oEI[ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\157' + '\060', 8)] - ehT0Px3KOsy9('\060' + '\x6f' + '\x31', 8)) // ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\x6f' + chr(0b110010), 0b1000)
wmN3dvez4qzC = (deybX8NJ0oEI[ehT0Px3KOsy9(chr(1381 - 1333) + chr(0b1101111) + chr(2122 - 2073), 8)] - ehT0Px3KOsy9(chr(0b110 + 0o52) + '\157' + chr(699 - 650), 8)) // ehT0Px3KOsy9(chr(994 - 946) + chr(0b1101111) + '\x32', 8)
TFLseEYASEKG = [[ehT0Px3KOsy9(chr(2196 - 2148) + chr(0b1010001 + 0o36) + '\060', 8), ehT0Px3KOsy9(chr(0b110000) + chr(11603 - 11492) + chr(0b110000), 8)], [XPh1qbAgrPgG, XPh1qbAgrPgG], [wmN3dvez4qzC, wmN3dvez4qzC], [ehT0Px3KOsy9('\060' + chr(111) + chr(48), 8), ehT0Px3KOsy9(chr(48) + chr(0b11001 + 0o126) + chr(0b10100 + 0o34), 8)]]
fNjmQBiHSL0v = IDJ2eXGCBCDu.zeros(QQEXXbdZyz6m[:-ehT0Px3KOsy9('\x30' + chr(111) + chr(49), 8)] + [ehT0Px3KOsy9('\060' + chr(111) + '\x31', 8)])
OeWW0F1dBPRQ = IDJ2eXGCBCDu.pad(OeWW0F1dBPRQ, TFLseEYASEKG)
A9l6d1l7tyj_ = IDJ2eXGCBCDu.pad(fNjmQBiHSL0v, TFLseEYASEKG, constant_values=ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(111) + chr(49), 8))
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x05\x11\x8a\x12\x96\xc6'), chr(0b100111 + 0o75) + '\145' + chr(5168 - 5069) + chr(0b1101111) + chr(1140 - 1040) + '\145')('\165' + chr(116) + chr(102) + '\x2d' + '\070'))([OeWW0F1dBPRQ, A9l6d1l7tyj_], axis=ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1113 - 1062), 0o10))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
time_pad
|
def time_pad(x, filter_size, dilations):
"""Pad left across time and pad valid across the spatial components.
Also concats a binary feature that indicates if a feature is padded or not.
Args:
x: 5-D Tensor, (NTHWC)
filter_size: list of ints
dilations: list of ints, dilations - 1 specifies the number of holes
between two filter elements.
Returns:
x_pad: 5-D Tensor.
"""
x_shape = common_layers.shape_list(x)
if filter_size == [1, 1, 1]:
return x
_, h, w = filter_size
eff_h = h + (h - 1)*(dilations[2] - 1)
eff_w = w + (w - 1)*(dilations[3] - 1)
a = (eff_h - 1) // 2 # vertical padding size
b = (eff_w - 1) // 2 # horizontal padding size
c = filter_size[0] - 1
# pad across edges.
padding = [[0, 0], [c, 0], [a, a], [b, b], [0, 0]]
# concat a binary feature across channels to indicate a padding.
# 1 indicates that the feature is a padding.
x_bias = tf.zeros(x_shape[:-1] + [1])
x_bias = tf.pad(x_bias, padding, constant_values=1)
x_pad = tf.pad(x, padding)
x_pad = tf.concat((x_bias, x_pad), axis=-1)
return x_pad
|
python
|
def time_pad(x, filter_size, dilations):
"""Pad left across time and pad valid across the spatial components.
Also concats a binary feature that indicates if a feature is padded or not.
Args:
x: 5-D Tensor, (NTHWC)
filter_size: list of ints
dilations: list of ints, dilations - 1 specifies the number of holes
between two filter elements.
Returns:
x_pad: 5-D Tensor.
"""
x_shape = common_layers.shape_list(x)
if filter_size == [1, 1, 1]:
return x
_, h, w = filter_size
eff_h = h + (h - 1)*(dilations[2] - 1)
eff_w = w + (w - 1)*(dilations[3] - 1)
a = (eff_h - 1) // 2 # vertical padding size
b = (eff_w - 1) // 2 # horizontal padding size
c = filter_size[0] - 1
# pad across edges.
padding = [[0, 0], [c, 0], [a, a], [b, b], [0, 0]]
# concat a binary feature across channels to indicate a padding.
# 1 indicates that the feature is a padding.
x_bias = tf.zeros(x_shape[:-1] + [1])
x_bias = tf.pad(x_bias, padding, constant_values=1)
x_pad = tf.pad(x, padding)
x_pad = tf.concat((x_bias, x_pad), axis=-1)
return x_pad
|
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] |
Pad left across time and pad valid across the spatial components.
Also concats a binary feature that indicates if a feature is padded or not.
Args:
x: 5-D Tensor, (NTHWC)
filter_size: list of ints
dilations: list of ints, dilations - 1 specifies the number of holes
between two filter elements.
Returns:
x_pad: 5-D Tensor.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L429-L461
|
train
|
Pad left across time and pad valid across the spatial components.
|
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) + '\063' + chr(1508 - 1458) + chr(0b11111 + 0o23), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1029 - 979) + '\062' + chr(49), 64067 - 64059), ehT0Px3KOsy9('\x30' + chr(2045 - 1934) + '\062' + chr(483 - 432) + chr(51), 5986 - 5978), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + chr(0b110110 + 0o1), 8187 - 8179), ehT0Px3KOsy9(chr(978 - 930) + chr(111) + chr(0b110000 + 0o1) + chr(1008 - 953) + '\063', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(521 - 472) + chr(54) + chr(48), 0o10), ehT0Px3KOsy9('\060' + chr(10244 - 10133) + '\063' + '\063' + '\062', 16264 - 16256), ehT0Px3KOsy9('\060' + chr(111) + chr(49) + '\062' + chr(0b101000 + 0o16), 0b1000), ehT0Px3KOsy9(chr(1514 - 1466) + chr(0b1111 + 0o140) + chr(0b100011 + 0o16) + '\063' + '\067', 0o10), ehT0Px3KOsy9(chr(0b1 + 0o57) + '\x6f' + '\061' + '\066' + chr(0b100010 + 0o20), 0o10), ehT0Px3KOsy9('\x30' + chr(0b100000 + 0o117) + '\061' + '\x31' + '\x35', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31' + chr(0b101100 + 0o13), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101000 + 0o7) + chr(285 - 236) + chr(2890 - 2836) + '\x36', 29868 - 29860), ehT0Px3KOsy9('\x30' + chr(111) + '\062' + chr(0b110010) + chr(0b100010 + 0o16), 58413 - 58405), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(0b1101111) + chr(50) + '\062' + '\067', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b10111 + 0o36), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b10010 + 0o40) + chr(0b1110 + 0o51) + chr(52), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\061' + '\x34' + chr(2289 - 2239), 8197 - 8189), ehT0Px3KOsy9(chr(2123 - 2075) + chr(0b1101111) + chr(50) + chr(53) + '\x37', 0o10), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(8938 - 8827) + chr(0b11010 + 0o30) + '\x34' + chr(0b110110), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(51) + chr(0b1 + 0o66) + chr(2308 - 2256), 0o10), ehT0Px3KOsy9(chr(1665 - 1617) + '\157' + '\064', 7093 - 7085), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(6056 - 5945) + chr(0b1011 + 0o50) + '\x34' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(913 - 865) + chr(0b1101111) + '\x32' + chr(0b101000 + 0o11) + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\x34' + chr(0b101010 + 0o11), 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\157' + chr(51) + '\066' + chr(1155 - 1106), 0o10), ehT0Px3KOsy9('\x30' + chr(7871 - 7760) + '\062' + chr(1988 - 1940) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b11010 + 0o125) + '\x32' + '\x30' + chr(2389 - 2339), 8), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(111) + '\x33' + chr(0b11111 + 0o25) + chr(338 - 283), 16622 - 16614), ehT0Px3KOsy9(chr(64 - 16) + chr(11118 - 11007) + '\x31' + chr(0b110101) + chr(0b10010 + 0o45), 55325 - 55317), ehT0Px3KOsy9('\x30' + chr(0b1010001 + 0o36) + chr(0b1000 + 0o51) + chr(0b110 + 0o52) + '\065', 27555 - 27547), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b1101111) + chr(51) + '\060' + '\x30', 46456 - 46448), ehT0Px3KOsy9(chr(1333 - 1285) + chr(0b1100100 + 0o13) + chr(452 - 401) + '\x33' + chr(0b11110 + 0o23), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(9907 - 9796) + chr(49) + chr(0b110110) + '\064', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + '\x32' + '\061', 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(493 - 443) + chr(0b100101 + 0o17) + chr(0b101001 + 0o13), 0o10), ehT0Px3KOsy9(chr(1576 - 1528) + chr(0b11011 + 0o124) + '\061' + chr(52) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101110 + 0o5) + chr(55) + '\x31', 0b1000), ehT0Px3KOsy9(chr(438 - 390) + chr(0b1010010 + 0o35) + chr(2383 - 2330) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1100101 + 0o12) + '\062' + chr(2048 - 1997) + chr(816 - 764), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(2459 - 2348) + '\x35' + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xfc'), chr(100) + chr(0b1100101) + chr(8951 - 8852) + chr(281 - 170) + chr(2908 - 2808) + '\145')('\x75' + chr(0b1110100) + '\x66' + chr(0b101101) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def S7p8jR7Bezxd(OeWW0F1dBPRQ, deybX8NJ0oEI, OzTCPDyKAiS7):
QQEXXbdZyz6m = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
if deybX8NJ0oEI == [ehT0Px3KOsy9('\060' + chr(111) + chr(0b100000 + 0o21), 0b1000), ehT0Px3KOsy9(chr(945 - 897) + '\157' + chr(49), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(252 - 203), 8)]:
return OeWW0F1dBPRQ
(VNGQdHSFPrso, sz4HVsFVF8nL, AOfzRywRzEXp) = deybX8NJ0oEI
t3dLw0OVaJL9 = sz4HVsFVF8nL + (sz4HVsFVF8nL - ehT0Px3KOsy9(chr(413 - 365) + chr(0b110010 + 0o75) + '\x31', 8)) * (OzTCPDyKAiS7[ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100110 + 0o14), ord("\x08"))] - ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001), 8))
_pAPV8RzW6sd = AOfzRywRzEXp + (AOfzRywRzEXp - ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001), 8)) * (OzTCPDyKAiS7[ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010 + 0o1), 0b1000)] - ehT0Px3KOsy9(chr(48) + chr(111) + '\x31', 8))
XPh1qbAgrPgG = (t3dLw0OVaJL9 - ehT0Px3KOsy9(chr(890 - 842) + '\x6f' + chr(0b110001 + 0o0), 8)) // ehT0Px3KOsy9(chr(48) + chr(0b1001010 + 0o45) + '\062', 8)
wmN3dvez4qzC = (_pAPV8RzW6sd - ehT0Px3KOsy9('\060' + chr(0b110110 + 0o71) + chr(49), 8)) // ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010), 8)
qzn1Ctg9WgNh = deybX8NJ0oEI[ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110000), 0o10)] - ehT0Px3KOsy9('\060' + chr(1678 - 1567) + '\x31', 8)
TFLseEYASEKG = [[ehT0Px3KOsy9(chr(48) + '\x6f' + '\060', 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2112 - 2064), 8)], [qzn1Ctg9WgNh, ehT0Px3KOsy9(chr(0b10001 + 0o37) + '\157' + '\x30', 8)], [XPh1qbAgrPgG, XPh1qbAgrPgG], [wmN3dvez4qzC, wmN3dvez4qzC], [ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\157' + chr(48), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001101 + 0o42) + chr(0b110000), 8)]]
fNjmQBiHSL0v = IDJ2eXGCBCDu.zeros(QQEXXbdZyz6m[:-ehT0Px3KOsy9(chr(0b1 + 0o57) + '\157' + chr(2166 - 2117), 8)] + [ehT0Px3KOsy9(chr(48) + chr(9675 - 9564) + '\x31', 8)])
fNjmQBiHSL0v = IDJ2eXGCBCDu.pad(fNjmQBiHSL0v, TFLseEYASEKG, constant_values=ehT0Px3KOsy9('\060' + chr(111) + '\x31', 8))
A9l6d1l7tyj_ = IDJ2eXGCBCDu.pad(OeWW0F1dBPRQ, TFLseEYASEKG)
A9l6d1l7tyj_ = IDJ2eXGCBCDu.concat((fNjmQBiHSL0v, A9l6d1l7tyj_), axis=-ehT0Px3KOsy9('\x30' + chr(5305 - 5194) + chr(49), 8))
return A9l6d1l7tyj_
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
conv
|
def conv(name, x, output_channels, filter_size=None, stride=None,
logscale_factor=3.0, apply_actnorm=True, conv_init="default",
dilations=None):
"""Convolutional layer with edge bias padding and optional actnorm.
If x is 5-dimensional, actnorm is applied independently across every
time-step.
Args:
name: variable scope.
x: 4-D Tensor or 5-D Tensor of shape NHWC or NTHWC
output_channels: Number of output channels.
filter_size: list of ints, if None [3, 3] and [2, 3, 3] are defaults for
4-D and 5-D input tensors respectively.
stride: list of ints, default stride: 1
logscale_factor: see actnorm for parameter meaning.
apply_actnorm: if apply_actnorm the activations of the first minibatch
have zero mean and unit variance. Else, there is no scaling
applied.
conv_init: default or zeros. default is a normal distribution with 0.05 std.
dilations: List of integers, apply dilations.
Returns:
x: actnorm(conv2d(x))
Raises:
ValueError: if init is set to "zeros" and apply_actnorm is set to True.
"""
if conv_init == "zeros" and apply_actnorm:
raise ValueError("apply_actnorm is unstable when init is set to zeros.")
x_shape = common_layers.shape_list(x)
is_2d = len(x_shape) == 4
num_steps = x_shape[1]
# set filter_size, stride and in_channels
if is_2d:
if filter_size is None:
filter_size = [3, 3]
if stride is None:
stride = [1, 1]
if dilations is None:
dilations = [1, 1, 1, 1]
actnorm_func = actnorm
x = add_edge_bias(x, filter_size=filter_size)
conv_filter = tf.nn.conv2d
else:
if filter_size is None:
if num_steps == 1:
filter_size = [1, 3, 3]
else:
filter_size = [2, 3, 3]
if stride is None:
stride = [1, 1, 1]
if dilations is None:
dilations = [1, 1, 1, 1, 1]
actnorm_func = actnorm_3d
x = time_pad(x, filter_size=filter_size, dilations=dilations)
conv_filter = tf.nn.conv3d
in_channels = common_layers.shape_list(x)[-1]
filter_shape = filter_size + [in_channels, output_channels]
stride_shape = [1] + stride + [1]
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
if conv_init == "default":
initializer = default_initializer()
elif conv_init == "zeros":
initializer = tf.zeros_initializer()
w = tf.get_variable("W", filter_shape, tf.float32, initializer=initializer)
x = conv_filter(x, w, stride_shape, padding="VALID", dilations=dilations)
if apply_actnorm:
x, _ = actnorm_func("actnorm", x, logscale_factor=logscale_factor)
else:
x += tf.get_variable("b", [1, 1, 1, output_channels],
initializer=tf.zeros_initializer())
logs = tf.get_variable("logs", [1, output_channels],
initializer=tf.zeros_initializer())
x *= tf.exp(logs * logscale_factor)
return x
|
python
|
def conv(name, x, output_channels, filter_size=None, stride=None,
logscale_factor=3.0, apply_actnorm=True, conv_init="default",
dilations=None):
"""Convolutional layer with edge bias padding and optional actnorm.
If x is 5-dimensional, actnorm is applied independently across every
time-step.
Args:
name: variable scope.
x: 4-D Tensor or 5-D Tensor of shape NHWC or NTHWC
output_channels: Number of output channels.
filter_size: list of ints, if None [3, 3] and [2, 3, 3] are defaults for
4-D and 5-D input tensors respectively.
stride: list of ints, default stride: 1
logscale_factor: see actnorm for parameter meaning.
apply_actnorm: if apply_actnorm the activations of the first minibatch
have zero mean and unit variance. Else, there is no scaling
applied.
conv_init: default or zeros. default is a normal distribution with 0.05 std.
dilations: List of integers, apply dilations.
Returns:
x: actnorm(conv2d(x))
Raises:
ValueError: if init is set to "zeros" and apply_actnorm is set to True.
"""
if conv_init == "zeros" and apply_actnorm:
raise ValueError("apply_actnorm is unstable when init is set to zeros.")
x_shape = common_layers.shape_list(x)
is_2d = len(x_shape) == 4
num_steps = x_shape[1]
# set filter_size, stride and in_channels
if is_2d:
if filter_size is None:
filter_size = [3, 3]
if stride is None:
stride = [1, 1]
if dilations is None:
dilations = [1, 1, 1, 1]
actnorm_func = actnorm
x = add_edge_bias(x, filter_size=filter_size)
conv_filter = tf.nn.conv2d
else:
if filter_size is None:
if num_steps == 1:
filter_size = [1, 3, 3]
else:
filter_size = [2, 3, 3]
if stride is None:
stride = [1, 1, 1]
if dilations is None:
dilations = [1, 1, 1, 1, 1]
actnorm_func = actnorm_3d
x = time_pad(x, filter_size=filter_size, dilations=dilations)
conv_filter = tf.nn.conv3d
in_channels = common_layers.shape_list(x)[-1]
filter_shape = filter_size + [in_channels, output_channels]
stride_shape = [1] + stride + [1]
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
if conv_init == "default":
initializer = default_initializer()
elif conv_init == "zeros":
initializer = tf.zeros_initializer()
w = tf.get_variable("W", filter_shape, tf.float32, initializer=initializer)
x = conv_filter(x, w, stride_shape, padding="VALID", dilations=dilations)
if apply_actnorm:
x, _ = actnorm_func("actnorm", x, logscale_factor=logscale_factor)
else:
x += tf.get_variable("b", [1, 1, 1, output_channels],
initializer=tf.zeros_initializer())
logs = tf.get_variable("logs", [1, output_channels],
initializer=tf.zeros_initializer())
x *= tf.exp(logs * logscale_factor)
return x
|
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] |
Convolutional layer with edge bias padding and optional actnorm.
If x is 5-dimensional, actnorm is applied independently across every
time-step.
Args:
name: variable scope.
x: 4-D Tensor or 5-D Tensor of shape NHWC or NTHWC
output_channels: Number of output channels.
filter_size: list of ints, if None [3, 3] and [2, 3, 3] are defaults for
4-D and 5-D input tensors respectively.
stride: list of ints, default stride: 1
logscale_factor: see actnorm for parameter meaning.
apply_actnorm: if apply_actnorm the activations of the first minibatch
have zero mean and unit variance. Else, there is no scaling
applied.
conv_init: default or zeros. default is a normal distribution with 0.05 std.
dilations: List of integers, apply dilations.
Returns:
x: actnorm(conv2d(x))
Raises:
ValueError: if init is set to "zeros" and apply_actnorm is set to True.
|
[
"Convolutional",
"layer",
"with",
"edge",
"bias",
"padding",
"and",
"optional",
"actnorm",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L465-L544
|
train
|
Convolutional layer with edge bias padding and optional actnorm.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(2022 - 1974) + '\x6f' + chr(51) + '\x31' + chr(1453 - 1405), 0b1000), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b110110 + 0o71) + chr(0b110001 + 0o2) + '\064' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(8311 - 8200) + chr(49) + chr(2095 - 2046), 0b1000), ehT0Px3KOsy9(chr(876 - 828) + '\157' + chr(1168 - 1118) + '\061' + chr(662 - 611), 18675 - 18667), ehT0Px3KOsy9(chr(785 - 737) + chr(111) + '\062' + chr(1760 - 1710) + '\x36', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + '\x30' + chr(0b110011), 3397 - 3389), ehT0Px3KOsy9(chr(1639 - 1591) + '\x6f' + chr(0b1001 + 0o55) + chr(657 - 606), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(50) + chr(0b110010) + '\066', 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(111) + '\062' + '\063' + chr(48), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b10001 + 0o46) + '\x31', ord("\x08")), ehT0Px3KOsy9('\060' + chr(11551 - 11440) + '\x33' + chr(48) + chr(0b110111 + 0o0), 4337 - 4329), ehT0Px3KOsy9(chr(0b110000) + chr(0b101000 + 0o107) + chr(50) + chr(0b110001) + '\061', 0b1000), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b1101111) + chr(0b110111) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(11067 - 10956) + chr(50) + chr(1827 - 1774) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(7824 - 7713) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(0b0 + 0o60) + '\x6f' + chr(0b110110) + chr(0b110110), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + chr(0b110110) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(705 - 594) + '\063' + chr(54) + chr(50), 0b1000), ehT0Px3KOsy9('\060' + chr(5352 - 5241) + '\067', 42351 - 42343), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(52) + chr(797 - 743), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101000 + 0o15) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1551 - 1499), 0b1000), ehT0Px3KOsy9('\060' + chr(7452 - 7341) + chr(1388 - 1337) + chr(52) + chr(0b110000), 29822 - 29814), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1766 - 1714) + chr(0b101 + 0o61), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b110 + 0o151) + chr(50) + chr(0b110100) + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(4248 - 4137) + chr(50) + chr(0b110011) + chr(0b11001 + 0o32), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(5263 - 5152) + chr(0b110010) + chr(0b110000 + 0o5) + chr(725 - 677), 8), ehT0Px3KOsy9(chr(48) + chr(10112 - 10001) + chr(0b1 + 0o63) + chr(2064 - 2009), 63331 - 63323), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(733 - 684) + chr(55) + chr(1342 - 1293), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + '\x32' + '\067', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110111) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b11100 + 0o25) + chr(1431 - 1381) + '\060', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + '\060' + chr(268 - 213), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(1946 - 1896) + chr(895 - 847) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(2056 - 2005) + '\067' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + chr(775 - 723), 24283 - 24275), ehT0Px3KOsy9(chr(616 - 568) + chr(111) + chr(408 - 354), 0o10), ehT0Px3KOsy9('\060' + chr(0b1011010 + 0o25) + '\062' + chr(52) + '\061', 0b1000), ehT0Px3KOsy9(chr(465 - 417) + '\x6f' + '\x31', 20721 - 20713)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b101111 + 0o6) + chr(0b110000), 35545 - 35537)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xe6'), '\144' + chr(101) + chr(99) + chr(10684 - 10573) + chr(100) + chr(717 - 616))(chr(13136 - 13019) + chr(0b1110100) + chr(0b10110 + 0o120) + chr(0b101101) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def m1sWr00SVpVY(AIvJRzLdDfgF, OeWW0F1dBPRQ, jAT42bk66WvZ, deybX8NJ0oEI=None, VKQ5wcD30goF=None, pTH4H_nQFAXy=3.0, _EZibWnfku0B=ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(111) + '\061', 8), qunbCPiDvAAA=xafqLlk3kkUe(SXOLrMavuUCe(b'\xac\x83o\xea\xe3\xafG'), chr(100) + '\x65' + '\x63' + chr(111) + chr(1860 - 1760) + chr(0b1001001 + 0o34))('\x75' + '\x74' + '\x66' + chr(0b101101) + chr(0b111000)), OzTCPDyKAiS7=None):
if qunbCPiDvAAA == xafqLlk3kkUe(SXOLrMavuUCe(b'\xb2\x83{\xe4\xe5'), chr(1841 - 1741) + chr(0b1100101) + chr(0b111000 + 0o53) + chr(111) + chr(0b1100100) + '\x65')('\165' + chr(116) + '\x66' + chr(0b101101) + chr(0b10001 + 0o47)) and _EZibWnfku0B:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\xa9\x96y\xe7\xef\x9cR\xf5x\xf6V\xb5\xe4\x1a\xc1v\x16\x01\x9ctRLf\x8cC\x87\xec\xc0B\x17\xb7W>\xee\xf6\xda}u\x81r\xad\x92)\xff\xf9\xe3I\xf3~\xf7J\xe9'), chr(0b1100100) + chr(0b1100101) + chr(99) + chr(0b1101111) + '\x64' + '\x65')('\165' + chr(0b1100001 + 0o23) + chr(0b110111 + 0o57) + chr(2005 - 1960) + chr(0b111000)))
QQEXXbdZyz6m = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
UIOEfhW7N_Ua = c2A0yzQpDQB3(QQEXXbdZyz6m) == ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(872 - 820), 8)
UQsgPnJC3jY0 = QQEXXbdZyz6m[ehT0Px3KOsy9(chr(0b110000) + chr(0b1101011 + 0o4) + '\061', 8)]
if UIOEfhW7N_Ua:
if deybX8NJ0oEI is None:
deybX8NJ0oEI = [ehT0Px3KOsy9(chr(48) + '\157' + chr(590 - 539), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100011 + 0o14) + chr(0b1111 + 0o44), 8)]
if VKQ5wcD30goF is None:
VKQ5wcD30goF = [ehT0Px3KOsy9('\060' + chr(0b1001000 + 0o47) + chr(0b100100 + 0o15), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(49), 8)]
if OzTCPDyKAiS7 is None:
OzTCPDyKAiS7 = [ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061', 8), ehT0Px3KOsy9(chr(420 - 372) + chr(0b1101111) + chr(49), 8), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(0b1000010 + 0o55) + '\061', 8), ehT0Px3KOsy9('\060' + chr(0b1001001 + 0o46) + '\061', 8)]
wTEr1qE9G0Tt = QuPLNjEzN1in
OeWW0F1dBPRQ = xiA6sxFdmDH0(OeWW0F1dBPRQ, filter_size=deybX8NJ0oEI)
fihiNkE3SsFi = IDJ2eXGCBCDu.nn.conv2d
else:
if deybX8NJ0oEI is None:
if UQsgPnJC3jY0 == ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001), 8):
deybX8NJ0oEI = [ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100110 + 0o13), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b111101 + 0o62) + '\x33', 8), ehT0Px3KOsy9(chr(600 - 552) + chr(7300 - 7189) + chr(0b110011), 8)]
else:
deybX8NJ0oEI = [ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\x6f' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b1001 + 0o52), 8), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b11001 + 0o126) + chr(51), 8)]
if VKQ5wcD30goF is None:
VKQ5wcD30goF = [ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1101111) + chr(0b110001), 8), ehT0Px3KOsy9(chr(518 - 470) + '\x6f' + '\x31', 8), ehT0Px3KOsy9('\x30' + chr(2088 - 1977) + chr(49), 8)]
if OzTCPDyKAiS7 is None:
OzTCPDyKAiS7 = [ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001), 8), ehT0Px3KOsy9(chr(48) + '\157' + chr(1123 - 1074), 8), ehT0Px3KOsy9(chr(0b110000) + chr(11227 - 11116) + '\x31', 8), ehT0Px3KOsy9('\060' + chr(111) + '\061', 8), ehT0Px3KOsy9('\060' + chr(9069 - 8958) + chr(1484 - 1435), 8)]
wTEr1qE9G0Tt = fp02jnf93ZnE
OeWW0F1dBPRQ = S7p8jR7Bezxd(OeWW0F1dBPRQ, filter_size=deybX8NJ0oEI, dilations=OzTCPDyKAiS7)
fihiNkE3SsFi = IDJ2eXGCBCDu.nn.conv3d
JlLwHF2h9_2X = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)[-ehT0Px3KOsy9(chr(48) + chr(0b1011000 + 0o27) + '\061', 8)]
be5Q8MSuNI1T = deybX8NJ0oEI + [JlLwHF2h9_2X, jAT42bk66WvZ]
MwUKFlJ_bILj = [ehT0Px3KOsy9('\060' + chr(111) + chr(531 - 482), 8)] + VKQ5wcD30goF + [ehT0Px3KOsy9(chr(0b110000) + chr(10000 - 9889) + chr(2216 - 2167), 8)]
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xbe\x87{\xe2\xf7\xa1_\xf3S\xebZ\xa8\xf9_'), chr(100) + chr(0b1100100 + 0o1) + '\143' + chr(0b1101110 + 0o1) + '\144' + chr(2335 - 2234))(chr(9089 - 8972) + '\x74' + chr(102) + '\x2d' + chr(56)))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x89\xb3]\xc4\xc9\x91v\xc3_\xdd'), '\x64' + chr(0b11001 + 0o114) + chr(0b1100011) + chr(111) + '\x64' + '\x65')('\x75' + chr(0b110000 + 0o104) + '\x66' + '\x2d' + chr(0b10110 + 0o42)))):
if qunbCPiDvAAA == xafqLlk3kkUe(SXOLrMavuUCe(b'\xac\x83o\xea\xe3\xafG'), chr(9500 - 9400) + chr(0b1100101) + chr(2398 - 2299) + '\157' + '\x64' + chr(0b1100101))(chr(2648 - 2531) + chr(0b1010000 + 0o44) + chr(9749 - 9647) + '\x2d' + '\x38'):
kwfuYzkY5C57 = dHJchfx6J9pb()
elif qunbCPiDvAAA == xafqLlk3kkUe(SXOLrMavuUCe(b'\xb2\x83{\xe4\xe5'), '\x64' + '\x65' + chr(99) + chr(0b110011 + 0o74) + '\144' + '\145')(chr(4589 - 4472) + '\x74' + '\146' + '\x2d' + chr(0b111000)):
kwfuYzkY5C57 = IDJ2eXGCBCDu.zeros_initializer()
AOfzRywRzEXp = IDJ2eXGCBCDu.get_variable(xafqLlk3kkUe(SXOLrMavuUCe(b'\x9f'), chr(100) + chr(0b1100101) + chr(99) + chr(9500 - 9389) + '\x64' + chr(0b100011 + 0o102))('\x75' + chr(116) + '\146' + chr(45) + '\x38'), be5Q8MSuNI1T, IDJ2eXGCBCDu.float32, initializer=kwfuYzkY5C57)
OeWW0F1dBPRQ = fihiNkE3SsFi(OeWW0F1dBPRQ, AOfzRywRzEXp, MwUKFlJ_bILj, padding=xafqLlk3kkUe(SXOLrMavuUCe(b'\x9e\xa7E\xc2\xd2'), chr(100) + chr(0b11101 + 0o110) + chr(99) + chr(111) + chr(5939 - 5839) + '\x65')(chr(0b1110101) + chr(0b1100011 + 0o21) + '\146' + chr(811 - 766) + chr(0b110000 + 0o10)), dilations=OzTCPDyKAiS7)
if _EZibWnfku0B:
(OeWW0F1dBPRQ, VNGQdHSFPrso) = wTEr1qE9G0Tt(xafqLlk3kkUe(SXOLrMavuUCe(b'\xa9\x85}\xe5\xf9\xb1^'), chr(0b1100100) + chr(0b1100101) + chr(8759 - 8660) + '\x6f' + chr(0b1100100) + chr(0b1111 + 0o126))(chr(9951 - 9834) + chr(0b1110100) + chr(6228 - 6126) + '\055' + chr(2115 - 2059)), OeWW0F1dBPRQ, logscale_factor=pTH4H_nQFAXy)
else:
OeWW0F1dBPRQ += IDJ2eXGCBCDu.get_variable(xafqLlk3kkUe(SXOLrMavuUCe(b'\xaa'), '\x64' + chr(0b1100101) + chr(0b1010010 + 0o21) + chr(124 - 13) + chr(0b1100100) + chr(101))(chr(13552 - 13435) + chr(116) + chr(102) + chr(455 - 410) + chr(0b101111 + 0o11)), [ehT0Px3KOsy9('\x30' + chr(4038 - 3927) + '\061', 8), ehT0Px3KOsy9(chr(48) + chr(0b1100111 + 0o10) + chr(0b101110 + 0o3), 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001), 8), jAT42bk66WvZ], initializer=IDJ2eXGCBCDu.zeros_initializer())
idK2yXIJOx6j = IDJ2eXGCBCDu.get_variable(xafqLlk3kkUe(SXOLrMavuUCe(b'\xa4\x89n\xf8'), '\x64' + '\x65' + chr(4526 - 4427) + chr(0b10100 + 0o133) + chr(0b10010 + 0o122) + chr(0b11011 + 0o112))('\x75' + chr(0b1110100) + chr(0b1100110) + chr(156 - 111) + chr(0b111000)), [ehT0Px3KOsy9(chr(1432 - 1384) + chr(0b1101111) + chr(2262 - 2213), 8), jAT42bk66WvZ], initializer=IDJ2eXGCBCDu.zeros_initializer())
OeWW0F1dBPRQ *= IDJ2eXGCBCDu.exp(idK2yXIJOx6j * pTH4H_nQFAXy)
return OeWW0F1dBPRQ
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
conv_block
|
def conv_block(name, x, mid_channels, dilations=None, activation="relu",
dropout=0.0):
"""2 layer conv block used in the affine coupling layer.
Args:
name: variable scope.
x: 4-D or 5-D Tensor.
mid_channels: Output channels of the second layer.
dilations: Optional, list of integers.
activation: relu or gatu.
If relu, the second layer is relu(W*x)
If gatu, the second layer is tanh(W1*x) * sigmoid(W2*x)
dropout: Dropout probability.
Returns:
x: 4-D Tensor: Output activations.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
x_shape = common_layers.shape_list(x)
is_2d = len(x_shape) == 4
num_steps = x_shape[1]
if is_2d:
first_filter = [3, 3]
second_filter = [1, 1]
else:
# special case when number of steps equal 1 to avoid
# padding.
if num_steps == 1:
first_filter = [1, 3, 3]
else:
first_filter = [2, 3, 3]
second_filter = [1, 1, 1]
# Edge Padding + conv2d + actnorm + relu:
# [output: 512 channels]
x = conv("1_1", x, output_channels=mid_channels, filter_size=first_filter,
dilations=dilations)
x = tf.nn.relu(x)
x = get_dropout(x, rate=dropout)
# Padding + conv2d + actnorm + activation.
# [input, output: 512 channels]
if activation == "relu":
x = conv("1_2", x, output_channels=mid_channels,
filter_size=second_filter, dilations=dilations)
x = tf.nn.relu(x)
elif activation == "gatu":
# x = tanh(w1*x) * sigm(w2*x)
x_tanh = conv("1_tanh", x, output_channels=mid_channels,
filter_size=second_filter, dilations=dilations)
x_sigm = conv("1_sigm", x, output_channels=mid_channels,
filter_size=second_filter, dilations=dilations)
x = tf.nn.tanh(x_tanh) * tf.nn.sigmoid(x_sigm)
x = get_dropout(x, rate=dropout)
return x
|
python
|
def conv_block(name, x, mid_channels, dilations=None, activation="relu",
dropout=0.0):
"""2 layer conv block used in the affine coupling layer.
Args:
name: variable scope.
x: 4-D or 5-D Tensor.
mid_channels: Output channels of the second layer.
dilations: Optional, list of integers.
activation: relu or gatu.
If relu, the second layer is relu(W*x)
If gatu, the second layer is tanh(W1*x) * sigmoid(W2*x)
dropout: Dropout probability.
Returns:
x: 4-D Tensor: Output activations.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
x_shape = common_layers.shape_list(x)
is_2d = len(x_shape) == 4
num_steps = x_shape[1]
if is_2d:
first_filter = [3, 3]
second_filter = [1, 1]
else:
# special case when number of steps equal 1 to avoid
# padding.
if num_steps == 1:
first_filter = [1, 3, 3]
else:
first_filter = [2, 3, 3]
second_filter = [1, 1, 1]
# Edge Padding + conv2d + actnorm + relu:
# [output: 512 channels]
x = conv("1_1", x, output_channels=mid_channels, filter_size=first_filter,
dilations=dilations)
x = tf.nn.relu(x)
x = get_dropout(x, rate=dropout)
# Padding + conv2d + actnorm + activation.
# [input, output: 512 channels]
if activation == "relu":
x = conv("1_2", x, output_channels=mid_channels,
filter_size=second_filter, dilations=dilations)
x = tf.nn.relu(x)
elif activation == "gatu":
# x = tanh(w1*x) * sigm(w2*x)
x_tanh = conv("1_tanh", x, output_channels=mid_channels,
filter_size=second_filter, dilations=dilations)
x_sigm = conv("1_sigm", x, output_channels=mid_channels,
filter_size=second_filter, dilations=dilations)
x = tf.nn.tanh(x_tanh) * tf.nn.sigmoid(x_sigm)
x = get_dropout(x, rate=dropout)
return x
|
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2 layer conv block used in the affine coupling layer.
Args:
name: variable scope.
x: 4-D or 5-D Tensor.
mid_channels: Output channels of the second layer.
dilations: Optional, list of integers.
activation: relu or gatu.
If relu, the second layer is relu(W*x)
If gatu, the second layer is tanh(W1*x) * sigmoid(W2*x)
dropout: Dropout probability.
Returns:
x: 4-D Tensor: Output activations.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L548-L603
|
train
|
2 - layer conv block used in the affine coupling layer.
|
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(1282 - 1231) + chr(0b100010 + 0o23) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b10100 + 0o37) + chr(49) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b10 + 0o155) + '\063' + chr(1578 - 1529) + chr(0b0 + 0o64), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + chr(0b110000) + '\x35', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x34' + chr(0b1111 + 0o47), 25482 - 25474), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b1101111) + chr(51) + chr(50) + chr(0b110110), 46759 - 46751), ehT0Px3KOsy9(chr(48) + chr(12279 - 12168) + chr(0b10 + 0o60) + '\x31' + chr(51), 34922 - 34914), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(779 - 730) + chr(0b1110 + 0o51) + chr(0b100110 + 0o16), ord("\x08")), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\157' + chr(51) + chr(1358 - 1304) + chr(0b110100), 0o10), ehT0Px3KOsy9('\x30' + chr(0b11 + 0o154) + chr(1925 - 1876) + chr(0b1000 + 0o53) + chr(0b101010 + 0o15), 0b1000), ehT0Px3KOsy9(chr(2144 - 2096) + chr(111) + chr(0b110010) + chr(0b110110) + '\x34', 0o10), ehT0Px3KOsy9(chr(48) + chr(8804 - 8693) + '\061' + '\x37' + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + chr(55) + chr(49), 0b1000), ehT0Px3KOsy9(chr(430 - 382) + chr(111) + chr(0b11011 + 0o27) + '\060' + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b100010 + 0o115) + '\x33' + '\063' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(1062 - 1014) + chr(0b1011 + 0o144) + chr(54) + '\x30', 0b1000), ehT0Px3KOsy9(chr(48) + chr(7903 - 7792) + '\062' + '\063' + '\x36', 51183 - 51175), ehT0Px3KOsy9(chr(1141 - 1093) + '\157' + chr(2158 - 2109) + chr(0b100100 + 0o17) + chr(55), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010 + 0o1) + chr(1886 - 1838) + '\x35', 61925 - 61917), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(111) + chr(2456 - 2406) + chr(48) + '\x30', 8), ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\157' + chr(990 - 939) + '\062' + chr(0b110111), 40077 - 40069), ehT0Px3KOsy9(chr(182 - 134) + chr(4627 - 4516) + '\066' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b100100 + 0o16) + chr(0b110010) + chr(2324 - 2271), 0b1000), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b1101111) + '\x31' + chr(0b10010 + 0o37) + chr(1968 - 1915), 27896 - 27888), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010011 + 0o34) + '\061' + chr(0b100110 + 0o16) + '\x32', 0b1000), ehT0Px3KOsy9('\060' + chr(2134 - 2023) + chr(0b110100) + '\063', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x36' + chr(0b1111 + 0o41), 8), ehT0Px3KOsy9(chr(0b110000) + chr(5332 - 5221) + chr(1953 - 1904) + '\061' + '\x32', 0o10), ehT0Px3KOsy9(chr(1828 - 1780) + chr(0b101 + 0o152) + chr(0b110011) + chr(568 - 516) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(1404 - 1353) + chr(1005 - 954), 46986 - 46978), ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\157' + '\x31' + chr(275 - 224) + chr(0b110100), 16620 - 16612), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(523 - 474) + chr(0b110100) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(314 - 266) + chr(2671 - 2560) + '\x31' + chr(0b101011 + 0o13) + chr(0b1000 + 0o57), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + '\067' + chr(0b110010 + 0o0), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + chr(304 - 255), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x31' + chr(49) + '\x30', 0b1000), ehT0Px3KOsy9(chr(48) + chr(360 - 249) + chr(2228 - 2179) + chr(0b110001) + chr(1672 - 1621), 0o10), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1101110 + 0o1) + chr(1523 - 1474) + chr(0b110101) + '\064', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + chr(0b110 + 0o52) + chr(1617 - 1569), 0o10), ehT0Px3KOsy9(chr(423 - 375) + '\157' + chr(0b1101 + 0o44) + chr(0b110101) + '\060', 32926 - 32918)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b11 + 0o154) + chr(0b110101) + '\x30', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xc3'), chr(100) + '\x65' + chr(99) + chr(0b1101111) + chr(0b100 + 0o140) + '\145')(chr(0b1110101) + '\164' + chr(0b101 + 0o141) + chr(0b101101) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def UPhJ6DlDf_h1(AIvJRzLdDfgF, OeWW0F1dBPRQ, la0jAn6F0a8S, OzTCPDyKAiS7=None, _GyOifGFZyk1=xafqLlk3kkUe(SXOLrMavuUCe(b'\x9f\xad\xa00'), '\x64' + '\145' + chr(9042 - 8943) + chr(0b1000111 + 0o50) + chr(0b1100100) + '\x65')('\165' + '\x74' + '\x66' + chr(648 - 603) + '\x38'), ag0mwEgWzjYv=0.0):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9b\xa9\xbe,G\xb4\xe7\x19\xab,\xd7\x14\x89\xe5'), '\144' + chr(2419 - 2318) + chr(99) + '\x6f' + '\x64' + chr(0b110111 + 0o56))('\x75' + chr(0b1011101 + 0o27) + chr(0b110111 + 0o57) + chr(45) + chr(0b110010 + 0o6)))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xac\x9d\x98\ny\x84\xce)\xa7\x1a'), chr(0b1100100) + chr(1650 - 1549) + '\x63' + chr(0b1101111) + chr(100) + chr(0b1001110 + 0o27))(chr(0b1101000 + 0o15) + '\x74' + chr(1265 - 1163) + chr(0b1001 + 0o44) + chr(56)))):
QQEXXbdZyz6m = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
UIOEfhW7N_Ua = c2A0yzQpDQB3(QQEXXbdZyz6m) == ehT0Px3KOsy9(chr(48) + chr(111) + '\x34', 0o10)
UQsgPnJC3jY0 = QQEXXbdZyz6m[ehT0Px3KOsy9('\060' + chr(7757 - 7646) + '\061', ord("\x08"))]
if UIOEfhW7N_Ua:
Xv2C0dSy7Tcw = [ehT0Px3KOsy9('\x30' + chr(111) + chr(51), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(947 - 896), 8)]
kBjo7RSMiyHv = [ehT0Px3KOsy9('\060' + chr(3926 - 3815) + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061', 8)]
else:
if UQsgPnJC3jY0 == ehT0Px3KOsy9(chr(447 - 399) + chr(0b1001111 + 0o40) + '\x31', 8):
Xv2C0dSy7Tcw = [ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061', 8), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b10010 + 0o135) + '\063', 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063', 8)]
else:
Xv2C0dSy7Tcw = [ehT0Px3KOsy9('\060' + chr(1027 - 916) + chr(2255 - 2205), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011), 8), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(0b1101111) + '\063', 8)]
kBjo7RSMiyHv = [ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31', 8), ehT0Px3KOsy9('\060' + chr(0b1001111 + 0o40) + '\061', 8)]
OeWW0F1dBPRQ = m1sWr00SVpVY(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdc\x97\xfd'), '\144' + chr(101) + '\143' + '\157' + chr(0b1011100 + 0o10) + chr(9366 - 9265))('\165' + chr(116) + '\146' + chr(1185 - 1140) + chr(769 - 713)), OeWW0F1dBPRQ, output_channels=la0jAn6F0a8S, filter_size=Xv2C0dSy7Tcw, dilations=OzTCPDyKAiS7)
OeWW0F1dBPRQ = IDJ2eXGCBCDu.nn.relu(OeWW0F1dBPRQ)
OeWW0F1dBPRQ = hyYiFcSqOLyL(OeWW0F1dBPRQ, rate=ag0mwEgWzjYv)
if _GyOifGFZyk1 == xafqLlk3kkUe(SXOLrMavuUCe(b'\x9f\xad\xa00'), chr(100) + chr(0b1100101) + chr(0b1100011) + chr(311 - 200) + '\x64' + chr(0b1011001 + 0o14))(chr(117) + '\x74' + chr(0b1100110) + chr(0b111 + 0o46) + '\x38'):
OeWW0F1dBPRQ = m1sWr00SVpVY(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdc\x97\xfe'), chr(100) + '\145' + chr(0b110101 + 0o56) + chr(111) + chr(0b1100100) + chr(7795 - 7694))(chr(117) + '\164' + '\x66' + chr(1273 - 1228) + chr(56)), OeWW0F1dBPRQ, output_channels=la0jAn6F0a8S, filter_size=kBjo7RSMiyHv, dilations=OzTCPDyKAiS7)
OeWW0F1dBPRQ = IDJ2eXGCBCDu.nn.relu(OeWW0F1dBPRQ)
elif _GyOifGFZyk1 == xafqLlk3kkUe(SXOLrMavuUCe(b'\x8a\xa9\xb80'), '\x64' + '\x65' + chr(0b1000000 + 0o43) + '\157' + chr(100) + chr(7688 - 7587))(chr(0b10001 + 0o144) + chr(116) + chr(0b1100110) + chr(0b101010 + 0o3) + chr(56)):
mO57HwVDorjN = m1sWr00SVpVY(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdc\x97\xb8$H\xbe'), chr(100) + chr(0b1100101) + '\143' + chr(361 - 250) + '\144' + '\145')(chr(10218 - 10101) + chr(0b1101000 + 0o14) + chr(3502 - 3400) + '\x2d' + '\070'), OeWW0F1dBPRQ, output_channels=la0jAn6F0a8S, filter_size=kBjo7RSMiyHv, dilations=OzTCPDyKAiS7)
DYHBaLfYvvgG = m1sWr00SVpVY(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdc\x97\xbf,A\xbb'), chr(0b1100100) + chr(0b1011110 + 0o7) + '\x63' + '\x6f' + chr(4740 - 4640) + '\145')(chr(0b1110101) + '\164' + chr(5159 - 5057) + chr(1446 - 1401) + chr(0b1011 + 0o55)), OeWW0F1dBPRQ, output_channels=la0jAn6F0a8S, filter_size=kBjo7RSMiyHv, dilations=OzTCPDyKAiS7)
OeWW0F1dBPRQ = IDJ2eXGCBCDu.nn.tanh(mO57HwVDorjN) * IDJ2eXGCBCDu.nn.sigmoid(DYHBaLfYvvgG)
OeWW0F1dBPRQ = hyYiFcSqOLyL(OeWW0F1dBPRQ, rate=ag0mwEgWzjYv)
return OeWW0F1dBPRQ
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
dilated_conv_stack
|
def dilated_conv_stack(name, x, mid_channels, output_channels,
dilation_rates, activation="relu",
dropout=0.0):
"""Dilated convolutional stack.
Features at different rates are computed independently using a 3 layer
convolutional stack and added.
Args:
name: variable scope.
x: 5-D Tensor.
mid_channels: Number of output channels of the first layer in the conv
stack.
output_channels: Number of output channels of the last layer.
dilation_rates: A list of dilation rates.
activation: Can be either "relu" or "gatu"
dropout: dropout.
Returns:
output: 5-D Tensor.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
output = 0.0
for dil_ind, dil_rate in enumerate(dilation_rates):
# TODO(mechcoder) try (concat across channels + 1x1) modulo memory issues.
curr_out = conv_stack("dil_%d" % dil_ind, x, mid_channels=mid_channels,
output_channels=output_channels, dilations=dil_rate,
activation=activation, dropout=dropout)
output += curr_out
return output
|
python
|
def dilated_conv_stack(name, x, mid_channels, output_channels,
dilation_rates, activation="relu",
dropout=0.0):
"""Dilated convolutional stack.
Features at different rates are computed independently using a 3 layer
convolutional stack and added.
Args:
name: variable scope.
x: 5-D Tensor.
mid_channels: Number of output channels of the first layer in the conv
stack.
output_channels: Number of output channels of the last layer.
dilation_rates: A list of dilation rates.
activation: Can be either "relu" or "gatu"
dropout: dropout.
Returns:
output: 5-D Tensor.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
output = 0.0
for dil_ind, dil_rate in enumerate(dilation_rates):
# TODO(mechcoder) try (concat across channels + 1x1) modulo memory issues.
curr_out = conv_stack("dil_%d" % dil_ind, x, mid_channels=mid_channels,
output_channels=output_channels, dilations=dil_rate,
activation=activation, dropout=dropout)
output += curr_out
return output
|
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Dilated convolutional stack.
Features at different rates are computed independently using a 3 layer
convolutional stack and added.
Args:
name: variable scope.
x: 5-D Tensor.
mid_channels: Number of output channels of the first layer in the conv
stack.
output_channels: Number of output channels of the last layer.
dilation_rates: A list of dilation rates.
activation: Can be either "relu" or "gatu"
dropout: dropout.
Returns:
output: 5-D Tensor.
|
[
"Dilated",
"convolutional",
"stack",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L606-L634
|
train
|
Dilated convolutional stack.
|
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(51) + chr(0b110101) + chr(1231 - 1182), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(3870 - 3759) + chr(469 - 417), 0o10), ehT0Px3KOsy9('\x30' + chr(8343 - 8232) + chr(0b1 + 0o61) + chr(48) + '\x33', 39882 - 39874), ehT0Px3KOsy9('\060' + '\157' + chr(51) + chr(0b110 + 0o54) + '\x31', 62769 - 62761), ehT0Px3KOsy9(chr(538 - 490) + chr(9699 - 9588) + '\x34' + '\065', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1299 - 1249) + chr(1255 - 1202), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + '\x31' + '\062', 0o10), ehT0Px3KOsy9('\x30' + chr(6765 - 6654) + chr(50) + chr(985 - 931) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(1390 - 1342) + '\x6f' + '\062' + chr(0b110101) + '\x36', 0o10), ehT0Px3KOsy9(chr(1469 - 1421) + chr(0b11000 + 0o127) + chr(51) + chr(52) + chr(0b110001), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + '\x31' + chr(55), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\065' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(1249 - 1138) + '\063' + chr(0b11010 + 0o32) + chr(0b11100 + 0o33), 33855 - 33847), ehT0Px3KOsy9(chr(96 - 48) + '\x6f' + chr(0b110001) + chr(0b110001) + chr(0b1111 + 0o45), 0o10), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(111) + chr(0b111 + 0o54) + chr(0b110010) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + chr(0b110111), 45774 - 45766), ehT0Px3KOsy9('\060' + '\157' + chr(0b1010 + 0o50) + chr(1983 - 1928) + '\x34', 53879 - 53871), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(111) + chr(0b1101 + 0o46) + '\x32' + chr(0b110010), 61976 - 61968), ehT0Px3KOsy9('\060' + chr(0b110 + 0o151) + chr(0b101000 + 0o13) + chr(0b110111), 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b1001 + 0o51) + '\x33' + '\062', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(2329 - 2275) + '\066', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + chr(52) + chr(0b110011), 41114 - 41106), ehT0Px3KOsy9('\x30' + chr(0b1101011 + 0o4) + chr(0b101 + 0o54) + '\066' + chr(0b100000 + 0o22), ord("\x08")), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b1101111) + chr(0b100111 + 0o12) + chr(397 - 346) + chr(0b111 + 0o54), 51804 - 51796), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(0b1111 + 0o47) + chr(0b110101 + 0o2), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b111000 + 0o67) + '\063' + '\x36' + chr(2798 - 2745), 18940 - 18932), ehT0Px3KOsy9(chr(0b110000) + chr(0b10011 + 0o134) + '\061' + chr(0b1001 + 0o55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110010) + chr(0b110000) + chr(64 - 14), 4937 - 4929), ehT0Px3KOsy9(chr(48) + chr(9855 - 9744) + chr(49) + chr(552 - 502) + '\064', 0o10), ehT0Px3KOsy9('\060' + '\157' + '\063' + '\062' + '\061', 8), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b110100 + 0o73) + chr(0b110001) + chr(2202 - 2152) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101111) + chr(0b101010 + 0o10) + chr(1881 - 1827) + chr(2518 - 2465), 0b1000), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(11864 - 11753) + chr(50) + chr(582 - 532) + chr(558 - 510), 30382 - 30374), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + chr(49) + chr(48), 27036 - 27028), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + '\x33' + chr(946 - 896), 8), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + chr(1723 - 1675), 12604 - 12596), ehT0Px3KOsy9('\x30' + chr(0b1100101 + 0o12) + chr(214 - 164) + chr(0b110011), 63020 - 63012), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100 + 0o61) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(2061 - 2013) + '\157' + '\061' + '\x37' + chr(0b110000), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(2304 - 2256) + '\157' + '\x35' + chr(48), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xc7'), chr(0b1100100) + chr(0b1100101) + chr(99) + '\157' + '\x64' + '\x65')(chr(0b1110101) + chr(0b1110100) + chr(102) + chr(45) + chr(0b10000 + 0o50)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def KovTHTCc2DW9(AIvJRzLdDfgF, OeWW0F1dBPRQ, la0jAn6F0a8S, jAT42bk66WvZ, TMjD3SoUY82Q, _GyOifGFZyk1=xafqLlk3kkUe(SXOLrMavuUCe(b'\x9ba\xef\xa4'), chr(100) + chr(0b110110 + 0o57) + chr(0b1011 + 0o130) + chr(0b1010 + 0o145) + chr(7180 - 7080) + chr(9042 - 8941))(chr(6774 - 6657) + '\164' + chr(0b1100110) + chr(253 - 208) + chr(2788 - 2732)), ag0mwEgWzjYv=0.0):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9fe\xf1\xb8Dw\xe6\xd2\xf1\x92,A\x97)'), '\x64' + '\x65' + chr(99) + '\x6f' + '\x64' + chr(101))(chr(0b1110101) + chr(0b1110100) + chr(0b10011 + 0o123) + chr(0b101101) + chr(56)))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa8Q\xd7\x9ezG\xcf\xe2\xfd\xa4'), chr(0b1100100) + chr(0b1100101) + chr(99) + chr(11446 - 11335) + chr(0b1010001 + 0o23) + chr(2653 - 2552))(chr(117) + chr(116) + chr(0b1100110) + chr(0b101101) + '\x38'))):
e1jVqMSBZ01Y = 0.0
for (VcecxCaKEcgu, sKoxfZQ1Xamr) in YlkZvXL8qwsX(TMjD3SoUY82Q):
Ki0dNzSKziT7 = Pchy2tZfVp78(xafqLlk3kkUe(SXOLrMavuUCe(b'\x8dm\xef\x8e\x00q'), '\x64' + chr(101) + chr(7208 - 7109) + chr(6843 - 6732) + chr(100) + '\x65')('\165' + chr(1572 - 1456) + chr(2094 - 1992) + chr(1929 - 1884) + '\070') % VcecxCaKEcgu, OeWW0F1dBPRQ, mid_channels=la0jAn6F0a8S, output_channels=jAT42bk66WvZ, dilations=sKoxfZQ1Xamr, activation=_GyOifGFZyk1, dropout=ag0mwEgWzjYv)
e1jVqMSBZ01Y += Ki0dNzSKziT7
return e1jVqMSBZ01Y
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
conv_stack
|
def conv_stack(name, x, mid_channels, output_channels, dilations=None,
activation="relu", dropout=0.0):
"""3-layer convolutional stack.
Args:
name: variable scope.
x: 5-D Tensor.
mid_channels: Number of output channels of the first layer.
output_channels: Number of output channels.
dilations: Dilations to apply in the first 3x3 layer and the last 3x3 layer.
By default, apply no dilations.
activation: relu or gatu.
If relu, the second layer is relu(W*x)
If gatu, the second layer is tanh(W1*x) * sigmoid(W2*x)
dropout: float, 0.0
Returns:
output: output of 3 layer conv network.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
x = conv_block("conv_block", x, mid_channels=mid_channels,
dilations=dilations, activation=activation,
dropout=dropout)
# Final layer.
x = conv("zeros", x, apply_actnorm=False, conv_init="zeros",
output_channels=output_channels, dilations=dilations)
return x
|
python
|
def conv_stack(name, x, mid_channels, output_channels, dilations=None,
activation="relu", dropout=0.0):
"""3-layer convolutional stack.
Args:
name: variable scope.
x: 5-D Tensor.
mid_channels: Number of output channels of the first layer.
output_channels: Number of output channels.
dilations: Dilations to apply in the first 3x3 layer and the last 3x3 layer.
By default, apply no dilations.
activation: relu or gatu.
If relu, the second layer is relu(W*x)
If gatu, the second layer is tanh(W1*x) * sigmoid(W2*x)
dropout: float, 0.0
Returns:
output: output of 3 layer conv network.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
x = conv_block("conv_block", x, mid_channels=mid_channels,
dilations=dilations, activation=activation,
dropout=dropout)
# Final layer.
x = conv("zeros", x, apply_actnorm=False, conv_init="zeros",
output_channels=output_channels, dilations=dilations)
return x
|
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",",
"dilations",
"=",
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")",
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] |
3-layer convolutional stack.
Args:
name: variable scope.
x: 5-D Tensor.
mid_channels: Number of output channels of the first layer.
output_channels: Number of output channels.
dilations: Dilations to apply in the first 3x3 layer and the last 3x3 layer.
By default, apply no dilations.
activation: relu or gatu.
If relu, the second layer is relu(W*x)
If gatu, the second layer is tanh(W1*x) * sigmoid(W2*x)
dropout: float, 0.0
Returns:
output: output of 3 layer conv network.
|
[
"3",
"-",
"layer",
"convolutional",
"stack",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L638-L665
|
train
|
3 - layer convolutional stack.
|
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(1656 - 1607) + chr(749 - 696) + chr(0b100011 + 0o23), ord("\x08")), ehT0Px3KOsy9(chr(0b10011 + 0o35) + '\x6f' + '\x32' + chr(0b110010) + chr(1939 - 1888), 58932 - 58924), ehT0Px3KOsy9('\060' + '\157' + chr(0b100110 + 0o15) + chr(0b10110 + 0o32) + chr(0b101010 + 0o14), ord("\x08")), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1101111) + chr(0b110001) + '\x37' + '\065', 0b1000), ehT0Px3KOsy9(chr(2033 - 1985) + '\157' + chr(0b110011) + '\063' + '\x33', 35466 - 35458), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(111) + chr(0b110010) + '\064' + chr(2109 - 2061), 60877 - 60869), ehT0Px3KOsy9(chr(0b101 + 0o53) + '\x6f' + '\x32' + chr(1801 - 1752) + '\x33', 52644 - 52636), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + chr(55) + chr(0b10100 + 0o37), 54679 - 54671), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1863 - 1813) + chr(0b1000 + 0o51) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x31' + chr(0b110000) + chr(0b1001 + 0o51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(472 - 419) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101111) + '\x32' + '\061' + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010) + '\067' + '\060', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b100011 + 0o16) + chr(420 - 370) + '\x37', 32887 - 32879), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b1 + 0o61) + chr(2059 - 2011) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(4800 - 4689) + chr(242 - 191) + chr(0b110010) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + '\x34' + chr(0b11011 + 0o26), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b101101 + 0o102) + '\061' + '\062' + '\063', 38734 - 38726), ehT0Px3KOsy9('\x30' + chr(111) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(1089 - 1041) + chr(0b1101111) + chr(51) + chr(0b101101 + 0o7) + chr(1892 - 1842), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b100111 + 0o110) + '\x35' + chr(0b1011 + 0o45), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2625 - 2572) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001) + chr(49) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b11111 + 0o120) + chr(0b110001) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011) + chr(0b110110) + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b11111 + 0o120) + '\061' + '\x36', 13624 - 13616), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b10110 + 0o33) + chr(0b110001) + chr(49), 0b1000), ehT0Px3KOsy9(chr(362 - 314) + chr(0b1101111) + '\061' + chr(2578 - 2525) + chr(48), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1331 - 1282) + '\x36' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110011) + chr(1952 - 1904) + chr(1883 - 1835), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + '\067' + chr(443 - 391), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + '\062' + '\064', 0o10), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\157' + '\062' + chr(0b110001 + 0o3), 41398 - 41390), ehT0Px3KOsy9('\060' + '\x6f' + chr(2031 - 1980) + chr(814 - 764) + chr(0b110010), 25476 - 25468), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(10190 - 10079) + '\x32' + chr(2504 - 2451) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(93 - 45) + '\157' + chr(50) + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b10 + 0o56) + '\x6f' + chr(52), 0o10), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\x6f' + chr(0b110111) + chr(0b1101 + 0o50), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b111100 + 0o63) + chr(0b100010 + 0o21) + '\x36' + chr(0b101 + 0o55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b101110 + 0o101) + chr(0b1100 + 0o50) + chr(0b110000), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(111) + chr(53) + '\060', 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'@'), chr(1433 - 1333) + '\x65' + chr(99) + '\157' + chr(100) + chr(1027 - 926))(chr(0b1110101) + '\x74' + '\146' + chr(0b101101) + chr(815 - 759)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Pchy2tZfVp78(AIvJRzLdDfgF, OeWW0F1dBPRQ, la0jAn6F0a8S, jAT42bk66WvZ, OzTCPDyKAiS7=None, _GyOifGFZyk1=xafqLlk3kkUe(SXOLrMavuUCe(b'\x1c\xf6\xaa\x08'), chr(0b1100100) + chr(0b100111 + 0o76) + chr(6446 - 6347) + chr(0b1101111) + chr(100) + chr(0b1001001 + 0o34))('\165' + chr(0b1101101 + 0o7) + chr(4492 - 4390) + '\x2d' + chr(0b100110 + 0o22)), ag0mwEgWzjYv=0.0):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x18\xf2\xb4\x14\xba\xc2\xe7\x9e\xd11H\xe6\xc82'), chr(100) + chr(0b1100101) + chr(0b11110 + 0o105) + chr(0b1010000 + 0o37) + '\x64' + '\x65')('\x75' + '\x74' + chr(0b1100110) + chr(0b101101) + chr(0b111000)))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'/\xc6\x922\x84\xf2\xce\xae\xdd\x07'), chr(0b1100100) + chr(9753 - 9652) + chr(0b1100011) + chr(111) + chr(1270 - 1170) + chr(101))('\165' + chr(0b1110100) + chr(0b111001 + 0o55) + '\x2d' + chr(0b101110 + 0o12)))):
OeWW0F1dBPRQ = UPhJ6DlDf_h1(xafqLlk3kkUe(SXOLrMavuUCe(b'\r\xfc\xa8\x0b\x84\xc2\xe7\x94\xed)'), chr(7142 - 7042) + chr(0b110111 + 0o56) + chr(0b1100011) + chr(502 - 391) + chr(0b1 + 0o143) + chr(101))('\x75' + chr(0b0 + 0o164) + chr(6619 - 6517) + '\055' + '\x38'), OeWW0F1dBPRQ, mid_channels=la0jAn6F0a8S, dilations=OzTCPDyKAiS7, activation=_GyOifGFZyk1, dropout=ag0mwEgWzjYv)
OeWW0F1dBPRQ = m1sWr00SVpVY(xafqLlk3kkUe(SXOLrMavuUCe(b'\x14\xf6\xb4\x12\xa8'), chr(100) + '\145' + chr(0b1001010 + 0o31) + chr(0b1000010 + 0o55) + chr(8473 - 8373) + '\145')('\x75' + '\x74' + chr(102) + chr(0b100001 + 0o14) + chr(414 - 358)), OeWW0F1dBPRQ, apply_actnorm=ehT0Px3KOsy9(chr(0b10101 + 0o33) + '\x6f' + '\060', ord("\x08")), conv_init=xafqLlk3kkUe(SXOLrMavuUCe(b'\x14\xf6\xb4\x12\xa8'), '\x64' + chr(0b1000010 + 0o43) + '\x63' + '\x6f' + chr(0b1100100) + chr(0b100010 + 0o103))(chr(11071 - 10954) + chr(116) + '\146' + chr(45) + '\x38'), output_channels=jAT42bk66WvZ, dilations=OzTCPDyKAiS7)
return OeWW0F1dBPRQ
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
additive_coupling
|
def additive_coupling(name, x, mid_channels=512, reverse=False,
activation="relu", dropout=0.0):
"""Reversible additive coupling layer.
Args:
name: variable scope.
x: 4-D Tensor, shape=(NHWC).
mid_channels: number of channels in the coupling layer.
reverse: Forward or reverse operation.
activation: "relu" or "gatu"
dropout: default, 0.0
Returns:
output: 4-D Tensor, shape=(NHWC)
objective: 0.0
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
output_channels = common_layers.shape_list(x)[-1] // 2
x1, x2 = tf.split(x, num_or_size_splits=2, axis=-1)
z1 = x1
shift = conv_stack("nn", x1, mid_channels, output_channels=output_channels,
activation=activation, dropout=dropout)
if not reverse:
z2 = x2 + shift
else:
z2 = x2 - shift
return tf.concat([z1, z2], axis=3), 0.0
|
python
|
def additive_coupling(name, x, mid_channels=512, reverse=False,
activation="relu", dropout=0.0):
"""Reversible additive coupling layer.
Args:
name: variable scope.
x: 4-D Tensor, shape=(NHWC).
mid_channels: number of channels in the coupling layer.
reverse: Forward or reverse operation.
activation: "relu" or "gatu"
dropout: default, 0.0
Returns:
output: 4-D Tensor, shape=(NHWC)
objective: 0.0
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
output_channels = common_layers.shape_list(x)[-1] // 2
x1, x2 = tf.split(x, num_or_size_splits=2, axis=-1)
z1 = x1
shift = conv_stack("nn", x1, mid_channels, output_channels=output_channels,
activation=activation, dropout=dropout)
if not reverse:
z2 = x2 + shift
else:
z2 = x2 - shift
return tf.concat([z1, z2], axis=3), 0.0
|
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] |
Reversible additive coupling layer.
Args:
name: variable scope.
x: 4-D Tensor, shape=(NHWC).
mid_channels: number of channels in the coupling layer.
reverse: Forward or reverse operation.
activation: "relu" or "gatu"
dropout: default, 0.0
Returns:
output: 4-D Tensor, shape=(NHWC)
objective: 0.0
|
[
"Reversible",
"additive",
"coupling",
"layer",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L669-L696
|
train
|
Reversible additive coupling layer.
|
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(2408 - 2297) + '\x34' + chr(48), 21106 - 21098), ehT0Px3KOsy9('\x30' + chr(0b11011 + 0o124) + chr(185 - 131) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\060' + chr(11644 - 11533) + chr(0b0 + 0o61) + chr(0b110001) + '\x36', 0b1000), ehT0Px3KOsy9(chr(48) + chr(2586 - 2475) + '\063' + '\062', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + chr(367 - 319) + chr(0b1011 + 0o53), 0b1000), ehT0Px3KOsy9(chr(1107 - 1059) + chr(0b100011 + 0o114) + chr(0b110001) + '\x36' + chr(0b10110 + 0o37), 58228 - 58220), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + chr(2458 - 2408) + '\061', 48821 - 48813), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1101111) + chr(51) + chr(0b10101 + 0o37) + chr(427 - 374), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(3283 - 3172) + chr(0b10111 + 0o32) + chr(0b110001) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b101 + 0o53) + '\x6f' + '\x33' + chr(53) + '\x35', 0b1000), ehT0Px3KOsy9(chr(1062 - 1014) + chr(0b1101111) + chr(0b110011) + chr(0b110110) + chr(0b10101 + 0o34), 430 - 422), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x35', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110101) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110110) + chr(54), 30103 - 30095), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110011) + chr(53) + '\061', 38151 - 38143), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + '\x31' + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(1482 - 1434) + chr(0b1101111) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(9592 - 9481) + '\x33' + '\066' + chr(1300 - 1249), 37168 - 37160), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b1101111) + '\x31' + '\067' + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(106 - 58) + chr(5330 - 5219) + chr(0b100010 + 0o17) + chr(0b1011 + 0o46) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(601 - 552) + chr(1294 - 1245) + chr(93 - 39), 8), ehT0Px3KOsy9(chr(461 - 413) + '\157' + chr(588 - 536) + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10101 + 0o36) + '\063' + chr(2361 - 2307), 52282 - 52274), ehT0Px3KOsy9(chr(48) + chr(1469 - 1358) + chr(0b100110 + 0o13) + chr(605 - 556) + chr(0b11110 + 0o22), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b101110 + 0o5) + '\x35' + '\x32', 65384 - 65376), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(0b11001 + 0o30) + chr(0b110100), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(844 - 793) + chr(0b110011) + '\x30', 56961 - 56953), ehT0Px3KOsy9(chr(2239 - 2191) + chr(2737 - 2626) + chr(0b10011 + 0o37) + chr(0b110110) + '\x31', 44712 - 44704), ehT0Px3KOsy9('\060' + chr(4384 - 4273) + '\x33' + chr(1804 - 1754) + '\x31', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1001101 + 0o42) + chr(51) + chr(1650 - 1599) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b1011010 + 0o25) + '\x35' + chr(0b101101 + 0o11), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(663 - 611), 0b1000), ehT0Px3KOsy9('\060' + chr(0b100 + 0o153) + chr(217 - 168) + chr(0b100011 + 0o16) + chr(559 - 506), 0b1000), ehT0Px3KOsy9(chr(1005 - 957) + '\x6f' + chr(2429 - 2379) + '\060' + chr(0b110001), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + '\x31' + '\066', 0o10), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\157' + chr(0b11100 + 0o26) + '\062' + '\x36', 0o10), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b1010000 + 0o37) + chr(0b110011) + chr(0b10101 + 0o41) + chr(0b11111 + 0o24), 8), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(3520 - 3409) + chr(1288 - 1239) + chr(53) + chr(1653 - 1602), ord("\x08")), ehT0Px3KOsy9(chr(0b10011 + 0o35) + '\157' + '\063' + '\x35' + chr(53), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + chr(49) + chr(0b110100), 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + '\x6f' + chr(2074 - 2021) + '\060', 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x0e'), chr(100) + chr(0b10011 + 0o122) + '\x63' + chr(0b101000 + 0o107) + '\x64' + chr(0b11110 + 0o107))(chr(117) + '\164' + '\x66' + chr(0b101101) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def xe0WebfOYa8v(AIvJRzLdDfgF, OeWW0F1dBPRQ, la0jAn6F0a8S=ehT0Px3KOsy9('\x30' + chr(0b1010110 + 0o31) + chr(0b110001) + '\060' + '\060' + '\060', ord("\x08")), jPHyoIWAxyI_=ehT0Px3KOsy9(chr(0b110000) + chr(0b1000010 + 0o55) + '\060', ord("\x08")), _GyOifGFZyk1=xafqLlk3kkUe(SXOLrMavuUCe(b'RW"o'), chr(100) + chr(6700 - 6599) + '\x63' + chr(0b0 + 0o157) + '\x64' + '\x65')('\165' + chr(0b1010111 + 0o35) + chr(0b11011 + 0o113) + chr(0b101101) + '\070'), ag0mwEgWzjYv=0.0):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'VS<s\xe7\x17\xfd\x80\x17\x9e\x92jXS'), chr(4538 - 4438) + chr(410 - 309) + chr(0b1011110 + 0o5) + chr(0b1101111) + chr(9845 - 9745) + '\x65')(chr(0b1110101) + '\164' + chr(102) + chr(420 - 375) + chr(0b111000 + 0o0)))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b"ag\x1aU\xd9'\xd4\xb0\x1b\xa8"), chr(0b1100100) + chr(0b1100101) + '\143' + chr(0b1101111) + '\144' + '\145')(chr(0b1110101) + '\x74' + chr(102) + '\x2d' + chr(0b100111 + 0o21)))):
jAT42bk66WvZ = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)[-ehT0Px3KOsy9(chr(1800 - 1752) + chr(0b1011000 + 0o27) + chr(0b11110 + 0o23), 0o10)] // ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50), 34493 - 34485)
(pci1T9SDshKa, OVXzvB9BcGF_) = IDJ2eXGCBCDu.split(OeWW0F1dBPRQ, num_or_size_splits=ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(709 - 659), 8), axis=-ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061', 8))
LzR_MOcfgsxc = pci1T9SDshKa
LnbELFj1hfyx = Pchy2tZfVp78(xafqLlk3kkUe(SXOLrMavuUCe(b'N\\'), chr(0b1100100) + chr(6346 - 6245) + '\143' + chr(2397 - 2286) + chr(1264 - 1164) + chr(0b1100101))('\165' + chr(12748 - 12632) + chr(0b1010110 + 0o20) + chr(0b11111 + 0o16) + chr(0b111000)), pci1T9SDshKa, la0jAn6F0a8S, output_channels=jAT42bk66WvZ, activation=_GyOifGFZyk1, dropout=ag0mwEgWzjYv)
if not jPHyoIWAxyI_:
lDCWld3fRBzu = OVXzvB9BcGF_ + LnbELFj1hfyx
else:
lDCWld3fRBzu = OVXzvB9BcGF_ - LnbELFj1hfyx
return (xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'C] y\xe7\x01'), chr(8298 - 8198) + '\x65' + chr(1674 - 1575) + '\157' + chr(100) + chr(101))(chr(0b111101 + 0o70) + chr(10851 - 10735) + chr(102) + '\x2d' + chr(584 - 528)))([LzR_MOcfgsxc, lDCWld3fRBzu], axis=ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33', 8)), 0.0)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
affine_coupling
|
def affine_coupling(name, x, mid_channels=512, activation="relu",
reverse=False, dropout=0.0):
"""Reversible affine coupling layer.
Args:
name: variable scope.
x: 4-D Tensor.
mid_channels: number of channels in the coupling layer.
activation: Can be either "relu" or "gatu".
reverse: Forward or reverse operation.
dropout: default, 0.0
Returns:
output: x shifted and scaled by an affine transformation.
objective: log-determinant of the jacobian
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
x_shape = common_layers.shape_list(x)
x1, x2 = tf.split(x, num_or_size_splits=2, axis=-1)
# scale, shift = NN(x1)
# If reverse:
# z2 = scale * (x2 + shift)
# Else:
# z2 = (x2 / scale) - shift
z1 = x1
log_scale_and_shift = conv_stack(
"nn", x1, mid_channels, x_shape[-1], activation=activation,
dropout=dropout)
shift = log_scale_and_shift[:, :, :, 0::2]
scale = tf.nn.sigmoid(log_scale_and_shift[:, :, :, 1::2] + 2.0)
if not reverse:
z2 = (x2 + shift) * scale
else:
z2 = x2 / scale - shift
objective = tf.reduce_sum(tf.log(scale), axis=[1, 2, 3])
if reverse:
objective *= -1
return tf.concat([z1, z2], axis=3), objective
|
python
|
def affine_coupling(name, x, mid_channels=512, activation="relu",
reverse=False, dropout=0.0):
"""Reversible affine coupling layer.
Args:
name: variable scope.
x: 4-D Tensor.
mid_channels: number of channels in the coupling layer.
activation: Can be either "relu" or "gatu".
reverse: Forward or reverse operation.
dropout: default, 0.0
Returns:
output: x shifted and scaled by an affine transformation.
objective: log-determinant of the jacobian
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
x_shape = common_layers.shape_list(x)
x1, x2 = tf.split(x, num_or_size_splits=2, axis=-1)
# scale, shift = NN(x1)
# If reverse:
# z2 = scale * (x2 + shift)
# Else:
# z2 = (x2 / scale) - shift
z1 = x1
log_scale_and_shift = conv_stack(
"nn", x1, mid_channels, x_shape[-1], activation=activation,
dropout=dropout)
shift = log_scale_and_shift[:, :, :, 0::2]
scale = tf.nn.sigmoid(log_scale_and_shift[:, :, :, 1::2] + 2.0)
if not reverse:
z2 = (x2 + shift) * scale
else:
z2 = x2 / scale - shift
objective = tf.reduce_sum(tf.log(scale), axis=[1, 2, 3])
if reverse:
objective *= -1
return tf.concat([z1, z2], axis=3), objective
|
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] |
Reversible affine coupling layer.
Args:
name: variable scope.
x: 4-D Tensor.
mid_channels: number of channels in the coupling layer.
activation: Can be either "relu" or "gatu".
reverse: Forward or reverse operation.
dropout: default, 0.0
Returns:
output: x shifted and scaled by an affine transformation.
objective: log-determinant of the jacobian
|
[
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L700-L738
|
train
|
Reversible affine coupling layer.
|
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(11733 - 11622) + chr(0b110001) + '\062' + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b101010 + 0o6) + '\x6f' + chr(0b110011) + '\x36' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(54) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100 + 0o143) + '\x33' + chr(0b110001 + 0o4) + chr(0b11010 + 0o35), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(3446 - 3335) + '\067' + chr(0b10001 + 0o42), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + '\067' + '\x30', 0o10), ehT0Px3KOsy9(chr(48) + chr(4252 - 4141) + chr(50) + chr(52) + '\x37', 53725 - 53717), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + chr(0b110100) + chr(0b11011 + 0o31), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49) + chr(1088 - 1035) + chr(53), 0o10), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\x6f' + '\061' + chr(450 - 397) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(3221 - 3110) + chr(0b110010) + '\x30' + chr(53), 0b1000), ehT0Px3KOsy9(chr(2229 - 2181) + chr(2779 - 2668) + chr(0b101011 + 0o10) + chr(0b1101 + 0o47) + chr(48), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(55) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1100101 + 0o12) + chr(735 - 684) + '\x32' + chr(0b11001 + 0o27), ord("\x08")), ehT0Px3KOsy9(chr(1688 - 1640) + chr(111) + chr(0b101011 + 0o7) + chr(48) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(195 - 147) + '\157' + chr(0b100110 + 0o20) + chr(49), 55939 - 55931), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1 + 0o62) + chr(0b110101) + '\x34', 26096 - 26088), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110110) + chr(0b110001 + 0o5), 0o10), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(1208 - 1097) + chr(0b10001 + 0o40) + chr(0b110001) + chr(0b11111 + 0o26), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b100100 + 0o113) + '\x32' + chr(0b11001 + 0o32) + chr(0b11110 + 0o27), 57156 - 57148), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\157' + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(12303 - 12192) + chr(0b101100 + 0o6) + '\x36' + chr(0b110101), 59435 - 59427), ehT0Px3KOsy9('\x30' + chr(0b10 + 0o155) + '\062' + chr(0b110001) + '\x37', 0o10), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(111) + '\063' + chr(0b110000) + '\x34', 58839 - 58831), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(0b1101111) + '\063' + '\060' + chr(53), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(94 - 45) + chr(51) + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b11 + 0o154) + '\063' + chr(48) + chr(1593 - 1539), 34485 - 34477), ehT0Px3KOsy9(chr(2208 - 2160) + chr(3648 - 3537) + chr(1697 - 1647) + chr(50), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(0b100001 + 0o21) + chr(484 - 430), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1933 - 1883) + chr(0b1100 + 0o51) + chr(634 - 583), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(0b110010), 15688 - 15680), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\157' + chr(0b110 + 0o54) + chr(0b110101) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(1792 - 1744) + chr(0b1101111) + '\x31' + chr(0b110000 + 0o0) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(111) + '\x31' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(227 - 179) + '\x6f' + '\064' + chr(2512 - 2459), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(51) + chr(0b101111 + 0o3) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b1011 + 0o51) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100000 + 0o23) + chr(0b110101) + '\x37', 8), ehT0Px3KOsy9(chr(48) + chr(9594 - 9483) + '\x33' + chr(1223 - 1173), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(49) + chr(51), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(3792 - 3681) + '\x35' + chr(519 - 471), 35990 - 35982)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'~'), chr(100) + chr(0b111100 + 0o51) + chr(598 - 499) + chr(0b1101111) + '\x64' + chr(0b10011 + 0o122))(chr(117) + chr(4900 - 4784) + '\x66' + '\x2d' + chr(237 - 181)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Ueg0Y6WC7VSG(AIvJRzLdDfgF, OeWW0F1dBPRQ, la0jAn6F0a8S=ehT0Px3KOsy9('\060' + '\x6f' + '\061' + chr(0b101100 + 0o4) + chr(48) + chr(340 - 292), 0o10), _GyOifGFZyk1=xafqLlk3kkUe(SXOLrMavuUCe(b'"\x92_\x9a'), chr(2298 - 2198) + '\145' + '\143' + chr(111) + '\144' + chr(0b1100101))(chr(0b1010011 + 0o42) + chr(0b1110100) + chr(0b111 + 0o137) + chr(1475 - 1430) + '\070'), jPHyoIWAxyI_=ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(3345 - 3234) + chr(1587 - 1539), ord("\x08")), ag0mwEgWzjYv=0.0):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'&\x96A\x86Z\x1a\xcb\x012\x1b\xe6\x8fJ\xb5'), chr(8040 - 7940) + chr(5333 - 5232) + chr(99) + chr(3741 - 3630) + '\x64' + chr(2389 - 2288))(chr(117) + chr(0b1110100) + '\146' + chr(0b11010 + 0o23) + chr(0b100101 + 0o23)))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x11\xa2g\xa0d*\xe21>-'), chr(0b111 + 0o135) + chr(0b101100 + 0o71) + chr(99) + '\157' + chr(0b1100100) + chr(0b1011111 + 0o6))('\165' + chr(116) + chr(5844 - 5742) + chr(45) + chr(56)))):
QQEXXbdZyz6m = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
(pci1T9SDshKa, OVXzvB9BcGF_) = IDJ2eXGCBCDu.split(OeWW0F1dBPRQ, num_or_size_splits=ehT0Px3KOsy9('\x30' + chr(7786 - 7675) + chr(0b100111 + 0o13), 0o10), axis=-ehT0Px3KOsy9(chr(0b110000) + chr(0b111 + 0o150) + chr(49), ord("\x08")))
LzR_MOcfgsxc = pci1T9SDshKa
j7joEu2e8awj = Pchy2tZfVp78(xafqLlk3kkUe(SXOLrMavuUCe(b'>\x99'), chr(7356 - 7256) + '\145' + chr(0b1010110 + 0o15) + '\157' + chr(0b1100100) + '\x65')(chr(12278 - 12161) + chr(0b1110100) + '\x66' + chr(134 - 89) + chr(0b111000)), pci1T9SDshKa, la0jAn6F0a8S, QQEXXbdZyz6m[-ehT0Px3KOsy9('\x30' + chr(0b1011001 + 0o26) + chr(0b100 + 0o55), 8)], activation=_GyOifGFZyk1, dropout=ag0mwEgWzjYv)
LnbELFj1hfyx = j7joEu2e8awj[:, :, :, ehT0Px3KOsy9(chr(0b110000) + chr(4903 - 4792) + chr(48), 8)::ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062', 8)]
xjPLimsZRgb9 = IDJ2eXGCBCDu.nn.sigmoid(j7joEu2e8awj[:, :, :, ehT0Px3KOsy9(chr(641 - 593) + '\x6f' + chr(49), 8)::ehT0Px3KOsy9('\x30' + chr(111) + chr(50), 8)] + 2.0)
if not jPHyoIWAxyI_:
lDCWld3fRBzu = (OVXzvB9BcGF_ + LnbELFj1hfyx) * xjPLimsZRgb9
else:
lDCWld3fRBzu = OVXzvB9BcGF_ / xjPLimsZRgb9 - LnbELFj1hfyx
Ky8KMSzRafTo = IDJ2eXGCBCDu.reduce_sum(IDJ2eXGCBCDu.log(xjPLimsZRgb9), axis=[ehT0Px3KOsy9(chr(0b110000) + chr(0b11 + 0o154) + '\x31', 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1611 - 1561), 8), ehT0Px3KOsy9('\x30' + '\157' + '\063', 0b1000)])
if jPHyoIWAxyI_:
Ky8KMSzRafTo *= -ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49), 8)
return (xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'3\x98]\x8cZ\x0c'), '\144' + '\145' + '\143' + chr(4179 - 4068) + chr(0b1100100) + '\x65')(chr(6649 - 6532) + chr(116) + chr(0b1100110) + '\x2d' + chr(56)))([LzR_MOcfgsxc, lDCWld3fRBzu], axis=ehT0Px3KOsy9('\060' + '\x6f' + '\x33', 8)), Ky8KMSzRafTo)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
squeeze
|
def squeeze(name, x, factor=2, reverse=True):
"""Block-wise spatial squeezing of x to increase the number of channels.
Args:
name: Used for variable scoping.
x: 4-D Tensor of shape (batch_size X H X W X C)
factor: Factor by which the spatial dimensions should be squeezed.
reverse: Squueze or unsqueeze operation.
Returns:
x: 4-D Tensor of shape (batch_size X (H//factor) X (W//factor) X
(cXfactor^2). If reverse is True, then it is factor = (1 / factor)
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
shape = common_layers.shape_list(x)
if factor == 1:
return x
height = int(shape[1])
width = int(shape[2])
n_channels = int(shape[3])
if not reverse:
assert height % factor == 0 and width % factor == 0
x = tf.reshape(x, [-1, height//factor, factor,
width//factor, factor, n_channels])
x = tf.transpose(x, [0, 1, 3, 5, 2, 4])
x = tf.reshape(x, [-1, height//factor, width //
factor, n_channels*factor*factor])
else:
x = tf.reshape(
x, (-1, height, width, int(n_channels/factor**2), factor, factor))
x = tf.transpose(x, [0, 1, 4, 2, 5, 3])
x = tf.reshape(x, (-1, int(height*factor),
int(width*factor), int(n_channels/factor**2)))
return x
|
python
|
def squeeze(name, x, factor=2, reverse=True):
"""Block-wise spatial squeezing of x to increase the number of channels.
Args:
name: Used for variable scoping.
x: 4-D Tensor of shape (batch_size X H X W X C)
factor: Factor by which the spatial dimensions should be squeezed.
reverse: Squueze or unsqueeze operation.
Returns:
x: 4-D Tensor of shape (batch_size X (H//factor) X (W//factor) X
(cXfactor^2). If reverse is True, then it is factor = (1 / factor)
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
shape = common_layers.shape_list(x)
if factor == 1:
return x
height = int(shape[1])
width = int(shape[2])
n_channels = int(shape[3])
if not reverse:
assert height % factor == 0 and width % factor == 0
x = tf.reshape(x, [-1, height//factor, factor,
width//factor, factor, n_channels])
x = tf.transpose(x, [0, 1, 3, 5, 2, 4])
x = tf.reshape(x, [-1, height//factor, width //
factor, n_channels*factor*factor])
else:
x = tf.reshape(
x, (-1, height, width, int(n_channels/factor**2), factor, factor))
x = tf.transpose(x, [0, 1, 4, 2, 5, 3])
x = tf.reshape(x, (-1, int(height*factor),
int(width*factor), int(n_channels/factor**2)))
return x
|
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"int",
"(",
"width",
"*",
"factor",
")",
",",
"int",
"(",
"n_channels",
"/",
"factor",
"**",
"2",
")",
")",
")",
"return",
"x"
] |
Block-wise spatial squeezing of x to increase the number of channels.
Args:
name: Used for variable scoping.
x: 4-D Tensor of shape (batch_size X H X W X C)
factor: Factor by which the spatial dimensions should be squeezed.
reverse: Squueze or unsqueeze operation.
Returns:
x: 4-D Tensor of shape (batch_size X (H//factor) X (W//factor) X
(cXfactor^2). If reverse is True, then it is factor = (1 / factor)
|
[
"Block",
"-",
"wise",
"spatial",
"squeezing",
"of",
"x",
"to",
"increase",
"the",
"number",
"of",
"channels",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L742-L776
|
train
|
Block - wise spatial squeezing of x to increase the number of channels.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + '\157' + chr(695 - 640) + chr(961 - 912), 62553 - 62545), ehT0Px3KOsy9(chr(0b110000) + chr(0b111011 + 0o64) + chr(622 - 572) + '\x35' + chr(1997 - 1949), 30738 - 30730), ehT0Px3KOsy9(chr(1724 - 1676) + chr(0b111100 + 0o63) + '\061' + '\064' + chr(0b1101 + 0o52), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(50) + chr(2899 - 2845) + chr(2292 - 2243), 58928 - 58920), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + chr(1417 - 1366) + chr(1812 - 1764), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + chr(0b110001) + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b10 + 0o155) + chr(0b110001) + chr(1495 - 1447) + chr(1382 - 1327), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b101100 + 0o6) + '\067' + chr(0b101011 + 0o11), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x31' + chr(392 - 340) + '\x31', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\x31' + chr(0b101010 + 0o12) + '\x35', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1101 + 0o51) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(202 - 154) + '\x6f' + '\062' + chr(0b0 + 0o64), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + '\063' + '\060', ord("\x08")), ehT0Px3KOsy9(chr(475 - 427) + '\x6f' + chr(1531 - 1482) + '\x36' + '\067', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b110111 + 0o70) + '\061' + chr(50) + '\061', 0b1000), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\x6f' + '\063' + '\060' + chr(1121 - 1068), ord("\x08")), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b1101111) + chr(51) + chr(0b110101) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(910 - 862) + '\x6f' + chr(0b11111 + 0o22) + '\x37' + '\x35', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(2308 - 2258) + chr(50) + chr(1360 - 1312), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b100101 + 0o112) + chr(0b110010) + chr(0b110001) + chr(51), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + chr(48), 1788 - 1780), ehT0Px3KOsy9('\x30' + chr(10461 - 10350) + chr(1285 - 1230) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001 + 0o1) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(111) + '\063' + chr(0b101011 + 0o13) + chr(1388 - 1334), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101100 + 0o3) + '\x36' + '\x33', 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(0b10101 + 0o40) + chr(900 - 849), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + '\061', 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1111 + 0o44) + chr(0b100000 + 0o26) + chr(598 - 545), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b101 + 0o152) + '\x31' + '\x37' + chr(0b110001 + 0o1), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b101011 + 0o10) + chr(0b100011 + 0o24) + chr(49), 0b1000), ehT0Px3KOsy9(chr(2187 - 2139) + chr(0b1101111) + chr(0b110010) + '\x35' + chr(0b110111), 0b1000), ehT0Px3KOsy9('\060' + chr(7351 - 7240) + chr(0b110001) + '\061' + chr(0b110001 + 0o2), 51162 - 51154), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + chr(0b110011) + '\x32', 55449 - 55441), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + chr(0b10100 + 0o43) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061' + chr(50) + chr(522 - 469), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b100110 + 0o13) + '\x33' + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(964 - 916) + '\x6f' + chr(2031 - 1980) + '\x37' + chr(48), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\064' + '\x35', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x33' + chr(0b110100) + '\065', 50929 - 50921), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110100), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\157' + chr(87 - 34) + chr(0b11010 + 0o26), 6523 - 6515)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x17'), '\x64' + chr(0b100111 + 0o76) + '\x63' + '\157' + chr(100) + chr(4397 - 4296))(chr(117) + chr(1948 - 1832) + chr(1305 - 1203) + '\x2d' + chr(1843 - 1787)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def jSEJp8iu8Nw4(AIvJRzLdDfgF, OeWW0F1dBPRQ, Tx5AD3XZqDPl=ehT0Px3KOsy9('\x30' + chr(0b10000 + 0o137) + chr(50), 0b1000), jPHyoIWAxyI_=ehT0Px3KOsy9('\060' + chr(111) + chr(1087 - 1038), ord("\x08"))):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'O\xc9\x15\xd8\xb9\xaa+\xd9>\x16P{\xe8\x12'), chr(0b1000011 + 0o41) + '\x65' + '\143' + chr(7748 - 7637) + '\x64' + '\x65')(chr(117) + '\164' + chr(0b1100110) + chr(0b101101) + '\x38'))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'x\xfd3\xfe\x87\x9a\x02\xe92 '), chr(0b1001100 + 0o30) + chr(0b1100101) + chr(0b1010001 + 0o22) + chr(0b1101111) + '\144' + '\x65')(chr(0b1110101) + '\164' + chr(3230 - 3128) + chr(0b101101) + chr(56)))):
nauYfLglTpcb = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
if Tx5AD3XZqDPl == ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061', 8):
return OeWW0F1dBPRQ
ehbUULKuygfC = ehT0Px3KOsy9(nauYfLglTpcb[ehT0Px3KOsy9(chr(1657 - 1609) + chr(111) + chr(0b110001), 8)])
mPx09rBTrGXR = ehT0Px3KOsy9(nauYfLglTpcb[ehT0Px3KOsy9(chr(1750 - 1702) + chr(111) + chr(280 - 230), 8)])
Ds92BVm147dF = ehT0Px3KOsy9(nauYfLglTpcb[ehT0Px3KOsy9('\060' + chr(6208 - 6097) + chr(353 - 302), ord("\x08"))])
if not jPHyoIWAxyI_:
assert ehbUULKuygfC % Tx5AD3XZqDPl == ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110000), 1420 - 1412) and mPx09rBTrGXR % Tx5AD3XZqDPl == ehT0Px3KOsy9('\060' + chr(520 - 409) + '\060', 8)
OeWW0F1dBPRQ = IDJ2eXGCBCDu.reshape(OeWW0F1dBPRQ, [-ehT0Px3KOsy9(chr(1703 - 1655) + chr(0b10100 + 0o133) + chr(0b110001), 8), ehbUULKuygfC // Tx5AD3XZqDPl, Tx5AD3XZqDPl, mPx09rBTrGXR // Tx5AD3XZqDPl, Tx5AD3XZqDPl, Ds92BVm147dF])
OeWW0F1dBPRQ = IDJ2eXGCBCDu.transpose(OeWW0F1dBPRQ, [ehT0Px3KOsy9('\060' + '\x6f' + '\x30', 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b111000 + 0o67) + chr(510 - 459), 8), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b1101111) + chr(0b110101), 9811 - 9803), ehT0Px3KOsy9('\x30' + '\157' + chr(50), 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110100), 8)])
OeWW0F1dBPRQ = IDJ2eXGCBCDu.reshape(OeWW0F1dBPRQ, [-ehT0Px3KOsy9(chr(1462 - 1414) + chr(8425 - 8314) + '\061', 8), ehbUULKuygfC // Tx5AD3XZqDPl, mPx09rBTrGXR // Tx5AD3XZqDPl, Ds92BVm147dF * Tx5AD3XZqDPl * Tx5AD3XZqDPl])
else:
OeWW0F1dBPRQ = IDJ2eXGCBCDu.reshape(OeWW0F1dBPRQ, (-ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1100011 + 0o14) + chr(1812 - 1763), 8), ehbUULKuygfC, mPx09rBTrGXR, ehT0Px3KOsy9(Ds92BVm147dF / Tx5AD3XZqDPl ** ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110010 + 0o0), 8)), Tx5AD3XZqDPl, Tx5AD3XZqDPl))
OeWW0F1dBPRQ = IDJ2eXGCBCDu.transpose(OeWW0F1dBPRQ, [ehT0Px3KOsy9(chr(484 - 436) + chr(0b11001 + 0o126) + chr(0b110000), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b1110 + 0o46), 8), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b11110 + 0o121) + chr(50), 8), ehT0Px3KOsy9(chr(0b10001 + 0o37) + '\x6f' + chr(0b110 + 0o57), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51), 8)])
OeWW0F1dBPRQ = IDJ2eXGCBCDu.reshape(OeWW0F1dBPRQ, (-ehT0Px3KOsy9(chr(2197 - 2149) + chr(0b10111 + 0o130) + chr(49), 8), ehT0Px3KOsy9(ehbUULKuygfC * Tx5AD3XZqDPl), ehT0Px3KOsy9(mPx09rBTrGXR * Tx5AD3XZqDPl), ehT0Px3KOsy9(Ds92BVm147dF / Tx5AD3XZqDPl ** ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\157' + '\062', 8))))
return OeWW0F1dBPRQ
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
get_dilation_rates
|
def get_dilation_rates(hparams, width):
"""Get a list of valid dilation rates.
Args:
hparams: HParams.
width: spatial dimension. Ensures that the effective filter size is
not larger than the spatial dimension.
Returns:
allowed_dilations: A list of dilation rates.
"""
# dil_rate=1 means no dilation.
allowed_dilations = [[1]*5]
apply_dilations = hparams.get("latent_apply_dilations", False)
dilation_rates = hparams.get("latent_dilation_rates", [1, 3])
if apply_dilations:
for rate in dilation_rates:
# k + (k - 1) * rate but k is harcoded to be 3 everywhere.
filter_size = 3 + 2 * rate
if filter_size <= width:
curr_dilation = [1, 1, rate+1, rate+1, 1]
allowed_dilations.append(curr_dilation)
return allowed_dilations
|
python
|
def get_dilation_rates(hparams, width):
"""Get a list of valid dilation rates.
Args:
hparams: HParams.
width: spatial dimension. Ensures that the effective filter size is
not larger than the spatial dimension.
Returns:
allowed_dilations: A list of dilation rates.
"""
# dil_rate=1 means no dilation.
allowed_dilations = [[1]*5]
apply_dilations = hparams.get("latent_apply_dilations", False)
dilation_rates = hparams.get("latent_dilation_rates", [1, 3])
if apply_dilations:
for rate in dilation_rates:
# k + (k - 1) * rate but k is harcoded to be 3 everywhere.
filter_size = 3 + 2 * rate
if filter_size <= width:
curr_dilation = [1, 1, rate+1, rate+1, 1]
allowed_dilations.append(curr_dilation)
return allowed_dilations
|
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Get a list of valid dilation rates.
Args:
hparams: HParams.
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Returns:
allowed_dilations: A list of dilation rates.
|
[
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272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L779-L800
|
train
|
Get a list of valid dilation rates.
|
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) + '\063' + chr(1403 - 1354) + '\063', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + chr(0b110101) + '\065', 50122 - 50114), ehT0Px3KOsy9('\060' + chr(0b110101 + 0o72) + chr(49) + '\x32' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b1011000 + 0o27) + '\x33' + chr(49) + '\x33', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b100000 + 0o117) + chr(0b110001) + chr(0b100110 + 0o12) + chr(50), 2724 - 2716), ehT0Px3KOsy9('\060' + '\157' + chr(0b110001) + '\060' + '\x33', 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + chr(0b110110) + chr(48), 0b1000), ehT0Px3KOsy9(chr(48) + chr(8499 - 8388) + chr(0b110110) + chr(757 - 702), 0o10), ehT0Px3KOsy9(chr(1425 - 1377) + '\157' + chr(777 - 728) + chr(0b110001) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\063' + '\x32' + chr(1855 - 1801), 23290 - 23282), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + '\066' + '\067', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(11789 - 11678) + chr(0b100100 + 0o20) + chr(0b1111 + 0o46), 0b1000), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\157' + chr(49), 16906 - 16898), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + '\063' + '\065' + chr(2132 - 2077), 0b1000), ehT0Px3KOsy9('\060' + chr(7738 - 7627) + '\062' + chr(0b110110) + chr(53), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(50) + chr(0b100110 + 0o13), 0o10), ehT0Px3KOsy9(chr(569 - 521) + chr(0b1101111) + '\x32' + '\x31' + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\x32' + chr(373 - 319) + chr(1050 - 998), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + chr(0b110000) + '\x33', 8), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + chr(0b1111 + 0o41) + chr(0b110110), 43104 - 43096), ehT0Px3KOsy9('\060' + chr(4822 - 4711) + '\x37' + chr(566 - 515), 0o10), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(111) + '\063' + '\061' + '\061', 0o10), ehT0Px3KOsy9(chr(0b10 + 0o56) + '\x6f' + chr(0b10000 + 0o41) + chr(0b110001) + chr(55), 0o10), ehT0Px3KOsy9('\060' + chr(6014 - 5903) + chr(51) + chr(0b110011) + chr(0b100000 + 0o25), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(586 - 475) + chr(0b110011) + chr(0b101000 + 0o16) + chr(834 - 782), 56716 - 56708), ehT0Px3KOsy9(chr(2131 - 2083) + '\x6f' + chr(2062 - 2008) + chr(0b101010 + 0o10), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b11111 + 0o26) + '\x36', 0o10), ehT0Px3KOsy9(chr(1636 - 1588) + '\157' + '\063' + chr(0b100011 + 0o23) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(1919 - 1871) + chr(2731 - 2620) + chr(50) + chr(0b10001 + 0o37) + chr(52), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + chr(48) + chr(0b100011 + 0o20), 8), ehT0Px3KOsy9(chr(1294 - 1246) + chr(0b1101111) + '\061' + chr(53) + chr(0b1 + 0o64), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(54) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(760 - 712) + '\x6f' + chr(51) + '\x30' + '\064', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(0b1011 + 0o45) + chr(0b100001 + 0o22), ord("\x08")), ehT0Px3KOsy9(chr(2237 - 2189) + '\157' + chr(0b110011) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1000000 + 0o57) + chr(0b110001) + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110000 + 0o7) + chr(51 - 1), 51361 - 51353), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(2164 - 2116) + chr(55), 11453 - 11445), ehT0Px3KOsy9(chr(845 - 797) + '\157' + chr(2348 - 2299) + '\x32' + chr(52), 62010 - 62002), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(735 - 624) + chr(49) + chr(0b110010) + chr(1169 - 1120), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(0b1100001 + 0o16) + chr(1663 - 1610) + chr(0b11100 + 0o24), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xe5'), chr(0b1100100) + chr(101) + chr(0b1100011) + chr(0b100010 + 0o115) + chr(100) + chr(0b1100101))(chr(0b1110101) + chr(0b1011001 + 0o33) + chr(102) + chr(0b101101) + chr(1601 - 1545)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def x4M8KuD3N3sr(n4ljua2gi1Pr, mPx09rBTrGXR):
F2Dsgc90SORq = [[ehT0Px3KOsy9('\060' + '\x6f' + chr(1565 - 1516), 8)] * ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x35', 0b1000)]
rMns4WNWJqLe = n4ljua2gi1Pr.get(xafqLlk3kkUe(SXOLrMavuUCe(b'\xa7\x0c#\xae,7/V8\xa6\x9b\\^\x8b\xdc=\xea\xc0*\xa9U\xba'), chr(0b1100100) + chr(6326 - 6225) + chr(99) + chr(0b1001000 + 0o47) + '\144' + chr(101))(chr(117) + chr(116) + '\x66' + chr(841 - 796) + chr(0b111 + 0o61)), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(111) + chr(48), 0b1000))
TMjD3SoUY82Q = n4ljua2gi1Pr.get(xafqLlk3kkUe(SXOLrMavuUCe(b'\xa7\x0c#\xae,7/S!\xba\x96Qh\x80\xdb\x0e\xf9\xd57\xa3H'), chr(100) + '\x65' + '\143' + chr(0b1101111) + chr(100) + chr(2393 - 2292))(chr(3960 - 3843) + chr(116) + '\146' + chr(0b101101) + '\070'), [ehT0Px3KOsy9(chr(1626 - 1578) + chr(111) + '\x31', 8), ehT0Px3KOsy9(chr(0b110000) + chr(8939 - 8828) + chr(0b100011 + 0o20), 58821 - 58813)])
if rMns4WNWJqLe:
for YygZh57sDDVX in TMjD3SoUY82Q:
deybX8NJ0oEI = ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1010101 + 0o32) + chr(0b110 + 0o55), 8) + ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50), ord("\x08")) * YygZh57sDDVX
if deybX8NJ0oEI <= mPx09rBTrGXR:
N6MuVW1Woirm = [ehT0Px3KOsy9(chr(1399 - 1351) + chr(2643 - 2532) + '\x31', 8), ehT0Px3KOsy9('\x30' + chr(3446 - 3335) + '\061', 8), YygZh57sDDVX + ehT0Px3KOsy9(chr(1497 - 1449) + chr(111) + chr(1277 - 1228), 8), YygZh57sDDVX + ehT0Px3KOsy9(chr(0b100110 + 0o12) + '\157' + '\x31', 8), ehT0Px3KOsy9(chr(424 - 376) + chr(111) + chr(0b110001), 8)]
xafqLlk3kkUe(F2Dsgc90SORq, xafqLlk3kkUe(SXOLrMavuUCe(b"\xaa\x1d'\xae,'"), '\x64' + '\145' + '\x63' + chr(0b110 + 0o151) + '\144' + chr(101))(chr(0b1001111 + 0o46) + '\164' + chr(0b1100110) + chr(45) + '\x38'))(N6MuVW1Woirm)
return F2Dsgc90SORq
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
temporal_latent_to_dist
|
def temporal_latent_to_dist(name, x, hparams, output_channels=None):
"""Network that maps a time-indexed list of 3-D latents to a gaussian.
Args:
name: variable scope.
x: List of 4-D Tensors indexed by time, (NHWC)
hparams: tf.contrib.training.Hparams.
output_channels: int, Number of channels of the output gaussian mean.
Returns:
dist: tfp.distributions.Normal
"""
_, _, width, _, res_channels = common_layers.shape_list(x)
if output_channels is None:
output_channels = res_channels
dilation_rates = get_dilation_rates(hparams, width)
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
h = x
for i in range(hparams.latent_encoder_depth):
if hparams.latent_apply_dilations:
h2 = dilated_conv_stack("dil_latent_3d_res_%d" % i, h,
mid_channels=hparams.latent_encoder_width,
output_channels=res_channels,
dilation_rates=dilation_rates,
activation=hparams.latent_activation,
dropout=hparams.latent_dropout)
else:
h2 = conv_stack("latent_3d_res_%d" % i, h,
mid_channels=hparams.latent_encoder_width,
output_channels=res_channels,
activation=hparams.latent_activation,
dropout=hparams.latent_dropout)
h += h2
# take last activation that should capture all context since padding is
# on left.
h = h[:, -1, :, :, :]
h = conv("res_final", h, apply_actnorm=False, conv_init="zeros",
output_channels=2*output_channels, filter_size=[1, 1])
mean, log_scale = h[:, :, :, 0::2], h[:, :, :, 1::2]
return tfp.distributions.Normal(mean, tf.exp(log_scale))
|
python
|
def temporal_latent_to_dist(name, x, hparams, output_channels=None):
"""Network that maps a time-indexed list of 3-D latents to a gaussian.
Args:
name: variable scope.
x: List of 4-D Tensors indexed by time, (NHWC)
hparams: tf.contrib.training.Hparams.
output_channels: int, Number of channels of the output gaussian mean.
Returns:
dist: tfp.distributions.Normal
"""
_, _, width, _, res_channels = common_layers.shape_list(x)
if output_channels is None:
output_channels = res_channels
dilation_rates = get_dilation_rates(hparams, width)
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
h = x
for i in range(hparams.latent_encoder_depth):
if hparams.latent_apply_dilations:
h2 = dilated_conv_stack("dil_latent_3d_res_%d" % i, h,
mid_channels=hparams.latent_encoder_width,
output_channels=res_channels,
dilation_rates=dilation_rates,
activation=hparams.latent_activation,
dropout=hparams.latent_dropout)
else:
h2 = conv_stack("latent_3d_res_%d" % i, h,
mid_channels=hparams.latent_encoder_width,
output_channels=res_channels,
activation=hparams.latent_activation,
dropout=hparams.latent_dropout)
h += h2
# take last activation that should capture all context since padding is
# on left.
h = h[:, -1, :, :, :]
h = conv("res_final", h, apply_actnorm=False, conv_init="zeros",
output_channels=2*output_channels, filter_size=[1, 1])
mean, log_scale = h[:, :, :, 0::2], h[:, :, :, 1::2]
return tfp.distributions.Normal(mean, tf.exp(log_scale))
|
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Network that maps a time-indexed list of 3-D latents to a gaussian.
Args:
name: variable scope.
x: List of 4-D Tensors indexed by time, (NHWC)
hparams: tf.contrib.training.Hparams.
output_channels: int, Number of channels of the output gaussian mean.
Returns:
dist: tfp.distributions.Normal
|
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L804-L843
|
train
|
Network that maps a time - indexed list of 3 - D latents to a gaussian.
|
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) + '\067' + '\067', 637 - 629), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + '\x30' + '\062', 0o10), ehT0Px3KOsy9('\060' + '\157' + '\061' + chr(0b100011 + 0o24) + chr(126 - 75), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(408 - 355) + chr(53), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110000 + 0o1) + chr(0b100101 + 0o14) + chr(1522 - 1474), 0b1000), ehT0Px3KOsy9(chr(258 - 210) + chr(10606 - 10495) + chr(0b110001) + '\065' + '\067', 0o10), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b1011001 + 0o26) + chr(52) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000111 + 0o50) + chr(1275 - 1225), 0b1000), ehT0Px3KOsy9('\x30' + chr(10512 - 10401) + '\x33' + '\x31' + chr(0b110010), 519 - 511), ehT0Px3KOsy9(chr(106 - 58) + '\157' + chr(0b110001) + '\063' + chr(54), 0b1000), ehT0Px3KOsy9(chr(910 - 862) + '\x6f' + chr(50) + chr(2032 - 1979) + chr(1360 - 1307), 0b1000), ehT0Px3KOsy9('\x30' + chr(8185 - 8074) + chr(0b110001) + chr(0b110000) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(637 - 586) + chr(52), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111 + 0o0) + chr(1774 - 1723) + chr(0b11001 + 0o32) + chr(1033 - 983), 0o10), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(111) + chr(53) + chr(0b110010), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + '\062' + chr(0b110010), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b101000 + 0o12) + '\063' + chr(1435 - 1386), ord("\x08")), ehT0Px3KOsy9(chr(1462 - 1414) + chr(0b1101111) + chr(50) + chr(0b0 + 0o62) + chr(1740 - 1687), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(55) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061' + chr(1058 - 1008) + chr(0b11101 + 0o25), 7817 - 7809), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(644 - 533) + chr(0b110011) + '\x30' + chr(0b11001 + 0o33), 0b1000), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(111) + chr(53) + chr(0b1110 + 0o47), 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + '\x30' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(51) + chr(53) + chr(0b110100), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(1508 - 1456) + chr(0b110000), 58583 - 58575), ehT0Px3KOsy9('\060' + chr(5665 - 5554) + chr(0b110001) + chr(0b100000 + 0o21) + chr(51), 52825 - 52817), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(1901 - 1790) + chr(0b110011) + chr(0b1110 + 0o46) + '\063', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\061' + '\062', 30155 - 30147), ehT0Px3KOsy9(chr(2274 - 2226) + chr(10683 - 10572) + '\x37' + chr(0b1000 + 0o50), 55748 - 55740), ehT0Px3KOsy9('\060' + chr(0b1010001 + 0o36) + chr(0b110010) + '\062' + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(2125 - 2074) + '\x30' + chr(0b110111 + 0o0), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\x32' + chr(625 - 570) + '\062', 45881 - 45873), ehT0Px3KOsy9(chr(48) + chr(3041 - 2930) + chr(311 - 260) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(51) + chr(0b110110) + '\063', 36394 - 36386), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + chr(0b10 + 0o56) + chr(49), 0b1000), ehT0Px3KOsy9('\060' + chr(0b11101 + 0o122) + '\x33' + '\067' + chr(0b100101 + 0o20), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061' + chr(1666 - 1614) + '\x30', 0o10), ehT0Px3KOsy9('\060' + chr(10940 - 10829) + '\x33' + '\066' + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(111) + '\066' + chr(0b11011 + 0o32), 43931 - 43923), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + chr(0b110011) + '\061', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(165 - 117) + chr(0b1101111) + '\065' + '\x30', 37392 - 37384)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x11'), '\x64' + '\145' + chr(4045 - 3946) + '\157' + '\144' + '\x65')(chr(117) + chr(116) + '\146' + chr(0b101101) + chr(2055 - 1999)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def J0k8avRQFxAn(AIvJRzLdDfgF, OeWW0F1dBPRQ, n4ljua2gi1Pr, jAT42bk66WvZ=None):
(VNGQdHSFPrso, VNGQdHSFPrso, mPx09rBTrGXR, VNGQdHSFPrso, X6QYpQRfzJdZ) = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
if jAT42bk66WvZ is None:
jAT42bk66WvZ = X6QYpQRfzJdZ
TMjD3SoUY82Q = x4M8KuD3N3sr(n4ljua2gi1Pr, mPx09rBTrGXR)
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'I\xe3\tD)\rOg\x95-\xce,l\xbf'), chr(100) + chr(0b1100101) + chr(99) + chr(0b1101111) + '\x64' + '\x65')(chr(3208 - 3091) + chr(0b1110100) + '\146' + chr(0b11101 + 0o20) + chr(0b11 + 0o65)))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'~\xd7/b\x17=fW\x99\x1b'), '\144' + chr(0b1010110 + 0o17) + chr(0b11000 + 0o113) + '\157' + '\144' + '\x65')('\x75' + chr(116) + chr(0b111110 + 0o50) + '\055' + chr(0b111000)))):
sz4HVsFVF8nL = OeWW0F1dBPRQ
for WVxHKyX45z_L in vQr8gNKaIaWE(xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b"S\xe3\x0fH&\x1b|g\xa4=\xc2'y\xa8u\xb6\xfc\xe5M:"), chr(0b1011011 + 0o11) + '\145' + chr(0b1100011) + '\x6f' + '\144' + chr(0b1011010 + 0o13))('\x75' + chr(7577 - 7461) + chr(102) + chr(0b100100 + 0o11) + '\070'))):
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'S\xe3\x0fH&\x1b|c\xba.\xc1:C\xbeC\xbe\xf8\xe1P=\xaa^'), chr(605 - 505) + '\145' + '\x63' + chr(0b111100 + 0o63) + chr(0b1100100 + 0o0) + '\x65')(chr(0b100011 + 0o122) + chr(116) + '\146' + '\055' + chr(0b10010 + 0o46))):
GGNH7JNUgs4j = KovTHTCc2DW9(xafqLlk3kkUe(SXOLrMavuUCe(b'[\xeb\x17r$\x0eWg\xa4*\xf2px\x85X\xb7\xea\xca\x1c6'), chr(5331 - 5231) + '\145' + '\x63' + chr(0b111 + 0o150) + '\144' + chr(0b1100101))(chr(0b1100110 + 0o17) + '\x74' + chr(102) + chr(0b101101) + '\x38') % WVxHKyX45z_L, sz4HVsFVF8nL, mid_channels=n4ljua2gi1Pr.latent_encoder_width, output_channels=X6QYpQRfzJdZ, dilation_rates=TMjD3SoUY82Q, activation=n4ljua2gi1Pr.latent_activation, dropout=n4ljua2gi1Pr.latent_dropout)
else:
GGNH7JNUgs4j = Pchy2tZfVp78(xafqLlk3kkUe(SXOLrMavuUCe(b'S\xe3\x0fH&\x1b|1\xae\x01\xdf&o\x85\x0f\xb6'), chr(2747 - 2647) + '\145' + chr(99) + chr(0b1101111) + chr(0b100000 + 0o104) + chr(0b11110 + 0o107))('\165' + chr(0b1110100) + chr(3697 - 3595) + chr(0b100 + 0o51) + '\x38') % WVxHKyX45z_L, sz4HVsFVF8nL, mid_channels=n4ljua2gi1Pr.latent_encoder_width, output_channels=X6QYpQRfzJdZ, activation=n4ljua2gi1Pr.latent_activation, dropout=n4ljua2gi1Pr.latent_dropout)
sz4HVsFVF8nL += GGNH7JNUgs4j
sz4HVsFVF8nL = sz4HVsFVF8nL[:, -ehT0Px3KOsy9(chr(652 - 604) + chr(0b1101111) + chr(0b110001), 0o10), :, :, :]
sz4HVsFVF8nL = m1sWr00SVpVY(xafqLlk3kkUe(SXOLrMavuUCe(b'M\xe7\x08r.\x06Mc\xa6'), '\x64' + chr(774 - 673) + '\x63' + chr(0b11001 + 0o126) + chr(100) + chr(5961 - 5860))(chr(0b1110101) + chr(9761 - 9645) + '\146' + chr(0b101101) + '\x38'), sz4HVsFVF8nL, apply_actnorm=ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110000), 63219 - 63211), conv_init=xafqLlk3kkUe(SXOLrMavuUCe(b'E\xe7\tB;'), '\x64' + chr(101) + '\143' + '\157' + chr(0b1100100) + '\145')(chr(9931 - 9814) + chr(5954 - 5838) + chr(4925 - 4823) + chr(1389 - 1344) + '\070'), output_channels=ehT0Px3KOsy9(chr(1070 - 1022) + chr(0b10011 + 0o134) + chr(50), 8) * jAT42bk66WvZ, filter_size=[ehT0Px3KOsy9(chr(48) + chr(0b1100110 + 0o11) + '\x31', 8), ehT0Px3KOsy9(chr(1024 - 976) + chr(10686 - 10575) + '\x31', 8)])
(aJhItC_Vawlw, emKULJskFaJ8) = (sz4HVsFVF8nL[:, :, :, ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\060', 8)::ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50), 8)], sz4HVsFVF8nL[:, :, :, ehT0Px3KOsy9(chr(48) + chr(4909 - 4798) + chr(235 - 186), 8)::ehT0Px3KOsy9('\x30' + chr(0b111101 + 0o62) + chr(0b111 + 0o53), 8)])
return xafqLlk3kkUe(Ys555qziAbad.distributions, xafqLlk3kkUe(SXOLrMavuUCe(b'q\xed\t@)\x03'), chr(0b1100100) + chr(0b1011 + 0o132) + '\x63' + chr(111) + chr(0b1100100) + chr(0b1100101))('\x75' + chr(459 - 343) + '\146' + '\x2d' + chr(56)))(aJhItC_Vawlw, xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'Z\xfa\x0b'), '\x64' + chr(0b1010101 + 0o20) + '\143' + chr(0b1101111) + chr(0b1100100) + chr(4662 - 4561))(chr(117) + '\x74' + chr(0b1011101 + 0o11) + chr(45) + chr(56)))(emKULJskFaJ8))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
single_conv_dist
|
def single_conv_dist(name, x, output_channels=None):
"""A 3x3 convolution mapping x to a standard normal distribution at init.
Args:
name: variable scope.
x: 4-D Tensor.
output_channels: number of channels of the mean and std.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
x_shape = common_layers.shape_list(x)
if output_channels is None:
output_channels = x_shape[-1]
mean_log_scale = conv("conv2d", x, output_channels=2*output_channels,
conv_init="zeros", apply_actnorm=False)
mean = mean_log_scale[:, :, :, 0::2]
log_scale = mean_log_scale[:, :, :, 1::2]
return tf.distributions.Normal(mean, tf.exp(log_scale))
|
python
|
def single_conv_dist(name, x, output_channels=None):
"""A 3x3 convolution mapping x to a standard normal distribution at init.
Args:
name: variable scope.
x: 4-D Tensor.
output_channels: number of channels of the mean and std.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
x_shape = common_layers.shape_list(x)
if output_channels is None:
output_channels = x_shape[-1]
mean_log_scale = conv("conv2d", x, output_channels=2*output_channels,
conv_init="zeros", apply_actnorm=False)
mean = mean_log_scale[:, :, :, 0::2]
log_scale = mean_log_scale[:, :, :, 1::2]
return tf.distributions.Normal(mean, tf.exp(log_scale))
|
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A 3x3 convolution mapping x to a standard normal distribution at init.
Args:
name: variable scope.
x: 4-D Tensor.
output_channels: number of channels of the mean and std.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L847-L863
|
train
|
A 3x3 convolution mapping x to a standard normal distribution at init.
|
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(1551 - 1503) + '\x6f' + '\x32' + '\x32' + '\067', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(776 - 726) + chr(48) + chr(0b100101 + 0o20), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\063' + '\062' + chr(986 - 932), 58283 - 58275), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110 + 0o55) + chr(53) + '\x33', 0o10), ehT0Px3KOsy9(chr(1206 - 1158) + '\x6f' + chr(580 - 530) + '\067' + '\065', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\066' + chr(0b10001 + 0o40), 50346 - 50338), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + '\061' + chr(0b110010), 2814 - 2806), ehT0Px3KOsy9(chr(1902 - 1854) + chr(0b1001011 + 0o44) + '\x31' + chr(0b110000) + '\x30', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10 + 0o61) + chr(0b110001) + chr(84 - 34), 8), ehT0Px3KOsy9(chr(0b1100 + 0o44) + '\x6f' + chr(0b111 + 0o53) + chr(50) + chr(536 - 487), 15884 - 15876), ehT0Px3KOsy9(chr(1790 - 1742) + '\157' + chr(50) + chr(354 - 299) + chr(0b100000 + 0o24), 0o10), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b101111 + 0o100) + '\x32' + '\064' + '\063', 0o10), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(6684 - 6573) + '\066' + '\x35', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1111 + 0o44) + chr(50) + '\x34', 0o10), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\157' + chr(0b110101 + 0o2) + chr(0b110000), 35809 - 35801), ehT0Px3KOsy9('\x30' + chr(0b111110 + 0o61) + '\063' + chr(54) + chr(2454 - 2404), 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1101110 + 0o1) + chr(1315 - 1265) + '\060' + chr(53), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x34' + chr(0b101111 + 0o10), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(9831 - 9720) + chr(49) + '\x37' + chr(52), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(50) + chr(0b110110) + chr(0b101000 + 0o16), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b101 + 0o55) + chr(413 - 360) + chr(471 - 416), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(2254 - 2204) + chr(0b110011) + chr(1822 - 1772), 48349 - 48341), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010) + '\067' + '\062', 51286 - 51278), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b110001 + 0o76) + '\061' + '\063' + chr(916 - 862), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + chr(53) + chr(0b110011 + 0o1), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b100101 + 0o16) + '\063', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + chr(1880 - 1830) + chr(1772 - 1719), 0b1000), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(111) + chr(1090 - 1039) + '\062' + '\065', 8), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(1304 - 1193) + chr(0b10101 + 0o34) + '\062' + chr(49), 33121 - 33113), ehT0Px3KOsy9('\060' + chr(5205 - 5094) + chr(0b101011 + 0o10) + chr(50) + chr(51), 9001 - 8993), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2563 - 2512) + chr(1328 - 1277) + chr(0b101111 + 0o7), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(11730 - 11619) + '\063' + chr(1132 - 1078) + '\065', 0o10), ehT0Px3KOsy9(chr(1117 - 1069) + chr(0b1101111) + chr(2488 - 2438) + chr(0b10001 + 0o43) + chr(0b110001), 13265 - 13257), ehT0Px3KOsy9(chr(233 - 185) + '\x6f' + chr(2058 - 2008) + '\x31' + '\x32', 2898 - 2890), ehT0Px3KOsy9('\060' + chr(0b110101 + 0o72) + chr(0b110010) + chr(418 - 368) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100110 + 0o15) + chr(0b1011 + 0o46) + chr(48), 23580 - 23572), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + chr(1065 - 1014) + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b11111 + 0o23) + chr(1908 - 1859) + chr(0b110010), 8), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1101111) + chr(0b110001) + chr(50) + chr(0b110101), 17559 - 17551), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(1072 - 1022) + chr(0b100010 + 0o25) + chr(1788 - 1736), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(0b111011 + 0o64) + '\065' + chr(0b110000), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb9'), chr(0b1100100) + chr(0b11 + 0o142) + '\143' + chr(0b1101111) + chr(100) + chr(0b1100101))('\x75' + chr(4862 - 4746) + '\146' + chr(0b101101) + chr(0b101100 + 0o14)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ccE3dktzRVy2(AIvJRzLdDfgF, OeWW0F1dBPRQ, jAT42bk66WvZ=None):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe1\xe4\xa4\x82\xdcS\xa6%\x95\xe2\xdf\xccE\xb1'), '\144' + chr(0b111010 + 0o53) + chr(0b1100011) + chr(0b1101111) + '\144' + chr(0b1100101))(chr(9359 - 9242) + chr(148 - 32) + chr(0b1001100 + 0o32) + '\055' + '\070'))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd6\xd0\x82\xa4\xe2c\x8f\x15\x99\xd4'), '\144' + chr(0b1100101) + chr(0b1100011) + chr(11931 - 11820) + chr(100) + chr(0b1001110 + 0o27))(chr(0b1110101 + 0o0) + '\164' + '\146' + '\x2d' + '\x38'))):
QQEXXbdZyz6m = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
if jAT42bk66WvZ is None:
jAT42bk66WvZ = QQEXXbdZyz6m[-ehT0Px3KOsy9(chr(48) + chr(5954 - 5843) + chr(0b11111 + 0o22), ord("\x08"))]
MmgB0te19BWS = m1sWr00SVpVY(xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xea\xb8\x9d\x8fU'), '\x64' + chr(0b1100101) + chr(0b1100011) + chr(0b1101111) + chr(0b110110 + 0o56) + chr(101))('\165' + '\x74' + chr(6628 - 6526) + chr(0b101101) + '\x38'), OeWW0F1dBPRQ, output_channels=ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\x6f' + '\062', 0o10) * jAT42bk66WvZ, conv_init=xafqLlk3kkUe(SXOLrMavuUCe(b'\xed\xe0\xa4\x84\xce'), chr(0b1100100) + '\x65' + '\143' + chr(0b101100 + 0o103) + '\144' + '\x65')(chr(0b1101001 + 0o14) + '\164' + chr(8748 - 8646) + '\055' + '\070'), apply_actnorm=ehT0Px3KOsy9('\060' + chr(2157 - 2046) + chr(0b110000), 0b1000))
aJhItC_Vawlw = MmgB0te19BWS[:, :, :, ehT0Px3KOsy9('\x30' + '\157' + chr(0b10011 + 0o35), 8)::ehT0Px3KOsy9('\x30' + chr(0b101010 + 0o105) + chr(2219 - 2169), 8)]
emKULJskFaJ8 = MmgB0te19BWS[:, :, :, ehT0Px3KOsy9('\060' + chr(111) + chr(0b100111 + 0o12), 8)::ehT0Px3KOsy9(chr(0b110000) + chr(5567 - 5456) + chr(0b1101 + 0o45), 8)]
return xafqLlk3kkUe(IDJ2eXGCBCDu.distributions, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd9\xea\xa4\x86\xdc]'), chr(5946 - 5846) + chr(6239 - 6138) + '\143' + chr(0b11001 + 0o126) + chr(0b1100100) + chr(8387 - 8286))(chr(0b1011111 + 0o26) + '\164' + chr(0b1100110) + chr(1438 - 1393) + chr(0b101101 + 0o13)))(aJhItC_Vawlw, xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf2\xfd\xa6'), chr(8017 - 7917) + '\x65' + chr(0b1100011) + chr(0b1101111) + chr(395 - 295) + chr(0b1000111 + 0o36))('\165' + chr(12772 - 12656) + '\146' + chr(0b101101) + chr(0b111000)))(emKULJskFaJ8))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
latent_to_dist
|
def latent_to_dist(name, x, hparams, output_channels=None):
"""Map latent to the mean and log-scale of a Gaussian.
Args:
name: variable scope.
x: 4-D Tensor of shape (NHWC)
hparams: HParams.
latent_architecture - can be "single_conv", "glow_nn" or "glow_resnet",
default = single_conv
latent_encoder_depth - int, depth of architecture, valid if
latent_architecture is "glow_nn" or "glow_resnet".
latent_pre_output_channels - 512, valid only when latent_architecture
is "glow_nn".
latent_encoder_width - 512, maximum width of the network
output_channels: int, number of output channels of the mean (and std).
if not provided, set it to be the output channels of x.
Returns:
dist: instance of tfp.distributions.Normal
Raises:
ValueError: If architecture not in ["single_conv", "glow_nn"]
"""
architecture = hparams.get("latent_architecture", "single_conv")
depth = hparams.get("latent_encoder_depth", 1)
pre_output_channels = hparams.get("latent_pre_output_channels", 512)
width = hparams.get("latent_encoder_width", 512)
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
x_shape = common_layers.shape_list(x)
if output_channels is None:
output_channels = x_shape[-1]
if architecture == "single_conv":
return single_conv_dist("single_conv", x, output_channels)
if architecture == "glow_nn":
mean_log_scale = x
for layer in range(1, depth + 1):
mid_channels = pre_output_channels // 2**(depth - layer)
mean_log_scale = conv_block("glow_nn_%d" % layer, mean_log_scale,
mid_channels=mid_channels)
mean_log_scale = conv("glow_nn_zeros", mean_log_scale,
filter_size=[3, 3], stride=[1, 1],
output_channels=2*output_channels,
apply_actnorm=False, conv_init="zeros")
elif architecture == "glow_resnet":
h = x
for layer in range(depth):
h3 = conv_stack("latent_resnet_%d" % layer, h,
mid_channels=width, output_channels=x_shape[-1],
dropout=hparams.coupling_dropout)
h += h3
mean_log_scale = conv("glow_res_final", h, conv_init="zeros",
output_channels=2*output_channels,
apply_actnorm=False)
else:
raise ValueError("expected architecture to be single_conv or glow_nn "
"got %s" % architecture)
mean = mean_log_scale[:, :, :, 0::2]
log_scale = mean_log_scale[:, :, :, 1::2]
return tfp.distributions.Normal(mean, tf.exp(log_scale))
|
python
|
def latent_to_dist(name, x, hparams, output_channels=None):
"""Map latent to the mean and log-scale of a Gaussian.
Args:
name: variable scope.
x: 4-D Tensor of shape (NHWC)
hparams: HParams.
latent_architecture - can be "single_conv", "glow_nn" or "glow_resnet",
default = single_conv
latent_encoder_depth - int, depth of architecture, valid if
latent_architecture is "glow_nn" or "glow_resnet".
latent_pre_output_channels - 512, valid only when latent_architecture
is "glow_nn".
latent_encoder_width - 512, maximum width of the network
output_channels: int, number of output channels of the mean (and std).
if not provided, set it to be the output channels of x.
Returns:
dist: instance of tfp.distributions.Normal
Raises:
ValueError: If architecture not in ["single_conv", "glow_nn"]
"""
architecture = hparams.get("latent_architecture", "single_conv")
depth = hparams.get("latent_encoder_depth", 1)
pre_output_channels = hparams.get("latent_pre_output_channels", 512)
width = hparams.get("latent_encoder_width", 512)
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
x_shape = common_layers.shape_list(x)
if output_channels is None:
output_channels = x_shape[-1]
if architecture == "single_conv":
return single_conv_dist("single_conv", x, output_channels)
if architecture == "glow_nn":
mean_log_scale = x
for layer in range(1, depth + 1):
mid_channels = pre_output_channels // 2**(depth - layer)
mean_log_scale = conv_block("glow_nn_%d" % layer, mean_log_scale,
mid_channels=mid_channels)
mean_log_scale = conv("glow_nn_zeros", mean_log_scale,
filter_size=[3, 3], stride=[1, 1],
output_channels=2*output_channels,
apply_actnorm=False, conv_init="zeros")
elif architecture == "glow_resnet":
h = x
for layer in range(depth):
h3 = conv_stack("latent_resnet_%d" % layer, h,
mid_channels=width, output_channels=x_shape[-1],
dropout=hparams.coupling_dropout)
h += h3
mean_log_scale = conv("glow_res_final", h, conv_init="zeros",
output_channels=2*output_channels,
apply_actnorm=False)
else:
raise ValueError("expected architecture to be single_conv or glow_nn "
"got %s" % architecture)
mean = mean_log_scale[:, :, :, 0::2]
log_scale = mean_log_scale[:, :, :, 1::2]
return tfp.distributions.Normal(mean, tf.exp(log_scale))
|
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] |
Map latent to the mean and log-scale of a Gaussian.
Args:
name: variable scope.
x: 4-D Tensor of shape (NHWC)
hparams: HParams.
latent_architecture - can be "single_conv", "glow_nn" or "glow_resnet",
default = single_conv
latent_encoder_depth - int, depth of architecture, valid if
latent_architecture is "glow_nn" or "glow_resnet".
latent_pre_output_channels - 512, valid only when latent_architecture
is "glow_nn".
latent_encoder_width - 512, maximum width of the network
output_channels: int, number of output channels of the mean (and std).
if not provided, set it to be the output channels of x.
Returns:
dist: instance of tfp.distributions.Normal
Raises:
ValueError: If architecture not in ["single_conv", "glow_nn"]
|
[
"Map",
"latent",
"to",
"the",
"mean",
"and",
"log",
"-",
"scale",
"of",
"a",
"Gaussian",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L867-L925
|
train
|
Map latent to the mean and log - scale of a Gaussian.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1274 - 1226) + chr(111) + '\062' + '\x36' + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(0b1101111) + '\x37' + chr(49), 57434 - 57426), ehT0Px3KOsy9('\060' + chr(0b1000110 + 0o51) + '\x36' + chr(49), 2231 - 2223), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010 + 0o1) + '\062' + '\065', 0o10), ehT0Px3KOsy9(chr(1549 - 1501) + chr(0b1101111) + '\x31' + chr(0b11000 + 0o31) + chr(999 - 944), 0o10), ehT0Px3KOsy9(chr(2293 - 2245) + '\157' + '\062' + chr(0b110011) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(459 - 411) + chr(0b1101111) + chr(242 - 193) + chr(48) + chr(1939 - 1891), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b111101 + 0o62) + chr(51) + chr(0b101010 + 0o12) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(2423 - 2312) + chr(0b110001) + chr(0b101101 + 0o11) + chr(943 - 888), 15577 - 15569), ehT0Px3KOsy9(chr(0b101001 + 0o7) + '\x6f' + '\x32' + chr(55) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110011 + 0o1), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + '\067' + '\061', 51803 - 51795), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011) + chr(0b110 + 0o60) + '\x32', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\x33' + chr(408 - 353) + chr(0b10 + 0o65), 0o10), ehT0Px3KOsy9(chr(186 - 138) + '\x6f' + chr(398 - 348) + chr(0b110111 + 0o0) + chr(0b110111), 0o10), ehT0Px3KOsy9('\060' + chr(0b101010 + 0o105) + chr(0b1000 + 0o51) + chr(0b100 + 0o60) + chr(50), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b11101 + 0o122) + chr(653 - 601) + chr(0b110010), 38883 - 38875), ehT0Px3KOsy9(chr(1148 - 1100) + '\x6f' + chr(51) + chr(2266 - 2216) + '\063', 58779 - 58771), ehT0Px3KOsy9('\060' + chr(111) + chr(49) + chr(0b100 + 0o62) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1000000 + 0o57) + chr(49) + '\063' + '\x31', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(51) + '\060' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(50) + chr(0b111 + 0o60) + '\060', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(589 - 539) + chr(51) + chr(0b110100), 48195 - 48187), ehT0Px3KOsy9(chr(1033 - 985) + chr(0b1101111) + chr(0b100100 + 0o16) + '\x32' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(492 - 444) + chr(0b1101111) + chr(0b1110 + 0o44) + chr(52) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(52) + chr(0b10101 + 0o35), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b1001 + 0o51) + '\061' + '\x32', 0b1000), ehT0Px3KOsy9('\x30' + chr(6258 - 6147) + chr(50) + '\063', 0o10), ehT0Px3KOsy9('\x30' + chr(0b10111 + 0o130) + '\x32' + chr(0b11010 + 0o31) + chr(50), 51808 - 51800), ehT0Px3KOsy9(chr(0b1000 + 0o50) + '\157' + chr(55) + chr(0b110000), 11537 - 11529), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + chr(55), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(51) + chr(179 - 126) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(111) + chr(1337 - 1288) + '\063' + '\x31', 8), ehT0Px3KOsy9(chr(48) + chr(6828 - 6717) + chr(0b110010) + chr(0b110111) + chr(90 - 38), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(2094 - 1983) + chr(864 - 811) + chr(0b10100 + 0o35), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + chr(0b100011 + 0o17) + '\067', 37013 - 37005), ehT0Px3KOsy9(chr(0b110000) + chr(862 - 751) + '\061' + chr(51) + chr(49), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + chr(0b110110) + chr(1708 - 1657), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b11101 + 0o122) + chr(0b110000 + 0o5) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(1598 - 1550) + chr(0b11010 + 0o125) + '\x30', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\x6f' + '\x35' + chr(0b110 + 0o52), 1880 - 1872)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x9c'), '\144' + chr(2315 - 2214) + chr(2707 - 2608) + chr(8641 - 8530) + '\x64' + chr(0b1010001 + 0o24))(chr(0b10 + 0o163) + chr(0b1010110 + 0o36) + chr(8113 - 8011) + chr(0b101101) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def pVJLl_2H5xnT(AIvJRzLdDfgF, OeWW0F1dBPRQ, n4ljua2gi1Pr, jAT42bk66WvZ=None):
RD4unzZOLAZT = n4ljua2gi1Pr.get(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdeXE\xb0!\xea\x1f\x84\x05\xd9l\x90\x86\x9a\xdc\x16W\xa1\x11'), '\x64' + chr(101) + chr(0b1100011) + '\x6f' + chr(100) + chr(0b110111 + 0o56))(chr(0b1110101) + chr(116) + '\x66' + chr(1687 - 1642) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xc1P_\xb2#\xfb\x1f\x86\x18\xd4r'), chr(0b11101 + 0o107) + chr(0b1001001 + 0o34) + chr(0b1100 + 0o127) + chr(0b1101111) + chr(3581 - 3481) + chr(1931 - 1830))('\x75' + chr(6772 - 6656) + chr(0b1100110) + chr(45) + chr(0b111000)))
UEys4_lSwsID = n4ljua2gi1Pr.get(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdeXE\xb0!\xea\x1f\x80\x19\xd9k\x9d\x97\x8d\xe0\x06G\xa3\x001'), '\144' + chr(0b101100 + 0o71) + chr(99) + chr(10763 - 10652) + chr(1949 - 1849) + chr(4832 - 4731))(chr(0b110 + 0o157) + '\164' + '\146' + chr(0b101101) + chr(56)), ehT0Px3KOsy9(chr(1983 - 1935) + chr(0b11011 + 0o124) + chr(0b101011 + 0o6), 0b1000))
jbtckiOviwLq = n4ljua2gi1Pr.get(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdeXE\xb0!\xea\x1f\x95\x05\xdf[\x96\x87\x8b\xcf\x17V\x8c\x171\xa3\xd6\xf2\xf5\xcfQ'), '\x64' + chr(0b101100 + 0o71) + chr(0b1100011) + chr(111) + chr(0b1100100) + chr(0b1100101))(chr(7459 - 7342) + chr(0b1100 + 0o150) + '\x66' + chr(0b11011 + 0o22) + chr(372 - 316)), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + chr(0b11000 + 0o30) + chr(0b110000) + chr(48), 0o10))
mPx09rBTrGXR = n4ljua2gi1Pr.get(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdeXE\xb0!\xea\x1f\x80\x19\xd9k\x9d\x97\x8d\xe0\x15K\xb7\x001'), chr(100) + '\x65' + chr(4115 - 4016) + chr(0b1101111) + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + chr(0b100110 + 0o116) + '\146' + '\x2d' + chr(2624 - 2568)), ehT0Px3KOsy9(chr(1822 - 1774) + chr(0b1101111) + chr(49) + chr(0b110000) + '\x30' + chr(48), 8))
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc4XC\xbc.\xfc,\x80(\xc9g\x96\x82\x9a'), chr(100) + '\145' + chr(0b1100011) + chr(0b1101111) + chr(6585 - 6485) + '\x65')('\165' + chr(0b101010 + 0o112) + chr(0b10101 + 0o121) + chr(866 - 821) + '\x38'))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf3le\x9a\x10\xcc\x05\xb0$\xff'), chr(0b1000101 + 0o37) + chr(4018 - 3917) + chr(0b100101 + 0o76) + chr(0b111001 + 0o66) + chr(100) + chr(101))(chr(169 - 52) + '\164' + '\x66' + chr(0b101101) + chr(56)))):
QQEXXbdZyz6m = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
if jAT42bk66WvZ is None:
jAT42bk66WvZ = QQEXXbdZyz6m[-ehT0Px3KOsy9('\x30' + chr(111) + chr(49), 8)]
if RD4unzZOLAZT == xafqLlk3kkUe(SXOLrMavuUCe(b'\xc1P_\xb2#\xfb\x1f\x86\x18\xd4r'), '\144' + chr(101) + '\x63' + chr(0b1011000 + 0o27) + chr(0b1100100) + '\x65')(chr(0b1101010 + 0o13) + chr(0b1110100) + '\x66' + chr(45) + '\070'):
return ccE3dktzRVy2(xafqLlk3kkUe(SXOLrMavuUCe(b'\xc1P_\xb2#\xfb\x1f\x86\x18\xd4r'), chr(100) + '\x65' + chr(0b1100011) + chr(0b1000 + 0o147) + chr(4219 - 4119) + '\x65')(chr(0b100100 + 0o121) + chr(0b1101 + 0o147) + '\x66' + '\055' + '\070'), OeWW0F1dBPRQ, jAT42bk66WvZ)
if RD4unzZOLAZT == xafqLlk3kkUe(SXOLrMavuUCe(b'\xd5U^\xa2\x10\xf0.'), chr(0b1100100) + chr(9983 - 9882) + chr(99) + '\157' + chr(4075 - 3975) + chr(0b1100101))(chr(117) + chr(116) + chr(102) + chr(1152 - 1107) + chr(0b111000)):
MmgB0te19BWS = OeWW0F1dBPRQ
for wgamNHppspXj in vQr8gNKaIaWE(ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b10111 + 0o32), 8), UEys4_lSwsID + ehT0Px3KOsy9(chr(1274 - 1226) + '\x6f' + chr(0b101010 + 0o7), 8)):
la0jAn6F0a8S = jbtckiOviwLq // ehT0Px3KOsy9('\060' + chr(0b1010100 + 0o33) + chr(795 - 745), ord("\x08")) ** (UEys4_lSwsID - wgamNHppspXj)
MmgB0te19BWS = UPhJ6DlDf_h1(xafqLlk3kkUe(SXOLrMavuUCe(b'\xd5U^\xa2\x10\xf0.\xbaR\xde'), '\144' + chr(101) + chr(0b101000 + 0o73) + chr(4737 - 4626) + chr(0b11011 + 0o111) + chr(101))(chr(117) + '\164' + '\146' + chr(0b1000 + 0o45) + chr(56)) % wgamNHppspXj, MmgB0te19BWS, mid_channels=la0jAn6F0a8S)
MmgB0te19BWS = m1sWr00SVpVY(xafqLlk3kkUe(SXOLrMavuUCe(b'\xd5U^\xa2\x10\xf0.\xba\r\xdfv\x96\x81'), chr(7277 - 7177) + chr(786 - 685) + chr(0b1100011 + 0o0) + chr(0b1011011 + 0o24) + '\144' + '\145')(chr(0b111011 + 0o72) + chr(0b1110100) + chr(0b110110 + 0o60) + chr(1886 - 1841) + '\070'), MmgB0te19BWS, filter_size=[ehT0Px3KOsy9(chr(48) + '\x6f' + '\063', 0b1000), ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\157' + '\063', 8)], stride=[ehT0Px3KOsy9(chr(1763 - 1715) + chr(0b1010100 + 0o33) + chr(49), 8), ehT0Px3KOsy9(chr(1319 - 1271) + chr(0b1101111) + '\x31', 8)], output_channels=ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(2289 - 2178) + '\062', 8) * jAT42bk66WvZ, apply_actnorm=ehT0Px3KOsy9('\060' + '\x6f' + '\x30', 8), conv_init=xafqLlk3kkUe(SXOLrMavuUCe(b'\xc8\\C\xba<'), chr(100) + '\145' + chr(0b1100011) + chr(0b1101111) + chr(0b1000011 + 0o41) + '\145')('\165' + chr(116) + chr(0b1100110) + '\055' + chr(739 - 683)))
elif RD4unzZOLAZT == xafqLlk3kkUe(SXOLrMavuUCe(b'\xd5U^\xa2\x10\xec%\x96\x19\xdfp'), chr(5988 - 5888) + chr(6440 - 6339) + '\143' + chr(0b1101111) + chr(100) + chr(101))('\x75' + chr(116) + chr(0b111000 + 0o56) + '\x2d' + chr(3041 - 2985)):
sz4HVsFVF8nL = OeWW0F1dBPRQ
for wgamNHppspXj in vQr8gNKaIaWE(UEys4_lSwsID):
scP9vLOEXU0P = Pchy2tZfVp78(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdeXE\xb0!\xea\x1f\x97\x12\xc9j\x9c\x86\xa0\x9a\x06'), chr(0b111010 + 0o52) + '\x65' + chr(0b1100011) + chr(0b1101111) + chr(0b100000 + 0o104) + chr(0b1100101))('\x75' + chr(116) + chr(102) + '\055' + '\x38') % wgamNHppspXj, sz4HVsFVF8nL, mid_channels=mPx09rBTrGXR, output_channels=QQEXXbdZyz6m[-ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b101111 + 0o2), 8)], dropout=n4ljua2gi1Pr.coupling_dropout)
sz4HVsFVF8nL += scP9vLOEXU0P
MmgB0te19BWS = m1sWr00SVpVY(xafqLlk3kkUe(SXOLrMavuUCe(b'\xd5U^\xa2\x10\xec%\x96(\xdcm\x97\x93\x93'), chr(0b11110 + 0o106) + chr(0b1010110 + 0o17) + chr(99) + chr(11236 - 11125) + chr(0b1100100) + chr(0b100000 + 0o105))(chr(117) + chr(0b1110100) + chr(0b100011 + 0o103) + '\x2d' + chr(676 - 620)), sz4HVsFVF8nL, conv_init=xafqLlk3kkUe(SXOLrMavuUCe(b'\xc8\\C\xba<'), chr(0b1100100) + '\145' + chr(99) + chr(5341 - 5230) + '\144' + '\145')('\165' + chr(8096 - 7980) + chr(0b11 + 0o143) + chr(0b101101) + chr(0b111000)), output_channels=ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\157' + chr(50), 8) * jAT42bk66WvZ, apply_actnorm=ehT0Px3KOsy9('\060' + '\x6f' + '\060', 8))
else:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\xd7AA\xb0,\xea%\x81W\xdbv\x9a\x9a\x96\xcb\x07A\xa7\x01+\xa7\x98\xe8\xff\x83@\xef3\xe9Qy\x8b5\xd9v\xb46\x1dY \xddK\x11\xb2#\xf17\xba\x19\xd4$\x9e\x9d\x8b\x9fGQ'), chr(100) + chr(0b1001111 + 0o26) + chr(5374 - 5275) + '\x6f' + '\144' + '\145')('\165' + '\164' + '\146' + chr(0b1101 + 0o40) + chr(0b11000 + 0o40)) % RD4unzZOLAZT)
aJhItC_Vawlw = MmgB0te19BWS[:, :, :, ehT0Px3KOsy9('\x30' + '\x6f' + '\x30', 8)::ehT0Px3KOsy9(chr(48) + '\157' + '\062', 8)]
emKULJskFaJ8 = MmgB0te19BWS[:, :, :, ehT0Px3KOsy9(chr(0b110000) + chr(1027 - 916) + '\061', 8)::ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010), 8)]
return xafqLlk3kkUe(Ys555qziAbad.distributions, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfcVC\xb8.\xf2'), '\144' + chr(0b1010000 + 0o25) + '\143' + '\157' + chr(0b100100 + 0o100) + '\145')(chr(0b1110101) + '\164' + '\146' + chr(0b100001 + 0o14) + chr(0b110110 + 0o2)))(aJhItC_Vawlw, xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd7AA'), chr(0b1011000 + 0o14) + chr(101) + chr(0b10 + 0o141) + chr(0b1101111) + chr(0b1100100) + chr(101))(chr(0b1110101) + chr(0b11111 + 0o125) + chr(102) + '\x2d' + '\x38'))(emKULJskFaJ8))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
noise_op
|
def noise_op(latents, hparams):
"""Adds isotropic gaussian-noise to each latent.
Args:
latents: 4-D or 5-D tensor, shape=(NTHWC) or (NHWC).
hparams: HParams.
Returns:
latents: latents with isotropic gaussian noise appended.
"""
if hparams.latent_noise == 0 or hparams.mode != tf.estimator.ModeKeys.TRAIN:
return latents
latent_shape = common_layers.shape_list(latents)
return latents + tf.random_normal(latent_shape, stddev=hparams.latent_noise)
|
python
|
def noise_op(latents, hparams):
"""Adds isotropic gaussian-noise to each latent.
Args:
latents: 4-D or 5-D tensor, shape=(NTHWC) or (NHWC).
hparams: HParams.
Returns:
latents: latents with isotropic gaussian noise appended.
"""
if hparams.latent_noise == 0 or hparams.mode != tf.estimator.ModeKeys.TRAIN:
return latents
latent_shape = common_layers.shape_list(latents)
return latents + tf.random_normal(latent_shape, stddev=hparams.latent_noise)
|
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",",
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")",
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".",
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"==",
"0",
"or",
"hparams",
".",
"mode",
"!=",
"tf",
".",
"estimator",
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"latents",
"latent_shape",
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"(",
"latents",
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"+",
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".",
"random_normal",
"(",
"latent_shape",
",",
"stddev",
"=",
"hparams",
".",
"latent_noise",
")"
] |
Adds isotropic gaussian-noise to each latent.
Args:
latents: 4-D or 5-D tensor, shape=(NTHWC) or (NHWC).
hparams: HParams.
Returns:
latents: latents with isotropic gaussian noise appended.
|
[
"Adds",
"isotropic",
"gaussian",
"-",
"noise",
"to",
"each",
"latent",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L929-L941
|
train
|
Adds isotropic gaussian - noise to each latent.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(811 - 758) + chr(0b11111 + 0o25), 28799 - 28791), ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\157' + '\x33' + '\062' + chr(307 - 258), 11033 - 11025), ehT0Px3KOsy9('\060' + chr(11762 - 11651) + '\x36' + chr(0b110111), 22172 - 22164), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b1010 + 0o50) + '\065' + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(49) + chr(0b110111) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110111) + chr(0b100 + 0o55), 29284 - 29276), ehT0Px3KOsy9('\060' + chr(3679 - 3568) + '\x31' + chr(0b110111) + chr(1071 - 1019), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(54) + chr(52), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(577 - 526) + '\x36' + chr(2123 - 2068), ord("\x08")), ehT0Px3KOsy9(chr(1388 - 1340) + chr(0b10110 + 0o131) + chr(0b1 + 0o62) + chr(1318 - 1266) + '\x36', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + chr(0b100 + 0o62) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\x6f' + '\062' + chr(0b10 + 0o64), 27869 - 27861), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(0b1101111) + '\063' + chr(2081 - 2030) + '\x31', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b111 + 0o54) + chr(876 - 828) + chr(765 - 714), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b100 + 0o56) + chr(1994 - 1942) + chr(580 - 528), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1011111 + 0o20) + '\x32' + '\060' + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(9192 - 9081) + '\x32' + chr(0b110011) + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + chr(9779 - 9668) + chr(0b110010) + chr(326 - 276) + '\061', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + chr(0b110110) + '\067', 8), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\157' + '\x32' + '\x30' + chr(0b1 + 0o60), 13446 - 13438), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(9747 - 9636) + '\x33' + chr(0b100010 + 0o25) + chr(50), 38251 - 38243), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(1352 - 1241) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(1323 - 1212) + chr(0b110100) + chr(2332 - 2280), 8277 - 8269), ehT0Px3KOsy9(chr(1799 - 1751) + '\157' + chr(0b110001) + '\x34' + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(111) + '\066' + chr(54), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b101111 + 0o100) + '\x32' + chr(55) + '\064', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101100 + 0o3) + chr(49) + chr(0b10101 + 0o35) + chr(54), 48612 - 48604), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + '\x31' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(1789 - 1741) + chr(0b1101111) + chr(0b110001) + chr(55) + '\x37', 26019 - 26011), ehT0Px3KOsy9(chr(227 - 179) + chr(111) + '\x31' + chr(0b10101 + 0o36) + '\x33', 0o10), ehT0Px3KOsy9(chr(1798 - 1750) + chr(0b1101111 + 0o0) + chr(1768 - 1718) + chr(291 - 238) + '\x34', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\061' + chr(0b1 + 0o65) + chr(1329 - 1274), 0b1000), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(2796 - 2685) + chr(2202 - 2151) + '\x33' + '\x36', 0b1000), ehT0Px3KOsy9(chr(1075 - 1027) + '\x6f' + chr(51) + '\x31' + chr(1492 - 1439), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(2195 - 2145) + chr(0b1 + 0o61), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(1231 - 1120) + chr(0b101010 + 0o11) + chr(0b110110 + 0o1) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\157' + chr(0b11001 + 0o31) + chr(326 - 277), 0b1000), ehT0Px3KOsy9(chr(534 - 486) + chr(0b11111 + 0o120) + chr(428 - 375) + chr(0b100000 + 0o26), 59391 - 59383), ehT0Px3KOsy9(chr(48) + chr(8891 - 8780) + chr(1751 - 1700) + '\060' + '\x33', 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + chr(0b110100) + chr(2309 - 2260), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\157' + chr(1770 - 1717) + chr(0b101011 + 0o5), 65442 - 65434)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x02'), chr(0b1100100) + '\145' + '\x63' + chr(111) + '\144' + '\x65')(chr(0b101111 + 0o106) + '\x74' + chr(102) + '\x2d' + chr(0b100111 + 0o21)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def B1HjdZtjHLgD(Q2AqdJPGTM7R, n4ljua2gi1Pr):
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'@\xb0C\xcd\x14M#Z\x98\x8f\x82s'), chr(100) + chr(0b10110 + 0o117) + '\x63' + chr(0b1101111) + chr(0b1100100) + chr(386 - 285))(chr(7696 - 7579) + chr(12873 - 12757) + chr(9632 - 9530) + chr(0b101101) + '\070')) == ehT0Px3KOsy9('\x30' + chr(0b101010 + 0o105) + chr(0b110000), 8) or xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'A\xbeS\xcd'), '\144' + chr(2059 - 1958) + chr(0b10010 + 0o121) + chr(3557 - 3446) + chr(662 - 562) + chr(0b101100 + 0o71))(chr(7479 - 7362) + chr(0b10011 + 0o141) + chr(8195 - 8093) + chr(0b101101) + chr(857 - 801))) != xafqLlk3kkUe(IDJ2eXGCBCDu.estimator.ModeKeys, xafqLlk3kkUe(SXOLrMavuUCe(b'x\x83v\xe14'), chr(0b100 + 0o140) + chr(7155 - 7054) + chr(99) + chr(0b111 + 0o150) + '\x64' + '\145')(chr(11490 - 11373) + chr(0b100111 + 0o115) + chr(0b1100110) + chr(45) + '\x38')):
return Q2AqdJPGTM7R
XhU4geNCR0zu = jSKPaHwSAfVv.shape_list(Q2AqdJPGTM7R)
return Q2AqdJPGTM7R + xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'^\xb0Y\xcc\x15T#Z\x98\x94\x9cw\xb5'), chr(100) + chr(101) + chr(0b1010011 + 0o20) + chr(0b1101111) + '\144' + chr(3121 - 3020))(chr(0b1110101) + chr(4388 - 4272) + chr(102) + chr(45) + '\x38'))(XhU4geNCR0zu, stddev=xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'@\xb0C\xcd\x14M#Z\x98\x8f\x82s'), chr(2587 - 2487) + chr(9791 - 9690) + '\143' + '\157' + chr(100) + '\145')(chr(0b1101110 + 0o7) + '\164' + chr(8520 - 8418) + '\x2d' + '\070')))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
merge_level_and_latent_dist
|
def merge_level_and_latent_dist(level_dist, latent_dist,
merge_std="prev_level"):
"""Merge level_dist and latent_dist.
new_dist ~ N(level_dist.mean + latent_dis.mean, std) where std is determined
according to merge_std.
Args:
level_dist: instance of tfp.distributions.Normal
latent_dist: instance of tfp.distributions.Normal
merge_std: can be "prev_level", "prev_step" or "normal".
Returns:
merged_dist: instance of tfp.distributions.Normal
"""
level_mean, level_std = level_dist.loc, level_dist.scale
latent_mean, latent_std = latent_dist.loc, latent_dist.scale
new_mean = level_mean + latent_mean
if merge_std == "normal":
z_shape = common_layers.shape_list(latent_mean)
log_scale = tf.get_variable(
"merge_std", shape=z_shape, dtype=tf.float32,
initializer=tf.zeros_initializer(), trainable=False)
scale = tf.exp(log_scale * 3.0)
elif merge_std == "prev_level":
scale = level_std
elif merge_std == "prev_step":
scale = latent_std
return tfp.distributions.Normal(loc=new_mean, scale=scale)
|
python
|
def merge_level_and_latent_dist(level_dist, latent_dist,
merge_std="prev_level"):
"""Merge level_dist and latent_dist.
new_dist ~ N(level_dist.mean + latent_dis.mean, std) where std is determined
according to merge_std.
Args:
level_dist: instance of tfp.distributions.Normal
latent_dist: instance of tfp.distributions.Normal
merge_std: can be "prev_level", "prev_step" or "normal".
Returns:
merged_dist: instance of tfp.distributions.Normal
"""
level_mean, level_std = level_dist.loc, level_dist.scale
latent_mean, latent_std = latent_dist.loc, latent_dist.scale
new_mean = level_mean + latent_mean
if merge_std == "normal":
z_shape = common_layers.shape_list(latent_mean)
log_scale = tf.get_variable(
"merge_std", shape=z_shape, dtype=tf.float32,
initializer=tf.zeros_initializer(), trainable=False)
scale = tf.exp(log_scale * 3.0)
elif merge_std == "prev_level":
scale = level_std
elif merge_std == "prev_step":
scale = latent_std
return tfp.distributions.Normal(loc=new_mean, scale=scale)
|
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] |
Merge level_dist and latent_dist.
new_dist ~ N(level_dist.mean + latent_dis.mean, std) where std is determined
according to merge_std.
Args:
level_dist: instance of tfp.distributions.Normal
latent_dist: instance of tfp.distributions.Normal
merge_std: can be "prev_level", "prev_step" or "normal".
Returns:
merged_dist: instance of tfp.distributions.Normal
|
[
"Merge",
"level_dist",
"and",
"latent_dist",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L945-L972
|
train
|
Merge level_dist and latent_dist.
|
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(10133 - 10022) + chr(0b100110 + 0o13) + chr(0b1101 + 0o45) + chr(0b110011), 43762 - 43754), ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\157' + chr(0b110110) + chr(0b11010 + 0o30), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(11564 - 11453) + chr(50) + chr(0b110101) + '\067', 0b1000), ehT0Px3KOsy9(chr(1443 - 1395) + '\157' + chr(0b1000 + 0o51) + chr(0b100010 + 0o16) + '\066', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(0b10000 + 0o43) + chr(0b11111 + 0o25), 32221 - 32213), ehT0Px3KOsy9('\060' + chr(11553 - 11442) + chr(49) + chr(52) + chr(0b100110 + 0o20), 0b1000), ehT0Px3KOsy9('\060' + chr(3042 - 2931) + '\061' + '\061' + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x35' + chr(51), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(1107 - 1058) + chr(52) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(876 - 825) + '\062' + chr(0b110111), 40188 - 40180), ehT0Px3KOsy9('\x30' + '\157' + '\x31' + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b101000 + 0o13) + chr(0b110011) + '\x34', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(48) + '\x32', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + '\x30' + chr(51), 0b1000), ehT0Px3KOsy9(chr(1828 - 1780) + chr(1495 - 1384) + chr(0b110001) + chr(0b1100 + 0o45) + chr(0b101010 + 0o10), 0o10), ehT0Px3KOsy9(chr(0b110 + 0o52) + '\x6f' + chr(51) + '\062' + '\x32', 0o10), ehT0Px3KOsy9(chr(1295 - 1247) + chr(0b1101111) + '\065' + chr(0b11111 + 0o21), 35047 - 35039), ehT0Px3KOsy9(chr(48) + '\x6f' + '\063', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010) + chr(2436 - 2385) + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\x36' + chr(0b101 + 0o60), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(1094 - 1045) + chr(138 - 90) + chr(51), 8), ehT0Px3KOsy9(chr(54 - 6) + chr(111) + chr(0b100000 + 0o21) + '\x31' + chr(49), 0o10), ehT0Px3KOsy9(chr(2248 - 2200) + '\x6f' + '\062' + chr(1158 - 1103) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + chr(2007 - 1952) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + chr(0b110101) + chr(54), 0o10), ehT0Px3KOsy9('\x30' + chr(3747 - 3636) + '\x31' + '\064' + chr(54), 8), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(0b1101111) + chr(0b110001) + chr(51) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + chr(0b100010 + 0o21) + chr(0b110011), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + chr(50) + chr(50), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b10000 + 0o44) + '\x36', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\062' + chr(571 - 522) + '\063', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010) + chr(1492 - 1438) + chr(1331 - 1281), 32364 - 32356), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + chr(0b1000 + 0o52) + '\065', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x37' + chr(0b1010 + 0o55), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1010111 + 0o30) + '\066' + chr(51), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\062' + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10111 + 0o34) + chr(1406 - 1351) + chr(202 - 147), ord("\x08")), ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\x6f' + chr(1964 - 1915) + '\x30' + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(48) + chr(1835 - 1724) + chr(49) + '\x31' + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(9773 - 9662) + '\062' + chr(0b11101 + 0o26) + chr(0b110011), 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b11000 + 0o127) + chr(0b1011 + 0o52) + '\x30', 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'}'), '\144' + '\x65' + chr(0b1100011) + chr(0b111101 + 0o62) + chr(100) + chr(0b1001110 + 0o27))(chr(0b1110101) + '\x74' + chr(0b1100110) + '\055' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def V7j36UebtQ8E(ODUfdK3GZIWx, YMevjCDNnvXm, fVUiVobSE6m6=xafqLlk3kkUe(SXOLrMavuUCe(b'#@\xca0\x03\n(]\x02\xbb'), chr(100) + '\x65' + chr(99) + chr(0b1101111) + chr(0b1100100) + chr(0b1010001 + 0o24))(chr(117) + chr(116) + chr(5892 - 5790) + '\x2d' + '\070')):
(Ov8ReZdCeHze, cmv9wj784cT6) = (ODUfdK3GZIWx.MmVY7Id_ODNA, ODUfdK3GZIWx.scale)
(HkFvf6riAnhp, mXpkKTnOrT8w) = (YMevjCDNnvXm.MmVY7Id_ODNA, YMevjCDNnvXm.scale)
OnPW0EWGtsDF = Ov8ReZdCeHze + HkFvf6riAnhp
if fVUiVobSE6m6 == xafqLlk3kkUe(SXOLrMavuUCe(b'=]\xdd+=\n'), '\144' + chr(101) + chr(0b1100011) + chr(0b110101 + 0o72) + chr(100) + '\x65')(chr(0b1101000 + 0o15) + chr(116) + chr(102) + chr(0b101101) + chr(0b111000)):
_xkFHo1IW7qc = jSKPaHwSAfVv.shape_list(HkFvf6riAnhp)
emKULJskFaJ8 = IDJ2eXGCBCDu.get_variable(xafqLlk3kkUe(SXOLrMavuUCe(b'>W\xdd!99>_\x03'), '\144' + chr(101) + chr(0b10111 + 0o114) + chr(0b1101111) + chr(0b1011111 + 0o5) + chr(0b1100101))(chr(12666 - 12549) + chr(0b110000 + 0o104) + chr(0b100000 + 0o106) + chr(45) + chr(2078 - 2022)), shape=_xkFHo1IW7qc, dtype=IDJ2eXGCBCDu.float32, initializer=IDJ2eXGCBCDu.zeros_initializer(), trainable=ehT0Px3KOsy9(chr(1332 - 1284) + chr(11641 - 11530) + chr(0b110000), 0b1000))
xjPLimsZRgb9 = IDJ2eXGCBCDu.exp(emKULJskFaJ8 * 3.0)
elif fVUiVobSE6m6 == xafqLlk3kkUe(SXOLrMavuUCe(b'#@\xca0\x03\n(]\x02\xbb'), chr(0b111 + 0o135) + '\145' + '\x63' + '\x6f' + '\x64' + '\x65')('\165' + chr(6287 - 6171) + chr(102) + chr(0b11100 + 0o21) + chr(56)):
xjPLimsZRgb9 = cmv9wj784cT6
elif fVUiVobSE6m6 == xafqLlk3kkUe(SXOLrMavuUCe(b'#@\xca0\x03\x159N\x17'), chr(100) + '\x65' + chr(326 - 227) + chr(3224 - 3113) + '\x64' + '\x65')('\165' + '\x74' + chr(0b1100110) + '\x2d' + chr(0b111000)):
xjPLimsZRgb9 = mXpkKTnOrT8w
return xafqLlk3kkUe(Ys555qziAbad.distributions, xafqLlk3kkUe(SXOLrMavuUCe(b'\x1d]\xdd+=\n'), chr(0b1011100 + 0o10) + chr(0b1100101) + '\x63' + '\157' + '\144' + chr(4868 - 4767))(chr(0b100011 + 0o122) + '\164' + chr(102) + chr(0b100101 + 0o10) + chr(2694 - 2638)))(loc=OnPW0EWGtsDF, scale=xjPLimsZRgb9)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
level_cond_prior
|
def level_cond_prior(prior_dist, z, latent, hparams, state):
"""Returns a conditional prior for each level.
Args:
prior_dist: Distribution conditioned on the previous levels.
z: Tensor, output of the previous levels.
latent: Tensor or a list of tensors to condition the latent_distribution.
hparams: next_frame_glow hparams.
state: Current LSTM state. Used only if hparams.latent_dist_encoder is
a lstm.
Raises:
ValueError: If hparams.latent_dist_encoder is "pointwise" and if the shape
of latent is different from z.
"""
latent_dist_encoder = hparams.get("latent_dist_encoder", None)
latent_skip = hparams.get("latent_skip", False)
if latent_dist_encoder == "pointwise":
last_latent = latent
merge_std = hparams.level_scale
latent_shape = common_layers.shape_list(latent)
z_shape = common_layers.shape_list(z)
if latent_shape != z_shape:
raise ValueError("Expected latent_shape to be %s, got %s" %
(latent_shape, z_shape))
latent_dist = scale_gaussian_prior(
"latent_prior", latent, logscale_factor=3.0)
cond_dist = merge_level_and_latent_dist(prior_dist, latent_dist,
merge_std=merge_std)
elif latent_dist_encoder == "conv_net":
output_channels = common_layers.shape_list(z)[-1]
last_latent = latent[-1]
latent_stack = tf.concat([prior_dist.loc] + latent, axis=-1)
latent_stack = noise_op(latent_stack, hparams)
cond_dist = latent_to_dist(
"latent_stack", latent_stack, hparams=hparams,
output_channels=output_channels)
elif latent_dist_encoder == "conv3d_net":
last_latent = latent[-1]
output_channels = common_layers.shape_list(last_latent)[-1]
num_steps = len(latent)
# Stack across time.
cond_latents = tf.stack(latent, axis=1)
# Concat latents from previous levels across channels.
prev_latents = tf.tile(tf.expand_dims(prior_dist.loc, axis=1),
[1, num_steps, 1, 1, 1])
cond_latents = tf.concat((cond_latents, prev_latents), axis=-1)
cond_latents = noise_op(cond_latents, hparams)
cond_dist = temporal_latent_to_dist(
"latent_stack", cond_latents, hparams, output_channels=output_channels)
elif latent_dist_encoder == "conv_lstm":
last_latent = latent
output_channels = common_layers.shape_list(z)[-1]
latent_stack = tf.concat((prior_dist.loc, latent), axis=-1)
latent_stack = noise_op(latent_stack, hparams)
_, state = common_video.conv_lstm_2d(
latent_stack, state, hparams.latent_encoder_width, kernel_size=3,
name="conv_lstm")
cond_dist = single_conv_dist(
"state_to_dist", state.h, output_channels=output_channels)
if latent_skip:
new_mean = cond_dist.loc + last_latent
cond_dist = tfp.distributions.Normal(new_mean, cond_dist.scale)
return cond_dist.loc, cond_dist.scale, state
|
python
|
def level_cond_prior(prior_dist, z, latent, hparams, state):
"""Returns a conditional prior for each level.
Args:
prior_dist: Distribution conditioned on the previous levels.
z: Tensor, output of the previous levels.
latent: Tensor or a list of tensors to condition the latent_distribution.
hparams: next_frame_glow hparams.
state: Current LSTM state. Used only if hparams.latent_dist_encoder is
a lstm.
Raises:
ValueError: If hparams.latent_dist_encoder is "pointwise" and if the shape
of latent is different from z.
"""
latent_dist_encoder = hparams.get("latent_dist_encoder", None)
latent_skip = hparams.get("latent_skip", False)
if latent_dist_encoder == "pointwise":
last_latent = latent
merge_std = hparams.level_scale
latent_shape = common_layers.shape_list(latent)
z_shape = common_layers.shape_list(z)
if latent_shape != z_shape:
raise ValueError("Expected latent_shape to be %s, got %s" %
(latent_shape, z_shape))
latent_dist = scale_gaussian_prior(
"latent_prior", latent, logscale_factor=3.0)
cond_dist = merge_level_and_latent_dist(prior_dist, latent_dist,
merge_std=merge_std)
elif latent_dist_encoder == "conv_net":
output_channels = common_layers.shape_list(z)[-1]
last_latent = latent[-1]
latent_stack = tf.concat([prior_dist.loc] + latent, axis=-1)
latent_stack = noise_op(latent_stack, hparams)
cond_dist = latent_to_dist(
"latent_stack", latent_stack, hparams=hparams,
output_channels=output_channels)
elif latent_dist_encoder == "conv3d_net":
last_latent = latent[-1]
output_channels = common_layers.shape_list(last_latent)[-1]
num_steps = len(latent)
# Stack across time.
cond_latents = tf.stack(latent, axis=1)
# Concat latents from previous levels across channels.
prev_latents = tf.tile(tf.expand_dims(prior_dist.loc, axis=1),
[1, num_steps, 1, 1, 1])
cond_latents = tf.concat((cond_latents, prev_latents), axis=-1)
cond_latents = noise_op(cond_latents, hparams)
cond_dist = temporal_latent_to_dist(
"latent_stack", cond_latents, hparams, output_channels=output_channels)
elif latent_dist_encoder == "conv_lstm":
last_latent = latent
output_channels = common_layers.shape_list(z)[-1]
latent_stack = tf.concat((prior_dist.loc, latent), axis=-1)
latent_stack = noise_op(latent_stack, hparams)
_, state = common_video.conv_lstm_2d(
latent_stack, state, hparams.latent_encoder_width, kernel_size=3,
name="conv_lstm")
cond_dist = single_conv_dist(
"state_to_dist", state.h, output_channels=output_channels)
if latent_skip:
new_mean = cond_dist.loc + last_latent
cond_dist = tfp.distributions.Normal(new_mean, cond_dist.scale)
return cond_dist.loc, cond_dist.scale, state
|
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] |
Returns a conditional prior for each level.
Args:
prior_dist: Distribution conditioned on the previous levels.
z: Tensor, output of the previous levels.
latent: Tensor or a list of tensors to condition the latent_distribution.
hparams: next_frame_glow hparams.
state: Current LSTM state. Used only if hparams.latent_dist_encoder is
a lstm.
Raises:
ValueError: If hparams.latent_dist_encoder is "pointwise" and if the shape
of latent is different from z.
|
[
"Returns",
"a",
"conditional",
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"for",
"each",
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L976-L1044
|
train
|
Returns a conditional prior for each level.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + chr(0b1 + 0o64) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x33', 4639 - 4631), ehT0Px3KOsy9('\x30' + chr(0b100000 + 0o117) + chr(1355 - 1306) + chr(845 - 796) + '\x34', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\062' + chr(53) + chr(51), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10000 + 0o43) + '\066' + chr(1653 - 1601), 12966 - 12958), ehT0Px3KOsy9(chr(48) + '\x6f' + '\063' + chr(1517 - 1467) + chr(53), 0b1000), ehT0Px3KOsy9(chr(670 - 622) + chr(0b1101111) + '\x32' + '\066' + '\060', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110000 + 0o4) + '\063', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(141 - 91) + chr(0b101010 + 0o14) + chr(0b11000 + 0o34), 2273 - 2265), ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\x6f' + chr(0b110001) + chr(2496 - 2445) + chr(1990 - 1936), ord("\x08")), ehT0Px3KOsy9(chr(1363 - 1315) + '\157' + chr(0b110110) + chr(51), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001) + chr(0b110011), 49603 - 49595), ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\157' + chr(0b10011 + 0o36) + chr(271 - 220) + chr(53), 0o10), ehT0Px3KOsy9('\060' + chr(11359 - 11248) + chr(203 - 153) + chr(705 - 655) + chr(1088 - 1034), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b11000 + 0o127) + chr(0b110001) + '\x35' + chr(963 - 910), 0b1000), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1101111) + chr(49) + '\x36' + chr(2250 - 2195), 0b1000), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101111) + '\x36' + '\x32', 17324 - 17316), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100 + 0o143) + '\x34' + chr(51), 8), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(10193 - 10082) + chr(0b110010) + chr(0b110001) + '\066', 9124 - 9116), ehT0Px3KOsy9(chr(48) + chr(10047 - 9936) + chr(0b110011) + chr(0b100000 + 0o22) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(1802 - 1754) + chr(111) + chr(0b110000 + 0o3) + '\x30' + chr(2290 - 2241), 13683 - 13675), ehT0Px3KOsy9(chr(1688 - 1640) + '\x6f' + '\x31' + chr(0b110111) + chr(2512 - 2457), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(49) + '\063' + '\x35', 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + chr(48) + '\x32', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x31' + chr(0b10010 + 0o44) + chr(851 - 799), ord("\x08")), ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\157' + '\x34' + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(293 - 244) + '\066', ord("\x08")), ehT0Px3KOsy9('\060' + chr(4636 - 4525) + '\x31' + chr(0b110111) + chr(55), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(1207 - 1157) + chr(0b110010 + 0o3) + '\061', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + '\x35' + chr(49), 8), ehT0Px3KOsy9(chr(235 - 187) + chr(0b1101111) + chr(1957 - 1904) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(1185 - 1137) + chr(0b1101111) + '\x31' + chr(0b11111 + 0o24) + '\x36', 8), ehT0Px3KOsy9('\x30' + chr(0b1100101 + 0o12) + chr(0b110111) + chr(484 - 432), 0b1000), ehT0Px3KOsy9('\060' + chr(11523 - 11412) + chr(0b101100 + 0o12) + chr(54), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b101111 + 0o100) + '\061' + chr(0b110110) + chr(0b110111), 8), ehT0Px3KOsy9('\x30' + chr(0b100001 + 0o116) + chr(243 - 192) + chr(0b110001) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\063' + chr(0b110011) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + '\064' + '\x31', 48766 - 48758), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(111) + '\x31' + '\061' + '\x36', 0b1000), ehT0Px3KOsy9(chr(1113 - 1065) + chr(7004 - 6893) + '\061' + chr(0b110000), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b111 + 0o150) + chr(0b1111 + 0o46) + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xc2'), chr(0b101111 + 0o65) + chr(8602 - 8501) + chr(99) + chr(0b1101111) + chr(3473 - 3373) + chr(101))(chr(117) + chr(9365 - 9249) + chr(0b100111 + 0o77) + chr(0b11111 + 0o16) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def PrnsB4wTsAMF(Hkm6siMkFoj8, AFGBo4BePxZi, WAc4zXt4LtrH, n4ljua2gi1Pr, KKFQISrGeiAm):
zwL8VoHC5z8O = n4ljua2gi1Pr.get(xafqLlk3kkUe(SXOLrMavuUCe(b'\x80b8\xce\x9a\xa1\xefG\xdd-GT8\xf8\x0e\x18VF\xfc'), chr(100) + '\145' + chr(0b1100011) + '\157' + chr(100) + chr(0b1100101))('\x75' + chr(8942 - 8826) + '\146' + '\x2d' + chr(0b111000)), None)
KMmaaY1GTSij = n4ljua2gi1Pr.get(xafqLlk3kkUe(SXOLrMavuUCe(b'\x80b8\xce\x9a\xa1\xefP\xdf7C'), chr(0b1100100) + chr(0b1011101 + 0o10) + chr(7032 - 6933) + '\x6f' + '\x64' + chr(1656 - 1555))('\x75' + chr(0b1101001 + 0o13) + chr(0b1100110) + chr(0b101101) + chr(0b111000)), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(111) + chr(48), ord("\x08")))
if zwL8VoHC5z8O == xafqLlk3kkUe(SXOLrMavuUCe(b'\x9cl%\xc5\x80\xa2\xd9P\xd1'), chr(0b1101 + 0o127) + chr(0b1100101) + chr(0b1100011) + '\x6f' + chr(100) + chr(8874 - 8773))(chr(937 - 820) + chr(2468 - 2352) + chr(0b1100110) + chr(241 - 196) + '\x38'):
XYA4QUh1Or4J = WAc4zXt4LtrH
fVUiVobSE6m6 = n4ljua2gi1Pr.level_scale
XhU4geNCR0zu = jSKPaHwSAfVv.shape_list(WAc4zXt4LtrH)
_xkFHo1IW7qc = jSKPaHwSAfVv.shape_list(AFGBo4BePxZi)
if XhU4geNCR0zu != _xkFHo1IW7qc:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\xa9{<\xce\x97\xa1\xd5G\x942R\x7f8\xf8\x19(AK\xef\xa1\xa4_)-TCk_\x8c\xda\x03~[Y\x03\xec\xfe\x92'), chr(0b1000 + 0o134) + chr(3752 - 3651) + chr(3225 - 3126) + chr(0b1101111) + chr(0b1100100) + chr(0b1011011 + 0o12))(chr(8628 - 8511) + '\x74' + '\146' + chr(0b101101) + chr(0b100101 + 0o23)) % (XhU4geNCR0zu, _xkFHo1IW7qc))
YMevjCDNnvXm = JATVRpFHYgRt(xafqLlk3kkUe(SXOLrMavuUCe(b'\x80b8\xce\x9a\xa1\xefS\xc67\\y'), chr(100) + chr(0b1100101) + chr(0b1100010 + 0o1) + '\157' + '\x64' + chr(101))(chr(0b1110101) + chr(0b1110100) + '\x66' + chr(0b1110 + 0o37) + chr(56)), WAc4zXt4LtrH, logscale_factor=3.0)
xiL0QpdypLLQ = V7j36UebtQ8E(Hkm6siMkFoj8, YMevjCDNnvXm, merge_std=fVUiVobSE6m6)
elif zwL8VoHC5z8O == xafqLlk3kkUe(SXOLrMavuUCe(b'\x8fl"\xdd\xab\xbb\xd5W'), chr(0b1100100) + '\145' + chr(0b1100011) + chr(111) + chr(0b1011000 + 0o14) + chr(0b1010111 + 0o16))(chr(10441 - 10324) + '\164' + '\146' + chr(45) + '\070'):
jAT42bk66WvZ = jSKPaHwSAfVv.shape_list(AFGBo4BePxZi)[-ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(0b111 + 0o150) + chr(0b110001), 0o10)]
XYA4QUh1Or4J = WAc4zXt4LtrH[-ehT0Px3KOsy9(chr(148 - 100) + chr(0b1000011 + 0o54) + chr(365 - 316), 8)]
Cr_izhltmFUy = IDJ2eXGCBCDu.concat([Hkm6siMkFoj8.MmVY7Id_ODNA] + WAc4zXt4LtrH, axis=-ehT0Px3KOsy9('\x30' + chr(3028 - 2917) + '\x31', 8))
Cr_izhltmFUy = B1HjdZtjHLgD(Cr_izhltmFUy, n4ljua2gi1Pr)
xiL0QpdypLLQ = pVJLl_2H5xnT(xafqLlk3kkUe(SXOLrMavuUCe(b'\x80b8\xce\x9a\xa1\xefP\xc0?P`'), chr(0b10000 + 0o124) + '\145' + chr(3357 - 3258) + '\157' + chr(0b111110 + 0o46) + '\x65')(chr(117) + chr(2602 - 2486) + '\x66' + '\x2d' + '\x38'), Cr_izhltmFUy, hparams=n4ljua2gi1Pr, output_channels=jAT42bk66WvZ)
elif zwL8VoHC5z8O == xafqLlk3kkUe(SXOLrMavuUCe(b'\x8fl"\xdd\xc7\xb1\xefM\xd1*'), chr(0b1100 + 0o130) + chr(0b1100101) + chr(99) + chr(4784 - 4673) + chr(0b1100100) + '\x65')('\x75' + chr(3932 - 3816) + chr(102) + chr(45) + chr(56)):
XYA4QUh1Or4J = WAc4zXt4LtrH[-ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\x6f' + chr(0b100100 + 0o15), 8)]
jAT42bk66WvZ = jSKPaHwSAfVv.shape_list(XYA4QUh1Or4J)[-ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(111) + chr(0b110000 + 0o1), 8)]
UQsgPnJC3jY0 = c2A0yzQpDQB3(WAc4zXt4LtrH)
EJNyt2wVt1N7 = IDJ2eXGCBCDu.stack(WAc4zXt4LtrH, axis=ehT0Px3KOsy9('\060' + '\157' + chr(49), 8))
xNju2N9Uy5qY = IDJ2eXGCBCDu.tile(IDJ2eXGCBCDu.expand_dims(Hkm6siMkFoj8.MmVY7Id_ODNA, axis=ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(111) + chr(49), 8)), [ehT0Px3KOsy9(chr(0b110000) + chr(0b1000100 + 0o53) + '\x31', 8), UQsgPnJC3jY0, ehT0Px3KOsy9(chr(938 - 890) + chr(0b1101111) + chr(0b110001 + 0o0), 8), ehT0Px3KOsy9(chr(202 - 154) + chr(0b1101111) + '\061', 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b11 + 0o56), 8)])
EJNyt2wVt1N7 = IDJ2eXGCBCDu.concat((EJNyt2wVt1N7, xNju2N9Uy5qY), axis=-ehT0Px3KOsy9(chr(48) + '\157' + '\061', 8))
EJNyt2wVt1N7 = B1HjdZtjHLgD(EJNyt2wVt1N7, n4ljua2gi1Pr)
xiL0QpdypLLQ = J0k8avRQFxAn(xafqLlk3kkUe(SXOLrMavuUCe(b'\x80b8\xce\x9a\xa1\xefP\xc0?P`'), '\x64' + chr(0b1000011 + 0o42) + chr(0b111001 + 0o52) + chr(6821 - 6710) + '\144' + chr(101))('\165' + chr(5177 - 5061) + chr(102) + chr(0b11001 + 0o24) + chr(604 - 548)), EJNyt2wVt1N7, n4ljua2gi1Pr, output_channels=jAT42bk66WvZ)
elif zwL8VoHC5z8O == xafqLlk3kkUe(SXOLrMavuUCe(b'\x8fl"\xdd\xab\xb9\xc3W\xd9'), chr(0b1100100) + '\145' + chr(3147 - 3048) + chr(111) + chr(100) + chr(2389 - 2288))(chr(0b1110101) + '\164' + '\146' + '\055' + chr(0b111000)):
XYA4QUh1Or4J = WAc4zXt4LtrH
jAT42bk66WvZ = jSKPaHwSAfVv.shape_list(AFGBo4BePxZi)[-ehT0Px3KOsy9(chr(48) + chr(111) + '\x31', 8)]
Cr_izhltmFUy = IDJ2eXGCBCDu.concat((Hkm6siMkFoj8.MmVY7Id_ODNA, WAc4zXt4LtrH), axis=-ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b10111 + 0o130) + chr(0b101 + 0o54), 8))
Cr_izhltmFUy = B1HjdZtjHLgD(Cr_izhltmFUy, n4ljua2gi1Pr)
(VNGQdHSFPrso, KKFQISrGeiAm) = feDooRjkbHzt.conv_lstm_2d(Cr_izhltmFUy, KKFQISrGeiAm, n4ljua2gi1Pr.latent_encoder_width, kernel_size=ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063', 8), name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x8fl"\xdd\xab\xb9\xc3W\xd9'), chr(0b110 + 0o136) + '\145' + '\143' + '\157' + chr(100) + chr(8546 - 8445))(chr(117) + '\x74' + chr(9478 - 9376) + '\055' + chr(2226 - 2170)))
xiL0QpdypLLQ = ccE3dktzRVy2(xafqLlk3kkUe(SXOLrMavuUCe(b'\x9fw-\xdf\x91\x8a\xc4L\xeb:Zx)'), chr(100) + '\145' + chr(0b1100011) + chr(0b1101111) + '\144' + '\145')(chr(117) + '\x74' + '\x66' + chr(1281 - 1236) + chr(0b10101 + 0o43)), KKFQISrGeiAm.h, output_channels=jAT42bk66WvZ)
if KMmaaY1GTSij:
OnPW0EWGtsDF = xiL0QpdypLLQ.MmVY7Id_ODNA + XYA4QUh1Or4J
xiL0QpdypLLQ = Ys555qziAbad.distributions.Normal(OnPW0EWGtsDF, xiL0QpdypLLQ.scale)
return (xafqLlk3kkUe(xiL0QpdypLLQ, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa1n\x1a\xf2\xc3\x9c\xd4|\xfb\x1a}J'), chr(0b1100100) + '\145' + chr(0b111001 + 0o52) + '\157' + chr(0b1100100) + '\x65')(chr(517 - 400) + chr(116) + '\x66' + chr(45) + chr(0b11110 + 0o32))), xafqLlk3kkUe(xiL0QpdypLLQ, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9f`-\xc7\x91'), chr(9970 - 9870) + '\145' + chr(99) + chr(111) + chr(0b101011 + 0o71) + '\x65')(chr(117) + '\x74' + '\146' + chr(45) + chr(56))), KKFQISrGeiAm)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
compute_prior
|
def compute_prior(name, z, latent, hparams, condition=False, state=None,
temperature=1.0):
"""Distribution on z_t conditioned on z_{t-1} and latent.
Args:
name: variable scope.
z: 4-D Tensor.
latent: optional,
if hparams.latent_dist_encoder == "pointwise", this is a list
of 4-D Tensors of length hparams.num_cond_latents.
else, this is just a 4-D Tensor
The first-three dimensions of the latent should be the same as z.
hparams: next_frame_glow_hparams.
condition: Whether or not to condition the distribution on latent.
state: tf.nn.rnn_cell.LSTMStateTuple.
the current state of a LSTM used to model the distribution. Used
only if hparams.latent_dist_encoder = "conv_lstm".
temperature: float, temperature with which to sample from the Gaussian.
Returns:
prior_dist: instance of tfp.distributions.Normal
state: Returns updated state.
Raises:
ValueError: If hparams.latent_dist_encoder is "pointwise" and if the shape
of latent is different from z.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
if isinstance(condition, bool):
condition = tf.constant(condition, dtype=tf.bool)
prior_dist = single_conv_dist("level_prior", z)
prior_mean, prior_scale = prior_dist.loc, prior_dist.scale
if latent is None:
mean, scale = prior_mean, prior_scale
else:
cond_mean, cond_scale, state = level_cond_prior(
prior_dist, z, latent, hparams, state)
mean, scale = tf.cond(
condition, lambda: (cond_mean, cond_scale),
lambda: (prior_mean, prior_scale))
dist = TemperedNormal(mean, scale, temperature)
return dist, state
|
python
|
def compute_prior(name, z, latent, hparams, condition=False, state=None,
temperature=1.0):
"""Distribution on z_t conditioned on z_{t-1} and latent.
Args:
name: variable scope.
z: 4-D Tensor.
latent: optional,
if hparams.latent_dist_encoder == "pointwise", this is a list
of 4-D Tensors of length hparams.num_cond_latents.
else, this is just a 4-D Tensor
The first-three dimensions of the latent should be the same as z.
hparams: next_frame_glow_hparams.
condition: Whether or not to condition the distribution on latent.
state: tf.nn.rnn_cell.LSTMStateTuple.
the current state of a LSTM used to model the distribution. Used
only if hparams.latent_dist_encoder = "conv_lstm".
temperature: float, temperature with which to sample from the Gaussian.
Returns:
prior_dist: instance of tfp.distributions.Normal
state: Returns updated state.
Raises:
ValueError: If hparams.latent_dist_encoder is "pointwise" and if the shape
of latent is different from z.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
if isinstance(condition, bool):
condition = tf.constant(condition, dtype=tf.bool)
prior_dist = single_conv_dist("level_prior", z)
prior_mean, prior_scale = prior_dist.loc, prior_dist.scale
if latent is None:
mean, scale = prior_mean, prior_scale
else:
cond_mean, cond_scale, state = level_cond_prior(
prior_dist, z, latent, hparams, state)
mean, scale = tf.cond(
condition, lambda: (cond_mean, cond_scale),
lambda: (prior_mean, prior_scale))
dist = TemperedNormal(mean, scale, temperature)
return dist, state
|
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] |
Distribution on z_t conditioned on z_{t-1} and latent.
Args:
name: variable scope.
z: 4-D Tensor.
latent: optional,
if hparams.latent_dist_encoder == "pointwise", this is a list
of 4-D Tensors of length hparams.num_cond_latents.
else, this is just a 4-D Tensor
The first-three dimensions of the latent should be the same as z.
hparams: next_frame_glow_hparams.
condition: Whether or not to condition the distribution on latent.
state: tf.nn.rnn_cell.LSTMStateTuple.
the current state of a LSTM used to model the distribution. Used
only if hparams.latent_dist_encoder = "conv_lstm".
temperature: float, temperature with which to sample from the Gaussian.
Returns:
prior_dist: instance of tfp.distributions.Normal
state: Returns updated state.
Raises:
ValueError: If hparams.latent_dist_encoder is "pointwise" and if the shape
of latent is different from z.
|
[
"Distribution",
"on",
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"-",
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L1048-L1088
|
train
|
Compute prior distribution on z_t conditioned on z_t and latent.
|
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(49) + '\x32' + chr(465 - 411), 40364 - 40356), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + '\x34', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2516 - 2465) + '\x37' + chr(685 - 632), ord("\x08")), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\x6f' + chr(393 - 344) + '\x34', 8), ehT0Px3KOsy9(chr(48) + chr(7125 - 7014) + chr(55) + '\x35', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + '\x31' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(1655 - 1607) + chr(0b111111 + 0o60) + chr(2238 - 2188) + chr(48) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + '\x37' + chr(53), 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\065' + chr(54), 4267 - 4259), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + chr(0b110100) + chr(48), 61687 - 61679), ehT0Px3KOsy9('\060' + '\157' + chr(1558 - 1503), 19750 - 19742), ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\x6f' + chr(0b110101 + 0o1) + '\064', 62996 - 62988), ehT0Px3KOsy9(chr(1314 - 1266) + chr(0b1101111) + '\x35' + chr(0b100111 + 0o17), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(2448 - 2398) + '\066' + '\062', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\067' + '\x35', 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b101011 + 0o7) + chr(0b110010) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(56 - 7) + chr(1575 - 1527) + chr(51), 40958 - 40950), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b1101111) + chr(0b110010) + chr(1250 - 1202) + '\x33', 6316 - 6308), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + chr(0b1010 + 0o47) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\062' + chr(1016 - 964) + chr(51), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b110010) + '\060' + chr(53), 16621 - 16613), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110100), 63090 - 63082), ehT0Px3KOsy9('\060' + '\x6f' + '\061' + '\x31' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(0b110110 + 0o71) + '\061' + chr(0b110010) + chr(0b110100), 56350 - 56342), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061' + chr(0b110100) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100000 + 0o21) + chr(1736 - 1681) + chr(0b110000), 46764 - 46756), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(0b11000 + 0o127) + '\061' + chr(0b101010 + 0o15), ord("\x08")), ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\x6f' + chr(0b110011) + chr(0b110000) + chr(52), 22160 - 22152), ehT0Px3KOsy9(chr(225 - 177) + '\x6f' + chr(0b10010 + 0o40) + chr(729 - 675) + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(510 - 460) + chr(48) + chr(49), 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(1991 - 1937) + '\067', 0o10), ehT0Px3KOsy9(chr(1826 - 1778) + chr(0b1001 + 0o146) + chr(914 - 860) + '\x32', 44623 - 44615), ehT0Px3KOsy9(chr(0b10000 + 0o40) + '\x6f' + chr(49) + chr(2046 - 1992), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\061' + chr(238 - 187) + chr(0b111 + 0o55), 44601 - 44593), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + chr(0b110010) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(10080 - 9969) + chr(0b110001), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + chr(48) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(1046 - 998) + chr(1515 - 1404) + chr(0b110001) + '\063' + chr(0b1100 + 0o45), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(50) + chr(0b110001) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110 + 0o60) + chr(1007 - 958), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(53) + chr(809 - 761), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'x'), chr(100) + chr(0b1100101) + '\143' + chr(0b1101111) + '\x64' + '\x65')('\x75' + chr(4685 - 4569) + chr(102) + '\055' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def sCzZ3JT4_MrX(AIvJRzLdDfgF, AFGBo4BePxZi, WAc4zXt4LtrH, n4ljua2gi1Pr, z3jGhw6b9vwa=ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(2894 - 2783) + '\x30', 0o10), KKFQISrGeiAm=None, uICaXvjWrxGa=1.0):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b' m\x8fe\\(\xed\x18q\x13d[^\xd7'), chr(100) + chr(0b1100101) + '\x63' + '\x6f' + '\144' + '\x65')(chr(0b1110101) + '\164' + chr(102) + chr(45) + chr(1629 - 1573)))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x17Y\xa9Cb\x18\xc4(}%'), chr(100) + chr(0b1100101) + chr(99) + '\157' + chr(0b1100100) + '\x65')(chr(0b1110101) + '\x74' + '\146' + chr(0b10011 + 0o32) + chr(56)))):
if PlSM16l2KDPD(z3jGhw6b9vwa, WbBjf8Y7v9VN):
z3jGhw6b9vwa = IDJ2eXGCBCDu.constant(z3jGhw6b9vwa, dtype=IDJ2eXGCBCDu.bool)
Hkm6siMkFoj8 = ccE3dktzRVy2(xafqLlk3kkUe(SXOLrMavuUCe(b':i\x8biQ\x15\xf1\x0fG\x0fu'), chr(274 - 174) + chr(6479 - 6378) + chr(0b1100011) + chr(0b1010110 + 0o31) + '\x64' + chr(0b1100101))(chr(9719 - 9602) + chr(0b1101111 + 0o5) + chr(0b1100110) + chr(0b101101) + chr(2632 - 2576)), AFGBo4BePxZi)
(cbYmnTygPYGJ, koVNpYO6vvYu) = (Hkm6siMkFoj8.MmVY7Id_ODNA, Hkm6siMkFoj8.scale)
if WAc4zXt4LtrH is None:
(aJhItC_Vawlw, xjPLimsZRgb9) = (cbYmnTygPYGJ, koVNpYO6vvYu)
else:
(jz5O135vQVBs, dgGsi6hplo6q, KKFQISrGeiAm) = PrnsB4wTsAMF(Hkm6siMkFoj8, AFGBo4BePxZi, WAc4zXt4LtrH, n4ljua2gi1Pr, KKFQISrGeiAm)
(aJhItC_Vawlw, xjPLimsZRgb9) = IDJ2eXGCBCDu.cond(z3jGhw6b9vwa, lambda : (jz5O135vQVBs, dgGsi6hplo6q), lambda : (cbYmnTygPYGJ, koVNpYO6vvYu))
ydho_1U2EnKK = Whh25RmwAjjb(aJhItC_Vawlw, xjPLimsZRgb9, uICaXvjWrxGa)
return (ydho_1U2EnKK, KKFQISrGeiAm)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
split
|
def split(name, x, reverse=False, eps=None, eps_std=None, cond_latents=None,
hparams=None, state=None, condition=False, temperature=1.0):
"""Splits / concatenates x into x1 and x2 across number of channels.
For the forward pass, x2 is assumed be gaussian,
i.e P(x2 | x1) ~ N(mu, sigma) where mu and sigma are the outputs of
a network conditioned on x1 and optionally on cond_latents.
For the reverse pass, x2 is determined from mu(x1) and sigma(x1).
This is deterministic/stochastic depending on whether eps is provided.
Args:
name: variable scope.
x: 4-D Tensor, shape (NHWC).
reverse: Forward or reverse pass.
eps: If eps is provided, x2 is set to be mu(x1) + eps * sigma(x1).
eps_std: Sample x2 with the provided eps_std.
cond_latents: optionally condition x2 on cond_latents.
hparams: next_frame_glow hparams.
state: tf.nn.rnn_cell.LSTMStateTuple.. Current state of the LSTM over z_2.
Used only when hparams.latent_dist_encoder == "conv_lstm"
condition: bool, Whether or not to condition the distribution on
cond_latents.
temperature: Temperature with which to sample from the gaussian.
Returns:
If reverse:
x: 4-D Tensor, concats input and x2 across channels.
x2: 4-D Tensor, a sample from N(mu(x1), sigma(x1))
Else:
x1: 4-D Tensor, Output of the split operation.
logpb: log-probability of x2 belonging to mu(x1), sigma(x1)
eps: 4-D Tensor, (x2 - mu(x1)) / sigma(x1)
x2: 4-D Tensor, Latent representation at the current level.
state: Current LSTM state.
4-D Tensor, only if hparams.latent_dist_encoder is set to conv_lstm.
Raises:
ValueError: If latent is provided and shape is not equal to NHW(C/2)
where (NHWC) is the size of x.
"""
# TODO(mechcoder) Change the return type to be a dict.
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
if not reverse:
x1, x2 = tf.split(x, num_or_size_splits=2, axis=-1)
# objective: P(x2|x1) ~N(x2 ; NN(x1))
prior_dist, state = compute_prior(
"prior_on_z2", x1, cond_latents, hparams, condition, state=state)
logpb = tf.reduce_sum(prior_dist.log_prob(x2), axis=[1, 2, 3])
eps = get_eps(prior_dist, x2)
return x1, logpb, eps, x2, state
else:
prior_dist, state = compute_prior(
"prior_on_z2", x, cond_latents, hparams, condition, state=state,
temperature=temperature)
if eps is not None:
x2 = set_eps(prior_dist, eps)
elif eps_std is not None:
x2 = eps_std * tf.random_normal(common_layers.shape_list(x))
else:
x2 = prior_dist.sample()
return tf.concat([x, x2], 3), x2, state
|
python
|
def split(name, x, reverse=False, eps=None, eps_std=None, cond_latents=None,
hparams=None, state=None, condition=False, temperature=1.0):
"""Splits / concatenates x into x1 and x2 across number of channels.
For the forward pass, x2 is assumed be gaussian,
i.e P(x2 | x1) ~ N(mu, sigma) where mu and sigma are the outputs of
a network conditioned on x1 and optionally on cond_latents.
For the reverse pass, x2 is determined from mu(x1) and sigma(x1).
This is deterministic/stochastic depending on whether eps is provided.
Args:
name: variable scope.
x: 4-D Tensor, shape (NHWC).
reverse: Forward or reverse pass.
eps: If eps is provided, x2 is set to be mu(x1) + eps * sigma(x1).
eps_std: Sample x2 with the provided eps_std.
cond_latents: optionally condition x2 on cond_latents.
hparams: next_frame_glow hparams.
state: tf.nn.rnn_cell.LSTMStateTuple.. Current state of the LSTM over z_2.
Used only when hparams.latent_dist_encoder == "conv_lstm"
condition: bool, Whether or not to condition the distribution on
cond_latents.
temperature: Temperature with which to sample from the gaussian.
Returns:
If reverse:
x: 4-D Tensor, concats input and x2 across channels.
x2: 4-D Tensor, a sample from N(mu(x1), sigma(x1))
Else:
x1: 4-D Tensor, Output of the split operation.
logpb: log-probability of x2 belonging to mu(x1), sigma(x1)
eps: 4-D Tensor, (x2 - mu(x1)) / sigma(x1)
x2: 4-D Tensor, Latent representation at the current level.
state: Current LSTM state.
4-D Tensor, only if hparams.latent_dist_encoder is set to conv_lstm.
Raises:
ValueError: If latent is provided and shape is not equal to NHW(C/2)
where (NHWC) is the size of x.
"""
# TODO(mechcoder) Change the return type to be a dict.
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
if not reverse:
x1, x2 = tf.split(x, num_or_size_splits=2, axis=-1)
# objective: P(x2|x1) ~N(x2 ; NN(x1))
prior_dist, state = compute_prior(
"prior_on_z2", x1, cond_latents, hparams, condition, state=state)
logpb = tf.reduce_sum(prior_dist.log_prob(x2), axis=[1, 2, 3])
eps = get_eps(prior_dist, x2)
return x1, logpb, eps, x2, state
else:
prior_dist, state = compute_prior(
"prior_on_z2", x, cond_latents, hparams, condition, state=state,
temperature=temperature)
if eps is not None:
x2 = set_eps(prior_dist, eps)
elif eps_std is not None:
x2 = eps_std * tf.random_normal(common_layers.shape_list(x))
else:
x2 = prior_dist.sample()
return tf.concat([x, x2], 3), x2, state
|
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] |
Splits / concatenates x into x1 and x2 across number of channels.
For the forward pass, x2 is assumed be gaussian,
i.e P(x2 | x1) ~ N(mu, sigma) where mu and sigma are the outputs of
a network conditioned on x1 and optionally on cond_latents.
For the reverse pass, x2 is determined from mu(x1) and sigma(x1).
This is deterministic/stochastic depending on whether eps is provided.
Args:
name: variable scope.
x: 4-D Tensor, shape (NHWC).
reverse: Forward or reverse pass.
eps: If eps is provided, x2 is set to be mu(x1) + eps * sigma(x1).
eps_std: Sample x2 with the provided eps_std.
cond_latents: optionally condition x2 on cond_latents.
hparams: next_frame_glow hparams.
state: tf.nn.rnn_cell.LSTMStateTuple.. Current state of the LSTM over z_2.
Used only when hparams.latent_dist_encoder == "conv_lstm"
condition: bool, Whether or not to condition the distribution on
cond_latents.
temperature: Temperature with which to sample from the gaussian.
Returns:
If reverse:
x: 4-D Tensor, concats input and x2 across channels.
x2: 4-D Tensor, a sample from N(mu(x1), sigma(x1))
Else:
x1: 4-D Tensor, Output of the split operation.
logpb: log-probability of x2 belonging to mu(x1), sigma(x1)
eps: 4-D Tensor, (x2 - mu(x1)) / sigma(x1)
x2: 4-D Tensor, Latent representation at the current level.
state: Current LSTM state.
4-D Tensor, only if hparams.latent_dist_encoder is set to conv_lstm.
Raises:
ValueError: If latent is provided and shape is not equal to NHW(C/2)
where (NHWC) is the size of x.
|
[
"Splits",
"/",
"concatenates",
"x",
"into",
"x1",
"and",
"x2",
"across",
"number",
"of",
"channels",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L1092-L1152
|
train
|
Splits x into x1 and x2 across number of channels.
|
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(0b1100100 + 0o13) + chr(51) + chr(0b110001 + 0o3) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\064' + chr(0b110110), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(1443 - 1395) + chr(53), 9305 - 9297), ehT0Px3KOsy9('\060' + chr(0b1010111 + 0o30) + chr(49) + chr(49) + chr(490 - 439), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(4786 - 4675) + chr(50) + chr(52) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1101111) + '\065', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011) + chr(2184 - 2129) + chr(49), 0b1000), ehT0Px3KOsy9(chr(334 - 286) + chr(11029 - 10918) + chr(0b110001 + 0o0) + chr(0b101001 + 0o7) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(7383 - 7272) + chr(0b110001) + '\061' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(5426 - 5315) + chr(0b110 + 0o53) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(245 - 194) + chr(0b110000) + chr(52), 45800 - 45792), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110011) + chr(0b110000 + 0o1) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(956 - 908) + chr(0b1101111) + chr(0b11111 + 0o23) + chr(0b101111 + 0o10) + chr(0b11100 + 0o31), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + '\x35' + '\062', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(6556 - 6445) + chr(1863 - 1813) + chr(0b110101) + chr(55), 0o10), ehT0Px3KOsy9(chr(346 - 298) + '\157' + chr(379 - 329) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(2077 - 2026) + '\064' + chr(49), 0o10), ehT0Px3KOsy9('\060' + chr(11897 - 11786) + chr(0b101010 + 0o7) + '\065' + '\066', 0b1000), ehT0Px3KOsy9('\x30' + chr(7032 - 6921) + '\063' + '\x36' + chr(54), 52705 - 52697), ehT0Px3KOsy9(chr(0b110000) + chr(4650 - 4539) + chr(50) + chr(54) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(2343 - 2293) + chr(2273 - 2222) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + chr(53) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(0b11011 + 0o33), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + chr(897 - 847) + chr(0b10010 + 0o40), 57131 - 57123), ehT0Px3KOsy9('\x30' + chr(6191 - 6080) + '\x33' + chr(0b101000 + 0o14), 35945 - 35937), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110111) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + '\x30' + chr(0b10001 + 0o41), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(1194 - 1083) + chr(1941 - 1891) + chr(2798 - 2744) + '\x31', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(514 - 464) + '\x30' + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(223 - 175) + chr(111) + chr(51) + chr(583 - 534) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(111) + '\061' + chr(1247 - 1198) + '\x30', 50026 - 50018), ehT0Px3KOsy9('\x30' + '\157' + '\062' + '\x31' + chr(0b11000 + 0o35), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b100011 + 0o114) + chr(232 - 182) + '\x30', 0b1000), ehT0Px3KOsy9('\060' + chr(0b10100 + 0o133) + chr(49) + chr(0b10011 + 0o40), 14949 - 14941), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(991 - 941) + '\061' + '\x35', 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b10001 + 0o43) + '\064', 47295 - 47287), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + chr(53) + chr(0b110110), 8), ehT0Px3KOsy9(chr(0b110000) + chr(1756 - 1645) + chr(0b1001 + 0o52) + chr(0b1010 + 0o47) + chr(0b110100), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110110) + chr(2340 - 2285), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1110 + 0o141) + '\x31' + chr(0b110100), 7760 - 7752)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(291 - 180) + chr(0b110101) + chr(48), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xca'), chr(0b1100100) + chr(0b1100101) + chr(7307 - 7208) + chr(0b1101111) + chr(2761 - 2661) + '\x65')('\165' + chr(116) + chr(0b110001 + 0o65) + chr(1479 - 1434) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def vsJU7GhuEuh6(AIvJRzLdDfgF, OeWW0F1dBPRQ, jPHyoIWAxyI_=ehT0Px3KOsy9('\060' + chr(0b111111 + 0o60) + chr(48), 0o10), ANx8zFubz7L8=None, AWsJhkHfuW0o=None, EJNyt2wVt1N7=None, n4ljua2gi1Pr=None, KKFQISrGeiAm=None, z3jGhw6b9vwa=ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x30', 8), uICaXvjWrxGa=1.0):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x92G\xb7"\xc2g\x95$\x10y\xa7\xa7\xcd\x0f'), chr(7240 - 7140) + chr(168 - 67) + '\143' + '\157' + chr(0b101 + 0o137) + chr(101))(chr(0b11111 + 0o126) + chr(10736 - 10620) + chr(102) + '\055' + chr(0b110011 + 0o5)))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa5s\x91\x04\xfcW\xbc\x14\x1cO'), '\x64' + chr(0b111101 + 0o50) + '\x63' + '\157' + '\x64' + '\x65')(chr(0b1110101) + chr(0b1110100) + chr(6526 - 6424) + '\055' + chr(1709 - 1653)))):
if not jPHyoIWAxyI_:
(pci1T9SDshKa, OVXzvB9BcGF_) = IDJ2eXGCBCDu.split(OeWW0F1dBPRQ, num_or_size_splits=ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110010), 0b1000), axis=-ehT0Px3KOsy9(chr(1520 - 1472) + chr(3132 - 3021) + chr(0b110001), 0b1000))
(Hkm6siMkFoj8, KKFQISrGeiAm) = sCzZ3JT4_MrX(xafqLlk3kkUe(SXOLrMavuUCe(b'\x94T\xac$\xd1Z\x96/\x10p\xf6'), '\x64' + chr(0b1100101) + chr(99) + '\x6f' + '\x64' + '\x65')('\165' + chr(0b11001 + 0o133) + chr(6725 - 6623) + '\x2d' + chr(0b111000)), pci1T9SDshKa, EJNyt2wVt1N7, n4ljua2gi1Pr, z3jGhw6b9vwa, state=KKFQISrGeiAm)
cUbYbjiVe_66 = IDJ2eXGCBCDu.reduce_sum(Hkm6siMkFoj8.log_prob(OVXzvB9BcGF_), axis=[ehT0Px3KOsy9('\060' + chr(111) + '\x31', 8), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1101111) + chr(50), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(1219 - 1168), ord("\x08"))])
ANx8zFubz7L8 = RyOS0GSlOI9w(Hkm6siMkFoj8, OVXzvB9BcGF_)
return (pci1T9SDshKa, cUbYbjiVe_66, ANx8zFubz7L8, OVXzvB9BcGF_, KKFQISrGeiAm)
else:
(Hkm6siMkFoj8, KKFQISrGeiAm) = sCzZ3JT4_MrX(xafqLlk3kkUe(SXOLrMavuUCe(b'\x94T\xac$\xd1Z\x96/\x10p\xf6'), chr(0b1100100) + '\145' + '\143' + chr(0b1101111) + '\x64' + '\145')('\165' + chr(10608 - 10492) + chr(0b0 + 0o146) + '\055' + '\x38'), OeWW0F1dBPRQ, EJNyt2wVt1N7, n4ljua2gi1Pr, z3jGhw6b9vwa, state=KKFQISrGeiAm, temperature=uICaXvjWrxGa)
if ANx8zFubz7L8 is not None:
OVXzvB9BcGF_ = RvG7603zrfui(Hkm6siMkFoj8, ANx8zFubz7L8)
elif AWsJhkHfuW0o is not None:
OVXzvB9BcGF_ = AWsJhkHfuW0o * IDJ2eXGCBCDu.random_normal(jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ))
else:
OVXzvB9BcGF_ = Hkm6siMkFoj8.sample()
return (xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x87I\xab(\xc2q'), chr(100) + chr(101) + chr(0b1100000 + 0o3) + chr(0b1001 + 0o146) + '\144' + chr(5605 - 5504))('\x75' + '\164' + chr(102) + chr(0b10111 + 0o26) + chr(0b111000)))([OeWW0F1dBPRQ, OVXzvB9BcGF_], ehT0Px3KOsy9(chr(0b110000) + chr(12026 - 11915) + chr(571 - 520), 8)), OVXzvB9BcGF_, KKFQISrGeiAm)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
revnet_step
|
def revnet_step(name, x, hparams, reverse=True):
"""One step of glow generative flow.
Actnorm + invertible 1X1 conv + affine_coupling.
Args:
name: used for variable scope.
x: input
hparams: coupling_width is the only hparam that is being used in
this function.
reverse: forward or reverse pass.
Returns:
z: Output of one step of reversible flow.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
if hparams.coupling == "additive":
coupling_layer = functools.partial(
additive_coupling, name="additive", reverse=reverse,
mid_channels=hparams.coupling_width,
activation=hparams.activation, dropout=hparams.coupling_dropout)
else:
coupling_layer = functools.partial(
affine_coupling, name="affine", reverse=reverse,
mid_channels=hparams.coupling_width,
activation=hparams.activation, dropout=hparams.coupling_dropout)
ops = [
functools.partial(actnorm, name="actnorm", reverse=reverse),
functools.partial(invertible_1x1_conv, name="invertible",
reverse=reverse), coupling_layer]
if reverse:
ops = ops[::-1]
objective = 0.0
for op in ops:
x, curr_obj = op(x=x)
objective += curr_obj
return x, objective
|
python
|
def revnet_step(name, x, hparams, reverse=True):
"""One step of glow generative flow.
Actnorm + invertible 1X1 conv + affine_coupling.
Args:
name: used for variable scope.
x: input
hparams: coupling_width is the only hparam that is being used in
this function.
reverse: forward or reverse pass.
Returns:
z: Output of one step of reversible flow.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
if hparams.coupling == "additive":
coupling_layer = functools.partial(
additive_coupling, name="additive", reverse=reverse,
mid_channels=hparams.coupling_width,
activation=hparams.activation, dropout=hparams.coupling_dropout)
else:
coupling_layer = functools.partial(
affine_coupling, name="affine", reverse=reverse,
mid_channels=hparams.coupling_width,
activation=hparams.activation, dropout=hparams.coupling_dropout)
ops = [
functools.partial(actnorm, name="actnorm", reverse=reverse),
functools.partial(invertible_1x1_conv, name="invertible",
reverse=reverse), coupling_layer]
if reverse:
ops = ops[::-1]
objective = 0.0
for op in ops:
x, curr_obj = op(x=x)
objective += curr_obj
return x, objective
|
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] |
One step of glow generative flow.
Actnorm + invertible 1X1 conv + affine_coupling.
Args:
name: used for variable scope.
x: input
hparams: coupling_width is the only hparam that is being used in
this function.
reverse: forward or reverse pass.
Returns:
z: Output of one step of reversible flow.
|
[
"One",
"step",
"of",
"glow",
"generative",
"flow",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L1156-L1193
|
train
|
One step of glow generative flow.
|
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(1871 - 1823) + '\x6f' + chr(51) + chr(0b11000 + 0o32) + chr(0b110000), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(0b111 + 0o57), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + '\x31', 42673 - 42665), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b1010010 + 0o35) + chr(2192 - 2142) + '\062' + chr(0b110011), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(0b110010) + chr(117 - 62), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b111000 + 0o67) + '\061' + '\x33' + '\063', 0o10), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(0b1100100 + 0o13) + chr(0b100 + 0o57) + chr(0b110 + 0o52) + chr(0b110100), 63895 - 63887), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + chr(0b110010) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + chr(50) + '\x31', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1111 + 0o43) + chr(49) + chr(0b100101 + 0o17), 0b1000), ehT0Px3KOsy9('\060' + chr(0b100100 + 0o113) + chr(464 - 415) + chr(54), 0o10), ehT0Px3KOsy9('\060' + chr(2579 - 2468) + chr(1616 - 1567) + chr(0b101000 + 0o10) + chr(1517 - 1469), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1100001 + 0o16) + chr(0b10011 + 0o36) + chr(55) + chr(0b11101 + 0o23), 0o10), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(11014 - 10903) + chr(0b101000 + 0o11) + '\067' + chr(54), 46556 - 46548), ehT0Px3KOsy9('\060' + chr(1496 - 1385) + '\065' + chr(0b110001), 55266 - 55258), ehT0Px3KOsy9(chr(48) + chr(11431 - 11320) + chr(0b110010) + chr(0b100100 + 0o14) + chr(50), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b111001 + 0o66) + chr(0b101100 + 0o7) + '\061' + chr(48), 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\x6f' + chr(49) + '\x35' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b110000 + 0o77) + chr(0b10110 + 0o33) + chr(0b110111) + '\x34', 0o10), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(2084 - 1973) + chr(2386 - 2335) + chr(0b110111), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b100 + 0o153) + '\x31' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b101000 + 0o10) + '\x6f' + chr(51) + chr(0b110101) + '\x37', 0o10), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b1010010 + 0o35) + chr(0b111 + 0o53) + chr(0b1100 + 0o45) + chr(1335 - 1283), 8), ehT0Px3KOsy9('\x30' + chr(4537 - 4426) + chr(0b110001) + chr(0b101 + 0o55) + chr(2361 - 2306), 8), ehT0Px3KOsy9('\060' + '\x6f' + '\x31' + chr(54) + '\x36', 0o10), ehT0Px3KOsy9('\060' + chr(4590 - 4479) + chr(0b110010) + chr(0b1000 + 0o52), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(54) + chr(0b11 + 0o61), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b11111 + 0o120) + chr(0b100110 + 0o15) + '\x34' + '\x33', 5973 - 5965), ehT0Px3KOsy9('\x30' + chr(0b100110 + 0o111) + chr(0b110110) + chr(0b10100 + 0o36), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1000110 + 0o51) + chr(952 - 902) + '\063' + chr(1429 - 1378), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x34' + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(48) + chr(8788 - 8677) + chr(2478 - 2423) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(51) + chr(50), 15970 - 15962), ehT0Px3KOsy9(chr(0b0 + 0o60) + '\157' + chr(0b1111 + 0o44) + chr(0b110000 + 0o4) + '\x37', 0o10), ehT0Px3KOsy9(chr(1402 - 1354) + chr(3503 - 3392) + chr(0b110011) + chr(48) + chr(0b110101), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + chr(2805 - 2752), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + chr(0b110111) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b1101111) + chr(2882 - 2828) + '\062', 8), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(0b1101111) + chr(1906 - 1857) + chr(53) + chr(49), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b111100 + 0o63) + chr(52) + chr(0b110111), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(0b1101111) + chr(0b110101) + chr(1889 - 1841), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xfe'), '\x64' + '\145' + chr(0b1100011) + '\157' + '\x64' + chr(0b1100101))(chr(0b110100 + 0o101) + chr(0b1011011 + 0o31) + chr(1891 - 1789) + chr(0b11101 + 0o20) + chr(854 - 798)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def aRdaWBBB87RJ(AIvJRzLdDfgF, OeWW0F1dBPRQ, n4ljua2gi1Pr, jPHyoIWAxyI_=ehT0Px3KOsy9(chr(2064 - 2016) + '\157' + '\x31', 0b1000)):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa6wk\xfa69\xa8\xb7\xce\xffm/\x08\x1b'), chr(0b1100100) + chr(101) + chr(0b1100011) + chr(0b1001011 + 0o44) + '\x64' + chr(3473 - 3372))('\x75' + chr(116) + chr(102) + chr(45) + '\070'))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x91CM\xdc\x08\t\x81\x87\xc2\xc9'), '\x64' + chr(101) + '\x63' + '\157' + '\x64' + chr(6245 - 6144))('\x75' + chr(3167 - 3051) + chr(0b1100110 + 0o0) + '\055' + '\070'))):
if xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb3yl\xe3;2\xaa\xb5'), '\144' + chr(0b1100101) + '\143' + chr(111) + chr(100) + chr(101))('\165' + chr(116) + '\x66' + chr(1650 - 1605) + chr(56))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1r}\xfa#2\xb2\xb7'), chr(0b1100100) + chr(9976 - 9875) + chr(0b1100011) + chr(111) + chr(100) + '\145')(chr(117) + chr(0b1110100) + chr(2092 - 1990) + chr(0b101101) + chr(2050 - 1994)):
XLqAHDr5sGMg = E6ula8_Zv1yl.partial(xe0WebfOYa8v, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1r}\xfa#2\xb2\xb7'), '\x64' + '\145' + chr(0b100001 + 0o102) + chr(111) + chr(0b1100100) + chr(0b1100101))(chr(0b10011 + 0o142) + chr(0b1110100) + chr(5188 - 5086) + '\x2d' + '\x38'), reverse=jPHyoIWAxyI_, mid_channels=n4ljua2gi1Pr.coupling_width, activation=n4ljua2gi1Pr.activation, dropout=n4ljua2gi1Pr.coupling_dropout)
else:
XLqAHDr5sGMg = E6ula8_Zv1yl.partial(Ueg0Y6WC7VSG, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1p\x7f\xfa9>'), '\144' + chr(0b100000 + 0o105) + chr(2600 - 2501) + '\157' + '\144' + chr(8264 - 8163))(chr(0b111001 + 0o74) + chr(0b1110100) + chr(102) + '\055' + '\x38'), reverse=jPHyoIWAxyI_, mid_channels=n4ljua2gi1Pr.coupling_width, activation=n4ljua2gi1Pr.activation, dropout=n4ljua2gi1Pr.coupling_dropout)
_nu2um5Q5WJf = [E6ula8_Zv1yl.partial(QuPLNjEzN1in, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1um\xfd8)\xa9'), '\x64' + '\x65' + chr(0b1100011) + chr(0b1001100 + 0o43) + chr(9388 - 9288) + '\145')(chr(0b1110101) + chr(0b101101 + 0o107) + '\146' + '\055' + chr(2394 - 2338)), reverse=jPHyoIWAxyI_), E6ula8_Zv1yl.partial(pTULwZ4Toet1, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\xb9xo\xf6%/\xad\xb0\xfd\xe9'), '\144' + chr(5221 - 5120) + '\x63' + chr(11759 - 11648) + chr(100) + chr(101))('\165' + chr(0b1110100) + chr(102) + '\x2d' + chr(0b111000)), reverse=jPHyoIWAxyI_), XLqAHDr5sGMg]
if jPHyoIWAxyI_:
_nu2um5Q5WJf = _nu2um5Q5WJf[::-ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100110 + 0o13), 8)]
Ky8KMSzRafTo = 0.0
for C8dAr6Ujq2Tn in _nu2um5Q5WJf:
(OeWW0F1dBPRQ, skPjoCNtoW4B) = C8dAr6Ujq2Tn(x=OeWW0F1dBPRQ)
Ky8KMSzRafTo += skPjoCNtoW4B
return (OeWW0F1dBPRQ, Ky8KMSzRafTo)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
revnet
|
def revnet(name, x, hparams, reverse=True):
"""'hparams.depth' steps of generative flow.
Args:
name: variable scope for the revnet block.
x: 4-D Tensor, shape=(NHWC).
hparams: HParams.
reverse: bool, forward or backward pass.
Returns:
x: 4-D Tensor, shape=(NHWC).
objective: float.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
steps = np.arange(hparams.depth)
if reverse:
steps = steps[::-1]
objective = 0.0
for step in steps:
x, curr_obj = revnet_step(
"revnet_step_%d" % step, x, hparams, reverse=reverse)
objective += curr_obj
return x, objective
|
python
|
def revnet(name, x, hparams, reverse=True):
"""'hparams.depth' steps of generative flow.
Args:
name: variable scope for the revnet block.
x: 4-D Tensor, shape=(NHWC).
hparams: HParams.
reverse: bool, forward or backward pass.
Returns:
x: 4-D Tensor, shape=(NHWC).
objective: float.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
steps = np.arange(hparams.depth)
if reverse:
steps = steps[::-1]
objective = 0.0
for step in steps:
x, curr_obj = revnet_step(
"revnet_step_%d" % step, x, hparams, reverse=reverse)
objective += curr_obj
return x, objective
|
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] |
hparams.depth' steps of generative flow.
Args:
name: variable scope for the revnet block.
x: 4-D Tensor, shape=(NHWC).
hparams: HParams.
reverse: bool, forward or backward pass.
Returns:
x: 4-D Tensor, shape=(NHWC).
objective: float.
|
[
"hparams",
".",
"depth",
"steps",
"of",
"generative",
"flow",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L1196-L1218
|
train
|
A function that computes the revnet step of the block.
|
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(0b10010 + 0o135) + chr(0b10110 + 0o34) + '\x32' + chr(0b100010 + 0o22), 40053 - 40045), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010 + 0o0) + chr(0b100011 + 0o15) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(2196 - 2148) + '\x6f' + chr(50) + '\x32' + chr(55), 15433 - 15425), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1152 - 1103) + chr(0b101110 + 0o2), 0b1000), ehT0Px3KOsy9('\060' + chr(0b110001 + 0o76) + chr(0b101111 + 0o3) + '\067' + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(5188 - 5077) + chr(53 - 3) + '\063' + chr(0b110111), 16051 - 16043), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100 + 0o55) + chr(0b1001 + 0o54) + '\061', 48228 - 48220), ehT0Px3KOsy9(chr(1751 - 1703) + chr(0b1101111) + chr(50) + chr(0b100101 + 0o22) + chr(0b101000 + 0o13), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110001) + chr(2239 - 2190) + '\066', 46336 - 46328), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011000 + 0o27) + chr(0b100001 + 0o21) + chr(1329 - 1274) + chr(1126 - 1073), 0b1000), ehT0Px3KOsy9(chr(0b1011 + 0o45) + '\157' + chr(50) + chr(54) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(661 - 613) + chr(0b1101111) + '\x31' + chr(49) + chr(0b100011 + 0o15), 22107 - 22099), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110011) + '\065' + chr(0b11110 + 0o23), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101000 + 0o7) + chr(0b110001) + chr(0b11110 + 0o31) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + chr(1220 - 1170) + '\x34', 8), ehT0Px3KOsy9(chr(2282 - 2234) + chr(8051 - 7940) + '\063' + chr(1416 - 1365) + chr(0b110000), 13459 - 13451), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + chr(481 - 427) + chr(914 - 865), 0b1000), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(0b1101111) + chr(49) + chr(1954 - 1906) + '\067', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + chr(0b10110 + 0o35) + chr(0b11011 + 0o32), 61503 - 61495), ehT0Px3KOsy9(chr(1461 - 1413) + chr(111) + chr(51) + chr(54) + '\x32', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(50) + chr(0b10000 + 0o45) + chr(1843 - 1795), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(52) + chr(0b110110), 10600 - 10592), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(51) + chr(0b101011 + 0o6) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b101 + 0o55) + '\066' + '\x36', 16345 - 16337), ehT0Px3KOsy9(chr(1431 - 1383) + '\157' + chr(0b110010) + '\x36' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1010011 + 0o34) + chr(0b101011 + 0o6) + chr(48) + chr(1059 - 1004), 8), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + '\x37' + '\061', 0b1000), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1101111) + chr(50) + '\x30' + chr(54), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110010) + '\063' + chr(0b100101 + 0o21), 12990 - 12982), ehT0Px3KOsy9('\x30' + '\157' + chr(49) + chr(0b101011 + 0o5) + chr(0b11100 + 0o26), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(10890 - 10779) + chr(0b110101), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\063' + chr(54) + chr(0b100100 + 0o20), ord("\x08")), ehT0Px3KOsy9(chr(726 - 678) + chr(0b1101111) + chr(747 - 698) + '\063' + '\066', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\063' + '\x34' + '\x33', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101010 + 0o5) + chr(51) + '\064' + chr(49), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(52) + chr(48), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1001011 + 0o44) + chr(0b110010) + chr(0b110 + 0o60) + '\x30', 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b10101 + 0o34) + chr(48), 8), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b1101111) + chr(0b110000 + 0o1) + '\067' + '\061', 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + '\060' + chr(0b110101), 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b1001011 + 0o44) + chr(2239 - 2186) + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xba'), chr(0b1000110 + 0o36) + chr(0b1100101) + '\143' + chr(111) + '\144' + chr(0b1010010 + 0o23))('\165' + '\x74' + chr(102) + chr(1898 - 1853) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def A_aCh8ip8oEC(AIvJRzLdDfgF, OeWW0F1dBPRQ, n4ljua2gi1Pr, jPHyoIWAxyI_=ehT0Px3KOsy9('\x30' + chr(0b11010 + 0o125) + chr(0b110001), 0b1000)):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b"\xe2\xe4\xe5a\xde\xfd\x05\xde\x11\xce\xd6'\x99\x1c"), '\x64' + chr(4416 - 4315) + chr(0b110110 + 0o55) + chr(0b1101111) + chr(100) + chr(0b1100101))(chr(0b1101011 + 0o12) + chr(0b1000111 + 0o55) + chr(0b1100110) + '\x2d' + '\x38'))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd5\xd0\xc3G\xe0\xcd,\xee\x1d\xf8'), '\x64' + chr(101) + chr(3697 - 3598) + '\157' + chr(0b110010 + 0o62) + chr(0b100100 + 0o101))('\165' + chr(116) + '\146' + chr(1783 - 1738) + chr(100 - 44)))):
v0VhEmlMsO_l = WqUC3KWvYVup.arange(n4ljua2gi1Pr.depth)
if jPHyoIWAxyI_:
v0VhEmlMsO_l = v0VhEmlMsO_l[::-ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(11886 - 11775) + chr(0b110001), 8)]
Ky8KMSzRafTo = 0.0
for kDuFsAhEatcU in v0VhEmlMsO_l:
(OeWW0F1dBPRQ, skPjoCNtoW4B) = aRdaWBBB87RJ(xafqLlk3kkUe(SXOLrMavuUCe(b'\xe6\xe0\xe1f\xda\xeb6\xc8:\xd8\xc5\x17\xcc\x1d'), chr(0b1100100) + chr(0b111100 + 0o51) + chr(0b1100011) + chr(3951 - 3840) + '\x64' + chr(101))('\165' + chr(116) + chr(0b1100110) + chr(45) + '\x38') % kDuFsAhEatcU, OeWW0F1dBPRQ, n4ljua2gi1Pr, reverse=jPHyoIWAxyI_)
Ky8KMSzRafTo += skPjoCNtoW4B
return (OeWW0F1dBPRQ, Ky8KMSzRafTo)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
scale_gaussian_prior
|
def scale_gaussian_prior(name, z, logscale_factor=3.0, trainable=True):
"""Returns N(s^i * z^i, std^i) where s^i and std^i are pre-component.
s^i is a learnable parameter with identity initialization.
std^i is optionally learnable with identity initialization.
Args:
name: variable scope.
z: input_tensor
logscale_factor: equivalent to scaling up the learning_rate by a factor
of logscale_factor.
trainable: Whether or not std^i is learnt.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
z_shape = common_layers.shape_list(z)
latent_multiplier = tf.get_variable(
"latent_multiplier", shape=z_shape, dtype=tf.float32,
initializer=tf.ones_initializer())
log_scale = tf.get_variable(
"log_scale_latent", shape=z_shape, dtype=tf.float32,
initializer=tf.zeros_initializer(), trainable=trainable)
log_scale = log_scale * logscale_factor
return tfp.distributions.Normal(
loc=latent_multiplier * z, scale=tf.exp(log_scale))
|
python
|
def scale_gaussian_prior(name, z, logscale_factor=3.0, trainable=True):
"""Returns N(s^i * z^i, std^i) where s^i and std^i are pre-component.
s^i is a learnable parameter with identity initialization.
std^i is optionally learnable with identity initialization.
Args:
name: variable scope.
z: input_tensor
logscale_factor: equivalent to scaling up the learning_rate by a factor
of logscale_factor.
trainable: Whether or not std^i is learnt.
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
z_shape = common_layers.shape_list(z)
latent_multiplier = tf.get_variable(
"latent_multiplier", shape=z_shape, dtype=tf.float32,
initializer=tf.ones_initializer())
log_scale = tf.get_variable(
"log_scale_latent", shape=z_shape, dtype=tf.float32,
initializer=tf.zeros_initializer(), trainable=trainable)
log_scale = log_scale * logscale_factor
return tfp.distributions.Normal(
loc=latent_multiplier * z, scale=tf.exp(log_scale))
|
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Returns N(s^i * z^i, std^i) where s^i and std^i are pre-component.
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std^i is optionally learnable with identity initialization.
Args:
name: variable scope.
z: input_tensor
logscale_factor: equivalent to scaling up the learning_rate by a factor
of logscale_factor.
trainable: Whether or not std^i is learnt.
|
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L1222-L1245
|
train
|
Returns N where s^i and std^i are pre - component.
|
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(0b1001 + 0o47) + chr(111) + '\063' + chr(1961 - 1910), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(10742 - 10631) + chr(0b0 + 0o62) + chr(0b10 + 0o63) + chr(0b11110 + 0o27), ord("\x08")), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\x6f' + '\x32' + chr(0b101100 + 0o13) + chr(51), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1100100 + 0o13) + chr(0b100 + 0o55) + chr(1367 - 1318) + chr(0b110111), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(149 - 99) + chr(53) + '\x35', 8), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + chr(51) + '\063', 0o10), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(111) + chr(50) + chr(0b110100 + 0o1) + chr(1545 - 1497), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101101 + 0o2) + chr(0b110001) + chr(983 - 931) + chr(0b110111), 0b1000), ehT0Px3KOsy9('\x30' + chr(3187 - 3076) + '\063' + chr(0b100101 + 0o13) + chr(1725 - 1677), 27727 - 27719), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x37' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(48) + chr(2376 - 2265) + chr(2440 - 2390) + '\x37' + chr(0b110100 + 0o0), 13282 - 13274), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110000 + 0o7) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b1101111) + '\x33' + chr(51) + chr(0b11011 + 0o30), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(53 - 3) + '\x36' + chr(0b100011 + 0o24), 0b1000), ehT0Px3KOsy9(chr(622 - 574) + '\x6f' + chr(1631 - 1578) + '\x35', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1011010 + 0o25) + chr(803 - 749) + chr(1616 - 1561), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(1111 - 1000) + chr(53) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(1047 - 999) + chr(0b1101111) + chr(0b110001) + chr(0b110111) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1394 - 1345), 24921 - 24913), ehT0Px3KOsy9('\060' + '\157' + chr(0b100111 + 0o14) + '\065' + chr(0b100101 + 0o17), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b101000 + 0o11) + '\064', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + chr(0b110111) + chr(0b110111), 8), ehT0Px3KOsy9(chr(0b110000) + chr(8509 - 8398) + chr(54), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + '\066' + chr(0b110010), 9409 - 9401), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1410 - 1357), 0o10), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b100011 + 0o114) + chr(0b110010) + '\064' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(2138 - 2088) + '\067' + '\x32', 0b1000), ehT0Px3KOsy9(chr(1266 - 1218) + '\157' + chr(51) + chr(52) + chr(53), 10370 - 10362), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b110000 + 0o77) + chr(814 - 763) + chr(0b110000) + chr(0b110000), 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + chr(54) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(1936 - 1888) + '\157' + '\x32' + chr(52), 52896 - 52888), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(0b1101111) + chr(0b110010) + '\x37' + '\x34', 8), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + chr(1729 - 1675) + chr(0b110101), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + chr(48) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b1010101 + 0o32) + chr(0b110011) + '\063' + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b100101 + 0o112) + chr(373 - 324) + '\067' + '\061', 2477 - 2469), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + chr(55) + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(0b1111 + 0o41) + '\x35', 7112 - 7104), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(2347 - 2298) + chr(2310 - 2258) + chr(603 - 548), 8), ehT0Px3KOsy9('\060' + chr(0b110110 + 0o71) + '\062' + chr(365 - 310) + chr(50), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(1356 - 1308) + chr(111) + chr(53) + '\060', 11483 - 11475)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'5'), chr(7943 - 7843) + chr(101) + chr(99) + chr(0b1101111) + '\x64' + chr(101))(chr(0b1100001 + 0o24) + chr(8964 - 8848) + '\146' + '\x2d' + chr(0b101000 + 0o20)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def JATVRpFHYgRt(AIvJRzLdDfgF, AFGBo4BePxZi, pTH4H_nQFAXy=3.0, blO62vIs9J6u=ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001), 8)):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'm\xcc\xc9&\xcc\xb9\xc4\x02\x9fL\xdfR\xab\xd2'), chr(3503 - 3403) + chr(0b1010100 + 0o21) + chr(0b1100011) + '\157' + chr(100) + chr(0b110100 + 0o61))(chr(0b1110101) + chr(1250 - 1134) + chr(9904 - 9802) + chr(45) + '\070'))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'Z\xf8\xef\x00\xf2\x89\xed2\x93z'), chr(7097 - 6997) + '\x65' + chr(0b1100011) + chr(0b10011 + 0o134) + chr(0b110 + 0o136) + chr(101))(chr(117) + chr(116) + chr(4113 - 4011) + chr(45) + '\070'))):
_xkFHo1IW7qc = jSKPaHwSAfVv.shape_list(AFGBo4BePxZi)
de8dHWXiT1Xd = IDJ2eXGCBCDu.get_variable(xafqLlk3kkUe(SXOLrMavuUCe(b'w\xcc\xcf*\xc3\xaf\xf7\n\xb5S\xc8T\xab\xdbDR^'), chr(100) + '\145' + chr(99) + chr(0b1101111) + '\144' + chr(0b1100101))(chr(0b1101110 + 0o7) + chr(9580 - 9464) + '\x66' + chr(1126 - 1081) + chr(56)), shape=_xkFHo1IW7qc, dtype=IDJ2eXGCBCDu.float32, initializer=IDJ2eXGCBCDu.ones_initializer())
emKULJskFaJ8 = IDJ2eXGCBCDu.get_variable(xafqLlk3kkUe(SXOLrMavuUCe(b'w\xc2\xdc\x10\xde\xb8\xc9\x0b\xa5`\xd0\\\xaf\xd2CC'), '\144' + chr(101) + '\x63' + chr(0b1100 + 0o143) + '\x64' + chr(0b1100101))(chr(9762 - 9645) + chr(0b1110100) + '\146' + chr(1748 - 1703) + '\070'), shape=_xkFHo1IW7qc, dtype=IDJ2eXGCBCDu.float32, initializer=IDJ2eXGCBCDu.zeros_initializer(), trainable=blO62vIs9J6u)
emKULJskFaJ8 = emKULJskFaJ8 * pTH4H_nQFAXy
return xafqLlk3kkUe(Ys555qziAbad.distributions, xafqLlk3kkUe(SXOLrMavuUCe(b'U\xc2\xc9"\xcc\xb7'), chr(6521 - 6421) + '\x65' + '\143' + chr(0b111101 + 0o62) + chr(2846 - 2746) + chr(0b1100101))('\165' + chr(0b1001100 + 0o50) + chr(0b1100110) + chr(0b101101) + chr(0b101 + 0o63)))(loc=de8dHWXiT1Xd * AFGBo4BePxZi, scale=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'~\xd5\xcb'), '\x64' + chr(4763 - 4662) + chr(3581 - 3482) + chr(111) + chr(0b1100100) + '\x65')(chr(117) + chr(0b111001 + 0o73) + '\146' + chr(0b101101) + chr(0b111000)))(emKULJskFaJ8))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
top_prior
|
def top_prior(name, z_shape, learn_prior="normal", temperature=1.0):
"""Unconditional prior distribution.
Args:
name: variable scope
z_shape: Shape of the mean / scale of the prior distribution.
learn_prior: Possible options are "normal" and "single_conv".
If set to "single_conv", the gaussian is parametrized by a
single convolutional layer whose input are an array of zeros
and initialized such that the mean and std are zero and one.
If set to "normal", the prior is just a Gaussian with zero
mean and unit variance.
temperature: Temperature with which to sample from the Gaussian.
Returns:
objective: 1-D Tensor shape=(batch_size,) summed across spatial components.
Raises:
ValueError: If learn_prior not in "normal" or "single_conv"
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
h = tf.zeros(z_shape, dtype=tf.float32)
if learn_prior == "normal":
prior_dist = tfp.distributions.Normal(h, tf.exp(h))
elif learn_prior == "single_conv":
prior_dist = single_conv_dist("top_learn_prior", h)
else:
raise ValueError("Expected learn_prior to be normal or single_conv "
"got %s" % learn_prior)
return TemperedNormal(prior_dist.loc, prior_dist.scale, temperature)
|
python
|
def top_prior(name, z_shape, learn_prior="normal", temperature=1.0):
"""Unconditional prior distribution.
Args:
name: variable scope
z_shape: Shape of the mean / scale of the prior distribution.
learn_prior: Possible options are "normal" and "single_conv".
If set to "single_conv", the gaussian is parametrized by a
single convolutional layer whose input are an array of zeros
and initialized such that the mean and std are zero and one.
If set to "normal", the prior is just a Gaussian with zero
mean and unit variance.
temperature: Temperature with which to sample from the Gaussian.
Returns:
objective: 1-D Tensor shape=(batch_size,) summed across spatial components.
Raises:
ValueError: If learn_prior not in "normal" or "single_conv"
"""
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
h = tf.zeros(z_shape, dtype=tf.float32)
if learn_prior == "normal":
prior_dist = tfp.distributions.Normal(h, tf.exp(h))
elif learn_prior == "single_conv":
prior_dist = single_conv_dist("top_learn_prior", h)
else:
raise ValueError("Expected learn_prior to be normal or single_conv "
"got %s" % learn_prior)
return TemperedNormal(prior_dist.loc, prior_dist.scale, temperature)
|
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",",
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",",
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")"
] |
Unconditional prior distribution.
Args:
name: variable scope
z_shape: Shape of the mean / scale of the prior distribution.
learn_prior: Possible options are "normal" and "single_conv".
If set to "single_conv", the gaussian is parametrized by a
single convolutional layer whose input are an array of zeros
and initialized such that the mean and std are zero and one.
If set to "normal", the prior is just a Gaussian with zero
mean and unit variance.
temperature: Temperature with which to sample from the Gaussian.
Returns:
objective: 1-D Tensor shape=(batch_size,) summed across spatial components.
Raises:
ValueError: If learn_prior not in "normal" or "single_conv"
|
[
"Unconditional",
"prior",
"distribution",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L1249-L1276
|
train
|
Unconditional prior distribution.
|
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' + '\061' + chr(48) + chr(53), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b111110 + 0o61) + chr(49) + chr(1978 - 1930) + '\x35', 8), ehT0Px3KOsy9(chr(593 - 545) + chr(0b1101111) + '\x31' + chr(0b110011) + chr(51), 58243 - 58235), ehT0Px3KOsy9(chr(0b1011 + 0o45) + '\x6f' + chr(51) + '\x33' + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(4578 - 4467) + chr(1446 - 1395) + chr(53) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b110000 + 0o77) + chr(0b110011) + chr(0b101010 + 0o10) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(317 - 269) + chr(111) + chr(1952 - 1902) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(7485 - 7374) + '\x31' + chr(52) + '\x32', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + chr(0b110111) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(1972 - 1924) + chr(111) + chr(0b11 + 0o64) + chr(2430 - 2378), 52799 - 52791), ehT0Px3KOsy9('\x30' + chr(6806 - 6695) + chr(324 - 275) + chr(0b11 + 0o63) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(3185 - 3074) + chr(0b110011) + '\x33' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b11111 + 0o120) + '\x31' + chr(54), 49105 - 49097), ehT0Px3KOsy9(chr(48) + chr(3167 - 3056) + '\x34' + chr(0b10011 + 0o44), 23964 - 23956), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(637 - 586) + chr(0b10000 + 0o42) + chr(1380 - 1330), 64190 - 64182), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + '\x33' + chr(380 - 326), 0b1000), ehT0Px3KOsy9(chr(1670 - 1622) + '\157' + '\x35' + chr(2861 - 2806), 59589 - 59581), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(2094 - 1983) + chr(0b110010) + chr(52) + '\064', 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x31' + chr(0b100111 + 0o16) + chr(1812 - 1760), 59574 - 59566), ehT0Px3KOsy9('\x30' + chr(5785 - 5674) + '\062' + chr(48) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(48) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1011001 + 0o26) + chr(0b101011 + 0o6) + chr(2046 - 1997) + chr(1441 - 1389), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x31' + chr(0b110001) + chr(1453 - 1401), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + '\066' + chr(0b110001), 0o10), ehT0Px3KOsy9('\060' + chr(0b100110 + 0o111) + chr(49) + chr(0b10001 + 0o45) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(111) + '\063' + chr(1598 - 1549) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + chr(0b110000), 9910 - 9902), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + chr(0b100110 + 0o17) + chr(535 - 481), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b111 + 0o150) + chr(0b110010) + chr(0b110011) + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\062' + chr(1110 - 1060) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x33' + chr(51) + chr(0b101 + 0o62), 0o10), ehT0Px3KOsy9('\060' + chr(0b10101 + 0o132) + '\061' + '\067' + '\x33', 55121 - 55113), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110110) + chr(51), 1055 - 1047), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + chr(1809 - 1758) + chr(693 - 640), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b100100 + 0o15) + chr(482 - 430) + chr(1349 - 1295), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(1826 - 1775) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(1538 - 1490) + '\x6f' + chr(49) + chr(53) + chr(0b110100), 8), ehT0Px3KOsy9(chr(1621 - 1573) + chr(0b11010 + 0o125) + '\063' + chr(51) + chr(0b101100 + 0o4), 10516 - 10508), ehT0Px3KOsy9(chr(1579 - 1531) + chr(0b1101111) + '\062' + chr(0b1100 + 0o44) + chr(0b110001), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b101000 + 0o13) + chr(0b110101) + '\x34', 15622 - 15614)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(168 - 120) + chr(9278 - 9167) + chr(0b110101) + chr(0b100001 + 0o17), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'k'), chr(100) + chr(0b110 + 0o137) + '\143' + '\x6f' + '\144' + chr(101))(chr(0b1110101) + chr(4942 - 4826) + chr(966 - 864) + '\x2d' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def w2YGKaT5EGFl(AIvJRzLdDfgF, _xkFHo1IW7qc, bT6hnv8oRvQP=xafqLlk3kkUe(SXOLrMavuUCe(b'+*)\xb6\x8c\xba'), '\x64' + chr(9817 - 9716) + chr(99) + chr(0b1101111) + chr(0b1100100) + chr(101))(chr(0b1110101) + '\x74' + chr(0b1100110) + '\x2d' + chr(1883 - 1827)), uICaXvjWrxGa=1.0):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'3$)\xb2\x8c\xb4~\x07\xa7O\x16\xb2~B'), chr(100) + '\145' + '\x63' + chr(11434 - 11323) + chr(100) + '\x65')(chr(0b1000100 + 0o61) + '\x74' + chr(0b1100110) + chr(0b1 + 0o54) + '\070'))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\x10\x0f\x94\xb2\x84W7\xaby'), '\144' + chr(0b10000 + 0o125) + chr(0b1100011) + chr(0b1101111) + chr(6653 - 6553) + chr(101))('\x75' + '\x74' + chr(0b1100110) + chr(1568 - 1523) + '\070'))):
sz4HVsFVF8nL = IDJ2eXGCBCDu.zeros(_xkFHo1IW7qc, dtype=IDJ2eXGCBCDu.float32)
if bT6hnv8oRvQP == xafqLlk3kkUe(SXOLrMavuUCe(b'+*)\xb6\x8c\xba'), '\x64' + chr(0b1100101) + chr(0b1001 + 0o132) + chr(0b1101111) + chr(0b1011000 + 0o14) + chr(0b1011100 + 0o11))(chr(0b1110101) + '\164' + chr(2459 - 2357) + '\x2d' + chr(0b11001 + 0o37)):
Hkm6siMkFoj8 = Ys555qziAbad.distributions.Normal(sz4HVsFVF8nL, IDJ2eXGCBCDu.exp(sz4HVsFVF8nL))
elif bT6hnv8oRvQP == xafqLlk3kkUe(SXOLrMavuUCe(b'6,5\xbc\x81\xb3M\x01\x97R\x03'), chr(0b111100 + 0o50) + chr(101) + chr(99) + '\x6f' + '\144' + chr(1843 - 1742))('\x75' + chr(116) + chr(0b1100110) + chr(45) + chr(0b101100 + 0o14)):
Hkm6siMkFoj8 = ccE3dktzRVy2(xafqLlk3kkUe(SXOLrMavuUCe(b'1*+\x84\x81\xb3s\x10\x96c\x05\xafgH\xa0'), chr(8772 - 8672) + chr(8009 - 7908) + '\x63' + chr(0b1000110 + 0o51) + chr(1481 - 1381) + chr(0b1010010 + 0o23))(chr(2013 - 1896) + chr(0b1101110 + 0o6) + chr(0b1100110) + '\x2d' + chr(0b111000)), sz4HVsFVF8nL)
else:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\x00=+\xbe\x8e\xa2w\x06\xd8P\x10\xbc|I\x8d.]\xcd\x03\xf1b8#Q\x15\xaf8\xc0\xf6\xe3\xb2\x1a_}\tkL\xab\xe8\x82")>\x84\x8e\xb9|\x14\xd8[\x1a\xa9.\x02\xa1'), chr(0b1100100) + '\145' + '\x63' + chr(5971 - 5860) + chr(100) + chr(0b111101 + 0o50))('\165' + '\x74' + chr(0b1011 + 0o133) + chr(0b101101) + chr(965 - 909)) % bT6hnv8oRvQP)
return Whh25RmwAjjb(xafqLlk3kkUe(Hkm6siMkFoj8, xafqLlk3kkUe(SXOLrMavuUCe(b'\x08(\r\x82\xda\x9fv=\xb7x;\x9c'), chr(100) + chr(3499 - 3398) + chr(0b1100011) + chr(0b1101111) + '\144' + '\145')(chr(117) + '\164' + chr(0b111111 + 0o47) + chr(0b101101) + '\x38')), xafqLlk3kkUe(Hkm6siMkFoj8, xafqLlk3kkUe(SXOLrMavuUCe(b'6&:\xb7\x88'), chr(0b1100100) + chr(10152 - 10051) + chr(99) + chr(0b1101111) + chr(100) + chr(0b1100101))(chr(0b110111 + 0o76) + '\x74' + '\146' + chr(45) + chr(56))), uICaXvjWrxGa)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
uniform_binning_correction
|
def uniform_binning_correction(x, n_bits=8):
"""Replaces x^i with q^i(x) = U(x, x + 1.0 / 256.0).
Args:
x: 4-D Tensor of shape (NHWC)
n_bits: optional.
Returns:
x: x ~ U(x, x + 1.0 / 256)
objective: Equivalent to -q(x)*log(q(x)).
"""
n_bins = 2**n_bits
batch_size, height, width, n_channels = common_layers.shape_list(x)
hwc = float(height * width * n_channels)
x = x + tf.random_uniform(
shape=(batch_size, height, width, n_channels),
minval=0.0, maxval=1.0/n_bins)
objective = -np.log(n_bins) * hwc * tf.ones(batch_size)
return x, objective
|
python
|
def uniform_binning_correction(x, n_bits=8):
"""Replaces x^i with q^i(x) = U(x, x + 1.0 / 256.0).
Args:
x: 4-D Tensor of shape (NHWC)
n_bits: optional.
Returns:
x: x ~ U(x, x + 1.0 / 256)
objective: Equivalent to -q(x)*log(q(x)).
"""
n_bins = 2**n_bits
batch_size, height, width, n_channels = common_layers.shape_list(x)
hwc = float(height * width * n_channels)
x = x + tf.random_uniform(
shape=(batch_size, height, width, n_channels),
minval=0.0, maxval=1.0/n_bins)
objective = -np.log(n_bins) * hwc * tf.ones(batch_size)
return x, objective
|
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Replaces x^i with q^i(x) = U(x, x + 1.0 / 256.0).
Args:
x: 4-D Tensor of shape (NHWC)
n_bits: optional.
Returns:
x: x ~ U(x, x + 1.0 / 256)
objective: Equivalent to -q(x)*log(q(x)).
|
[
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272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L1279-L1297
|
train
|
Replaces x^i with q^i ( x ) = x + q^i ( x + 1. 0 / 256. 0
|
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(111) + '\066' + '\064', 0o10), ehT0Px3KOsy9('\060' + chr(0b111001 + 0o66) + '\x33' + '\064' + '\065', 0b1000), ehT0Px3KOsy9('\060' + chr(0b111000 + 0o67) + chr(0b10001 + 0o41) + chr(0b110110) + chr(0b10101 + 0o42), 64377 - 64369), ehT0Px3KOsy9(chr(622 - 574) + chr(4639 - 4528) + chr(1353 - 1302) + chr(0b10110 + 0o36) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(714 - 666) + chr(0b1001111 + 0o40) + chr(0b110001) + '\060' + chr(0b1000 + 0o57), 0o10), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b1101111) + chr(1932 - 1882) + '\062' + '\x30', 0o10), ehT0Px3KOsy9('\060' + chr(0b1 + 0o156) + chr(0b1001 + 0o51) + '\x30' + chr(0b101110 + 0o2), 0o10), ehT0Px3KOsy9('\x30' + chr(7195 - 7084) + '\x31' + chr(2205 - 2153) + chr(0b100110 + 0o20), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b111010 + 0o65) + chr(0b101 + 0o60) + chr(0b10111 + 0o34), 0o10), ehT0Px3KOsy9('\060' + chr(0b1010011 + 0o34) + '\064' + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1100 + 0o47) + '\x34', 0b1000), ehT0Px3KOsy9(chr(2069 - 2021) + chr(111) + chr(2447 - 2397) + chr(52) + chr(1143 - 1093), 0b1000), ehT0Px3KOsy9(chr(1298 - 1250) + chr(111) + chr(0b1100 + 0o51) + '\x35', ord("\x08")), ehT0Px3KOsy9('\060' + chr(3105 - 2994) + chr(49) + chr(2781 - 2728) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001110 + 0o41) + '\x36' + chr(0b10100 + 0o34), 0b1000), ehT0Px3KOsy9(chr(0b10011 + 0o35) + '\x6f' + '\x31' + chr(631 - 579), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + chr(179 - 124) + chr(0b110101), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110110) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\x6f' + chr(0b110001) + chr(1819 - 1767), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1110 + 0o45) + '\063' + chr(1577 - 1523), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32' + chr(53) + chr(0b10110 + 0o41), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + chr(0b110111) + chr(0b101110 + 0o7), 8), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + '\066' + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(0b110001) + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + chr(1500 - 1450) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(2233 - 2184) + '\060' + chr(0b10110 + 0o37), 0o10), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(111) + chr(0b110001 + 0o1) + '\061' + chr(0b100101 + 0o22), 6628 - 6620), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + '\060' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(11180 - 11069) + chr(2301 - 2251) + chr(0b110001) + chr(48), 8), ehT0Px3KOsy9('\x30' + '\157' + chr(51) + '\x30' + chr(2490 - 2435), ord("\x08")), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(111) + '\x35' + chr(0b11110 + 0o25), 8), ehT0Px3KOsy9('\x30' + chr(9712 - 9601) + chr(0b110011) + '\063' + '\x35', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(813 - 764) + chr(0b110001) + '\x36', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(8520 - 8409) + '\061' + chr(305 - 255) + chr(0b101011 + 0o7), 0o10), ehT0Px3KOsy9(chr(419 - 371) + chr(111) + chr(50) + '\x31' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(1099 - 988) + chr(741 - 692) + chr(2446 - 2396) + '\x31', 31860 - 31852), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b100110 + 0o14) + chr(52) + chr(53), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\x32' + chr(0b110110) + chr(0b11010 + 0o34), 22642 - 22634), ehT0Px3KOsy9(chr(48) + chr(0b1001100 + 0o43) + chr(817 - 768) + chr(0b110011) + '\061', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + '\x6f' + chr(2562 - 2509) + chr(48), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x1a'), chr(9619 - 9519) + chr(101) + '\x63' + '\157' + '\x64' + chr(0b110 + 0o137))('\x75' + '\x74' + chr(0b1100110) + '\055' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def w79N1gxi7m7l(OeWW0F1dBPRQ, lYjdgHNYRgVM=ehT0Px3KOsy9(chr(0b110000) + chr(7095 - 6984) + chr(0b101110 + 0o3) + chr(48), 43114 - 43106)):
LLSk4SSpKO6g = ehT0Px3KOsy9(chr(48) + chr(6516 - 6405) + '\062', ord("\x08")) ** lYjdgHNYRgVM
(ix9dZyeAmUxY, ehbUULKuygfC, mPx09rBTrGXR, Ds92BVm147dF) = jSKPaHwSAfVv.shape_list(OeWW0F1dBPRQ)
gJockgbtna_g = kkSX4ccExqw4(ehbUULKuygfC * mPx09rBTrGXR * Ds92BVm147dF)
OeWW0F1dBPRQ = OeWW0F1dBPRQ + IDJ2eXGCBCDu.random_uniform(shape=(ix9dZyeAmUxY, ehbUULKuygfC, mPx09rBTrGXR, Ds92BVm147dF), minval=0.0, maxval=1.0 / LLSk4SSpKO6g)
Ky8KMSzRafTo = -WqUC3KWvYVup.log(LLSk4SSpKO6g) * gJockgbtna_g * IDJ2eXGCBCDu.ones(ix9dZyeAmUxY)
return (OeWW0F1dBPRQ, Ky8KMSzRafTo)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/glow_ops.py
|
encoder_decoder
|
def encoder_decoder(name, x, hparams, eps=None, reverse=False,
cond_latents=None, condition=False, states=None,
temperature=1.0):
"""Glow encoder-decoder. n_levels of (Squeeze + Flow + Split.) operations.
Args:
name: variable scope.
x: 4-D Tensor, shape=(NHWC).
hparams: HParams.
eps: Stores (glow(x) - mu) / sigma during the forward pass.
Used only to test if the network is reversible.
reverse: Forward or reverse pass.
cond_latents: list of lists of tensors.
outer length equals hparams.num_cond_latents
innter length equals hparams.num_levels - 1.
condition: If set to True, condition the encoder/decoder on cond_latents.
states: LSTM states, used only if hparams.latent_dist_encoder is set
to "conv_lstm.
temperature: Temperature set during sampling.
Returns:
x: If reverse, decoded image, else the encoded glow latent representation.
objective: log-likelihood.
eps: list of tensors, shape=(num_levels-1).
Stores (glow(x) - mu_level(x)) / sigma_level(x)) for each level.
all_latents: list of tensors, shape=(num_levels-1).
Latent representatios for each level.
new_states: list of tensors, shape=(num_levels-1).
useful only if hparams.latent_dist_encoder="conv_lstm", returns
the current state of each level.
"""
# TODO(mechcoder) Change return_type to a dict to be backward compatible.
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
if states and len(states) != hparams.n_levels - 1:
raise ValueError("Expected length of states to be %d, got %d" %
(hparams.n_levels - 1, len(states)))
if states is None:
states = [None] * (hparams.n_levels - 1)
if eps and len(eps) != hparams.n_levels - 1:
raise ValueError("Expected length of eps to be %d, got %d" %
(hparams.n_levels - 1, len(eps)))
if eps is None:
eps = [None] * (hparams.n_levels - 1)
check_cond_latents(cond_latents, hparams)
objective = 0.0
all_eps = []
all_latents = []
new_states = []
if not reverse:
# Squeeze + Flow + Split
for level in range(hparams.n_levels):
x = squeeze("squeeze_%d" % level, x, factor=2, reverse=False)
x, obj = revnet("revnet_%d" % level, x, hparams, reverse=False)
objective += obj
if level < hparams.n_levels - 1:
curr_cond_latents = get_cond_latents_at_level(
cond_latents, level, hparams)
x, obj, eps, z, state = split("split_%d" % level, x, reverse=False,
cond_latents=curr_cond_latents,
condition=condition,
hparams=hparams, state=states[level])
objective += obj
all_eps.append(eps)
all_latents.append(z)
new_states.append(state)
return x, objective, all_eps, all_latents, new_states
else:
for level in reversed(range(hparams.n_levels)):
if level < hparams.n_levels - 1:
curr_cond_latents = get_cond_latents_at_level(
cond_latents, level, hparams)
x, latent, state = split("split_%d" % level, x, eps=eps[level],
reverse=True, cond_latents=curr_cond_latents,
condition=condition, hparams=hparams,
state=states[level],
temperature=temperature)
new_states.append(state)
all_latents.append(latent)
x, obj = revnet(
"revnet_%d" % level, x, hparams=hparams, reverse=True)
objective += obj
x = squeeze("squeeze_%d" % level, x, reverse=True)
return x, objective, all_latents[::-1], new_states[::-1]
|
python
|
def encoder_decoder(name, x, hparams, eps=None, reverse=False,
cond_latents=None, condition=False, states=None,
temperature=1.0):
"""Glow encoder-decoder. n_levels of (Squeeze + Flow + Split.) operations.
Args:
name: variable scope.
x: 4-D Tensor, shape=(NHWC).
hparams: HParams.
eps: Stores (glow(x) - mu) / sigma during the forward pass.
Used only to test if the network is reversible.
reverse: Forward or reverse pass.
cond_latents: list of lists of tensors.
outer length equals hparams.num_cond_latents
innter length equals hparams.num_levels - 1.
condition: If set to True, condition the encoder/decoder on cond_latents.
states: LSTM states, used only if hparams.latent_dist_encoder is set
to "conv_lstm.
temperature: Temperature set during sampling.
Returns:
x: If reverse, decoded image, else the encoded glow latent representation.
objective: log-likelihood.
eps: list of tensors, shape=(num_levels-1).
Stores (glow(x) - mu_level(x)) / sigma_level(x)) for each level.
all_latents: list of tensors, shape=(num_levels-1).
Latent representatios for each level.
new_states: list of tensors, shape=(num_levels-1).
useful only if hparams.latent_dist_encoder="conv_lstm", returns
the current state of each level.
"""
# TODO(mechcoder) Change return_type to a dict to be backward compatible.
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
if states and len(states) != hparams.n_levels - 1:
raise ValueError("Expected length of states to be %d, got %d" %
(hparams.n_levels - 1, len(states)))
if states is None:
states = [None] * (hparams.n_levels - 1)
if eps and len(eps) != hparams.n_levels - 1:
raise ValueError("Expected length of eps to be %d, got %d" %
(hparams.n_levels - 1, len(eps)))
if eps is None:
eps = [None] * (hparams.n_levels - 1)
check_cond_latents(cond_latents, hparams)
objective = 0.0
all_eps = []
all_latents = []
new_states = []
if not reverse:
# Squeeze + Flow + Split
for level in range(hparams.n_levels):
x = squeeze("squeeze_%d" % level, x, factor=2, reverse=False)
x, obj = revnet("revnet_%d" % level, x, hparams, reverse=False)
objective += obj
if level < hparams.n_levels - 1:
curr_cond_latents = get_cond_latents_at_level(
cond_latents, level, hparams)
x, obj, eps, z, state = split("split_%d" % level, x, reverse=False,
cond_latents=curr_cond_latents,
condition=condition,
hparams=hparams, state=states[level])
objective += obj
all_eps.append(eps)
all_latents.append(z)
new_states.append(state)
return x, objective, all_eps, all_latents, new_states
else:
for level in reversed(range(hparams.n_levels)):
if level < hparams.n_levels - 1:
curr_cond_latents = get_cond_latents_at_level(
cond_latents, level, hparams)
x, latent, state = split("split_%d" % level, x, eps=eps[level],
reverse=True, cond_latents=curr_cond_latents,
condition=condition, hparams=hparams,
state=states[level],
temperature=temperature)
new_states.append(state)
all_latents.append(latent)
x, obj = revnet(
"revnet_%d" % level, x, hparams=hparams, reverse=True)
objective += obj
x = squeeze("squeeze_%d" % level, x, reverse=True)
return x, objective, all_latents[::-1], new_states[::-1]
|
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] |
Glow encoder-decoder. n_levels of (Squeeze + Flow + Split.) operations.
Args:
name: variable scope.
x: 4-D Tensor, shape=(NHWC).
hparams: HParams.
eps: Stores (glow(x) - mu) / sigma during the forward pass.
Used only to test if the network is reversible.
reverse: Forward or reverse pass.
cond_latents: list of lists of tensors.
outer length equals hparams.num_cond_latents
innter length equals hparams.num_levels - 1.
condition: If set to True, condition the encoder/decoder on cond_latents.
states: LSTM states, used only if hparams.latent_dist_encoder is set
to "conv_lstm.
temperature: Temperature set during sampling.
Returns:
x: If reverse, decoded image, else the encoded glow latent representation.
objective: log-likelihood.
eps: list of tensors, shape=(num_levels-1).
Stores (glow(x) - mu_level(x)) / sigma_level(x)) for each level.
all_latents: list of tensors, shape=(num_levels-1).
Latent representatios for each level.
new_states: list of tensors, shape=(num_levels-1).
useful only if hparams.latent_dist_encoder="conv_lstm", returns
the current state of each level.
|
[
"Glow",
"encoder",
"-",
"decoder",
".",
"n_levels",
"of",
"(",
"Squeeze",
"+",
"Flow",
"+",
"Split",
".",
")",
"operations",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/glow_ops.py#L1301-L1392
|
train
|
Glow encoder - decoder. n_levels of Squeeze + Flow + Split.
|
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(54) + '\x37', 13752 - 13744), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1000 + 0o53) + '\066' + chr(233 - 181), 56929 - 56921), ehT0Px3KOsy9(chr(1698 - 1650) + chr(6518 - 6407) + chr(1123 - 1072) + chr(0b1110 + 0o45) + chr(48), 11177 - 11169), ehT0Px3KOsy9(chr(48) + chr(0b11100 + 0o123) + '\x33' + chr(1422 - 1374) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(1047 - 999) + '\x6f' + '\x34' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b101111 + 0o4) + chr(181 - 133) + '\x37', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1011110 + 0o21) + '\x31' + '\x33' + '\067', 0b1000), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(0b101101 + 0o102) + chr(488 - 433) + chr(2772 - 2717), 0b1000), ehT0Px3KOsy9(chr(724 - 676) + chr(7122 - 7011) + '\x31' + '\063' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(48) + chr(1484 - 1373) + '\x31' + chr(1445 - 1392) + chr(1048 - 996), 0o10), ehT0Px3KOsy9(chr(0b1010 + 0o46) + '\157' + chr(957 - 907) + chr(54) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b110 + 0o52) + '\x6f' + chr(0b110010) + chr(0b1110 + 0o44) + chr(0b100001 + 0o22), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + '\x36' + chr(875 - 824), ord("\x08")), ehT0Px3KOsy9(chr(2241 - 2193) + '\157' + chr(1424 - 1373) + '\065' + chr(1720 - 1669), 6466 - 6458), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001) + chr(53) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + chr(0b10100 + 0o34), ord("\x08")), ehT0Px3KOsy9('\060' + chr(3084 - 2973) + '\062' + '\x30' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(615 - 567) + '\157' + '\061' + chr(50) + chr(54), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b10000 + 0o42) + chr(0b110101 + 0o2) + chr(1395 - 1342), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000111 + 0o50) + chr(0b101010 + 0o10) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b100101 + 0o14) + '\x33' + chr(891 - 838), 0o10), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b1101111) + '\x32' + chr(48), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + chr(2497 - 2444) + chr(0b110011), 8), ehT0Px3KOsy9(chr(48) + chr(5967 - 5856) + '\x32' + chr(0b100110 + 0o20) + chr(0b1110 + 0o45), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\062' + chr(0b110110) + '\x37', 63038 - 63030), ehT0Px3KOsy9('\060' + chr(0b1001000 + 0o47) + '\x31' + chr(521 - 466) + chr(0b1010 + 0o53), 0b1000), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(2292 - 2181) + chr(49) + '\062' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1101111) + '\062' + chr(0b110100) + '\062', 16525 - 16517), ehT0Px3KOsy9('\x30' + chr(11909 - 11798) + '\064' + chr(1403 - 1351), 19816 - 19808), ehT0Px3KOsy9(chr(173 - 125) + chr(111) + '\x32' + chr(53) + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(491 - 439) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(52) + chr(0b110001), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\063' + chr(0b1111 + 0o44), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b1111 + 0o43) + chr(0b0 + 0o62) + chr(0b110010), 0b1000), ehT0Px3KOsy9('\x30' + chr(11528 - 11417) + '\063' + chr(55) + chr(48), 51578 - 51570), ehT0Px3KOsy9('\060' + chr(7624 - 7513) + chr(49) + chr(2016 - 1961) + chr(0b100011 + 0o22), 8), ehT0Px3KOsy9('\x30' + chr(11836 - 11725) + chr(292 - 239), 8), ehT0Px3KOsy9(chr(830 - 782) + chr(111) + chr(0b110001) + '\064' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50) + chr(2696 - 2642) + chr(2362 - 2308), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b1011 + 0o144) + chr(1560 - 1507) + chr(0b110000), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x19'), '\x64' + chr(6720 - 6619) + '\x63' + chr(111) + '\x64' + chr(9549 - 9448))('\165' + chr(2611 - 2495) + chr(2956 - 2854) + chr(1410 - 1365) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def cVP8ImpbnUuk(AIvJRzLdDfgF, OeWW0F1dBPRQ, n4ljua2gi1Pr, ANx8zFubz7L8=None, jPHyoIWAxyI_=ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1770 - 1722), ord("\x08")), EJNyt2wVt1N7=None, z3jGhw6b9vwa=ehT0Px3KOsy9(chr(844 - 796) + chr(0b1110 + 0o141) + chr(0b11110 + 0o22), 8), jI0E6zso5mLP=None, uICaXvjWrxGa=1.0):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'A\x95\xaa\xabG\xa53Z\x05\x1f\xd3\xfc\x83\x8e'), '\144' + chr(0b1100101) + chr(99) + chr(0b1001100 + 0o43) + chr(0b1100100) + chr(0b1100101))(chr(12834 - 12717) + chr(0b1110100) + '\146' + chr(1674 - 1629) + chr(1727 - 1671)))(AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'v\xa1\x8c\x8dy\x95\x1aj\t)'), chr(100) + chr(101) + chr(99) + chr(7775 - 7664) + '\144' + '\145')('\x75' + '\x74' + chr(0b11001 + 0o115) + chr(45) + chr(56)))):
if jI0E6zso5mLP and c2A0yzQpDQB3(jI0E6zso5mLP) != xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'Y\xab\xb4\xa7P\xa23L'), chr(100) + chr(101) + '\143' + chr(1258 - 1147) + '\x64' + chr(101))(chr(0b1001101 + 0o50) + chr(11035 - 10919) + chr(5163 - 5061) + chr(439 - 394) + chr(0b111000))) - ehT0Px3KOsy9('\060' + '\x6f' + chr(1646 - 1597), ord("\x08")):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'r\x8c\xa8\xa7E\xb3:[z\x00\xd5\xfd\x94\x9fmIg\xe4v\xcef<d\x8e\xc0\x97\t?\x82F\xcbF\x04\x7f\xbe\xd8\x1aj\x11\x96\x12\x90'), chr(100) + '\x65' + '\143' + chr(11039 - 10928) + chr(8813 - 8713) + chr(101))(chr(0b1011000 + 0o35) + chr(0b1110100) + chr(102) + '\x2d' + chr(0b111000)) % (xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'Y\xab\xb4\xa7P\xa23L'), chr(0b1011011 + 0o11) + '\145' + chr(3391 - 3292) + chr(111) + '\144' + chr(0b1100101))('\165' + '\x74' + chr(9949 - 9847) + '\055' + '\x38')) - ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b1100 + 0o45), 8), c2A0yzQpDQB3(jI0E6zso5mLP)))
if jI0E6zso5mLP is None:
jI0E6zso5mLP = [None] * (n4ljua2gi1Pr.n_levels - ehT0Px3KOsy9(chr(678 - 630) + chr(0b1101111) + '\x31', 8))
if ANx8zFubz7L8 and c2A0yzQpDQB3(ANx8zFubz7L8) != xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'Y\xab\xb4\xa7P\xa23L'), chr(100) + chr(0b1100101) + chr(1956 - 1857) + chr(9775 - 9664) + chr(0b1001011 + 0o31) + '\x65')(chr(0b111110 + 0o67) + chr(0b1110100) + '\x66' + '\x2d' + chr(56))) - ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31', 8):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'r\x8c\xa8\xa7E\xb3:[z\x00\xd5\xfd\x94\x9fmIg\xe4v\xd8b.0\x9f\xdc\x97\x1f5\x82\x01\xcaJ\x01|\xfd\x8c] \x01'), '\x64' + chr(0b1100101) + '\x63' + chr(1516 - 1405) + chr(0b10111 + 0o115) + chr(3312 - 3211))(chr(0b110000 + 0o105) + '\164' + '\146' + chr(0b101101) + chr(56)) % (xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'Y\xab\xb4\xa7P\xa23L'), chr(0b1100100) + chr(0b1001011 + 0o32) + '\x63' + '\157' + chr(0b1010101 + 0o17) + chr(101))(chr(0b111110 + 0o67) + chr(0b1110100) + chr(102) + '\x2d' + chr(1601 - 1545))) - ehT0Px3KOsy9(chr(48) + chr(111) + chr(2340 - 2291), 8), c2A0yzQpDQB3(ANx8zFubz7L8)))
if ANx8zFubz7L8 is None:
ANx8zFubz7L8 = [None] * (n4ljua2gi1Pr.n_levels - ehT0Px3KOsy9(chr(48) + '\157' + '\x31', 8))
VAs_1jgFBuYm(EJNyt2wVt1N7, n4ljua2gi1Pr)
Ky8KMSzRafTo = 0.0
ZbV63anAa65k = []
EAmjp5vnsBda = []
VMSSkcR_XYxL = []
if not jPHyoIWAxyI_:
for K3VjCQe_lvJZ in vQr8gNKaIaWE(xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'Y\xab\xb4\xa7P\xa23L'), chr(0b1100100) + chr(6529 - 6428) + '\143' + '\157' + chr(0b100000 + 0o104) + chr(0b1100100 + 0o1))('\165' + '\x74' + '\146' + chr(0b100111 + 0o6) + chr(56)))):
OeWW0F1dBPRQ = jSEJp8iu8Nw4(xafqLlk3kkUe(SXOLrMavuUCe(b'D\x85\xad\xa7C\xbd:`\x7f\x08'), '\x64' + chr(0b1011000 + 0o15) + chr(99) + chr(4384 - 4273) + chr(7175 - 7075) + chr(0b111101 + 0o50))(chr(5913 - 5796) + chr(0b1110100) + chr(7315 - 7213) + '\x2d' + chr(1114 - 1058)) % K3VjCQe_lvJZ, OeWW0F1dBPRQ, factor=ehT0Px3KOsy9('\x30' + chr(0b11 + 0o154) + '\062', ord("\x08")), reverse=ehT0Px3KOsy9(chr(0b110000) + chr(10272 - 10161) + chr(1472 - 1424), 8))
(OeWW0F1dBPRQ, mDuDykdz0pcm) = A_aCh8ip8oEC(xafqLlk3kkUe(SXOLrMavuUCe(b'E\x91\xae\xacC\xb3\x00\x1a>'), chr(100) + chr(8330 - 8229) + '\143' + '\x6f' + '\144' + chr(10063 - 9962))(chr(0b1110101) + '\164' + '\146' + chr(0b101101) + chr(0b111000)) % K3VjCQe_lvJZ, OeWW0F1dBPRQ, n4ljua2gi1Pr, reverse=ehT0Px3KOsy9(chr(2037 - 1989) + '\157' + '\x30', 8))
Ky8KMSzRafTo += mDuDykdz0pcm
if K3VjCQe_lvJZ < xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'Y\xab\xb4\xa7P\xa23L'), chr(100) + '\x65' + chr(0b1100011) + chr(0b1001101 + 0o42) + chr(0b1100100) + '\145')(chr(0b1110101) + '\x74' + '\x66' + '\055' + '\070')) - ehT0Px3KOsy9(chr(0b110000) + chr(9283 - 9172) + chr(49), 8):
vzSoehQvzUTu = zZWeegG44oB_(EJNyt2wVt1N7, K3VjCQe_lvJZ, n4ljua2gi1Pr)
(OeWW0F1dBPRQ, mDuDykdz0pcm, ANx8zFubz7L8, AFGBo4BePxZi, KKFQISrGeiAm) = vsJU7GhuEuh6(xafqLlk3kkUe(SXOLrMavuUCe(b'D\x84\xb4\xabR\x98z['), chr(0b1100100) + chr(0b101010 + 0o73) + chr(0b1011010 + 0o11) + chr(3015 - 2904) + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + '\x74' + chr(0b1100110) + chr(0b101101) + chr(0b10100 + 0o44)) % K3VjCQe_lvJZ, OeWW0F1dBPRQ, reverse=ehT0Px3KOsy9('\060' + chr(0b1010011 + 0o34) + chr(0b110000), 8), cond_latents=vzSoehQvzUTu, condition=z3jGhw6b9vwa, hparams=n4ljua2gi1Pr, state=jI0E6zso5mLP[K3VjCQe_lvJZ])
Ky8KMSzRafTo += mDuDykdz0pcm
xafqLlk3kkUe(ZbV63anAa65k, xafqLlk3kkUe(SXOLrMavuUCe(b'V\x84\xa8\xa7H\xa3'), chr(4108 - 4008) + chr(7756 - 7655) + chr(99) + chr(2868 - 2757) + chr(100) + chr(5618 - 5517))('\x75' + '\x74' + chr(2554 - 2452) + chr(0b101101) + chr(0b1000 + 0o60)))(ANx8zFubz7L8)
xafqLlk3kkUe(EAmjp5vnsBda, xafqLlk3kkUe(SXOLrMavuUCe(b'V\x84\xa8\xa7H\xa3'), chr(0b10010 + 0o122) + chr(0b10111 + 0o116) + '\143' + chr(111) + chr(0b1100100) + '\145')(chr(117) + '\164' + chr(0b1011010 + 0o14) + chr(1492 - 1447) + chr(966 - 910)))(AFGBo4BePxZi)
xafqLlk3kkUe(VMSSkcR_XYxL, xafqLlk3kkUe(SXOLrMavuUCe(b'V\x84\xa8\xa7H\xa3'), '\x64' + '\x65' + chr(7125 - 7026) + '\x6f' + chr(0b1100100) + chr(7662 - 7561))(chr(0b1000101 + 0o60) + '\164' + chr(102) + '\x2d' + chr(1438 - 1382)))(KKFQISrGeiAm)
return (OeWW0F1dBPRQ, Ky8KMSzRafTo, ZbV63anAa65k, EAmjp5vnsBda, VMSSkcR_XYxL)
else:
for K3VjCQe_lvJZ in RFiwrCZH9Ie6(vQr8gNKaIaWE(xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'Y\xab\xb4\xa7P\xa23L'), chr(100) + chr(101) + chr(0b1100011) + chr(0b1101111) + '\x64' + '\145')(chr(117) + chr(4230 - 4114) + chr(0b1100 + 0o132) + chr(0b101101) + chr(2483 - 2427))))):
if K3VjCQe_lvJZ < xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'Y\xab\xb4\xa7P\xa23L'), chr(0b1100011 + 0o1) + chr(0b1011010 + 0o13) + '\143' + '\157' + chr(0b0 + 0o144) + '\x65')(chr(10879 - 10762) + chr(12629 - 12513) + '\146' + chr(0b101101) + '\x38')) - ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\x6f' + '\x31', 8):
vzSoehQvzUTu = zZWeegG44oB_(EJNyt2wVt1N7, K3VjCQe_lvJZ, n4ljua2gi1Pr)
(OeWW0F1dBPRQ, WAc4zXt4LtrH, KKFQISrGeiAm) = vsJU7GhuEuh6(xafqLlk3kkUe(SXOLrMavuUCe(b'D\x84\xb4\xabR\x98z['), chr(0b1100100) + chr(0b1100101) + chr(99) + '\157' + chr(0b1010101 + 0o17) + '\145')(chr(2722 - 2605) + '\164' + chr(0b1100110) + chr(0b10010 + 0o33) + '\070') % K3VjCQe_lvJZ, OeWW0F1dBPRQ, eps=ANx8zFubz7L8[K3VjCQe_lvJZ], reverse=ehT0Px3KOsy9('\x30' + chr(0b11110 + 0o121) + chr(0b11110 + 0o23), 8), cond_latents=vzSoehQvzUTu, condition=z3jGhw6b9vwa, hparams=n4ljua2gi1Pr, state=jI0E6zso5mLP[K3VjCQe_lvJZ], temperature=uICaXvjWrxGa)
xafqLlk3kkUe(VMSSkcR_XYxL, xafqLlk3kkUe(SXOLrMavuUCe(b'V\x84\xa8\xa7H\xa3'), chr(0b1100100) + '\x65' + chr(99) + '\x6f' + chr(4807 - 4707) + chr(9612 - 9511))(chr(0b1110101) + chr(0b1110100) + chr(711 - 609) + '\055' + '\070'))(KKFQISrGeiAm)
xafqLlk3kkUe(EAmjp5vnsBda, xafqLlk3kkUe(SXOLrMavuUCe(b'V\x84\xa8\xa7H\xa3'), chr(3797 - 3697) + '\145' + '\143' + chr(0b1011010 + 0o25) + chr(7377 - 7277) + chr(3095 - 2994))(chr(0b1110101) + chr(0b1110100) + chr(0b100111 + 0o77) + '\x2d' + '\070'))(WAc4zXt4LtrH)
(OeWW0F1dBPRQ, mDuDykdz0pcm) = A_aCh8ip8oEC(xafqLlk3kkUe(SXOLrMavuUCe(b'E\x91\xae\xacC\xb3\x00\x1a>'), '\x64' + chr(101) + chr(99) + '\157' + chr(100) + chr(0b1001 + 0o134))(chr(0b1110101) + chr(0b1110100) + chr(1836 - 1734) + chr(45) + chr(56)) % K3VjCQe_lvJZ, OeWW0F1dBPRQ, hparams=n4ljua2gi1Pr, reverse=ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\x6f' + chr(0b101100 + 0o5), 8))
Ky8KMSzRafTo += mDuDykdz0pcm
OeWW0F1dBPRQ = jSEJp8iu8Nw4(xafqLlk3kkUe(SXOLrMavuUCe(b'D\x85\xad\xa7C\xbd:`\x7f\x08'), '\144' + chr(0b111011 + 0o52) + chr(9304 - 9205) + chr(1771 - 1660) + chr(100) + '\145')(chr(7013 - 6896) + chr(0b11001 + 0o133) + '\146' + '\x2d' + chr(0b111000)) % K3VjCQe_lvJZ, OeWW0F1dBPRQ, reverse=ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(1832 - 1721) + '\061', 8))
return (OeWW0F1dBPRQ, Ky8KMSzRafTo, EAmjp5vnsBda[::-ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(0b1101111) + '\x31', 8)], VMSSkcR_XYxL[::-ehT0Px3KOsy9(chr(2271 - 2223) + chr(0b1101111) + chr(0b110001), 8)])
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/quantization.py
|
bfloat16_activations_var_getter
|
def bfloat16_activations_var_getter(getter, *args, **kwargs):
"""A custom getter function for float32 parameters and bfloat16 activations.
Args:
getter: custom getter
*args: arguments
**kwargs: keyword arguments
Returns:
variables with the correct dtype.
Raises:
KeyError: if "dtype" is not provided as a kwarg.
"""
requested_dtype = kwargs["dtype"]
if requested_dtype == tf.bfloat16:
kwargs["dtype"] = tf.float32
var = getter(*args, **kwargs)
# This if statement is needed to guard the cast, because batch norm
# assigns directly to the return value of this custom getter. The cast
# makes the return value not a variable so it cannot be assigned. Batch
# norm variables are always in fp32 so this if statement is never
# triggered for them.
if var.dtype.base_dtype != requested_dtype:
var = tf.cast(var, requested_dtype)
return var
|
python
|
def bfloat16_activations_var_getter(getter, *args, **kwargs):
"""A custom getter function for float32 parameters and bfloat16 activations.
Args:
getter: custom getter
*args: arguments
**kwargs: keyword arguments
Returns:
variables with the correct dtype.
Raises:
KeyError: if "dtype" is not provided as a kwarg.
"""
requested_dtype = kwargs["dtype"]
if requested_dtype == tf.bfloat16:
kwargs["dtype"] = tf.float32
var = getter(*args, **kwargs)
# This if statement is needed to guard the cast, because batch norm
# assigns directly to the return value of this custom getter. The cast
# makes the return value not a variable so it cannot be assigned. Batch
# norm variables are always in fp32 so this if statement is never
# triggered for them.
if var.dtype.base_dtype != requested_dtype:
var = tf.cast(var, requested_dtype)
return var
|
[
"def",
"bfloat16_activations_var_getter",
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",",
"*",
"args",
",",
"*",
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"[",
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"# This if statement is needed to guard the cast, because batch norm",
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"# triggered for them.",
"if",
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"(",
"var",
",",
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] |
A custom getter function for float32 parameters and bfloat16 activations.
Args:
getter: custom getter
*args: arguments
**kwargs: keyword arguments
Returns:
variables with the correct dtype.
Raises:
KeyError: if "dtype" is not provided as a kwarg.
|
[
"A",
"custom",
"getter",
"function",
"for",
"float32",
"parameters",
"and",
"bfloat16",
"activations",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/quantization.py#L25-L48
|
train
|
A custom getter function for float32 parameters and bfloat16 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('\060' + chr(111) + chr(0b110001) + chr(52), 36611 - 36603), ehT0Px3KOsy9('\060' + chr(820 - 709) + '\062' + '\x30' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(111) + chr(545 - 494) + '\060' + chr(2000 - 1948), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1110 + 0o45) + chr(0b110111 + 0o0) + chr(2301 - 2248), ord("\x08")), ehT0Px3KOsy9(chr(1476 - 1428) + chr(5608 - 5497) + chr(0b110011) + chr(0b110100) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + chr(7507 - 7396) + '\x31' + '\064' + chr(563 - 511), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x32' + '\067' + '\067', 0b1000), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(1999 - 1888) + '\062' + chr(0b101010 + 0o12) + chr(0b11 + 0o55), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b0 + 0o61) + chr(0b101111 + 0o7) + chr(2258 - 2205), ord("\x08")), ehT0Px3KOsy9(chr(1338 - 1290) + chr(111) + '\x32' + '\061' + chr(1470 - 1419), 14397 - 14389), ehT0Px3KOsy9(chr(0b110000) + chr(12181 - 12070) + '\x33' + chr(52) + chr(2547 - 2494), 17812 - 17804), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10001 + 0o40) + chr(0b110011) + chr(0b110001), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\065' + chr(54), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1100110 + 0o11) + chr(2600 - 2548) + chr(0b110111), 24389 - 24381), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110 + 0o54) + chr(0b110001) + chr(0b110011), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110101) + chr(0b1101 + 0o45), 0b1000), ehT0Px3KOsy9(chr(859 - 811) + chr(0b110101 + 0o72) + chr(0b101100 + 0o5) + chr(0b110101) + chr(0b111 + 0o54), 54512 - 54504), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(51) + chr(630 - 577) + chr(1409 - 1361), 29619 - 29611), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + chr(0b11110 + 0o22) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(2211 - 2163) + '\157' + chr(843 - 792) + chr(0b11100 + 0o33) + chr(0b101011 + 0o5), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110011) + chr(0b110101) + chr(53), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001) + chr(0b101011 + 0o11) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011010 + 0o25) + chr(1930 - 1879) + chr(54) + chr(400 - 352), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(0b11000 + 0o37) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + '\060', 0b1000), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1101111) + chr(54) + '\x31', 37141 - 37133), ehT0Px3KOsy9(chr(1850 - 1802) + chr(0b1101111) + '\x35' + chr(1081 - 1032), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\064' + '\x34', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + '\x34', 0o10), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(111) + chr(0b10011 + 0o41) + '\x34', 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + '\x36' + chr(0b110111), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b100011 + 0o16) + '\x36' + chr(127 - 77), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + chr(0b110111) + '\x30', 42346 - 42338), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(0b100111 + 0o12) + chr(0b111 + 0o54), 8), ehT0Px3KOsy9('\x30' + '\157' + '\x32' + chr(0b110111) + chr(0b110110), 29699 - 29691), ehT0Px3KOsy9(chr(0b110000) + chr(0b10 + 0o155) + chr(49) + chr(55) + chr(48), 8), ehT0Px3KOsy9(chr(1164 - 1116) + '\157' + '\062' + '\063' + chr(2497 - 2445), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + chr(0b10011 + 0o41) + '\063', 0o10), ehT0Px3KOsy9(chr(1469 - 1421) + '\157' + chr(446 - 397) + chr(0b110011) + chr(48), 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + chr(0b110000 + 0o0) + '\x33', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(53) + '\060', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'"'), chr(0b1100100) + chr(4563 - 4462) + '\143' + chr(0b1101111) + '\144' + '\145')(chr(0b1110101) + chr(9514 - 9398) + chr(0b101010 + 0o74) + '\055' + chr(716 - 660)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def mRleLTcw02L8(XGjmdKmSZ8Qs, *kJDRfRhcZHjS, **M8EIoTs2GJXE):
iZaeiSw52vim = M8EIoTs2GJXE[xafqLlk3kkUe(SXOLrMavuUCe(b'h\xf3\xbd\x8d\x85'), '\x64' + chr(9585 - 9484) + chr(0b1000100 + 0o37) + chr(111) + chr(0b1100100) + chr(0b1001000 + 0o35))(chr(0b1110101) + '\x74' + chr(2991 - 2889) + '\x2d' + '\070')]
if iZaeiSw52vim == xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'n\xe1\xa8\x92\x81\x10\x8e\x96'), chr(0b1100100) + chr(101) + chr(99) + '\157' + chr(100) + chr(0b1100001 + 0o4))('\165' + '\164' + chr(102) + '\055' + chr(1504 - 1448))):
M8EIoTs2GJXE[xafqLlk3kkUe(SXOLrMavuUCe(b'h\xf3\xbd\x8d\x85'), '\144' + '\x65' + '\143' + '\157' + chr(7710 - 7610) + chr(101))(chr(0b1101001 + 0o14) + chr(0b1110100) + chr(0b1100110) + '\055' + chr(0b100110 + 0o22))] = IDJ2eXGCBCDu.float32
l38lb8xQZNsE = XGjmdKmSZ8Qs(*kJDRfRhcZHjS, **M8EIoTs2GJXE)
if xafqLlk3kkUe(l38lb8xQZNsE.dtype, xafqLlk3kkUe(SXOLrMavuUCe(b'n\xe6\xb7\x98\xbf\x00\xcb\xd9\x05\xee'), '\144' + '\x65' + chr(99) + '\x6f' + chr(0b1010101 + 0o17) + '\x65')(chr(117) + chr(116) + chr(0b1100110) + chr(0b101101) + chr(0b110010 + 0o6))) != iZaeiSw52vim:
l38lb8xQZNsE = IDJ2eXGCBCDu.cast(l38lb8xQZNsE, iZaeiSw52vim)
return l38lb8xQZNsE
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/quantization.py
|
float16_activations_var_getter
|
def float16_activations_var_getter(getter, *args, **kwargs):
"""A custom getter function for float32 parameters and float16 activations.
This function ensures the following:
1. All variables requested with type fp16 are stored as type fp32.
2. All variables requested with type fp32 are returned as type fp16.
See https://docs.nvidia.com/deeplearning/sdk/mixed-precision-training/
#training_tensorflow for more information on this strategy.
Args:
getter: custom getter
*args: arguments
**kwargs: keyword arguments
Returns:
variables with the correct dtype.
Raises:
KeyError: if "dtype" is not provided as a kwarg.
"""
requested_dtype = kwargs["dtype"]
if requested_dtype == tf.float16:
kwargs["dtype"] = tf.float32
if requested_dtype == tf.float32:
requested_dtype = tf.float16
var = getter(*args, **kwargs)
# This if statement is needed to guard the cast, because batch norm
# assigns directly to the return value of this custom getter. The cast
# makes the return value not a variable so it cannot be assigned. Batch
# norm variables are always in fp32 so this if statement is never
# triggered for them.
if var.dtype.base_dtype != requested_dtype:
var = tf.cast(var, requested_dtype)
return var
|
python
|
def float16_activations_var_getter(getter, *args, **kwargs):
"""A custom getter function for float32 parameters and float16 activations.
This function ensures the following:
1. All variables requested with type fp16 are stored as type fp32.
2. All variables requested with type fp32 are returned as type fp16.
See https://docs.nvidia.com/deeplearning/sdk/mixed-precision-training/
#training_tensorflow for more information on this strategy.
Args:
getter: custom getter
*args: arguments
**kwargs: keyword arguments
Returns:
variables with the correct dtype.
Raises:
KeyError: if "dtype" is not provided as a kwarg.
"""
requested_dtype = kwargs["dtype"]
if requested_dtype == tf.float16:
kwargs["dtype"] = tf.float32
if requested_dtype == tf.float32:
requested_dtype = tf.float16
var = getter(*args, **kwargs)
# This if statement is needed to guard the cast, because batch norm
# assigns directly to the return value of this custom getter. The cast
# makes the return value not a variable so it cannot be assigned. Batch
# norm variables are always in fp32 so this if statement is never
# triggered for them.
if var.dtype.base_dtype != requested_dtype:
var = tf.cast(var, requested_dtype)
return var
|
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] |
A custom getter function for float32 parameters and float16 activations.
This function ensures the following:
1. All variables requested with type fp16 are stored as type fp32.
2. All variables requested with type fp32 are returned as type fp16.
See https://docs.nvidia.com/deeplearning/sdk/mixed-precision-training/
#training_tensorflow for more information on this strategy.
Args:
getter: custom getter
*args: arguments
**kwargs: keyword arguments
Returns:
variables with the correct dtype.
Raises:
KeyError: if "dtype" is not provided as a kwarg.
|
[
"A",
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/quantization.py#L51-L86
|
train
|
A custom getter function for float32 parameters and float16 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(0b110000) + chr(8625 - 8514) + chr(0b10110 + 0o33) + chr(0b110010) + chr(48), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b111010 + 0o65) + chr(647 - 596) + chr(0b110011) + '\x34', 0o10), ehT0Px3KOsy9('\060' + chr(0b1010011 + 0o34) + chr(0b110001) + chr(2304 - 2256), 0b1000), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(0b1101111) + chr(0b11111 + 0o23) + chr(0b11100 + 0o32) + '\067', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b1010 + 0o51) + '\065' + chr(0b1100 + 0o46), 23856 - 23848), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b1101111) + chr(1872 - 1821) + '\067' + chr(0b11010 + 0o30), 14934 - 14926), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(1710 - 1662) + chr(51), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1849 - 1798) + '\061' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(1697 - 1643) + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(9981 - 9870) + chr(0b11100 + 0o27) + chr(52) + chr(852 - 804), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(7708 - 7597) + chr(1256 - 1205) + '\066' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x32' + chr(48) + chr(50), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(50) + chr(0b110101) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + '\x30' + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(10471 - 10360) + chr(170 - 118) + '\064', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b101000 + 0o13) + chr(1172 - 1122) + '\062', 0b1000), ehT0Px3KOsy9(chr(1951 - 1903) + chr(681 - 570) + chr(129 - 77) + chr(0b1101 + 0o44), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000111 + 0o50) + chr(0b110011) + '\066' + chr(569 - 519), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + chr(50) + chr(48), 61235 - 61227), ehT0Px3KOsy9('\x30' + chr(0b111 + 0o150) + '\061' + chr(1165 - 1116) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(1931 - 1883) + chr(5274 - 5163) + chr(0b110011) + '\067' + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(2356 - 2302) + chr(55), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + chr(0b110001) + chr(49), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + '\x32' + '\065', 64002 - 63994), ehT0Px3KOsy9(chr(151 - 103) + '\x6f' + '\061' + '\x36' + chr(48), 43967 - 43959), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + '\x36' + chr(1931 - 1881), ord("\x08")), ehT0Px3KOsy9(chr(959 - 911) + chr(0b1101111) + '\061' + chr(0b1100 + 0o44) + chr(48), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1011101 + 0o22) + '\x33' + '\x37' + chr(48), 0o10), ehT0Px3KOsy9('\x30' + chr(7310 - 7199) + chr(0b110011 + 0o0) + chr(1450 - 1402) + chr(2645 - 2590), 55910 - 55902), ehT0Px3KOsy9(chr(552 - 504) + chr(0b100011 + 0o114) + chr(49) + chr(49) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(0b1101010 + 0o5) + chr(50) + '\x33', 21525 - 21517), ehT0Px3KOsy9(chr(63 - 15) + chr(111) + chr(1376 - 1326) + '\x34' + chr(0b110001), 27275 - 27267), ehT0Px3KOsy9('\060' + '\x6f' + chr(448 - 399) + '\x35' + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(111) + chr(51) + chr(0b110010) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(205 - 157) + chr(524 - 413) + '\061' + chr(53) + chr(57 - 9), 43624 - 43616), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + '\061' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(0b1100111 + 0o10) + '\x33', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\x36' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110 + 0o61) + '\x32', 4532 - 4524), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110011) + chr(0b110100) + '\x36', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\065' + chr(48), 42196 - 42188)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'~'), '\144' + '\145' + chr(99) + chr(9245 - 9134) + chr(0b1100100) + '\145')(chr(0b110 + 0o157) + chr(116) + chr(0b100 + 0o142) + chr(0b11011 + 0o22) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Hs43uYM_qzNs(XGjmdKmSZ8Qs, *kJDRfRhcZHjS, **M8EIoTs2GJXE):
iZaeiSw52vim = M8EIoTs2GJXE[xafqLlk3kkUe(SXOLrMavuUCe(b'4\xa8q\xc7\x8f'), chr(5412 - 5312) + '\145' + '\x63' + chr(2738 - 2627) + chr(0b1100100) + chr(0b100110 + 0o77))(chr(5712 - 5595) + chr(0b1100011 + 0o21) + chr(0b1011100 + 0o12) + chr(45) + chr(0b10100 + 0o44))]
if iZaeiSw52vim == xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'6\xb0g\xd6\x9e\xcb\xb5'), chr(0b1001111 + 0o25) + chr(0b110001 + 0o64) + chr(0b1100011) + chr(6155 - 6044) + chr(100) + chr(101))(chr(4105 - 3988) + chr(0b1110010 + 0o2) + chr(3257 - 3155) + chr(0b101101) + chr(0b111000))):
M8EIoTs2GJXE[xafqLlk3kkUe(SXOLrMavuUCe(b'4\xa8q\xc7\x8f'), '\x64' + chr(0b1010001 + 0o24) + chr(7383 - 7284) + '\157' + chr(100) + chr(0b10101 + 0o120))('\165' + chr(0b1110011 + 0o1) + chr(0b1100110) + chr(0b101101) + '\070')] = IDJ2eXGCBCDu.float32
if iZaeiSw52vim == xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'6\xb0g\xd6\x9e\xc9\xb1'), '\x64' + chr(0b1 + 0o144) + chr(99) + chr(111) + '\144' + chr(9343 - 9242))(chr(8793 - 8676) + chr(116) + chr(0b1100110) + '\055' + '\070')):
iZaeiSw52vim = IDJ2eXGCBCDu.float16
l38lb8xQZNsE = XGjmdKmSZ8Qs(*kJDRfRhcZHjS, **M8EIoTs2GJXE)
if xafqLlk3kkUe(l38lb8xQZNsE.dtype, xafqLlk3kkUe(SXOLrMavuUCe(b'2\xbd{\xd2\xb5\x9e\xf7\xb7@\x85'), chr(0b1100100) + chr(101) + chr(99) + '\157' + chr(1021 - 921) + '\145')('\x75' + '\164' + '\x66' + '\x2d' + '\x38')) != iZaeiSw52vim:
l38lb8xQZNsE = IDJ2eXGCBCDu.cast(l38lb8xQZNsE, iZaeiSw52vim)
return l38lb8xQZNsE
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/quantization.py
|
simulated_quantize
|
def simulated_quantize(x, num_bits, noise):
"""Simulate quantization to num_bits bits, with externally-stored scale.
num_bits is the number of bits used to store each value.
noise is a float32 Tensor containing values in [0, 1).
Each value in noise should take different values across
different steps, approximating a uniform distribution over [0, 1).
In the case of replicated TPU training, noise should be identical
across replicas in order to keep the parameters identical across replicas.
The natural choice for noise would be tf.random_uniform(),
but this is not possible for TPU, since there is currently no way to seed
the different cores to produce identical values across replicas. Instead we
use noise_from_step_num() (see below).
The quantization scheme is as follows:
Compute the maximum absolute value by row (call this max_abs).
Store this either in an auxiliary variable or in an extra column.
Divide the parameters by (max_abs / (2^(num_bits-1)-1)). This gives a
float32 value in the range [-2^(num_bits-1)-1, 2^(num_bits-1)-1]
Unbiased randomized roundoff by adding noise and rounding down.
This produces a signed integer with num_bits bits which can then be stored.
Args:
x: a float32 Tensor
num_bits: an integer between 1 and 22
noise: a float Tensor broadcastable to the shape of x.
Returns:
a float32 Tensor
"""
shape = x.get_shape().as_list()
if not (len(shape) >= 2 and shape[-1] > 1):
return x
max_abs = tf.reduce_max(tf.abs(x), -1, keepdims=True) + 1e-9
max_int = 2 ** (num_bits - 1) - 1
scale = max_abs / max_int
x /= scale
x = tf.floor(x + noise)
# dequantize before storing (since this is a simulation)
x *= scale
return x
|
python
|
def simulated_quantize(x, num_bits, noise):
"""Simulate quantization to num_bits bits, with externally-stored scale.
num_bits is the number of bits used to store each value.
noise is a float32 Tensor containing values in [0, 1).
Each value in noise should take different values across
different steps, approximating a uniform distribution over [0, 1).
In the case of replicated TPU training, noise should be identical
across replicas in order to keep the parameters identical across replicas.
The natural choice for noise would be tf.random_uniform(),
but this is not possible for TPU, since there is currently no way to seed
the different cores to produce identical values across replicas. Instead we
use noise_from_step_num() (see below).
The quantization scheme is as follows:
Compute the maximum absolute value by row (call this max_abs).
Store this either in an auxiliary variable or in an extra column.
Divide the parameters by (max_abs / (2^(num_bits-1)-1)). This gives a
float32 value in the range [-2^(num_bits-1)-1, 2^(num_bits-1)-1]
Unbiased randomized roundoff by adding noise and rounding down.
This produces a signed integer with num_bits bits which can then be stored.
Args:
x: a float32 Tensor
num_bits: an integer between 1 and 22
noise: a float Tensor broadcastable to the shape of x.
Returns:
a float32 Tensor
"""
shape = x.get_shape().as_list()
if not (len(shape) >= 2 and shape[-1] > 1):
return x
max_abs = tf.reduce_max(tf.abs(x), -1, keepdims=True) + 1e-9
max_int = 2 ** (num_bits - 1) - 1
scale = max_abs / max_int
x /= scale
x = tf.floor(x + noise)
# dequantize before storing (since this is a simulation)
x *= scale
return x
|
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] |
Simulate quantization to num_bits bits, with externally-stored scale.
num_bits is the number of bits used to store each value.
noise is a float32 Tensor containing values in [0, 1).
Each value in noise should take different values across
different steps, approximating a uniform distribution over [0, 1).
In the case of replicated TPU training, noise should be identical
across replicas in order to keep the parameters identical across replicas.
The natural choice for noise would be tf.random_uniform(),
but this is not possible for TPU, since there is currently no way to seed
the different cores to produce identical values across replicas. Instead we
use noise_from_step_num() (see below).
The quantization scheme is as follows:
Compute the maximum absolute value by row (call this max_abs).
Store this either in an auxiliary variable or in an extra column.
Divide the parameters by (max_abs / (2^(num_bits-1)-1)). This gives a
float32 value in the range [-2^(num_bits-1)-1, 2^(num_bits-1)-1]
Unbiased randomized roundoff by adding noise and rounding down.
This produces a signed integer with num_bits bits which can then be stored.
Args:
x: a float32 Tensor
num_bits: an integer between 1 and 22
noise: a float Tensor broadcastable to the shape of x.
Returns:
a float32 Tensor
|
[
"Simulate",
"quantization",
"to",
"num_bits",
"bits",
"with",
"externally",
"-",
"stored",
"scale",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/quantization.py#L89-L134
|
train
|
Simulate quantization to num_bits bits with externally - stored scale.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + '\x6f' + '\062' + chr(0b110100 + 0o3) + chr(0b1100 + 0o53), 29738 - 29730), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + chr(0b110000) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + '\061' + '\x37', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + chr(54) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(0b111010 + 0o65) + chr(1733 - 1682) + '\x33' + chr(50), 0o10), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1101111) + chr(1608 - 1557) + chr(2215 - 2160), 0o10), ehT0Px3KOsy9('\x30' + chr(6293 - 6182) + '\x31' + '\x30' + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(111) + chr(1672 - 1622) + chr(698 - 644) + chr(1198 - 1145), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + chr(1469 - 1419) + '\x34', 40822 - 40814), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + '\x31' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(0b110100) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1010 + 0o51) + chr(0b11000 + 0o32), 15031 - 15023), ehT0Px3KOsy9(chr(48) + chr(913 - 802) + chr(0b100 + 0o60) + chr(0b11111 + 0o25), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + chr(0b110101) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(111) + '\064' + chr(2159 - 2107), 8), ehT0Px3KOsy9('\x30' + '\157' + chr(49) + '\x33', 33912 - 33904), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(111) + chr(2313 - 2264) + chr(0b110011) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\x31' + chr(0b110011), 8), ehT0Px3KOsy9(chr(2246 - 2198) + '\x6f' + '\x33' + chr(49) + '\063', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b101101 + 0o11) + '\062', 25905 - 25897), ehT0Px3KOsy9(chr(0b110000) + chr(8261 - 8150) + chr(0b1000 + 0o56) + '\x31', 23617 - 23609), ehT0Px3KOsy9('\x30' + '\157' + chr(160 - 109) + chr(49) + chr(1679 - 1624), 0b1000), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b101100 + 0o103) + '\063' + '\x34' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\x36' + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b0 + 0o60) + '\157' + chr(51) + chr(0b110101) + chr(1596 - 1544), ord("\x08")), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(7916 - 7805) + chr(0b110101) + chr(0b10010 + 0o40), 1311 - 1303), ehT0Px3KOsy9('\060' + chr(0b1101100 + 0o3) + chr(0b110011) + chr(0b110110) + chr(55), 0b1000), ehT0Px3KOsy9('\060' + chr(0b11010 + 0o125) + chr(0b110011) + '\x31' + chr(55), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(1582 - 1531) + '\067' + chr(1506 - 1454), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x31' + '\x35' + chr(1061 - 1012), 62318 - 62310), ehT0Px3KOsy9('\060' + '\157' + chr(0b101010 + 0o12) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + chr(0b1101 + 0o44) + chr(0b110111), 8), ehT0Px3KOsy9('\060' + '\157' + '\062' + '\067' + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b101000 + 0o10) + '\157' + chr(0b1001 + 0o52) + '\064' + chr(52), 18576 - 18568), ehT0Px3KOsy9(chr(1969 - 1921) + '\x6f' + '\063' + chr(0b110000) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(1025 - 977) + '\157' + chr(50) + '\062', 33107 - 33099), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b1001 + 0o51) + chr(0b110001) + chr(0b110 + 0o52), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + chr(1021 - 970) + '\062', 8), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(0b1000010 + 0o55) + chr(2152 - 2100) + chr(160 - 107), 0b1000), ehT0Px3KOsy9(chr(1170 - 1122) + chr(0b1100010 + 0o15) + chr(0b100101 + 0o14) + '\063' + chr(153 - 102), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(1457 - 1409) + chr(6801 - 6690) + '\x35' + chr(0b110 + 0o52), 36921 - 36913)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x91'), chr(1047 - 947) + chr(101) + '\143' + chr(111) + '\x64' + '\x65')(chr(0b1001000 + 0o55) + chr(6212 - 6096) + chr(102) + chr(0b101101) + chr(0b10010 + 0o46)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def wwTuf8MNIlGf(OeWW0F1dBPRQ, xvzt498SEA6K, MudPQU2D1pmv):
nauYfLglTpcb = OeWW0F1dBPRQ.get_shape().as_list()
if not (c2A0yzQpDQB3(nauYfLglTpcb) >= ehT0Px3KOsy9(chr(48) + '\157' + chr(2292 - 2242), ord("\x08")) and nauYfLglTpcb[-ehT0Px3KOsy9(chr(0b110000) + chr(1422 - 1311) + chr(565 - 516), 44459 - 44451)] > ehT0Px3KOsy9(chr(139 - 91) + chr(0b101 + 0o152) + chr(0b110001), 8)):
return OeWW0F1dBPRQ
Z_zpWL3oN9BI = IDJ2eXGCBCDu.reduce_max(IDJ2eXGCBCDu.abs(OeWW0F1dBPRQ), -ehT0Px3KOsy9(chr(1759 - 1711) + '\x6f' + chr(49), 8), keepdims=ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001), 8)) + 1e-09
vukQRVwg7nXM = ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\x6f' + chr(50), 8) ** (xvzt498SEA6K - ehT0Px3KOsy9('\x30' + chr(0b110111 + 0o70) + chr(49), 8)) - ehT0Px3KOsy9('\x30' + chr(0b111000 + 0o67) + chr(0b110001), 8)
xjPLimsZRgb9 = Z_zpWL3oN9BI / vukQRVwg7nXM
OeWW0F1dBPRQ /= xjPLimsZRgb9
OeWW0F1dBPRQ = IDJ2eXGCBCDu.floor(OeWW0F1dBPRQ + MudPQU2D1pmv)
OeWW0F1dBPRQ *= xjPLimsZRgb9
return OeWW0F1dBPRQ
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/quantization.py
|
noise_from_step_num
|
def noise_from_step_num():
"""Quantization noise equal to (phi * (step_num + 1)) mod 1.0.
Not using random_uniform here due to a problem on TPU in that random seeds
are not respected, which may cause the parameters on different replicas
to go out-of-sync.
Returns:
a float32 scalar
"""
step = tf.to_int32(tf.train.get_or_create_global_step()) + 1
phi = ((5 ** 0.5) - 1) / 2
# Naive computation tf.mod(phi * step, 1.0) in float32 would be disastrous
# due to loss of precision when the step number gets large.
# Computation in doubles does not work on TPU, so we use this complicated
# alternative computation which does not suffer from these roundoff errors.
ret = 0.0
for i in range(30):
ret += (((phi * (2 ** i)) % 1.0) # double-precision computation in python
* tf.to_float(tf.mod(step // (2 ** i), 2)))
return tf.mod(ret, 1.0)
|
python
|
def noise_from_step_num():
"""Quantization noise equal to (phi * (step_num + 1)) mod 1.0.
Not using random_uniform here due to a problem on TPU in that random seeds
are not respected, which may cause the parameters on different replicas
to go out-of-sync.
Returns:
a float32 scalar
"""
step = tf.to_int32(tf.train.get_or_create_global_step()) + 1
phi = ((5 ** 0.5) - 1) / 2
# Naive computation tf.mod(phi * step, 1.0) in float32 would be disastrous
# due to loss of precision when the step number gets large.
# Computation in doubles does not work on TPU, so we use this complicated
# alternative computation which does not suffer from these roundoff errors.
ret = 0.0
for i in range(30):
ret += (((phi * (2 ** i)) % 1.0) # double-precision computation in python
* tf.to_float(tf.mod(step // (2 ** i), 2)))
return tf.mod(ret, 1.0)
|
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Quantization noise equal to (phi * (step_num + 1)) mod 1.0.
Not using random_uniform here due to a problem on TPU in that random seeds
are not respected, which may cause the parameters on different replicas
to go out-of-sync.
Returns:
a float32 scalar
|
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/quantization.py#L137-L157
|
train
|
Quantization noise equal to phi * step_num mod 1. 0.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b1101111) + '\062' + '\x32' + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(0b11101 + 0o122) + chr(0b110010) + chr(53) + chr(48), 0o10), ehT0Px3KOsy9(chr(217 - 169) + '\x6f' + chr(0b110110) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + '\x32' + chr(1555 - 1507), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(191 - 136) + chr(2039 - 1989), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + '\065' + '\060', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110111) + '\066', 0b1000), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1101010 + 0o5) + chr(547 - 497) + chr(580 - 527) + '\067', 10584 - 10576), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\x6f' + chr(0b110001) + chr(0b11101 + 0o26) + chr(1963 - 1909), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(1698 - 1649) + chr(0b110111) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1000000 + 0o57) + chr(50) + chr(52) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b101000 + 0o107) + chr(51) + chr(50) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(1570 - 1522) + chr(0b1101111) + chr(0b110010) + chr(0b101100 + 0o12) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(352 - 304) + chr(8877 - 8766) + '\x31' + chr(0b110110), 53547 - 53539), ehT0Px3KOsy9(chr(191 - 143) + chr(0b111111 + 0o60) + '\061' + '\064' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(111) + '\061' + chr(636 - 584), 0o10), ehT0Px3KOsy9(chr(2084 - 2036) + chr(0b11110 + 0o121) + chr(647 - 596) + '\x32' + '\x33', 0o10), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(9456 - 9345) + chr(0b110111) + '\067', 56992 - 56984), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1908 - 1857) + '\060' + '\063', 8053 - 8045), ehT0Px3KOsy9('\060' + chr(0b101100 + 0o103) + chr(50) + '\x34' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(48) + chr(11205 - 11094) + chr(51) + chr(2115 - 2061) + chr(0b101 + 0o62), 49295 - 49287), ehT0Px3KOsy9(chr(0b110000) + chr(7221 - 7110) + '\x31' + chr(0b110111) + chr(0b110111), 0b1000), ehT0Px3KOsy9('\060' + chr(0b100011 + 0o114) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b11111 + 0o120) + chr(0b110010 + 0o1) + chr(0b100001 + 0o21) + chr(0b10111 + 0o35), 8), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b1101111) + chr(50) + chr(923 - 869) + '\x35', 48288 - 48280), ehT0Px3KOsy9(chr(2137 - 2089) + chr(0b1101111) + chr(50) + chr(0b110011) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(11452 - 11341) + chr(2170 - 2119) + chr(0b11010 + 0o27) + '\x32', 27334 - 27326), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + chr(54) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(2388 - 2337) + chr(0b11000 + 0o30) + '\063', 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(49) + chr(51) + '\060', 58628 - 58620), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(51), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + chr(52) + '\x30', 0b1000), ehT0Px3KOsy9(chr(1130 - 1082) + chr(0b1101111) + '\x31' + chr(53) + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110101) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101110 + 0o1) + chr(51) + chr(0b110000) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(2124 - 2076) + chr(0b110110 + 0o71) + '\x31' + chr(1626 - 1573) + chr(0b11111 + 0o24), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(8705 - 8594) + chr(0b100 + 0o56) + chr(55), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1001000 + 0o47) + chr(0b100100 + 0o16) + chr(51) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110011) + chr(0b11010 + 0o31) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(2024 - 1976) + '\157' + chr(0b11111 + 0o24) + chr(0b110001) + '\064', 45360 - 45352)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(10046 - 9935) + chr(53) + chr(314 - 266), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb8'), '\144' + chr(0b1001100 + 0o31) + '\143' + chr(0b1101111) + chr(100) + chr(0b1100101))(chr(0b10 + 0o163) + '\x74' + '\146' + chr(0b10 + 0o53) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def wcD4H0YsSFQA():
kDuFsAhEatcU = IDJ2eXGCBCDu.to_int32(IDJ2eXGCBCDu.train.get_or_create_global_step()) + ehT0Px3KOsy9(chr(48) + chr(0b1101 + 0o142) + chr(0b11110 + 0o23), 0b1000)
IOGtkN7op9UY = (ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\065', 8) ** 0.5 - ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001), 8)) / ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010), 0b1000)
VHn4CV4Ymrei = 0.0
for WVxHKyX45z_L in vQr8gNKaIaWE(ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + chr(54), 0b1000)):
VHn4CV4Ymrei += IOGtkN7op9UY * ehT0Px3KOsy9('\060' + '\157' + '\x32', 8) ** WVxHKyX45z_L % 1.0 * IDJ2eXGCBCDu.to_float(IDJ2eXGCBCDu.mod(kDuFsAhEatcU // ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(112 - 62), 8) ** WVxHKyX45z_L, ehT0Px3KOsy9('\060' + chr(0b1101111) + '\062', 8)))
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfb\xc7S'), '\144' + '\145' + chr(0b11001 + 0o112) + '\157' + chr(0b1011100 + 0o10) + chr(101))(chr(117) + chr(700 - 584) + chr(102) + '\055' + chr(0b111000)))(VHn4CV4Ymrei, 1.0)
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/quantization.py
|
_randomized_roundoff_to_bfloat16
|
def _randomized_roundoff_to_bfloat16(x, noise, cand1, cand2):
"""Round-off x to cand1 or to cand2 in an unbiased way.
Cand1 and cand2 are the same shape as x.
For every element of x, the corresponding elements of cand1 and cand2 should
be the two closest bfloat16 values to x. Order does not matter.
cand1 and cand2 must differ from each other.
Args:
x: A float32 Tensor.
noise: A Tensor broadcastable to the shape of x containing
random uniform values in [0.0, 1.0].
cand1: A bfloat16 Tensor the same shape as x.
cand2: A bfloat16 Tensor the same shape as x.
Returns:
A bfloat16 Tensor.
"""
cand1_f = tf.to_float(cand1)
cand2_f = tf.to_float(cand2)
step_size = cand2_f - cand1_f
fpart = (x - cand1_f) / step_size
ret = tf.where(tf.greater(fpart, noise), cand2, cand1)
return ret
|
python
|
def _randomized_roundoff_to_bfloat16(x, noise, cand1, cand2):
"""Round-off x to cand1 or to cand2 in an unbiased way.
Cand1 and cand2 are the same shape as x.
For every element of x, the corresponding elements of cand1 and cand2 should
be the two closest bfloat16 values to x. Order does not matter.
cand1 and cand2 must differ from each other.
Args:
x: A float32 Tensor.
noise: A Tensor broadcastable to the shape of x containing
random uniform values in [0.0, 1.0].
cand1: A bfloat16 Tensor the same shape as x.
cand2: A bfloat16 Tensor the same shape as x.
Returns:
A bfloat16 Tensor.
"""
cand1_f = tf.to_float(cand1)
cand2_f = tf.to_float(cand2)
step_size = cand2_f - cand1_f
fpart = (x - cand1_f) / step_size
ret = tf.where(tf.greater(fpart, noise), cand2, cand1)
return ret
|
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Round-off x to cand1 or to cand2 in an unbiased way.
Cand1 and cand2 are the same shape as x.
For every element of x, the corresponding elements of cand1 and cand2 should
be the two closest bfloat16 values to x. Order does not matter.
cand1 and cand2 must differ from each other.
Args:
x: A float32 Tensor.
noise: A Tensor broadcastable to the shape of x containing
random uniform values in [0.0, 1.0].
cand1: A bfloat16 Tensor the same shape as x.
cand2: A bfloat16 Tensor the same shape as x.
Returns:
A bfloat16 Tensor.
|
[
"Round",
"-",
"off",
"x",
"to",
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/quantization.py#L160-L183
|
train
|
Round - off x to cand1 or cand2 in an unbiased way.
|
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(271 - 223) + chr(111) + chr(0b101001 + 0o11) + '\067' + chr(50), 0b1000), ehT0Px3KOsy9(chr(654 - 606) + chr(0b1101111) + chr(0b1000 + 0o51) + chr(0b110100) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(111) + chr(283 - 233) + chr(0b101001 + 0o10) + chr(0b110101 + 0o0), 29447 - 29439), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110010) + chr(2542 - 2490) + chr(0b11 + 0o64), 0b1000), ehT0Px3KOsy9('\060' + chr(0b10101 + 0o132) + '\061' + chr(0b110011), 39154 - 39146), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(111) + chr(0b1001 + 0o56) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1821 - 1770) + '\x36' + chr(0b11010 + 0o35), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1100111 + 0o10) + chr(534 - 481) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(0b100101 + 0o112) + chr(50) + chr(713 - 665) + '\x36', 0b1000), ehT0Px3KOsy9(chr(2080 - 2032) + '\157' + chr(1267 - 1216) + chr(464 - 413), 59500 - 59492), ehT0Px3KOsy9(chr(48) + chr(111) + chr(871 - 816) + '\x31', 47941 - 47933), ehT0Px3KOsy9(chr(1319 - 1271) + chr(0b1101111) + chr(2359 - 2309) + chr(48) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x32', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b100000 + 0o21) + chr(1697 - 1646) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b10110 + 0o131) + '\x37' + '\066', 0b1000), ehT0Px3KOsy9('\x30' + chr(1541 - 1430) + '\063' + '\x31' + chr(0b10001 + 0o40), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + chr(54) + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\x31' + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(835 - 787) + chr(0b1101000 + 0o7) + '\064' + chr(132 - 80), 35548 - 35540), ehT0Px3KOsy9('\x30' + chr(3246 - 3135) + '\x32' + chr(0b110111) + chr(50), 8), ehT0Px3KOsy9(chr(689 - 641) + chr(0b1011000 + 0o27) + chr(51) + '\x32' + '\x36', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063' + chr(0b110100) + '\065', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1001110 + 0o41) + '\x33' + '\062', 17329 - 17321), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + '\x32' + chr(0b110101), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b11 + 0o56) + chr(539 - 486) + chr(0b101110 + 0o2), ord("\x08")), ehT0Px3KOsy9(chr(1317 - 1269) + '\157' + chr(49) + chr(0b110110) + chr(0b10110 + 0o32), 236 - 228), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b1001 + 0o52) + chr(1018 - 969) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(5753 - 5642) + chr(0b10010 + 0o41) + '\x31' + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b1100 + 0o44) + '\157' + chr(0b110011) + chr(54) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(10372 - 10261) + chr(0b110011) + chr(2681 - 2629) + '\063', 8461 - 8453), ehT0Px3KOsy9('\x30' + chr(3992 - 3881) + chr(49) + chr(0b110001) + chr(48), 1847 - 1839), ehT0Px3KOsy9('\060' + chr(0b111111 + 0o60) + '\x33' + '\061' + '\062', 13104 - 13096), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011 + 0o3) + '\062', 55098 - 55090), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + chr(54) + chr(2349 - 2294), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b111010 + 0o65) + '\x31' + chr(0b110100) + '\x35', 65047 - 65039), ehT0Px3KOsy9('\x30' + chr(0b1101 + 0o142) + chr(1431 - 1381) + chr(0b110001) + chr(0b110011 + 0o3), ord("\x08")), ehT0Px3KOsy9(chr(0b10110 + 0o32) + '\157' + chr(50) + chr(785 - 736) + chr(49), 0o10), ehT0Px3KOsy9('\060' + chr(2418 - 2307) + '\063' + '\x31' + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(350 - 300) + chr(1904 - 1856) + chr(0b1101 + 0o47), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101011 + 0o4) + '\065' + '\060', 48264 - 48256)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x94'), chr(100) + chr(0b100011 + 0o102) + '\143' + '\x6f' + chr(100) + '\145')('\165' + chr(13103 - 12987) + '\x66' + chr(0b101000 + 0o5) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def xXfdHI3yK8l8(OeWW0F1dBPRQ, MudPQU2D1pmv, HlAsPkaHmL8H, zW2wsoLIx6Vk):
gGf8Nq5vlDOF = IDJ2eXGCBCDu.to_float(HlAsPkaHmL8H)
_4rPNNVGSpFe = IDJ2eXGCBCDu.to_float(zW2wsoLIx6Vk)
TJfriPHamLwP = _4rPNNVGSpFe - gGf8Nq5vlDOF
RIO3DNJk4_M7 = (OeWW0F1dBPRQ - gGf8Nq5vlDOF) / TJfriPHamLwP
VHn4CV4Ymrei = IDJ2eXGCBCDu.dRFAC59yQBm_(IDJ2eXGCBCDu.greater(RIO3DNJk4_M7, MudPQU2D1pmv), zW2wsoLIx6Vk, HlAsPkaHmL8H)
return VHn4CV4Ymrei
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/quantization.py
|
_to_bfloat16_unbiased
|
def _to_bfloat16_unbiased(x, noise):
"""Convert a float32 to a bfloat16 using randomized roundoff.
Args:
x: A float32 Tensor.
noise: a float32 Tensor with values in [0, 1), broadcastable to tf.shape(x)
Returns:
A float32 Tensor.
"""
x_sign = tf.sign(x)
# Make sure x is positive. If it is zero, the two candidates are identical.
x = x * x_sign + 1e-30
cand1 = tf.to_bfloat16(x)
cand1_f = tf.to_float(cand1)
# This relies on the fact that for a positive bfloat16 b,
# b * 1.005 gives you the next higher bfloat16 and b*0.995 gives you the
# next lower one. Both 1.005 and 0.995 are ballpark estimation.
cand2 = tf.to_bfloat16(
tf.where(tf.greater(x, cand1_f), cand1_f * 1.005, cand1_f * 0.995))
ret = _randomized_roundoff_to_bfloat16(x, noise, cand1, cand2)
return ret * tf.to_bfloat16(x_sign)
|
python
|
def _to_bfloat16_unbiased(x, noise):
"""Convert a float32 to a bfloat16 using randomized roundoff.
Args:
x: A float32 Tensor.
noise: a float32 Tensor with values in [0, 1), broadcastable to tf.shape(x)
Returns:
A float32 Tensor.
"""
x_sign = tf.sign(x)
# Make sure x is positive. If it is zero, the two candidates are identical.
x = x * x_sign + 1e-30
cand1 = tf.to_bfloat16(x)
cand1_f = tf.to_float(cand1)
# This relies on the fact that for a positive bfloat16 b,
# b * 1.005 gives you the next higher bfloat16 and b*0.995 gives you the
# next lower one. Both 1.005 and 0.995 are ballpark estimation.
cand2 = tf.to_bfloat16(
tf.where(tf.greater(x, cand1_f), cand1_f * 1.005, cand1_f * 0.995))
ret = _randomized_roundoff_to_bfloat16(x, noise, cand1, cand2)
return ret * tf.to_bfloat16(x_sign)
|
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Convert a float32 to a bfloat16 using randomized roundoff.
Args:
x: A float32 Tensor.
noise: a float32 Tensor with values in [0, 1), broadcastable to tf.shape(x)
Returns:
A float32 Tensor.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/quantization.py#L186-L206
|
train
|
Convert a float32 to a bfloat16 using randomized roundoff.
|
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) + '\157' + chr(0b0 + 0o62) + '\x36' + '\x32', 1806 - 1798), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(2230 - 2181) + chr(49) + '\x35', 14166 - 14158), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(53) + chr(0b110010), 0o10), ehT0Px3KOsy9('\x30' + chr(2100 - 1989) + chr(1055 - 1006) + '\064' + chr(0b11111 + 0o22), 18368 - 18360), ehT0Px3KOsy9(chr(0b110000) + chr(6387 - 6276) + '\x33' + '\060' + '\067', 26166 - 26158), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(239 - 189) + chr(0b110100) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(1133 - 1085) + chr(0b1101111) + chr(49) + chr(0b110001) + '\065', 8), ehT0Px3KOsy9(chr(48) + chr(0b1010111 + 0o30) + chr(0b110101) + chr(55), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + '\x37' + chr(0b1011 + 0o54), ord("\x08")), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(111) + '\x31' + '\064', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + '\x32' + chr(53), 23758 - 23750), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011) + chr(0b110010) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(3620 - 3509) + '\x32' + chr(2116 - 2067) + chr(0b111 + 0o56), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110011) + chr(49) + chr(0b100010 + 0o16), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2311 - 2261) + '\062' + chr(0b11111 + 0o25), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110 + 0o61) + chr(51), 30499 - 30491), ehT0Px3KOsy9('\x30' + chr(0b1001101 + 0o42) + chr(0b10001 + 0o45) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(2149 - 2101) + chr(0b110010 + 0o75) + '\062' + chr(53) + chr(51), 54815 - 54807), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(0b110110) + '\x34', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b101111 + 0o3) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(653 - 605) + '\x6f' + '\x35' + chr(48), 60611 - 60603), ehT0Px3KOsy9(chr(776 - 728) + chr(0b1001111 + 0o40) + '\061' + '\x34' + chr(0b11111 + 0o23), 2574 - 2566), ehT0Px3KOsy9(chr(0b110000) + chr(0b1111 + 0o140) + chr(1907 - 1858) + '\061' + chr(0b110011), 9070 - 9062), ehT0Px3KOsy9(chr(1778 - 1730) + chr(0b100100 + 0o113) + '\061' + chr(0b110101) + '\x36', 0o10), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(0b1101111) + chr(2253 - 2204) + chr(0b100010 + 0o25) + '\x37', 48213 - 48205), ehT0Px3KOsy9('\060' + '\157' + chr(0b110010 + 0o0) + '\060', 0o10), ehT0Px3KOsy9(chr(1266 - 1218) + chr(0b110 + 0o151) + chr(1732 - 1683) + '\066' + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011000 + 0o27) + chr(49) + '\061', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + chr(0b1100 + 0o50), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b10100 + 0o133) + chr(0b1010 + 0o47) + chr(734 - 686) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(1922 - 1874) + chr(2193 - 2082) + chr(0b110100) + chr(1323 - 1271), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(7808 - 7697) + chr(0b101100 + 0o6) + '\x34' + chr(0b11101 + 0o31), 8), ehT0Px3KOsy9('\x30' + chr(9155 - 9044) + '\061' + '\065' + chr(0b100111 + 0o14), ord("\x08")), ehT0Px3KOsy9(chr(863 - 815) + chr(2206 - 2095) + '\066' + chr(55), 0o10), ehT0Px3KOsy9(chr(867 - 819) + chr(0b1101111) + chr(1688 - 1638) + chr(0b10100 + 0o35) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(7964 - 7853) + chr(0b110010) + chr(53) + '\065', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110 + 0o55) + chr(53) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(4512 - 4401) + chr(0b100110 + 0o14) + chr(2062 - 2014) + '\x36', 24597 - 24589), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b1010 + 0o47) + chr(1364 - 1311) + '\x33', 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + chr(55) + chr(0b11011 + 0o33), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b111 + 0o150) + chr(53) + chr(48), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x9c'), chr(100) + '\x65' + chr(9401 - 9302) + '\157' + chr(0b110010 + 0o62) + chr(101))(chr(9554 - 9437) + chr(116) + chr(0b10001 + 0o125) + chr(0b11010 + 0o23) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def opgbz0DpvIAI(OeWW0F1dBPRQ, MudPQU2D1pmv):
GYNrSOkVwykV = IDJ2eXGCBCDu.sign(OeWW0F1dBPRQ)
OeWW0F1dBPRQ = OeWW0F1dBPRQ * GYNrSOkVwykV + 1e-30
HlAsPkaHmL8H = IDJ2eXGCBCDu.to_bfloat16(OeWW0F1dBPRQ)
gGf8Nq5vlDOF = IDJ2eXGCBCDu.to_float(HlAsPkaHmL8H)
zW2wsoLIx6Vk = IDJ2eXGCBCDu.to_bfloat16(IDJ2eXGCBCDu.dRFAC59yQBm_(IDJ2eXGCBCDu.greater(OeWW0F1dBPRQ, gGf8Nq5vlDOF), gGf8Nq5vlDOF * 1.005, gGf8Nq5vlDOF * 0.995))
VHn4CV4Ymrei = xXfdHI3yK8l8(OeWW0F1dBPRQ, MudPQU2D1pmv, HlAsPkaHmL8H, zW2wsoLIx6Vk)
return VHn4CV4Ymrei * xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc6"u\x03\xa1\xca"N\xcb=\xe3'), '\x64' + chr(0b1100101) + chr(99) + chr(0b100000 + 0o117) + chr(0b1100000 + 0o4) + '\145')('\165' + chr(0b1110001 + 0o3) + '\146' + '\055' + chr(718 - 662)))(GYNrSOkVwykV)
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/quantization.py
|
ParameterEncoding.custom_getter
|
def custom_getter(self, activation_dtype=tf.bfloat16):
"""A custom getter that uses the encoding for bfloat16 and float32 vars.
When a bfloat16 or float32 variable is requsted, an encoded float16
varaible is created, which is then decoded and cast to a bfloat16
activation.
Args:
activation_dtype: a dtype to which to convert the decoded value.
Returns:
a function.
"""
def getter_fn(getter, *args, **kwargs):
requested_dtype = kwargs["dtype"]
if requested_dtype in (tf.bfloat16, tf.float32):
kwargs["dtype"] = tf.bfloat16
kwargs["initializer"] = _EncodingInitializer(
kwargs["initializer"], self)
ret = self._decode_with_identity_gradient(getter(*args, **kwargs))
return tf.cast(ret, activation_dtype)
return getter(*args, **kwargs)
return getter_fn
|
python
|
def custom_getter(self, activation_dtype=tf.bfloat16):
"""A custom getter that uses the encoding for bfloat16 and float32 vars.
When a bfloat16 or float32 variable is requsted, an encoded float16
varaible is created, which is then decoded and cast to a bfloat16
activation.
Args:
activation_dtype: a dtype to which to convert the decoded value.
Returns:
a function.
"""
def getter_fn(getter, *args, **kwargs):
requested_dtype = kwargs["dtype"]
if requested_dtype in (tf.bfloat16, tf.float32):
kwargs["dtype"] = tf.bfloat16
kwargs["initializer"] = _EncodingInitializer(
kwargs["initializer"], self)
ret = self._decode_with_identity_gradient(getter(*args, **kwargs))
return tf.cast(ret, activation_dtype)
return getter(*args, **kwargs)
return getter_fn
|
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] |
A custom getter that uses the encoding for bfloat16 and float32 vars.
When a bfloat16 or float32 variable is requsted, an encoded float16
varaible is created, which is then decoded and cast to a bfloat16
activation.
Args:
activation_dtype: a dtype to which to convert the decoded value.
Returns:
a function.
|
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"A",
"custom",
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"that",
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"and",
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"vars",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/quantization.py#L246-L268
|
train
|
A custom getter that uses the encoding for bfloat16 and float32 vars.
|
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) + '\x33' + '\062' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b101101 + 0o5) + chr(1426 - 1372) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(11050 - 10939) + chr(50) + '\x33', 0b1000), ehT0Px3KOsy9(chr(222 - 174) + chr(0b1101111) + chr(50) + '\067' + '\x31', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x31' + '\060' + chr(0b1001 + 0o51), 0o10), ehT0Px3KOsy9(chr(48) + chr(4788 - 4677) + chr(50) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b10000 + 0o40) + '\157' + chr(49) + '\x35' + chr(1511 - 1462), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(753 - 642) + chr(49) + '\060' + '\x37', 49118 - 49110), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(2323 - 2274) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10101 + 0o34) + chr(2749 - 2695) + '\067', 13500 - 13492), ehT0Px3KOsy9('\060' + chr(111) + '\067' + chr(0b10010 + 0o40), 0b1000), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b1101111) + chr(0b101000 + 0o14) + chr(0b100100 + 0o23), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b10000 + 0o41) + '\060' + '\060', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001) + '\067' + chr(0b110 + 0o60), 4536 - 4528), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + chr(51) + chr(0b101110 + 0o7), 31475 - 31467), ehT0Px3KOsy9(chr(1602 - 1554) + chr(111) + chr(51) + chr(51) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(2291 - 2241) + chr(0b101001 + 0o14) + '\x36', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(0b100111 + 0o14) + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x32' + chr(0b11010 + 0o33) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(789 - 741) + '\157' + '\063' + '\x32' + chr(0b110000), 8951 - 8943), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b101010 + 0o105) + chr(0b1011 + 0o50) + chr(55) + '\x33', 48531 - 48523), ehT0Px3KOsy9('\x30' + '\157' + '\065', 0o10), ehT0Px3KOsy9(chr(0b1011 + 0o45) + '\157' + chr(0b100000 + 0o22) + '\x31' + '\x31', 9661 - 9653), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(51) + '\062' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(84 - 36) + chr(5896 - 5785) + chr(51) + '\064' + chr(0b110001 + 0o5), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(6119 - 6008) + '\x31' + chr(0b110000) + chr(0b110010 + 0o1), 20462 - 20454), ehT0Px3KOsy9(chr(48) + chr(4073 - 3962) + chr(0b110011) + chr(0b110001) + '\063', 0o10), ehT0Px3KOsy9(chr(2176 - 2128) + chr(0b1101111) + '\x33' + '\062' + chr(0b110 + 0o60), 0b1000), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(500 - 389) + chr(0b110011) + chr(0b110101) + chr(915 - 862), 0o10), ehT0Px3KOsy9('\x30' + chr(8143 - 8032) + chr(0b110010) + '\x32' + '\x32', 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + chr(997 - 942) + chr(1309 - 1261), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(1558 - 1507) + chr(0b11110 + 0o31) + chr(0b1110 + 0o46), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b100111 + 0o110) + '\x31' + '\x37' + chr(1136 - 1087), ord("\x08")), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(1983 - 1872) + chr(0b110001) + '\x35' + '\061', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101011 + 0o4) + chr(2147 - 2098), 12555 - 12547), ehT0Px3KOsy9(chr(894 - 846) + '\157' + chr(50) + chr(52), 0o10), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(4398 - 4287) + chr(0b110011) + '\x34' + chr(0b110110), 8), ehT0Px3KOsy9(chr(48) + chr(0b1001100 + 0o43) + '\x32' + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31' + '\060' + '\x34', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + '\x35' + chr(0b10101 + 0o41), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(111) + chr(0b1 + 0o64) + '\060', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xfb'), chr(0b1100100) + chr(0b110011 + 0o62) + '\x63' + chr(0b111011 + 0o64) + '\x64' + '\x65')('\165' + chr(116) + '\146' + '\055' + chr(0b10100 + 0o44)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def JF98kqC39wAN(oVre8I6UXc3b, n6ZCgJ7AKd3U=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb7\xd2\x7f\xd6#dXq'), '\144' + '\145' + chr(99) + chr(0b1101111) + chr(0b1100100) + chr(101))('\x75' + chr(0b1110100) + chr(102) + '\x2d' + chr(0b111000)))):
def iZHaispm3G3r(XGjmdKmSZ8Qs, *kJDRfRhcZHjS, **M8EIoTs2GJXE):
iZaeiSw52vim = M8EIoTs2GJXE[xafqLlk3kkUe(SXOLrMavuUCe(b"\xb1\xc0j\xc9'"), chr(100) + chr(0b1110 + 0o127) + '\143' + '\157' + chr(0b100000 + 0o104) + '\x65')('\x75' + chr(0b1110100) + chr(5501 - 5399) + '\055' + '\x38')]
if iZaeiSw52vim in (xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb7\xd2\x7f\xd6#dXq'), '\144' + '\x65' + chr(99) + chr(0b1101111) + '\144' + chr(0b1100101))(chr(0b1110101) + '\164' + '\x66' + chr(0b101101) + '\070')), xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb3\xd8|\xd86#['), chr(0b11110 + 0o106) + '\145' + chr(99) + chr(0b1010111 + 0o30) + '\x64' + '\145')(chr(10305 - 10188) + chr(0b101000 + 0o114) + chr(102) + chr(0b101101) + chr(0b111000)))):
M8EIoTs2GJXE[xafqLlk3kkUe(SXOLrMavuUCe(b"\xb1\xc0j\xc9'"), chr(100) + '\145' + chr(0b1100011) + chr(9189 - 9078) + '\144' + '\145')(chr(117) + chr(0b1110 + 0o146) + chr(102) + '\055' + chr(1861 - 1805))] = IDJ2eXGCBCDu.bfloat16
M8EIoTs2GJXE[xafqLlk3kkUe(SXOLrMavuUCe(b'\xbc\xdaz\xcd+q\x05.0\x12H'), chr(0b1011011 + 0o11) + '\145' + chr(0b1100011) + chr(0b1101111) + chr(0b111111 + 0o45) + '\x65')(chr(0b1110101) + chr(0b1110100) + chr(658 - 556) + '\x2d' + '\070')] = U4QYIR28GubK(M8EIoTs2GJXE[xafqLlk3kkUe(SXOLrMavuUCe(b'\xbc\xdaz\xcd+q\x05.0\x12H'), '\144' + chr(0b110 + 0o137) + chr(0b1100011) + '\157' + chr(100) + '\145')(chr(117) + chr(116) + chr(0b1100110) + chr(45) + chr(0b111000))], oVre8I6UXc3b)
VHn4CV4Ymrei = oVre8I6UXc3b._decode_with_identity_gradient(XGjmdKmSZ8Qs(*kJDRfRhcZHjS, **M8EIoTs2GJXE))
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb6\xd5`\xcd'), chr(0b1011100 + 0o10) + chr(0b10001 + 0o124) + chr(99) + '\x6f' + chr(9503 - 9403) + chr(101))(chr(0b1100111 + 0o16) + '\164' + chr(0b1100110) + '\055' + chr(56)))(VHn4CV4Ymrei, n6ZCgJ7AKd3U)
return XGjmdKmSZ8Qs(*kJDRfRhcZHjS, **M8EIoTs2GJXE)
return iZHaispm3G3r
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/video_metrics.py
|
load_videos
|
def load_videos(template, video_length, frame_shape):
"""Loads videos from files.
Args:
template: template string for listing the image files.
video_length: length of the video.
frame_shape: shape of each frame.
Returns:
dataset: the tf dataset frame by frame.
dataset_len: number of the items which is the number of image files.
Raises:
ValueError: if no files found.
"""
filenames = tf.gfile.Glob(template)
if not filenames:
raise ValueError("no files found.")
filenames = sorted(filenames)
dataset_len = len(filenames)
filenames = tf.constant(filenames)
dataset = tf.data.Dataset.from_tensor_slices(filenames)
dataset = dataset.apply(tf.data.experimental.map_and_batch(
lambda filename: load_image_map_function(filename, frame_shape),
video_length, drop_remainder=True))
return dataset, dataset_len
|
python
|
def load_videos(template, video_length, frame_shape):
"""Loads videos from files.
Args:
template: template string for listing the image files.
video_length: length of the video.
frame_shape: shape of each frame.
Returns:
dataset: the tf dataset frame by frame.
dataset_len: number of the items which is the number of image files.
Raises:
ValueError: if no files found.
"""
filenames = tf.gfile.Glob(template)
if not filenames:
raise ValueError("no files found.")
filenames = sorted(filenames)
dataset_len = len(filenames)
filenames = tf.constant(filenames)
dataset = tf.data.Dataset.from_tensor_slices(filenames)
dataset = dataset.apply(tf.data.experimental.map_and_batch(
lambda filename: load_image_map_function(filename, frame_shape),
video_length, drop_remainder=True))
return dataset, dataset_len
|
[
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",",
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",",
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",",
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"True",
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",",
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] |
Loads videos from files.
Args:
template: template string for listing the image files.
video_length: length of the video.
frame_shape: shape of each frame.
Returns:
dataset: the tf dataset frame by frame.
dataset_len: number of the items which is the number of image files.
Raises:
ValueError: if no files found.
|
[
"Loads",
"videos",
"from",
"files",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/video_metrics.py#L38-L63
|
train
|
Loads videos from files.
|
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(0b110001) + chr(0b110011) + '\x34', 41420 - 41412), ehT0Px3KOsy9(chr(48) + '\157' + '\064' + '\x35', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1001000 + 0o47) + '\062' + '\x36' + chr(2292 - 2242), ord("\x08")), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b1101111) + '\x34' + chr(754 - 699), ord("\x08")), ehT0Px3KOsy9(chr(904 - 856) + chr(0b1101111) + chr(0b11110 + 0o23) + chr(2471 - 2420) + chr(0b101110 + 0o6), 8), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(1884 - 1773) + chr(0b110010 + 0o3) + chr(206 - 151), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b1110 + 0o47) + chr(52), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(2538 - 2487) + chr(53) + '\064', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b101011 + 0o6) + chr(0b110101) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b1101011 + 0o4) + '\063' + chr(0b11100 + 0o24) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b10100 + 0o36), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1240 - 1191) + chr(2499 - 2447) + chr(1178 - 1126), 0o10), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(0b10011 + 0o134) + chr(0b100 + 0o56) + chr(0b11010 + 0o30) + chr(0b11111 + 0o24), 36598 - 36590), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110111) + chr(0b110101), 19332 - 19324), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(0b1001 + 0o52) + chr(0b100111 + 0o15), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(2346 - 2295) + '\x37' + chr(52), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b10000 + 0o137) + chr(515 - 464) + chr(1407 - 1354) + chr(0b110001), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(1188 - 1137) + chr(502 - 448) + chr(792 - 740), 56733 - 56725), ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\157' + '\063' + chr(2463 - 2408) + chr(0b110110), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1011100 + 0o23) + chr(0b110010) + chr(0b110011) + '\x33', 57436 - 57428), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(9235 - 9124) + chr(0b100111 + 0o13) + '\x34' + chr(52), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(50) + chr(0b110101) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(2124 - 2076) + chr(0b11101 + 0o122) + '\062' + chr(0b110001) + '\x31', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + '\064', ord("\x08")), ehT0Px3KOsy9('\060' + chr(2683 - 2572) + chr(436 - 386) + chr(1735 - 1684), 51296 - 51288), ehT0Px3KOsy9('\x30' + chr(0b1111 + 0o140) + chr(1804 - 1754), 8), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + '\x30' + chr(50), ord("\x08")), ehT0Px3KOsy9('\060' + chr(7157 - 7046) + '\065' + chr(0b11 + 0o57), 32530 - 32522), ehT0Px3KOsy9(chr(0b101001 + 0o7) + '\x6f' + '\063' + '\x37' + chr(1265 - 1212), 0o10), ehT0Px3KOsy9(chr(966 - 918) + chr(0b1101111) + chr(50) + '\x33' + '\063', 8), ehT0Px3KOsy9(chr(0b110000) + chr(6575 - 6464) + '\063' + '\060' + '\063', 19727 - 19719), ehT0Px3KOsy9(chr(1394 - 1346) + '\x6f' + chr(0b110010) + chr(49) + chr(0b1010 + 0o53), 0b1000), ehT0Px3KOsy9(chr(1181 - 1133) + chr(111) + chr(51) + chr(288 - 234) + '\x33', 0b1000), ehT0Px3KOsy9('\060' + chr(863 - 752) + chr(49) + '\061' + chr(0b10100 + 0o37), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000000 + 0o57) + chr(0b1011 + 0o50) + chr(0b11 + 0o57) + '\063', 23684 - 23676), ehT0Px3KOsy9(chr(48) + chr(0b1100111 + 0o10) + chr(0b10100 + 0o37) + chr(49) + chr(1630 - 1581), 35471 - 35463), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + '\x34' + chr(1994 - 1945), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(3324 - 3213) + '\x32' + '\x35' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\157' + chr(353 - 303) + chr(0b110000 + 0o6) + '\x33', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(7333 - 7222) + '\065' + '\x30', 55061 - 55053)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'r'), '\144' + chr(8770 - 8669) + chr(8853 - 8754) + chr(0b1100110 + 0o11) + chr(100) + chr(137 - 36))(chr(0b10010 + 0o143) + chr(12526 - 12410) + '\146' + chr(45) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def y5gKG4COBFrz(jJBnSHEgylNZ, KK_OXZqCJ1S_, eut3NH0zeXzv):
Xs6zu3BFE2Ws = IDJ2eXGCBCDu.gfile.Glob(jJBnSHEgylNZ)
if not Xs6zu3BFE2Ws:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'2J\x92A5CI\x9fK\xa2m\x11\xfdY\xf2'), chr(100) + '\145' + chr(99) + chr(0b100100 + 0o113) + chr(1963 - 1863) + chr(0b1100101))(chr(11506 - 11389) + chr(0b1110100) + '\x66' + chr(1576 - 1531) + chr(0b111000)))
Xs6zu3BFE2Ws = vUlqIvNSaRMa(Xs6zu3BFE2Ws)
bspwyjidg95p = c2A0yzQpDQB3(Xs6zu3BFE2Ws)
Xs6zu3BFE2Ws = IDJ2eXGCBCDu.constant(Xs6zu3BFE2Ws)
xQt6gV9VfTO3 = IDJ2eXGCBCDu.data.Dataset.from_tensor_slices(Xs6zu3BFE2Ws)
xQt6gV9VfTO3 = xQt6gV9VfTO3.apply(IDJ2eXGCBCDu.data.experimental.map_and_batch(lambda xw4DsBfIJ22E: IxNFYrVMbDwF(xw4DsBfIJ22E, eut3NH0zeXzv), KK_OXZqCJ1S_, drop_remainder=ehT0Px3KOsy9(chr(396 - 348) + chr(8601 - 8490) + '\x31', 0b1000)))
return (xQt6gV9VfTO3, bspwyjidg95p)
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/video_metrics.py
|
psnr_and_ssim
|
def psnr_and_ssim(output, target):
"""Compute the PSNR and SSIM.
Args:
output: 4-D Tensor, shape=(num_frames, height, width, num_channels)
target: 4-D Tensor, shape=(num_frames, height, width, num_channels)
Returns:
psnr: 1-D Tensor, shape=(num_frames,)
ssim: 1-D Tensor, shape=(num_frames,)
"""
output = tf.cast(output, dtype=tf.int32)
target = tf.cast(target, dtype=tf.int32)
psnr = tf.image.psnr(output, target, max_val=255)
ssim = tf.image.ssim(output, target, max_val=255)
return psnr, ssim
|
python
|
def psnr_and_ssim(output, target):
"""Compute the PSNR and SSIM.
Args:
output: 4-D Tensor, shape=(num_frames, height, width, num_channels)
target: 4-D Tensor, shape=(num_frames, height, width, num_channels)
Returns:
psnr: 1-D Tensor, shape=(num_frames,)
ssim: 1-D Tensor, shape=(num_frames,)
"""
output = tf.cast(output, dtype=tf.int32)
target = tf.cast(target, dtype=tf.int32)
psnr = tf.image.psnr(output, target, max_val=255)
ssim = tf.image.ssim(output, target, max_val=255)
return psnr, ssim
|
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] |
Compute the PSNR and SSIM.
Args:
output: 4-D Tensor, shape=(num_frames, height, width, num_channels)
target: 4-D Tensor, shape=(num_frames, height, width, num_channels)
Returns:
psnr: 1-D Tensor, shape=(num_frames,)
ssim: 1-D Tensor, shape=(num_frames,)
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/video_metrics.py#L93-L107
|
train
|
Compute the PSNR and SSIM.
|
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(1298 - 1250) + '\157' + chr(0b110110) + chr(52), 25448 - 25440), ehT0Px3KOsy9(chr(479 - 431) + chr(0b1101111) + chr(0b0 + 0o63) + chr(2119 - 2065) + chr(0b110100), 4724 - 4716), ehT0Px3KOsy9(chr(0b110000) + chr(2313 - 2202) + chr(0b1101 + 0o44) + chr(0b11011 + 0o25) + chr(55), 0b1000), ehT0Px3KOsy9(chr(1005 - 957) + chr(0b1101111) + chr(201 - 152) + chr(51) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + chr(0b110011) + chr(0b10111 + 0o35), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + chr(0b110101) + chr(55), 17919 - 17911), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(8778 - 8667) + '\x32' + '\062' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + chr(0b0 + 0o66) + '\063', 49287 - 49279), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b1101111) + chr(49) + chr(0b110100) + chr(2074 - 2019), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b111 + 0o150) + chr(49) + chr(0b101000 + 0o12) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001 + 0o0) + chr(48) + chr(1652 - 1599), 49476 - 49468), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b111 + 0o60) + chr(2444 - 2392), 0o10), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1101111) + chr(1758 - 1709) + chr(55) + '\063', 1975 - 1967), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\063' + chr(49) + chr(0b110100), 0b1000), ehT0Px3KOsy9('\060' + chr(9702 - 9591) + '\x31' + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(790 - 742) + chr(0b11110 + 0o121) + chr(1689 - 1640) + '\063' + '\065', 46019 - 46011), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(111) + chr(0b10010 + 0o37) + chr(49) + chr(1967 - 1914), 0o10), ehT0Px3KOsy9(chr(2008 - 1960) + chr(0b1111 + 0o140) + chr(0b110111 + 0o0), ord("\x08")), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(1426 - 1315) + chr(2392 - 2341) + '\065' + '\065', 2332 - 2324), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b111 + 0o54) + chr(0b101 + 0o57) + chr(0b101101 + 0o7), 0o10), ehT0Px3KOsy9(chr(1084 - 1036) + '\x6f' + chr(1264 - 1214) + chr(0b110011) + '\060', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100010 + 0o21) + '\x35', 0o10), ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\157' + chr(2276 - 2226) + chr(246 - 197) + chr(1019 - 970), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101110 + 0o1) + '\x33' + chr(0b101001 + 0o13) + chr(53), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + chr(0b110110) + chr(0b100110 + 0o17), 0o10), ehT0Px3KOsy9(chr(0b101 + 0o53) + '\157' + chr(82 - 30) + chr(1228 - 1174), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(0b110000) + '\x37', 8), ehT0Px3KOsy9('\x30' + chr(0b1001100 + 0o43) + chr(2071 - 2021) + chr(0b1110 + 0o47) + chr(1332 - 1283), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(49) + '\x32' + chr(0b101101 + 0o6), 0b1000), ehT0Px3KOsy9(chr(1076 - 1028) + chr(111) + chr(1386 - 1337) + chr(0b110111) + '\x34', 65088 - 65080), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + chr(55) + '\x32', 34001 - 33993), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(0b1101 + 0o43) + chr(1429 - 1375), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(10362 - 10251) + chr(0b110001 + 0o2) + chr(55) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b1011 + 0o47) + chr(48) + chr(0b101110 + 0o6), 0o10), ehT0Px3KOsy9('\x30' + chr(807 - 696) + '\x35' + '\x30', 24699 - 24691), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\060', 0b1000), ehT0Px3KOsy9(chr(74 - 26) + '\157' + chr(55) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x32' + chr(0b10011 + 0o37) + chr(0b110100 + 0o2), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100000 + 0o20) + '\x6f' + '\065' + chr(2046 - 1998), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x1a'), '\x64' + chr(4515 - 4414) + chr(8931 - 8832) + chr(0b1000000 + 0o57) + '\x64' + chr(101))(chr(4516 - 4399) + '\164' + chr(102) + '\x2d' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ZE_xH_hy4CFU(e1jVqMSBZ01Y, GR1581dR5rDS):
e1jVqMSBZ01Y = IDJ2eXGCBCDu.cast(e1jVqMSBZ01Y, dtype=IDJ2eXGCBCDu.int32)
GR1581dR5rDS = IDJ2eXGCBCDu.cast(GR1581dR5rDS, dtype=IDJ2eXGCBCDu.int32)
ign79hDwEGZ5 = IDJ2eXGCBCDu.image.psnr(e1jVqMSBZ01Y, GR1581dR5rDS, max_val=ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1273 - 1222) + chr(55) + chr(0b101111 + 0o10), 12029 - 12021))
xyNBHWxn_aiq = IDJ2eXGCBCDu.image.ssim(e1jVqMSBZ01Y, GR1581dR5rDS, max_val=ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + chr(0b110111) + chr(55), 8))
return (ign79hDwEGZ5, xyNBHWxn_aiq)
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/video_metrics.py
|
get_zipped_dataset_from_predictions
|
def get_zipped_dataset_from_predictions(predictions):
"""Creates dataset from in-memory predictions."""
targets = stack_data_given_key(predictions, "targets")
outputs = stack_data_given_key(predictions, "outputs")
num_videos, num_steps = targets.shape[:2]
# Truncate output time-steps to match target time-steps
outputs = outputs[:, :num_steps]
targets_placeholder = tf.placeholder(targets.dtype, targets.shape)
outputs_placeholder = tf.placeholder(outputs.dtype, outputs.shape)
dataset = tf.data.Dataset.from_tensor_slices(
(targets_placeholder, outputs_placeholder))
iterator = dataset.make_initializable_iterator()
feed_dict = {targets_placeholder: targets,
outputs_placeholder: outputs}
return iterator, feed_dict, num_videos
|
python
|
def get_zipped_dataset_from_predictions(predictions):
"""Creates dataset from in-memory predictions."""
targets = stack_data_given_key(predictions, "targets")
outputs = stack_data_given_key(predictions, "outputs")
num_videos, num_steps = targets.shape[:2]
# Truncate output time-steps to match target time-steps
outputs = outputs[:, :num_steps]
targets_placeholder = tf.placeholder(targets.dtype, targets.shape)
outputs_placeholder = tf.placeholder(outputs.dtype, outputs.shape)
dataset = tf.data.Dataset.from_tensor_slices(
(targets_placeholder, outputs_placeholder))
iterator = dataset.make_initializable_iterator()
feed_dict = {targets_placeholder: targets,
outputs_placeholder: outputs}
return iterator, feed_dict, num_videos
|
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] |
Creates dataset from in-memory predictions.
|
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/video_metrics.py#L116-L132
|
train
|
Creates a dataset from in - memory predictions.
|
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(50) + chr(51) + chr(1614 - 1559), ord("\x08")), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1100 + 0o143) + chr(0b110100) + '\x32', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(409 - 360) + chr(55) + chr(55), 0o10), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(0b1010110 + 0o31) + chr(903 - 854) + chr(97 - 47) + chr(0b11111 + 0o25), 0b1000), ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\x6f' + chr(0b101010 + 0o10) + chr(1936 - 1886) + chr(443 - 393), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(1260 - 1209) + chr(1021 - 971) + '\x34', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101101 + 0o6) + chr(0b110001) + chr(394 - 342), 41613 - 41605), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(48) + chr(4574 - 4463) + chr(0b110010) + '\066' + '\064', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b101001 + 0o11) + '\x30' + chr(0b110011), 0b1000), ehT0Px3KOsy9('\x30' + chr(5918 - 5807) + chr(732 - 681) + chr(508 - 454) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(1629 - 1581) + '\157' + chr(50) + '\x33' + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(467 - 419) + chr(0b101000 + 0o107) + chr(0b100111 + 0o13) + chr(1628 - 1580) + chr(0b101011 + 0o11), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\063' + chr(0b110110) + '\065', 25086 - 25078), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31' + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1010011 + 0o34) + chr(49) + chr(1043 - 993) + chr(2632 - 2580), 8), ehT0Px3KOsy9(chr(363 - 315) + chr(111) + '\062' + '\x32' + chr(48), 26931 - 26923), ehT0Px3KOsy9(chr(48) + chr(0b1101101 + 0o2) + '\x31', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(737 - 687) + chr(1152 - 1097) + chr(0b10010 + 0o42), ord("\x08")), ehT0Px3KOsy9('\060' + chr(2966 - 2855) + chr(0b110110) + '\x35', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001 + 0o1) + chr(0b110110) + '\x34', 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101010 + 0o10) + '\x35' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1101111) + chr(0b110001) + chr(48) + '\x30', 0o10), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b1101111) + '\063' + '\067' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(1444 - 1396) + chr(0b1101111) + chr(0b110001) + '\x33' + chr(0b100001 + 0o17), ord("\x08")), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\157' + chr(1133 - 1078) + '\x36', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\064', 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(1902 - 1853) + chr(49) + chr(0b100110 + 0o21), 36074 - 36066), ehT0Px3KOsy9(chr(48) + chr(0b100001 + 0o116) + chr(0b110001) + '\x35' + chr(0b111 + 0o57), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + '\x30' + '\x31', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(8427 - 8316) + chr(51) + chr(152 - 98) + '\x33', 64898 - 64890), ehT0Px3KOsy9('\060' + '\157' + chr(0b11001 + 0o31) + chr(49) + chr(0b101 + 0o53), 22218 - 22210), ehT0Px3KOsy9('\x30' + '\x6f' + chr(51) + '\x36' + '\063', 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + chr(0b110101) + chr(55), 0b1000), ehT0Px3KOsy9('\060' + chr(8119 - 8008) + chr(50) + chr(0b110110) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\x6f' + chr(0b1000 + 0o51) + chr(48) + '\064', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + chr(0b110000 + 0o6), 42630 - 42622), ehT0Px3KOsy9('\x30' + '\x6f' + '\x32' + chr(0b110001) + '\066', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(639 - 528) + '\x32' + chr(0b110011) + chr(2095 - 2041), 0b1000), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1101111) + chr(0b101011 + 0o7) + chr(444 - 394) + chr(52), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b11011 + 0o32) + chr(0b11010 + 0o26), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1'), '\x64' + chr(101) + chr(0b1100011) + chr(0b110100 + 0o73) + '\144' + chr(0b1100101))(chr(0b100011 + 0o122) + '\x74' + '\146' + chr(0b100011 + 0o12) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def AieXDFR9AeH2(qIQi_VFCIFZL):
xIEmRseySp3z = GLCMl6IfVcI9(qIQi_VFCIFZL, xafqLlk3kkUe(SXOLrMavuUCe(b'\xebC\r3\xf7\xa0\xbf'), chr(100) + '\x65' + '\143' + chr(111) + chr(6512 - 6412) + '\145')(chr(0b1110101) + '\164' + chr(1388 - 1286) + '\x2d' + chr(0b11101 + 0o33)))
Dx_DllZ8uCko = GLCMl6IfVcI9(qIQi_VFCIFZL, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf0W\x0b$\xe7\xa0\xbf'), chr(0b1100100) + chr(1928 - 1827) + chr(0b1100011) + '\157' + '\144' + chr(0b100010 + 0o103))(chr(0b1010101 + 0o40) + '\x74' + chr(0b1100110) + chr(45) + '\x38'))
(winPy1dgL9st, UQsgPnJC3jY0) = xIEmRseySp3z.nauYfLglTpcb[:ehT0Px3KOsy9(chr(91 - 43) + chr(111) + chr(50), 0o10)]
Dx_DllZ8uCko = Dx_DllZ8uCko[:, :UQsgPnJC3jY0]
SVfZih79i_Nq = IDJ2eXGCBCDu.placeholder(xIEmRseySp3z.jSV9IKnemH7K, xIEmRseySp3z.nauYfLglTpcb)
GVEOIpQRBeVq = IDJ2eXGCBCDu.placeholder(Dx_DllZ8uCko.jSV9IKnemH7K, Dx_DllZ8uCko.nauYfLglTpcb)
xQt6gV9VfTO3 = IDJ2eXGCBCDu.data.Dataset.from_tensor_slices((SVfZih79i_Nq, GVEOIpQRBeVq))
qS80gn7HOKhx = xQt6gV9VfTO3.make_initializable_iterator()
knvK4sqTZWNg = {SVfZih79i_Nq: xIEmRseySp3z, GVEOIpQRBeVq: Dx_DllZ8uCko}
return (qS80gn7HOKhx, knvK4sqTZWNg, winPy1dgL9st)
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/video_metrics.py
|
compute_one_decoding_video_metrics
|
def compute_one_decoding_video_metrics(iterator, feed_dict, num_videos):
"""Computes the average of all the metric for one decoding.
Args:
iterator: dataset iterator.
feed_dict: feed dict to initialize iterator.
num_videos: number of videos.
Returns:
all_psnr: 2-D Numpy array, shape=(num_samples, num_frames)
all_ssim: 2-D Numpy array, shape=(num_samples, num_frames)
"""
output, target = iterator.get_next()
metrics = psnr_and_ssim(output, target)
with tf.Session() as sess:
sess.run(tf.local_variables_initializer())
initalizer = iterator._initializer # pylint: disable=protected-access
if initalizer is not None:
sess.run(initalizer, feed_dict=feed_dict)
all_psnr, all_ssim = [], []
for i in range(num_videos):
print("Computing video: %d" % i)
psnr_np, ssim_np = sess.run(metrics)
all_psnr.append(psnr_np)
all_ssim.append(ssim_np)
all_psnr = np.array(all_psnr)
all_ssim = np.array(all_ssim)
return all_psnr, all_ssim
|
python
|
def compute_one_decoding_video_metrics(iterator, feed_dict, num_videos):
"""Computes the average of all the metric for one decoding.
Args:
iterator: dataset iterator.
feed_dict: feed dict to initialize iterator.
num_videos: number of videos.
Returns:
all_psnr: 2-D Numpy array, shape=(num_samples, num_frames)
all_ssim: 2-D Numpy array, shape=(num_samples, num_frames)
"""
output, target = iterator.get_next()
metrics = psnr_and_ssim(output, target)
with tf.Session() as sess:
sess.run(tf.local_variables_initializer())
initalizer = iterator._initializer # pylint: disable=protected-access
if initalizer is not None:
sess.run(initalizer, feed_dict=feed_dict)
all_psnr, all_ssim = [], []
for i in range(num_videos):
print("Computing video: %d" % i)
psnr_np, ssim_np = sess.run(metrics)
all_psnr.append(psnr_np)
all_ssim.append(ssim_np)
all_psnr = np.array(all_psnr)
all_ssim = np.array(all_ssim)
return all_psnr, all_ssim
|
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Computes the average of all the metric for one decoding.
Args:
iterator: dataset iterator.
feed_dict: feed dict to initialize iterator.
num_videos: number of videos.
Returns:
all_psnr: 2-D Numpy array, shape=(num_samples, num_frames)
all_ssim: 2-D Numpy array, shape=(num_samples, num_frames)
|
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/video_metrics.py#L135-L164
|
train
|
Computes the average of all the metric for one 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(chr(48) + chr(8795 - 8684) + chr(1787 - 1737) + chr(50) + chr(54), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + '\x33' + chr(1144 - 1095), ord("\x08")), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b1101111) + '\x31' + chr(2582 - 2528) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(111) + chr(53) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + '\063' + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(111) + chr(1388 - 1339) + '\x34' + chr(0b101 + 0o62), ord("\x08")), ehT0Px3KOsy9(chr(1051 - 1003) + '\157' + chr(0b1100 + 0o46) + chr(0b100011 + 0o15) + '\060', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\x32' + '\x37' + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x33' + chr(49) + chr(1327 - 1276), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\066', 0b1000), ehT0Px3KOsy9(chr(48) + chr(3135 - 3024) + chr(50) + chr(54), 0b1000), ehT0Px3KOsy9(chr(1983 - 1935) + chr(4618 - 4507) + chr(1568 - 1519) + chr(51) + chr(0b110 + 0o55), 0b1000), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(111) + chr(51) + chr(0b110000) + chr(1847 - 1795), 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\x6f' + chr(51) + chr(0b1001 + 0o52) + chr(51), 8), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\x6f' + chr(49) + chr(0b101110 + 0o4) + chr(0b110110), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101100 + 0o3) + chr(197 - 146) + chr(51), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(10140 - 10029) + chr(0b10010 + 0o37) + '\x32' + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\x6f' + chr(1327 - 1276) + '\062' + '\x31', 0b1000), ehT0Px3KOsy9(chr(1386 - 1338) + chr(0b1101111) + '\x31' + chr(0b11101 + 0o32) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b10011 + 0o35) + '\x6f' + chr(0b110001) + '\066' + chr(53), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(11123 - 11012) + chr(0b110011) + '\067' + chr(0b10 + 0o56), 23564 - 23556), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b1101111) + chr(0b10100 + 0o41) + chr(0b110110), 31218 - 31210), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1172 - 1123) + chr(0b110100) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b1 + 0o62) + '\061', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b101111 + 0o2) + '\x33' + '\063', 8), ehT0Px3KOsy9('\060' + '\157' + chr(110 - 61) + '\x36' + chr(0b101011 + 0o5), 8), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(111) + chr(51) + chr(0b110001) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110111) + chr(188 - 133), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x32' + chr(54), 8), ehT0Px3KOsy9(chr(543 - 495) + '\x6f' + chr(51) + chr(0b110110) + '\x31', 0b1000), ehT0Px3KOsy9(chr(1196 - 1148) + chr(3395 - 3284) + chr(49) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + chr(0b110101) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1100100 + 0o13) + chr(0b110001) + '\x37' + chr(2016 - 1965), 7139 - 7131), ehT0Px3KOsy9(chr(921 - 873) + chr(0b1101111) + chr(52) + chr(0b110000), 0o10), ehT0Px3KOsy9('\060' + chr(0b110111 + 0o70) + '\061' + chr(0b110111) + chr(1826 - 1778), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(55) + chr(53), 0b1000), ehT0Px3KOsy9(chr(1130 - 1082) + chr(0b101011 + 0o104) + chr(2575 - 2522) + chr(52), 52867 - 52859), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110000 + 0o6) + chr(0b110011), 57502 - 57494), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110011) + chr(0b101001 + 0o13) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(111) + '\063' + '\060', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(111) + '\065' + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb8'), '\144' + chr(101) + '\x63' + chr(0b1101111) + chr(0b1100100) + chr(0b1100101))(chr(117) + chr(0b1110100) + chr(0b1100110) + chr(0b10100 + 0o31) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def VT4XUnzsK_G7(qS80gn7HOKhx, knvK4sqTZWNg, winPy1dgL9st):
(e1jVqMSBZ01Y, GR1581dR5rDS) = qS80gn7HOKhx.get_next()
yYegMqDoSfs5 = ZE_xH_hy4CFU(e1jVqMSBZ01Y, GR1581dR5rDS)
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc5\xbc\x03^\xb2\x08\xee'), '\x64' + '\145' + chr(5597 - 5498) + chr(0b1110 + 0o141) + chr(100) + chr(0b1100101 + 0o0))(chr(0b101000 + 0o115) + chr(116) + chr(102) + chr(45) + chr(829 - 773)))() as HVWCHjSQ2I35:
xafqLlk3kkUe(HVWCHjSQ2I35, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe5\xbe\x04\x18\x992\xb6\x88\xa9qLi'), '\144' + chr(0b1100101) + '\143' + chr(9640 - 9529) + chr(0b100111 + 0o75) + chr(0b1100101))(chr(5828 - 5711) + chr(116) + chr(102) + chr(0b101101) + chr(0b111000)))(xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfa\xb6\x13L\xb78\xf6\xd8\xb9ow9\xa8\xbe%D=\xbf\x16\x01\x91O\rp!\x15\xbb'), '\144' + chr(0b1010 + 0o133) + chr(0b1100011) + '\157' + chr(0b1100100) + '\145')('\165' + chr(116) + chr(5317 - 5215) + '\055' + chr(0b101111 + 0o11)))())
uLh_1pIC4mbv = qS80gn7HOKhx._initializer
if uLh_1pIC4mbv is not None:
xafqLlk3kkUe(HVWCHjSQ2I35, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe5\xbe\x04\x18\x992\xb6\x88\xa9qLi'), chr(0b1110 + 0o126) + '\x65' + '\x63' + chr(0b11 + 0o154) + '\x64' + chr(101))(chr(0b1010110 + 0o37) + chr(0b11101 + 0o127) + '\x66' + chr(45) + chr(284 - 228)))(uLh_1pIC4mbv, feed_dict=knvK4sqTZWNg)
(kIsgdqbhW5yd, rShKxkeLEHsf) = ([], [])
for WVxHKyX45z_L in vQr8gNKaIaWE(winPy1dgL9st):
zLUzGokYBM2Z(xafqLlk3kkUe(SXOLrMavuUCe(b'\xd5\xb6\x1d]\xae\x13\xe9\xd7\xac&`2\xa0\xbe9!t\xf4\x1b'), chr(8778 - 8678) + chr(820 - 719) + chr(7622 - 7523) + chr(0b1101111) + '\144' + '\x65')(chr(0b1110101) + '\164' + '\146' + '\x2d' + '\070') % WVxHKyX45z_L)
(dA4Pj7ObFGIK, B16emZZzyuwf) = HVWCHjSQ2I35.sgt5BU61bwZ2(yYegMqDoSfs5)
xafqLlk3kkUe(kIsgdqbhW5yd, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf7\xa9\x00H\xb5\x03'), chr(100) + chr(0b1100101) + chr(99) + chr(111) + chr(7225 - 7125) + '\x65')(chr(2829 - 2712) + chr(0b1010111 + 0o35) + chr(0b1100110) + chr(45) + chr(56)))(dA4Pj7ObFGIK)
xafqLlk3kkUe(rShKxkeLEHsf, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf7\xa9\x00H\xb5\x03'), '\144' + chr(0b1010000 + 0o25) + '\x63' + '\x6f' + chr(100) + chr(0b1100101))(chr(4007 - 3890) + chr(116) + chr(4297 - 4195) + chr(938 - 893) + '\070'))(B16emZZzyuwf)
kIsgdqbhW5yd = WqUC3KWvYVup.B0ePDhpqxN5n(kIsgdqbhW5yd)
rShKxkeLEHsf = WqUC3KWvYVup.B0ePDhpqxN5n(rShKxkeLEHsf)
return (kIsgdqbhW5yd, rShKxkeLEHsf)
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/video_metrics.py
|
reduce_to_best_decode
|
def reduce_to_best_decode(metrics, reduce_func):
"""Extracts the best-decode from the metrics according to reduce_func.
Args:
metrics: 3-D numpy array, shape=(num_decodes, num_samples, num_frames)
reduce_func: callable, np.argmax or np.argmin.
Returns:
best_metrics: 2-D numpy array, shape=(num_samples, num_frames).
best_decode_ind: 1-D numpy array, shape=(num_samples,)
"""
num_videos = metrics.shape[1]
# Take mean of the metric across the frames to approximate the video
# closest to the ground truth.
mean_across_frames = np.mean(metrics, axis=-1)
# For every sample, use the decode that has a maximum mean-metric.
best_decode_ind = reduce_func(mean_across_frames, axis=0)
best_metrics = metrics[best_decode_ind, np.arange(num_videos), :]
return best_metrics, best_decode_ind
|
python
|
def reduce_to_best_decode(metrics, reduce_func):
"""Extracts the best-decode from the metrics according to reduce_func.
Args:
metrics: 3-D numpy array, shape=(num_decodes, num_samples, num_frames)
reduce_func: callable, np.argmax or np.argmin.
Returns:
best_metrics: 2-D numpy array, shape=(num_samples, num_frames).
best_decode_ind: 1-D numpy array, shape=(num_samples,)
"""
num_videos = metrics.shape[1]
# Take mean of the metric across the frames to approximate the video
# closest to the ground truth.
mean_across_frames = np.mean(metrics, axis=-1)
# For every sample, use the decode that has a maximum mean-metric.
best_decode_ind = reduce_func(mean_across_frames, axis=0)
best_metrics = metrics[best_decode_ind, np.arange(num_videos), :]
return best_metrics, best_decode_ind
|
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Extracts the best-decode from the metrics according to reduce_func.
Args:
metrics: 3-D numpy array, shape=(num_decodes, num_samples, num_frames)
reduce_func: callable, np.argmax or np.argmin.
Returns:
best_metrics: 2-D numpy array, shape=(num_samples, num_frames).
best_decode_ind: 1-D numpy array, shape=(num_samples,)
|
[
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"-",
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"metrics",
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/video_metrics.py#L167-L185
|
train
|
Extracts the best - decode from the metrics according to reduce_func.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b100000 + 0o23) + '\x31' + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(48) + chr(139 - 28) + chr(54) + chr(0b11011 + 0o30), 210 - 202), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\x6f' + chr(50) + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b101 + 0o53) + '\x6f' + chr(0b1000 + 0o51) + '\066' + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\x6f' + '\063' + '\x34', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(674 - 623) + chr(154 - 103) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x37' + chr(0b100011 + 0o24), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b11110 + 0o121) + chr(0b110011) + chr(0b110000) + '\062', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b101 + 0o152) + chr(0b11111 + 0o24) + chr(0b110111) + '\061', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x32' + chr(0b110110) + '\061', 0b1000), ehT0Px3KOsy9(chr(1362 - 1314) + '\x6f' + '\063' + chr(0b110110) + chr(0b0 + 0o62), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b11100 + 0o27) + chr(0b1101 + 0o47) + chr(0b101011 + 0o7), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(193 - 144) + chr(1725 - 1676) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + '\065' + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(856 - 808) + chr(8599 - 8488) + chr(0b10 + 0o61) + '\063' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110100) + chr(662 - 607), 0b1000), ehT0Px3KOsy9(chr(1203 - 1155) + chr(0b1101111) + chr(50) + chr(479 - 425) + chr(725 - 672), 48657 - 48649), ehT0Px3KOsy9('\060' + chr(0b10000 + 0o137) + chr(50) + chr(0b110101 + 0o0) + chr(0b1001 + 0o54), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + '\063' + chr(0b101111 + 0o10), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1560 - 1511) + chr(52), 6960 - 6952), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + chr(0b10000 + 0o42) + '\x36', 7042 - 7034), ehT0Px3KOsy9('\x30' + chr(0b1000101 + 0o52) + chr(197 - 146) + chr(0b0 + 0o63) + chr(0b100000 + 0o25), 8), ehT0Px3KOsy9('\060' + chr(111) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(111) + chr(1255 - 1204) + '\065' + '\067', 8), ehT0Px3KOsy9(chr(0b110000) + chr(746 - 635) + chr(49) + chr(858 - 809) + '\x34', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x33' + chr(0b1010 + 0o50) + chr(1764 - 1714), 38601 - 38593), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + chr(53) + '\063', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(5743 - 5632) + '\062' + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(6838 - 6727) + chr(0b11101 + 0o31) + '\x32', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + '\064' + '\067', 0o10), ehT0Px3KOsy9(chr(458 - 410) + '\157' + '\062' + '\x37' + chr(0b100111 + 0o13), 3082 - 3074), ehT0Px3KOsy9(chr(48) + '\x6f' + '\063' + '\060' + chr(50), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b101100 + 0o6) + chr(2041 - 1992) + '\061', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x31' + '\060' + chr(0b11100 + 0o24), 34729 - 34721), ehT0Px3KOsy9(chr(0b110000) + chr(0b101 + 0o152) + '\x37' + chr(51), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1010011 + 0o34) + chr(0b11 + 0o63) + chr(0b110000), 61609 - 61601), ehT0Px3KOsy9(chr(0b0 + 0o60) + '\157' + chr(687 - 638) + chr(2689 - 2635) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1100 + 0o143) + chr(0b100101 + 0o14) + chr(0b11001 + 0o36) + '\x35', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1001101 + 0o42) + chr(0b110011) + '\x36' + chr(0b1 + 0o62), ord("\x08")), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(111) + chr(0b110010) + chr(50) + '\x37', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(5489 - 5378) + chr(1496 - 1443) + chr(0b110000), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xe2'), '\144' + '\145' + chr(0b1010110 + 0o15) + chr(0b101110 + 0o101) + chr(0b1100100) + chr(101))(chr(117) + '\164' + '\x66' + '\x2d' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def _g76MwAWeWlI(yYegMqDoSfs5, d6YvoFGCQbn8):
winPy1dgL9st = yYegMqDoSfs5.nauYfLglTpcb[ehT0Px3KOsy9(chr(1549 - 1501) + '\x6f' + chr(0b110001), 0b1000)]
bi_Vtix90R2b = WqUC3KWvYVup.aJhItC_Vawlw(yYegMqDoSfs5, axis=-ehT0Px3KOsy9(chr(48) + chr(0b101111 + 0o100) + chr(0b10 + 0o57), 8))
p1PXgfg2izJc = d6YvoFGCQbn8(bi_Vtix90R2b, axis=ehT0Px3KOsy9(chr(1289 - 1241) + chr(1811 - 1700) + '\x30', 8))
TKnLaOgH_K5S = yYegMqDoSfs5[p1PXgfg2izJc, WqUC3KWvYVup.arange(winPy1dgL9st), :]
return (TKnLaOgH_K5S, p1PXgfg2izJc)
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/video_metrics.py
|
compute_all_metrics_statistics
|
def compute_all_metrics_statistics(all_results):
"""Computes statistics of metrics across multiple decodings.
Args:
all_results: dict of 3-D numpy arrays.
Each array has shape=(num_decodes, num_samples, num_frames).
Returns:
statistics: dict of 1-D numpy arrays, shape=(num_frames).
First the statistic (max/mean/std) is computed across the
decodes, then the mean is taken across num_samples.
decode_inds: dict of 1-D numpy arrays, shape=(num_samples,)
Each element represents the index of the decode corresponding
to the best statistic.
"""
statistics = {}
decode_inds = {}
all_metrics = all_results.keys()
for key in all_metrics:
values = all_results[key]
statistics[key + "_MEAN"] = np.mean(values, axis=0)
statistics[key + "_STD"] = np.std(values, axis=0)
min_stats, min_decode_ind = reduce_to_best_decode(values, np.argmin)
statistics[key + "_MIN"] = min_stats
decode_inds[key + "_MIN_DECODE"] = min_decode_ind
max_stats, max_decode_ind = reduce_to_best_decode(values, np.argmax)
statistics[key + "_MAX"] = max_stats
decode_inds[key + "_MAX_DECODE"] = max_decode_ind
# Computes mean of each statistic across the dataset.
for key in statistics:
statistics[key] = np.mean(statistics[key], axis=0)
return statistics, decode_inds
|
python
|
def compute_all_metrics_statistics(all_results):
"""Computes statistics of metrics across multiple decodings.
Args:
all_results: dict of 3-D numpy arrays.
Each array has shape=(num_decodes, num_samples, num_frames).
Returns:
statistics: dict of 1-D numpy arrays, shape=(num_frames).
First the statistic (max/mean/std) is computed across the
decodes, then the mean is taken across num_samples.
decode_inds: dict of 1-D numpy arrays, shape=(num_samples,)
Each element represents the index of the decode corresponding
to the best statistic.
"""
statistics = {}
decode_inds = {}
all_metrics = all_results.keys()
for key in all_metrics:
values = all_results[key]
statistics[key + "_MEAN"] = np.mean(values, axis=0)
statistics[key + "_STD"] = np.std(values, axis=0)
min_stats, min_decode_ind = reduce_to_best_decode(values, np.argmin)
statistics[key + "_MIN"] = min_stats
decode_inds[key + "_MIN_DECODE"] = min_decode_ind
max_stats, max_decode_ind = reduce_to_best_decode(values, np.argmax)
statistics[key + "_MAX"] = max_stats
decode_inds[key + "_MAX_DECODE"] = max_decode_ind
# Computes mean of each statistic across the dataset.
for key in statistics:
statistics[key] = np.mean(statistics[key], axis=0)
return statistics, decode_inds
|
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Computes statistics of metrics across multiple decodings.
Args:
all_results: dict of 3-D numpy arrays.
Each array has shape=(num_decodes, num_samples, num_frames).
Returns:
statistics: dict of 1-D numpy arrays, shape=(num_frames).
First the statistic (max/mean/std) is computed across the
decodes, then the mean is taken across num_samples.
decode_inds: dict of 1-D numpy arrays, shape=(num_samples,)
Each element represents the index of the decode corresponding
to the best statistic.
|
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/video_metrics.py#L188-L220
|
train
|
Computes statistics of metrics across multiple decodings.
|
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(1112 - 1064) + chr(111) + chr(50) + '\060' + chr(1686 - 1632), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1590 - 1537) + chr(872 - 822), 17304 - 17296), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x35' + chr(1468 - 1413), ord("\x08")), ehT0Px3KOsy9(chr(1425 - 1377) + chr(0b1101111) + chr(0b10010 + 0o41) + '\064' + chr(0b100110 + 0o16), 40707 - 40699), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(54) + chr(0b0 + 0o63), ord("\x08")), ehT0Px3KOsy9(chr(1306 - 1258) + chr(111) + chr(51) + chr(0b110000) + chr(0b100101 + 0o22), ord("\x08")), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(111) + chr(0b100001 + 0o22) + chr(772 - 723) + chr(0b10 + 0o64), 13169 - 13161), ehT0Px3KOsy9(chr(1401 - 1353) + chr(111) + chr(1881 - 1830) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b0 + 0o63) + chr(0b110000) + chr(0b101110 + 0o2), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(2373 - 2322) + chr(0b1111 + 0o41) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1319 - 1268) + chr(984 - 931) + '\x35', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110111) + chr(0b100000 + 0o27), 0b1000), ehT0Px3KOsy9('\060' + chr(0b11 + 0o154) + chr(51) + chr(0b1010 + 0o50) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(10933 - 10822) + chr(0b1000 + 0o51) + chr(0b11010 + 0o30) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x32' + chr(51) + chr(0b11010 + 0o34), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b110011 + 0o74) + '\063' + chr(52) + chr(1318 - 1267), 50902 - 50894), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b1010 + 0o47) + '\x31' + chr(54), 45421 - 45413), ehT0Px3KOsy9('\060' + chr(0b1010100 + 0o33) + '\067' + '\063', 0o10), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\x6f' + chr(271 - 222) + '\x37' + chr(55), 27094 - 27086), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110111) + chr(0b101000 + 0o12), 0o10), ehT0Px3KOsy9(chr(1870 - 1822) + chr(2387 - 2276) + '\061' + chr(0b110010) + chr(1866 - 1813), 0o10), ehT0Px3KOsy9(chr(0b101001 + 0o7) + '\x6f' + '\061' + '\063' + chr(0b101101 + 0o3), 0o10), ehT0Px3KOsy9(chr(1604 - 1556) + chr(12311 - 12200) + chr(49) + chr(2081 - 2033) + chr(1505 - 1456), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b11101 + 0o25) + chr(54) + chr(534 - 485), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\061' + chr(583 - 528), 15989 - 15981), ehT0Px3KOsy9('\060' + chr(5681 - 5570) + chr(0b110 + 0o61) + chr(2632 - 2578), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(2331 - 2220) + '\061' + '\x33' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b100 + 0o57) + chr(53) + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(0b110111) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b10000 + 0o137) + chr(0b101110 + 0o3) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\157' + '\061' + chr(1867 - 1818) + chr(1632 - 1581), 0b1000), ehT0Px3KOsy9('\060' + chr(4446 - 4335) + chr(0b11100 + 0o25) + chr(50) + '\x30', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(1235 - 1185) + chr(0b101110 + 0o10) + chr(49), 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b101 + 0o55) + '\x34' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + chr(0b11111 + 0o26) + '\x36', 49381 - 49373), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2293 - 2242) + chr(0b101011 + 0o10) + chr(48), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110101) + chr(0b11101 + 0o23), 0o10), ehT0Px3KOsy9(chr(666 - 618) + chr(111) + chr(0b1101 + 0o46) + chr(0b110001) + '\062', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\064', 0o10), ehT0Px3KOsy9(chr(938 - 890) + '\x6f' + chr(50) + chr(272 - 224) + chr(0b110101), 13585 - 13577)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110101) + '\x30', 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xa8'), '\144' + chr(101) + '\143' + chr(0b1011110 + 0o21) + chr(100) + '\x65')('\165' + chr(116) + '\146' + chr(45) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Qo3Ff0ReiFg9(avFs0855rVKi):
YUsWrtZTFZy3 = {}
DLql_UzLBLot = {}
NINq2lVTrR_6 = avFs0855rVKi.keys()
for K3J4ZwSlE0sT in NINq2lVTrR_6:
SPnCNu54H1db = avFs0855rVKi[K3J4ZwSlE0sT]
YUsWrtZTFZy3[K3J4ZwSlE0sT + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd9gj\xa5}'), '\144' + '\145' + chr(0b1100011) + '\x6f' + '\x64' + chr(0b1100101))(chr(13372 - 13255) + chr(116) + chr(0b1001 + 0o135) + '\055' + chr(1643 - 1587))] = WqUC3KWvYVup.aJhItC_Vawlw(SPnCNu54H1db, axis=ehT0Px3KOsy9('\x30' + chr(9085 - 8974) + chr(0b10011 + 0o35), 0o10))
YUsWrtZTFZy3[K3J4ZwSlE0sT + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd9y{\xa0'), '\x64' + chr(10041 - 9940) + '\x63' + chr(0b1101010 + 0o5) + chr(9318 - 9218) + chr(101))('\165' + '\x74' + chr(0b1100110) + '\x2d' + chr(0b111000))] = WqUC3KWvYVup.o3E_VFExiNOk(SPnCNu54H1db, axis=ehT0Px3KOsy9('\x30' + chr(111) + '\060', 8))
(nckZv5CpeSeA, CfGIhBExjRAA) = _g76MwAWeWlI(SPnCNu54H1db, WqUC3KWvYVup.argmin)
YUsWrtZTFZy3[K3J4ZwSlE0sT + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd9gf\xaa'), '\144' + chr(101) + '\143' + chr(0b1101111) + chr(0b1001010 + 0o32) + '\145')(chr(117) + chr(116) + chr(0b1011010 + 0o14) + '\x2d' + chr(2626 - 2570))] = nckZv5CpeSeA
DLql_UzLBLot[K3J4ZwSlE0sT + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd9gf\xaal\x83\x8b[\x8f\x80\xa8'), chr(3974 - 3874) + '\x65' + '\x63' + chr(11241 - 11130) + chr(0b100011 + 0o101) + '\x65')(chr(0b1110101) + '\164' + chr(0b1100100 + 0o2) + chr(0b100101 + 0o10) + '\070')] = CfGIhBExjRAA
(q2imAbFFByyR, IJd_cCymj7oa) = _g76MwAWeWlI(SPnCNu54H1db, WqUC3KWvYVup.argmax)
YUsWrtZTFZy3[K3J4ZwSlE0sT + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd9gn\xbc'), chr(0b1100100) + chr(0b1100101) + '\143' + chr(0b111111 + 0o60) + chr(0b1100100) + chr(1941 - 1840))('\x75' + chr(116) + '\x66' + chr(0b101101) + chr(0b111000))] = q2imAbFFByyR
DLql_UzLBLot[K3J4ZwSlE0sT + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd9gn\xbcl\x83\x8b[\x8f\x80\xa8'), '\x64' + chr(5107 - 5006) + '\x63' + chr(0b1101111) + chr(5842 - 5742) + chr(1712 - 1611))(chr(0b11111 + 0o126) + chr(116) + '\x66' + chr(0b1110 + 0o37) + chr(0b111000))] = IJd_cCymj7oa
for K3J4ZwSlE0sT in YUsWrtZTFZy3:
YUsWrtZTFZy3[K3J4ZwSlE0sT] = WqUC3KWvYVup.aJhItC_Vawlw(YUsWrtZTFZy3[K3J4ZwSlE0sT], axis=ehT0Px3KOsy9(chr(380 - 332) + chr(0b1101110 + 0o1) + chr(1199 - 1151), 8))
return (YUsWrtZTFZy3, DLql_UzLBLot)
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/video_metrics.py
|
compute_video_metrics_from_predictions
|
def compute_video_metrics_from_predictions(predictions, decode_hparams):
"""Computes metrics from predictions.
Args:
predictions: list of list of dicts.
outer length: num_decodes, inner_length: num_samples
decode_hparams: Decode hparams. instance of HParams.
Returns:
statistics: dict of Tensors, key being the metric with each Tensor
having the shape (num_samples, num_frames).
"""
all_results = {}
ssim_all_decodes, psnr_all_decodes = [], []
for single_decode in predictions:
args = get_zipped_dataset_from_predictions(single_decode)
psnr_single, ssim_single = compute_one_decoding_video_metrics(*args)
psnr_all_decodes.append(psnr_single)
ssim_all_decodes.append(ssim_single)
psnr_all_decodes = np.array(psnr_all_decodes)
ssim_all_decodes = np.array(ssim_all_decodes)
all_results.update({"PSNR": psnr_all_decodes, "SSIM": ssim_all_decodes})
return compute_all_metrics_statistics(all_results)
|
python
|
def compute_video_metrics_from_predictions(predictions, decode_hparams):
"""Computes metrics from predictions.
Args:
predictions: list of list of dicts.
outer length: num_decodes, inner_length: num_samples
decode_hparams: Decode hparams. instance of HParams.
Returns:
statistics: dict of Tensors, key being the metric with each Tensor
having the shape (num_samples, num_frames).
"""
all_results = {}
ssim_all_decodes, psnr_all_decodes = [], []
for single_decode in predictions:
args = get_zipped_dataset_from_predictions(single_decode)
psnr_single, ssim_single = compute_one_decoding_video_metrics(*args)
psnr_all_decodes.append(psnr_single)
ssim_all_decodes.append(ssim_single)
psnr_all_decodes = np.array(psnr_all_decodes)
ssim_all_decodes = np.array(ssim_all_decodes)
all_results.update({"PSNR": psnr_all_decodes, "SSIM": ssim_all_decodes})
return compute_all_metrics_statistics(all_results)
|
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] |
Computes metrics from predictions.
Args:
predictions: list of list of dicts.
outer length: num_decodes, inner_length: num_samples
decode_hparams: Decode hparams. instance of HParams.
Returns:
statistics: dict of Tensors, key being the metric with each Tensor
having the shape (num_samples, num_frames).
|
[
"Computes",
"metrics",
"from",
"predictions",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/video_metrics.py#L223-L246
|
train
|
Computes metrics from predictions.
|
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(0b11101 + 0o122) + '\x32' + '\x35' + chr(1407 - 1352), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b1100 + 0o50), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + chr(240 - 192), 9995 - 9987), ehT0Px3KOsy9('\x30' + '\157' + chr(0b1010 + 0o47) + chr(61 - 13) + chr(0b100 + 0o54), 0o10), ehT0Px3KOsy9('\x30' + chr(4681 - 4570) + chr(49) + chr(0b110111) + chr(0b11101 + 0o23), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b11110 + 0o121) + chr(0b110011) + chr(0b110110) + chr(0b110010), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(2070 - 2019) + '\x31' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(2689 - 2578) + chr(1580 - 1526), ord("\x08")), ehT0Px3KOsy9(chr(1624 - 1576) + chr(111) + '\x31' + chr(1148 - 1099) + chr(374 - 321), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b1100 + 0o45) + chr(52) + chr(0b110100), 57476 - 57468), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100011 + 0o14) + chr(0b101001 + 0o13) + '\064', 20902 - 20894), ehT0Px3KOsy9(chr(1130 - 1082) + chr(0b1101111) + chr(0b100111 + 0o12) + chr(1774 - 1726), 0o10), ehT0Px3KOsy9('\x30' + chr(0b111111 + 0o60) + chr(1072 - 1018) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + '\062' + chr(2593 - 2538), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x35' + '\065', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b110000 + 0o77) + chr(51) + chr(0b110111) + '\x32', 55165 - 55157), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b10101 + 0o41) + chr(0b100000 + 0o22), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x32' + '\x34' + chr(213 - 161), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + chr(0b100001 + 0o21) + chr(1345 - 1292), ord("\x08")), ehT0Px3KOsy9(chr(2256 - 2208) + '\x6f' + '\062' + '\x33' + chr(1764 - 1709), 0o10), ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\x6f' + chr(0b110011) + chr(0b100010 + 0o17) + chr(55), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1111 + 0o42) + '\x32' + '\x31', 0o10), ehT0Px3KOsy9('\x30' + chr(5014 - 4903) + chr(0b100101 + 0o14) + '\065' + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b1101111) + chr(0b100101 + 0o15) + chr(50) + chr(0b10011 + 0o44), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b11000 + 0o32) + chr(0b100011 + 0o16) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(111) + chr(2210 - 2161) + chr(0b101110 + 0o11) + chr(0b110010), 46518 - 46510), ehT0Px3KOsy9(chr(48) + '\157' + chr(1013 - 962) + chr(0b110111) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + chr(2190 - 2138) + chr(0b100100 + 0o17), 55263 - 55255), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110000 + 0o3) + chr(0b101001 + 0o12) + chr(2589 - 2538), 0b1000), ehT0Px3KOsy9(chr(1526 - 1478) + chr(8881 - 8770) + chr(366 - 316) + '\060' + '\x30', 0o10), ehT0Px3KOsy9(chr(0b100010 + 0o16) + '\x6f' + chr(51) + '\067' + chr(1160 - 1106), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x31' + chr(0b101000 + 0o15) + chr(1999 - 1947), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001) + chr(2647 - 2592), 0o10), ehT0Px3KOsy9('\x30' + chr(2834 - 2723) + chr(0b100001 + 0o21) + chr(1546 - 1497) + chr(51), 65132 - 65124), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + '\060' + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(479 - 431) + '\x6f' + '\x32' + chr(0b10010 + 0o37) + chr(0b110100), 56935 - 56927), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + chr(54) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1101111) + chr(0b110010) + chr(135 - 81) + chr(55), 0o10), ehT0Px3KOsy9(chr(559 - 511) + '\x6f' + chr(0b110001) + chr(595 - 541) + chr(0b1100 + 0o50), 0b1000), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(4869 - 4758) + '\062' + chr(919 - 865) + chr(618 - 568), 695 - 687)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\x6f' + chr(0b1010 + 0o53) + chr(940 - 892), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x81'), chr(0b1100100) + chr(5000 - 4899) + '\x63' + chr(0b1101111) + '\144' + chr(0b1100101))('\165' + '\x74' + chr(0b1100110) + '\055' + chr(0b10001 + 0o47)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def KM03wYXQYIxr(qIQi_VFCIFZL, LrQSWg3uwmK8):
avFs0855rVKi = {}
(cXIt_Zgu9uXD, cPBBKlXKLwL1) = ([], [])
for uLdgt5CZKKhh in qIQi_VFCIFZL:
kJDRfRhcZHjS = AieXDFR9AeH2(uLdgt5CZKKhh)
(lwLDp7XEuEiC, jGJ9KYW0_4v4) = VT4XUnzsK_G7(*kJDRfRhcZHjS)
xafqLlk3kkUe(cPBBKlXKLwL1, xafqLlk3kkUe(SXOLrMavuUCe(b'\xcet`%\x16\x96'), '\x64' + '\x65' + chr(99) + '\157' + '\x64' + '\145')(chr(8695 - 8578) + chr(116) + '\x66' + '\055' + chr(56)))(lwLDp7XEuEiC)
xafqLlk3kkUe(cXIt_Zgu9uXD, xafqLlk3kkUe(SXOLrMavuUCe(b'\xcet`%\x16\x96'), chr(100) + chr(4557 - 4456) + '\x63' + '\x6f' + chr(9695 - 9595) + chr(3010 - 2909))('\x75' + '\164' + chr(0b1100001 + 0o5) + chr(1947 - 1902) + '\x38'))(jGJ9KYW0_4v4)
cPBBKlXKLwL1 = WqUC3KWvYVup.B0ePDhpqxN5n(cPBBKlXKLwL1)
cXIt_Zgu9uXD = WqUC3KWvYVup.B0ePDhpqxN5n(cXIt_Zgu9uXD)
xafqLlk3kkUe(avFs0855rVKi, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf5pQ\x05\x11\xbc\x84h4PA8'), '\x64' + chr(101) + chr(99) + '\x6f' + chr(329 - 229) + chr(101))(chr(117) + chr(11110 - 10994) + chr(102) + chr(1415 - 1370) + '\x38'))({xafqLlk3kkUe(SXOLrMavuUCe(b'\xffW^\x12'), '\144' + chr(0b1100101) + '\143' + chr(0b1101111) + chr(100) + chr(0b1001001 + 0o34))(chr(570 - 453) + chr(12131 - 12015) + chr(3144 - 3042) + chr(0b10010 + 0o33) + '\x38'): cPBBKlXKLwL1, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfcWY\r'), chr(0b1100100) + chr(101) + chr(444 - 345) + '\157' + '\x64' + '\x65')(chr(0b1110101) + '\164' + chr(0b1100110) + chr(1964 - 1919) + chr(56)): cXIt_Zgu9uXD})
return Qo3Ff0ReiFg9(avFs0855rVKi)
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/video_metrics.py
|
compute_video_metrics_from_png_files
|
def compute_video_metrics_from_png_files(
output_dirs, problem_name, video_length, frame_shape):
"""Computes the average of all the metric for one decoding.
This function assumes that all the predicted and target frames
have been saved on the disk and sorting them by name will result
to consecutive frames saved in order.
Args:
output_dirs: directory with all the saved frames.
problem_name: prefix of the saved frames usually name of the problem.
video_length: length of the videos.
frame_shape: shape of each frame in HxWxC format.
Returns:
Dictionary which contains the average of each metric per frame.
"""
ssim_all_decodes, psnr_all_decodes = [], []
for output_dir in output_dirs:
output_files, target_files = get_target_and_output_filepatterns(
output_dir, problem_name)
args = get_zipped_dataset_from_png_files(
output_files, target_files, video_length, frame_shape)
psnr_single, ssim_single = compute_one_decoding_video_metrics(*args)
psnr_all_decodes.append(psnr_single)
ssim_all_decodes.append(ssim_single)
psnr_all_decodes = np.array(psnr_all_decodes)
ssim_all_decodes = np.array(ssim_all_decodes)
all_results = {"PSNR": psnr_all_decodes, "SSIM": ssim_all_decodes}
return compute_all_metrics_statistics(all_results)
|
python
|
def compute_video_metrics_from_png_files(
output_dirs, problem_name, video_length, frame_shape):
"""Computes the average of all the metric for one decoding.
This function assumes that all the predicted and target frames
have been saved on the disk and sorting them by name will result
to consecutive frames saved in order.
Args:
output_dirs: directory with all the saved frames.
problem_name: prefix of the saved frames usually name of the problem.
video_length: length of the videos.
frame_shape: shape of each frame in HxWxC format.
Returns:
Dictionary which contains the average of each metric per frame.
"""
ssim_all_decodes, psnr_all_decodes = [], []
for output_dir in output_dirs:
output_files, target_files = get_target_and_output_filepatterns(
output_dir, problem_name)
args = get_zipped_dataset_from_png_files(
output_files, target_files, video_length, frame_shape)
psnr_single, ssim_single = compute_one_decoding_video_metrics(*args)
psnr_all_decodes.append(psnr_single)
ssim_all_decodes.append(ssim_single)
psnr_all_decodes = np.array(psnr_all_decodes)
ssim_all_decodes = np.array(ssim_all_decodes)
all_results = {"PSNR": psnr_all_decodes, "SSIM": ssim_all_decodes}
return compute_all_metrics_statistics(all_results)
|
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] |
Computes the average of all the metric for one decoding.
This function assumes that all the predicted and target frames
have been saved on the disk and sorting them by name will result
to consecutive frames saved in order.
Args:
output_dirs: directory with all the saved frames.
problem_name: prefix of the saved frames usually name of the problem.
video_length: length of the videos.
frame_shape: shape of each frame in HxWxC format.
Returns:
Dictionary which contains the average of each metric per frame.
|
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/video_metrics.py#L249-L279
|
train
|
Computes the average of all the metric for one decoding.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1143 - 1095) + chr(6726 - 6615) + chr(49) + chr(48) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(1552 - 1504) + chr(1859 - 1748) + '\061' + chr(50) + '\067', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(492 - 442) + chr(0b110111) + chr(0b110011), 0b1000), ehT0Px3KOsy9('\060' + chr(11956 - 11845) + '\x35' + '\066', 0o10), ehT0Px3KOsy9(chr(48) + chr(1081 - 970) + '\064', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + chr(0b0 + 0o65) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b10001 + 0o37) + '\157' + chr(51) + chr(0b0 + 0o61) + chr(639 - 585), 0o10), ehT0Px3KOsy9('\060' + chr(4168 - 4057) + chr(0b110010) + chr(0b11 + 0o57) + '\067', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(7765 - 7654) + chr(2382 - 2333) + chr(0b100011 + 0o22) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(0b11101 + 0o24) + '\060', 41823 - 41815), ehT0Px3KOsy9('\060' + chr(2006 - 1895) + chr(2204 - 2153) + '\066', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1111 + 0o44) + '\x35' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(111) + '\062' + chr(2058 - 2005) + '\x30', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(980 - 929) + '\064' + '\067', 0o10), ehT0Px3KOsy9('\060' + chr(8412 - 8301) + chr(52) + chr(3011 - 2956), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11101 + 0o24) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x35' + chr(271 - 223), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x31' + chr(1243 - 1194) + chr(430 - 380), 36004 - 35996), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\157' + chr(0b110011) + chr(50) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000011 + 0o54) + chr(0b110001) + chr(2423 - 2373) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + '\060' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1101111) + '\067' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b111 + 0o54) + chr(48) + chr(0b100000 + 0o21), 27831 - 27823), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(51) + '\x32', 15373 - 15365), ehT0Px3KOsy9(chr(0b110000) + chr(9365 - 9254) + chr(0b110001) + chr(0b110111) + '\062', 0o10), ehT0Px3KOsy9('\x30' + chr(1860 - 1749) + chr(1804 - 1753) + chr(0b110100) + chr(0b110101), 6876 - 6868), ehT0Px3KOsy9('\x30' + chr(10092 - 9981) + chr(0b110010) + chr(0b110001) + chr(981 - 933), 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\x33' + chr(0b110010) + chr(53), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\062' + chr(53) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\157' + chr(1624 - 1573) + '\063' + chr(0b101101 + 0o7), 62123 - 62115), ehT0Px3KOsy9(chr(469 - 421) + chr(111) + '\x36' + chr(49), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + '\067' + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(1264 - 1216) + '\157' + chr(0b110011) + chr(55) + '\061', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(2216 - 2167) + '\067', 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(0b10101 + 0o36) + '\065', 17801 - 17793), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + '\x36' + '\x30', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b101 + 0o54) + '\062' + chr(55), 8), ehT0Px3KOsy9('\x30' + '\157' + '\063' + chr(0b110100) + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\x6f' + chr(0b110010 + 0o0) + chr(324 - 272) + chr(0b110011), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(298 - 250) + chr(9843 - 9732) + '\065' + '\x30', 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'o'), '\x64' + '\145' + chr(156 - 57) + '\x6f' + chr(0b1100100) + '\x65')('\165' + '\x74' + chr(8204 - 8102) + chr(67 - 22) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def B4TjaqSuf2Wp(Y_PWX8ooWmlm, wezGpYDorAsK, KK_OXZqCJ1S_, eut3NH0zeXzv):
(cXIt_Zgu9uXD, cPBBKlXKLwL1) = ([], [])
for nd0OX_BS6_o4 in Y_PWX8ooWmlm:
(j3WX3QRvIfaK, ZitfIDad90LP) = y4krzMoP71KJ(nd0OX_BS6_o4, wezGpYDorAsK)
kJDRfRhcZHjS = mqfEKEGoItwU(j3WX3QRvIfaK, ZitfIDad90LP, KK_OXZqCJ1S_, eut3NH0zeXzv)
(lwLDp7XEuEiC, jGJ9KYW0_4v4) = VT4XUnzsK_G7(*kJDRfRhcZHjS)
xafqLlk3kkUe(cPBBKlXKLwL1, xafqLlk3kkUe(SXOLrMavuUCe(b" '\xcbKj\x8a"), '\x64' + '\x65' + chr(0b1011 + 0o130) + '\x6f' + chr(3317 - 3217) + '\x65')('\x75' + '\164' + chr(0b1010000 + 0o26) + '\055' + chr(0b111000)))(lwLDp7XEuEiC)
xafqLlk3kkUe(cXIt_Zgu9uXD, xafqLlk3kkUe(SXOLrMavuUCe(b" '\xcbKj\x8a"), '\144' + chr(0b111100 + 0o51) + '\143' + chr(0b11010 + 0o125) + chr(0b1100100) + chr(5140 - 5039))('\x75' + chr(0b1110100) + chr(0b110101 + 0o61) + chr(0b101101) + chr(56)))(jGJ9KYW0_4v4)
cPBBKlXKLwL1 = WqUC3KWvYVup.B0ePDhpqxN5n(cPBBKlXKLwL1)
cXIt_Zgu9uXD = WqUC3KWvYVup.B0ePDhpqxN5n(cXIt_Zgu9uXD)
avFs0855rVKi = {xafqLlk3kkUe(SXOLrMavuUCe(b'\x11\x04\xf5|'), chr(0b0 + 0o144) + '\x65' + chr(6823 - 6724) + chr(0b110000 + 0o77) + chr(0b1001001 + 0o33) + chr(0b1100101))(chr(0b1110101) + '\164' + '\146' + '\x2d' + chr(0b10001 + 0o47)): cPBBKlXKLwL1, xafqLlk3kkUe(SXOLrMavuUCe(b'\x12\x04\xf2c'), chr(0b1100100) + '\145' + chr(0b1001010 + 0o31) + chr(0b111000 + 0o67) + chr(0b1100010 + 0o2) + chr(101))(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + '\x2d' + chr(56)): cXIt_Zgu9uXD}
return Qo3Ff0ReiFg9(avFs0855rVKi)
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/video_metrics.py
|
compute_and_save_video_metrics
|
def compute_and_save_video_metrics(
output_dirs, problem_name, video_length, frame_shape):
"""Compute and saves the video metrics."""
statistics, all_results = compute_video_metrics_from_png_files(
output_dirs, problem_name, video_length, frame_shape)
for results, output_dir in zip(all_results, output_dirs):
save_results(results, output_dir, problem_name)
parent_dir = os.path.join(output_dirs[0], os.pardir)
final_dir = os.path.join(parent_dir, "decode")
tf.gfile.MakeDirs(parent_dir)
save_results(statistics, final_dir, problem_name)
|
python
|
def compute_and_save_video_metrics(
output_dirs, problem_name, video_length, frame_shape):
"""Compute and saves the video metrics."""
statistics, all_results = compute_video_metrics_from_png_files(
output_dirs, problem_name, video_length, frame_shape)
for results, output_dir in zip(all_results, output_dirs):
save_results(results, output_dir, problem_name)
parent_dir = os.path.join(output_dirs[0], os.pardir)
final_dir = os.path.join(parent_dir, "decode")
tf.gfile.MakeDirs(parent_dir)
save_results(statistics, final_dir, problem_name)
|
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] |
Compute and saves the video metrics.
|
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/video_metrics.py#L282-L294
|
train
|
Compute and saves the video 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(chr(1422 - 1374) + '\157' + '\x32' + '\061' + chr(55), 63578 - 63570), ehT0Px3KOsy9('\060' + '\157' + chr(50) + chr(0b110011) + chr(0b11011 + 0o27), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + '\066' + chr(0b110100), 1023 - 1015), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b101000 + 0o12) + chr(1766 - 1716) + '\067', 39642 - 39634), ehT0Px3KOsy9(chr(2112 - 2064) + chr(0b1101111) + '\x32' + chr(0b1101 + 0o44) + chr(0b1011 + 0o54), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + '\x37' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(844 - 796) + chr(0b100011 + 0o114) + chr(0b110001) + '\063' + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x33' + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(1776 - 1726) + '\x37' + chr(0b110000 + 0o6), 53334 - 53326), ehT0Px3KOsy9('\x30' + chr(0b101110 + 0o101) + chr(0b110110) + '\x34', 0b1000), ehT0Px3KOsy9(chr(48) + chr(2669 - 2558) + '\x32' + chr(53) + chr(48), ord("\x08")), ehT0Px3KOsy9('\060' + chr(8777 - 8666) + chr(0b101100 + 0o6) + chr(2408 - 2355) + chr(940 - 891), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063' + '\061', 0b1000), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1001010 + 0o45) + '\x33' + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b11 + 0o154) + '\063' + chr(0b110101) + chr(1141 - 1087), 0b1000), ehT0Px3KOsy9(chr(522 - 474) + '\x6f' + '\x33' + chr(593 - 538), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000011 + 0o54) + chr(0b1001 + 0o54) + chr(0b110100), 52833 - 52825), ehT0Px3KOsy9(chr(795 - 747) + '\157' + chr(49) + chr(350 - 295) + chr(0b110101 + 0o2), ord("\x08")), ehT0Px3KOsy9('\060' + chr(6150 - 6039) + chr(0b110011) + chr(1892 - 1840) + chr(0b110100), 23719 - 23711), ehT0Px3KOsy9(chr(0b110000) + chr(6967 - 6856) + chr(0b110010) + chr(0b110101) + '\064', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(0b110010) + '\x37', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1100100 + 0o13) + '\063' + '\062' + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010 + 0o0) + chr(50), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b11010 + 0o27) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(9383 - 9272) + '\x31' + chr(0b11110 + 0o31) + chr(0b110011), 6500 - 6492), ehT0Px3KOsy9(chr(443 - 395) + chr(0b100010 + 0o115) + chr(0b101110 + 0o5) + '\060' + chr(50), 0o10), ehT0Px3KOsy9(chr(1751 - 1703) + chr(0b1101111 + 0o0) + chr(0b110001) + '\060' + chr(0b10110 + 0o41), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(2492 - 2381) + chr(0b110001 + 0o2) + chr(49) + chr(0b110001), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + chr(2401 - 2346) + '\063', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(0b10001 + 0o37) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + chr(6249 - 6138) + '\063' + chr(0b110100) + '\061', 0b1000), ehT0Px3KOsy9(chr(2157 - 2109) + '\x6f' + chr(129 - 79) + chr(529 - 479) + '\x30', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + '\x33' + chr(0b10110 + 0o35), 54484 - 54476), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010101 + 0o32) + chr(0b110 + 0o53) + chr(0b10 + 0o56), 22574 - 22566), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(0b100100 + 0o17) + chr(0b110111), 0b1000), ehT0Px3KOsy9('\060' + chr(0b110001 + 0o76) + chr(0b110001) + '\066' + '\x33', 41800 - 41792), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(0b110011) + '\x35', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b100000 + 0o23) + chr(0b1101 + 0o45) + chr(2198 - 2143), 8), ehT0Px3KOsy9(chr(0b1 + 0o57) + '\157' + chr(0b110011) + '\064', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + '\064' + chr(0b110100), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(53) + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xa1'), chr(100) + '\x65' + chr(0b110111 + 0o54) + chr(0b1101111) + '\x64' + chr(0b1100101))('\x75' + chr(0b1110100) + chr(102) + chr(0b101 + 0o50) + chr(0b101011 + 0o15)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def uLTFsfX5N5Xm(Y_PWX8ooWmlm, wezGpYDorAsK, KK_OXZqCJ1S_, eut3NH0zeXzv):
(YUsWrtZTFZy3, avFs0855rVKi) = B4TjaqSuf2Wp(Y_PWX8ooWmlm, wezGpYDorAsK, KK_OXZqCJ1S_, eut3NH0zeXzv)
for (iIGKX2zSEGYP, nd0OX_BS6_o4) in pZ0NK2y6HRbn(avFs0855rVKi, Y_PWX8ooWmlm):
lWttvtjfMffg(iIGKX2zSEGYP, nd0OX_BS6_o4, wezGpYDorAsK)
bsdJzEjGYYxg = oqhJDdMJfuwx.path.join(Y_PWX8ooWmlm[ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b1101111) + chr(48), 0o10)], oqhJDdMJfuwx.pardir)
Vpg5pBRYRIgZ = oqhJDdMJfuwx.path.join(bsdJzEjGYYxg, xafqLlk3kkUe(SXOLrMavuUCe(b'\xeb\xff\xd7\xf8\xeb\x9b'), '\x64' + chr(101) + '\143' + chr(111) + chr(100) + chr(101))(chr(5016 - 4899) + '\x74' + chr(0b10101 + 0o121) + chr(0b11100 + 0o21) + chr(0b10100 + 0o44)))
xafqLlk3kkUe(IDJ2eXGCBCDu.gfile, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc2\xfb\xdf\xf2\xcb\x97+l'), chr(0b1100100) + chr(0b1100101 + 0o0) + chr(0b1100011) + chr(111) + '\144' + chr(101))(chr(8597 - 8480) + chr(4194 - 4078) + chr(0b1100110) + chr(1496 - 1451) + '\070'))(bsdJzEjGYYxg)
lWttvtjfMffg(YUsWrtZTFZy3, Vpg5pBRYRIgZ, wezGpYDorAsK)
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
swap_time_and_batch_axes
|
def swap_time_and_batch_axes(inputs):
"""Swaps time and batch axis (the first two axis)."""
transposed_axes = tf.concat([[1, 0], tf.range(2, tf.rank(inputs))], axis=0)
return tf.transpose(inputs, transposed_axes)
|
python
|
def swap_time_and_batch_axes(inputs):
"""Swaps time and batch axis (the first two axis)."""
transposed_axes = tf.concat([[1, 0], tf.range(2, tf.rank(inputs))], axis=0)
return tf.transpose(inputs, transposed_axes)
|
[
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"swap_time_and_batch_axes",
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"transposed_axes",
"=",
"tf",
".",
"concat",
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"[",
"[",
"1",
",",
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"]",
",",
"tf",
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"range",
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",",
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"rank",
"(",
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")",
"]",
",",
"axis",
"=",
"0",
")",
"return",
"tf",
".",
"transpose",
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] |
Swaps time and batch axis (the first two axis).
|
[
"Swaps",
"time",
"and",
"batch",
"axis",
"(",
"the",
"first",
"two",
"axis",
")",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L41-L44
|
train
|
Swaps time and batch axis.
|
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' + '\x31' + chr(0b11 + 0o56) + chr(710 - 661), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101010 + 0o5) + '\x37' + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(12287 - 12176) + '\x37' + '\062', 8), ehT0Px3KOsy9(chr(2082 - 2034) + '\x6f' + chr(0b10 + 0o61) + chr(55) + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b110110 + 0o71) + chr(0b11011 + 0o27) + chr(0b101010 + 0o11) + chr(55), 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + '\x35' + '\x35', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b100110 + 0o20), 0o10), ehT0Px3KOsy9(chr(48) + chr(1913 - 1802) + chr(0b100111 + 0o13) + chr(0b10100 + 0o43) + chr(2057 - 2002), 38502 - 38494), ehT0Px3KOsy9('\060' + chr(111) + chr(49) + '\061' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\066' + chr(0b110010), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + chr(0b110001 + 0o2) + chr(2674 - 2620), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(8300 - 8189) + chr(1010 - 956) + chr(0b110111), 18890 - 18882), ehT0Px3KOsy9(chr(373 - 325) + chr(0b1001110 + 0o41) + chr(51) + chr(0b110110) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(0b110000 + 0o77) + chr(0b110001) + chr(0b1100 + 0o50) + chr(2113 - 2063), 0b1000), ehT0Px3KOsy9(chr(48) + chr(724 - 613) + '\064', 17585 - 17577), ehT0Px3KOsy9(chr(177 - 129) + chr(7285 - 7174) + chr(0b1110 + 0o45) + '\x32', 18004 - 17996), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110100) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x32' + '\064' + chr(55), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + '\x30' + '\x37', 885 - 877), ehT0Px3KOsy9(chr(340 - 292) + '\157' + chr(0b110010) + '\060' + chr(54), 13214 - 13206), ehT0Px3KOsy9(chr(48) + chr(8782 - 8671) + chr(0b10010 + 0o41) + chr(0b110100) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(0b110011) + chr(1281 - 1233), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(51) + chr(119 - 69) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x35' + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(236 - 188) + '\x6f' + chr(0b110101) + chr(48), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11010 + 0o27) + chr(0b101111 + 0o10) + chr(391 - 340), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(8767 - 8656) + chr(2627 - 2573) + chr(0b110000), 48767 - 48759), ehT0Px3KOsy9('\060' + chr(11806 - 11695) + '\x33' + chr(0b110110) + chr(0b1101 + 0o47), ord("\x08")), ehT0Px3KOsy9(chr(1436 - 1388) + chr(0b1101111) + chr(49) + chr(55) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b1000011 + 0o54) + chr(1668 - 1619) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b100111 + 0o110) + '\061' + chr(465 - 411) + '\064', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\062' + chr(0b110100) + chr(0b101101 + 0o11), 40642 - 40634), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + chr(1506 - 1454) + chr(0b101 + 0o61), 53010 - 53002), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + chr(52) + chr(1570 - 1521), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100110 + 0o13) + chr(0b110101) + '\064', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(50) + '\x30' + chr(0b101010 + 0o15), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b100 + 0o153) + '\x37' + chr(2204 - 2154), 8), ehT0Px3KOsy9('\060' + chr(0b1000100 + 0o53) + '\062' + chr(48) + chr(51), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(50) + '\063' + '\062', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + chr(2153 - 2099) + '\065', 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b111110 + 0o61) + chr(0b101001 + 0o14) + chr(0b1011 + 0o45), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'g'), chr(0b1100100) + chr(0b100101 + 0o100) + '\x63' + chr(0b111001 + 0o66) + '\x64' + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + chr(0b100111 + 0o77) + chr(45) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def xlDAa6mELHHC(vXoupepMtCXU):
sVBB3j521aKF = IDJ2eXGCBCDu.concat([[ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31', 4651 - 4643), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(2914 - 2803) + chr(0b100111 + 0o11), 0b1000)], IDJ2eXGCBCDu.range(ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\x6f' + chr(0b0 + 0o62), 56335 - 56327), IDJ2eXGCBCDu.rank(vXoupepMtCXU))], axis=ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1101111) + chr(0b110000), 8))
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'=H[\x94\xec\x9di\xcc+'), '\144' + chr(0b1100010 + 0o3) + chr(0b100000 + 0o103) + chr(8024 - 7913) + '\x64' + chr(9252 - 9151))(chr(0b1110101) + chr(0b1001111 + 0o45) + chr(8692 - 8590) + '\055' + chr(56)))(vXoupepMtCXU, sVBB3j521aKF)
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
encode_to_shape
|
def encode_to_shape(inputs, shape, scope):
"""Encode the given tensor to given image shape."""
with tf.variable_scope(scope, reuse=tf.AUTO_REUSE):
w, h = shape[1], shape[2]
x = inputs
x = tfl.flatten(x)
x = tfl.dense(x, w * h, activation=None, name="enc_dense")
x = tf.reshape(x, (-1, w, h, 1))
return x
|
python
|
def encode_to_shape(inputs, shape, scope):
"""Encode the given tensor to given image shape."""
with tf.variable_scope(scope, reuse=tf.AUTO_REUSE):
w, h = shape[1], shape[2]
x = inputs
x = tfl.flatten(x)
x = tfl.dense(x, w * h, activation=None, name="enc_dense")
x = tf.reshape(x, (-1, w, h, 1))
return x
|
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Encode the given tensor to given image shape.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L47-L55
|
train
|
Encode the given tensor to given image 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 + 0o0) + chr(0b1101111) + chr(0b110001) + chr(0b110010) + '\063', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + '\066' + '\067', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(1348 - 1293) + chr(2663 - 2610), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b101010 + 0o105) + chr(0b110011) + chr(50) + chr(0b110001), 56973 - 56965), ehT0Px3KOsy9('\060' + chr(111) + chr(1556 - 1506) + chr(50) + chr(0b110111), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b110111) + chr(1571 - 1520), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(786 - 735) + chr(55) + chr(0b100100 + 0o20), ord("\x08")), ehT0Px3KOsy9('\060' + chr(9158 - 9047) + '\x37' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(1028 - 980) + chr(0b1101111) + chr(0b110100) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\157' + chr(0b1010 + 0o51) + '\062' + chr(53), 0o10), ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\157' + '\065' + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(55) + chr(50), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(2509 - 2455) + chr(0b1001 + 0o55), 0b1000), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(0b1101111) + chr(0b110001) + chr(0b110010) + chr(1487 - 1438), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(8344 - 8233) + chr(49) + '\062' + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(2283 - 2234) + '\x34' + chr(0b100101 + 0o20), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b11010 + 0o31) + '\x33' + chr(55), 24054 - 24046), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\x6f' + '\063' + '\064' + chr(0b110011), 43297 - 43289), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110101) + '\x32', 8), ehT0Px3KOsy9('\x30' + chr(2944 - 2833) + chr(1394 - 1343) + '\x33' + chr(0b110000), 31056 - 31048), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + chr(55) + chr(51), 29883 - 29875), ehT0Px3KOsy9(chr(0b110000) + chr(0b111101 + 0o62) + chr(49) + chr(51) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b11011 + 0o124) + chr(0b10101 + 0o35) + '\066' + chr(0b1100 + 0o50), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + chr(432 - 380) + chr(329 - 280), 29570 - 29562), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(2543 - 2432) + chr(1627 - 1576) + '\x36' + chr(0b100011 + 0o21), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b100011 + 0o114) + chr(49) + '\x37', 0o10), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\157' + chr(50) + '\063' + chr(2187 - 2133), 0b1000), ehT0Px3KOsy9(chr(0b1011 + 0o45) + '\157' + chr(0b11010 + 0o27) + '\060' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(0b1101111) + '\067' + chr(1011 - 956), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + '\x36' + chr(0b101111 + 0o2), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101 + 0o54) + chr(50) + chr(0b110011 + 0o4), 8), ehT0Px3KOsy9(chr(48) + chr(4443 - 4332) + chr(551 - 499) + chr(0b110111), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + '\061' + '\065', 10624 - 10616), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(111) + chr(455 - 405) + chr(0b100110 + 0o13) + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(1216 - 1105) + chr(0b100000 + 0o21) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b101011 + 0o7) + '\064' + chr(54), 0o10), ehT0Px3KOsy9(chr(166 - 118) + chr(0b1001100 + 0o43) + '\x31' + chr(0b110110) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(6288 - 6177) + '\x37' + chr(0b110000), 8), ehT0Px3KOsy9(chr(48) + chr(1020 - 909) + chr(49) + '\x33' + chr(49), 51829 - 51821), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(53) + '\x33', 22563 - 22555)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + '\157' + '\065' + chr(48), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'}'), chr(0b1000101 + 0o37) + '\x65' + chr(99) + '\157' + '\x64' + chr(3758 - 3657))(chr(0b1110101) + '\164' + chr(0b1100110) + chr(45) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def z7kGB17nriXF(vXoupepMtCXU, nauYfLglTpcb, CJBHNoj4zKoT):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'%\x16\x0f\xb8\xf6Y\x90]~\xa6IUF4'), chr(0b1100100) + chr(0b1000100 + 0o41) + chr(0b1100011) + chr(6572 - 6461) + '\144' + '\145')(chr(0b1010001 + 0o44) + '\164' + chr(102) + chr(0b10011 + 0o32) + chr(0b111000)))(CJBHNoj4zKoT, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x12")\x9e\xc8i\xb9mr\x90'), chr(0b1100100) + '\145' + chr(99) + '\157' + chr(3648 - 3548) + '\145')(chr(12241 - 12124) + chr(9275 - 9159) + chr(102) + chr(0b101101) + chr(0b111000)))):
(AOfzRywRzEXp, sz4HVsFVF8nL) = (nauYfLglTpcb[ehT0Px3KOsy9('\060' + '\157' + '\061', ord("\x08"))], nauYfLglTpcb[ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1011110 + 0o21) + chr(0b110010), ord("\x08"))])
OeWW0F1dBPRQ = vXoupepMtCXU
OeWW0F1dBPRQ = uWOby3XrTzFz.flatten(OeWW0F1dBPRQ)
OeWW0F1dBPRQ = uWOby3XrTzFz.dense(OeWW0F1dBPRQ, AOfzRywRzEXp * sz4HVsFVF8nL, activation=None, name=xafqLlk3kkUe(SXOLrMavuUCe(b'6\x19\x1e\x8e\xf3^\x92KD'), chr(0b110001 + 0o63) + '\x65' + '\x63' + '\157' + chr(0b100100 + 0o100) + '\x65')(chr(117) + chr(8218 - 8102) + chr(0b10100 + 0o122) + '\x2d' + '\x38'))
OeWW0F1dBPRQ = IDJ2eXGCBCDu.reshape(OeWW0F1dBPRQ, (-ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(49), 8), AOfzRywRzEXp, sz4HVsFVF8nL, ehT0Px3KOsy9(chr(0b101010 + 0o6) + '\x6f' + chr(114 - 65), 8)))
return OeWW0F1dBPRQ
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
decode_to_shape
|
def decode_to_shape(inputs, shape, scope):
"""Encode the given tensor to given image shape."""
with tf.variable_scope(scope, reuse=tf.AUTO_REUSE):
x = inputs
x = tfl.flatten(x)
x = tfl.dense(x, shape[2], activation=None, name="dec_dense")
x = tf.expand_dims(x, axis=1)
return x
|
python
|
def decode_to_shape(inputs, shape, scope):
"""Encode the given tensor to given image shape."""
with tf.variable_scope(scope, reuse=tf.AUTO_REUSE):
x = inputs
x = tfl.flatten(x)
x = tfl.dense(x, shape[2], activation=None, name="dec_dense")
x = tf.expand_dims(x, axis=1)
return x
|
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] |
Encode the given tensor to given image shape.
|
[
"Encode",
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"to",
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L58-L65
|
train
|
Encode the given tensor to given image 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(48) + '\x6f' + chr(49) + '\063', 57266 - 57258), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1500 - 1451) + '\x31' + '\063', 0b1000), ehT0Px3KOsy9(chr(687 - 639) + chr(0b1000100 + 0o53) + '\x33' + '\066' + chr(52), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x32' + '\x34', 0o10), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1101111) + chr(50) + chr(870 - 820) + '\063', 39654 - 39646), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(111) + chr(0b1 + 0o60) + chr(1566 - 1515) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b10110 + 0o32) + '\157' + '\x33' + '\065' + chr(0b11010 + 0o27), 0o10), ehT0Px3KOsy9(chr(1532 - 1484) + chr(0b1010100 + 0o33) + chr(50) + chr(0b1100 + 0o45) + chr(50), 31029 - 31021), ehT0Px3KOsy9('\x30' + chr(0b101010 + 0o105) + '\063' + '\x32' + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b1010 + 0o51) + '\061' + chr(0b110101), 25636 - 25628), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1 + 0o62) + chr(0b101010 + 0o7), 33085 - 33077), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b11100 + 0o123) + chr(48), 12142 - 12134), ehT0Px3KOsy9(chr(739 - 691) + '\157' + chr(0b110001) + chr(1377 - 1325) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b101 + 0o152) + chr(0b110100) + chr(461 - 408), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + '\066' + chr(54), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(50) + '\063' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(1508 - 1460) + chr(0b1101111) + '\x32' + chr(756 - 705) + '\x32', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110000 + 0o2) + chr(0b110 + 0o57) + chr(0b11011 + 0o31), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + '\x31' + '\066', 6207 - 6199), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010 + 0o0) + chr(0b110101) + chr(0b11110 + 0o30), 64150 - 64142), ehT0Px3KOsy9(chr(82 - 34) + chr(4414 - 4303) + '\063' + '\x36' + '\x30', 2632 - 2624), ehT0Px3KOsy9(chr(942 - 894) + chr(6658 - 6547) + chr(0b110010) + '\x33' + chr(0b111 + 0o56), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + '\062' + chr(0b110110), 8), ehT0Px3KOsy9('\x30' + chr(0b1001101 + 0o42) + chr(49) + '\x35' + chr(0b110101), 0o10), ehT0Px3KOsy9('\060' + chr(0b1000011 + 0o54) + '\066' + chr(67 - 19), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1149 - 1098) + '\067' + chr(307 - 258), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b11100 + 0o27) + chr(48), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\061' + chr(53) + chr(54), 0b1000), ehT0Px3KOsy9(chr(1432 - 1384) + '\157' + chr(1253 - 1203) + '\061' + chr(1080 - 1030), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000100 + 0o53) + chr(1284 - 1235) + chr(0b100011 + 0o22) + '\x32', 53042 - 53034), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\x6f' + chr(0b0 + 0o62) + chr(0b10010 + 0o40) + '\x31', 0b1000), ehT0Px3KOsy9(chr(1411 - 1363) + chr(9725 - 9614) + '\x34' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(1274 - 1226) + chr(0b111000 + 0o67) + chr(0b10101 + 0o34) + chr(50) + chr(542 - 492), 22397 - 22389), ehT0Px3KOsy9('\060' + chr(0b1101011 + 0o4) + chr(0b110111) + '\063', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1111 + 0o140) + chr(0b100101 + 0o20) + '\x37', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(3385 - 3274) + chr(0b10111 + 0o33) + chr(0b1111 + 0o42), 3957 - 3949), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(111) + chr(2284 - 2233) + chr(55) + chr(0b11000 + 0o30), 63434 - 63426), ehT0Px3KOsy9(chr(0b110000) + chr(11695 - 11584) + chr(0b1001 + 0o52) + '\064' + chr(0b110101), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(50) + chr(1783 - 1735) + chr(0b110000), 14163 - 14155), ehT0Px3KOsy9('\060' + chr(6062 - 5951) + chr(0b110010) + '\064', 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(1184 - 1136) + chr(0b1101111) + '\065' + '\060', 34623 - 34615)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'%'), chr(8011 - 7911) + '\x65' + chr(0b110000 + 0o63) + chr(0b1101111) + chr(4842 - 4742) + chr(0b1001011 + 0o32))(chr(7314 - 7197) + chr(10978 - 10862) + '\x66' + chr(651 - 606) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def jvtg8rpQnaej(vXoupepMtCXU, nauYfLglTpcb, CJBHNoj4zKoT):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'}*\x86}\xf2?\x85\xef\x89\xbezo\x10@'), '\x64' + chr(101) + '\143' + chr(0b1101111) + chr(0b1100100) + chr(987 - 886))(chr(12800 - 12683) + chr(0b1000000 + 0o64) + '\x66' + '\x2d' + chr(0b110010 + 0o6)))(CJBHNoj4zKoT, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'J\x1e\xa0[\xcc\x0f\xac\xdf\x85\x88'), chr(0b11001 + 0o113) + chr(101) + '\x63' + chr(3825 - 3714) + chr(0b1100100) + chr(0b1100101))(chr(0b1011110 + 0o27) + '\x74' + '\x66' + '\x2d' + chr(1894 - 1838)))):
OeWW0F1dBPRQ = vXoupepMtCXU
OeWW0F1dBPRQ = uWOby3XrTzFz.flatten(OeWW0F1dBPRQ)
OeWW0F1dBPRQ = uWOby3XrTzFz.dense(OeWW0F1dBPRQ, nauYfLglTpcb[ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b1110 + 0o44), 0b1000)], activation=None, name=xafqLlk3kkUe(SXOLrMavuUCe(b'o.\x97K\xf78\x87\xf9\xb3'), '\x64' + chr(0b1100101) + '\x63' + chr(0b1000011 + 0o54) + chr(0b1100100) + '\145')(chr(117) + chr(0b1110100) + chr(0b1100110) + '\x2d' + chr(0b111000)))
OeWW0F1dBPRQ = IDJ2eXGCBCDu.expand_dims(OeWW0F1dBPRQ, axis=ehT0Px3KOsy9('\x30' + chr(111) + chr(302 - 253), 0o10))
return OeWW0F1dBPRQ
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
basic_lstm
|
def basic_lstm(inputs, state, num_units, name=None):
"""Basic LSTM."""
input_shape = common_layers.shape_list(inputs)
# reuse parameters across time-steps.
cell = tf.nn.rnn_cell.BasicLSTMCell(
num_units, name=name, reuse=tf.AUTO_REUSE)
if state is None:
state = cell.zero_state(input_shape[0], tf.float32)
outputs, new_state = cell(inputs, state)
return outputs, new_state
|
python
|
def basic_lstm(inputs, state, num_units, name=None):
"""Basic LSTM."""
input_shape = common_layers.shape_list(inputs)
# reuse parameters across time-steps.
cell = tf.nn.rnn_cell.BasicLSTMCell(
num_units, name=name, reuse=tf.AUTO_REUSE)
if state is None:
state = cell.zero_state(input_shape[0], tf.float32)
outputs, new_state = cell(inputs, state)
return outputs, new_state
|
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":",
"input_shape",
"=",
"common_layers",
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"(",
"inputs",
")",
"# reuse parameters across time-steps.",
"cell",
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"tf",
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"nn",
".",
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".",
"BasicLSTMCell",
"(",
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",",
"name",
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")",
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] |
Basic LSTM.
|
[
"Basic",
"LSTM",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L68-L77
|
train
|
Basic LSTM.
|
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(0b10 + 0o155) + chr(0b1101 + 0o45) + chr(55) + chr(0b100000 + 0o26), 0o10), ehT0Px3KOsy9(chr(1666 - 1618) + '\157' + '\x35' + chr(0b110111), 30266 - 30258), ehT0Px3KOsy9(chr(48) + chr(111) + '\061' + '\x35' + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b111111 + 0o60) + '\x33' + '\064' + chr(2185 - 2136), 0o10), ehT0Px3KOsy9('\060' + chr(0b111010 + 0o65) + chr(50) + chr(0b1010 + 0o53) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(928 - 880) + chr(111) + chr(0b101101 + 0o6) + chr(0b1001 + 0o47) + chr(55), 34018 - 34010), ehT0Px3KOsy9(chr(1040 - 992) + '\157' + chr(50) + chr(0b100001 + 0o20) + '\x34', 61716 - 61708), ehT0Px3KOsy9('\x30' + chr(1940 - 1829) + '\x33' + chr(0b110101) + chr(0b11101 + 0o27), 59919 - 59911), ehT0Px3KOsy9(chr(48) + chr(111) + chr(598 - 544) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b1101111) + chr(50), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(51) + chr(53) + '\061', 0o10), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b1101111) + chr(839 - 787) + chr(1009 - 955), 0b1000), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\x6f' + '\062' + chr(0b10001 + 0o42) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + chr(0b10110 + 0o35) + '\x36', 50357 - 50349), ehT0Px3KOsy9('\x30' + chr(0b111100 + 0o63) + chr(0b110001) + '\065' + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1010101 + 0o32) + chr(51) + '\066' + chr(291 - 239), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(10893 - 10782) + '\x33' + chr(50) + chr(53), 0o10), ehT0Px3KOsy9(chr(389 - 341) + chr(1429 - 1318) + chr(53) + '\064', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(51) + chr(0b110101) + '\064', 8), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + chr(51) + chr(807 - 758), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(7285 - 7174) + chr(0b110010) + chr(0b100111 + 0o15) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(48) + chr(3133 - 3022) + chr(51) + '\x33', 0o10), ehT0Px3KOsy9('\060' + chr(0b10011 + 0o134) + '\061' + chr(0b10001 + 0o45) + chr(53), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + chr(2019 - 1971) + chr(0b110000), 20575 - 20567), ehT0Px3KOsy9('\060' + chr(111) + chr(226 - 177) + chr(49) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\062' + '\066' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + chr(49) + chr(0b100101 + 0o22), ord("\x08")), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(0b1101001 + 0o6) + chr(0b10100 + 0o37) + chr(0b111 + 0o52) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b10101 + 0o132) + chr(0b110011) + chr(0b1010 + 0o54) + '\060', ord("\x08")), ehT0Px3KOsy9('\060' + chr(4535 - 4424) + chr(0b110011) + chr(0b1100 + 0o52) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\066' + chr(0b11010 + 0o31), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(9181 - 9070) + chr(0b10001 + 0o41) + chr(0b100011 + 0o20) + chr(53), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b101000 + 0o107) + chr(0b110010), 8), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(111) + chr(0b110010) + '\x32' + chr(0b101010 + 0o11), ord("\x08")), ehT0Px3KOsy9('\060' + chr(5479 - 5368) + chr(0b110010) + chr(0b110001) + chr(0b10001 + 0o42), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + chr(1244 - 1191) + '\064', 8), ehT0Px3KOsy9(chr(1742 - 1694) + chr(0b1010101 + 0o32) + '\062' + '\061' + chr(0b10001 + 0o46), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b110000 + 0o77) + chr(0b110001 + 0o0), 0b1000), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(6060 - 5949) + chr(0b110011) + chr(0b101101 + 0o7) + chr(0b110101), 60498 - 60490), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49) + chr(54) + '\060', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(111) + '\x35' + '\060', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x90'), chr(100) + chr(0b1100101) + chr(6939 - 6840) + chr(0b1101111) + '\x64' + chr(0b1100001 + 0o4))(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + chr(45) + chr(1081 - 1025)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ts0MS_BK31EQ(vXoupepMtCXU, KKFQISrGeiAm, tD4pOzGSKim2, AIvJRzLdDfgF=None):
tANyZeuTfu5y = jSKPaHwSAfVv.shape_list(vXoupepMtCXU)
XQrM8eZytga5 = IDJ2eXGCBCDu.nn.rnn_cell.BasicLSTMCell(tD4pOzGSKim2, name=AIvJRzLdDfgF, reuse=IDJ2eXGCBCDu.AUTO_REUSE)
if KKFQISrGeiAm is None:
KKFQISrGeiAm = XQrM8eZytga5.zero_state(tANyZeuTfu5y[ehT0Px3KOsy9('\060' + chr(4236 - 4125) + '\x30', ord("\x08"))], IDJ2eXGCBCDu.float32)
(Dx_DllZ8uCko, bzRb0v_p_rjD) = XQrM8eZytga5(vXoupepMtCXU, KKFQISrGeiAm)
return (Dx_DllZ8uCko, bzRb0v_p_rjD)
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
lstm_cell
|
def lstm_cell(inputs,
state,
num_units,
use_peepholes=False,
cell_clip=0.0,
initializer=None,
num_proj=None,
num_unit_shards=None,
num_proj_shards=None,
reuse=None,
name=None):
"""Full LSTM cell."""
input_shape = common_layers.shape_list(inputs)
cell = tf.nn.rnn_cell.LSTMCell(num_units,
use_peepholes=use_peepholes,
cell_clip=cell_clip,
initializer=initializer,
num_proj=num_proj,
num_unit_shards=num_unit_shards,
num_proj_shards=num_proj_shards,
reuse=reuse,
name=name,
state_is_tuple=False)
if state is None:
state = cell.zero_state(input_shape[0], tf.float32)
outputs, new_state = cell(inputs, state)
return outputs, new_state
|
python
|
def lstm_cell(inputs,
state,
num_units,
use_peepholes=False,
cell_clip=0.0,
initializer=None,
num_proj=None,
num_unit_shards=None,
num_proj_shards=None,
reuse=None,
name=None):
"""Full LSTM cell."""
input_shape = common_layers.shape_list(inputs)
cell = tf.nn.rnn_cell.LSTMCell(num_units,
use_peepholes=use_peepholes,
cell_clip=cell_clip,
initializer=initializer,
num_proj=num_proj,
num_unit_shards=num_unit_shards,
num_proj_shards=num_proj_shards,
reuse=reuse,
name=name,
state_is_tuple=False)
if state is None:
state = cell.zero_state(input_shape[0], tf.float32)
outputs, new_state = cell(inputs, state)
return outputs, new_state
|
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] |
Full LSTM cell.
|
[
"Full",
"LSTM",
"cell",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L80-L106
|
train
|
Full LSTM cell.
|
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) + '\157' + chr(0b110011) + '\x32' + chr(366 - 317), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b0 + 0o62) + '\x34' + chr(0b11 + 0o57), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\062' + chr(1446 - 1398) + chr(1306 - 1256), ord("\x08")), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(4919 - 4808) + chr(1046 - 995) + '\x36' + chr(49), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b10011 + 0o36) + chr(51) + chr(49), 0b1000), ehT0Px3KOsy9(chr(2130 - 2082) + '\x6f' + '\x33' + chr(1342 - 1290) + '\067', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(0b1110 + 0o42) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32' + chr(0b110010 + 0o1) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(111) + chr(51) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\x6f' + chr(54) + chr(48), 43972 - 43964), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110101) + chr(1257 - 1207), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + chr(0b101010 + 0o6) + chr(0b1011 + 0o53), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + chr(48) + chr(0b110110), 0b1000), ehT0Px3KOsy9('\x30' + chr(6685 - 6574) + chr(0b101001 + 0o10) + '\067' + chr(1370 - 1320), 33280 - 33272), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101111 + 0o3) + '\x34' + '\x37', 0o10), ehT0Px3KOsy9('\x30' + chr(8878 - 8767) + '\x31' + chr(55) + '\x34', 0b1000), ehT0Px3KOsy9(chr(1146 - 1098) + chr(111) + '\062' + chr(0b110000) + '\067', 0o10), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(111) + chr(55) + chr(2045 - 1996), 0b1000), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b1101111) + chr(0b10111 + 0o35) + chr(0b11110 + 0o22), 17714 - 17706), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100101 + 0o15) + '\066' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(1194 - 1146) + chr(0b1101111) + '\x32' + '\066' + chr(51), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b101001 + 0o106) + chr(0b11010 + 0o33) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\063' + '\x37' + chr(50), 0o10), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(111) + chr(49) + '\064' + chr(272 - 224), 0b1000), ehT0Px3KOsy9(chr(0b10100 + 0o34) + '\157' + chr(51) + '\067' + '\064', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b101000 + 0o12) + chr(53) + chr(0b110011), 63601 - 63593), ehT0Px3KOsy9(chr(48) + chr(0b1000100 + 0o53) + '\x33' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(4655 - 4544) + '\061' + '\x32' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b11 + 0o63) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\157' + chr(53) + chr(54), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101110 + 0o1) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b111 + 0o150) + '\x30', 0b1000), ehT0Px3KOsy9(chr(399 - 351) + chr(111) + chr(51) + '\x31' + chr(0b1 + 0o60), 25679 - 25671), ehT0Px3KOsy9('\060' + '\x6f' + chr(843 - 794) + '\x33' + chr(1314 - 1266), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100001 + 0o20) + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b11 + 0o154) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(53) + chr(501 - 452), 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(345 - 294) + '\x37' + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(829 - 780) + chr(49) + chr(52), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\x6f' + chr(53) + '\060', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xff'), '\144' + '\145' + '\143' + chr(0b110001 + 0o76) + '\144' + '\x65')(chr(0b1101000 + 0o15) + chr(116) + chr(3301 - 3199) + '\x2d' + chr(2991 - 2935)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def niKwoNx3HagZ(vXoupepMtCXU, KKFQISrGeiAm, tD4pOzGSKim2, dk2mkVXJKthP=ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(518 - 470), 8), mGJiGrzbmvAH=0.0, kwfuYzkY5C57=None, OO5ZCPOMlETl=None, doj50PCmH4eB=None, fRxx2u9wj7N2=None, pmC5wdSFgdFj=None, AIvJRzLdDfgF=None):
tANyZeuTfu5y = jSKPaHwSAfVv.shape_list(vXoupepMtCXU)
XQrM8eZytga5 = IDJ2eXGCBCDu.nn.rnn_cell.LSTMCell(tD4pOzGSKim2, use_peepholes=dk2mkVXJKthP, cell_clip=mGJiGrzbmvAH, initializer=kwfuYzkY5C57, num_proj=OO5ZCPOMlETl, num_unit_shards=doj50PCmH4eB, num_proj_shards=fRxx2u9wj7N2, reuse=pmC5wdSFgdFj, name=AIvJRzLdDfgF, state_is_tuple=ehT0Px3KOsy9(chr(48) + chr(10263 - 10152) + chr(0b11100 + 0o24), 8))
if KKFQISrGeiAm is None:
KKFQISrGeiAm = XQrM8eZytga5.zero_state(tANyZeuTfu5y[ehT0Px3KOsy9(chr(1750 - 1702) + chr(111) + chr(0b100111 + 0o11), 8)], IDJ2eXGCBCDu.float32)
(Dx_DllZ8uCko, bzRb0v_p_rjD) = XQrM8eZytga5(vXoupepMtCXU, KKFQISrGeiAm)
return (Dx_DllZ8uCko, bzRb0v_p_rjD)
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
conv_lstm_2d
|
def conv_lstm_2d(inputs, state, output_channels,
kernel_size=5, name=None, spatial_dims=None):
"""2D Convolutional LSTM."""
input_shape = common_layers.shape_list(inputs)
batch_size, input_channels = input_shape[0], input_shape[-1]
if spatial_dims is None:
input_shape = input_shape[1:]
else:
input_shape = spatial_dims + [input_channels]
cell = tf.contrib.rnn.ConvLSTMCell(
2, input_shape, output_channels,
[kernel_size, kernel_size], name=name)
if state is None:
state = cell.zero_state(batch_size, tf.float32)
outputs, new_state = cell(inputs, state)
return outputs, new_state
|
python
|
def conv_lstm_2d(inputs, state, output_channels,
kernel_size=5, name=None, spatial_dims=None):
"""2D Convolutional LSTM."""
input_shape = common_layers.shape_list(inputs)
batch_size, input_channels = input_shape[0], input_shape[-1]
if spatial_dims is None:
input_shape = input_shape[1:]
else:
input_shape = spatial_dims + [input_channels]
cell = tf.contrib.rnn.ConvLSTMCell(
2, input_shape, output_channels,
[kernel_size, kernel_size], name=name)
if state is None:
state = cell.zero_state(batch_size, tf.float32)
outputs, new_state = cell(inputs, state)
return outputs, new_state
|
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] |
2D Convolutional LSTM.
|
[
"2D",
"Convolutional",
"LSTM",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L109-L125
|
train
|
2D Convolutional LSTM.
|
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) + chr(1902 - 1791) + '\062' + chr(0b110111) + chr(55), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100110 + 0o14) + chr(0b100010 + 0o22) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b11011 + 0o124) + '\x31' + chr(54) + chr(48), 25414 - 25406), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b1101111) + chr(0b110110) + '\064', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(865 - 817), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + chr(0b11000 + 0o36) + '\067', 65399 - 65391), ehT0Px3KOsy9(chr(0b110000) + chr(9673 - 9562) + '\x33' + '\x32' + chr(1464 - 1409), 0o10), ehT0Px3KOsy9(chr(48) + chr(3639 - 3528) + '\062' + '\063' + chr(0b110101), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010 + 0o5) + chr(53), 0o10), ehT0Px3KOsy9('\060' + chr(6883 - 6772) + chr(0b110011) + chr(48) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(79 - 31) + chr(5900 - 5789) + chr(0b110011) + '\x36' + chr(0b10111 + 0o40), 8), ehT0Px3KOsy9(chr(0b10000 + 0o40) + '\157' + chr(55) + chr(0b1000 + 0o57), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + chr(55) + chr(0b10100 + 0o40), ord("\x08")), ehT0Px3KOsy9('\060' + chr(3654 - 3543) + chr(51) + '\x31' + chr(0b110001), 0b1000), ehT0Px3KOsy9('\060' + chr(6026 - 5915) + chr(51) + '\063' + chr(49), 48566 - 48558), ehT0Px3KOsy9(chr(1306 - 1258) + chr(0b1101111) + chr(0b110011) + chr(0b110010) + '\065', 0b1000), ehT0Px3KOsy9(chr(1565 - 1517) + '\157' + '\062' + chr(0b110101) + '\066', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b0 + 0o60), 50928 - 50920), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + chr(48) + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\067' + chr(52), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x31' + chr(0b100011 + 0o15) + chr(0b110100), 8), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1101111) + '\061' + chr(0b11011 + 0o32) + '\060', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(2401 - 2350) + chr(51) + '\x33', 0o10), ehT0Px3KOsy9('\x30' + chr(0b101110 + 0o101) + '\063' + chr(0b110111) + chr(0b110111), 9676 - 9668), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(1795 - 1744) + chr(0b110011) + '\063', 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b100111 + 0o13) + chr(1714 - 1659) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(1124 - 1076) + '\x6f' + chr(2040 - 1988) + chr(1520 - 1470), 0o10), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(111) + '\061' + '\064' + chr(0b110111 + 0o0), 0o10), ehT0Px3KOsy9(chr(85 - 37) + '\157' + chr(1033 - 983) + '\x33' + chr(2078 - 2025), 8), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b0 + 0o157) + chr(54) + chr(0b110010), 4875 - 4867), ehT0Px3KOsy9(chr(48) + chr(0b1010011 + 0o34) + '\061', 35500 - 35492), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011) + chr(0b11001 + 0o31) + chr(0b110001 + 0o2), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + chr(0b11001 + 0o30) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(102 - 54) + '\157' + chr(50) + chr(48) + '\x37', 41741 - 41733), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b10101 + 0o132) + chr(0b11010 + 0o27) + '\x31' + chr(52), 58714 - 58706), ehT0Px3KOsy9(chr(1178 - 1130) + '\157' + chr(0b110100) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(1856 - 1808) + '\157' + chr(0b110010) + chr(419 - 367) + chr(49), 25007 - 24999), ehT0Px3KOsy9('\060' + chr(111) + '\x32', 0o10), ehT0Px3KOsy9(chr(1165 - 1117) + chr(1864 - 1753) + '\061' + chr(0b110001) + chr(0b1 + 0o66), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + '\066' + chr(0b110110), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\x6f' + chr(53) + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x91'), chr(0b1010110 + 0o16) + chr(2869 - 2768) + chr(99) + '\x6f' + '\x64' + '\x65')('\x75' + chr(0b100101 + 0o117) + chr(102) + chr(0b1000 + 0o45) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def JdcoHcHwSoPG(vXoupepMtCXU, KKFQISrGeiAm, jAT42bk66WvZ, m6gwVXy4D3Au=ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(53), 0b1000), AIvJRzLdDfgF=None, TWwVi7qAVoy2=None):
tANyZeuTfu5y = jSKPaHwSAfVv.shape_list(vXoupepMtCXU)
(ix9dZyeAmUxY, UnmU0r1RTZJ0) = (tANyZeuTfu5y[ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1480 - 1432), 8)], tANyZeuTfu5y[-ehT0Px3KOsy9(chr(746 - 698) + chr(424 - 313) + '\061', 8)])
if TWwVi7qAVoy2 is None:
tANyZeuTfu5y = tANyZeuTfu5y[ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061', 8):]
else:
tANyZeuTfu5y = TWwVi7qAVoy2 + [UnmU0r1RTZJ0]
XQrM8eZytga5 = IDJ2eXGCBCDu.contrib.rnn.ConvLSTMCell(ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(50), 8), tANyZeuTfu5y, jAT42bk66WvZ, [m6gwVXy4D3Au, m6gwVXy4D3Au], name=AIvJRzLdDfgF)
if KKFQISrGeiAm is None:
KKFQISrGeiAm = XQrM8eZytga5.zero_state(ix9dZyeAmUxY, IDJ2eXGCBCDu.float32)
(Dx_DllZ8uCko, bzRb0v_p_rjD) = XQrM8eZytga5(vXoupepMtCXU, KKFQISrGeiAm)
return (Dx_DllZ8uCko, bzRb0v_p_rjD)
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
scheduled_sample_count
|
def scheduled_sample_count(ground_truth_x,
generated_x,
batch_size,
scheduled_sample_var):
"""Sample batch with specified mix of groundtruth and generated data points.
Args:
ground_truth_x: tensor of ground-truth data points.
generated_x: tensor of generated data points.
batch_size: batch size
scheduled_sample_var: number of ground-truth examples to include in batch.
Returns:
New batch with num_ground_truth sampled from ground_truth_x and the rest
from generated_x.
"""
num_ground_truth = scheduled_sample_var
idx = tf.random_shuffle(tf.range(batch_size))
ground_truth_idx = tf.gather(idx, tf.range(num_ground_truth))
generated_idx = tf.gather(idx, tf.range(num_ground_truth, batch_size))
ground_truth_examps = tf.gather(ground_truth_x, ground_truth_idx)
generated_examps = tf.gather(generated_x, generated_idx)
output = tf.dynamic_stitch([ground_truth_idx, generated_idx],
[ground_truth_examps, generated_examps])
# if batch size is known set it.
if isinstance(batch_size, int):
output.set_shape([batch_size] + common_layers.shape_list(output)[1:])
return output
|
python
|
def scheduled_sample_count(ground_truth_x,
generated_x,
batch_size,
scheduled_sample_var):
"""Sample batch with specified mix of groundtruth and generated data points.
Args:
ground_truth_x: tensor of ground-truth data points.
generated_x: tensor of generated data points.
batch_size: batch size
scheduled_sample_var: number of ground-truth examples to include in batch.
Returns:
New batch with num_ground_truth sampled from ground_truth_x and the rest
from generated_x.
"""
num_ground_truth = scheduled_sample_var
idx = tf.random_shuffle(tf.range(batch_size))
ground_truth_idx = tf.gather(idx, tf.range(num_ground_truth))
generated_idx = tf.gather(idx, tf.range(num_ground_truth, batch_size))
ground_truth_examps = tf.gather(ground_truth_x, ground_truth_idx)
generated_examps = tf.gather(generated_x, generated_idx)
output = tf.dynamic_stitch([ground_truth_idx, generated_idx],
[ground_truth_examps, generated_examps])
# if batch size is known set it.
if isinstance(batch_size, int):
output.set_shape([batch_size] + common_layers.shape_list(output)[1:])
return output
|
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] |
Sample batch with specified mix of groundtruth and generated data points.
Args:
ground_truth_x: tensor of ground-truth data points.
generated_x: tensor of generated data points.
batch_size: batch size
scheduled_sample_var: number of ground-truth examples to include in batch.
Returns:
New batch with num_ground_truth sampled from ground_truth_x and the rest
from generated_x.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L128-L156
|
train
|
Sample a batch with specified mix of groundtruth and generated data points.
|
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' + '\062' + chr(858 - 806) + chr(0b110111), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x32' + chr(0b110101) + chr(1899 - 1844), 0o10), ehT0Px3KOsy9(chr(1038 - 990) + chr(111) + '\062' + chr(0b1011 + 0o53) + chr(0b100111 + 0o12), 0b1000), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(0b11011 + 0o124) + chr(908 - 853) + chr(115 - 64), 0o10), ehT0Px3KOsy9(chr(0b111 + 0o51) + '\157' + chr(1066 - 1016) + chr(0b110110) + chr(55), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + '\x33' + chr(53), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1001001 + 0o46) + chr(0b110001) + chr(49) + chr(0b10000 + 0o42), 0o10), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(3147 - 3036) + chr(1932 - 1883) + chr(52) + '\065', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(0b10111 + 0o35) + '\x30', 11365 - 11357), ehT0Px3KOsy9(chr(0b110000) + chr(11454 - 11343) + chr(0b101100 + 0o11) + chr(1759 - 1707), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + chr(54), 0o10), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(111) + '\067' + chr(0b110011), 8), ehT0Px3KOsy9(chr(650 - 602) + chr(2601 - 2490) + chr(50) + '\065' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(1319 - 1271) + chr(0b1100110 + 0o11) + chr(0b1100 + 0o50) + chr(0b10111 + 0o31), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b101011 + 0o10) + chr(49) + chr(51), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(0b110101) + '\x33', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\063' + '\066', 0b1000), ehT0Px3KOsy9(chr(98 - 50) + chr(111) + chr(0b1001 + 0o50) + chr(0b110110) + chr(0b110010), 37494 - 37486), ehT0Px3KOsy9(chr(2242 - 2194) + chr(111) + '\x33' + '\060' + chr(51), 0o10), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\x6f' + chr(0b1001 + 0o52) + '\067' + chr(0b11011 + 0o30), 11091 - 11083), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + '\067' + chr(48), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(51) + chr(0b110101) + '\x33', 10338 - 10330), ehT0Px3KOsy9('\060' + chr(0b101001 + 0o106) + chr(0b100011 + 0o17) + chr(1502 - 1452) + chr(272 - 223), 25604 - 25596), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b1101111) + chr(0b110011) + chr(0b11000 + 0o30) + chr(1390 - 1340), 0b1000), ehT0Px3KOsy9(chr(48) + chr(7558 - 7447) + chr(53) + '\067', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(6967 - 6856) + chr(51) + '\x33' + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b10101 + 0o33) + '\x6f' + '\x33' + chr(1252 - 1203) + chr(134 - 85), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(8078 - 7967) + chr(50) + chr(0b110111) + chr(0b110001 + 0o5), 0b1000), ehT0Px3KOsy9(chr(2109 - 2061) + '\x6f' + chr(0b100000 + 0o23) + '\x32' + chr(0b1001 + 0o53), 0b1000), ehT0Px3KOsy9(chr(1421 - 1373) + chr(9379 - 9268) + chr(0b110010) + chr(51) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(11517 - 11406) + chr(2646 - 2593) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\157' + chr(0b110001) + chr(1879 - 1826) + chr(49), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + '\x31' + chr(51), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b101100 + 0o5) + '\060' + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + chr(7771 - 7660) + chr(51) + '\060' + chr(0b110100), 0o10), ehT0Px3KOsy9('\060' + chr(0b1011010 + 0o25) + chr(49) + chr(54) + chr(1010 - 957), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1100000 + 0o17) + '\x33' + '\x31' + chr(784 - 734), 11254 - 11246), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b1101111) + '\062' + chr(1325 - 1274) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b10000 + 0o40) + '\x6f' + '\062' + '\066' + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(0b1001000 + 0o47) + chr(0b100000 + 0o21) + chr(0b110100) + chr(1831 - 1780), 58243 - 58235)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(1819 - 1771) + '\x6f' + '\065' + chr(48), 16992 - 16984)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x89'), chr(100) + chr(0b1100101) + '\x63' + '\x6f' + chr(0b1 + 0o143) + '\145')('\x75' + '\x74' + chr(4499 - 4397) + '\x2d' + chr(0b11100 + 0o34)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def eqACXHyHhohl(LzzByjXQ_xA6, E0Mo2AgI6jSE, ix9dZyeAmUxY, EiR0iDFIEsC1):
IgzxyHcGPZP1 = EiR0iDFIEsC1
YlqusYB6InkM = IDJ2eXGCBCDu.random_shuffle(IDJ2eXGCBCDu.range(ix9dZyeAmUxY))
_f1x5eCe1YRo = IDJ2eXGCBCDu.gather(YlqusYB6InkM, IDJ2eXGCBCDu.range(IgzxyHcGPZP1))
P_wFJmPfyfqN = IDJ2eXGCBCDu.gather(YlqusYB6InkM, IDJ2eXGCBCDu.range(IgzxyHcGPZP1, ix9dZyeAmUxY))
fcCBTNfMK4fp = IDJ2eXGCBCDu.gather(LzzByjXQ_xA6, _f1x5eCe1YRo)
eF5VdLXVzkIM = IDJ2eXGCBCDu.gather(E0Mo2AgI6jSE, P_wFJmPfyfqN)
e1jVqMSBZ01Y = IDJ2eXGCBCDu.dynamic_stitch([_f1x5eCe1YRo, P_wFJmPfyfqN], [fcCBTNfMK4fp, eF5VdLXVzkIM])
if PlSM16l2KDPD(ix9dZyeAmUxY, ehT0Px3KOsy9):
xafqLlk3kkUe(e1jVqMSBZ01Y, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd4\xca\xc5d\xc4\xb5+\x15\x05'), chr(211 - 111) + chr(0b1100101) + chr(5099 - 5000) + chr(111) + chr(0b100101 + 0o77) + '\145')(chr(117) + chr(116) + '\146' + chr(45) + chr(2449 - 2393)))([ix9dZyeAmUxY] + xafqLlk3kkUe(jSKPaHwSAfVv, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd4\xc7\xd0K\xd2\x82&\x0c\x13X'), '\144' + '\145' + chr(3383 - 3284) + chr(3899 - 3788) + chr(0b11010 + 0o112) + chr(0b1100101))('\165' + chr(0b10111 + 0o135) + chr(0b110011 + 0o63) + chr(0b101101) + '\x38'))(e1jVqMSBZ01Y)[ehT0Px3KOsy9(chr(48) + chr(0b111000 + 0o67) + chr(318 - 269), 33546 - 33538):])
return e1jVqMSBZ01Y
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
inject_additional_input
|
def inject_additional_input(layer, inputs, name, mode="concat"):
"""Injects the additional input into the layer.
Args:
layer: layer that the input should be injected to.
inputs: inputs to be injected.
name: TF scope name.
mode: how the infor should be added to the layer:
"concat" concats as additional channels.
"multiplicative" broadcasts inputs and multiply them to the channels.
"multi_additive" broadcasts inputs and multiply and add to the channels.
Returns:
updated layer.
Raises:
ValueError: in case of unknown mode.
"""
layer_shape = common_layers.shape_list(layer)
input_shape = common_layers.shape_list(inputs)
zeros_mask = tf.zeros(layer_shape, dtype=tf.float32)
if mode == "concat":
emb = encode_to_shape(inputs, layer_shape, name)
layer = tf.concat(values=[layer, emb], axis=-1)
elif mode == "multiplicative":
filters = layer_shape[-1]
input_reshaped = tf.reshape(inputs, [-1, 1, 1, input_shape[-1]])
input_mask = tf.layers.dense(input_reshaped, filters, name=name)
input_broad = input_mask + zeros_mask
layer *= input_broad
elif mode == "multi_additive":
filters = layer_shape[-1]
input_reshaped = tf.reshape(inputs, [-1, 1, 1, input_shape[-1]])
input_mul = tf.layers.dense(input_reshaped, filters, name=name + "_mul")
layer *= tf.nn.sigmoid(input_mul)
input_add = tf.layers.dense(input_reshaped, filters, name=name + "_add")
layer += input_add
else:
raise ValueError("Unknown injection mode: %s" % mode)
return layer
|
python
|
def inject_additional_input(layer, inputs, name, mode="concat"):
"""Injects the additional input into the layer.
Args:
layer: layer that the input should be injected to.
inputs: inputs to be injected.
name: TF scope name.
mode: how the infor should be added to the layer:
"concat" concats as additional channels.
"multiplicative" broadcasts inputs and multiply them to the channels.
"multi_additive" broadcasts inputs and multiply and add to the channels.
Returns:
updated layer.
Raises:
ValueError: in case of unknown mode.
"""
layer_shape = common_layers.shape_list(layer)
input_shape = common_layers.shape_list(inputs)
zeros_mask = tf.zeros(layer_shape, dtype=tf.float32)
if mode == "concat":
emb = encode_to_shape(inputs, layer_shape, name)
layer = tf.concat(values=[layer, emb], axis=-1)
elif mode == "multiplicative":
filters = layer_shape[-1]
input_reshaped = tf.reshape(inputs, [-1, 1, 1, input_shape[-1]])
input_mask = tf.layers.dense(input_reshaped, filters, name=name)
input_broad = input_mask + zeros_mask
layer *= input_broad
elif mode == "multi_additive":
filters = layer_shape[-1]
input_reshaped = tf.reshape(inputs, [-1, 1, 1, input_shape[-1]])
input_mul = tf.layers.dense(input_reshaped, filters, name=name + "_mul")
layer *= tf.nn.sigmoid(input_mul)
input_add = tf.layers.dense(input_reshaped, filters, name=name + "_add")
layer += input_add
else:
raise ValueError("Unknown injection mode: %s" % mode)
return layer
|
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] |
Injects the additional input into the layer.
Args:
layer: layer that the input should be injected to.
inputs: inputs to be injected.
name: TF scope name.
mode: how the infor should be added to the layer:
"concat" concats as additional channels.
"multiplicative" broadcasts inputs and multiply them to the channels.
"multi_additive" broadcasts inputs and multiply and add to the channels.
Returns:
updated layer.
Raises:
ValueError: in case of unknown mode.
|
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L159-L199
|
train
|
Injects the additional input into the layer.
|
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' + '\063' + chr(53) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\157' + chr(0b11010 + 0o30), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31' + chr(866 - 818), 36951 - 36943), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + chr(1204 - 1153) + chr(1767 - 1713), 0b1000), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b11001 + 0o126) + '\x32' + '\x37' + chr(0b100001 + 0o17), 0b1000), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(111) + chr(2333 - 2283) + chr(53) + chr(1750 - 1699), 37826 - 37818), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b1101 + 0o44) + '\065' + chr(0b10101 + 0o42), 0b1000), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(0b1101111) + chr(0b100101 + 0o15) + chr(52) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + chr(166 - 115) + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\x32', 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + '\063' + '\x32', 0o10), ehT0Px3KOsy9(chr(1031 - 983) + chr(0b10 + 0o155) + chr(0b110011) + '\060' + chr(54), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x32' + '\x34' + '\062', 8), ehT0Px3KOsy9(chr(0b110000) + chr(9044 - 8933) + chr(50) + chr(0b1011 + 0o51), 0b1000), ehT0Px3KOsy9(chr(48) + chr(5315 - 5204) + chr(0b110010) + '\x31' + chr(0b100111 + 0o11), 0o10), ehT0Px3KOsy9(chr(217 - 169) + '\x6f' + chr(932 - 881) + chr(0b110111) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b0 + 0o60) + '\x6f' + chr(2384 - 2335) + chr(403 - 352) + '\x31', 0o10), ehT0Px3KOsy9(chr(1305 - 1257) + '\x6f' + chr(50) + chr(55) + chr(0b10111 + 0o33), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\065' + chr(54), 2393 - 2385), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10110 + 0o35) + chr(886 - 834) + chr(0b111 + 0o57), 20487 - 20479), ehT0Px3KOsy9(chr(48) + chr(111) + '\x32' + chr(48) + '\066', 45663 - 45655), ehT0Px3KOsy9('\x30' + chr(0b1011001 + 0o26) + '\063' + chr(0b101110 + 0o4) + chr(54), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b100110 + 0o13) + chr(649 - 601) + chr(55), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b111111 + 0o60) + chr(0b110010) + chr(1929 - 1879) + chr(1772 - 1720), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1001111 + 0o40) + chr(957 - 906) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(52) + chr(0b110101 + 0o0), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b100001 + 0o20) + chr(0b101110 + 0o11) + chr(2348 - 2293), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(558 - 507) + chr(1515 - 1461) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110000 + 0o2) + chr(49) + '\065', 40009 - 40001), ehT0Px3KOsy9(chr(48) + '\157' + '\x36' + '\x33', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\061' + '\061' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(165 - 115) + chr(0b1100 + 0o50) + chr(55), 0o10), ehT0Px3KOsy9(chr(231 - 183) + chr(0b1101111) + chr(1482 - 1431) + '\063' + chr(0b110110), 8), ehT0Px3KOsy9(chr(634 - 586) + chr(10386 - 10275) + '\x32' + chr(0b110111) + chr(0b110000), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(51) + chr(0b110101) + chr(53), 22705 - 22697), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(0b1001 + 0o47) + chr(1286 - 1231), 8), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(111) + chr(52) + '\x32', 43071 - 43063), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31' + chr(55) + chr(1440 - 1387), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + chr(51) + chr(0b11 + 0o60), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(2287 - 2234) + chr(48), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xc5'), chr(0b1011111 + 0o5) + '\x65' + '\x63' + chr(0b1101111) + chr(100) + chr(0b1100101 + 0o0))(chr(117) + '\164' + '\x66' + chr(1089 - 1044) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def _TZwL62JNTSw(wgamNHppspXj, vXoupepMtCXU, AIvJRzLdDfgF, holLFgwB7vsP=xafqLlk3kkUe(SXOLrMavuUCe(b'\x88mf\xbd\xd9\xdf'), chr(0b1100100) + chr(5188 - 5087) + chr(7356 - 7257) + '\157' + chr(100) + chr(0b1100101))(chr(8647 - 8530) + chr(0b111001 + 0o73) + chr(102) + '\055' + chr(56))):
oit_P5DKb_NP = jSKPaHwSAfVv.shape_list(wgamNHppspXj)
tANyZeuTfu5y = jSKPaHwSAfVv.shape_list(vXoupepMtCXU)
t0uUvAIAqU_i = IDJ2eXGCBCDu.zeros(oit_P5DKb_NP, dtype=IDJ2eXGCBCDu.float32)
if holLFgwB7vsP == xafqLlk3kkUe(SXOLrMavuUCe(b'\x88mf\xbd\xd9\xdf'), chr(3272 - 3172) + chr(0b1100101) + chr(0b1100011) + chr(7569 - 7458) + chr(0b1100100) + '\x65')(chr(0b1110101) + '\x74' + '\146' + '\055' + chr(0b101 + 0o63)):
Jm7YCQYx8Wnq = z7kGB17nriXF(vXoupepMtCXU, oit_P5DKb_NP, AIvJRzLdDfgF)
wgamNHppspXj = IDJ2eXGCBCDu.concat(values=[wgamNHppspXj, Jm7YCQYx8Wnq], axis=-ehT0Px3KOsy9('\060' + chr(0b1100101 + 0o12) + chr(240 - 191), 0b1000))
elif holLFgwB7vsP == xafqLlk3kkUe(SXOLrMavuUCe(b'\x86wd\xaa\xd1\xdb\x03\xcb\xbbc\xee\xaf\xd4q'), chr(7516 - 7416) + '\x65' + '\143' + '\157' + chr(100) + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + chr(102) + chr(0b101101) + '\x38'):
MErh319F3bgE = oit_P5DKb_NP[-ehT0Px3KOsy9('\x30' + chr(6082 - 5971) + '\061', 8)]
y9Ks5ezs9wOV = IDJ2eXGCBCDu.reshape(vXoupepMtCXU, [-ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(111) + chr(2345 - 2296), 8), ehT0Px3KOsy9(chr(0b110000) + chr(6356 - 6245) + '\061', 8), ehT0Px3KOsy9(chr(48) + chr(4440 - 4329) + '\061', 8), tANyZeuTfu5y[-ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001), 8)]])
kA61TR8pjraF = IDJ2eXGCBCDu.layers.dense(y9Ks5ezs9wOV, MErh319F3bgE, name=AIvJRzLdDfgF)
_n_AUpJoBYR8 = kA61TR8pjraF + t0uUvAIAqU_i
wgamNHppspXj *= _n_AUpJoBYR8
elif holLFgwB7vsP == xafqLlk3kkUe(SXOLrMavuUCe(b'\x86wd\xaa\xd1\xf4\x0e\xc6\xbck\xee\xaf\xd4q'), chr(0b1100100) + '\x65' + '\143' + chr(111) + chr(0b10100 + 0o120) + chr(101))(chr(0b111101 + 0o70) + chr(6562 - 6446) + '\x66' + chr(45) + chr(56)):
MErh319F3bgE = oit_P5DKb_NP[-ehT0Px3KOsy9('\060' + chr(6655 - 6544) + '\x31', 8)]
y9Ks5ezs9wOV = IDJ2eXGCBCDu.reshape(vXoupepMtCXU, [-ehT0Px3KOsy9(chr(48) + chr(11096 - 10985) + '\x31', 8), ehT0Px3KOsy9(chr(48) + chr(10357 - 10246) + '\x31', 8), ehT0Px3KOsy9(chr(341 - 293) + chr(4754 - 4643) + chr(0b110001), 8), tANyZeuTfu5y[-ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\157' + chr(49), 8)]])
e0l6nmtBhGzI = IDJ2eXGCBCDu.layers.dense(y9Ks5ezs9wOV, MErh319F3bgE, name=AIvJRzLdDfgF + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb4o}\xb2'), chr(0b10110 + 0o116) + '\145' + chr(5479 - 5380) + chr(0b1101111) + chr(0b10101 + 0o117) + chr(5196 - 5095))(chr(4369 - 4252) + '\164' + chr(102) + chr(0b101101) + chr(56)))
wgamNHppspXj *= IDJ2eXGCBCDu.nn.sigmoid(e0l6nmtBhGzI)
AvprsSZrFzYe = IDJ2eXGCBCDu.layers.dense(y9Ks5ezs9wOV, MErh319F3bgE, name=AIvJRzLdDfgF + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb4cl\xba'), chr(0b1100100) + '\x65' + chr(0b1100011) + chr(111) + chr(0b10101 + 0o117) + '\x65')(chr(0b1010001 + 0o44) + chr(0b1110100) + '\146' + chr(45) + '\070'))
wgamNHppspXj += AvprsSZrFzYe
else:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\xbelc\xb0\xd7\xdc\x01\x82\xb1l\xf0\xa3\xc1`\xe1\x917\x9aC\x89\xe2\xb3}\xb48V'), '\144' + '\x65' + chr(0b1100011) + '\157' + chr(0b1100100) + chr(0b1100101))(chr(0b1110101 + 0o0) + chr(116) + chr(6529 - 6427) + chr(0b101101) + '\070') % holLFgwB7vsP)
return wgamNHppspXj
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
scheduled_sample_prob
|
def scheduled_sample_prob(ground_truth_x,
generated_x,
batch_size,
scheduled_sample_var):
"""Probability based scheduled sampling.
Args:
ground_truth_x: tensor of ground-truth data points.
generated_x: tensor of generated data points.
batch_size: batch size
scheduled_sample_var: probability of choosing from ground_truth.
Returns:
New batch with randomly selected data points.
"""
probability_threshold = scheduled_sample_var
probability_of_generated = tf.random_uniform([batch_size])
return tf.where(probability_of_generated > probability_threshold,
generated_x, ground_truth_x)
|
python
|
def scheduled_sample_prob(ground_truth_x,
generated_x,
batch_size,
scheduled_sample_var):
"""Probability based scheduled sampling.
Args:
ground_truth_x: tensor of ground-truth data points.
generated_x: tensor of generated data points.
batch_size: batch size
scheduled_sample_var: probability of choosing from ground_truth.
Returns:
New batch with randomly selected data points.
"""
probability_threshold = scheduled_sample_var
probability_of_generated = tf.random_uniform([batch_size])
return tf.where(probability_of_generated > probability_threshold,
generated_x, ground_truth_x)
|
[
"def",
"scheduled_sample_prob",
"(",
"ground_truth_x",
",",
"generated_x",
",",
"batch_size",
",",
"scheduled_sample_var",
")",
":",
"probability_threshold",
"=",
"scheduled_sample_var",
"probability_of_generated",
"=",
"tf",
".",
"random_uniform",
"(",
"[",
"batch_size",
"]",
")",
"return",
"tf",
".",
"where",
"(",
"probability_of_generated",
">",
"probability_threshold",
",",
"generated_x",
",",
"ground_truth_x",
")"
] |
Probability based scheduled sampling.
Args:
ground_truth_x: tensor of ground-truth data points.
generated_x: tensor of generated data points.
batch_size: batch size
scheduled_sample_var: probability of choosing from ground_truth.
Returns:
New batch with randomly selected data points.
|
[
"Probability",
"based",
"scheduled",
"sampling",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L202-L219
|
train
|
Probability based scheduled sampling.
|
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(0b10100 + 0o43) + '\061', 0o10), ehT0Px3KOsy9(chr(797 - 749) + chr(0b1101111) + '\x33' + chr(0b101001 + 0o14) + chr(0b110110), 23435 - 23427), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + '\x31' + chr(1770 - 1721), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b10001 + 0o41) + chr(50) + chr(53), 3477 - 3469), ehT0Px3KOsy9(chr(48) + chr(3091 - 2980) + '\x31' + '\065' + '\060', 57551 - 57543), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000 + 0o147) + chr(0b11101 + 0o26) + chr(1719 - 1671) + chr(0b10101 + 0o42), 45142 - 45134), ehT0Px3KOsy9(chr(2132 - 2084) + chr(111) + '\062' + '\063' + chr(0b110100 + 0o2), 44721 - 44713), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b1101111) + '\063' + chr(55) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(0b110100) + '\x32', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(852 - 803) + chr(0b110010) + chr(2689 - 2637), 6185 - 6177), ehT0Px3KOsy9(chr(0b110000) + chr(4823 - 4712) + chr(642 - 592) + chr(52) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b10000 + 0o40) + '\157' + chr(0b110010 + 0o3) + chr(0b110100), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b11 + 0o57) + chr(0b11101 + 0o31) + chr(0b110001 + 0o0), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x34' + chr(1852 - 1801), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(10662 - 10551) + chr(0b110010) + chr(2260 - 2208) + '\x30', 25757 - 25749), ehT0Px3KOsy9(chr(0b101010 + 0o6) + '\157' + '\061' + '\061' + chr(0b101100 + 0o13), 0o10), ehT0Px3KOsy9(chr(654 - 606) + chr(0b1011111 + 0o20) + chr(1402 - 1353) + '\x36' + chr(0b100000 + 0o24), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1011 + 0o53) + chr(48), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + chr(1496 - 1446) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + chr(2271 - 2219) + chr(1577 - 1528), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b100110 + 0o15) + chr(365 - 316), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + chr(2488 - 2436) + '\x30', 8), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b1101111) + chr(0b110111) + chr(0b110010), 17988 - 17980), ehT0Px3KOsy9(chr(0b11011 + 0o25) + '\x6f' + chr(52) + chr(54), 0b1000), ehT0Px3KOsy9('\060' + chr(8923 - 8812) + '\061' + chr(0b11100 + 0o31) + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + '\062' + '\067', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(1123 - 1073), 59266 - 59258), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(54) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(0b10110 + 0o33) + chr(1113 - 1060), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(2455 - 2404) + chr(48) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(111) + chr(0b110001) + chr(0b101001 + 0o16) + chr(0b110010), 17555 - 17547), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + chr(48) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110011) + '\062' + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b100 + 0o54) + '\x6f' + '\063' + chr(0b1110 + 0o46) + chr(0b110010), 8), ehT0Px3KOsy9('\x30' + chr(4192 - 4081) + chr(51) + '\x32' + '\x34', 43778 - 43770), ehT0Px3KOsy9(chr(1931 - 1883) + chr(111) + chr(0b110001) + '\061' + chr(422 - 371), 22819 - 22811), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + chr(0b11110 + 0o30) + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b111 + 0o51) + '\x6f' + chr(0b110 + 0o55) + chr(863 - 810), 51172 - 51164), ehT0Px3KOsy9('\x30' + chr(0b100 + 0o153) + chr(1602 - 1552) + chr(0b100011 + 0o16) + '\061', 10988 - 10980)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b1101111) + '\x35' + '\x30', 43533 - 43525)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x17'), chr(0b10001 + 0o123) + chr(6688 - 6587) + chr(7832 - 7733) + chr(111) + chr(100) + chr(2926 - 2825))(chr(4333 - 4216) + chr(0b10000 + 0o144) + chr(0b1100110) + '\055' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def KZfWgA_WNsHp(LzzByjXQ_xA6, E0Mo2AgI6jSE, ix9dZyeAmUxY, EiR0iDFIEsC1):
EJ9BOFpZHM2A = EiR0iDFIEsC1
L9xtEI7Xj84k = IDJ2eXGCBCDu.random_uniform([ix9dZyeAmUxY])
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b']\xbc\x8f\xd4+&\xfe\xe7\xab\xa09\xfa'), chr(7185 - 7085) + chr(0b1001100 + 0o31) + chr(0b1100011) + chr(0b101000 + 0o107) + chr(100) + chr(0b1100101))('\x75' + chr(0b1110100) + chr(0b1100110) + chr(0b10011 + 0o32) + chr(0b10111 + 0o41)))(L9xtEI7Xj84k > EJ9BOFpZHM2A, E0Mo2AgI6jSE, LzzByjXQ_xA6)
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
dna_transformation
|
def dna_transformation(prev_image, dna_input, dna_kernel_size, relu_shift):
"""Apply dynamic neural advection to previous image.
Args:
prev_image: previous image to be transformed.
dna_input: hidden lyaer to be used for computing DNA transformation.
dna_kernel_size: dna kernel size.
relu_shift: shift for ReLU function.
Returns:
List of images transformed by the predicted CDNA kernels.
"""
# Construct translated images.
prev_image_pad = tf.pad(prev_image, [[0, 0], [2, 2], [2, 2], [0, 0]])
image_height = int(prev_image.get_shape()[1])
image_width = int(prev_image.get_shape()[2])
inputs = []
for xkern in range(dna_kernel_size):
for ykern in range(dna_kernel_size):
inputs.append(
tf.expand_dims(
tf.slice(prev_image_pad, [0, xkern, ykern, 0],
[-1, image_height, image_width, -1]), [3]))
inputs = tf.concat(axis=3, values=inputs)
# Normalize channels to 1.
kernel = tf.nn.relu(dna_input - relu_shift) + relu_shift
kernel = tf.expand_dims(
kernel / tf.reduce_sum(kernel, [3], keep_dims=True), [4])
return tf.reduce_sum(kernel * inputs, [3], keep_dims=False)
|
python
|
def dna_transformation(prev_image, dna_input, dna_kernel_size, relu_shift):
"""Apply dynamic neural advection to previous image.
Args:
prev_image: previous image to be transformed.
dna_input: hidden lyaer to be used for computing DNA transformation.
dna_kernel_size: dna kernel size.
relu_shift: shift for ReLU function.
Returns:
List of images transformed by the predicted CDNA kernels.
"""
# Construct translated images.
prev_image_pad = tf.pad(prev_image, [[0, 0], [2, 2], [2, 2], [0, 0]])
image_height = int(prev_image.get_shape()[1])
image_width = int(prev_image.get_shape()[2])
inputs = []
for xkern in range(dna_kernel_size):
for ykern in range(dna_kernel_size):
inputs.append(
tf.expand_dims(
tf.slice(prev_image_pad, [0, xkern, ykern, 0],
[-1, image_height, image_width, -1]), [3]))
inputs = tf.concat(axis=3, values=inputs)
# Normalize channels to 1.
kernel = tf.nn.relu(dna_input - relu_shift) + relu_shift
kernel = tf.expand_dims(
kernel / tf.reduce_sum(kernel, [3], keep_dims=True), [4])
return tf.reduce_sum(kernel * inputs, [3], keep_dims=False)
|
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] |
Apply dynamic neural advection to previous image.
Args:
prev_image: previous image to be transformed.
dna_input: hidden lyaer to be used for computing DNA transformation.
dna_kernel_size: dna kernel size.
relu_shift: shift for ReLU function.
Returns:
List of images transformed by the predicted CDNA kernels.
|
[
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L222-L251
|
train
|
Apply dynamic neural advection to previous image.
|
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(50), 0b1000), ehT0Px3KOsy9(chr(844 - 796) + chr(111) + chr(997 - 949), 19837 - 19829), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x34' + '\x31', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b110001 + 0o76) + '\067' + chr(0b11101 + 0o25), 0o10), ehT0Px3KOsy9('\x30' + chr(3053 - 2942) + chr(1299 - 1250) + '\x33' + chr(0b110111), 60258 - 60250), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2234 - 2184) + chr(0b110000) + chr(53), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\067' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(1959 - 1911) + chr(111) + '\063' + chr(0b101001 + 0o12) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(111) + chr(636 - 586) + chr(0b110001) + chr(0b10000 + 0o43), 0b1000), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(111) + chr(49) + chr(0b110110) + '\x34', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1200 - 1148) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(5318 - 5207) + chr(0b10011 + 0o40) + chr(1576 - 1525) + chr(1323 - 1272), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(9753 - 9642) + '\062' + chr(0b101101 + 0o6) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + chr(1842 - 1791) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b10111 + 0o130) + chr(858 - 808) + chr(0b110101) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(804 - 756) + chr(0b101010 + 0o105) + '\061' + chr(1186 - 1137) + '\x32', 13740 - 13732), ehT0Px3KOsy9(chr(0b100111 + 0o11) + '\x6f' + chr(0b110001) + chr(54) + '\065', 13719 - 13711), ehT0Px3KOsy9(chr(206 - 158) + '\x6f' + chr(1818 - 1768) + chr(50) + chr(2881 - 2826), 29899 - 29891), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(153 - 102) + chr(0b110000) + chr(0b110001), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101100 + 0o3) + chr(0b110010) + chr(0b1000 + 0o55) + '\066', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1931 - 1882) + chr(48) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b10000 + 0o40) + '\x6f' + '\x31' + '\x36' + chr(0b110100), 8), ehT0Px3KOsy9('\060' + chr(3360 - 3249) + '\061' + chr(0b11 + 0o63) + chr(0b110110 + 0o1), 14133 - 14125), ehT0Px3KOsy9('\060' + '\x6f' + '\061' + chr(51) + '\066', 35884 - 35876), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + '\x31' + chr(0b110100), 57483 - 57475), ehT0Px3KOsy9(chr(0b110000) + chr(911 - 800) + chr(837 - 787) + chr(53), 0o10), ehT0Px3KOsy9(chr(48) + chr(9336 - 9225) + '\062' + chr(0b110100) + '\x33', 5129 - 5121), ehT0Px3KOsy9(chr(1078 - 1030) + chr(6540 - 6429) + chr(0b1000 + 0o53) + chr(0b101111 + 0o3) + chr(52), 21933 - 21925), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + '\065' + chr(0b110000), 15840 - 15832), ehT0Px3KOsy9(chr(0b110000) + chr(6069 - 5958) + chr(0b100111 + 0o12) + chr(0b100101 + 0o13), 50764 - 50756), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(109 - 59) + chr(0b11101 + 0o25) + '\064', 22776 - 22768), ehT0Px3KOsy9(chr(48) + chr(6130 - 6019) + '\x33' + '\x37' + '\063', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111 + 0o0) + chr(174 - 125) + '\061' + chr(0b110001), 59221 - 59213), ehT0Px3KOsy9(chr(232 - 184) + chr(111) + chr(0b110111) + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(5025 - 4914) + chr(50) + chr(1942 - 1894) + '\063', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + chr(48) + chr(0b100110 + 0o14), ord("\x08")), ehT0Px3KOsy9(chr(1909 - 1861) + chr(111) + chr(51) + chr(0b110011) + '\x32', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b110001) + chr(51) + chr(0b101 + 0o57), ord("\x08")), ehT0Px3KOsy9(chr(1478 - 1430) + chr(111) + chr(0b110011) + '\067' + '\061', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1010101 + 0o32) + '\066' + chr(55), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1011000 + 0o27) + '\065' + '\x30', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b','), chr(0b1100100) + '\x65' + chr(99) + chr(111) + '\x64' + chr(101))(chr(10969 - 10852) + chr(0b1101010 + 0o12) + chr(2096 - 1994) + '\x2d' + chr(2524 - 2468)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def LPUmThoGSW49(SSEY66YT1vMU, T_H7qaRPx7q7, sA_rGseXGm3n, caqJLVRtuAS0):
NMEmsPowmYKU = IDJ2eXGCBCDu.pad(SSEY66YT1vMU, [[ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110000), 8), ehT0Px3KOsy9(chr(0b110000) + chr(7671 - 7560) + chr(0b110000), 8)], [ehT0Px3KOsy9('\060' + chr(4924 - 4813) + chr(318 - 268), 8), ehT0Px3KOsy9('\060' + chr(0b1101010 + 0o5) + chr(50), 8)], [ehT0Px3KOsy9(chr(0b110000) + chr(0b1100110 + 0o11) + chr(50), 8), ehT0Px3KOsy9('\060' + '\x6f' + '\x32', 8)], [ehT0Px3KOsy9('\060' + '\x6f' + chr(48), 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110000), 8)]])
aVRbWzCw2Vuo = ehT0Px3KOsy9(SSEY66YT1vMU.get_shape()[ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b1101111) + chr(0b10011 + 0o36), 0o10)])
RmwDor39z9oL = ehT0Px3KOsy9(SSEY66YT1vMU.get_shape()[ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(11353 - 11242) + '\062', 8)])
vXoupepMtCXU = []
for AXsNQNbgViX0 in vQr8gNKaIaWE(sA_rGseXGm3n):
for dVZCYwAiJ6is in vQr8gNKaIaWE(sA_rGseXGm3n):
xafqLlk3kkUe(vXoupepMtCXU, xafqLlk3kkUe(SXOLrMavuUCe(b'cpQ_1\xe1'), chr(0b1100100) + chr(0b1100101) + chr(99) + chr(8762 - 8651) + '\x64' + '\145')('\165' + chr(6147 - 6031) + '\146' + chr(0b101101) + chr(1538 - 1482)))(xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'gxQ[1\xe1a\xb8\xe2\x19T'), chr(100) + '\145' + '\143' + '\x6f' + chr(100) + '\x65')(chr(117) + chr(0b1110100) + '\146' + '\x2d' + chr(0b111000)))(xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'qlHY:'), '\144' + '\145' + chr(99) + chr(0b110100 + 0o73) + chr(8817 - 8717) + chr(0b100100 + 0o101))(chr(7998 - 7881) + '\164' + chr(1021 - 919) + '\x2d' + '\x38'))(NMEmsPowmYKU, [ehT0Px3KOsy9(chr(2047 - 1999) + chr(0b1101111) + chr(48), 8), AXsNQNbgViX0, dVZCYwAiJ6is, ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\x6f' + chr(2226 - 2178), 8)], [-ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061', 8), aVRbWzCw2Vuo, RmwDor39z9oL, -ehT0Px3KOsy9(chr(1797 - 1749) + chr(0b100000 + 0o117) + '\x31', 8)]), [ehT0Px3KOsy9(chr(48) + '\157' + '\063', 0o10)]))
vXoupepMtCXU = IDJ2eXGCBCDu.concat(axis=ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(3350 - 3239) + chr(51), 8), values=vXoupepMtCXU)
iaILEoszmqXb = IDJ2eXGCBCDu.nn.relu(T_H7qaRPx7q7 - caqJLVRtuAS0) + caqJLVRtuAS0
iaILEoszmqXb = IDJ2eXGCBCDu.expand_dims(iaILEoszmqXb / IDJ2eXGCBCDu.reduce_sum(iaILEoszmqXb, [ehT0Px3KOsy9('\060' + '\157' + chr(0b110011), 8)], keep_dims=ehT0Px3KOsy9('\x30' + '\157' + chr(49), 8)), [ehT0Px3KOsy9(chr(970 - 922) + chr(9749 - 9638) + chr(52), ord("\x08"))])
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'peEO<\xe0a\xaf\xfe\x19'), chr(0b1100100) + '\x65' + chr(0b1100011) + chr(11747 - 11636) + '\x64' + '\145')(chr(0b1000010 + 0o63) + chr(116) + chr(0b1100110) + chr(0b101101) + '\x38'))(iaILEoszmqXb * vXoupepMtCXU, [ehT0Px3KOsy9('\x30' + chr(111) + chr(51), 8)], keep_dims=ehT0Px3KOsy9(chr(48) + chr(6740 - 6629) + chr(428 - 380), 8))
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
cdna_transformation
|
def cdna_transformation(prev_image, cdna_input, num_masks, color_channels,
dna_kernel_size, relu_shift):
"""Apply convolutional dynamic neural advection to previous image.
Args:
prev_image: previous image to be transformed.
cdna_input: hidden lyaer to be used for computing CDNA kernels.
num_masks: number of masks and hence the number of CDNA transformations.
color_channels: the number of color channels in the images.
dna_kernel_size: dna kernel size.
relu_shift: shift for ReLU function.
Returns:
List of images transformed by the predicted CDNA kernels.
"""
batch_size = tf.shape(cdna_input)[0]
height = int(prev_image.get_shape()[1])
width = int(prev_image.get_shape()[2])
# Predict kernels using linear function of last hidden layer.
cdna_kerns = tfl.dense(
cdna_input, dna_kernel_size * dna_kernel_size * num_masks,
name="cdna_params",
activation=None)
# Reshape and normalize.
cdna_kerns = tf.reshape(
cdna_kerns, [batch_size, dna_kernel_size, dna_kernel_size, 1, num_masks])
cdna_kerns = (tf.nn.relu(cdna_kerns - relu_shift) + relu_shift)
norm_factor = tf.reduce_sum(cdna_kerns, [1, 2, 3], keep_dims=True)
cdna_kerns /= norm_factor
# Treat the color channel dimension as the batch dimension since the same
# transformation is applied to each color channel.
# Treat the batch dimension as the channel dimension so that
# depthwise_conv2d can apply a different transformation to each sample.
cdna_kerns = tf.transpose(cdna_kerns, [1, 2, 0, 4, 3])
cdna_kerns = tf.reshape(
cdna_kerns, [dna_kernel_size, dna_kernel_size, batch_size, num_masks])
# Swap the batch and channel dimensions.
prev_image = tf.transpose(prev_image, [3, 1, 2, 0])
# Transform image.
transformed = tf.nn.depthwise_conv2d(
prev_image, cdna_kerns, [1, 1, 1, 1], "SAME")
# Transpose the dimensions to where they belong.
transformed = tf.reshape(
transformed, [color_channels, height, width, batch_size, num_masks])
transformed = tf.transpose(transformed, [3, 1, 2, 0, 4])
transformed = tf.unstack(transformed, axis=-1)
return transformed
|
python
|
def cdna_transformation(prev_image, cdna_input, num_masks, color_channels,
dna_kernel_size, relu_shift):
"""Apply convolutional dynamic neural advection to previous image.
Args:
prev_image: previous image to be transformed.
cdna_input: hidden lyaer to be used for computing CDNA kernels.
num_masks: number of masks and hence the number of CDNA transformations.
color_channels: the number of color channels in the images.
dna_kernel_size: dna kernel size.
relu_shift: shift for ReLU function.
Returns:
List of images transformed by the predicted CDNA kernels.
"""
batch_size = tf.shape(cdna_input)[0]
height = int(prev_image.get_shape()[1])
width = int(prev_image.get_shape()[2])
# Predict kernels using linear function of last hidden layer.
cdna_kerns = tfl.dense(
cdna_input, dna_kernel_size * dna_kernel_size * num_masks,
name="cdna_params",
activation=None)
# Reshape and normalize.
cdna_kerns = tf.reshape(
cdna_kerns, [batch_size, dna_kernel_size, dna_kernel_size, 1, num_masks])
cdna_kerns = (tf.nn.relu(cdna_kerns - relu_shift) + relu_shift)
norm_factor = tf.reduce_sum(cdna_kerns, [1, 2, 3], keep_dims=True)
cdna_kerns /= norm_factor
# Treat the color channel dimension as the batch dimension since the same
# transformation is applied to each color channel.
# Treat the batch dimension as the channel dimension so that
# depthwise_conv2d can apply a different transformation to each sample.
cdna_kerns = tf.transpose(cdna_kerns, [1, 2, 0, 4, 3])
cdna_kerns = tf.reshape(
cdna_kerns, [dna_kernel_size, dna_kernel_size, batch_size, num_masks])
# Swap the batch and channel dimensions.
prev_image = tf.transpose(prev_image, [3, 1, 2, 0])
# Transform image.
transformed = tf.nn.depthwise_conv2d(
prev_image, cdna_kerns, [1, 1, 1, 1], "SAME")
# Transpose the dimensions to where they belong.
transformed = tf.reshape(
transformed, [color_channels, height, width, batch_size, num_masks])
transformed = tf.transpose(transformed, [3, 1, 2, 0, 4])
transformed = tf.unstack(transformed, axis=-1)
return transformed
|
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] |
Apply convolutional dynamic neural advection to previous image.
Args:
prev_image: previous image to be transformed.
cdna_input: hidden lyaer to be used for computing CDNA kernels.
num_masks: number of masks and hence the number of CDNA transformations.
color_channels: the number of color channels in the images.
dna_kernel_size: dna kernel size.
relu_shift: shift for ReLU function.
Returns:
List of images transformed by the predicted CDNA kernels.
|
[
"Apply",
"convolutional",
"dynamic",
"neural",
"advection",
"to",
"previous",
"image",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L254-L304
|
train
|
Apply convolutional dynamic neural advection to previous image.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(828 - 780) + chr(0b1010110 + 0o31) + '\x32' + chr(0b100110 + 0o16) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1011101 + 0o22) + chr(157 - 108) + '\x33' + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(11956 - 11845) + chr(0b110001) + '\064' + chr(0b110100 + 0o1), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\x31' + chr(0b110111) + chr(1004 - 955), ord("\x08")), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(111) + chr(50) + chr(49) + '\066', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1669 - 1620) + '\x34', 24465 - 24457), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + chr(479 - 424) + chr(0b100100 + 0o16), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(83 - 32) + chr(953 - 904) + '\061', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101 + 0o142) + '\062' + '\060' + chr(49), 62232 - 62224), ehT0Px3KOsy9(chr(442 - 394) + chr(0b111010 + 0o65) + '\x31' + chr(1912 - 1857) + chr(458 - 409), 8), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1101111 + 0o0) + chr(0b100100 + 0o16) + '\066' + chr(0b110011), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b101 + 0o152) + chr(528 - 475) + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\157' + chr(2549 - 2498) + chr(2196 - 2146) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + '\067' + '\061', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001 + 0o146) + chr(0b100010 + 0o20) + '\x36' + '\067', 0b1000), ehT0Px3KOsy9('\060' + chr(5643 - 5532) + chr(50) + chr(0b100100 + 0o21) + chr(0b110000), 28978 - 28970), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(50) + chr(0b11010 + 0o30), 64378 - 64370), ehT0Px3KOsy9(chr(48) + '\157' + chr(55) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + chr(0b101110 + 0o10) + chr(0b1110 + 0o43), 56864 - 56856), ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\157' + chr(51) + chr(0b110111) + chr(0b110110), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x34' + chr(2569 - 2517), 12879 - 12871), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + '\x30' + '\x35', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(2196 - 2085) + '\063' + chr(2203 - 2152) + chr(2896 - 2841), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(3884 - 3773) + '\x37' + '\061', 0o10), ehT0Px3KOsy9(chr(875 - 827) + chr(1730 - 1619) + '\x33' + chr(0b110000) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + '\060' + chr(0b10101 + 0o34), 29678 - 29670), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(2370 - 2320) + chr(0b110011) + chr(55), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\062' + chr(2166 - 2115) + chr(0b10111 + 0o35), 0o10), ehT0Px3KOsy9(chr(48) + chr(793 - 682) + chr(0b110010) + '\065' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1973 - 1922) + chr(55), 0b1000), ehT0Px3KOsy9(chr(1354 - 1306) + '\157' + chr(0b11100 + 0o27) + chr(0b1010 + 0o47) + chr(0b110111), 2558 - 2550), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\066' + '\x31', 34966 - 34958), ehT0Px3KOsy9('\060' + chr(9394 - 9283) + '\062' + chr(841 - 793) + chr(761 - 712), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + chr(54) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(8111 - 8000) + '\x33' + '\063', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + chr(0b101010 + 0o10) + chr(0b100110 + 0o15), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(8001 - 7890) + chr(51) + chr(669 - 621) + '\062', 56902 - 56894), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1666 - 1617) + chr(0b10100 + 0o37) + '\x31', 0b1000), ehT0Px3KOsy9(chr(2229 - 2181) + chr(7220 - 7109) + '\066' + '\x36', 30051 - 30043), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101 + 0o54) + chr(0b110 + 0o57) + '\x34', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(3511 - 3400) + chr(53) + chr(0b111 + 0o51), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c'), chr(0b101100 + 0o70) + '\145' + chr(0b1100011) + chr(0b1101111) + '\x64' + chr(0b1100101))(chr(0b110000 + 0o105) + '\x74' + chr(102) + chr(515 - 470) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def eLO3CDwxPdOz(SSEY66YT1vMU, fOal6P6F0RHq, u84CemFRNZLD, KZi3AzA7v2pr, sA_rGseXGm3n, caqJLVRtuAS0):
ix9dZyeAmUxY = IDJ2eXGCBCDu.nauYfLglTpcb(fOal6P6F0RHq)[ehT0Px3KOsy9('\060' + chr(111) + chr(0b110000), 0o10)]
ehbUULKuygfC = ehT0Px3KOsy9(SSEY66YT1vMU.get_shape()[ehT0Px3KOsy9(chr(48) + '\157' + '\061', 0o10)])
mPx09rBTrGXR = ehT0Px3KOsy9(SSEY66YT1vMU.get_shape()[ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b10111 + 0o33), 0o10)])
TMGrMylv2eIZ = uWOby3XrTzFz.dense(fOal6P6F0RHq, sA_rGseXGm3n * sA_rGseXGm3n * u84CemFRNZLD, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\xc1;\x0b\x18\xd1|\x1b\xbb\xe0\x14\xc0'), chr(4709 - 4609) + chr(6779 - 6678) + '\x63' + chr(0b100001 + 0o116) + chr(6396 - 6296) + chr(0b1100101))(chr(13108 - 12991) + '\164' + chr(8963 - 8861) + '\x2d' + chr(56)), activation=None)
TMGrMylv2eIZ = IDJ2eXGCBCDu.reshape(TMGrMylv2eIZ, [ix9dZyeAmUxY, sA_rGseXGm3n, sA_rGseXGm3n, ehT0Px3KOsy9('\060' + '\x6f' + '\061', 8), u84CemFRNZLD])
TMGrMylv2eIZ = IDJ2eXGCBCDu.nn.relu(TMGrMylv2eIZ - caqJLVRtuAS0) + caqJLVRtuAS0
bpfVEDkeFFQa = IDJ2eXGCBCDu.reduce_sum(TMGrMylv2eIZ, [ehT0Px3KOsy9(chr(0b1011 + 0o45) + '\x6f' + chr(94 - 45), 8), ehT0Px3KOsy9(chr(620 - 572) + chr(0b1010101 + 0o32) + '\x32', 8), ehT0Px3KOsy9(chr(48) + '\157' + chr(1119 - 1068), ord("\x08"))], keep_dims=ehT0Px3KOsy9(chr(48) + chr(1544 - 1433) + chr(49), 8))
TMGrMylv2eIZ /= bpfVEDkeFFQa
TMGrMylv2eIZ = IDJ2eXGCBCDu.transpose(TMGrMylv2eIZ, [ehT0Px3KOsy9(chr(866 - 818) + chr(111) + '\x31', 8), ehT0Px3KOsy9('\x30' + chr(6402 - 6291) + chr(1832 - 1782), 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(48), 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110000 + 0o4), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(1254 - 1203), 8)])
TMGrMylv2eIZ = IDJ2eXGCBCDu.reshape(TMGrMylv2eIZ, [sA_rGseXGm3n, sA_rGseXGm3n, ix9dZyeAmUxY, u84CemFRNZLD])
SSEY66YT1vMU = IDJ2eXGCBCDu.transpose(SSEY66YT1vMU, [ehT0Px3KOsy9(chr(1502 - 1454) + chr(858 - 747) + chr(0b110011), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b10 + 0o155) + chr(0b101000 + 0o12), 8), ehT0Px3KOsy9(chr(48) + '\157' + '\x30', 8)])
aMh8mto44T2o = IDJ2eXGCBCDu.nn.depthwise_conv2d(SSEY66YT1vMU, TMGrMylv2eIZ, [ehT0Px3KOsy9(chr(48) + chr(111) + chr(748 - 699), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31', 8), ehT0Px3KOsy9('\x30' + chr(679 - 568) + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b110000) + chr(8743 - 8632) + '\061', 8)], xafqLlk3kkUe(SXOLrMavuUCe(b'\xf1\x1e(<'), chr(0b1100100) + '\x65' + chr(99) + chr(0b1101110 + 0o1) + '\144' + chr(101))('\x75' + '\x74' + chr(3751 - 3649) + chr(1259 - 1214) + chr(56)))
aMh8mto44T2o = IDJ2eXGCBCDu.reshape(aMh8mto44T2o, [KZi3AzA7v2pr, ehbUULKuygfC, mPx09rBTrGXR, ix9dZyeAmUxY, u84CemFRNZLD])
aMh8mto44T2o = IDJ2eXGCBCDu.transpose(aMh8mto44T2o, [ehT0Px3KOsy9('\060' + '\x6f' + chr(51), 8), ehT0Px3KOsy9('\060' + chr(4141 - 4030) + '\061', 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(743 - 693), 8), ehT0Px3KOsy9('\060' + chr(2211 - 2100) + chr(48), 8), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\x6f' + '\x34', 8)])
aMh8mto44T2o = IDJ2eXGCBCDu.unstack(aMh8mto44T2o, axis=-ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31', 8))
return aMh8mto44T2o
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
vgg_layer
|
def vgg_layer(inputs,
nout,
kernel_size=3,
activation=tf.nn.leaky_relu,
padding="SAME",
is_training=True,
has_batchnorm=False,
scope=None):
"""A layer of VGG network with batch norm.
Args:
inputs: image tensor
nout: number of output channels
kernel_size: size of the kernel
activation: activation function
padding: padding of the image
is_training: whether it is training mode or not
has_batchnorm: whether batchnorm is applied or not
scope: variable scope of the op
Returns:
net: output of layer
"""
with tf.variable_scope(scope):
net = tfl.conv2d(inputs, nout, kernel_size=kernel_size, padding=padding,
activation=None, name="conv")
if has_batchnorm:
net = tfl.batch_normalization(net, training=is_training, name="bn")
net = activation(net)
return net
|
python
|
def vgg_layer(inputs,
nout,
kernel_size=3,
activation=tf.nn.leaky_relu,
padding="SAME",
is_training=True,
has_batchnorm=False,
scope=None):
"""A layer of VGG network with batch norm.
Args:
inputs: image tensor
nout: number of output channels
kernel_size: size of the kernel
activation: activation function
padding: padding of the image
is_training: whether it is training mode or not
has_batchnorm: whether batchnorm is applied or not
scope: variable scope of the op
Returns:
net: output of layer
"""
with tf.variable_scope(scope):
net = tfl.conv2d(inputs, nout, kernel_size=kernel_size, padding=padding,
activation=None, name="conv")
if has_batchnorm:
net = tfl.batch_normalization(net, training=is_training, name="bn")
net = activation(net)
return net
|
[
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"3",
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"activation",
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"tf",
".",
"nn",
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"leaky_relu",
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"padding",
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"\"SAME\"",
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] |
A layer of VGG network with batch norm.
Args:
inputs: image tensor
nout: number of output channels
kernel_size: size of the kernel
activation: activation function
padding: padding of the image
is_training: whether it is training mode or not
has_batchnorm: whether batchnorm is applied or not
scope: variable scope of the op
Returns:
net: output of layer
|
[
"A",
"layer",
"of",
"VGG",
"network",
"with",
"batch",
"norm",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L307-L335
|
train
|
A layer of VGG network with batch norm.
|
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(12305 - 12194) + chr(51) + chr(701 - 646) + chr(107 - 53), ord("\x08")), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(0b10 + 0o155) + '\x32' + '\061' + chr(0b10000 + 0o44), 0o10), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\157' + chr(50) + '\063', 0b1000), ehT0Px3KOsy9(chr(165 - 117) + chr(0b1101111) + chr(615 - 565) + chr(0b110110) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(364 - 253) + '\x31' + '\x37' + chr(49), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + '\064' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001001 + 0o46) + chr(0b101101 + 0o4) + chr(52) + '\x31', 12362 - 12354), ehT0Px3KOsy9(chr(48) + chr(0b101 + 0o152) + chr(51) + chr(0b101 + 0o55) + chr(2669 - 2616), 0b1000), ehT0Px3KOsy9('\x30' + chr(8750 - 8639) + '\x32', 0b1000), ehT0Px3KOsy9('\x30' + chr(10728 - 10617) + chr(302 - 253) + '\060' + chr(2054 - 2001), 42431 - 42423), ehT0Px3KOsy9(chr(0b110000) + chr(10634 - 10523) + '\x31' + chr(1550 - 1495) + '\065', 0b1000), ehT0Px3KOsy9(chr(1513 - 1465) + chr(1599 - 1488) + chr(50) + chr(0b1000 + 0o51) + chr(0b10100 + 0o35), 0b1000), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(10012 - 9901) + chr(0b110001) + '\x37' + '\063', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(935 - 881) + '\x30', 0o10), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(111) + chr(0b1 + 0o62) + chr(0b110101) + chr(49), 36546 - 36538), ehT0Px3KOsy9('\x30' + '\157' + chr(645 - 596) + '\064' + '\067', 0o10), ehT0Px3KOsy9(chr(338 - 290) + chr(0b1100101 + 0o12) + chr(0b111 + 0o52) + '\x35' + chr(0b11000 + 0o34), 0b1000), ehT0Px3KOsy9(chr(390 - 342) + '\157' + '\x32' + '\x37' + chr(55), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b1111 + 0o43) + '\x33' + chr(1471 - 1417), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\x31' + chr(0b110000 + 0o2) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1101111) + chr(1669 - 1619) + chr(0b110101) + chr(1843 - 1791), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1011110 + 0o21) + chr(0b110010) + '\063' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b100111 + 0o12) + chr(2469 - 2416) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(6597 - 6486) + '\x34' + chr(0b10011 + 0o35), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1011100 + 0o23) + chr(0b110001) + '\062' + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + chr(52) + '\x37', 0o10), ehT0Px3KOsy9(chr(48) + chr(11409 - 11298) + chr(0b110011) + '\060' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(232 - 184) + chr(111) + '\x35' + chr(0b110101), 52154 - 52146), ehT0Px3KOsy9(chr(0b110000) + chr(12031 - 11920) + chr(0b11 + 0o62) + chr(54), 0b1000), ehT0Px3KOsy9(chr(1259 - 1211) + chr(0b1011010 + 0o25) + chr(0b10110 + 0o35) + '\x30' + chr(670 - 615), 0b1000), ehT0Px3KOsy9(chr(2195 - 2147) + chr(0b1101111) + '\x33' + chr(0b10010 + 0o43) + chr(0b1010 + 0o52), 13570 - 13562), ehT0Px3KOsy9('\060' + '\157' + chr(112 - 63) + chr(411 - 358) + chr(50), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b11110 + 0o25) + '\x35' + chr(55), 38967 - 38959), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b1001011 + 0o44) + chr(49) + chr(956 - 905) + chr(1861 - 1809), 0o10), ehT0Px3KOsy9(chr(1337 - 1289) + chr(0b10001 + 0o136) + chr(0b11010 + 0o31) + chr(0b110011) + chr(49), 35279 - 35271), ehT0Px3KOsy9('\x30' + '\157' + chr(0b100111 + 0o17) + chr(55), 0o10), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(0b1101111) + chr(0b110001) + chr(1201 - 1153) + chr(0b1000 + 0o55), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + chr(0b110111) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x31' + '\066' + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110100), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(111) + '\x35' + chr(423 - 375), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd0'), '\x64' + '\x65' + '\x63' + chr(111) + chr(0b1100100) + chr(0b101010 + 0o73))('\x75' + chr(0b1110100) + chr(2353 - 2251) + chr(0b10100 + 0o31) + chr(0b11 + 0o65)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Lmw8zVshGEMD(vXoupepMtCXU, SrQ3Hfhd_bRp, m6gwVXy4D3Au=ehT0Px3KOsy9(chr(48) + '\x6f' + '\063', 0o10), _GyOifGFZyk1=xafqLlk3kkUe(IDJ2eXGCBCDu.nn, xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\xe9r\xd9\x00\xbb\x13\xb0n0'), chr(9539 - 9439) + '\x65' + chr(99) + chr(111) + '\144' + '\x65')(chr(0b1110101) + chr(0b11111 + 0o125) + chr(0b11000 + 0o116) + chr(0b101101) + '\x38')), TFLseEYASEKG=xafqLlk3kkUe(SXOLrMavuUCe(b'\xad\xcd^\xf7'), chr(4578 - 4478) + '\x65' + chr(99) + '\157' + chr(8437 - 8337) + chr(101))(chr(0b1110101) + chr(116) + chr(0b1100110) + chr(0b100100 + 0o11) + '\070'), XQJVi3cQFN5l=ehT0Px3KOsy9(chr(1863 - 1815) + chr(10400 - 10289) + '\061', ord("\x08")), VsVzIDwVAdNX=ehT0Px3KOsy9(chr(48) + chr(111) + '\060', 0o10), CJBHNoj4zKoT=None):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x88\xeda\xdb\x18\x86\r\xb0]6\x1e\xe6\x0bU'), chr(0b101010 + 0o72) + chr(101) + chr(0b1100011) + chr(0b1101111) + chr(100) + '\x65')(chr(11351 - 11234) + '\x74' + chr(0b1100110) + chr(0b101101) + chr(1477 - 1421)))(CJBHNoj4zKoT):
DyzboKL9cczb = uWOby3XrTzFz.conv2d(vXoupepMtCXU, SrQ3Hfhd_bRp, kernel_size=m6gwVXy4D3Au, padding=TFLseEYASEKG, activation=None, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x9d\xe3}\xc4'), '\144' + chr(0b111010 + 0o53) + chr(4173 - 4074) + chr(111) + chr(7653 - 7553) + chr(101))('\165' + chr(116) + chr(102) + '\x2d' + chr(0b100110 + 0o22)))
if VsVzIDwVAdNX:
DyzboKL9cczb = uWOby3XrTzFz.batch_normalization(DyzboKL9cczb, training=XQJVi3cQFN5l, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x9c\xe2'), chr(8858 - 8758) + chr(101) + chr(7220 - 7121) + chr(0b1101111) + chr(8325 - 8225) + '\x65')(chr(117) + '\x74' + '\x66' + '\x2d' + chr(0b1111 + 0o51)))
DyzboKL9cczb = _GyOifGFZyk1(DyzboKL9cczb)
return DyzboKL9cczb
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
tile_and_concat
|
def tile_and_concat(image, latent, concat_latent=True):
"""Tile latent and concatenate to image across depth.
Args:
image: 4-D Tensor, (batch_size X height X width X channels)
latent: 2-D Tensor, (batch_size X latent_dims)
concat_latent: If set to False, the image is returned as is.
Returns:
concat_latent: 4-D Tensor, (batch_size X height X width X channels+1)
latent tiled and concatenated to the image across the channels.
"""
if not concat_latent:
return image
image_shape = common_layers.shape_list(image)
latent_shape = common_layers.shape_list(latent)
height, width = image_shape[1], image_shape[2]
latent_dims = latent_shape[1]
height_multiples = height // latent_dims
pad = height - (height_multiples * latent_dims)
latent = tf.reshape(latent, (-1, latent_dims, 1, 1))
latent = tf.tile(latent, (1, height_multiples, width, 1))
latent = tf.pad(latent, [[0, 0], [pad // 2, pad // 2], [0, 0], [0, 0]])
return tf.concat([image, latent], axis=-1)
|
python
|
def tile_and_concat(image, latent, concat_latent=True):
"""Tile latent and concatenate to image across depth.
Args:
image: 4-D Tensor, (batch_size X height X width X channels)
latent: 2-D Tensor, (batch_size X latent_dims)
concat_latent: If set to False, the image is returned as is.
Returns:
concat_latent: 4-D Tensor, (batch_size X height X width X channels+1)
latent tiled and concatenated to the image across the channels.
"""
if not concat_latent:
return image
image_shape = common_layers.shape_list(image)
latent_shape = common_layers.shape_list(latent)
height, width = image_shape[1], image_shape[2]
latent_dims = latent_shape[1]
height_multiples = height // latent_dims
pad = height - (height_multiples * latent_dims)
latent = tf.reshape(latent, (-1, latent_dims, 1, 1))
latent = tf.tile(latent, (1, height_multiples, width, 1))
latent = tf.pad(latent, [[0, 0], [pad // 2, pad // 2], [0, 0], [0, 0]])
return tf.concat([image, latent], axis=-1)
|
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Tile latent and concatenate to image across depth.
Args:
image: 4-D Tensor, (batch_size X height X width X channels)
latent: 2-D Tensor, (batch_size X latent_dims)
concat_latent: If set to False, the image is returned as is.
Returns:
concat_latent: 4-D Tensor, (batch_size X height X width X channels+1)
latent tiled and concatenated to the image across the channels.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L338-L361
|
train
|
Tile latent and concatenate to image across depth.
|
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(0b1010110 + 0o31) + chr(0b110001) + chr(0b101001 + 0o15) + chr(0b110111 + 0o0), 0o10), ehT0Px3KOsy9(chr(1436 - 1388) + chr(3485 - 3374) + chr(0b11001 + 0o31) + chr(53) + '\066', 32584 - 32576), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1589 - 1536) + '\066', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b11101 + 0o122) + '\x33' + chr(2480 - 2428), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(2384 - 2333) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\062' + '\061' + chr(55), 5457 - 5449), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b11011 + 0o27) + chr(0b110100) + chr(787 - 733), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\064' + chr(0b101110 + 0o4), 41614 - 41606), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x32' + chr(0b1000 + 0o55) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101000 + 0o7) + chr(0b110001) + '\x34' + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061' + '\063' + '\x31', 49234 - 49226), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(111) + chr(0b100100 + 0o16) + chr(0b101111 + 0o2) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(1863 - 1815) + chr(0b10011 + 0o134) + chr(0b110011) + '\x32' + chr(0b110101), 0o10), ehT0Px3KOsy9('\060' + chr(0b11011 + 0o124) + '\063' + chr(1347 - 1297) + chr(0b10111 + 0o32), 61528 - 61520), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(0b1101111) + chr(0b1011 + 0o46) + chr(0b110010) + '\066', 0o10), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(5941 - 5830) + chr(0b110010) + '\066' + '\062', 29039 - 29031), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1 + 0o60) + chr(49) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\060' + chr(7165 - 7054) + chr(1953 - 1903) + chr(0b1000 + 0o50) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b1101111) + '\x32' + chr(49) + chr(0b100110 + 0o14), 8), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(10780 - 10669) + chr(2831 - 2777) + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(111) + chr(0b11111 + 0o22) + chr(0b110010) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b111010 + 0o65) + chr(50) + chr(49) + chr(54), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\061' + chr(839 - 787) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + chr(363 - 314) + chr(260 - 207), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10101 + 0o34) + chr(0b110111) + chr(927 - 875), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b110 + 0o151) + '\x31' + chr(0b0 + 0o66) + '\x37', 8), ehT0Px3KOsy9(chr(48) + chr(111) + '\062' + '\x31' + '\067', 8), ehT0Px3KOsy9(chr(48) + chr(0b1000111 + 0o50) + chr(0b110010) + chr(53) + '\064', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\x32' + '\060' + chr(55), 262 - 254), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(381 - 333) + chr(111) + '\061' + '\062' + chr(561 - 509), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\x31' + chr(52) + '\060', 16731 - 16723), ehT0Px3KOsy9(chr(0b1100 + 0o44) + '\157' + chr(0b101010 + 0o10) + '\x32' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\063' + chr(0b110111) + chr(54), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b10001 + 0o136) + chr(52) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(411 - 363) + chr(111) + chr(49) + chr(0b110001) + chr(268 - 220), 22693 - 22685), ehT0Px3KOsy9(chr(691 - 643) + '\x6f' + chr(54) + chr(2612 - 2558), 8), ehT0Px3KOsy9(chr(0b110000) + chr(2200 - 2089) + chr(361 - 311) + '\062' + chr(1728 - 1674), 26097 - 26089), ehT0Px3KOsy9(chr(694 - 646) + chr(10318 - 10207) + chr(0b1011 + 0o46) + '\x36' + chr(0b0 + 0o61), 20217 - 20209), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + '\x36' + '\067', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(0b1100000 + 0o17) + chr(1583 - 1530) + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'Y'), chr(100) + chr(0b1100101) + chr(99) + '\x6f' + chr(8106 - 8006) + chr(0b1100101))(chr(0b1110101) + chr(116) + chr(0b1001 + 0o135) + '\055' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def sITYaSS53aue(IdmAHWfCqrnp, WAc4zXt4LtrH, Ys0s563mWYnk=ehT0Px3KOsy9('\060' + chr(111) + chr(742 - 693), 26195 - 26187)):
if not Ys0s563mWYnk:
return IdmAHWfCqrnp
y75rm19CmWff = jSKPaHwSAfVv.shape_list(IdmAHWfCqrnp)
XhU4geNCR0zu = jSKPaHwSAfVv.shape_list(WAc4zXt4LtrH)
(ehbUULKuygfC, mPx09rBTrGXR) = (y75rm19CmWff[ehT0Px3KOsy9(chr(0b10 + 0o56) + '\x6f' + '\x31', 8)], y75rm19CmWff[ehT0Px3KOsy9(chr(1284 - 1236) + '\x6f' + chr(0b110010), ord("\x08"))])
qVkmW8bKVmfm = XhU4geNCR0zu[ehT0Px3KOsy9(chr(2216 - 2168) + chr(7514 - 7403) + '\061', 8)]
UcjyljSLU8Lb = ehbUULKuygfC // qVkmW8bKVmfm
jq0C7ttmqXPS = ehbUULKuygfC - UcjyljSLU8Lb * qVkmW8bKVmfm
WAc4zXt4LtrH = IDJ2eXGCBCDu.reshape(WAc4zXt4LtrH, (-ehT0Px3KOsy9(chr(2055 - 2007) + chr(0b11010 + 0o125) + chr(0b101100 + 0o5), 8), qVkmW8bKVmfm, ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061', 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001), 8)))
WAc4zXt4LtrH = IDJ2eXGCBCDu.tile(WAc4zXt4LtrH, (ehT0Px3KOsy9(chr(48) + chr(7567 - 7456) + '\x31', 8), UcjyljSLU8Lb, mPx09rBTrGXR, ehT0Px3KOsy9('\060' + chr(0b1010011 + 0o34) + chr(0b10 + 0o57), 8)))
WAc4zXt4LtrH = IDJ2eXGCBCDu.pad(WAc4zXt4LtrH, [[ehT0Px3KOsy9(chr(48) + chr(0b1101 + 0o142) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1208 - 1160), 8)], [jq0C7ttmqXPS // ehT0Px3KOsy9(chr(48) + chr(11450 - 11339) + chr(0b110010), 8), jq0C7ttmqXPS // ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010), 8)], [ehT0Px3KOsy9(chr(708 - 660) + chr(0b1101111) + chr(0b11000 + 0o30), 8), ehT0Px3KOsy9(chr(48) + '\157' + '\x30', 8)], [ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b11011 + 0o25), 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(48), 8)]])
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x14\xc1@\x7f\xb8\xfb'), '\x64' + '\145' + '\143' + chr(111) + chr(100) + '\x65')(chr(0b1110101) + '\x74' + chr(0b1100110) + chr(45) + '\070'))([IdmAHWfCqrnp, WAc4zXt4LtrH], axis=-ehT0Px3KOsy9(chr(0b110000) + chr(11429 - 11318) + '\x31', 8))
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
_encode_gif
|
def _encode_gif(images, fps):
"""Encodes numpy images into gif string.
Args:
images: A 4-D `uint8` `np.array` (or a list of 3-D images) of shape
`[time, height, width, channels]` where `channels` is 1 or 3.
fps: frames per second of the animation
Returns:
The encoded gif string.
Raises:
IOError: If the ffmpeg command returns an error.
"""
writer = WholeVideoWriter(fps)
writer.write_multi(images)
return writer.finish()
|
python
|
def _encode_gif(images, fps):
"""Encodes numpy images into gif string.
Args:
images: A 4-D `uint8` `np.array` (or a list of 3-D images) of shape
`[time, height, width, channels]` where `channels` is 1 or 3.
fps: frames per second of the animation
Returns:
The encoded gif string.
Raises:
IOError: If the ffmpeg command returns an error.
"""
writer = WholeVideoWriter(fps)
writer.write_multi(images)
return writer.finish()
|
[
"def",
"_encode_gif",
"(",
"images",
",",
"fps",
")",
":",
"writer",
"=",
"WholeVideoWriter",
"(",
"fps",
")",
"writer",
".",
"write_multi",
"(",
"images",
")",
"return",
"writer",
".",
"finish",
"(",
")"
] |
Encodes numpy images into gif string.
Args:
images: A 4-D `uint8` `np.array` (or a list of 3-D images) of shape
`[time, height, width, channels]` where `channels` is 1 or 3.
fps: frames per second of the animation
Returns:
The encoded gif string.
Raises:
IOError: If the ffmpeg command returns an error.
|
[
"Encodes",
"numpy",
"images",
"into",
"gif",
"string",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L364-L380
|
train
|
Encodes numpy images into gif string.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + '\x32' + chr(0b110000), 29277 - 29269), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + chr(52) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(7794 - 7683) + chr(0b110011) + '\066' + '\x30', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b10000 + 0o137) + chr(0b110010) + chr(0b110110) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(1591 - 1480) + chr(49) + '\065' + chr(48), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b10001 + 0o40) + '\067' + '\066', 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b11100 + 0o123) + chr(937 - 888) + '\x32' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(527 - 476) + chr(0b110001) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b101110 + 0o101) + chr(0b100100 + 0o15) + chr(55), 0o10), ehT0Px3KOsy9(chr(1040 - 992) + '\x6f' + chr(49) + chr(2385 - 2333) + chr(0b101001 + 0o14), 0b1000), ehT0Px3KOsy9(chr(285 - 237) + chr(0b1101111) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110011) + chr(55) + chr(0b110100), 47432 - 47424), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100111 + 0o15) + '\067', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b10101 + 0o34) + '\064', 15694 - 15686), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + chr(0b111 + 0o55), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b110010) + chr(435 - 385) + '\061', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11111 + 0o23) + chr(944 - 894) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b1000 + 0o53) + chr(534 - 485) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(1301 - 1253) + chr(3421 - 3310) + '\061', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + '\060' + chr(1073 - 1019), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b101 + 0o152) + chr(52) + chr(0b101111 + 0o4), 0o10), ehT0Px3KOsy9(chr(374 - 326) + chr(0b1101111) + chr(0b1011 + 0o50) + chr(1797 - 1749) + chr(0b1001 + 0o47), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(11620 - 11509) + '\062' + '\x31' + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(111) + '\067' + chr(1377 - 1324), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + '\x33' + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(1472 - 1422) + chr(51), 53575 - 53567), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\062' + chr(0b1010 + 0o53) + '\x31', 28216 - 28208), ehT0Px3KOsy9('\060' + chr(6490 - 6379) + chr(0b1100 + 0o45) + chr(0b110100), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b100010 + 0o115) + '\x31' + chr(55) + chr(0b100010 + 0o17), 38196 - 38188), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\062' + chr(0b110011) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(48) + chr(7154 - 7043) + chr(55) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(1236 - 1188) + '\065', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b100001 + 0o22) + chr(0b110110) + chr(50), 0o10), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b1101111) + chr(0b100010 + 0o20) + chr(0b110100) + chr(0b111 + 0o51), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + chr(0b10010 + 0o41) + chr(2000 - 1951), 31023 - 31015), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001) + '\x33' + chr(0b10100 + 0o40), 0o10), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(111) + chr(52) + chr(51), 8), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(0b110010) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(48) + chr(5433 - 5322) + chr(0b11111 + 0o22) + chr(0b1001 + 0o55) + chr(50), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101100 + 0o3) + '\062' + '\067' + chr(55), 30483 - 30475)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011 + 0o2) + chr(48), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xfe'), chr(0b1011001 + 0o13) + chr(5592 - 5491) + chr(0b1100011) + chr(0b1010010 + 0o35) + '\144' + chr(101))(chr(742 - 625) + chr(0b1110100) + chr(0b1000 + 0o136) + chr(1768 - 1723) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ss2p6qRYCfPP(YJOmEcibG8C0, ToH1dgLAm5iP):
AkL2ZqopDgiR = IlATtqvAQLfB(ToH1dgLAm5iP)
xafqLlk3kkUe(AkL2ZqopDgiR, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa7\x90\x99\xc1\r!8\xbec\x11j'), chr(0b1100100) + '\145' + chr(0b1100011) + '\157' + chr(0b1100100) + chr(101))('\x75' + '\x74' + chr(8295 - 8193) + '\x2d' + '\070'))(YJOmEcibG8C0)
return xafqLlk3kkUe(AkL2ZqopDgiR, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb6\x8b\x9e\xdc\x1b\x16'), '\x64' + chr(0b11011 + 0o112) + chr(0b1011 + 0o130) + '\x6f' + chr(7357 - 7257) + chr(0b1100 + 0o131))('\x75' + '\x74' + '\146' + chr(0b101101) + '\070'))()
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
ffmpeg_works
|
def ffmpeg_works():
"""Tries to encode images with ffmpeg to check if it works."""
images = np.zeros((2, 32, 32, 3), dtype=np.uint8)
try:
_encode_gif(images, 2)
return True
except (IOError, OSError):
return False
|
python
|
def ffmpeg_works():
"""Tries to encode images with ffmpeg to check if it works."""
images = np.zeros((2, 32, 32, 3), dtype=np.uint8)
try:
_encode_gif(images, 2)
return True
except (IOError, OSError):
return False
|
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Tries to encode images with ffmpeg to check if it works.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L383-L390
|
train
|
Tries to encode images with ffmpeg to check if it works.
|
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(111) + chr(231 - 182) + chr(0b110010) + chr(229 - 179), 0o10), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b1010101 + 0o32) + chr(50) + '\061' + chr(0b101011 + 0o7), 5573 - 5565), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001 + 0o1) + '\067' + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + '\067' + chr(0b110111), 8), ehT0Px3KOsy9(chr(48) + chr(111) + '\063' + chr(0b101011 + 0o7) + chr(0b11101 + 0o32), 0b1000), ehT0Px3KOsy9(chr(2047 - 1999) + '\x6f' + chr(0b110011) + '\x36' + chr(0b101100 + 0o11), 0b1000), ehT0Px3KOsy9('\060' + chr(7800 - 7689) + chr(0b100110 + 0o15) + chr(1067 - 1013) + chr(54), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b10111 + 0o130) + chr(50) + '\066', 36334 - 36326), ehT0Px3KOsy9(chr(48) + '\157' + chr(1519 - 1470) + '\062' + chr(1734 - 1684), 8), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + chr(282 - 233) + '\066', 26533 - 26525), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\157' + chr(51) + '\065' + chr(54), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\x32' + chr(540 - 488) + chr(230 - 178), 54010 - 54002), ehT0Px3KOsy9(chr(0b110000) + chr(4681 - 4570) + chr(1077 - 1028) + '\x32', 0b1000), ehT0Px3KOsy9(chr(2252 - 2204) + chr(0b1101111) + chr(55) + '\067', 12598 - 12590), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b1101 + 0o44) + '\065' + '\061', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + '\065' + '\x33', 5014 - 5006), ehT0Px3KOsy9('\060' + '\x6f' + '\x36' + chr(48), 48493 - 48485), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(51) + chr(0b11111 + 0o23), 0b1000), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b1100001 + 0o16) + chr(51) + '\065' + chr(0b110110), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + '\067', 0o10), ehT0Px3KOsy9('\060' + chr(0b1000110 + 0o51) + '\x33' + chr(0b110110) + chr(48), 24389 - 24381), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\157' + chr(0b110010) + chr(0b10001 + 0o46) + '\063', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(0b110010) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(0b1101111) + chr(2160 - 2109) + chr(0b110100) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b101101 + 0o102) + chr(1745 - 1694) + chr(0b110101) + '\063', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061' + chr(0b1111 + 0o41) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + '\x34' + '\x34', 8), ehT0Px3KOsy9(chr(1005 - 957) + chr(8999 - 8888) + '\x32' + chr(2644 - 2591), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(1471 - 1420) + '\065' + chr(669 - 621), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1001011 + 0o44) + '\061' + '\065' + chr(0b10100 + 0o36), 0b1000), ehT0Px3KOsy9(chr(1796 - 1748) + chr(4044 - 3933) + '\x32' + chr(1879 - 1831) + chr(54), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\x33' + '\x35' + '\067', 57340 - 57332), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110100) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(0b1101111) + '\x31' + chr(0b11000 + 0o30) + chr(0b10110 + 0o32), 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(0b110010) + '\065', 8), ehT0Px3KOsy9(chr(48) + chr(2294 - 2183) + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(1924 - 1876) + '\x6f' + '\063' + '\067' + '\x34', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1011101 + 0o22) + chr(0b110011) + chr(55) + chr(0b110111), 40181 - 40173), ehT0Px3KOsy9('\060' + chr(551 - 440) + chr(50) + chr(53) + chr(0b110101), 21280 - 21272)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b110100 + 0o73) + chr(2287 - 2234) + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'|'), chr(0b101101 + 0o67) + chr(8069 - 7968) + chr(0b1100011) + '\x6f' + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + chr(0b1110001 + 0o3) + '\x66' + chr(0b10000 + 0o35) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def JJaTtAyx3Rd8():
YJOmEcibG8C0 = WqUC3KWvYVup.zeros((ehT0Px3KOsy9(chr(0b110000) + chr(10841 - 10730) + chr(0b100011 + 0o17), 28965 - 28957), ehT0Px3KOsy9(chr(48) + chr(0b1000110 + 0o51) + '\064' + '\x30', 8), ehT0Px3KOsy9(chr(0b100101 + 0o13) + '\x6f' + chr(2503 - 2451) + chr(48), 8), ehT0Px3KOsy9('\x30' + '\x6f' + '\063', 8)), dtype=WqUC3KWvYVup.uint8)
try:
ss2p6qRYCfPP(YJOmEcibG8C0, ehT0Px3KOsy9(chr(0b100101 + 0o13) + '\x6f' + '\x32', 8))
return ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31', 0o10)
except (sR2sPcm7Zrfn, KlPSljPzIJ_u):
return ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\060', 60110 - 60102)
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
py_gif_summary
|
def py_gif_summary(tag, images, max_outputs, fps, return_summary_value=False):
"""Outputs a `Summary` protocol buffer with gif animations.
Args:
tag: Name of the summary.
images: A 5-D `uint8` `np.array` of shape `[batch_size, time, height, width,
channels]` where `channels` is 1 or 3.
max_outputs: Max number of batch elements to generate gifs for.
fps: frames per second of the animation.
return_summary_value: If set to True, return a list of tf.Summary.Value
objects in addition to the protocol buffer.
Returns:
The serialized `Summary` protocol buffer.
Raises:
ValueError: If `images` is not a 5-D `uint8` array with 1 or 3 channels.
"""
images = np.asarray(images)
if images.dtype != np.uint8:
raise ValueError("Tensor must have dtype uint8 for gif summary.")
if images.ndim != 5:
raise ValueError("Tensor must be 5-D for gif summary.")
batch_size, _, height, width, channels = images.shape
if channels not in (1, 3):
raise ValueError("Tensors must have 1 or 3 channels for gif summary.")
summ = tf.Summary()
all_summ_values = []
num_outputs = min(batch_size, max_outputs)
for i in range(num_outputs):
image_summ = tf.Summary.Image()
image_summ.height = height
image_summ.width = width
image_summ.colorspace = channels # 1: grayscale, 3: RGB
try:
image_summ.encoded_image_string = _encode_gif(images[i], fps)
except (IOError, OSError) as e:
tf.logging.warning(
"Unable to encode images to a gif string because either ffmpeg is "
"not installed or ffmpeg returned an error: %s. Falling back to an "
"image summary of the first frame in the sequence.", e)
try:
from PIL import Image # pylint: disable=g-import-not-at-top
import io # pylint: disable=g-import-not-at-top
with io.BytesIO() as output:
Image.fromarray(images[i][0]).save(output, "PNG")
image_summ.encoded_image_string = output.getvalue()
except ImportError as e:
tf.logging.warning(
"Gif summaries requires ffmpeg or PIL to be installed: %s", e)
image_summ.encoded_image_string = ""
if num_outputs == 1:
summ_tag = "{}/gif".format(tag)
else:
summ_tag = "{}/gif/{}".format(tag, i)
curr_summ_value = tf.Summary.Value(tag=summ_tag, image=image_summ)
all_summ_values.append(curr_summ_value)
summ.value.add(tag=summ_tag, image=image_summ)
summ_str = summ.SerializeToString()
if return_summary_value:
return all_summ_values, summ_str
return summ_str
|
python
|
def py_gif_summary(tag, images, max_outputs, fps, return_summary_value=False):
"""Outputs a `Summary` protocol buffer with gif animations.
Args:
tag: Name of the summary.
images: A 5-D `uint8` `np.array` of shape `[batch_size, time, height, width,
channels]` where `channels` is 1 or 3.
max_outputs: Max number of batch elements to generate gifs for.
fps: frames per second of the animation.
return_summary_value: If set to True, return a list of tf.Summary.Value
objects in addition to the protocol buffer.
Returns:
The serialized `Summary` protocol buffer.
Raises:
ValueError: If `images` is not a 5-D `uint8` array with 1 or 3 channels.
"""
images = np.asarray(images)
if images.dtype != np.uint8:
raise ValueError("Tensor must have dtype uint8 for gif summary.")
if images.ndim != 5:
raise ValueError("Tensor must be 5-D for gif summary.")
batch_size, _, height, width, channels = images.shape
if channels not in (1, 3):
raise ValueError("Tensors must have 1 or 3 channels for gif summary.")
summ = tf.Summary()
all_summ_values = []
num_outputs = min(batch_size, max_outputs)
for i in range(num_outputs):
image_summ = tf.Summary.Image()
image_summ.height = height
image_summ.width = width
image_summ.colorspace = channels # 1: grayscale, 3: RGB
try:
image_summ.encoded_image_string = _encode_gif(images[i], fps)
except (IOError, OSError) as e:
tf.logging.warning(
"Unable to encode images to a gif string because either ffmpeg is "
"not installed or ffmpeg returned an error: %s. Falling back to an "
"image summary of the first frame in the sequence.", e)
try:
from PIL import Image # pylint: disable=g-import-not-at-top
import io # pylint: disable=g-import-not-at-top
with io.BytesIO() as output:
Image.fromarray(images[i][0]).save(output, "PNG")
image_summ.encoded_image_string = output.getvalue()
except ImportError as e:
tf.logging.warning(
"Gif summaries requires ffmpeg or PIL to be installed: %s", e)
image_summ.encoded_image_string = ""
if num_outputs == 1:
summ_tag = "{}/gif".format(tag)
else:
summ_tag = "{}/gif/{}".format(tag, i)
curr_summ_value = tf.Summary.Value(tag=summ_tag, image=image_summ)
all_summ_values.append(curr_summ_value)
summ.value.add(tag=summ_tag, image=image_summ)
summ_str = summ.SerializeToString()
if return_summary_value:
return all_summ_values, summ_str
return summ_str
|
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"summ_str"
] |
Outputs a `Summary` protocol buffer with gif animations.
Args:
tag: Name of the summary.
images: A 5-D `uint8` `np.array` of shape `[batch_size, time, height, width,
channels]` where `channels` is 1 or 3.
max_outputs: Max number of batch elements to generate gifs for.
fps: frames per second of the animation.
return_summary_value: If set to True, return a list of tf.Summary.Value
objects in addition to the protocol buffer.
Returns:
The serialized `Summary` protocol buffer.
Raises:
ValueError: If `images` is not a 5-D `uint8` array with 1 or 3 channels.
|
[
"Outputs",
"a",
"Summary",
"protocol",
"buffer",
"with",
"gif",
"animations",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L393-L455
|
train
|
Outputs a tf. Summary protocol buffer with gif animations.
|
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(0b101111 + 0o1) + chr(0b1101111) + chr(1016 - 961) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(6384 - 6273) + chr(0b110101) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(5950 - 5839) + '\x33' + chr(0b110110) + '\x37', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + '\x30', 45642 - 45634), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1010111 + 0o30) + chr(0b111 + 0o53) + chr(50) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10110 + 0o35) + chr(0b110111) + chr(50), 0b1000), ehT0Px3KOsy9('\x30' + chr(987 - 876) + chr(0b100111 + 0o13) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(0b110011) + '\x35', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10001 + 0o41) + chr(53) + chr(403 - 348), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\061' + chr(0b110100) + chr(51), 0o10), ehT0Px3KOsy9(chr(731 - 683) + chr(111) + chr(0b110001) + '\x37' + '\x35', 10898 - 10890), ehT0Px3KOsy9(chr(0b0 + 0o60) + '\157' + chr(51) + '\x37' + '\065', 44922 - 44914), ehT0Px3KOsy9('\060' + chr(111) + chr(479 - 429) + chr(616 - 568) + chr(51), 59766 - 59758), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000100 + 0o53) + chr(49) + chr(0b10101 + 0o35) + '\x37', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + chr(0b110101) + chr(0b11110 + 0o27), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + chr(52), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b101111 + 0o2) + '\060' + chr(2516 - 2465), 58242 - 58234), ehT0Px3KOsy9(chr(862 - 814) + chr(0b1101111) + '\064' + chr(0b111 + 0o55), 0b1000), ehT0Px3KOsy9(chr(2229 - 2181) + chr(0b1101111) + '\x32' + chr(0b10100 + 0o35) + chr(0b101101 + 0o10), 0o10), ehT0Px3KOsy9(chr(213 - 165) + chr(10517 - 10406) + chr(0b101111 + 0o3) + '\067' + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1001 + 0o50) + chr(954 - 900) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49) + '\064' + chr(0b110110), 6302 - 6294), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\157' + chr(50) + chr(55) + chr(1326 - 1275), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(1857 - 1808) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(9338 - 9227) + chr(2362 - 2313) + chr(0b110111) + chr(52), 41858 - 41850), ehT0Px3KOsy9('\x30' + chr(7785 - 7674) + chr(778 - 729) + chr(1200 - 1148) + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + '\064' + '\066', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\x31' + chr(52) + chr(1686 - 1637), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(53) + chr(48), 8), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + '\061' + chr(55), 0o10), ehT0Px3KOsy9(chr(0b100111 + 0o11) + '\157' + '\063' + '\x33' + chr(923 - 875), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + chr(0b110001 + 0o4) + chr(1369 - 1320), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b101011 + 0o14) + chr(55), 60086 - 60078), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\063' + '\x30' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\x31' + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b101000 + 0o10) + '\157' + chr(917 - 868) + '\066', ord("\x08")), ehT0Px3KOsy9('\060' + chr(10481 - 10370) + chr(2386 - 2336) + chr(54) + chr(0b1100 + 0o45), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101000 + 0o7) + chr(0b110111) + '\x37', 8), ehT0Px3KOsy9(chr(799 - 751) + chr(111) + '\063', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(5457 - 5346) + '\061' + '\x35' + '\x30', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\157' + '\065' + chr(411 - 363), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x17'), chr(100) + chr(896 - 795) + chr(0b1100011) + chr(11265 - 11154) + '\144' + '\145')(chr(0b110110 + 0o77) + chr(116) + chr(102) + '\x2d' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def xhFjw0K_I8fl(CPdEsc5O1sf7, YJOmEcibG8C0, i7r136MIYrlH, ToH1dgLAm5iP, FxdmyZsPJg_k=ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b1101111) + chr(0b11000 + 0o30), 0o10)):
YJOmEcibG8C0 = WqUC3KWvYVup.asarray(YJOmEcibG8C0)
if xafqLlk3kkUe(YJOmEcibG8C0, xafqLlk3kkUe(SXOLrMavuUCe(b'S{\xa1!\xdc\xb1~\xf8\xc2+J\xb6'), '\144' + chr(101) + chr(99) + '\x6f' + '\144' + chr(0b1100101))(chr(0b1110101) + '\164' + chr(0b1100110) + chr(0b101101) + '\070')) != xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'LA\x99l\xad'), chr(7482 - 7382) + chr(1393 - 1292) + chr(99) + chr(5550 - 5439) + chr(0b1100100) + '\145')(chr(0b1110101) + '\164' + '\146' + chr(0b101101) + chr(0b110101 + 0o3))):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'mM\x99k\xfa\x880\xf0\xda\x10\t\xdd\xeb6\x9byc@\xf9\xc5\x01\x03\x9b\x7f\x15\t\xd2Y\x08)\xb7\xdb\x1f\xa1bh\x91Lv\x05TI\x85a\xbb'), chr(0b110011 + 0o61) + chr(0b100111 + 0o76) + chr(0b1100011) + '\x6f' + chr(0b1100100) + chr(0b1100101))('\x75' + chr(0b1110100) + '\x66' + '\055' + '\070'))
if xafqLlk3kkUe(YJOmEcibG8C0, xafqLlk3kkUe(SXOLrMavuUCe(b'^G\x9ah\xdd\xb8y\xc9\xdc\x057\xa9'), chr(100) + chr(3282 - 3181) + chr(7424 - 7325) + '\157' + chr(0b1100100) + chr(6506 - 6405))(chr(12906 - 12789) + chr(0b101000 + 0o114) + chr(0b1000011 + 0o43) + chr(0b101101) + chr(897 - 841))) != ehT0Px3KOsy9(chr(0b111 + 0o51) + '\x6f' + '\x35', ord("\x08")):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'mM\x99k\xfa\x880\xf0\xda\x10\t\xdd\xe12\xcd)n`\xad\xda\x1e\x14\x9bm\x15\x01\x86\x12]"\xb5\xc8M\xbf%'), chr(0b1100100) + '\145' + chr(0b1100011) + chr(7161 - 7050) + chr(0b1001010 + 0o32) + chr(7166 - 7065))(chr(117) + chr(0b1110100) + chr(0b1100110) + '\x2d' + '\x38'))
(ix9dZyeAmUxY, VNGQdHSFPrso, ehbUULKuygfC, mPx09rBTrGXR, H2MQqAZeamNo) = YJOmEcibG8C0.nauYfLglTpcb
if H2MQqAZeamNo not in (ehT0Px3KOsy9('\060' + chr(5693 - 5582) + '\061', 0b1000), ehT0Px3KOsy9('\x30' + chr(3075 - 2964) + '\063', 8)):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'mM\x99k\xfa\x88c\xbd\xc2\x16\x0e\x89\xa3?\x8cj&\x04\xbc\x9c\x1e\x14\x9b9\\\x04\xce\x00F!\xbd\xc5L\xe6ma\xc3\x1fd\x01_\x08\x84m\xf8\x97q\xef\xd6M'), '\x64' + '\145' + chr(3515 - 3416) + chr(0b1101111) + chr(100) + chr(2907 - 2806))(chr(0b11001 + 0o134) + '\x74' + '\x66' + chr(298 - 253) + chr(56)))
w5iFCBxwbec3 = IDJ2eXGCBCDu.Summary()
bxGkVLj0A5FD = []
YzOh4ZueGp_Q = Dx22bkKPdt5d(ix9dZyeAmUxY, i7r136MIYrlH)
for WVxHKyX45z_L in vQr8gNKaIaWE(YzOh4ZueGp_Q):
t74EiaGw72vT = IDJ2eXGCBCDu.Summary.Image()
t74EiaGw72vT.ehbUULKuygfC = ehbUULKuygfC
t74EiaGw72vT.mPx09rBTrGXR = mPx09rBTrGXR
t74EiaGw72vT.c4rrCFe7EcdI = H2MQqAZeamNo
try:
t74EiaGw72vT.wtqt5pYirw30 = ss2p6qRYCfPP(YJOmEcibG8C0[WVxHKyX45z_L], ToH1dgLAm5iP)
except (sR2sPcm7Zrfn, KlPSljPzIJ_u) as GlnVAPeT6CUe:
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'NI\x85v\xfc\x94w'), chr(100) + chr(101) + chr(0b1100011) + chr(0b1101111) + chr(3718 - 3618) + '\145')(chr(0b1110101) + '\164' + '\146' + chr(0b1010 + 0o43) + chr(1718 - 1662)))(xafqLlk3kkUe(SXOLrMavuUCe(b"lF\x96z\xf9\x9f0\xe9\xc0C\x18\x93\xe08\x89ycM\xe0\xdd\x16\x03\xc8*\x08\x08\x86\x00\x08(\xb1\xcf\x1f\xb5\x7f|\xd8QdH[M\x94y\xe0\x89u\xbd\xca\n\t\x95\xe6%\xcdz%I\xfd\xd9\x16F\xd2y\\\t\xc9\x15\x08&\xb6\xdaK\xa7gb\xd4[#\x07K\x08\x91~\xf8\x8au\xfa\x8f\x11\x18\x89\xf6%\x83y'\x04\xec\xd2Q\x03\xc9x\x13\x15\x9cA\r<\xf6\x89y\xa7gb\xd8QdH[I\x94s\xb5\x8e\x7f\xbd\xce\r]\x94\xee6\x8aycW\xf8\xd1\x1c\x07\xc9s\\\x08\xc0A\\'\xbd\x89Y\xafy}\xc5\x1fe\x1aXE\x928\xfc\x940\xe9\xc7\x06]\x8e\xe6&\x98y-G\xe8\x92"), chr(100) + chr(0b1100101) + '\143' + chr(296 - 185) + chr(9864 - 9764) + chr(101))(chr(0b1100100 + 0o21) + chr(116) + '\146' + chr(45) + '\x38'), GlnVAPeT6CUe)
try:
(Xi3KfA6brWYX,) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'ia\xbb'), chr(100) + chr(101) + '\143' + chr(0b10010 + 0o135) + chr(0b1101 + 0o127) + '\145')(chr(0b1110101) + chr(0b1110100) + chr(0b1100 + 0o132) + '\x2d' + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'pE\x96\x7f\xf0'), '\x64' + chr(714 - 613) + chr(0b1001000 + 0o33) + '\x6f' + '\144' + chr(0b1100101))(chr(0b1101101 + 0o10) + chr(12851 - 12735) + chr(0b10100 + 0o122) + '\x2d' + chr(191 - 135))), xafqLlk3kkUe(SXOLrMavuUCe(b'pE\x96\x7f\xf0'), chr(100) + chr(0b1001000 + 0o35) + chr(0b1100011) + '\157' + chr(0b1100100) + '\145')(chr(117) + chr(116) + chr(102) + '\x2d' + chr(0b110010 + 0o6))),)
(Bey9a5LqdaFa,) = (jFWsnpHpAUWz(xafqLlk3kkUe(SXOLrMavuUCe(b'PG'), chr(100) + '\145' + chr(0b1100011) + chr(0b1101111) + chr(0b1001100 + 0o30) + chr(0b1100101))('\x75' + '\x74' + '\x66' + chr(0b100101 + 0o10) + '\x38')),)
with xafqLlk3kkUe(Bey9a5LqdaFa, xafqLlk3kkUe(SXOLrMavuUCe(b'{Q\x83}\xe6\xb3_'), chr(3762 - 3662) + chr(0b1111 + 0o126) + '\143' + chr(0b1101111) + '\x64' + chr(8410 - 8309))(chr(0b1 + 0o164) + chr(116) + chr(102) + chr(988 - 943) + '\x38'))() as e1jVqMSBZ01Y:
xafqLlk3kkUe(Xi3KfA6brWYX.fromarray(YJOmEcibG8C0[WVxHKyX45z_L][ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1011 + 0o45), 8)]), xafqLlk3kkUe(SXOLrMavuUCe(b'JI\x81}'), chr(7829 - 7729) + '\145' + chr(0b1100011) + chr(10136 - 10025) + '\144' + chr(3173 - 3072))(chr(0b1110101) + '\164' + chr(0b10001 + 0o125) + chr(0b100 + 0o51) + chr(2824 - 2768)))(e1jVqMSBZ01Y, xafqLlk3kkUe(SXOLrMavuUCe(b'if\xb0'), '\144' + chr(0b100011 + 0o102) + chr(0b11100 + 0o107) + chr(0b1101111) + '\x64' + '\145')(chr(4425 - 4308) + chr(116) + chr(0b1100110) + chr(722 - 677) + '\070'))
t74EiaGw72vT.wtqt5pYirw30 = e1jVqMSBZ01Y.getvalue()
except yROw0HWBk0Qc as GlnVAPeT6CUe:
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'NI\x85v\xfc\x94w'), chr(0b1100100) + chr(101) + chr(0b100100 + 0o77) + chr(0b1011111 + 0o20) + chr(0b100110 + 0o76) + chr(0b110110 + 0o57))(chr(8290 - 8173) + '\x74' + chr(5854 - 5752) + chr(0b101101) + chr(0b101100 + 0o14)))(xafqLlk3kkUe(SXOLrMavuUCe(b'~A\x918\xe6\x8f}\xf0\xce\x11\x14\x98\xf0w\x9fy2Q\xe4\xce\x14\x15\x9bl\x1a\n\xd6\x04Oo\xb7\xdb\x1f\x96BB\x91KlH[M\xd7q\xfb\x89d\xfc\xc3\x0f\x18\x99\xb9w\xc8o'), chr(0b110001 + 0o63) + '\x65' + chr(99) + chr(111) + chr(0b101111 + 0o65) + '\x65')(chr(117) + chr(0b1011101 + 0o27) + chr(0b1100110) + '\x2d' + '\070'), GlnVAPeT6CUe)
t74EiaGw72vT.wtqt5pYirw30 = xafqLlk3kkUe(SXOLrMavuUCe(b''), chr(0b1100100) + chr(4243 - 4142) + '\143' + '\x6f' + chr(100) + '\x65')('\x75' + '\164' + chr(5537 - 5435) + chr(0b101101) + '\070')
if YzOh4ZueGp_Q == ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001), 8):
iBR9MOBjexSD = xafqLlk3kkUe(SXOLrMavuUCe(b'BU\xd8\x7f\xfc\x9c'), chr(4230 - 4130) + '\145' + chr(0b11 + 0o140) + '\157' + chr(0b10011 + 0o121) + '\x65')(chr(0b1110101) + chr(116) + '\x66' + chr(45) + '\070').V4roHaS3Ppej(CPdEsc5O1sf7)
else:
iBR9MOBjexSD = xafqLlk3kkUe(SXOLrMavuUCe(b'BU\xd8\x7f\xfc\x9c?\xe6\xd2'), '\144' + chr(0b111000 + 0o55) + chr(0b1000110 + 0o35) + '\x6f' + chr(0b1100100) + chr(0b1100101))('\x75' + chr(0b1101110 + 0o6) + chr(102) + chr(796 - 751) + chr(56)).V4roHaS3Ppej(CPdEsc5O1sf7, WVxHKyX45z_L)
g8eZKz1Ge7cK = IDJ2eXGCBCDu.Summary.Value(tag=iBR9MOBjexSD, image=t74EiaGw72vT)
xafqLlk3kkUe(bxGkVLj0A5FD, xafqLlk3kkUe(SXOLrMavuUCe(b'XX\x87}\xfb\x9e'), chr(0b1001111 + 0o25) + chr(0b1100101) + '\x63' + chr(0b1010 + 0o145) + '\144' + '\x65')(chr(2904 - 2787) + chr(0b1110100) + chr(186 - 84) + '\x2d' + '\x38'))(g8eZKz1Ge7cK)
xafqLlk3kkUe(w5iFCBxwbec3.value, xafqLlk3kkUe(SXOLrMavuUCe(b'XL\x93'), chr(100) + chr(0b1100101) + chr(99) + '\157' + chr(0b1100100) + '\145')(chr(2515 - 2398) + '\164' + '\146' + chr(45) + chr(0b110110 + 0o2)))(tag=iBR9MOBjexSD, image=t74EiaGw72vT)
OEJH44GZLPtB = w5iFCBxwbec3.SerializeToString()
if FxdmyZsPJg_k:
return (bxGkVLj0A5FD, OEJH44GZLPtB)
return OEJH44GZLPtB
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
gif_summary
|
def gif_summary(name, tensor, max_outputs=3, fps=10, collections=None,
family=None):
"""Outputs a `Summary` protocol buffer with gif animations.
Args:
name: Name of the summary.
tensor: A 5-D `uint8` `Tensor` of shape `[batch_size, time, height, width,
channels]` where `channels` is 1 or 3.
max_outputs: Max number of batch elements to generate gifs for.
fps: frames per second of the animation
collections: Optional list of tf.GraphKeys. The collections to add the
summary to. Defaults to [tf.GraphKeys.SUMMARIES]
family: Optional; if provided, used as the prefix of the summary tag name,
which controls the tab name used for display on Tensorboard.
Returns:
A scalar `Tensor` of type `string`. The serialized `Summary` protocol
buffer.
Raises:
ValueError: if the given tensor has the wrong shape.
"""
tensor = tf.convert_to_tensor(tensor)
if len(tensor.get_shape()) != 5:
raise ValueError("Assuming videos given as tensors in the format "
"[batch, time, height, width, channels] but got one "
"of shape: %s" % str(tensor.get_shape()))
tensor = tf.cast(tensor, tf.uint8)
if distribute_summary_op_util.skip_summary():
return tf.constant("")
with summary_op_util.summary_scope(
name, family, values=[tensor]) as (tag, scope):
val = tf.py_func(
py_gif_summary,
[tag, tensor, max_outputs, fps],
tf.string,
stateful=False,
name=scope)
summary_op_util.collect(val, collections, [tf.GraphKeys.SUMMARIES])
return val
|
python
|
def gif_summary(name, tensor, max_outputs=3, fps=10, collections=None,
family=None):
"""Outputs a `Summary` protocol buffer with gif animations.
Args:
name: Name of the summary.
tensor: A 5-D `uint8` `Tensor` of shape `[batch_size, time, height, width,
channels]` where `channels` is 1 or 3.
max_outputs: Max number of batch elements to generate gifs for.
fps: frames per second of the animation
collections: Optional list of tf.GraphKeys. The collections to add the
summary to. Defaults to [tf.GraphKeys.SUMMARIES]
family: Optional; if provided, used as the prefix of the summary tag name,
which controls the tab name used for display on Tensorboard.
Returns:
A scalar `Tensor` of type `string`. The serialized `Summary` protocol
buffer.
Raises:
ValueError: if the given tensor has the wrong shape.
"""
tensor = tf.convert_to_tensor(tensor)
if len(tensor.get_shape()) != 5:
raise ValueError("Assuming videos given as tensors in the format "
"[batch, time, height, width, channels] but got one "
"of shape: %s" % str(tensor.get_shape()))
tensor = tf.cast(tensor, tf.uint8)
if distribute_summary_op_util.skip_summary():
return tf.constant("")
with summary_op_util.summary_scope(
name, family, values=[tensor]) as (tag, scope):
val = tf.py_func(
py_gif_summary,
[tag, tensor, max_outputs, fps],
tf.string,
stateful=False,
name=scope)
summary_op_util.collect(val, collections, [tf.GraphKeys.SUMMARIES])
return val
|
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"SUMMARIES",
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] |
Outputs a `Summary` protocol buffer with gif animations.
Args:
name: Name of the summary.
tensor: A 5-D `uint8` `Tensor` of shape `[batch_size, time, height, width,
channels]` where `channels` is 1 or 3.
max_outputs: Max number of batch elements to generate gifs for.
fps: frames per second of the animation
collections: Optional list of tf.GraphKeys. The collections to add the
summary to. Defaults to [tf.GraphKeys.SUMMARIES]
family: Optional; if provided, used as the prefix of the summary tag name,
which controls the tab name used for display on Tensorboard.
Returns:
A scalar `Tensor` of type `string`. The serialized `Summary` protocol
buffer.
Raises:
ValueError: if the given tensor has the wrong shape.
|
[
"Outputs",
"a",
"Summary",
"protocol",
"buffer",
"with",
"gif",
"animations",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L458-L497
|
train
|
Outputs a Summary protocol buffer with gif animations.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101011 + 0o4) + '\063' + chr(0b11 + 0o61) + '\x33', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b110000 + 0o77) + '\x33' + chr(0b110011) + chr(0b10010 + 0o41), 0o10), ehT0Px3KOsy9(chr(2171 - 2123) + chr(0b100011 + 0o114) + '\063' + chr(0b110010) + '\x34', 0o10), ehT0Px3KOsy9('\060' + chr(0b1011 + 0o144) + chr(1575 - 1520) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(5460 - 5349) + chr(49) + chr(0b110101) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(0b101111 + 0o100) + chr(240 - 189) + chr(2216 - 2162), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(49) + chr(0b110100), 16494 - 16486), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2355 - 2302) + chr(53), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1011 + 0o144) + chr(0b110010) + chr(584 - 534) + '\x37', 22465 - 22457), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101000 + 0o7) + chr(1952 - 1903) + chr(53) + chr(475 - 426), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11110 + 0o23) + chr(0b110100) + '\061', 34853 - 34845), ehT0Px3KOsy9('\x30' + '\157' + chr(1123 - 1072) + '\x33' + chr(2430 - 2380), 20930 - 20922), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + chr(51) + chr(1558 - 1509), 0o10), ehT0Px3KOsy9('\060' + chr(0b1010101 + 0o32) + chr(0b10000 + 0o42) + chr(1409 - 1356) + chr(2161 - 2108), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + chr(0b110110) + chr(0b11000 + 0o30), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(54) + '\060', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1011 + 0o46) + chr(49) + chr(0b100 + 0o56), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1405 - 1355) + '\065' + '\x31', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001) + chr(0b1100 + 0o45), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(2068 - 2017) + '\061' + chr(370 - 320), ord("\x08")), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1101111) + chr(2037 - 1988) + chr(55) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + chr(0b10100 + 0o37) + '\x34', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1001011 + 0o44) + '\x33' + chr(381 - 327) + '\062', 52368 - 52360), ehT0Px3KOsy9(chr(1473 - 1425) + chr(11123 - 11012) + chr(769 - 720) + '\x32' + chr(0b110000), 54473 - 54465), ehT0Px3KOsy9(chr(1361 - 1313) + chr(8801 - 8690) + chr(0b11 + 0o56) + chr(596 - 548) + chr(55), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(53) + chr(51), 8), ehT0Px3KOsy9(chr(48) + chr(2748 - 2637) + '\x31' + '\061' + chr(0b110100), 21078 - 21070), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2215 - 2164) + chr(51) + chr(0b101 + 0o54), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + '\064' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(523 - 475) + chr(111) + chr(0b110010) + '\x30' + chr(2129 - 2081), 0o10), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b1100000 + 0o17) + chr(50) + '\066' + '\x34', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1001001 + 0o46) + '\x31' + '\x32' + chr(0b110110), 557 - 549), ehT0Px3KOsy9(chr(48) + chr(0b1001000 + 0o47) + chr(49) + '\x30' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(1969 - 1921) + chr(0b110111 + 0o70) + chr(0b110011) + '\x30' + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b10000 + 0o137) + chr(0b10110 + 0o33) + chr(0b10011 + 0o35) + '\065', 8437 - 8429), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b1 + 0o60) + chr(52) + chr(0b0 + 0o65), ord("\x08")), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(111) + chr(0b110011) + chr(0b110100 + 0o1), 15075 - 15067), ehT0Px3KOsy9(chr(863 - 815) + chr(0b1000100 + 0o53) + '\x32' + chr(0b110100) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(111) + '\x33' + chr(0b110110) + '\x31', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(3062 - 2951) + chr(1646 - 1593) + chr(0b110000), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'/'), '\x64' + chr(0b1100101) + chr(0b1100011) + chr(0b1101 + 0o142) + chr(0b1100100) + chr(7944 - 7843))(chr(0b1110101) + '\164' + '\x66' + chr(0b111 + 0o46) + chr(0b101110 + 0o12)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def y7fKhR9Mn11D(AIvJRzLdDfgF, LK3cpXJU3UM0, i7r136MIYrlH=ehT0Px3KOsy9(chr(48) + '\x6f' + '\063', 0b1000), ToH1dgLAm5iP=ehT0Px3KOsy9(chr(0b110000) + chr(8048 - 7937) + chr(49) + chr(0b110010), 0b1000), FGhnnwoh1Dd8=None, KAP4PedPabnA=None):
LK3cpXJU3UM0 = IDJ2eXGCBCDu.convert_to_tensor(LK3cpXJU3UM0)
if c2A0yzQpDQB3(xafqLlk3kkUe(LK3cpXJU3UM0, xafqLlk3kkUe(SXOLrMavuUCe(b'f\x86\xaf\x8bI\x03\x7f|H'), chr(100) + '\x65' + chr(0b1100000 + 0o3) + chr(0b100010 + 0o115) + '\144' + chr(2144 - 2043))('\x75' + '\164' + chr(0b1100110) + '\055' + '\x38'))()) != ehT0Px3KOsy9(chr(0b110000) + chr(0b10111 + 0o130) + chr(0b110101), ord("\x08")):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'@\x90\xa8\xa1W\x02pk\r\xe1\x00\x05\xbf6\xde\x90W#\xdfl\xa4Z=\x81p3\x0e"\xaa\xcf\xf2\xc7v-\xa9e\x11u\xc3\xd1g\x8c\xa9\xb9[\x1f>WO\xf6\x1d\x02\xb2u\x8d\xc4Y\'\xcc%\xea\x129\x9b7/\x1f`\xf9\xd7\xe9\xd0",\xebe\x06u\xc7\x9fo\x86\xb7\xa7gK|yY\xb7\x0e\x0e\xaey\xc2\xdeUj\xc6o\xea\t4\x93 "Ql\xfc\xd3'), chr(0b101 + 0o137) + '\x65' + '\x63' + chr(0b1010011 + 0o34) + chr(100) + chr(0b1100101))(chr(117) + chr(0b10011 + 0o141) + chr(1343 - 1241) + chr(943 - 898) + '\070') % M8_cKLkHVB2V(xafqLlk3kkUe(LK3cpXJU3UM0, xafqLlk3kkUe(SXOLrMavuUCe(b'f\x86\xaf\x8bI\x03\x7f|H'), chr(100) + chr(0b110 + 0o137) + chr(5025 - 4926) + '\x6f' + chr(0b1100100) + chr(0b101001 + 0o74))(chr(117) + chr(0b1110100) + chr(0b110011 + 0o63) + chr(1907 - 1862) + '\070'))()))
LK3cpXJU3UM0 = IDJ2eXGCBCDu.cast(LK3cpXJU3UM0, IDJ2eXGCBCDu.uint8)
if xafqLlk3kkUe(kafK5R_kcXqM, xafqLlk3kkUe(SXOLrMavuUCe(b'r\x88\xb2\xa4e\x18ka@\xf6\x1b\x18'), chr(0b1100100) + chr(1612 - 1511) + '\143' + chr(111) + chr(0b1100100) + '\145')(chr(1807 - 1690) + chr(0b1000001 + 0o63) + chr(0b1100110) + '\055' + chr(1134 - 1078)))():
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'b\x8c\xb5\xa7N\npx'), '\x64' + '\x65' + '\x63' + chr(0b101010 + 0o105) + chr(0b1100100 + 0o0) + chr(0b1100101))('\165' + '\164' + chr(0b1100000 + 0o6) + chr(0b101101) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b''), '\144' + chr(101) + chr(0b10000 + 0o123) + chr(0b11010 + 0o125) + chr(0b1011000 + 0o14) + '\145')(chr(0b1110101) + chr(116) + chr(0b10100 + 0o122) + chr(893 - 848) + '\x38'))
with xafqLlk3kkUe(y9EBrLtzODcF, xafqLlk3kkUe(SXOLrMavuUCe(b'r\x96\xb6\xb9[\x19gS^\xf4\x06\x11\xbf'), '\144' + '\x65' + chr(99) + '\x6f' + '\x64' + chr(0b101011 + 0o72))(chr(117) + chr(0b1100101 + 0o17) + '\146' + chr(0b101101) + '\x38'))(AIvJRzLdDfgF, KAP4PedPabnA, values=[LK3cpXJU3UM0]) as (CPdEsc5O1sf7, CJBHNoj4zKoT):
pQxH2D_k9sXQ = IDJ2eXGCBCDu.py_func(xhFjw0K_I8fl, [CPdEsc5O1sf7, LK3cpXJU3UM0, i7r136MIYrlH, ToH1dgLAm5iP], IDJ2eXGCBCDu.string, stateful=ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b10000 + 0o40), ord("\x08")), name=CJBHNoj4zKoT)
xafqLlk3kkUe(y9EBrLtzODcF, xafqLlk3kkUe(SXOLrMavuUCe(b'b\x8c\xb7\xb8_\x08j'), chr(1650 - 1550) + chr(0b1100101) + chr(6491 - 6392) + '\157' + chr(8694 - 8594) + '\x65')('\x75' + chr(0b10111 + 0o135) + chr(0b1100110) + '\x2d' + '\070'))(pQxH2D_k9sXQ, FGhnnwoh1Dd8, [xafqLlk3kkUe(IDJ2eXGCBCDu.GraphKeys, xafqLlk3kkUe(SXOLrMavuUCe(b'R\xb6\x96\x99{9WI~'), '\144' + chr(8681 - 8580) + '\x63' + '\x6f' + chr(100) + '\x65')('\165' + chr(116) + chr(0b1100110) + chr(0b101101) + chr(767 - 711)))])
return pQxH2D_k9sXQ
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
conv_latent_tower
|
def conv_latent_tower(images, time_axis, latent_channels=1, min_logvar=-5,
is_training=False, random_latent=False,
tiny_mode=False, small_mode=False):
"""Builds convolutional latent tower for stochastic model.
At training time this tower generates a latent distribution (mean and std)
conditioned on the entire video. This latent variable will be fed to the
main tower as an extra variable to be used for future frames prediction.
At inference time, the tower is disabled and only returns latents sampled
from N(0,1).
If the multi_latent flag is on, a different latent for every timestep would
be generated.
Args:
images: tensor of ground truth image sequences
time_axis: the time axis in images tensor
latent_channels: number of latent channels
min_logvar: minimum value for log_var
is_training: whether or not it is training mode
random_latent: whether or not generate random latents
tiny_mode: whether or not it is tiny_mode. tiny_mode sets the number
of conv channels to 1 at each layer. useful for testing the
integration tests.
small_mode: whether or not it is small_mode. small mode is the same model
with less conv and lstm layers and also lower number of channels.
suitable for videos with less complexity and testing.
Returns:
latent_mean: predicted latent mean
latent_logvar: predicted latent log variance
"""
conv_size = tinyify([32, 64, 64], tiny_mode, small_mode)
with tf.variable_scope("latent", reuse=tf.AUTO_REUSE):
images = tf.to_float(images)
images = tf.unstack(images, axis=time_axis)
images = tf.concat(images, axis=3)
x = images
x = common_layers.make_even_size(x)
x = tfl.conv2d(x, conv_size[0], [3, 3], strides=(2, 2),
padding="SAME", activation=tf.nn.relu, name="latent_conv1")
x = tfcl.layer_norm(x)
if not small_mode:
x = tfl.conv2d(x, conv_size[1], [3, 3], strides=(2, 2),
padding="SAME", activation=tf.nn.relu, name="latent_conv2")
x = tfcl.layer_norm(x)
x = tfl.conv2d(x, conv_size[2], [3, 3], strides=(1, 1),
padding="SAME", activation=tf.nn.relu, name="latent_conv3")
x = tfcl.layer_norm(x)
nc = latent_channels
mean = tfl.conv2d(x, nc, [3, 3], strides=(2, 2),
padding="SAME", activation=None, name="latent_mean")
logv = tfl.conv2d(x, nc, [3, 3], strides=(2, 2),
padding="SAME", activation=tf.nn.relu, name="latent_std")
logvar = logv + min_logvar
# No latent tower at inference time, just standard gaussian.
if not is_training:
return tf.zeros_like(mean), tf.zeros_like(logvar)
# No latent in the first phase
ret_mean, ret_logvar = tf.cond(
random_latent,
lambda: (tf.zeros_like(mean), tf.zeros_like(logvar)),
lambda: (mean, logvar))
return ret_mean, ret_logvar
|
python
|
def conv_latent_tower(images, time_axis, latent_channels=1, min_logvar=-5,
is_training=False, random_latent=False,
tiny_mode=False, small_mode=False):
"""Builds convolutional latent tower for stochastic model.
At training time this tower generates a latent distribution (mean and std)
conditioned on the entire video. This latent variable will be fed to the
main tower as an extra variable to be used for future frames prediction.
At inference time, the tower is disabled and only returns latents sampled
from N(0,1).
If the multi_latent flag is on, a different latent for every timestep would
be generated.
Args:
images: tensor of ground truth image sequences
time_axis: the time axis in images tensor
latent_channels: number of latent channels
min_logvar: minimum value for log_var
is_training: whether or not it is training mode
random_latent: whether or not generate random latents
tiny_mode: whether or not it is tiny_mode. tiny_mode sets the number
of conv channels to 1 at each layer. useful for testing the
integration tests.
small_mode: whether or not it is small_mode. small mode is the same model
with less conv and lstm layers and also lower number of channels.
suitable for videos with less complexity and testing.
Returns:
latent_mean: predicted latent mean
latent_logvar: predicted latent log variance
"""
conv_size = tinyify([32, 64, 64], tiny_mode, small_mode)
with tf.variable_scope("latent", reuse=tf.AUTO_REUSE):
images = tf.to_float(images)
images = tf.unstack(images, axis=time_axis)
images = tf.concat(images, axis=3)
x = images
x = common_layers.make_even_size(x)
x = tfl.conv2d(x, conv_size[0], [3, 3], strides=(2, 2),
padding="SAME", activation=tf.nn.relu, name="latent_conv1")
x = tfcl.layer_norm(x)
if not small_mode:
x = tfl.conv2d(x, conv_size[1], [3, 3], strides=(2, 2),
padding="SAME", activation=tf.nn.relu, name="latent_conv2")
x = tfcl.layer_norm(x)
x = tfl.conv2d(x, conv_size[2], [3, 3], strides=(1, 1),
padding="SAME", activation=tf.nn.relu, name="latent_conv3")
x = tfcl.layer_norm(x)
nc = latent_channels
mean = tfl.conv2d(x, nc, [3, 3], strides=(2, 2),
padding="SAME", activation=None, name="latent_mean")
logv = tfl.conv2d(x, nc, [3, 3], strides=(2, 2),
padding="SAME", activation=tf.nn.relu, name="latent_std")
logvar = logv + min_logvar
# No latent tower at inference time, just standard gaussian.
if not is_training:
return tf.zeros_like(mean), tf.zeros_like(logvar)
# No latent in the first phase
ret_mean, ret_logvar = tf.cond(
random_latent,
lambda: (tf.zeros_like(mean), tf.zeros_like(logvar)),
lambda: (mean, logvar))
return ret_mean, ret_logvar
|
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Builds convolutional latent tower for stochastic model.
At training time this tower generates a latent distribution (mean and std)
conditioned on the entire video. This latent variable will be fed to the
main tower as an extra variable to be used for future frames prediction.
At inference time, the tower is disabled and only returns latents sampled
from N(0,1).
If the multi_latent flag is on, a different latent for every timestep would
be generated.
Args:
images: tensor of ground truth image sequences
time_axis: the time axis in images tensor
latent_channels: number of latent channels
min_logvar: minimum value for log_var
is_training: whether or not it is training mode
random_latent: whether or not generate random latents
tiny_mode: whether or not it is tiny_mode. tiny_mode sets the number
of conv channels to 1 at each layer. useful for testing the
integration tests.
small_mode: whether or not it is small_mode. small mode is the same model
with less conv and lstm layers and also lower number of channels.
suitable for videos with less complexity and testing.
Returns:
latent_mean: predicted latent mean
latent_logvar: predicted latent log variance
|
[
"Builds",
"convolutional",
"latent",
"tower",
"for",
"stochastic",
"model",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L516-L582
|
train
|
Builds a convolutional latent tower for stochastic model.
|
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(1108 - 1060) + '\157' + '\063' + chr(53) + '\064', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110010) + '\x33' + chr(1919 - 1867), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(49) + chr(0b110001 + 0o0) + '\x36', 0o10), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(111) + '\063' + chr(0b101011 + 0o7), 0b1000), ehT0Px3KOsy9('\060' + chr(3145 - 3034) + chr(0b110111) + chr(0b110111), 6271 - 6263), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(0b10011 + 0o35) + chr(53), 56758 - 56750), ehT0Px3KOsy9(chr(0b110000) + chr(4045 - 3934) + '\061' + chr(53) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + chr(0b10001 + 0o43) + chr(0b110010), 60836 - 60828), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110100) + '\x33', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\065', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\062' + '\x31' + chr(48), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b111000 + 0o67) + '\061' + chr(0b110100) + chr(0b11100 + 0o31), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + chr(2669 - 2615) + chr(218 - 168), 50945 - 50937), ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\157' + '\x31' + '\x33', 22928 - 22920), ehT0Px3KOsy9(chr(484 - 436) + chr(5084 - 4973) + chr(0b11000 + 0o31) + '\x33' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(0b1011111 + 0o20) + chr(0b11001 + 0o31) + chr(52) + chr(0b110011), 62431 - 62423), ehT0Px3KOsy9('\060' + '\157' + '\066' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1000000 + 0o57) + chr(55) + chr(925 - 873), 64140 - 64132), ehT0Px3KOsy9(chr(1313 - 1265) + chr(0b1101111) + chr(49) + chr(0b110011), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b1100 + 0o52) + '\x30', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1581 - 1531) + '\064' + chr(2157 - 2104), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b10000 + 0o47) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(814 - 766) + chr(0b1011110 + 0o21) + chr(1423 - 1373) + '\064' + chr(0b110110), 35274 - 35266), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32' + '\x34' + chr(0b101100 + 0o6), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b101011 + 0o12) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(738 - 687) + '\x31' + chr(0b110001), 40497 - 40489), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(0b110100) + chr(0b110 + 0o56), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(11454 - 11343) + '\063' + chr(54) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(2156 - 2045) + chr(50) + chr(2085 - 2035) + '\065', 60581 - 60573), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b101100 + 0o5) + chr(0b101100 + 0o5) + chr(0b100111 + 0o12), 0o10), ehT0Px3KOsy9(chr(48) + chr(9188 - 9077) + chr(156 - 106) + '\x36' + chr(287 - 237), 55356 - 55348), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(5032 - 4921) + chr(0b0 + 0o62) + chr(0b110011) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + chr(51) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(0b110100), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063' + '\066' + '\x32', 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1675 - 1624) + '\x35' + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b100100 + 0o15) + chr(0b100101 + 0o15), 45506 - 45498), ehT0Px3KOsy9(chr(459 - 411) + chr(0b100110 + 0o111) + chr(1403 - 1354) + chr(49) + chr(50), 62449 - 62441), ehT0Px3KOsy9(chr(1770 - 1722) + '\157' + chr(0b10100 + 0o41) + chr(54), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101010 + 0o5) + '\x32' + '\065' + chr(2502 - 2450), 29471 - 29463)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\157' + '\065' + '\060', 3349 - 3341)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xc2'), '\x64' + chr(101) + chr(0b101100 + 0o67) + chr(711 - 600) + chr(0b1100011 + 0o1) + chr(0b1011110 + 0o7))('\165' + chr(0b0 + 0o164) + '\x66' + chr(0b101101) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Q9e3kcLqK9yN(YJOmEcibG8C0, YWTp_1OQiOr_, nKweRlOAw0tE=ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49), 21471 - 21463), ncKTjfnUB7nm=-ehT0Px3KOsy9(chr(1444 - 1396) + '\157' + chr(0b101101 + 0o10), 8), XQJVi3cQFN5l=ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(167 - 56) + '\x30', 0o10), gpSwFbaP3PtG=ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(111) + chr(0b110000), 8), kB3gdA9MY2jm=ehT0Px3KOsy9('\060' + '\x6f' + chr(525 - 477), 8), Wz3kvzGxIPZB=ehT0Px3KOsy9(chr(854 - 806) + chr(9363 - 9252) + chr(0b11110 + 0o22), 8)):
aPuZymafZqX7 = z80SymjyBoMQ([ehT0Px3KOsy9('\060' + chr(0b110111 + 0o70) + '\x34' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(11215 - 11104) + '\061' + '\060' + chr(1720 - 1672), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(48) + chr(0b10100 + 0o34), 8)], kB3gdA9MY2jm, Wz3kvzGxIPZB)
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9a\xfd<s^\xe7\x07\x87|v\xeb\n\x82n'), chr(0b1100100) + chr(6586 - 6485) + '\143' + chr(3967 - 3856) + '\144' + '\145')(chr(117) + '\x74' + chr(6206 - 6104) + '\055' + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x80\xfd:\x7fQ\xf1'), '\x64' + chr(0b1100101) + chr(0b1100011) + chr(0b1101111) + '\x64' + chr(0b1100101))(chr(0b1110101) + chr(0b1000 + 0o154) + chr(0b111111 + 0o47) + chr(1332 - 1287) + chr(0b111000)), reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xad\xc9\x1aU`\xd7.\xb7p@'), chr(0b1100100) + chr(101) + chr(0b1100000 + 0o3) + chr(6953 - 6842) + '\x64' + '\x65')('\x75' + '\164' + chr(0b1100110) + chr(833 - 788) + chr(0b1100 + 0o54)))):
YJOmEcibG8C0 = IDJ2eXGCBCDu.to_float(YJOmEcibG8C0)
YJOmEcibG8C0 = IDJ2eXGCBCDu.unstack(YJOmEcibG8C0, axis=YWTp_1OQiOr_)
YJOmEcibG8C0 = IDJ2eXGCBCDu.concat(YJOmEcibG8C0, axis=ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51), 16874 - 16866))
OeWW0F1dBPRQ = YJOmEcibG8C0
OeWW0F1dBPRQ = jSKPaHwSAfVv.make_even_size(OeWW0F1dBPRQ)
OeWW0F1dBPRQ = uWOby3XrTzFz.conv2d(OeWW0F1dBPRQ, aPuZymafZqX7[ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(0b1010000 + 0o37) + chr(512 - 464), 8)], [ehT0Px3KOsy9(chr(1439 - 1391) + chr(111) + chr(0b10101 + 0o36), 8), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33', 8)], strides=(ehT0Px3KOsy9('\060' + chr(0b111111 + 0o60) + chr(50), 0o10), ehT0Px3KOsy9('\x30' + chr(1276 - 1165) + chr(50), 8)), padding=xafqLlk3kkUe(SXOLrMavuUCe(b'\xbf\xdd\x03_'), chr(635 - 535) + chr(0b1100101) + chr(0b1100011) + '\x6f' + '\x64' + '\145')(chr(7573 - 7456) + chr(116) + chr(102) + chr(0b11101 + 0o20) + '\x38'), activation=IDJ2eXGCBCDu.nn.relu, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x80\xfd:\x7fQ\xf14\x81Lk\xfeT'), chr(100) + chr(0b1010111 + 0o16) + chr(0b1100011) + '\x6f' + chr(8865 - 8765) + chr(0b1011011 + 0o12))(chr(0b1010100 + 0o41) + '\164' + chr(102) + chr(45) + chr(0b111000)))
OeWW0F1dBPRQ = ev3q2izvoZUr.layer_norm(OeWW0F1dBPRQ)
if not Wz3kvzGxIPZB:
OeWW0F1dBPRQ = uWOby3XrTzFz.conv2d(OeWW0F1dBPRQ, aPuZymafZqX7[ehT0Px3KOsy9('\x30' + chr(111) + '\061', 8)], [ehT0Px3KOsy9(chr(0b110000) + chr(0b100010 + 0o115) + '\x33', 8), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + chr(0b1110 + 0o45), 8)], strides=(ehT0Px3KOsy9('\x30' + chr(5861 - 5750) + chr(0b10001 + 0o41), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010), 8)), padding=xafqLlk3kkUe(SXOLrMavuUCe(b'\xbf\xdd\x03_'), '\x64' + chr(9832 - 9731) + chr(99) + '\x6f' + chr(0b10010 + 0o122) + chr(101))(chr(117) + chr(116) + chr(2336 - 2234) + '\055' + '\070'), activation=IDJ2eXGCBCDu.nn.relu, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x80\xfd:\x7fQ\xf14\x81Lk\xfeW'), chr(7785 - 7685) + '\x65' + chr(4596 - 4497) + chr(0b110011 + 0o74) + chr(0b100100 + 0o100) + chr(0b1100101))('\x75' + chr(0b1110100) + chr(0b1100110) + '\x2d' + chr(148 - 92)))
OeWW0F1dBPRQ = ev3q2izvoZUr.layer_norm(OeWW0F1dBPRQ)
OeWW0F1dBPRQ = uWOby3XrTzFz.conv2d(OeWW0F1dBPRQ, aPuZymafZqX7[ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(0b1101111) + chr(1838 - 1788), 8)], [ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b11100 + 0o27), 8), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110011), 8)], strides=(ehT0Px3KOsy9('\060' + '\157' + chr(265 - 216), 8), ehT0Px3KOsy9(chr(1305 - 1257) + chr(0b1101111) + '\x31', 8)), padding=xafqLlk3kkUe(SXOLrMavuUCe(b'\xbf\xdd\x03_'), '\144' + chr(0b111111 + 0o46) + '\x63' + chr(9577 - 9466) + '\x64' + chr(101))(chr(0b1001 + 0o154) + '\x74' + chr(0b1100110) + chr(1609 - 1564) + chr(0b11100 + 0o34)), activation=IDJ2eXGCBCDu.nn.relu, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x80\xfd:\x7fQ\xf14\x81Lk\xfeV'), chr(3150 - 3050) + chr(101) + '\x63' + chr(111) + '\x64' + chr(101))(chr(10401 - 10284) + chr(0b1110100) + '\146' + '\x2d' + '\070'))
OeWW0F1dBPRQ = ev3q2izvoZUr.layer_norm(OeWW0F1dBPRQ)
hAyzt8r6DLE7 = nKweRlOAw0tE
aJhItC_Vawlw = uWOby3XrTzFz.conv2d(OeWW0F1dBPRQ, hAyzt8r6DLE7, [ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(0b11100 + 0o123) + chr(1803 - 1752), 8), ehT0Px3KOsy9(chr(48) + chr(0b1011000 + 0o27) + chr(0b100101 + 0o16), 8)], strides=(ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50), 8)), padding=xafqLlk3kkUe(SXOLrMavuUCe(b'\xbf\xdd\x03_'), chr(0b1100100) + chr(3203 - 3102) + chr(99) + '\x6f' + chr(0b1100100) + '\x65')('\x75' + chr(0b10011 + 0o141) + chr(102) + '\x2d' + chr(1857 - 1801)), activation=None, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x80\xfd:\x7fQ\xf14\x8fFd\xe6'), '\x64' + chr(101) + chr(99) + chr(111) + chr(6815 - 6715) + chr(101))(chr(0b1110101) + chr(8947 - 8831) + chr(0b1100110) + chr(708 - 663) + chr(56)))
Ey8FLY8Ign7f = uWOby3XrTzFz.conv2d(OeWW0F1dBPRQ, hAyzt8r6DLE7, [ehT0Px3KOsy9(chr(1909 - 1861) + '\157' + chr(0b110011), 8), ehT0Px3KOsy9(chr(1412 - 1364) + '\157' + chr(1968 - 1917), 8)], strides=(ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1975 - 1925), 8), ehT0Px3KOsy9(chr(48) + chr(8389 - 8278) + chr(0b110010), 8)), padding=xafqLlk3kkUe(SXOLrMavuUCe(b'\xbf\xdd\x03_'), chr(0b1 + 0o143) + '\145' + '\x63' + '\x6f' + chr(5928 - 5828) + chr(101))(chr(8201 - 8084) + '\x74' + chr(7578 - 7476) + '\x2d' + '\x38'), activation=IDJ2eXGCBCDu.nn.relu, name=xafqLlk3kkUe(SXOLrMavuUCe(b'\x80\xfd:\x7fQ\xf14\x91Wa'), chr(100) + chr(101) + chr(0b100100 + 0o77) + '\157' + '\x64' + chr(0b1011011 + 0o12))(chr(6974 - 6857) + '\x74' + '\x66' + chr(0b11 + 0o52) + chr(1034 - 978)))
OlrEeJlEyWRB = Ey8FLY8Ign7f + ncKTjfnUB7nm
if not XQJVi3cQFN5l:
return (xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x96\xf9<uL\xda\x07\x8bH`'), chr(6762 - 6662) + '\145' + '\x63' + chr(6391 - 6280) + chr(0b1100100) + chr(0b1100101))('\165' + chr(0b1110010 + 0o2) + '\146' + chr(0b101101) + chr(0b110101 + 0o3)))(aJhItC_Vawlw), xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x96\xf9<uL\xda\x07\x8bH`'), chr(0b11000 + 0o114) + chr(0b1100101) + chr(0b110110 + 0o55) + chr(1119 - 1008) + chr(0b1100100) + chr(0b1100101))('\165' + chr(9358 - 9242) + chr(4528 - 4426) + chr(0b101101) + chr(662 - 606)))(OlrEeJlEyWRB))
(CW0efoKlLmge, i9AeH4WidyAz) = IDJ2eXGCBCDu.cond(gpSwFbaP3PtG, lambda : (IDJ2eXGCBCDu.zeros_like(aJhItC_Vawlw), IDJ2eXGCBCDu.zeros_like(OlrEeJlEyWRB)), lambda : (aJhItC_Vawlw, OlrEeJlEyWRB))
return (CW0efoKlLmge, i9AeH4WidyAz)
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
beta_schedule
|
def beta_schedule(schedule, global_step, final_beta, decay_start, decay_end):
"""Get KL multiplier (beta) based on the schedule."""
if decay_start > decay_end:
raise ValueError("decay_end is smaller than decay_end.")
# Since some of the TF schedules do not support incrementing a value,
# in all of the schedules, we anneal the beta from final_beta to zero
# and then reverse it at the bottom.
if schedule == "constant":
decayed_value = 0.0
elif schedule == "linear":
decayed_value = tf.train.polynomial_decay(
learning_rate=final_beta,
global_step=global_step - decay_start,
decay_steps=decay_end - decay_start,
end_learning_rate=0.0)
elif schedule == "noisy_linear_cosine_decay":
decayed_value = tf.train.noisy_linear_cosine_decay(
learning_rate=final_beta,
global_step=global_step - decay_start,
decay_steps=decay_end - decay_start)
# TODO(mechcoder): Add log_annealing schedule.
else:
raise ValueError("Unknown beta schedule.")
increased_value = final_beta - decayed_value
increased_value = tf.maximum(0.0, increased_value)
beta = tf.case(
pred_fn_pairs={
tf.less(global_step, decay_start): lambda: 0.0,
tf.greater(global_step, decay_end): lambda: final_beta},
default=lambda: increased_value)
return beta
|
python
|
def beta_schedule(schedule, global_step, final_beta, decay_start, decay_end):
"""Get KL multiplier (beta) based on the schedule."""
if decay_start > decay_end:
raise ValueError("decay_end is smaller than decay_end.")
# Since some of the TF schedules do not support incrementing a value,
# in all of the schedules, we anneal the beta from final_beta to zero
# and then reverse it at the bottom.
if schedule == "constant":
decayed_value = 0.0
elif schedule == "linear":
decayed_value = tf.train.polynomial_decay(
learning_rate=final_beta,
global_step=global_step - decay_start,
decay_steps=decay_end - decay_start,
end_learning_rate=0.0)
elif schedule == "noisy_linear_cosine_decay":
decayed_value = tf.train.noisy_linear_cosine_decay(
learning_rate=final_beta,
global_step=global_step - decay_start,
decay_steps=decay_end - decay_start)
# TODO(mechcoder): Add log_annealing schedule.
else:
raise ValueError("Unknown beta schedule.")
increased_value = final_beta - decayed_value
increased_value = tf.maximum(0.0, increased_value)
beta = tf.case(
pred_fn_pairs={
tf.less(global_step, decay_start): lambda: 0.0,
tf.greater(global_step, decay_end): lambda: final_beta},
default=lambda: increased_value)
return beta
|
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] |
Get KL multiplier (beta) based on the schedule.
|
[
"Get",
"KL",
"multiplier",
"(",
"beta",
")",
"based",
"on",
"the",
"schedule",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L585-L618
|
train
|
Get the KL multiplier based on the schedule.
|
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(869 - 821) + chr(7558 - 7447) + chr(0b100100 + 0o17) + chr(600 - 552), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(2789 - 2678) + chr(0b101100 + 0o5) + chr(74 - 26) + chr(0b101010 + 0o6), 56331 - 56323), ehT0Px3KOsy9(chr(0b110000) + chr(11293 - 11182) + chr(0b110011) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b101001 + 0o7) + '\157' + '\x31' + chr(0b110111) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1101111) + chr(0b10010 + 0o40) + '\061' + '\062', 57519 - 57511), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + chr(0b10111 + 0o32) + '\066', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b1101111) + chr(0b110011) + chr(0b10001 + 0o42) + chr(1994 - 1945), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(10803 - 10692) + '\x33' + chr(0b110000) + '\064', 57338 - 57330), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b10110 + 0o33) + '\x30' + chr(0b11110 + 0o22), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + chr(332 - 279) + '\x32', 20722 - 20714), ehT0Px3KOsy9('\060' + chr(0b10000 + 0o137) + '\x31' + chr(50) + chr(55), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1100100 + 0o13) + '\063' + chr(0b110101) + chr(51), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011) + '\x32' + '\060', 9987 - 9979), ehT0Px3KOsy9(chr(48) + chr(0b1110 + 0o141) + '\x32' + chr(1751 - 1698) + chr(0b110110), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1100 + 0o143) + chr(0b101110 + 0o3) + chr(0b110001) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(795 - 747) + chr(0b1101111) + chr(0b110010) + chr(0b110100) + '\061', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b101011 + 0o104) + '\x33' + chr(0b1 + 0o64) + '\x34', 2830 - 2822), ehT0Px3KOsy9('\060' + '\157' + '\x31' + chr(52) + chr(54), 7845 - 7837), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + chr(53) + chr(0b101 + 0o62), 0o10), ehT0Px3KOsy9(chr(0b100000 + 0o20) + '\157' + chr(0b10000 + 0o41) + chr(0b10 + 0o61) + '\060', 48838 - 48830), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + '\063' + '\x33', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\066' + chr(0b101101 + 0o3), 36720 - 36712), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + chr(50) + chr(2365 - 2315), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\062' + '\x37' + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1339 - 1290) + chr(0b110111) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + chr(1784 - 1736) + chr(0b11010 + 0o34), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b101101 + 0o6) + chr(0b10000 + 0o44) + chr(50), 37639 - 37631), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2157 - 2104) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101111) + chr(1744 - 1694) + chr(48) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b11100 + 0o27) + '\065' + chr(851 - 796), 0o10), ehT0Px3KOsy9(chr(1486 - 1438) + chr(111) + chr(2279 - 2230) + chr(0b110001 + 0o4) + chr(55), 8), ehT0Px3KOsy9('\060' + chr(111) + '\061' + chr(0b100101 + 0o20) + chr(0b110010), 0o10), ehT0Px3KOsy9('\060' + chr(6659 - 6548) + '\x33' + chr(50) + chr(1284 - 1235), 831 - 823), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(111) + '\x33' + chr(0b101001 + 0o10) + chr(0b1111 + 0o45), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b1010 + 0o51) + chr(0b11 + 0o60) + chr(435 - 386), 8), ehT0Px3KOsy9('\x30' + chr(0b110 + 0o151) + chr(173 - 123) + chr(731 - 676) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(6803 - 6692) + chr(323 - 274) + '\x33' + chr(0b110000 + 0o3), 8), ehT0Px3KOsy9('\060' + '\157' + chr(0b110001) + chr(51) + chr(218 - 164), 52678 - 52670), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + '\062' + '\065', 59790 - 59782)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b1011 + 0o45) + '\157' + chr(53) + '\x30', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'6'), '\x64' + '\145' + '\143' + '\157' + chr(100) + '\x65')(chr(0b100110 + 0o117) + chr(0b1110100) + chr(0b1100110) + '\055' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ebHhz7WCoQGA(UAGQwjlXRoHO, tnqEWmPx71Oj, iNkjvimXOCY9, aNNED4zel0gP, BnRMil4uJBYu):
if aNNED4zel0gP > BnRMil4uJBYu:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'|%~\x1b\xf3\x11`\xb7\xa0`\xc3$\xcb\xa3\xc3+\xcd\x80\x03\x1dx/X\xf3\xd6Y\xa2\x87L\xe3\x960\x0f\xbf\xa8\xf7'), '\x64' + chr(8985 - 8884) + chr(0b1100011) + chr(0b110100 + 0o73) + '\x64' + chr(3445 - 3344))(chr(5263 - 5146) + '\x74' + '\146' + chr(45) + chr(0b10011 + 0o45)))
if UAGQwjlXRoHO == xafqLlk3kkUe(SXOLrMavuUCe(b'{/s\t\xfe/k\xad'), chr(0b1100100) + chr(5612 - 5511) + chr(9162 - 9063) + '\x6f' + chr(100) + chr(0b1100101))(chr(117) + chr(116) + chr(102) + chr(1916 - 1871) + '\x38'):
vJon3tNYFaAi = 0.0
elif UAGQwjlXRoHO == xafqLlk3kkUe(SXOLrMavuUCe(b't)s\x1f\xeb<'), '\x64' + '\145' + '\143' + '\x6f' + chr(8062 - 7962) + chr(0b1100101))(chr(0b100000 + 0o125) + chr(116) + chr(0b1100110) + chr(45) + '\070'):
vJon3tNYFaAi = IDJ2eXGCBCDu.train.polynomial_decay(learning_rate=iNkjvimXOCY9, global_step=tnqEWmPx71Oj - aNNED4zel0gP, decay_steps=BnRMil4uJBYu - aNNED4zel0gP, end_learning_rate=0.0)
elif UAGQwjlXRoHO == xafqLlk3kkUe(SXOLrMavuUCe(b'v/t\t\xf3\x11i\xb0\xaa%\xcb%\xb4\xb3\xc19\xc8\x82\x030<>S\xf3\xc1'), chr(8793 - 8693) + chr(0b1010011 + 0o22) + chr(0b1100011) + chr(0b101001 + 0o106) + chr(9487 - 9387) + chr(101))('\x75' + chr(0b111111 + 0o65) + chr(102) + chr(70 - 25) + chr(0b11001 + 0o37)):
vJon3tNYFaAi = IDJ2eXGCBCDu.train.noisy_linear_cosine_decay(learning_rate=iNkjvimXOCY9, global_step=tnqEWmPx71Oj - aNNED4zel0gP, decay_steps=BnRMil4uJBYu - aNNED4zel0gP)
else:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'M.v\x14\xe59k\xf9\xa6%\xde6\xcb\xa3\xcd"\xc4\x88\x13\x03=u'), chr(0b111110 + 0o46) + chr(0b1100101) + chr(99) + '\157' + chr(100) + chr(0b1100101))('\x75' + chr(0b1110100) + '\146' + chr(0b101101) + '\070'))
OvUEvcS4LxPG = iNkjvimXOCY9 - vJon3tNYFaAi
OvUEvcS4LxPG = IDJ2eXGCBCDu.maximum(0.0, OvUEvcS4LxPG)
FjcovgoHM1LG = IDJ2eXGCBCDu.case(pred_fn_pairs={IDJ2eXGCBCDu.less(tnqEWmPx71Oj, aNNED4zel0gP): lambda : 0.0, IDJ2eXGCBCDu.greater(tnqEWmPx71Oj, BnRMil4uJBYu): lambda : iNkjvimXOCY9}, default=lambda : OvUEvcS4LxPG)
return FjcovgoHM1LG
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
extract_random_video_patch
|
def extract_random_video_patch(videos, num_frames=-1):
"""For every video, extract a random consecutive patch of num_frames.
Args:
videos: 5-D Tensor, (NTHWC)
num_frames: Integer, if -1 then the entire video is returned.
Returns:
video_patch: 5-D Tensor, (NTHWC) with T = num_frames.
Raises:
ValueError: If num_frames is greater than the number of total frames in
the video.
"""
if num_frames == -1:
return videos
batch_size, num_total_frames, h, w, c = common_layers.shape_list(videos)
if num_total_frames < num_frames:
raise ValueError("Expected num_frames <= %d, got %d" %
(num_total_frames, num_frames))
# Randomly choose start_inds for each video.
frame_start = tf.random_uniform(
shape=(batch_size,), minval=0, maxval=num_total_frames - num_frames + 1,
dtype=tf.int32)
# [start[0], start[0] + 1, ... start[0] + num_frames - 1] + ...
# [start[batch_size-1], ... start[batch_size-1] + num_frames - 1]
range_inds = tf.expand_dims(tf.range(num_frames), axis=0)
frame_inds = range_inds + tf.expand_dims(frame_start, axis=1)
frame_inds = tf.reshape(frame_inds, [-1])
# [0]*num_frames + [1]*num_frames + ... [batch_size-1]*num_frames
batch_inds = tf.expand_dims(tf.range(batch_size), axis=1)
batch_inds = tf.tile(batch_inds, [1, num_frames])
batch_inds = tf.reshape(batch_inds, [-1])
gather_inds = tf.stack((batch_inds, frame_inds), axis=1)
video_patches = tf.gather_nd(videos, gather_inds)
return tf.reshape(video_patches, (batch_size, num_frames, h, w, c))
|
python
|
def extract_random_video_patch(videos, num_frames=-1):
"""For every video, extract a random consecutive patch of num_frames.
Args:
videos: 5-D Tensor, (NTHWC)
num_frames: Integer, if -1 then the entire video is returned.
Returns:
video_patch: 5-D Tensor, (NTHWC) with T = num_frames.
Raises:
ValueError: If num_frames is greater than the number of total frames in
the video.
"""
if num_frames == -1:
return videos
batch_size, num_total_frames, h, w, c = common_layers.shape_list(videos)
if num_total_frames < num_frames:
raise ValueError("Expected num_frames <= %d, got %d" %
(num_total_frames, num_frames))
# Randomly choose start_inds for each video.
frame_start = tf.random_uniform(
shape=(batch_size,), minval=0, maxval=num_total_frames - num_frames + 1,
dtype=tf.int32)
# [start[0], start[0] + 1, ... start[0] + num_frames - 1] + ...
# [start[batch_size-1], ... start[batch_size-1] + num_frames - 1]
range_inds = tf.expand_dims(tf.range(num_frames), axis=0)
frame_inds = range_inds + tf.expand_dims(frame_start, axis=1)
frame_inds = tf.reshape(frame_inds, [-1])
# [0]*num_frames + [1]*num_frames + ... [batch_size-1]*num_frames
batch_inds = tf.expand_dims(tf.range(batch_size), axis=1)
batch_inds = tf.tile(batch_inds, [1, num_frames])
batch_inds = tf.reshape(batch_inds, [-1])
gather_inds = tf.stack((batch_inds, frame_inds), axis=1)
video_patches = tf.gather_nd(videos, gather_inds)
return tf.reshape(video_patches, (batch_size, num_frames, h, w, c))
|
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] |
For every video, extract a random consecutive patch of num_frames.
Args:
videos: 5-D Tensor, (NTHWC)
num_frames: Integer, if -1 then the entire video is returned.
Returns:
video_patch: 5-D Tensor, (NTHWC) with T = num_frames.
Raises:
ValueError: If num_frames is greater than the number of total frames in
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|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L621-L658
|
train
|
For every video extract a random consecutive patch of num_frames.
|
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(0b101001 + 0o7) + '\x6f' + chr(50) + '\x36' + chr(337 - 287), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110010) + '\065' + chr(0b110100), 45493 - 45485), ehT0Px3KOsy9(chr(100 - 52) + chr(10027 - 9916) + chr(2145 - 2092) + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(0b111 + 0o52) + '\060', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\x36', 37332 - 37324), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(111) + chr(50) + chr(51) + chr(0b110110), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(816 - 767) + chr(2708 - 2654) + chr(0b101100 + 0o5), 0b1000), ehT0Px3KOsy9(chr(1072 - 1024) + chr(0b101 + 0o152) + chr(0b110011) + chr(52) + chr(2455 - 2404), 0b1000), ehT0Px3KOsy9(chr(895 - 847) + '\x6f' + chr(0b110011) + '\x37' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(48) + chr(3714 - 3603) + '\063' + chr(0b11110 + 0o22), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100000 + 0o21) + chr(0b110100), 43024 - 43016), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110011) + chr(198 - 149), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100011 + 0o14) + chr(52) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b10111 + 0o33) + '\062' + chr(50), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1086 - 1036) + chr(0b10001 + 0o41) + '\x37', 0b1000), ehT0Px3KOsy9(chr(1521 - 1473) + chr(12071 - 11960) + chr(0b110001) + chr(2559 - 2507) + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b111100 + 0o63) + chr(0b101111 + 0o3) + chr(0b110110) + '\x33', 34660 - 34652), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110010) + chr(0b100011 + 0o16) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(12124 - 12013) + '\x33' + '\x33' + chr(2586 - 2535), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(432 - 379) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1100010 + 0o15) + chr(0b10010 + 0o42) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1776 - 1726) + chr(53) + chr(0b110110), 26129 - 26121), ehT0Px3KOsy9(chr(862 - 814) + chr(0b1101111) + chr(53) + chr(0b100110 + 0o16), ord("\x08")), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(243 - 132) + chr(0b110010) + chr(0b110110) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(5046 - 4935) + '\x32' + chr(51) + chr(407 - 356), 45007 - 44999), ehT0Px3KOsy9('\060' + chr(0b11110 + 0o121) + '\x31' + '\062' + '\x30', 0o10), ehT0Px3KOsy9('\060' + chr(0b1000000 + 0o57) + '\061' + '\062' + chr(0b11111 + 0o24), 0o10), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1011111 + 0o20) + '\061' + chr(0b110111) + chr(48), 31382 - 31374), ehT0Px3KOsy9('\x30' + chr(0b1110 + 0o141) + '\x31' + chr(0b110101 + 0o0) + chr(0b10111 + 0o40), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(803 - 753) + chr(0b110110) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + chr(54) + '\x37', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + '\x32' + chr(0b110011), 8), ehT0Px3KOsy9(chr(414 - 366) + '\x6f' + '\x32', 0b1000), ehT0Px3KOsy9(chr(391 - 343) + chr(0b1101111) + '\x31' + chr(0b110110) + chr(52), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b10101 + 0o132) + chr(51) + '\067' + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(111) + chr(2552 - 2501) + chr(50) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\157' + chr(51) + '\x37' + chr(1567 - 1517), 8), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(2210 - 2157) + chr(2258 - 2203), 8), ehT0Px3KOsy9(chr(0b110000) + chr(3432 - 3321) + '\062' + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b1101111) + chr(51) + chr(0b110100 + 0o3) + chr(0b101111 + 0o2), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + '\x6f' + chr(2141 - 2088) + '\060', 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x9c'), '\144' + chr(0b1010100 + 0o21) + chr(6153 - 6054) + chr(111) + chr(0b1100100) + chr(2103 - 2002))(chr(13232 - 13115) + chr(116) + chr(0b110011 + 0o63) + '\055' + chr(0b100101 + 0o23)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def zVFetsYqOdNs(shWq9euYnBMw, S89Y3lISBlM4=-ehT0Px3KOsy9(chr(0b1100 + 0o44) + '\157' + '\061', 36688 - 36680)):
if S89Y3lISBlM4 == -ehT0Px3KOsy9('\x30' + chr(0b1011110 + 0o21) + chr(0b100101 + 0o14), 8):
return shWq9euYnBMw
(ix9dZyeAmUxY, L_TXuL7Uvj2p, sz4HVsFVF8nL, AOfzRywRzEXp, qzn1Ctg9WgNh) = jSKPaHwSAfVv.shape_list(shWq9euYnBMw)
if L_TXuL7Uvj2p < S89Y3lISBlM4:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\xf7\xd4X\xade\xea\x14\x87\xdavyt|\xf4\xe5\x06\xde\xef\xa8\x0e\x19\x93\x0c\x93\xff|s\x1f\x00\xc3Wvf'), chr(0b1100100) + '\x65' + chr(99) + chr(111) + chr(0b111111 + 0o45) + chr(0b1011100 + 0o11))('\165' + '\164' + chr(0b1100110) + chr(45) + chr(1903 - 1847)) % (L_TXuL7Uvj2p, S89Y3lISBlM4))
XOU8BNOLNt1A = IDJ2eXGCBCDu.random_uniform(shape=(ix9dZyeAmUxY,), minval=ehT0Px3KOsy9(chr(2108 - 2060) + chr(0b1101010 + 0o5) + chr(0b0 + 0o60), 0o10), maxval=L_TXuL7Uvj2p - S89Y3lISBlM4 + ehT0Px3KOsy9(chr(0b110000) + chr(7693 - 7582) + '\x31', 8), dtype=IDJ2eXGCBCDu.int32)
Qjh24v5nftyR = IDJ2eXGCBCDu.expand_dims(IDJ2eXGCBCDu.range(S89Y3lISBlM4), axis=ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11000 + 0o30), 8))
AEQyuNjUqpUq = Qjh24v5nftyR + IDJ2eXGCBCDu.expand_dims(XOU8BNOLNt1A, axis=ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001), 8))
AEQyuNjUqpUq = IDJ2eXGCBCDu.reshape(AEQyuNjUqpUq, [-ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(111) + chr(1495 - 1446), 8)])
avS2sJOLgPlg = IDJ2eXGCBCDu.expand_dims(IDJ2eXGCBCDu.range(ix9dZyeAmUxY), axis=ehT0Px3KOsy9('\x30' + '\157' + '\x31', 8))
avS2sJOLgPlg = IDJ2eXGCBCDu.tile(avS2sJOLgPlg, [ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(111) + '\061', 8), S89Y3lISBlM4])
avS2sJOLgPlg = IDJ2eXGCBCDu.reshape(avS2sJOLgPlg, [-ehT0Px3KOsy9('\060' + chr(0b100 + 0o153) + chr(0b10011 + 0o36), 8)])
UspWQ_6E96TU = IDJ2eXGCBCDu.stack((avS2sJOLgPlg, AEQyuNjUqpUq), axis=ehT0Px3KOsy9('\x30' + chr(9915 - 9804) + '\x31', 8))
PbVNoXH4myWe = IDJ2eXGCBCDu.gather_nd(shWq9euYnBMw, UspWQ_6E96TU)
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc0\xc9[\xa0g\xee\x14'), '\x64' + chr(3087 - 2986) + chr(0b101011 + 0o70) + chr(111) + chr(100) + chr(0b1100101))(chr(528 - 411) + chr(0b1110100) + chr(9071 - 8969) + chr(0b101101) + chr(56)))(PbVNoXH4myWe, (ix9dZyeAmUxY, S89Y3lISBlM4, sz4HVsFVF8nL, AOfzRywRzEXp, qzn1Ctg9WgNh))
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
VideoWriter.write_multi
|
def write_multi(self, frames, encoded_frames=None):
"""Writes multiple video frames."""
if encoded_frames is None:
# Infinite iterator.
encoded_frames = iter(lambda: None, 1)
for (frame, encoded_frame) in zip(frames, encoded_frames):
self.write(frame, encoded_frame)
|
python
|
def write_multi(self, frames, encoded_frames=None):
"""Writes multiple video frames."""
if encoded_frames is None:
# Infinite iterator.
encoded_frames = iter(lambda: None, 1)
for (frame, encoded_frame) in zip(frames, encoded_frames):
self.write(frame, encoded_frame)
|
[
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"write_multi",
"(",
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",",
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",",
"encoded_frames",
"=",
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",",
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")"
] |
Writes multiple video frames.
|
[
"Writes",
"multiple",
"video",
"frames",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L668-L674
|
train
|
Writes multiple video frames.
|
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(0b1000110 + 0o51) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(0b1101111) + chr(251 - 202) + '\x36' + '\067', 28720 - 28712), ehT0Px3KOsy9(chr(1254 - 1206) + chr(0b10011 + 0o134) + chr(1201 - 1152) + chr(52) + '\065', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b100000 + 0o22) + '\x33' + chr(1131 - 1082), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\066' + chr(0b1101 + 0o47), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(52), 0b1000), ehT0Px3KOsy9(chr(1804 - 1756) + chr(111) + chr(2035 - 1984) + '\x33' + '\062', 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\062' + '\x32' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + '\x34' + '\x37', 1555 - 1547), ehT0Px3KOsy9('\x30' + chr(0b1010000 + 0o37) + chr(1533 - 1484) + '\065' + chr(2481 - 2431), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(3477 - 3366) + chr(0b110001) + '\067' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(1354 - 1301) + chr(1027 - 978), 12758 - 12750), ehT0Px3KOsy9(chr(1842 - 1794) + '\x6f' + '\x31' + '\x30' + chr(0b10100 + 0o34), ord("\x08")), ehT0Px3KOsy9(chr(109 - 61) + chr(8798 - 8687) + chr(0b110011) + chr(0b110110) + '\x31', 10881 - 10873), ehT0Px3KOsy9(chr(0b101001 + 0o7) + '\x6f' + chr(0b11100 + 0o27) + chr(1318 - 1268) + '\x36', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10000 + 0o41) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b110000 + 0o77) + chr(0b110001) + chr(0b10110 + 0o34) + chr(0b10011 + 0o35), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110 + 0o55) + '\x30' + chr(2283 - 2234), ord("\x08")), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(0b1101111) + chr(0b11101 + 0o32) + '\x33', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b10000 + 0o41) + '\x33' + '\065', 14587 - 14579), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1 + 0o65) + chr(2664 - 2612), 8), ehT0Px3KOsy9('\x30' + chr(0b100100 + 0o113) + '\x33' + '\x36' + chr(1843 - 1788), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(726 - 675) + chr(0b110001) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(532 - 484) + '\x6f' + chr(230 - 181) + chr(0b110111) + '\x32', 0o10), ehT0Px3KOsy9('\060' + chr(0b10100 + 0o133) + chr(1687 - 1636) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b110110 + 0o71) + chr(51) + chr(0b110101) + chr(55), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(50) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(8116 - 8005) + '\066' + chr(0b110010), 9199 - 9191), ehT0Px3KOsy9(chr(1625 - 1577) + chr(111) + chr(0b100 + 0o56) + chr(48) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\x6f' + '\x33' + chr(0b110010) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\x6f' + chr(0b100 + 0o57) + '\x35' + chr(48), 0o10), ehT0Px3KOsy9(chr(161 - 113) + chr(111) + chr(0b100101 + 0o15) + '\061' + '\x35', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\063', 64653 - 64645), ehT0Px3KOsy9(chr(589 - 541) + chr(0b1011010 + 0o25) + chr(1788 - 1737) + chr(0b10001 + 0o44) + '\x36', 20199 - 20191), ehT0Px3KOsy9('\x30' + chr(3378 - 3267) + '\061' + chr(51), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(0b100000 + 0o27), ord("\x08")), ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\x6f' + chr(49) + chr(1840 - 1787) + '\065', 34661 - 34653), ehT0Px3KOsy9(chr(2092 - 2044) + '\x6f' + chr(0b100000 + 0o22) + chr(50) + '\x36', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(54) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(61 - 13) + chr(7252 - 7141) + chr(2640 - 2586) + chr(0b10100 + 0o42), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b101 + 0o53) + '\157' + chr(796 - 743) + chr(0b110000), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'('), chr(5207 - 5107) + chr(0b1100101) + '\143' + '\157' + chr(1790 - 1690) + '\145')(chr(3047 - 2930) + chr(0b10011 + 0o141) + chr(102) + '\055' + chr(2884 - 2828)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def fudLdrELsDhz(oVre8I6UXc3b, RlRNrq1190ue, e9AwA4HRtZpf=None):
if e9AwA4HRtZpf is None:
e9AwA4HRtZpf = ZdP978XkGspL(lambda : None, ehT0Px3KOsy9('\x30' + '\157' + chr(49), 51625 - 51617))
for (C4IqNNmLfHXB, DXtx2Xs7bZm6) in pZ0NK2y6HRbn(RlRNrq1190ue, e9AwA4HRtZpf):
xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'q\x05\x0c\xedQ'), '\x64' + '\145' + '\143' + chr(0b1100000 + 0o17) + '\x64' + '\145')('\x75' + chr(0b1000010 + 0o62) + '\x66' + '\x2d' + '\x38'))(C4IqNNmLfHXB, DXtx2Xs7bZm6)
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
WholeVideoWriter.__init_ffmpeg
|
def __init_ffmpeg(self, image_shape):
"""Initializes ffmpeg to write frames."""
import itertools # pylint: disable=g-import-not-at-top
from subprocess import Popen, PIPE # pylint: disable=g-import-not-at-top,g-multiple-import,g-importing-member
ffmpeg = "ffmpeg"
height, width, channels = image_shape
self.cmd = [
ffmpeg, "-y",
"-f", "rawvideo",
"-vcodec", "rawvideo",
"-r", "%.02f" % self.fps,
"-s", "%dx%d" % (width, height),
"-pix_fmt", {1: "gray", 3: "rgb24"}[channels],
"-i", "-",
"-filter_complex", "[0:v]split[x][z];[x]fifo[w];[z]palettegen,fifo[y];"
"[w][y]paletteuse,fifo",
"-r", "%.02f" % self.fps,
"-f", self.file_format,
"-qscale", "0",
"-"
]
self.proc = Popen(
self.cmd, stdin=PIPE, stdout=PIPE, stderr=PIPE, bufsize=-1
)
(self._out_thread, self._err_thread) = itertools.starmap(
self._start_reader_thread, [
(self.proc.stdout, self._out_chunks),
(self.proc.stderr, self._err_chunks)
]
)
|
python
|
def __init_ffmpeg(self, image_shape):
"""Initializes ffmpeg to write frames."""
import itertools # pylint: disable=g-import-not-at-top
from subprocess import Popen, PIPE # pylint: disable=g-import-not-at-top,g-multiple-import,g-importing-member
ffmpeg = "ffmpeg"
height, width, channels = image_shape
self.cmd = [
ffmpeg, "-y",
"-f", "rawvideo",
"-vcodec", "rawvideo",
"-r", "%.02f" % self.fps,
"-s", "%dx%d" % (width, height),
"-pix_fmt", {1: "gray", 3: "rgb24"}[channels],
"-i", "-",
"-filter_complex", "[0:v]split[x][z];[x]fifo[w];[z]palettegen,fifo[y];"
"[w][y]paletteuse,fifo",
"-r", "%.02f" % self.fps,
"-f", self.file_format,
"-qscale", "0",
"-"
]
self.proc = Popen(
self.cmd, stdin=PIPE, stdout=PIPE, stderr=PIPE, bufsize=-1
)
(self._out_thread, self._err_thread) = itertools.starmap(
self._start_reader_thread, [
(self.proc.stdout, self._out_chunks),
(self.proc.stderr, self._err_chunks)
]
)
|
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"]",
")"
] |
Initializes ffmpeg to write frames.
|
[
"Initializes",
"ffmpeg",
"to",
"write",
"frames",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L715-L744
|
train
|
Initializes the ffmpeg to read frames.
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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(0b101010 + 0o10) + chr(52 - 4) + chr(0b101011 + 0o10), 0o10), ehT0Px3KOsy9(chr(712 - 664) + chr(0b1101111) + chr(1860 - 1809) + chr(0b110101) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b10001 + 0o37) + '\157' + '\x34' + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061' + chr(0b100101 + 0o13) + chr(0b1001 + 0o50), 0o10), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(111) + chr(51) + '\060' + '\064', 20591 - 20583), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110100) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(805 - 756) + '\064' + '\x30', 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\x6f' + '\x31' + chr(0b100010 + 0o22) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(204 - 156) + chr(7894 - 7783) + chr(51) + '\x34' + chr(0b1100 + 0o46), ord("\x08")), ehT0Px3KOsy9(chr(458 - 410) + '\x6f' + '\x31' + chr(0b110101) + '\x33', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b111 + 0o53) + chr(0b11000 + 0o34) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + chr(0b1011 + 0o51) + chr(0b1011 + 0o47), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010110 + 0o31) + chr(0b101010 + 0o7) + chr(49) + chr(0b11110 + 0o25), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1011010 + 0o25) + '\063' + chr(49) + chr(0b1101 + 0o47), 65497 - 65489), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + chr(51) + '\x30', 38555 - 38547), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(0b100100 + 0o20) + chr(50), 0o10), ehT0Px3KOsy9(chr(1071 - 1023) + chr(10786 - 10675) + '\063' + chr(0b110011) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11101 + 0o24) + chr(0b110001) + chr(0b110011 + 0o0), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(54) + '\064', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + chr(0b100111 + 0o11) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(2682 - 2571) + chr(51) + '\x37' + '\x35', 0b1000), ehT0Px3KOsy9(chr(1132 - 1084) + '\x6f' + chr(0b1111 + 0o45) + chr(0b11011 + 0o30), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10110 + 0o34) + chr(0b100110 + 0o15) + '\061', 0b1000), ehT0Px3KOsy9(chr(2170 - 2122) + chr(2053 - 1942) + chr(50) + chr(970 - 918) + chr(1787 - 1739), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b1011 + 0o47) + chr(301 - 253) + chr(49), 0o10), ehT0Px3KOsy9(chr(0b1000 + 0o50) + '\x6f' + chr(0b0 + 0o64) + '\061', 24636 - 24628), ehT0Px3KOsy9(chr(262 - 214) + '\x6f' + chr(0b110010) + chr(1193 - 1144) + '\x36', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110100) + chr(55), 64894 - 64886), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(0b1101111) + chr(50) + chr(1179 - 1126) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2268 - 2219) + chr(658 - 608) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(678 - 630) + '\157' + '\x32' + '\x35' + '\060', 0o10), ehT0Px3KOsy9(chr(1392 - 1344) + chr(0b100010 + 0o115) + chr(0b110011) + chr(52) + chr(52), 0o10), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(5987 - 5876) + chr(2061 - 2010) + chr(93 - 40) + chr(0b101101 + 0o3), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + chr(1481 - 1430) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(2076 - 2028) + '\157' + chr(0b110010) + '\065' + chr(0b100000 + 0o26), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\061' + '\x31' + '\066', 0o10), ehT0Px3KOsy9('\x30' + chr(0b101001 + 0o106) + chr(924 - 874) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(1161 - 1113) + chr(1515 - 1404) + '\062' + chr(1154 - 1104) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100011 + 0o17) + '\060' + chr(0b110100), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(0b110101) + chr(1463 - 1411), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b101111 + 0o100) + chr(0b101111 + 0o6) + chr(0b100 + 0o54), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xad'), chr(0b11100 + 0o110) + chr(0b1100101) + chr(0b1100011) + chr(0b1 + 0o156) + chr(0b1100001 + 0o3) + chr(5477 - 5376))('\x75' + chr(0b1110100) + '\x66' + '\055' + chr(214 - 158)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def mjO1gme8csWQ(oVre8I6UXc3b, y75rm19CmWff):
(nLSuLqmR6kNP,) = (jFWsnpHpAUWz(xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\x9dC3\xb0J\x0f\x0e\x91'), '\144' + '\145' + '\143' + '\157' + chr(529 - 429) + chr(101))(chr(0b11011 + 0o132) + chr(0b1101110 + 0o6) + chr(10239 - 10137) + chr(1889 - 1844) + chr(0b111000))),)
(AwT96CkVCSSy, LbMp3lPepCj3) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\xf0\x9cD1\xb6J\x03\x07\x91\x18'), chr(0b10010 + 0o122) + '\145' + '\x63' + '\157' + chr(6101 - 6001) + '\x65')(chr(0b1100111 + 0o16) + chr(0b1110100) + chr(0b111111 + 0o47) + '\x2d' + chr(0b101 + 0o63)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xd3\x86V$\xaa'), '\144' + chr(8991 - 8890) + '\x63' + '\x6f' + chr(0b100 + 0o140) + chr(1228 - 1127))('\165' + chr(5962 - 5846) + chr(0b100 + 0o142) + '\055' + '\070')), xafqLlk3kkUe(SXOLrMavuUCe(b'\xd3\x86V$\xaa'), chr(100) + chr(101) + '\x63' + chr(0b1101111) + chr(6715 - 6615) + chr(101))(chr(7481 - 7364) + chr(116) + chr(102) + '\055' + '\070')), xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\xf0\x9cD1\xb6J\x03\x07\x91\x18'), chr(100) + chr(101) + chr(99) + chr(111) + '\144' + chr(0b11101 + 0o110))(chr(4596 - 4479) + '\x74' + '\146' + chr(0b101001 + 0o4) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xd3\xa0v\x04'), '\x64' + '\x65' + chr(0b1000001 + 0o42) + chr(111) + chr(0b11001 + 0o113) + chr(0b1100101))('\x75' + chr(116) + chr(0b1010010 + 0o24) + chr(0b1101 + 0o40) + chr(393 - 337))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xd3\xa0v\x04'), chr(0b10001 + 0o123) + '\x65' + chr(99) + '\157' + chr(1418 - 1318) + chr(0b1100101))('\165' + chr(7906 - 7790) + chr(0b1100110) + '\x2d' + chr(0b11110 + 0o32))))
QHLUao7n6Jti = xafqLlk3kkUe(SXOLrMavuUCe(b'\xe5\x8fK1\xa1B'), chr(100) + '\x65' + chr(0b111001 + 0o52) + chr(111) + '\144' + chr(0b1011111 + 0o6))('\165' + '\x74' + chr(102) + chr(0b11011 + 0o22) + chr(690 - 634))
(ehbUULKuygfC, mPx09rBTrGXR, H2MQqAZeamNo) = y75rm19CmWff
oVre8I6UXc3b.cTsjNbtiBYNK = [QHLUao7n6Jti, xafqLlk3kkUe(SXOLrMavuUCe(b'\xae\x90'), '\x64' + chr(0b1001011 + 0o32) + chr(99) + chr(2627 - 2516) + chr(0b1100100) + '\145')(chr(0b1110101) + chr(179 - 63) + chr(102) + chr(0b101101) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xae\x8f'), chr(4336 - 4236) + '\x65' + chr(0b110110 + 0o55) + chr(0b1100010 + 0o15) + '\x64' + chr(0b1100101))(chr(0b1011001 + 0o34) + chr(116) + chr(0b1101 + 0o131) + chr(0b101101) + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xf1\x88Q7\xadA\x05\r'), '\144' + chr(101) + chr(99) + chr(0b1101111) + chr(0b11 + 0o141) + '\145')('\x75' + chr(0b1110100) + '\x66' + '\055' + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xae\x9fE.\xa0@\x03'), chr(0b1011000 + 0o14) + chr(0b101011 + 0o72) + chr(0b1100011) + '\x6f' + '\144' + chr(0b1100101))(chr(0b100011 + 0o122) + chr(0b1110100) + '\x66' + chr(0b10011 + 0o32) + chr(0b11010 + 0o36)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xf1\x88Q7\xadA\x05\r'), chr(0b1100100) + chr(0b100101 + 0o100) + chr(99) + chr(0b1101111) + chr(0b100 + 0o140) + chr(0b1011010 + 0o13))('\x75' + chr(0b1010100 + 0o40) + chr(102) + chr(0b10010 + 0o33) + chr(0b110100 + 0o4)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xae\x9b'), chr(100) + chr(5594 - 5493) + chr(0b1100011) + chr(11526 - 11415) + '\x64' + chr(0b101010 + 0o73))('\165' + '\164' + chr(0b11001 + 0o115) + '\x2d' + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xa6\xc7\x16s\xa2'), chr(7378 - 7278) + '\145' + chr(99) + chr(8098 - 7987) + chr(0b1100100) + chr(0b110110 + 0o57))('\x75' + chr(0b10000 + 0o144) + '\x66' + chr(45) + '\x38') % oVre8I6UXc3b.fps, xafqLlk3kkUe(SXOLrMavuUCe(b'\xae\x9a'), chr(6647 - 6547) + chr(101) + chr(0b10111 + 0o114) + '\157' + chr(100) + chr(101))(chr(117) + chr(9067 - 8951) + '\x66' + '\055' + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xa6\x8d^d\xa0'), '\x64' + '\145' + chr(0b1101 + 0o126) + chr(3729 - 3618) + '\x64' + chr(101))(chr(10598 - 10481) + chr(0b1110100) + '\146' + chr(1368 - 1323) + chr(56)) % (mPx09rBTrGXR, ehbUULKuygfC), xafqLlk3kkUe(SXOLrMavuUCe(b'\xae\x99O9\x9bC\r\x16'), chr(0b1001100 + 0o30) + chr(101) + chr(99) + '\x6f' + chr(0b1100100) + '\x65')(chr(0b101100 + 0o111) + chr(0b1110100) + '\x66' + chr(0b11011 + 0o22) + chr(0b100001 + 0o27)), {ehT0Px3KOsy9(chr(1663 - 1615) + chr(111) + chr(49), ord("\x08")): xafqLlk3kkUe(SXOLrMavuUCe(b'\xe4\x9bG8'), chr(0b1000001 + 0o43) + chr(101) + chr(99) + chr(0b101010 + 0o105) + chr(0b1000101 + 0o37) + chr(0b1100101))(chr(0b1101111 + 0o6) + '\x74' + chr(0b1100110) + '\x2d' + chr(0b111000)), ehT0Px3KOsy9('\x30' + '\157' + chr(2424 - 2373), 0b1000): xafqLlk3kkUe(SXOLrMavuUCe(b'\xf1\x8eDs\xf0'), '\144' + chr(0b1100101) + chr(9018 - 8919) + chr(1978 - 1867) + chr(6307 - 6207) + chr(101))(chr(0b1001010 + 0o53) + '\x74' + chr(0b1111 + 0o127) + chr(480 - 435) + '\x38')}[H2MQqAZeamNo], xafqLlk3kkUe(SXOLrMavuUCe(b'\xae\x80'), '\x64' + chr(101) + chr(4613 - 4514) + chr(0b1101111) + chr(7948 - 7848) + chr(101))('\x75' + '\x74' + '\146' + chr(0b101001 + 0o4) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xae'), chr(0b1100100) + chr(101) + '\143' + '\157' + chr(0b11101 + 0o107) + chr(0b100111 + 0o76))('\165' + '\x74' + chr(0b1100110) + chr(397 - 352) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b"\xae\x8fO-\xb0@\x12=\x81\x04\xcc\x92'\xa9\xa0"), chr(0b1100100) + chr(1160 - 1059) + chr(0b1010001 + 0o22) + chr(111) + '\x64' + chr(101))(chr(0b1011001 + 0o34) + chr(1900 - 1784) + chr(9678 - 9576) + chr(0b10111 + 0o26) + '\x38'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xd8\xd9\x1c7\x99V\x10\x0e\x8b\x1f\xfa\x9a\x16\x97\xa2\xff\xe5\x10\x8c\x9a\x9bJ\xff\xcf\xdaV\xd3\x1c\xf1-\xf5\x94\x89\xf6\xcb:d\xf0\xe3\t\xed\xc5@(\xa2J;\x1b\xbfP\xfa\x95\x16\x97\xa1\xff\xae*\x98\xa2\x89W\xfc\xd5\xf2D\xa2A\xc31\xc7'), chr(0b111 + 0o135) + '\145' + '\143' + chr(0b1100111 + 0o10) + '\x64' + chr(0b1100101))(chr(117) + chr(116) + chr(0b1100110) + chr(0b101101) + chr(0b101 + 0o63)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xae\x9b'), chr(5447 - 5347) + '\145' + '\x63' + chr(0b110000 + 0o77) + chr(0b1100100) + chr(101))(chr(0b1110101) + chr(4021 - 3905) + '\146' + chr(0b101101) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xa6\xc7\x16s\xa2'), chr(100) + chr(101) + '\143' + chr(11376 - 11265) + chr(7644 - 7544) + '\145')(chr(117) + chr(116) + '\146' + chr(45) + chr(511 - 455)) % oVre8I6UXc3b.fps, xafqLlk3kkUe(SXOLrMavuUCe(b'\xae\x8f'), chr(100) + chr(0b1100101) + chr(3935 - 3836) + '\157' + chr(0b1100100) + '\x65')(chr(11251 - 11134) + chr(0b1110100) + chr(7076 - 6974) + '\x2d' + '\x38'), oVre8I6UXc3b.file_format, xafqLlk3kkUe(SXOLrMavuUCe(b'\xae\x98U"\xa5I\x05'), chr(4698 - 4598) + '\x65' + chr(99) + chr(2006 - 1895) + chr(0b1100100) + chr(1780 - 1679))(chr(0b1010011 + 0o42) + chr(12992 - 12876) + '\146' + '\x2d' + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xb3'), '\x64' + chr(101) + chr(0b1100011) + chr(111) + '\x64' + chr(5238 - 5137))(chr(117) + chr(116) + chr(102) + chr(1840 - 1795) + chr(2034 - 1978)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xae'), '\144' + '\145' + chr(99) + chr(0b1101111) + '\x64' + chr(101))(chr(0b1001000 + 0o55) + chr(0b110011 + 0o101) + chr(0b1100110) + chr(0b101101) + '\070')]
oVre8I6UXc3b.qWgorv6lsPwr = AwT96CkVCSSy(oVre8I6UXc3b.cTsjNbtiBYNK, stdin=LbMp3lPepCj3, stdout=LbMp3lPepCj3, stderr=LbMp3lPepCj3, bufsize=-ehT0Px3KOsy9(chr(1689 - 1641) + '\x6f' + '\x31', 8))
(oVre8I6UXc3b.eQ3kAhxJav7w, oVre8I6UXc3b.axhujNJ6R2Ay) = nLSuLqmR6kNP.starmap(oVre8I6UXc3b._start_reader_thread, [(oVre8I6UXc3b.proc.stdout, oVre8I6UXc3b._out_chunks), (oVre8I6UXc3b.proc.stderr, oVre8I6UXc3b._err_chunks)])
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
WholeVideoWriter._start_reader_thread
|
def _start_reader_thread(self, stream, chunks):
"""Starts a thread for reading output from FFMPEG.
The thread reads consecutive chunks from the stream and saves them in
the given list.
Args:
stream: output stream of the FFMPEG process.
chunks: list to save output chunks to.
Returns:
Thread
"""
import io # pylint: disable=g-import-not-at-top
import threading # pylint: disable=g-import-not-at-top
def target():
while True:
chunk = stream.read(io.DEFAULT_BUFFER_SIZE)
if not chunk:
break
chunks.append(chunk)
thread = threading.Thread(target=target)
thread.start()
return thread
|
python
|
def _start_reader_thread(self, stream, chunks):
"""Starts a thread for reading output from FFMPEG.
The thread reads consecutive chunks from the stream and saves them in
the given list.
Args:
stream: output stream of the FFMPEG process.
chunks: list to save output chunks to.
Returns:
Thread
"""
import io # pylint: disable=g-import-not-at-top
import threading # pylint: disable=g-import-not-at-top
def target():
while True:
chunk = stream.read(io.DEFAULT_BUFFER_SIZE)
if not chunk:
break
chunks.append(chunk)
thread = threading.Thread(target=target)
thread.start()
return thread
|
[
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",",
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":",
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"# pylint: disable=g-import-not-at-top",
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")",
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":",
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"(",
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"Thread",
"(",
"target",
"=",
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")",
"thread",
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"(",
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] |
Starts a thread for reading output from FFMPEG.
The thread reads consecutive chunks from the stream and saves them in
the given list.
Args:
stream: output stream of the FFMPEG process.
chunks: list to save output chunks to.
Returns:
Thread
|
[
"Starts",
"a",
"thread",
"for",
"reading",
"output",
"from",
"FFMPEG",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L746-L769
|
train
|
Starts a thread for reading output from the given stream.
|
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(5668 - 5557) + '\062' + chr(2377 - 2322), 0b1000), ehT0Px3KOsy9(chr(0b10000 + 0o40) + '\157' + chr(1779 - 1729) + chr(0b110110) + '\x33', 48425 - 48417), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11110 + 0o30) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + '\066' + chr(1088 - 1039), 27747 - 27739), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(2533 - 2422) + '\062' + '\x32' + chr(0b110111), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + '\066' + chr(2104 - 2050), 53246 - 53238), ehT0Px3KOsy9('\x30' + chr(9909 - 9798) + '\x30', 614 - 606), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(5194 - 5083) + '\062' + chr(0b110010) + '\064', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(3893 - 3782) + chr(318 - 268) + chr(51) + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(1892 - 1844) + chr(5941 - 5830) + chr(49) + chr(55) + '\x30', 0b1000), ehT0Px3KOsy9(chr(2219 - 2171) + '\157' + chr(0b110001) + chr(0b11010 + 0o27) + chr(2666 - 2611), ord("\x08")), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(1057 - 946) + chr(0b110110) + '\067', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b110101) + '\060', 3294 - 3286), ehT0Px3KOsy9('\060' + chr(11774 - 11663) + '\063' + '\x36' + chr(482 - 433), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1585 - 1534) + chr(0b1111 + 0o41) + chr(0b100110 + 0o14), 32172 - 32164), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b10111 + 0o130) + chr(0b110001) + chr(0b110001) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(11363 - 11252) + '\x33' + '\065' + chr(52), 11760 - 11752), ehT0Px3KOsy9(chr(48) + chr(0b110011 + 0o74) + chr(0b110100) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(769 - 721) + chr(111) + '\062' + chr(49) + chr(0b10000 + 0o44), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(49) + chr(0b101000 + 0o12) + chr(418 - 369), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110110) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110110) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\061' + chr(0b110011) + '\061', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + chr(529 - 478) + '\060', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + '\067' + '\063', 0o10), ehT0Px3KOsy9('\x30' + chr(7054 - 6943) + chr(1246 - 1196) + '\x34' + chr(53), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x34' + chr(51), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b110100 + 0o73) + '\x31' + chr(0b101 + 0o53) + chr(49), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x31' + '\x30' + chr(0b10101 + 0o37), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + '\066' + chr(471 - 419), ord("\x08")), ehT0Px3KOsy9(chr(0b10001 + 0o37) + '\x6f' + '\065', 7080 - 7072), ehT0Px3KOsy9(chr(204 - 156) + chr(0b1101111) + chr(755 - 700) + chr(842 - 787), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1001 + 0o146) + '\x33' + chr(1605 - 1555) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b101100 + 0o103) + chr(0b101110 + 0o4) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + '\064' + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(4151 - 4040) + chr(0b100111 + 0o14) + chr(0b10101 + 0o42) + chr(1612 - 1557), 13503 - 13495), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50) + '\x32' + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1101111) + '\x33' + chr(2053 - 2005) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(111) + chr(0b101011 + 0o6) + '\x31' + '\066', 43728 - 43720), ehT0Px3KOsy9('\060' + chr(111) + chr(2324 - 2273) + chr(0b110011) + '\x36', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(1503 - 1392) + chr(0b101110 + 0o7) + chr(0b110000), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'9'), chr(0b110110 + 0o56) + '\145' + chr(0b10 + 0o141) + '\x6f' + chr(0b1100100) + '\145')(chr(6127 - 6010) + '\x74' + chr(0b1001110 + 0o30) + chr(0b11010 + 0o23) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def KfGXfnk5z50v(oVre8I6UXc3b, Mj3LKRMxKCNZ, XVRfrZhsDVHr):
(Bey9a5LqdaFa,) = (jFWsnpHpAUWz(xafqLlk3kkUe(SXOLrMavuUCe(b'~\xdc'), chr(2356 - 2256) + chr(8199 - 8098) + chr(0b1100011) + chr(111) + chr(0b10110 + 0o116) + chr(101))(chr(0b1110101) + '\164' + '\146' + chr(0b101101) + '\070')),)
(mitHeYQsEXej,) = (jFWsnpHpAUWz(xafqLlk3kkUe(SXOLrMavuUCe(b'c\xdbG\x14\xf6\x92i\xfa\xfb'), chr(100) + '\145' + chr(1410 - 1311) + chr(111) + '\144' + chr(0b1100101))(chr(4162 - 4045) + chr(0b1010001 + 0o43) + chr(0b110010 + 0o64) + '\x2d' + '\070')),)
def GR1581dR5rDS():
while ehT0Px3KOsy9('\x30' + '\x6f' + chr(1839 - 1790), ord("\x08")):
qrKMvKviNzHg = Mj3LKRMxKCNZ.U6MiWrhuCi2Y(Bey9a5LqdaFa.DEFAULT_BUFFER_SIZE)
if not qrKMvKviNzHg:
break
xafqLlk3kkUe(XVRfrZhsDVHr, xafqLlk3kkUe(SXOLrMavuUCe(b'v\xc3E\x14\xf9\x92'), chr(0b1100100) + chr(0b1010010 + 0o23) + chr(0b1100011) + '\x6f' + chr(100) + chr(101))(chr(0b10001 + 0o144) + chr(6022 - 5906) + chr(102) + chr(126 - 81) + chr(0b100111 + 0o21)))(qrKMvKviNzHg)
yvpi0Ts_CAvx = mitHeYQsEXej.Thread(target=GR1581dR5rDS)
xafqLlk3kkUe(yvpi0Ts_CAvx, xafqLlk3kkUe(SXOLrMavuUCe(b'd\xc7T\x03\xe3'), chr(0b1100100) + chr(101) + chr(6413 - 6314) + '\157' + '\x64' + chr(101))(chr(0b1110101) + chr(485 - 369) + chr(0b1001110 + 0o30) + chr(894 - 849) + chr(56)))()
return yvpi0Ts_CAvx
|
tensorflow/tensor2tensor
|
tensor2tensor/layers/common_video.py
|
WholeVideoWriter.finish
|
def finish(self):
"""Finishes transconding and returns the video.
Returns:
bytes
Raises:
IOError: in case of transcoding error.
"""
if self.proc is None:
return None
self.proc.stdin.close()
for thread in (self._out_thread, self._err_thread):
thread.join()
(out, err) = [
b"".join(chunks) for chunks in (self._out_chunks, self._err_chunks)
]
self.proc.stdout.close()
self.proc.stderr.close()
if self.proc.returncode:
err = "\n".join([" ".join(self.cmd), err.decode("utf8")])
raise IOError(err)
del self.proc
self.proc = None
return out
|
python
|
def finish(self):
"""Finishes transconding and returns the video.
Returns:
bytes
Raises:
IOError: in case of transcoding error.
"""
if self.proc is None:
return None
self.proc.stdin.close()
for thread in (self._out_thread, self._err_thread):
thread.join()
(out, err) = [
b"".join(chunks) for chunks in (self._out_chunks, self._err_chunks)
]
self.proc.stdout.close()
self.proc.stderr.close()
if self.proc.returncode:
err = "\n".join([" ".join(self.cmd), err.decode("utf8")])
raise IOError(err)
del self.proc
self.proc = None
return out
|
[
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"finish",
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")",
":",
"if",
"self",
".",
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"is",
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".",
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"self",
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"=",
"None",
"return",
"out"
] |
Finishes transconding and returns the video.
Returns:
bytes
Raises:
IOError: in case of transcoding error.
|
[
"Finishes",
"transconding",
"and",
"returns",
"the",
"video",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_video.py#L776-L800
|
train
|
Finishes transconding and returns the video.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(115 - 67) + '\157' + chr(0b11000 + 0o34) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1100000 + 0o17) + chr(0b110011) + chr(0b110110) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10001 + 0o41) + chr(0b1 + 0o63) + '\x34', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + chr(0b101101 + 0o12) + chr(0b10111 + 0o32), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + chr(0b11 + 0o64) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + chr(0b110011) + '\066', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + chr(0b110111) + chr(0b110011), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1001000 + 0o47) + '\061' + '\067' + chr(2217 - 2168), 8), ehT0Px3KOsy9('\060' + chr(9546 - 9435) + chr(0b110001) + chr(0b110010) + chr(49), 0o10), ehT0Px3KOsy9(chr(2012 - 1964) + chr(0b1011000 + 0o27) + chr(1438 - 1388) + chr(634 - 586) + '\061', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b10010 + 0o135) + chr(0b110010) + '\x36' + '\x30', 15609 - 15601), ehT0Px3KOsy9('\x30' + chr(111) + '\063' + chr(78 - 26) + chr(50), 0o10), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b1101111) + '\063' + chr(0b100100 + 0o16) + chr(0b101101 + 0o5), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(653 - 601), 55691 - 55683), ehT0Px3KOsy9('\x30' + '\x6f' + chr(51) + chr(2098 - 2046) + '\x33', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(0b110101) + chr(48), 0b1000), ehT0Px3KOsy9(chr(396 - 348) + '\157' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b1101111) + chr(0b110 + 0o55) + '\060' + chr(0b10 + 0o62), ord("\x08")), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(111) + '\x31' + chr(0b111 + 0o53) + '\060', 0o10), ehT0Px3KOsy9(chr(936 - 888) + chr(0b1101111) + chr(0b110001) + chr(0b110011) + chr(51), 0o10), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(0b110110 + 0o71) + chr(53) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(0b110000) + chr(53), 40345 - 40337), ehT0Px3KOsy9(chr(0b110000) + chr(11866 - 11755) + '\064' + '\062', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(52) + '\063', 0b1000), ehT0Px3KOsy9(chr(1141 - 1093) + '\x6f' + '\x32' + '\x36' + '\060', 8), ehT0Px3KOsy9('\060' + '\157' + chr(51) + chr(0b110010) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b1101111) + '\x33' + chr(0b101001 + 0o14) + chr(0b110011), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b100111 + 0o14) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(11439 - 11328) + '\x33' + chr(0b110010) + chr(1285 - 1233), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(439 - 387) + chr(352 - 297), 8), ehT0Px3KOsy9(chr(48) + chr(0b10110 + 0o131) + '\061' + '\065' + '\063', 0b1000), ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\157' + '\x33' + '\067' + chr(811 - 757), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + chr(1117 - 1069) + '\063', 50586 - 50578), ehT0Px3KOsy9(chr(1673 - 1625) + '\157' + '\x31' + '\067' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b110 + 0o151) + chr(657 - 606) + chr(0b101111 + 0o3) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(556 - 508) + chr(0b1100001 + 0o16) + chr(0b11010 + 0o31) + chr(55) + chr(51), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110101) + '\067', 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(2153 - 2103) + chr(0b11101 + 0o32) + chr(770 - 719), ord("\x08")), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b10110 + 0o131) + '\x33' + chr(48) + chr(52), 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b11000 + 0o127) + chr(0b11011 + 0o32) + chr(0b10101 + 0o33), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\t'), '\144' + '\145' + chr(0b1100011) + chr(0b1001100 + 0o43) + chr(100) + chr(0b1100101))(chr(7437 - 7320) + chr(0b1110100) + chr(0b1100110) + '\055' + chr(0b1010 + 0o56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def qdA9wGpjb5L6(oVre8I6UXc3b):
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'VO\x95\xcb\x0b\x89h\x97\n\x01\xf6\xc2'), chr(0b1100100) + chr(0b1001011 + 0o32) + chr(3587 - 3488) + chr(111) + '\144' + '\145')(chr(0b1110101) + chr(0b11 + 0o161) + chr(102) + chr(45) + '\070')) is None:
return None
xafqLlk3kkUe(oVre8I6UXc3b.proc.stdin, xafqLlk3kkUe(SXOLrMavuUCe(b'Dt\x9d\xd7\x1c'), chr(100) + chr(4675 - 4574) + chr(6666 - 6567) + chr(0b1101111) + chr(0b1100100) + chr(5121 - 5020))('\x75' + chr(116) + chr(102) + chr(45) + '\070'))()
for yvpi0Ts_CAvx in (xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b"BI\xc1\xcf8\x97&\xb1\x18'\xb6\xc7"), chr(3000 - 2900) + chr(0b1100101) + chr(99) + '\157' + '\x64' + chr(101))(chr(8648 - 8531) + '\x74' + chr(0b1100101 + 0o1) + chr(0b101001 + 0o4) + chr(56))), xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'F`\x9a\xd1\x13\xb1\x14\xcd+c\xc0\xc9'), '\144' + '\145' + chr(0b1100011) + '\x6f' + '\144' + '\145')(chr(0b1011011 + 0o32) + chr(0b100 + 0o160) + chr(6663 - 6561) + chr(0b101101) + '\070'))):
xafqLlk3kkUe(yvpi0Ts_CAvx, xafqLlk3kkUe(SXOLrMavuUCe(b'Mw\x9b\xca'), chr(100) + '\x65' + '\x63' + '\157' + chr(2580 - 2480) + chr(101))('\165' + '\164' + '\x66' + chr(0b10110 + 0o27) + chr(1874 - 1818)))()
(UkrMp_I0RDmo, n8HlHl2rqNTp) = [SXOLrMavuUCe(b'').join(XVRfrZhsDVHr) for XVRfrZhsDVHr in (oVre8I6UXc3b._out_chunks, oVre8I6UXc3b._err_chunks)]
xafqLlk3kkUe(oVre8I6UXc3b.proc.stdout, xafqLlk3kkUe(SXOLrMavuUCe(b'Dt\x9d\xd7\x1c'), chr(100) + chr(0b11000 + 0o115) + '\143' + chr(111) + '\x64' + chr(0b1011101 + 0o10))('\x75' + '\x74' + '\146' + '\055' + chr(0b10111 + 0o41)))()
xafqLlk3kkUe(oVre8I6UXc3b.proc.stderr, xafqLlk3kkUe(SXOLrMavuUCe(b'Dt\x9d\xd7\x1c'), '\x64' + '\145' + '\143' + chr(111) + '\x64' + chr(0b10 + 0o143))('\165' + '\x74' + chr(0b1100110) + chr(0b101101) + '\x38'))()
if xafqLlk3kkUe(oVre8I6UXc3b.proc, xafqLlk3kkUe(SXOLrMavuUCe(b'U}\x86\xd1\x0b\x91=\x94\x1d4'), chr(0b101010 + 0o72) + '\x65' + chr(99) + '\157' + '\x64' + chr(101))(chr(117) + chr(116) + chr(102) + chr(0b10011 + 0o32) + chr(56))):
n8HlHl2rqNTp = xafqLlk3kkUe(SXOLrMavuUCe(b'-'), chr(0b1100100) + chr(0b1100101) + chr(0b101001 + 0o72) + chr(0b111100 + 0o63) + '\x64' + chr(5288 - 5187))(chr(9830 - 9713) + '\164' + chr(102) + chr(0b101101) + chr(2503 - 2447)).join([xafqLlk3kkUe(SXOLrMavuUCe(b'\x07'), chr(100) + chr(0b1000111 + 0o36) + chr(0b1001110 + 0o25) + '\x6f' + '\144' + chr(304 - 203))(chr(0b1000101 + 0o60) + chr(0b1010010 + 0o42) + chr(7694 - 7592) + chr(45) + '\070').join(oVre8I6UXc3b.cTsjNbtiBYNK), n8HlHl2rqNTp.decode(xafqLlk3kkUe(SXOLrMavuUCe(b'Rl\x94\x9c'), chr(9837 - 9737) + chr(0b1100101) + chr(99) + chr(0b1010010 + 0o35) + chr(7618 - 7518) + chr(101))(chr(6729 - 6612) + '\164' + chr(102) + chr(0b101101) + chr(2754 - 2698)))])
raise sR2sPcm7Zrfn(n8HlHl2rqNTp)
del xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'VO\x95\xcb\x0b\x89h\x97\n\x01\xf6\xc2'), '\x64' + '\145' + chr(0b1100011) + '\x6f' + chr(0b1100100) + '\x65')(chr(0b110111 + 0o76) + chr(9070 - 8954) + chr(0b1100110) + chr(0b11100 + 0o21) + chr(56)))
oVre8I6UXc3b.qWgorv6lsPwr = None
return UkrMp_I0RDmo
|
tensorflow/tensor2tensor
|
tensor2tensor/serving/query.py
|
validate_flags
|
def validate_flags():
"""Validates flags are set to acceptable values."""
if FLAGS.cloud_mlengine_model_name:
assert not FLAGS.server
assert not FLAGS.servable_name
else:
assert FLAGS.server
assert FLAGS.servable_name
|
python
|
def validate_flags():
"""Validates flags are set to acceptable values."""
if FLAGS.cloud_mlengine_model_name:
assert not FLAGS.server
assert not FLAGS.servable_name
else:
assert FLAGS.server
assert FLAGS.servable_name
|
[
"def",
"validate_flags",
"(",
")",
":",
"if",
"FLAGS",
".",
"cloud_mlengine_model_name",
":",
"assert",
"not",
"FLAGS",
".",
"server",
"assert",
"not",
"FLAGS",
".",
"servable_name",
"else",
":",
"assert",
"FLAGS",
".",
"server",
"assert",
"FLAGS",
".",
"servable_name"
] |
Validates flags are set to acceptable values.
|
[
"Validates",
"flags",
"are",
"set",
"to",
"acceptable",
"values",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/serving/query.py#L53-L60
|
train
|
Validates flags are set to acceptable 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('\x30' + chr(0b1101111) + '\x37' + chr(0b100110 + 0o13), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b100110 + 0o15) + chr(52) + chr(0b100110 + 0o13), 0o10), ehT0Px3KOsy9('\x30' + chr(5302 - 5191) + chr(51) + chr(54) + chr(0b101011 + 0o7), 0o10), ehT0Px3KOsy9(chr(0b1000 + 0o50) + '\157' + chr(50) + '\x33' + chr(2199 - 2147), 3529 - 3521), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(2203 - 2151) + chr(1412 - 1364), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(48) + chr(940 - 885), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b110001 + 0o76) + chr(1266 - 1215) + '\063' + '\x34', 0o10), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(0b1010110 + 0o31) + chr(1430 - 1380) + chr(1430 - 1375), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b110101 + 0o72) + chr(50) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + '\066', 0b1000), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b1101111) + chr(51) + chr(49) + chr(0b110011 + 0o0), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(50) + chr(0b100100 + 0o20), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b1 + 0o61) + chr(0b110100) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + chr(2922 - 2867) + chr(2230 - 2175), 64875 - 64867), ehT0Px3KOsy9('\x30' + chr(2720 - 2609) + '\062' + chr(53) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(611 - 563) + chr(0b1101111) + chr(0b110111 + 0o0), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(1609 - 1555) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(1495 - 1447) + chr(0b110000 + 0o77) + chr(170 - 119) + chr(0b110010) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(1260 - 1212) + chr(2030 - 1919) + '\061' + chr(48) + chr(0b100010 + 0o21), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2084 - 2035) + chr(48) + chr(0b11110 + 0o27), 0b1000), ehT0Px3KOsy9(chr(370 - 322) + chr(7617 - 7506) + '\063' + chr(51) + chr(0b110011), 61994 - 61986), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(3722 - 3611) + '\x33' + chr(0b110111), 61200 - 61192), ehT0Px3KOsy9(chr(0b10 + 0o56) + '\157' + chr(51) + chr(54) + '\063', 0b1000), ehT0Px3KOsy9(chr(48) + chr(10736 - 10625) + '\062' + chr(0b10011 + 0o43) + '\x36', 24445 - 24437), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101000 + 0o16) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b10110 + 0o32) + '\x6f' + chr(0b110001) + chr(51) + '\065', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011), 0b1000), ehT0Px3KOsy9('\x30' + chr(11057 - 10946) + chr(49) + chr(0b110000) + chr(265 - 217), 0o10), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b1101111) + '\x37' + '\x33', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + chr(0b110100) + chr(52), 51987 - 51979), ehT0Px3KOsy9(chr(1093 - 1045) + chr(111) + chr(918 - 867) + chr(53), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + chr(49) + chr(51), 8), ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\x6f' + chr(49) + chr(52) + chr(55), 0b1000), ehT0Px3KOsy9(chr(546 - 498) + chr(0b10000 + 0o137) + '\x31' + chr(0b110111) + '\067', 31383 - 31375), ehT0Px3KOsy9(chr(0b110000) + chr(1058 - 947) + chr(0b100100 + 0o16) + chr(203 - 149) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(1053 - 1005) + chr(111) + '\x33' + '\x31', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1011001 + 0o26) + '\064', 45830 - 45822), ehT0Px3KOsy9('\060' + '\157' + chr(0b11 + 0o56) + '\x32' + '\067', 31162 - 31154), ehT0Px3KOsy9(chr(0b10100 + 0o34) + '\157' + chr(0b10011 + 0o40) + chr(49) + chr(0b10100 + 0o34), 10056 - 10048), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + '\x37' + chr(54), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(111) + chr(1752 - 1699) + chr(1736 - 1688), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x17'), chr(100) + chr(101) + chr(99) + chr(10182 - 10071) + '\x64' + chr(0b101000 + 0o75))(chr(117) + chr(116) + chr(3023 - 2921) + '\x2d' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def rorYBhj9q0YL():
if xafqLlk3kkUe(vUTZFbqN0o8F, xafqLlk3kkUe(SXOLrMavuUCe(b'Z\x8d\x9d\xe9D\x18\xb1{vx\xac}\xcf\x9a\xf6j]\xb1&)\x84q\x92\xdbV'), chr(100) + chr(101) + '\x63' + '\x6f' + '\x64' + chr(101))(chr(0b1000011 + 0o62) + chr(0b1110100) + chr(6881 - 6779) + '\055' + chr(520 - 464))):
assert not xafqLlk3kkUe(vUTZFbqN0o8F, xafqLlk3kkUe(SXOLrMavuUCe(b'l\x95\xc6\xadw\x05\xbbg}`\xf9F'), chr(0b101011 + 0o71) + chr(101) + chr(0b1100011) + chr(111) + chr(0b1100100) + chr(0b1100101))(chr(11806 - 11689) + chr(0b1011111 + 0o25) + chr(0b1100110) + chr(45) + '\x38'))
assert not xafqLlk3kkUe(vUTZFbqN0o8F, xafqLlk3kkUe(SXOLrMavuUCe(b'J\x84\x80\xeaA%\xb0rLx\xaay\xc4'), '\x64' + chr(0b1010100 + 0o21) + '\143' + chr(111) + chr(0b1011001 + 0o13) + '\145')(chr(0b1101010 + 0o13) + '\x74' + chr(3155 - 3053) + chr(0b101101) + '\070'))
else:
assert xafqLlk3kkUe(vUTZFbqN0o8F, xafqLlk3kkUe(SXOLrMavuUCe(b'l\x95\xc6\xadw\x05\xbbg}`\xf9F'), chr(0b1100100) + '\145' + '\x63' + '\157' + '\x64' + '\x65')(chr(117) + chr(0b1110100) + chr(102) + chr(0b1100 + 0o41) + chr(0b110 + 0o62)))
assert xafqLlk3kkUe(vUTZFbqN0o8F, xafqLlk3kkUe(SXOLrMavuUCe(b'J\x84\x80\xeaA%\xb0rLx\xaay\xc4'), '\144' + chr(2255 - 2154) + '\143' + chr(4553 - 4442) + chr(100) + chr(1280 - 1179))(chr(5023 - 4906) + chr(10737 - 10621) + chr(0b1001010 + 0o34) + chr(45) + '\070'))
|
tensorflow/tensor2tensor
|
tensor2tensor/serving/query.py
|
make_request_fn
|
def make_request_fn():
"""Returns a request function."""
if FLAGS.cloud_mlengine_model_name:
request_fn = serving_utils.make_cloud_mlengine_request_fn(
credentials=GoogleCredentials.get_application_default(),
model_name=FLAGS.cloud_mlengine_model_name,
version=FLAGS.cloud_mlengine_model_version)
else:
request_fn = serving_utils.make_grpc_request_fn(
servable_name=FLAGS.servable_name,
server=FLAGS.server,
timeout_secs=FLAGS.timeout_secs)
return request_fn
|
python
|
def make_request_fn():
"""Returns a request function."""
if FLAGS.cloud_mlengine_model_name:
request_fn = serving_utils.make_cloud_mlengine_request_fn(
credentials=GoogleCredentials.get_application_default(),
model_name=FLAGS.cloud_mlengine_model_name,
version=FLAGS.cloud_mlengine_model_version)
else:
request_fn = serving_utils.make_grpc_request_fn(
servable_name=FLAGS.servable_name,
server=FLAGS.server,
timeout_secs=FLAGS.timeout_secs)
return request_fn
|
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] |
Returns a request function.
|
[
"Returns",
"a",
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"function",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/serving/query.py#L63-L76
|
train
|
Returns a request 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(1258 - 1210) + chr(111) + chr(50) + chr(55) + chr(2260 - 2212), 0o10), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\157' + chr(0b10111 + 0o34) + chr(48) + chr(52), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110010) + chr(440 - 390) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + chr(0b100111 + 0o11), 6852 - 6844), ehT0Px3KOsy9('\x30' + chr(11374 - 11263) + chr(0b10 + 0o57) + chr(0b11101 + 0o25) + '\065', 0o10), ehT0Px3KOsy9(chr(2102 - 2054) + chr(0b1101111) + chr(1572 - 1523) + chr(1276 - 1223) + '\061', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + chr(51) + chr(2332 - 2281), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(10645 - 10534) + '\x35' + chr(0b101000 + 0o11), ord("\x08")), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(111) + '\x37' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001) + chr(0b1011 + 0o52) + chr(50), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x36' + chr(0b1 + 0o64), 0o10), ehT0Px3KOsy9('\060' + chr(3502 - 3391) + chr(873 - 823) + '\061' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\157' + chr(0b110011) + chr(55) + '\x33', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b100001 + 0o20) + chr(0b1000 + 0o55), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(54) + chr(53), 8), ehT0Px3KOsy9(chr(48) + chr(11606 - 11495) + chr(296 - 247) + chr(54) + chr(49), 34333 - 34325), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(219 - 168) + chr(0b1 + 0o63), 0o10), ehT0Px3KOsy9('\060' + chr(1968 - 1857) + '\x34' + chr(0b100000 + 0o27), 58149 - 58141), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1434 - 1385) + '\067' + chr(0b110010), 14185 - 14177), ehT0Px3KOsy9(chr(1131 - 1083) + chr(111) + '\061' + chr(0b0 + 0o67) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1825 - 1775) + chr(2531 - 2477) + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(111) + chr(169 - 120) + chr(0b101000 + 0o16) + chr(51), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\x31' + chr(0b110000) + '\065', 0b1000), ehT0Px3KOsy9(chr(437 - 389) + chr(111) + '\062' + chr(55) + '\060', 8), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\x6f' + chr(0b10001 + 0o40) + chr(0b110011) + '\063', 0b1000), ehT0Px3KOsy9(chr(1366 - 1318) + '\x6f' + '\065' + chr(50), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\061' + chr(49) + chr(0b110100), 33386 - 33378), ehT0Px3KOsy9(chr(844 - 796) + chr(111) + chr(0b10001 + 0o41) + chr(51) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001) + '\067' + '\061', ord("\x08")), ehT0Px3KOsy9(chr(2236 - 2188) + chr(0b1001 + 0o146) + chr(2045 - 1994) + chr(361 - 308) + chr(1846 - 1797), 9597 - 9589), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1188 - 1138) + chr(513 - 460) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(553 - 505) + chr(3605 - 3494) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(111) + chr(50) + '\066' + '\x33', 0b1000), ehT0Px3KOsy9('\x30' + chr(9386 - 9275) + chr(0b100001 + 0o21) + chr(0b110001) + chr(0b0 + 0o61), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1110 + 0o141) + chr(0b11100 + 0o32) + '\x35', 8), ehT0Px3KOsy9(chr(48) + chr(0b1100000 + 0o17) + '\x33' + chr(0b11 + 0o56) + chr(0b10110 + 0o35), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b11110 + 0o25) + chr(55) + chr(0b110 + 0o61), 0o10), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(111) + chr(0b110100) + chr(2627 - 2575), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\063' + chr(0b110101) + chr(0b0 + 0o66), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(2198 - 2150) + '\157' + '\065' + chr(609 - 561), 8752 - 8744)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x96'), chr(100) + '\145' + '\x63' + '\157' + chr(0b10 + 0o142) + chr(0b1100101))('\x75' + '\164' + chr(0b11111 + 0o107) + chr(45) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def hGxDqUtuBZd9():
if xafqLlk3kkUe(vUTZFbqN0o8F, xafqLlk3kkUe(SXOLrMavuUCe(b'\xdb\xa8\xfd}16\xb6EX\x04g\\\xe7\x9eRX\x1e8B\x16!\xda\x12(\xdd'), chr(1039 - 939) + '\145' + '\x63' + chr(111) + '\x64' + '\145')(chr(117) + chr(7359 - 7243) + '\x66' + chr(45) + chr(2740 - 2684))):
zHJVBMKPML9S = Y8akUFTuWzud.make_cloud_mlengine_request_fn(credentials=F22FQ_xr6XGG.get_application_default(), model_name=vUTZFbqN0o8F.cloud_mlengine_model_name, version=vUTZFbqN0o8F.cloud_mlengine_model_version)
else:
zHJVBMKPML9S = Y8akUFTuWzud.make_grpc_request_fn(servable_name=vUTZFbqN0o8F.servable_name, server=vUTZFbqN0o8F.Ut41WBgpnv2R, timeout_secs=vUTZFbqN0o8F.timeout_secs)
return zHJVBMKPML9S
|
tensorflow/tensor2tensor
|
tensor2tensor/models/video/savp.py
|
NextFrameSavpBase.encoder
|
def encoder(self, inputs, n_layers=3):
"""Convnet that encodes inputs into mean and std of a gaussian.
Args:
inputs: 5-D Tensor, shape (batch_size, num_frames, width, height, channels)
n_layers: Number of layers.
Returns:
z_mu: Mean of the latent gaussians.
z_log_var: log(var) of the latent gaussians.
Raises:
ValueError: If inputs is not a 5-D tensor or not float32.
"""
latent_dims = self.hparams.z_dim
shape_as_list = inputs.shape.as_list()
if len(shape_as_list) != 5:
raise ValueError("Expected inputs to be a 5-D, got %d" %
len(shape_as_list))
if inputs.dtype != tf.float32:
raise ValueError("Expected dtype tf.float32, got %s" % inputs.dtype)
# Flatten (N,T,W,H,C) into (NT,W,H,C)
batch_size, _ = shape_as_list[:2]
inputs = tf.reshape(inputs, [-1] + list(inputs.shape)[2:])
n_filters = 64
rectified = None
# Applies 3 layer conv-net with padding, instance normalization
# and leaky relu as per the encoder in
# https://github.com/alexlee-gk/video_prediction
padding = [[0, 0], [1, 1], [1, 1], [0, 0]]
for i in range(n_layers):
with tf.variable_scope("layer_%d" % (i + 1)):
n_filters *= 2**i
if i:
padded = tf.pad(rectified, padding)
else:
padded = tf.pad(inputs, padding)
convolved = tf.layers.conv2d(padded, filters=n_filters, kernel_size=4,
strides=2, padding="VALID")
normalized = tf.contrib.layers.instance_norm(convolved)
rectified = tf.nn.leaky_relu(normalized, alpha=0.2)
# Mean pooling across all spatial dimensions.
pooled = tf.nn.avg_pool(
rectified, [1] + rectified.shape[1:3].as_list() + [1],
strides=[1, 1, 1, 1], padding="VALID")
squeezed = tf.squeeze(pooled, [1, 2])
# Down-project and output the mean and log of the standard deviation of
# the latents.
with tf.variable_scope("z_mu"):
z_mu = tf.layers.dense(squeezed, latent_dims)
with tf.variable_scope("z_log_sigma_sq"):
z_log_var = tf.layers.dense(squeezed, latent_dims)
z_log_var = tf.clip_by_value(z_log_var, -10, 10)
# Reshape to (batch_size X num_frames X latent_dims)
z_mu = tf.reshape(z_mu, (batch_size, -1, latent_dims))
z_log_var = tf.reshape(
z_log_var, (batch_size, -1, latent_dims))
return z_mu, z_log_var
|
python
|
def encoder(self, inputs, n_layers=3):
"""Convnet that encodes inputs into mean and std of a gaussian.
Args:
inputs: 5-D Tensor, shape (batch_size, num_frames, width, height, channels)
n_layers: Number of layers.
Returns:
z_mu: Mean of the latent gaussians.
z_log_var: log(var) of the latent gaussians.
Raises:
ValueError: If inputs is not a 5-D tensor or not float32.
"""
latent_dims = self.hparams.z_dim
shape_as_list = inputs.shape.as_list()
if len(shape_as_list) != 5:
raise ValueError("Expected inputs to be a 5-D, got %d" %
len(shape_as_list))
if inputs.dtype != tf.float32:
raise ValueError("Expected dtype tf.float32, got %s" % inputs.dtype)
# Flatten (N,T,W,H,C) into (NT,W,H,C)
batch_size, _ = shape_as_list[:2]
inputs = tf.reshape(inputs, [-1] + list(inputs.shape)[2:])
n_filters = 64
rectified = None
# Applies 3 layer conv-net with padding, instance normalization
# and leaky relu as per the encoder in
# https://github.com/alexlee-gk/video_prediction
padding = [[0, 0], [1, 1], [1, 1], [0, 0]]
for i in range(n_layers):
with tf.variable_scope("layer_%d" % (i + 1)):
n_filters *= 2**i
if i:
padded = tf.pad(rectified, padding)
else:
padded = tf.pad(inputs, padding)
convolved = tf.layers.conv2d(padded, filters=n_filters, kernel_size=4,
strides=2, padding="VALID")
normalized = tf.contrib.layers.instance_norm(convolved)
rectified = tf.nn.leaky_relu(normalized, alpha=0.2)
# Mean pooling across all spatial dimensions.
pooled = tf.nn.avg_pool(
rectified, [1] + rectified.shape[1:3].as_list() + [1],
strides=[1, 1, 1, 1], padding="VALID")
squeezed = tf.squeeze(pooled, [1, 2])
# Down-project and output the mean and log of the standard deviation of
# the latents.
with tf.variable_scope("z_mu"):
z_mu = tf.layers.dense(squeezed, latent_dims)
with tf.variable_scope("z_log_sigma_sq"):
z_log_var = tf.layers.dense(squeezed, latent_dims)
z_log_var = tf.clip_by_value(z_log_var, -10, 10)
# Reshape to (batch_size X num_frames X latent_dims)
z_mu = tf.reshape(z_mu, (batch_size, -1, latent_dims))
z_log_var = tf.reshape(
z_log_var, (batch_size, -1, latent_dims))
return z_mu, z_log_var
|
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] |
Convnet that encodes inputs into mean and std of a gaussian.
Args:
inputs: 5-D Tensor, shape (batch_size, num_frames, width, height, channels)
n_layers: Number of layers.
Returns:
z_mu: Mean of the latent gaussians.
z_log_var: log(var) of the latent gaussians.
Raises:
ValueError: If inputs is not a 5-D tensor or not float32.
|
[
"Convnet",
"that",
"encodes",
"inputs",
"into",
"mean",
"and",
"std",
"of",
"a",
"gaussian",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/video/savp.py#L42-L105
|
train
|
Convnet that encodes inputs into mean and std of a gaussian.
|
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(2112 - 2064) + chr(0b1101111) + chr(0b110001) + '\x32' + chr(52), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001) + '\x34' + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\062' + chr(0b110000) + chr(1460 - 1409), ord("\x08")), ehT0Px3KOsy9(chr(1954 - 1906) + '\157' + '\062' + chr(696 - 644) + chr(1880 - 1825), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b10111 + 0o33) + '\066' + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(4184 - 4073) + chr(0b110001) + chr(48) + chr(235 - 186), 22600 - 22592), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(0b100101 + 0o16) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(2027 - 1978) + chr(818 - 764), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(3063 - 2952) + '\061' + '\x37' + '\x35', 44174 - 44166), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001 + 0o1) + '\063' + '\060', 0b1000), ehT0Px3KOsy9(chr(1947 - 1899) + chr(0b1101111) + chr(0b110011) + chr(0b1 + 0o66), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x33' + chr(0b110011) + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110110) + chr(1317 - 1267), 53130 - 53122), ehT0Px3KOsy9(chr(1900 - 1852) + chr(0b101111 + 0o100) + chr(0b10011 + 0o40) + chr(0b110101) + chr(0b1110 + 0o45), 0o10), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b100100 + 0o113) + chr(49), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101100 + 0o3) + '\062' + '\x31' + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(669 - 618) + chr(1141 - 1093) + chr(52), 10918 - 10910), ehT0Px3KOsy9(chr(0b110000) + chr(0b11001 + 0o126) + '\x32' + chr(0b1111 + 0o43) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(111) + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011001 + 0o26) + chr(0b110010) + '\061' + '\x30', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\062' + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(295 - 184) + '\x33' + chr(55) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + chr(1941 - 1889) + '\063', 33624 - 33616), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49) + chr(0b10110 + 0o32) + chr(0b110010), 18694 - 18686), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(967 - 918) + chr(0b110000) + chr(49), 8), ehT0Px3KOsy9('\060' + '\157' + '\x31' + chr(153 - 99) + chr(51), 17433 - 17425), ehT0Px3KOsy9('\060' + chr(0b10001 + 0o136) + chr(50) + '\x32' + chr(1315 - 1261), 29811 - 29803), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + '\x33' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b101000 + 0o14) + chr(51), 0b1000), ehT0Px3KOsy9(chr(48) + chr(5512 - 5401) + '\063' + chr(0b110001) + '\061', 52165 - 52157), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1101111) + '\062' + '\x35' + chr(0b1111 + 0o45), 64511 - 64503), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11101 + 0o26) + chr(0b110000) + chr(0b110100), 8), ehT0Px3KOsy9(chr(1739 - 1691) + chr(0b111000 + 0o67) + '\x33' + chr(153 - 105) + '\064', 8), ehT0Px3KOsy9('\x30' + '\157' + '\x34' + chr(2076 - 2021), 34747 - 34739), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + chr(0b110100) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(8665 - 8554) + chr(0b110001) + chr(0b110011) + chr(0b110110), 12868 - 12860), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1500 - 1450) + '\065' + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + '\067' + chr(0b110011), 6155 - 6147), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(8572 - 8461) + chr(0b1111 + 0o44) + '\x32' + '\x32', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(694 - 641) + '\065', 44868 - 44860)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100000 + 0o20) + '\157' + chr(0b110101) + '\x30', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'z'), '\144' + chr(0b110 + 0o137) + '\143' + chr(2644 - 2533) + chr(4779 - 4679) + chr(0b1100101))(chr(117) + chr(0b1110100) + chr(0b100100 + 0o102) + '\x2d' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def hoK3K1TwFlkr(oVre8I6UXc3b, vXoupepMtCXU, NepKL85EaPyo=ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33', ord("\x08"))):
qVkmW8bKVmfm = oVre8I6UXc3b.hparams.z_dim
ZzknT_Y7LtcU = vXoupepMtCXU.shape.as_list()
if c2A0yzQpDQB3(ZzknT_Y7LtcU) != ehT0Px3KOsy9('\x30' + chr(111) + '\x35', 0o10):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\x11\x1f\xf3\xc2\xd259*]\xf1q\xa9G\x9fr\xa9\xb0\xfb"\xeav\xdc\x02bt^\xd2\xb2\x03\xae\xc3\xb0\xe4\x02\x81'), chr(0b1100100) + chr(0b1100101) + chr(0b101101 + 0o66) + '\x6f' + '\144' + chr(0b11100 + 0o111))('\x75' + chr(0b1101 + 0o147) + '\146' + '\055' + chr(2336 - 2280)) % c2A0yzQpDQB3(ZzknT_Y7LtcU))
if xafqLlk3kkUe(vXoupepMtCXU, xafqLlk3kkUe(SXOLrMavuUCe(b'>4\xd5\x9e\xf8\n2+\x10\xd0(\x92'), '\144' + chr(101) + '\143' + chr(0b1101111) + chr(8481 - 8381) + '\x65')(chr(0b1110101) + chr(0b1001 + 0o153) + chr(0b1100110) + '\055' + '\070')) != xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'2\x0b\xec\xc6\xc5rn'), chr(1407 - 1307) + chr(0b110011 + 0o62) + '\143' + chr(111) + '\x64' + chr(101))(chr(0b1100001 + 0o24) + chr(0b1011 + 0o151) + chr(102) + chr(45) + chr(0b10101 + 0o43))):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\x11\x1f\xf3\xc2\xd259*]\xfck\xa0B\x8e!\xfd\xa2\xbad\xe4|\x9d\x17qs_\xb6\xf9L\xbd\x8c\xe1\xb7'), chr(100) + '\145' + '\143' + chr(6467 - 6356) + chr(0b1011110 + 0o6) + chr(0b1100101))(chr(3673 - 3556) + chr(0b10010 + 0o142) + chr(0b100000 + 0o106) + chr(786 - 741) + chr(1858 - 1802)) % xafqLlk3kkUe(vXoupepMtCXU, xafqLlk3kkUe(SXOLrMavuUCe(b'>4\xd5\x9e\xf8\n2+\x10\xd0(\x92'), '\x64' + chr(0b101110 + 0o67) + chr(0b1010111 + 0o14) + chr(0b11011 + 0o124) + chr(8147 - 8047) + '\145')(chr(12131 - 12014) + '\x74' + chr(0b1100110 + 0o0) + chr(0b100001 + 0o14) + chr(56))))
(ix9dZyeAmUxY, VNGQdHSFPrso) = ZzknT_Y7LtcU[:ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1098 - 1048), 8)]
vXoupepMtCXU = IDJ2eXGCBCDu.reshape(vXoupepMtCXU, [-ehT0Px3KOsy9('\060' + chr(0b1010111 + 0o30) + '\x31', 8)] + YyaZ4tpXu4lf(vXoupepMtCXU.nauYfLglTpcb)[ehT0Px3KOsy9('\060' + '\x6f' + '\062', 8):])
Hug1D32ZEDaD = ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001) + '\x30' + chr(0b100111 + 0o11), 0b1000)
io84oVi6Kfn6 = None
TFLseEYASEKG = [[ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x30', 42285 - 42277), ehT0Px3KOsy9('\x30' + '\157' + chr(48), 8)], [ehT0Px3KOsy9(chr(0b110000) + chr(10127 - 10016) + chr(0b110001), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001), 8)], [ehT0Px3KOsy9(chr(113 - 65) + chr(111) + chr(49), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b11000 + 0o31), 8)], [ehT0Px3KOsy9('\060' + chr(0b10100 + 0o133) + chr(0b110000), 8), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(4153 - 4042) + '\x30', 8)]]
for WVxHKyX45z_L in vQr8gNKaIaWE(NepKL85EaPyo):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'"\x06\xf1\xce\xd0#0+"\xeb|\xb6B\x8e'), '\144' + '\x65' + chr(2557 - 2458) + chr(0b1 + 0o156) + chr(100) + '\145')(chr(6800 - 6683) + '\x74' + chr(6291 - 6189) + chr(0b10 + 0o53) + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'8\x06\xfa\xc2\xc3\x1ey*'), chr(100) + chr(0b1100101) + chr(7346 - 7247) + '\x6f' + chr(9951 - 9851) + chr(0b1000011 + 0o42))(chr(0b1110101) + chr(0b1110100) + chr(102) + '\055' + '\x38') % (WVxHKyX45z_L + ehT0Px3KOsy9('\060' + chr(0b110000 + 0o77) + '\061', 8))):
Hug1D32ZEDaD *= ehT0Px3KOsy9('\060' + '\x6f' + '\x32', 8) ** WVxHKyX45z_L
if WVxHKyX45z_L:
Jr6qMmXilxlt = IDJ2eXGCBCDu.pad(io84oVi6Kfn6, TFLseEYASEKG)
else:
Jr6qMmXilxlt = IDJ2eXGCBCDu.pad(vXoupepMtCXU, TFLseEYASEKG)
tulGoizc7a_y = IDJ2eXGCBCDu.layers.conv2d(Jr6qMmXilxlt, filters=Hug1D32ZEDaD, kernel_size=ehT0Px3KOsy9(chr(0b110000) + chr(0b1000100 + 0o53) + chr(52), ord("\x08")), strides=ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1101 + 0o45), 8), padding=xafqLlk3kkUe(SXOLrMavuUCe(b'\x02&\xcf\xee\xf5'), chr(0b1100100) + chr(101) + chr(1963 - 1864) + chr(0b1101111) + chr(0b110000 + 0o64) + chr(0b101101 + 0o70))(chr(4938 - 4821) + chr(5071 - 4955) + chr(102) + chr(0b101101) + '\x38'))
FRzF_AGYk44w = IDJ2eXGCBCDu.contrib.layers.instance_norm(tulGoizc7a_y)
io84oVi6Kfn6 = IDJ2eXGCBCDu.nn.leaky_relu(FRzF_AGYk44w, alpha=0.2)
zBfqFfiBHzTT = IDJ2eXGCBCDu.nn.avg_pool(io84oVi6Kfn6, [ehT0Px3KOsy9('\x30' + chr(10122 - 10011) + chr(49), 8)] + io84oVi6Kfn6.shape[ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x31', 8):ehT0Px3KOsy9(chr(0b110 + 0o52) + '\x6f' + chr(0b110011), 8)].as_list() + [ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(0b10010 + 0o135) + chr(0b110001), 8)], strides=[ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(111) + '\061', 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001), 8), ehT0Px3KOsy9(chr(1345 - 1297) + chr(111) + chr(0b10000 + 0o41), 8), ehT0Px3KOsy9('\060' + chr(5706 - 5595) + '\061', 8)], padding=xafqLlk3kkUe(SXOLrMavuUCe(b'\x02&\xcf\xee\xf5'), chr(0b1010001 + 0o23) + chr(101) + chr(99) + chr(0b1101111) + chr(0b111101 + 0o47) + chr(8008 - 7907))(chr(0b1100 + 0o151) + chr(116) + chr(956 - 854) + '\055' + '\x38'))
yeXMkiStTsGj = IDJ2eXGCBCDu.squeeze(zBfqFfiBHzTT, [ehT0Px3KOsy9(chr(265 - 217) + chr(0b110101 + 0o72) + '\061', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50), 8)])
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'"\x06\xf1\xce\xd0#0+"\xeb|\xb6B\x8e'), chr(0b111111 + 0o45) + chr(101) + chr(0b1100011) + chr(6537 - 6426) + '\x64' + chr(0b111100 + 0o51))(chr(9582 - 9465) + chr(9098 - 8982) + chr(6444 - 6342) + chr(0b101101) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'.8\xee\xd2'), chr(100) + '\145' + '\143' + chr(0b1101111) + chr(0b1100100) + '\145')(chr(0b10101 + 0o140) + '\164' + chr(0b101001 + 0o75) + chr(0b101 + 0o50) + chr(1696 - 1640))):
JAS64qE3Kkya = IDJ2eXGCBCDu.layers.dense(yeXMkiStTsGj, qVkmW8bKVmfm)
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'"\x06\xf1\xce\xd0#0+"\xeb|\xb6B\x8e'), chr(0b1100100) + chr(0b1010100 + 0o21) + chr(4137 - 4038) + '\157' + chr(3802 - 3702) + chr(0b1010110 + 0o17))('\x75' + '\x74' + chr(102) + chr(0b1101 + 0o40) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b".8\xef\xc8\xd6\x1e/'\x1a\xf5~\x86A\x9a"), chr(6565 - 6465) + chr(2868 - 2767) + chr(99) + chr(0b110 + 0o151) + chr(0b1000101 + 0o37) + chr(0b110110 + 0o57))(chr(0b0 + 0o165) + '\x74' + '\x66' + chr(45) + chr(56))):
sZuGBDzfFxWr = IDJ2eXGCBCDu.layers.dense(yeXMkiStTsGj, qVkmW8bKVmfm)
sZuGBDzfFxWr = IDJ2eXGCBCDu.clip_by_value(sZuGBDzfFxWr, -ehT0Px3KOsy9(chr(0b101 + 0o53) + '\x6f' + chr(49) + chr(1952 - 1902), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1100100 + 0o13) + chr(1900 - 1851) + chr(0b110010), 8))
JAS64qE3Kkya = IDJ2eXGCBCDu.reshape(JAS64qE3Kkya, (ix9dZyeAmUxY, -ehT0Px3KOsy9(chr(1783 - 1735) + '\x6f' + chr(49), 8), qVkmW8bKVmfm))
sZuGBDzfFxWr = IDJ2eXGCBCDu.reshape(sZuGBDzfFxWr, (ix9dZyeAmUxY, -ehT0Px3KOsy9(chr(48) + chr(0b1011011 + 0o24) + chr(1263 - 1214), 8), qVkmW8bKVmfm))
return (JAS64qE3Kkya, sZuGBDzfFxWr)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/video/savp.py
|
NextFrameSavpBase.get_fc_dimensions
|
def get_fc_dimensions(self, strides, kernel_sizes):
"""Get expected fully connected shape after a series of convolutions."""
output_height, output_width, _ = self.hparams.problem.frame_shape
output_steps = self.hparams.video_num_target_frames
output_shape = np.array([output_steps, output_height, output_width])
for curr_stride, kernel_size in zip(strides, kernel_sizes):
output_shape = self.expected_output_shape(
output_shape, np.array(curr_stride), 1, kernel_size)
return np.prod(output_shape) * self.hparams.num_discriminator_filters * 8
|
python
|
def get_fc_dimensions(self, strides, kernel_sizes):
"""Get expected fully connected shape after a series of convolutions."""
output_height, output_width, _ = self.hparams.problem.frame_shape
output_steps = self.hparams.video_num_target_frames
output_shape = np.array([output_steps, output_height, output_width])
for curr_stride, kernel_size in zip(strides, kernel_sizes):
output_shape = self.expected_output_shape(
output_shape, np.array(curr_stride), 1, kernel_size)
return np.prod(output_shape) * self.hparams.num_discriminator_filters * 8
|
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Get expected fully connected shape after a series of convolutions.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/video/savp.py#L110-L118
|
train
|
Get expected fully connected shape after a series of 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('\060' + chr(111) + chr(49) + chr(0b100001 + 0o17) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(52 - 4) + '\x6f' + chr(49) + '\060' + '\065', 39620 - 39612), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b101101 + 0o5) + '\x32' + chr(1373 - 1322), 0o10), ehT0Px3KOsy9('\060' + chr(0b10100 + 0o133) + chr(0b10101 + 0o34) + chr(53) + chr(54), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061' + '\064' + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(1278 - 1230) + chr(0b1011001 + 0o26) + chr(0b11010 + 0o27), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b11100 + 0o26) + chr(52) + '\063', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b111110 + 0o61) + chr(0b100111 + 0o14) + chr(0b100100 + 0o23) + chr(1326 - 1272), 0o10), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1100000 + 0o17) + chr(49) + '\061' + chr(0b10001 + 0o40), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\063' + '\062', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b110110 + 0o71) + '\061' + chr(0b110011) + '\061', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b100 + 0o57) + '\063' + chr(481 - 430), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(9290 - 9179) + chr(0b1 + 0o60) + '\x34' + chr(0b100000 + 0o25), 0o10), ehT0Px3KOsy9('\060' + chr(0b10111 + 0o130) + chr(0b110010) + chr(0b100 + 0o57) + chr(0b11001 + 0o27), 0b1000), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(0b101001 + 0o106) + '\067' + chr(0b101111 + 0o5), ord("\x08")), ehT0Px3KOsy9(chr(0b10100 + 0o34) + '\x6f' + chr(49) + chr(0b110010) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(2104 - 1993) + chr(50) + '\x35' + '\062', 53351 - 53343), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b1101111) + chr(49) + chr(0b110000) + '\063', 41394 - 41386), ehT0Px3KOsy9(chr(0b110000) + chr(8720 - 8609) + chr(1036 - 986) + chr(0b100001 + 0o23) + chr(0b110011), 8), ehT0Px3KOsy9('\060' + '\157' + chr(1204 - 1154) + chr(48) + chr(54), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110000 + 0o5) + chr(119 - 69), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + chr(350 - 300) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b101101 + 0o102) + chr(0b110001) + chr(2094 - 2043) + '\065', 28137 - 28129), ehT0Px3KOsy9(chr(2133 - 2085) + chr(0b1101111) + chr(2365 - 2316) + chr(0b110110) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\x6f' + '\064' + chr(555 - 502), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x30', 21928 - 21920), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\x6f' + '\x33' + chr(0b110001) + chr(429 - 379), 0b1000), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(2835 - 2724) + chr(908 - 858) + chr(348 - 300) + '\060', 0o10), ehT0Px3KOsy9(chr(1433 - 1385) + chr(0b1101111) + chr(0b110011) + '\064' + chr(0b110111), 15249 - 15241), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(0b110110) + '\064', 0b1000), ehT0Px3KOsy9('\x30' + chr(6284 - 6173) + chr(1091 - 1040) + '\x32', 8), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(111) + '\x37' + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b1001 + 0o52) + '\066' + chr(0b110011), 44152 - 44144), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\x6f' + '\x32' + chr(0b110000) + chr(49), ord("\x08")), ehT0Px3KOsy9('\060' + chr(4136 - 4025) + chr(1485 - 1435) + chr(0b110100), 41213 - 41205), ehT0Px3KOsy9(chr(0b110000) + chr(0b100000 + 0o117) + '\x33' + '\061' + '\x31', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110011) + chr(0b10 + 0o61) + chr(55), 0o10), ehT0Px3KOsy9(chr(487 - 439) + '\157' + '\063' + chr(0b10 + 0o56) + chr(55), 0b1000), ehT0Px3KOsy9(chr(1691 - 1643) + '\x6f' + chr(49) + '\062' + chr(0b101111 + 0o5), 39594 - 39586)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110101) + chr(0b110000), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'j'), chr(0b1100100) + chr(0b1001001 + 0o34) + chr(99) + chr(111) + chr(977 - 877) + '\x65')('\165' + chr(0b1110100) + chr(5895 - 5793) + '\x2d' + chr(0b10001 + 0o47)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def K5oPH1Ope11c(oVre8I6UXc3b, r8knJmMTTKwv, dZWfq1KIDqAh):
(rtuDLoFVW_2X, ZfFMzpU6hX95, VNGQdHSFPrso) = oVre8I6UXc3b.hparams.problem.frame_shape
rA8oP8RdAAAT = oVre8I6UXc3b.hparams.UxYiT0ZFW2SZ
CeP8heSqnrCd = WqUC3KWvYVup.B0ePDhpqxN5n([rA8oP8RdAAAT, rtuDLoFVW_2X, ZfFMzpU6hX95])
for (sivnNGpgfXpo, m6gwVXy4D3Au) in pZ0NK2y6HRbn(r8knJmMTTKwv, dZWfq1KIDqAh):
CeP8heSqnrCd = oVre8I6UXc3b.expected_output_shape(CeP8heSqnrCd, WqUC3KWvYVup.B0ePDhpqxN5n(sivnNGpgfXpo), ehT0Px3KOsy9(chr(1695 - 1647) + '\157' + chr(1745 - 1696), 8), m6gwVXy4D3Au)
return xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'(\x07\xca\x05V8\xcf\xca\x07qa\xb3'), chr(1222 - 1122) + chr(6306 - 6205) + chr(7701 - 7602) + chr(111) + chr(100) + chr(6819 - 6718))(chr(117) + chr(11604 - 11488) + chr(6791 - 6689) + chr(0b101101) + chr(2372 - 2316)))(CeP8heSqnrCd) * xafqLlk3kkUe(oVre8I6UXc3b.hparams, xafqLlk3kkUe(SXOLrMavuUCe(b'*0\xfe1\x05h\xd0\x9d;s4\xb2\x0b\xf9H=\xd8\x1c\xc5\xefF\xe68\x02V'), '\x64' + chr(0b1100101) + chr(0b1100011) + chr(0b1100 + 0o143) + chr(0b1100100) + chr(0b1100101))(chr(117) + chr(12034 - 11918) + chr(1691 - 1589) + chr(1169 - 1124) + chr(0b11000 + 0o40))) * ehT0Px3KOsy9('\x30' + chr(10542 - 10431) + chr(0b110001) + '\060', 63630 - 63622)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/video/savp.py
|
NextFrameSavpBase.discriminator
|
def discriminator(self, frames):
"""3-D SNGAN discriminator.
Args:
frames: a list of batch-major tensors indexed by time.
Returns:
logits: 1-D Tensor with shape=batch_size.
Positive logits imply that the discriminator thinks that it
belongs to the true class.
"""
ndf = self.hparams.num_discriminator_filters
frames = tf.stack(frames)
# Switch from time-major axis to batch-major axis.
frames = common_video.swap_time_and_batch_axes(frames)
# 3-D Conv-net mapping inputs to activations.
num_outputs = [ndf, ndf*2, ndf*2, ndf*4, ndf*4, ndf*8, ndf*8]
kernel_sizes = [3, 4, 3, 4, 3, 4, 3]
strides = [[1, 1, 1], [1, 2, 2], [1, 1, 1], [1, 2, 2], [1, 1, 1],
[2, 2, 2], [1, 1, 1]]
names = ["video_sn_conv0_0", "video_sn_conv0_1", "video_sn_conv1_0",
"video_sn_conv1_1", "video_sn_conv2_0", "video_sn_conv2_1",
"video_sn_conv3_0"]
iterable = zip(num_outputs, kernel_sizes, strides, names)
activations = frames
for num_filters, kernel_size, stride, name in iterable:
activations = self.pad_conv3d_lrelu(activations, num_filters, kernel_size,
stride, name)
num_fc_dimensions = self.get_fc_dimensions(strides, kernel_sizes)
activations = tf.reshape(activations, (-1, num_fc_dimensions))
return tf.squeeze(tf.layers.dense(activations, 1))
|
python
|
def discriminator(self, frames):
"""3-D SNGAN discriminator.
Args:
frames: a list of batch-major tensors indexed by time.
Returns:
logits: 1-D Tensor with shape=batch_size.
Positive logits imply that the discriminator thinks that it
belongs to the true class.
"""
ndf = self.hparams.num_discriminator_filters
frames = tf.stack(frames)
# Switch from time-major axis to batch-major axis.
frames = common_video.swap_time_and_batch_axes(frames)
# 3-D Conv-net mapping inputs to activations.
num_outputs = [ndf, ndf*2, ndf*2, ndf*4, ndf*4, ndf*8, ndf*8]
kernel_sizes = [3, 4, 3, 4, 3, 4, 3]
strides = [[1, 1, 1], [1, 2, 2], [1, 1, 1], [1, 2, 2], [1, 1, 1],
[2, 2, 2], [1, 1, 1]]
names = ["video_sn_conv0_0", "video_sn_conv0_1", "video_sn_conv1_0",
"video_sn_conv1_1", "video_sn_conv2_0", "video_sn_conv2_1",
"video_sn_conv3_0"]
iterable = zip(num_outputs, kernel_sizes, strides, names)
activations = frames
for num_filters, kernel_size, stride, name in iterable:
activations = self.pad_conv3d_lrelu(activations, num_filters, kernel_size,
stride, name)
num_fc_dimensions = self.get_fc_dimensions(strides, kernel_sizes)
activations = tf.reshape(activations, (-1, num_fc_dimensions))
return tf.squeeze(tf.layers.dense(activations, 1))
|
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] |
3-D SNGAN discriminator.
Args:
frames: a list of batch-major tensors indexed by time.
Returns:
logits: 1-D Tensor with shape=batch_size.
Positive logits imply that the discriminator thinks that it
belongs to the true class.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/video/savp.py#L120-L153
|
train
|
3 - D SNGAN discriminator.
|
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(0b1000001 + 0o56) + chr(51) + '\x36' + chr(340 - 286), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061' + '\061' + chr(0b11110 + 0o30), ord("\x08")), ehT0Px3KOsy9(chr(0b1011 + 0o45) + '\157' + chr(0b0 + 0o63) + chr(0b110000) + '\x32', 61846 - 61838), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b101001 + 0o11) + chr(0b110010) + chr(0b1 + 0o60), ord("\x08")), ehT0Px3KOsy9(chr(1445 - 1397) + chr(0b1101111) + chr(0b111 + 0o54) + '\x37' + chr(0b110000), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(51) + chr(0b110101) + chr(49), 0o10), ehT0Px3KOsy9(chr(416 - 368) + chr(0b1011010 + 0o25) + '\063' + chr(1989 - 1935) + chr(215 - 161), 8), ehT0Px3KOsy9(chr(787 - 739) + '\x6f' + chr(0b100110 + 0o14) + chr(1933 - 1884) + '\x30', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(50) + '\x33' + '\x30', 54861 - 54853), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(2345 - 2294) + chr(48), 0b1000), ehT0Px3KOsy9(chr(2170 - 2122) + chr(637 - 526) + chr(0b11110 + 0o25) + chr(2326 - 2272) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010) + '\x30' + '\062', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1356 - 1306) + chr(0b100000 + 0o21) + chr(0b110101), 31953 - 31945), ehT0Px3KOsy9(chr(48) + chr(5903 - 5792) + chr(1101 - 1051) + '\x35' + chr(1555 - 1500), 0b1000), ehT0Px3KOsy9(chr(1498 - 1450) + chr(0b1100101 + 0o12) + chr(2006 - 1954) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1111 + 0o140) + chr(50) + '\x35' + chr(0b101011 + 0o11), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + '\x32' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(0b1101 + 0o50) + chr(54), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1010 + 0o145) + chr(0b110110) + '\x35', 26153 - 26145), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + chr(0b10110 + 0o37) + '\x34', 8), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b100 + 0o57) + chr(53) + '\064', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b111 + 0o150) + chr(50) + chr(0b100 + 0o63), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(51) + '\067' + chr(53), 0b1000), ehT0Px3KOsy9('\x30' + chr(5615 - 5504) + chr(882 - 832) + chr(1979 - 1926) + chr(0b11001 + 0o32), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(399 - 350) + '\x35' + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(0b11 + 0o154) + '\x31' + chr(0b11001 + 0o27) + chr(2242 - 2189), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b10001 + 0o42) + chr(49) + chr(852 - 800), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(7729 - 7618) + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1001101 + 0o42) + chr(756 - 707) + chr(52) + chr(48), 0o10), ehT0Px3KOsy9(chr(103 - 55) + chr(2038 - 1927) + '\063' + '\060' + '\063', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1000000 + 0o57) + chr(450 - 398), 58779 - 58771), ehT0Px3KOsy9('\060' + chr(0b0 + 0o157) + chr(142 - 92) + chr(50) + '\061', 8), ehT0Px3KOsy9(chr(0b111 + 0o51) + '\157' + chr(0b110001) + chr(0b10001 + 0o41), 57767 - 57759), ehT0Px3KOsy9(chr(48) + chr(0b1001100 + 0o43) + '\063' + '\x30' + '\064', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b1100 + 0o46) + chr(2778 - 2725) + chr(0b100101 + 0o20), 0b1000), ehT0Px3KOsy9(chr(48) + chr(5080 - 4969) + '\x32' + chr(0b101111 + 0o1) + '\x37', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(942 - 893) + chr(0b110010) + chr(2728 - 2674), 50176 - 50168), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(52) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1100 + 0o47) + chr(2077 - 2029) + chr(51), 8), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\x6f' + '\x32' + chr(0b110000 + 0o3) + chr(0b110100), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\157' + '\065' + chr(0b110000), 39673 - 39665)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd8'), chr(0b1011010 + 0o12) + '\x65' + chr(0b110101 + 0o56) + chr(10907 - 10796) + '\144' + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + '\146' + chr(1752 - 1707) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def PgtWWoVsho2z(oVre8I6UXc3b, RlRNrq1190ue):
Ax7AJCRkuN0W = oVre8I6UXc3b.hparams.num_discriminator_filters
RlRNrq1190ue = IDJ2eXGCBCDu.stack(RlRNrq1190ue)
RlRNrq1190ue = feDooRjkbHzt.swap_time_and_batch_axes(RlRNrq1190ue)
YzOh4ZueGp_Q = [Ax7AJCRkuN0W, Ax7AJCRkuN0W * ehT0Px3KOsy9(chr(0b110000) + chr(0b1101011 + 0o4) + chr(0b10001 + 0o41), 0b1000), Ax7AJCRkuN0W * ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010), 8), Ax7AJCRkuN0W * ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100001 + 0o23), 8), Ax7AJCRkuN0W * ehT0Px3KOsy9('\x30' + chr(0b1001110 + 0o41) + chr(0b110100), 8), Ax7AJCRkuN0W * ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b1000001 + 0o56) + chr(0b110001) + chr(0b110000), 62270 - 62262), Ax7AJCRkuN0W * ehT0Px3KOsy9('\060' + chr(111) + '\x31' + '\060', 8)]
dZWfq1KIDqAh = [ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\063', 0o10), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\x6f' + '\x34', 8), ehT0Px3KOsy9(chr(1957 - 1909) + chr(0b1100100 + 0o13) + '\063', 8), ehT0Px3KOsy9('\x30' + chr(0b1000111 + 0o50) + '\x34', 8), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(0b1101111) + chr(0b110011), 8), ehT0Px3KOsy9('\x30' + chr(9641 - 9530) + chr(52), 8), ehT0Px3KOsy9('\x30' + '\157' + '\x33', 8)]
r8knJmMTTKwv = [[ehT0Px3KOsy9(chr(48) + chr(0b1010101 + 0o32) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(843 - 794), 8), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(0b1101111) + '\x31', 8)], [ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(1088 - 1038), 8), ehT0Px3KOsy9(chr(2269 - 2221) + '\157' + '\x32', 8)], [ehT0Px3KOsy9('\x30' + '\x6f' + '\x31', 8), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(8400 - 8289) + '\x31', 8), ehT0Px3KOsy9('\060' + chr(111) + chr(2107 - 2058), 8)], [ehT0Px3KOsy9(chr(333 - 285) + '\x6f' + chr(49), 8), ehT0Px3KOsy9('\060' + chr(111) + '\062', 8), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(111) + chr(50), 8)], [ehT0Px3KOsy9(chr(48) + chr(111) + '\x31', 8), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(0b11001 + 0o126) + '\x31', 8), ehT0Px3KOsy9(chr(48) + chr(6480 - 6369) + chr(0b100010 + 0o17), 8)], [ehT0Px3KOsy9(chr(0b110000) + chr(7642 - 7531) + '\x32', 8), ehT0Px3KOsy9(chr(414 - 366) + chr(798 - 687) + '\062', 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32', 8)], [ehT0Px3KOsy9('\060' + chr(0b10101 + 0o132) + chr(49), 8), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(3608 - 3497) + '\x31', 8), ehT0Px3KOsy9(chr(360 - 312) + chr(0b1010111 + 0o30) + '\x31', 8)]]
OcnR1hZ7pGdr = [xafqLlk3kkUe(SXOLrMavuUCe(b"\x80'\xa6\xf4\x97\xb6\x85\xe6\xc7{\x9f\xec\xfb\x9f{\x9c"), '\x64' + chr(0b1100101) + chr(0b1010 + 0o131) + '\x6f' + chr(0b1100100) + chr(0b1011110 + 0o7))(chr(0b1110101) + chr(116) + chr(0b1001110 + 0o30) + chr(0b11011 + 0o22) + chr(2174 - 2118)), xafqLlk3kkUe(SXOLrMavuUCe(b"\x80'\xa6\xf4\x97\xb6\x85\xe6\xc7{\x9f\xec\xfb\x9f{\x9d"), chr(0b1001111 + 0o25) + '\x65' + chr(0b110101 + 0o56) + chr(3055 - 2944) + '\144' + '\145')(chr(0b1101110 + 0o7) + chr(0b1110100) + '\x66' + '\x2d' + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b"\x80'\xa6\xf4\x97\xb6\x85\xe6\xc7{\x9f\xec\xfb\x9e{\x9c"), '\x64' + chr(8267 - 8166) + chr(0b1000100 + 0o37) + chr(0b1001010 + 0o45) + chr(6768 - 6668) + '\145')('\x75' + '\164' + chr(0b1001000 + 0o36) + '\x2d' + chr(1439 - 1383)), xafqLlk3kkUe(SXOLrMavuUCe(b"\x80'\xa6\xf4\x97\xb6\x85\xe6\xc7{\x9f\xec\xfb\x9e{\x9d"), chr(0b1100100) + '\x65' + chr(0b1100011) + chr(0b1101111) + chr(0b1100100) + '\145')('\x75' + chr(10377 - 10261) + chr(0b110010 + 0o64) + chr(45) + chr(0b101000 + 0o20)), xafqLlk3kkUe(SXOLrMavuUCe(b"\x80'\xa6\xf4\x97\xb6\x85\xe6\xc7{\x9f\xec\xfb\x9d{\x9c"), '\x64' + chr(101) + chr(0b11011 + 0o110) + chr(0b1101111) + chr(0b1010000 + 0o24) + chr(0b1001100 + 0o31))(chr(0b1011010 + 0o33) + '\x74' + '\146' + '\055' + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b"\x80'\xa6\xf4\x97\xb6\x85\xe6\xc7{\x9f\xec\xfb\x9d{\x9d"), '\x64' + '\145' + chr(0b1100011) + '\157' + chr(6113 - 6013) + chr(0b1100101))(chr(0b1101110 + 0o7) + '\x74' + chr(0b1100110) + chr(67 - 22) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b"\x80'\xa6\xf4\x97\xb6\x85\xe6\xc7{\x9f\xec\xfb\x9c{\x9c"), chr(6711 - 6611) + '\x65' + chr(0b1001001 + 0o32) + chr(111) + '\x64' + '\x65')(chr(0b100111 + 0o116) + chr(7299 - 7183) + chr(0b1100110) + chr(0b101101) + '\x38')]
B7a8G3ORwfjH = pZ0NK2y6HRbn(YzOh4ZueGp_Q, dZWfq1KIDqAh, r8knJmMTTKwv, OcnR1hZ7pGdr)
mgDWDDVSXPyH = RlRNrq1190ue
for (zVkWryy7Pzt7, m6gwVXy4D3Au, VKQ5wcD30goF, AIvJRzLdDfgF) in B7a8G3ORwfjH:
mgDWDDVSXPyH = oVre8I6UXc3b.pad_conv3d_lrelu(mgDWDDVSXPyH, zVkWryy7Pzt7, m6gwVXy4D3Au, VKQ5wcD30goF, AIvJRzLdDfgF)
dBryz6sObHEO = oVre8I6UXc3b.get_fc_dimensions(r8knJmMTTKwv, dZWfq1KIDqAh)
mgDWDDVSXPyH = IDJ2eXGCBCDu.reshape(mgDWDDVSXPyH, (-ehT0Px3KOsy9(chr(1006 - 958) + chr(0b11101 + 0o122) + '\061', 8), dBryz6sObHEO))
return xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x85?\xb7\xf4\x9d\x93\x93'), chr(0b1100100) + '\145' + '\x63' + '\157' + chr(100) + chr(0b1011011 + 0o12))(chr(4070 - 3953) + chr(116) + '\146' + '\x2d' + '\070'))(xafqLlk3kkUe(IDJ2eXGCBCDu.layers, xafqLlk3kkUe(SXOLrMavuUCe(b'\x92+\xac\xe2\x9d'), chr(0b1100100) + '\x65' + chr(3977 - 3878) + chr(111) + '\144' + chr(7035 - 6934))(chr(0b1110101) + chr(116) + chr(102) + '\055' + chr(56)))(mgDWDDVSXPyH, ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49), 8)))
|
tensorflow/tensor2tensor
|
tensor2tensor/models/video/savp.py
|
NextFrameSavpBase.d_step
|
def d_step(self, true_frames, gen_frames):
"""Performs the discriminator step in computing the GAN loss.
Applies stop-gradient to the generated frames while computing the
discriminator loss to make sure that the gradients are not back-propagated
to the generator. This makes sure that only the discriminator is updated.
Args:
true_frames: True outputs
gen_frames: Generated frames.
Returns:
d_loss: Loss component due to the discriminator.
"""
hparam_to_disc_loss = {
"least_squares": gan_losses.least_squares_discriminator_loss,
"cross_entropy": gan_losses.modified_discriminator_loss,
"wasserstein": gan_losses.wasserstein_discriminator_loss}
# Concat across batch-axis.
_, batch_size, _, _, _ = common_layers.shape_list(true_frames)
all_frames = tf.concat(
[true_frames, tf.stop_gradient(gen_frames)], axis=1)
all_logits = self.discriminator(all_frames)
true_logits, fake_logits_stop = \
all_logits[:batch_size], all_logits[batch_size:]
mean_true_logits = tf.reduce_mean(true_logits)
tf.summary.scalar("mean_true_logits", mean_true_logits)
mean_fake_logits_stop = tf.reduce_mean(fake_logits_stop)
tf.summary.scalar("mean_fake_logits_stop", mean_fake_logits_stop)
discriminator_loss_func = hparam_to_disc_loss[self.hparams.gan_loss]
gan_d_loss = discriminator_loss_func(
discriminator_real_outputs=true_logits,
discriminator_gen_outputs=fake_logits_stop,
add_summaries=True)
return gan_d_loss, true_logits, fake_logits_stop
|
python
|
def d_step(self, true_frames, gen_frames):
"""Performs the discriminator step in computing the GAN loss.
Applies stop-gradient to the generated frames while computing the
discriminator loss to make sure that the gradients are not back-propagated
to the generator. This makes sure that only the discriminator is updated.
Args:
true_frames: True outputs
gen_frames: Generated frames.
Returns:
d_loss: Loss component due to the discriminator.
"""
hparam_to_disc_loss = {
"least_squares": gan_losses.least_squares_discriminator_loss,
"cross_entropy": gan_losses.modified_discriminator_loss,
"wasserstein": gan_losses.wasserstein_discriminator_loss}
# Concat across batch-axis.
_, batch_size, _, _, _ = common_layers.shape_list(true_frames)
all_frames = tf.concat(
[true_frames, tf.stop_gradient(gen_frames)], axis=1)
all_logits = self.discriminator(all_frames)
true_logits, fake_logits_stop = \
all_logits[:batch_size], all_logits[batch_size:]
mean_true_logits = tf.reduce_mean(true_logits)
tf.summary.scalar("mean_true_logits", mean_true_logits)
mean_fake_logits_stop = tf.reduce_mean(fake_logits_stop)
tf.summary.scalar("mean_fake_logits_stop", mean_fake_logits_stop)
discriminator_loss_func = hparam_to_disc_loss[self.hparams.gan_loss]
gan_d_loss = discriminator_loss_func(
discriminator_real_outputs=true_logits,
discriminator_gen_outputs=fake_logits_stop,
add_summaries=True)
return gan_d_loss, true_logits, fake_logits_stop
|
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] |
Performs the discriminator step in computing the GAN loss.
Applies stop-gradient to the generated frames while computing the
discriminator loss to make sure that the gradients are not back-propagated
to the generator. This makes sure that only the discriminator is updated.
Args:
true_frames: True outputs
gen_frames: Generated frames.
Returns:
d_loss: Loss component due to the discriminator.
|
[
"Performs",
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"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/video/savp.py#L155-L192
|
train
|
Performs the discriminator step in computing the GAN 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(0b110 + 0o52) + chr(0b1001000 + 0o47) + chr(0b110011) + chr(0b110001) + chr(0b10111 + 0o32), 61427 - 61419), ehT0Px3KOsy9(chr(0b10110 + 0o32) + '\x6f' + chr(0b110001) + chr(0b110011) + chr(0b110010 + 0o2), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(473 - 423) + chr(49) + chr(49), 65082 - 65074), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + '\x30' + chr(1679 - 1627), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b110010 + 0o75) + chr(0b110011), 28660 - 28652), ehT0Px3KOsy9('\x30' + chr(2621 - 2510) + chr(53) + chr(54), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(50) + chr(0b110011) + chr(200 - 149), 21468 - 21460), ehT0Px3KOsy9(chr(826 - 778) + '\x6f' + chr(0b111 + 0o57) + chr(1019 - 967), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\060', 11350 - 11342), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + chr(0b10010 + 0o44) + chr(505 - 451), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111 + 0o0) + '\061' + '\066' + chr(0b1100 + 0o53), 0b1000), ehT0Px3KOsy9(chr(1867 - 1819) + chr(111) + '\061' + '\066' + chr(0b11011 + 0o31), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b100101 + 0o112) + chr(0b1 + 0o61) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + chr(0b100101 + 0o22) + '\x34', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(2092 - 2042) + chr(48), 8), ehT0Px3KOsy9(chr(48) + chr(111) + '\x37' + '\x35', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b1001 + 0o50) + '\x37' + chr(1703 - 1655), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(54) + chr(0b100000 + 0o25), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101 + 0o142) + chr(51) + '\x35' + chr(1880 - 1829), 6038 - 6030), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(675 - 626) + '\x34' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(1462 - 1351) + chr(1609 - 1559) + chr(55) + chr(0b100010 + 0o20), 0b1000), ehT0Px3KOsy9(chr(918 - 870) + chr(111) + chr(2378 - 2329) + '\066' + chr(0b10100 + 0o37), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b101001 + 0o12) + chr(49) + chr(53), 0o10), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(0b1000110 + 0o51) + chr(51) + chr(0b110 + 0o55) + chr(0b101100 + 0o11), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(0b101 + 0o55) + chr(244 - 189), 0o10), ehT0Px3KOsy9(chr(93 - 45) + chr(0b101001 + 0o106) + '\062' + chr(49) + chr(0b110110), 45758 - 45750), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + chr(0b1011 + 0o52) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x33' + chr(0b110010) + chr(54), 0o10), ehT0Px3KOsy9(chr(523 - 475) + chr(0b1011111 + 0o20) + '\064' + chr(241 - 188), 54660 - 54652), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101110 + 0o1) + chr(0b110001) + chr(0b110011 + 0o2), 0o10), ehT0Px3KOsy9('\x30' + chr(4094 - 3983) + chr(50) + '\x36' + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + chr(0b10 + 0o57) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\x6f' + chr(1578 - 1528) + chr(0b101 + 0o56) + chr(53), 0o10), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(0b1101111) + chr(54) + '\064', 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(0b10011 + 0o41) + chr(53), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + chr(0b110110) + '\064', 65453 - 65445), ehT0Px3KOsy9('\x30' + '\x6f' + chr(51) + chr(50) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(0b1101111) + chr(2339 - 2289) + '\066' + '\x34', 8), ehT0Px3KOsy9(chr(1862 - 1814) + chr(111) + chr(0b100001 + 0o21) + chr(2331 - 2279) + chr(0b110110), 18350 - 18342), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b111 + 0o55), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(1023 - 975) + chr(4623 - 4512) + chr(53) + chr(2067 - 2019), 15179 - 15171)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xe7'), '\x64' + chr(101) + '\x63' + chr(0b1101111) + chr(0b1100100 + 0o0) + chr(9888 - 9787))(chr(0b1000001 + 0o64) + chr(0b1110100) + '\146' + '\055' + chr(0b101011 + 0o15)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def BP8lArdQw_V7(oVre8I6UXc3b, j_l58HFkYlQH, k0yN1BuOulXb):
lZkAAEl7oiUr = {xafqLlk3kkUe(SXOLrMavuUCe(b'\xa59\xe87wq\xe8Eu\x17\x05\x11c'), chr(0b1100100) + chr(101) + chr(0b1100011) + chr(111) + '\x64' + chr(101))(chr(117) + '\x74' + '\x66' + chr(596 - 551) + '\x38'): HDCDSTeou2Ry.least_squares_discriminator_loss, xafqLlk3kkUe(SXOLrMavuUCe(b'\xaa.\xe67pq\xfeZt\x04\x18\x04i'), chr(9249 - 9149) + '\145' + chr(0b1100011) + chr(12061 - 11950) + chr(0b1100100) + chr(0b11001 + 0o114))(chr(0b1110101) + chr(9249 - 9133) + chr(6953 - 6851) + chr(45) + chr(0b101100 + 0o14)): HDCDSTeou2Ry.modified_discriminator_loss, xafqLlk3kkUe(SXOLrMavuUCe(b'\xbe=\xfa7f\\\xe8@e\x1f\x19'), '\144' + chr(101) + chr(0b1100011) + chr(0b1101111) + chr(0b1100100) + chr(1905 - 1804))('\x75' + '\x74' + chr(1117 - 1015) + chr(0b101101) + chr(56)): HDCDSTeou2Ry.wasserstein_discriminator_loss}
(VNGQdHSFPrso, ix9dZyeAmUxY, VNGQdHSFPrso, VNGQdHSFPrso, VNGQdHSFPrso) = jSKPaHwSAfVv.shape_list(j_l58HFkYlQH)
hJU2FOlzyEcy = IDJ2eXGCBCDu.concat([j_l58HFkYlQH, IDJ2eXGCBCDu.stop_gradient(k0yN1BuOulXb)], axis=ehT0Px3KOsy9(chr(48) + '\x6f' + chr(49), 0b1000))
lSqEGdkl3u6I = oVre8I6UXc3b.discriminator(hJU2FOlzyEcy)
(KOL5TSDfTj99, P51q6yx_tuae) = (lSqEGdkl3u6I[:ix9dZyeAmUxY], lSqEGdkl3u6I[ix9dZyeAmUxY:])
Yc9eb6HNiAEi = IDJ2eXGCBCDu.reduce_mean(KOL5TSDfTj99)
xafqLlk3kkUe(IDJ2eXGCBCDu.summary, xafqLlk3kkUe(SXOLrMavuUCe(b'\xba?\xe8(b\\'), '\x64' + '\145' + '\x63' + '\x6f' + chr(0b1000001 + 0o43) + chr(0b1001010 + 0o33))(chr(8592 - 8475) + '\x74' + '\146' + chr(0b101101) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xa49\xe8*\\Z\xe9Ae)\x1b\x1bw\x15dN'), chr(2542 - 2442) + '\145' + '\143' + chr(0b1101111) + '\x64' + '\x65')(chr(0b110100 + 0o101) + '\x74' + '\146' + chr(0b110 + 0o47) + chr(56)), Yc9eb6HNiAEi)
mhYcF6PTRx7J = IDJ2eXGCBCDu.reduce_mean(P51q6yx_tuae)
xafqLlk3kkUe(IDJ2eXGCBCDu.summary, xafqLlk3kkUe(SXOLrMavuUCe(b'\xba?\xe8(b\\'), chr(0b1100100) + chr(101) + chr(99) + chr(111) + '\144' + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + chr(45) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b"\xa49\xe8*\\H\xfa_e)\x1b\x1bw\x15dN'F\x9f\t\xca"), chr(0b101010 + 0o72) + chr(0b1100101) + '\143' + chr(1038 - 927) + chr(0b1100100) + '\145')('\x75' + '\164' + '\146' + '\x2d' + '\x38'), mhYcF6PTRx7J)
FQDwX4bjjTD7 = lZkAAEl7oiUr[oVre8I6UXc3b.hparams.gan_loss]
Yd3FyKjonHV1 = FQDwX4bjjTD7(discriminator_real_outputs=KOL5TSDfTj99, discriminator_gen_outputs=P51q6yx_tuae, add_summaries=ehT0Px3KOsy9('\x30' + chr(111) + chr(49), 8))
return (Yd3FyKjonHV1, KOL5TSDfTj99, P51q6yx_tuae)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/video/savp.py
|
NextFrameSavpBase.g_step
|
def g_step(self, gen_frames, fake_logits_stop):
"""Performs the generator step in computing the GAN loss.
Args:
gen_frames: Generated frames
fake_logits_stop: Logits corresponding to the generated frames as per
the discriminator. Assumed to have a stop-gradient term.
Returns:
gan_g_loss_pos_d: Loss.
gan_g_loss_neg_d: -gan_g_loss_pos_d but with a stop gradient on generator.
"""
hparam_to_gen_loss = {
"least_squares": gan_losses.least_squares_generator_loss,
"cross_entropy": gan_losses.modified_generator_loss,
"wasserstein": gan_losses.wasserstein_generator_loss
}
fake_logits = self.discriminator(gen_frames)
mean_fake_logits = tf.reduce_mean(fake_logits)
tf.summary.scalar("mean_fake_logits", mean_fake_logits)
# Generator loss.
# Using gan_g_loss_pos_d updates the discriminator as well.
# To avoid this add gan_g_loss_neg_d = -gan_g_loss_pos_d
# but with stop gradient on the generator.
# This makes sure that the net gradient on the discriminator is zero and
# net-gradient on the generator is just due to the gan_g_loss_pos_d.
generator_loss_func = hparam_to_gen_loss[self.hparams.gan_loss]
gan_g_loss_pos_d = generator_loss_func(
discriminator_gen_outputs=fake_logits, add_summaries=True)
gan_g_loss_neg_d = -generator_loss_func(
discriminator_gen_outputs=fake_logits_stop, add_summaries=True)
return gan_g_loss_pos_d, gan_g_loss_neg_d
|
python
|
def g_step(self, gen_frames, fake_logits_stop):
"""Performs the generator step in computing the GAN loss.
Args:
gen_frames: Generated frames
fake_logits_stop: Logits corresponding to the generated frames as per
the discriminator. Assumed to have a stop-gradient term.
Returns:
gan_g_loss_pos_d: Loss.
gan_g_loss_neg_d: -gan_g_loss_pos_d but with a stop gradient on generator.
"""
hparam_to_gen_loss = {
"least_squares": gan_losses.least_squares_generator_loss,
"cross_entropy": gan_losses.modified_generator_loss,
"wasserstein": gan_losses.wasserstein_generator_loss
}
fake_logits = self.discriminator(gen_frames)
mean_fake_logits = tf.reduce_mean(fake_logits)
tf.summary.scalar("mean_fake_logits", mean_fake_logits)
# Generator loss.
# Using gan_g_loss_pos_d updates the discriminator as well.
# To avoid this add gan_g_loss_neg_d = -gan_g_loss_pos_d
# but with stop gradient on the generator.
# This makes sure that the net gradient on the discriminator is zero and
# net-gradient on the generator is just due to the gan_g_loss_pos_d.
generator_loss_func = hparam_to_gen_loss[self.hparams.gan_loss]
gan_g_loss_pos_d = generator_loss_func(
discriminator_gen_outputs=fake_logits, add_summaries=True)
gan_g_loss_neg_d = -generator_loss_func(
discriminator_gen_outputs=fake_logits_stop, add_summaries=True)
return gan_g_loss_pos_d, gan_g_loss_neg_d
|
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",",
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] |
Performs the generator step in computing the GAN loss.
Args:
gen_frames: Generated frames
fake_logits_stop: Logits corresponding to the generated frames as per
the discriminator. Assumed to have a stop-gradient term.
Returns:
gan_g_loss_pos_d: Loss.
gan_g_loss_neg_d: -gan_g_loss_pos_d but with a stop gradient on generator.
|
[
"Performs",
"the",
"generator",
"step",
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"computing",
"the",
"GAN",
"loss",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/video/savp.py#L194-L226
|
train
|
Performs the generator step in computing the GAN 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(469 - 421) + chr(5655 - 5544) + chr(0b110011) + '\x35' + '\x32', 0b1000), ehT0Px3KOsy9(chr(2022 - 1974) + '\157' + chr(0b110011) + '\065' + chr(0b11100 + 0o24), 48717 - 48709), ehT0Px3KOsy9(chr(1182 - 1134) + chr(5491 - 5380) + chr(51), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110011) + chr(1760 - 1712) + chr(1941 - 1893), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(52) + chr(1905 - 1857), ord("\x08")), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(0b1011 + 0o144) + '\x35' + '\x30', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x35' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b1010 + 0o46) + '\157' + chr(0b110001) + chr(0b1110 + 0o44) + chr(0b101111 + 0o6), ord("\x08")), ehT0Px3KOsy9(chr(892 - 844) + chr(0b1101111) + '\063' + '\064' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(111) + chr(1408 - 1358) + chr(1137 - 1084) + chr(49), 64417 - 64409), ehT0Px3KOsy9(chr(0b110000) + chr(9583 - 9472) + '\x32' + '\x37' + '\x32', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(2020 - 1965) + chr(0b101 + 0o55), 30162 - 30154), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001) + '\065' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\060' + chr(9752 - 9641) + '\061' + '\x31' + chr(0b10001 + 0o42), 0o10), ehT0Px3KOsy9(chr(48) + chr(4868 - 4757) + chr(2171 - 2122) + chr(0b110000) + chr(0b110 + 0o56), 0b1000), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(111) + '\x31' + chr(0b110100) + chr(1738 - 1688), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + '\x31' + chr(50), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11000 + 0o31) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(1109 - 1061) + chr(0b1011 + 0o144) + chr(416 - 365) + chr(1510 - 1458) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(2764 - 2653) + chr(0b110001) + chr(2024 - 1969) + chr(0b110001 + 0o6), 0o10), ehT0Px3KOsy9('\060' + chr(0b0 + 0o157) + chr(0b101001 + 0o10) + '\x32' + chr(464 - 414), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x33' + chr(53), 49291 - 49283), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b1010000 + 0o37) + chr(51) + '\x35' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b100 + 0o56) + '\064' + chr(796 - 743), 0o10), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b11001 + 0o126) + '\x35' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + chr(48) + chr(889 - 837), 8), ehT0Px3KOsy9(chr(48) + '\157' + '\x33' + chr(50) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + '\063' + '\061' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(49) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1010110 + 0o31) + chr(0b110001) + '\066', 34934 - 34926), ehT0Px3KOsy9('\x30' + chr(0b100 + 0o153) + chr(0b110011) + chr(0b110010), 0b1000), ehT0Px3KOsy9('\x30' + chr(9713 - 9602) + chr(49) + '\x36' + '\062', 42005 - 41997), ehT0Px3KOsy9(chr(0b10011 + 0o35) + '\x6f' + chr(138 - 87) + chr(0b110101) + chr(0b110101), 11454 - 11446), ehT0Px3KOsy9('\x30' + chr(111) + '\062' + chr(0b101000 + 0o11), ord("\x08")), ehT0Px3KOsy9(chr(848 - 800) + '\157' + chr(0b110001) + chr(1477 - 1422), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(4031 - 3920) + chr(0b110010) + chr(55) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(53) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1901 - 1852) + chr(0b110110) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b11010 + 0o27) + chr(0b110101) + chr(0b100 + 0o61), 0o10), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(2724 - 2613) + '\x33' + '\x37' + '\x33', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(111) + chr(0b110101) + chr(0b10010 + 0o36), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xc4'), chr(3609 - 3509) + '\x65' + chr(0b1100011) + chr(111) + '\x64' + '\145')(chr(117) + '\164' + chr(1947 - 1845) + chr(0b1110 + 0o37) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def aOF5qQnUQLzb(oVre8I6UXc3b, k0yN1BuOulXb, P51q6yx_tuae):
q6nq50xpSJyl = {xafqLlk3kkUe(SXOLrMavuUCe(b'\x86\x8db\xb3\x14w^$\x91\xc8\xc8_\x1c'), chr(0b110000 + 0o64) + chr(0b101100 + 0o71) + chr(99) + chr(0b101010 + 0o105) + chr(0b1100100) + '\145')('\165' + '\164' + '\x66' + chr(0b101101) + chr(0b110100 + 0o4)): HDCDSTeou2Ry.least_squares_generator_loss, xafqLlk3kkUe(SXOLrMavuUCe(b'\x89\x9al\xb3\x13wH;\x90\xdb\xd5J\x16'), '\144' + chr(0b1 + 0o144) + chr(4041 - 3942) + '\x6f' + '\144' + chr(101))(chr(0b1110101) + '\x74' + '\146' + chr(0b10010 + 0o33) + chr(56)): HDCDSTeou2Ry.modified_generator_loss, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9d\x89p\xb3\x05Z^!\x81\xc0\xd4'), chr(100) + chr(0b111000 + 0o55) + '\x63' + chr(0b1000001 + 0o56) + '\x64' + chr(101))('\x75' + '\x74' + chr(102) + '\x2d' + chr(56)): HDCDSTeou2Ry.wasserstein_generator_loss}
eD9EoUx4W7ks = oVre8I6UXc3b.discriminator(k0yN1BuOulXb)
ALxsVVQZM1qu = IDJ2eXGCBCDu.reduce_mean(eD9EoUx4W7ks)
xafqLlk3kkUe(IDJ2eXGCBCDu.summary, xafqLlk3kkUe(SXOLrMavuUCe(b'\x99\x8bb\xac\x01Z'), chr(3352 - 3252) + '\145' + '\x63' + chr(111) + '\144' + chr(5817 - 5716))('\165' + chr(0b1110000 + 0o4) + '\x66' + chr(818 - 773) + chr(165 - 109)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x87\x8db\xae?NL>\x81\xf6\xd6U\x08"0\x11'), chr(0b1100100) + '\145' + '\143' + chr(0b101011 + 0o104) + chr(0b101011 + 0o71) + '\145')(chr(6646 - 6529) + chr(0b1110100) + '\x66' + '\x2d' + chr(0b101111 + 0o11)), ALxsVVQZM1qu)
bVZu0DoaBcov = q6nq50xpSJyl[oVre8I6UXc3b.hparams.gan_loss]
XEZ72GUlPanh = bVZu0DoaBcov(discriminator_gen_outputs=eD9EoUx4W7ks, add_summaries=ehT0Px3KOsy9(chr(48) + chr(2367 - 2256) + chr(0b11101 + 0o24), 0b1000))
HkgAlNV6IHQ0 = -bVZu0DoaBcov(discriminator_gen_outputs=P51q6yx_tuae, add_summaries=ehT0Px3KOsy9(chr(0b110000) + chr(0b11100 + 0o123) + chr(49), 8))
return (XEZ72GUlPanh, HkgAlNV6IHQ0)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/video/savp.py
|
NextFrameSavpBase.get_gan_loss
|
def get_gan_loss(self, true_frames, gen_frames, name):
"""Get the discriminator + generator loss at every step.
This performs an 1:1 update of the discriminator and generator at every
step.
Args:
true_frames: 5-D Tensor of shape (num_steps, batch_size, H, W, C)
Assumed to be ground truth.
gen_frames: 5-D Tensor of shape (num_steps, batch_size, H, W, C)
Assumed to be fake.
name: discriminator scope.
Returns:
loss: 0-D Tensor, with d_loss + g_loss
"""
# D - STEP
with tf.variable_scope("%s_discriminator" % name, reuse=tf.AUTO_REUSE):
gan_d_loss, _, fake_logits_stop = self.d_step(
true_frames, gen_frames)
# G - STEP
with tf.variable_scope("%s_discriminator" % name, reuse=True):
gan_g_loss_pos_d, gan_g_loss_neg_d = self.g_step(
gen_frames, fake_logits_stop)
gan_g_loss = gan_g_loss_pos_d + gan_g_loss_neg_d
tf.summary.scalar("gan_loss_%s" % name, gan_g_loss_pos_d + gan_d_loss)
if self.hparams.gan_optimization == "joint":
gan_loss = gan_g_loss + gan_d_loss
else:
curr_step = self.get_iteration_num()
gan_loss = tf.cond(
tf.logical_not(curr_step % 2 == 0), lambda: gan_g_loss,
lambda: gan_d_loss)
return gan_loss
|
python
|
def get_gan_loss(self, true_frames, gen_frames, name):
"""Get the discriminator + generator loss at every step.
This performs an 1:1 update of the discriminator and generator at every
step.
Args:
true_frames: 5-D Tensor of shape (num_steps, batch_size, H, W, C)
Assumed to be ground truth.
gen_frames: 5-D Tensor of shape (num_steps, batch_size, H, W, C)
Assumed to be fake.
name: discriminator scope.
Returns:
loss: 0-D Tensor, with d_loss + g_loss
"""
# D - STEP
with tf.variable_scope("%s_discriminator" % name, reuse=tf.AUTO_REUSE):
gan_d_loss, _, fake_logits_stop = self.d_step(
true_frames, gen_frames)
# G - STEP
with tf.variable_scope("%s_discriminator" % name, reuse=True):
gan_g_loss_pos_d, gan_g_loss_neg_d = self.g_step(
gen_frames, fake_logits_stop)
gan_g_loss = gan_g_loss_pos_d + gan_g_loss_neg_d
tf.summary.scalar("gan_loss_%s" % name, gan_g_loss_pos_d + gan_d_loss)
if self.hparams.gan_optimization == "joint":
gan_loss = gan_g_loss + gan_d_loss
else:
curr_step = self.get_iteration_num()
gan_loss = tf.cond(
tf.logical_not(curr_step % 2 == 0), lambda: gan_g_loss,
lambda: gan_d_loss)
return gan_loss
|
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Get the discriminator + generator loss at every step.
This performs an 1:1 update of the discriminator and generator at every
step.
Args:
true_frames: 5-D Tensor of shape (num_steps, batch_size, H, W, C)
Assumed to be ground truth.
gen_frames: 5-D Tensor of shape (num_steps, batch_size, H, W, C)
Assumed to be fake.
name: discriminator scope.
Returns:
loss: 0-D Tensor, with d_loss + g_loss
|
[
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272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/video/savp.py#L228-L262
|
train
|
This function performs an 1 - 1 update of the discriminator and generator at every 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('\x30' + '\157' + '\062' + '\064' + chr(0b110000), 12048 - 12040), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(10768 - 10657) + chr(0b11101 + 0o26) + chr(0b110001) + chr(0b10010 + 0o42), 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(0b1101111) + chr(1386 - 1336) + chr(51) + '\063', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1001001 + 0o46) + chr(2230 - 2181) + chr(52) + chr(754 - 699), 16781 - 16773), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\157' + chr(51) + '\x37' + '\x34', 0o10), ehT0Px3KOsy9(chr(1317 - 1269) + '\157' + '\x32' + '\x37', 0o10), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(111) + chr(0b110100) + chr(277 - 225), 41238 - 41230), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + chr(1257 - 1209) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(3993 - 3882) + chr(0b110011) + chr(0b110111) + chr(52), 8), ehT0Px3KOsy9(chr(48) + chr(9028 - 8917) + chr(52) + '\x35', 28279 - 28271), ehT0Px3KOsy9('\060' + chr(3883 - 3772) + chr(49) + chr(549 - 501) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(818 - 707) + '\065', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110101 + 0o0) + '\x35', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b11010 + 0o27) + chr(54) + '\064', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + '\067' + '\061', 35528 - 35520), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110100) + chr(2747 - 2692), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b101 + 0o54) + chr(49) + chr(1914 - 1865), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101000 + 0o7) + chr(0b110010) + chr(51) + chr(1467 - 1417), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(865 - 814) + chr(0b101110 + 0o3) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(1656 - 1608) + chr(0b1101111) + '\x36' + '\x35', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b100101 + 0o14) + chr(0b110000) + chr(51), 61919 - 61911), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + '\064' + chr(0b10111 + 0o35), 41024 - 41016), ehT0Px3KOsy9('\060' + '\157' + chr(2474 - 2424) + chr(0b110100) + '\067', 11848 - 11840), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + chr(50) + chr(51), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + chr(0b10110 + 0o36) + '\x33', 47376 - 47368), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b0 + 0o63) + chr(52) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + '\x35' + '\x37', 0b1000), ehT0Px3KOsy9('\060' + chr(10601 - 10490) + chr(586 - 535) + '\063' + '\063', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b101000 + 0o107) + chr(321 - 271) + chr(0b110011) + chr(940 - 889), 8), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b10011 + 0o36) + '\x30' + chr(0b110011), 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1198 - 1147) + chr(0b101111 + 0o5) + chr(138 - 84), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + '\x33' + '\x32', 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(724 - 673) + '\061' + '\x37', 0o10), ehT0Px3KOsy9('\x30' + chr(0b101100 + 0o103) + chr(0b110011) + '\x30' + chr(0b110100), 10155 - 10147), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1101111) + chr(0b110010) + chr(54) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + '\x6f' + chr(0b110010) + '\x36' + '\062', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1010100 + 0o33) + '\x31' + '\x31' + chr(52), 7662 - 7654), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + '\067' + chr(0b110001 + 0o0), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b101000 + 0o107) + '\066' + chr(0b110010 + 0o1), ord("\x08")), ehT0Px3KOsy9(chr(1053 - 1005) + '\157' + chr(0b10010 + 0o44) + chr(1111 - 1061), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(111) + '\x35' + '\060', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e'), chr(100) + '\x65' + chr(7881 - 7782) + '\157' + '\x64' + chr(0b11110 + 0o107))(chr(117) + '\164' + chr(0b1100110) + chr(0b100110 + 0o7) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def PYRn4f37Bxyg(oVre8I6UXc3b, j_l58HFkYlQH, k0yN1BuOulXb, AIvJRzLdDfgF):
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd6\xad\xe9\x0e\x9duH%\xa3V!j]\x11'), '\144' + chr(5774 - 5673) + chr(0b1100011) + chr(0b1101111) + chr(2803 - 2703) + chr(101))(chr(0b1110101) + '\164' + chr(0b1011110 + 0o10) + chr(0b10111 + 0o26) + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x85\xbf\xc4\x03\x95dG2\x95H+kL\x00\x96U'), chr(0b1100100) + chr(8200 - 8099) + '\x63' + chr(2462 - 2351) + '\144' + chr(0b1100101))('\x75' + chr(4619 - 4503) + chr(7022 - 6920) + chr(45) + '\070') % AIvJRzLdDfgF, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe1\x99\xcf(\xa3Ea\x15\xaf`'), '\x64' + chr(0b1100101) + chr(99) + chr(0b111101 + 0o62) + '\144' + chr(0b1100101))(chr(0b1110101) + chr(535 - 419) + chr(5769 - 5667) + chr(160 - 115) + chr(0b111000)))):
(Yd3FyKjonHV1, VNGQdHSFPrso, P51q6yx_tuae) = oVre8I6UXc3b.d_step(j_l58HFkYlQH, k0yN1BuOulXb)
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd6\xad\xe9\x0e\x9duH%\xa3V!j]\x11'), chr(0b101011 + 0o71) + chr(0b111111 + 0o46) + '\x63' + chr(11236 - 11125) + chr(4685 - 4585) + chr(101))(chr(2267 - 2150) + chr(2308 - 2192) + chr(0b110101 + 0o61) + chr(646 - 601) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x85\xbf\xc4\x03\x95dG2\x95H+kL\x00\x96U'), chr(0b1100100) + '\x65' + chr(0b1100011) + '\157' + '\x64' + '\145')('\165' + chr(7110 - 6994) + chr(0b1010 + 0o134) + chr(45) + chr(0b111000)) % AIvJRzLdDfgF, reuse=ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31', ord("\x08"))):
(XEZ72GUlPanh, HkgAlNV6IHQ0) = oVre8I6UXc3b.g_step(k0yN1BuOulXb, P51q6yx_tuae)
ZJcxykapR7UL = XEZ72GUlPanh + HkgAlNV6IHQ0
xafqLlk3kkUe(IDJ2eXGCBCDu.summary, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd3\xaf\xfa\x0b\x9de'), chr(0b10110 + 0o116) + '\145' + chr(99) + chr(0b1101111) + chr(0b1100100) + chr(101))(chr(0b1110011 + 0o2) + chr(11745 - 11629) + chr(102) + chr(0b101101) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xc7\xad\xf58\x90xW3\xa3\x001'), chr(9659 - 9559) + chr(0b101 + 0o140) + chr(5156 - 5057) + chr(0b1011000 + 0o27) + '\x64' + chr(0b1001010 + 0o33))('\165' + '\164' + '\146' + chr(45) + chr(56)) % AIvJRzLdDfgF, XEZ72GUlPanh + Yd3FyKjonHV1)
if xafqLlk3kkUe(oVre8I6UXc3b.hparams, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc7\xad\xf58\x93gP)\x91L8dY\x1d\x96I'), chr(4272 - 4172) + '\145' + chr(0b111000 + 0o53) + chr(0b1101111) + chr(100) + chr(0b1100101))(chr(4758 - 4641) + chr(5316 - 5200) + chr(0b1010110 + 0o20) + chr(88 - 43) + chr(0b111000))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\xca\xa3\xf2\t\x88'), chr(0b1001110 + 0o26) + '\145' + chr(0b1011101 + 0o6) + chr(111) + '\144' + '\145')('\x75' + chr(10397 - 10281) + chr(0b1100110) + '\x2d' + chr(1298 - 1242)):
UTGcQfM6VMLD = ZJcxykapR7UL + Yd3FyKjonHV1
else:
LuNzNXAdQCGM = oVre8I6UXc3b.get_iteration_num()
UTGcQfM6VMLD = IDJ2eXGCBCDu.cond(IDJ2eXGCBCDu.logical_not(LuNzNXAdQCGM % ehT0Px3KOsy9('\060' + '\x6f' + '\062', 0b1000) == ehT0Px3KOsy9('\x30' + '\157' + '\060', 0o10)), lambda : ZJcxykapR7UL, lambda : Yd3FyKjonHV1)
return UTGcQfM6VMLD
|
tensorflow/tensor2tensor
|
tensor2tensor/models/video/savp.py
|
NextFrameSavpBase.get_extra_loss
|
def get_extra_loss(self, latent_means=None, latent_stds=None,
true_frames=None, gen_frames=None):
"""Gets extra loss from VAE and GAN."""
if not self.is_training:
return 0.0
vae_loss, d_vae_loss, d_gan_loss = 0.0, 0.0, 0.0
# Use sv2p's KL divergence computation.
if self.hparams.use_vae:
vae_loss = super(NextFrameSavpBase, self).get_extra_loss(
latent_means=latent_means, latent_stds=latent_stds)
if self.hparams.use_gan:
# Strip out the first context_frames for the true_frames
# Strip out the first context_frames - 1 for the gen_frames
context_frames = self.hparams.video_num_input_frames
true_frames = tf.stack(
tf.unstack(true_frames, axis=0)[context_frames:])
# discriminator for VAE.
if self.hparams.use_vae:
gen_enc_frames = tf.stack(
tf.unstack(gen_frames, axis=0)[context_frames-1:])
d_vae_loss = self.get_gan_loss(true_frames, gen_enc_frames, name="vae")
# discriminator for GAN.
gen_prior_frames = tf.stack(
tf.unstack(self.gen_prior_video, axis=0)[context_frames-1:])
d_gan_loss = self.get_gan_loss(true_frames, gen_prior_frames, name="gan")
return (
vae_loss + self.hparams.gan_loss_multiplier * d_gan_loss +
self.hparams.gan_vae_loss_multiplier * d_vae_loss)
|
python
|
def get_extra_loss(self, latent_means=None, latent_stds=None,
true_frames=None, gen_frames=None):
"""Gets extra loss from VAE and GAN."""
if not self.is_training:
return 0.0
vae_loss, d_vae_loss, d_gan_loss = 0.0, 0.0, 0.0
# Use sv2p's KL divergence computation.
if self.hparams.use_vae:
vae_loss = super(NextFrameSavpBase, self).get_extra_loss(
latent_means=latent_means, latent_stds=latent_stds)
if self.hparams.use_gan:
# Strip out the first context_frames for the true_frames
# Strip out the first context_frames - 1 for the gen_frames
context_frames = self.hparams.video_num_input_frames
true_frames = tf.stack(
tf.unstack(true_frames, axis=0)[context_frames:])
# discriminator for VAE.
if self.hparams.use_vae:
gen_enc_frames = tf.stack(
tf.unstack(gen_frames, axis=0)[context_frames-1:])
d_vae_loss = self.get_gan_loss(true_frames, gen_enc_frames, name="vae")
# discriminator for GAN.
gen_prior_frames = tf.stack(
tf.unstack(self.gen_prior_video, axis=0)[context_frames-1:])
d_gan_loss = self.get_gan_loss(true_frames, gen_prior_frames, name="gan")
return (
vae_loss + self.hparams.gan_loss_multiplier * d_gan_loss +
self.hparams.gan_vae_loss_multiplier * d_vae_loss)
|
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"true_frames",
",",
"gen_prior_frames",
",",
"name",
"=",
"\"gan\"",
")",
"return",
"(",
"vae_loss",
"+",
"self",
".",
"hparams",
".",
"gan_loss_multiplier",
"*",
"d_gan_loss",
"+",
"self",
".",
"hparams",
".",
"gan_vae_loss_multiplier",
"*",
"d_vae_loss",
")"
] |
Gets extra loss from VAE and GAN.
|
[
"Gets",
"extra",
"loss",
"from",
"VAE",
"and",
"GAN",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/video/savp.py#L264-L296
|
train
|
Gets extra loss from VAE and GAN.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(475 - 427) + '\x6f' + chr(49) + chr(0b100100 + 0o15) + chr(0b1 + 0o64), 0o10), ehT0Px3KOsy9(chr(1971 - 1923) + '\157' + chr(50) + chr(1323 - 1268) + chr(51), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(0b110101) + '\064', 0b1000), ehT0Px3KOsy9(chr(1829 - 1781) + chr(1217 - 1106) + '\x36' + chr(1874 - 1824), ord("\x08")), ehT0Px3KOsy9(chr(593 - 545) + chr(0b1101111) + '\x33' + '\065' + '\065', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(1938 - 1888) + chr(2468 - 2418), 0o10), ehT0Px3KOsy9(chr(1068 - 1020) + chr(0b11 + 0o154) + '\063' + chr(0b110001) + chr(54), 27885 - 27877), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + '\x30' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(9412 - 9301) + '\x31' + chr(0b110011) + chr(1147 - 1098), 19707 - 19699), ehT0Px3KOsy9('\060' + chr(0b0 + 0o157) + chr(0b110001) + '\067' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x36' + chr(0b110000), 63994 - 63986), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + chr(173 - 118) + '\x37', 24738 - 24730), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(346 - 296) + chr(219 - 167) + '\063', 0o10), ehT0Px3KOsy9(chr(102 - 54) + chr(0b100 + 0o153) + chr(0b10000 + 0o41) + chr(0b110011) + '\x31', 8), ehT0Px3KOsy9(chr(263 - 215) + chr(0b1001100 + 0o43) + '\062' + chr(0b110010) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + '\x37' + chr(0b11111 + 0o23), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\063' + chr(49) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(11489 - 11378) + chr(0b10000 + 0o45) + '\063', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51) + chr(0b10101 + 0o36), 17731 - 17723), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b1101111) + '\x33' + chr(0b100100 + 0o21), 38816 - 38808), ehT0Px3KOsy9('\x30' + '\157' + chr(0b11100 + 0o27) + chr(0b1010 + 0o50) + chr(49), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b111110 + 0o61) + chr(0b110111) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(523 - 475) + '\x6f' + chr(0b110100) + chr(639 - 589), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(2176 - 2124), 31529 - 31521), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(0b1101111) + chr(0b100111 + 0o13) + '\x32' + chr(953 - 905), ord("\x08")), ehT0Px3KOsy9('\060' + chr(9636 - 9525) + chr(2193 - 2142) + '\x32' + chr(55), 22346 - 22338), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(215 - 161) + chr(0b11001 + 0o35), 0o10), ehT0Px3KOsy9('\x30' + chr(9903 - 9792) + chr(0b101001 + 0o12) + chr(0b101010 + 0o11) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1101111) + chr(824 - 774) + '\x37' + '\066', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x32' + '\x33' + '\067', 52524 - 52516), ehT0Px3KOsy9(chr(48) + chr(0b1100000 + 0o17) + '\x32' + chr(82 - 34), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(2509 - 2398) + chr(1538 - 1490), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(8870 - 8759) + chr(50) + '\064' + chr(0b110010), 48998 - 48990), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + chr(48) + chr(49), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110 + 0o55) + '\x34' + chr(2108 - 2058), ord("\x08")), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\x6f' + '\x32' + '\x34' + '\x30', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + chr(930 - 881) + chr(53), 0o10), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\x6f' + chr(0b10010 + 0o42) + chr(2407 - 2353), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(2535 - 2483) + chr(631 - 580), 60863 - 60855), ehT0Px3KOsy9('\060' + chr(0b10110 + 0o131) + chr(2218 - 2169) + chr(0b0 + 0o64) + chr(51), 52094 - 52086)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x35' + '\x30', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'c'), '\144' + chr(9799 - 9698) + chr(99) + chr(111) + '\144' + chr(9583 - 9482))('\165' + chr(3887 - 3771) + chr(0b1000000 + 0o46) + chr(512 - 467) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def vYllZk0NaJnX(oVre8I6UXc3b, Nhq2KQIpHL6r=None, muHX0gW5VWDQ=None, j_l58HFkYlQH=None, k0yN1BuOulXb=None):
if not xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'$\xc8\xf3F\x9fs\xa7\xae0\x15W'), chr(0b1100001 + 0o3) + chr(9269 - 9168) + '\x63' + chr(0b1000111 + 0o50) + chr(0b1100100) + chr(0b1011011 + 0o12))(chr(0b1110101) + chr(116) + chr(0b110010 + 0o64) + chr(2024 - 1979) + '\x38')):
return 0.0
(pSlwNo408Y91, wuQEnPGh_Du5, PvmexPZHeywO) = (0.0, 0.0, 0.0)
if xafqLlk3kkUe(oVre8I6UXc3b.hparams, xafqLlk3kkUe(SXOLrMavuUCe(b'8\xc8\xc9m\x9bs\xab'), chr(100) + '\x65' + '\143' + chr(0b1101111) + '\144' + '\145')(chr(0b1110101) + chr(0b1110100) + chr(6799 - 6697) + '\055' + chr(56))):
pSlwNo408Y91 = KNx0Ujaz9UM0(wYW6nSxjEYpf, oVre8I6UXc3b).get_extra_loss(latent_means=Nhq2KQIpHL6r, latent_stds=muHX0gW5VWDQ)
if xafqLlk3kkUe(oVre8I6UXc3b.hparams, xafqLlk3kkUe(SXOLrMavuUCe(b'8\xc8\xc9m\x8as\xa0'), '\144' + '\x65' + '\143' + '\x6f' + chr(0b1011010 + 0o12) + chr(101))(chr(117) + '\x74' + '\x66' + '\055' + '\x38')):
VsDnLVITZVNd = oVre8I6UXc3b.hparams.UUXW9NWPZxPI
j_l58HFkYlQH = IDJ2eXGCBCDu.stack(IDJ2eXGCBCDu.unstack(j_l58HFkYlQH, axis=ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b110101 + 0o72) + chr(48), 8))[VsDnLVITZVNd:])
if xafqLlk3kkUe(oVre8I6UXc3b.hparams, xafqLlk3kkUe(SXOLrMavuUCe(b'8\xc8\xc9m\x9bs\xab'), chr(100) + '\x65' + chr(0b1100011) + chr(1613 - 1502) + chr(100) + chr(1668 - 1567))(chr(5815 - 5698) + chr(0b1000001 + 0o63) + chr(1826 - 1724) + chr(651 - 606) + '\070')):
iix290r8xad6 = IDJ2eXGCBCDu.stack(IDJ2eXGCBCDu.unstack(k0yN1BuOulXb, axis=ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b1101111) + chr(0b100101 + 0o13), 8))[VsDnLVITZVNd - ehT0Px3KOsy9(chr(48) + chr(111) + chr(49), 33401 - 33393):])
wuQEnPGh_Du5 = oVre8I6UXc3b.get_gan_loss(j_l58HFkYlQH, iix290r8xad6, name=xafqLlk3kkUe(SXOLrMavuUCe(b';\xda\xc9'), '\144' + chr(328 - 227) + '\143' + chr(0b111010 + 0o65) + chr(0b1100100) + '\x65')('\x75' + chr(8219 - 8103) + chr(0b1100110) + chr(0b101101) + '\x38'))
LZqUrH0PiBAD = IDJ2eXGCBCDu.stack(IDJ2eXGCBCDu.unstack(oVre8I6UXc3b.gen_prior_video, axis=ehT0Px3KOsy9('\060' + chr(0b100101 + 0o112) + chr(0b1011 + 0o45), 8))[VsDnLVITZVNd - ehT0Px3KOsy9('\060' + chr(1184 - 1073) + '\061', 8):])
PvmexPZHeywO = oVre8I6UXc3b.get_gan_loss(j_l58HFkYlQH, LZqUrH0PiBAD, name=xafqLlk3kkUe(SXOLrMavuUCe(b'*\xda\xc2'), chr(5214 - 5114) + chr(0b1100101) + chr(0b1100011) + chr(0b1101111) + chr(3071 - 2971) + '\145')(chr(949 - 832) + '\x74' + chr(3852 - 3750) + chr(0b11100 + 0o21) + chr(0b1111 + 0o51)))
return pSlwNo408Y91 + xafqLlk3kkUe(oVre8I6UXc3b.hparams, xafqLlk3kkUe(SXOLrMavuUCe(b'*\xda\xc2m\x81}\xbd\xb3\x06\x16E\x13\xd70\xe3\xd6\xa6Ni'), chr(0b1000100 + 0o40) + '\145' + chr(0b1100011) + chr(111) + '\144' + chr(0b10010 + 0o123))(chr(4042 - 3925) + '\x74' + '\146' + '\055' + '\070')) * PvmexPZHeywO + xafqLlk3kkUe(oVre8I6UXc3b.hparams, xafqLlk3kkUe(SXOLrMavuUCe(b'*\xda\xc2m\x9bs\xab\x9f5\x14C\x0c\xfc4\xe6\xd6\xbbBkq\xb8_P'), '\144' + chr(5345 - 5244) + chr(0b1100011) + chr(5448 - 5337) + chr(0b111010 + 0o52) + '\145')(chr(6380 - 6263) + '\x74' + chr(102) + chr(0b101101) + '\x38')) * wuQEnPGh_Du5
|
tensorflow/tensor2tensor
|
tensor2tensor/models/video/savp.py
|
NextFrameSavpBase.pad_conv3d_lrelu
|
def pad_conv3d_lrelu(self, activations, n_filters, kernel_size, strides,
scope):
"""Pad, apply 3-D convolution and leaky relu."""
padding = [[0, 0], [1, 1], [1, 1], [1, 1], [0, 0]]
# tf.nn.conv3d accepts a list of 5 values for strides
# with first and last value equal to 1
if isinstance(strides, numbers.Integral):
strides = [strides] * 3
strides = [1] + strides + [1]
# Filter_shape = [K, K, K, num_input, num_output]
filter_shape = (
[kernel_size]*3 + activations.shape[-1:].as_list() + [n_filters])
with tf.variable_scope(scope, reuse=tf.AUTO_REUSE):
conv_filter = tf.get_variable(
"conv_filter", shape=filter_shape,
initializer=tf.truncated_normal_initializer(stddev=0.02))
if self.hparams.use_spectral_norm:
conv_filter, assign_op = common_layers.apply_spectral_norm(conv_filter)
if self.is_training:
tf.add_to_collection(tf.GraphKeys.UPDATE_OPS, assign_op)
padded = tf.pad(activations, padding)
convolved = tf.nn.conv3d(
padded, conv_filter, strides=strides, padding="VALID")
rectified = tf.nn.leaky_relu(convolved, alpha=0.2)
return rectified
|
python
|
def pad_conv3d_lrelu(self, activations, n_filters, kernel_size, strides,
scope):
"""Pad, apply 3-D convolution and leaky relu."""
padding = [[0, 0], [1, 1], [1, 1], [1, 1], [0, 0]]
# tf.nn.conv3d accepts a list of 5 values for strides
# with first and last value equal to 1
if isinstance(strides, numbers.Integral):
strides = [strides] * 3
strides = [1] + strides + [1]
# Filter_shape = [K, K, K, num_input, num_output]
filter_shape = (
[kernel_size]*3 + activations.shape[-1:].as_list() + [n_filters])
with tf.variable_scope(scope, reuse=tf.AUTO_REUSE):
conv_filter = tf.get_variable(
"conv_filter", shape=filter_shape,
initializer=tf.truncated_normal_initializer(stddev=0.02))
if self.hparams.use_spectral_norm:
conv_filter, assign_op = common_layers.apply_spectral_norm(conv_filter)
if self.is_training:
tf.add_to_collection(tf.GraphKeys.UPDATE_OPS, assign_op)
padded = tf.pad(activations, padding)
convolved = tf.nn.conv3d(
padded, conv_filter, strides=strides, padding="VALID")
rectified = tf.nn.leaky_relu(convolved, alpha=0.2)
return rectified
|
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"leaky_relu",
"(",
"convolved",
",",
"alpha",
"=",
"0.2",
")",
"return",
"rectified"
] |
Pad, apply 3-D convolution and leaky relu.
|
[
"Pad",
"apply",
"3",
"-",
"D",
"convolution",
"and",
"leaky",
"relu",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/video/savp.py#L298-L327
|
train
|
Pad apply 3 - D convolution and leaky 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('\060' + '\x6f' + chr(270 - 221) + chr(0b110000) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b1100011 + 0o14) + chr(51) + chr(0b101010 + 0o14) + chr(0b101111 + 0o2), 1383 - 1375), ehT0Px3KOsy9('\x30' + chr(0b1000111 + 0o50) + chr(0b110011) + chr(49) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1011110 + 0o21) + '\x37' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + '\061' + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(0b110100) + chr(2104 - 2051), 4723 - 4715), ehT0Px3KOsy9('\x30' + chr(7595 - 7484) + chr(0b110001) + chr(54) + '\062', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + '\x33' + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(1181 - 1133) + chr(8334 - 8223) + chr(0b101010 + 0o7) + '\060', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + '\x31' + '\064', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(1859 - 1748) + chr(0b11 + 0o60) + chr(52) + chr(1650 - 1601), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + chr(0b110001 + 0o3) + chr(3003 - 2948), 0o10), ehT0Px3KOsy9('\x30' + chr(8392 - 8281) + chr(0b101100 + 0o6) + chr(0b110100) + '\x35', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011) + chr(774 - 725) + '\x31', 50758 - 50750), ehT0Px3KOsy9(chr(956 - 908) + chr(7738 - 7627) + chr(0b11101 + 0o31) + chr(1363 - 1310), 0b1000), ehT0Px3KOsy9(chr(2150 - 2102) + chr(111) + chr(52) + chr(52), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\061' + '\061' + chr(961 - 906), 0b1000), ehT0Px3KOsy9(chr(340 - 292) + chr(0b1100111 + 0o10) + chr(49) + '\x34' + chr(52), 53026 - 53018), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51) + chr(0b110100), 58428 - 58420), ehT0Px3KOsy9(chr(0b100010 + 0o16) + '\157' + chr(0b110011 + 0o1) + chr(0b11101 + 0o32), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b11001 + 0o126) + chr(0b10101 + 0o36) + '\066' + chr(1715 - 1663), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b0 + 0o62) + '\x34' + '\064', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + '\060' + '\x30', 8812 - 8804), ehT0Px3KOsy9(chr(48) + chr(3203 - 3092) + chr(51) + '\x33' + chr(49), 0b1000), ehT0Px3KOsy9('\060' + chr(0b100011 + 0o114) + chr(2414 - 2363) + chr(0b110110) + '\x35', 32955 - 32947), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10110 + 0o34) + '\x31' + chr(0b110100), 8), ehT0Px3KOsy9(chr(2220 - 2172) + '\x6f' + chr(1683 - 1632) + chr(0b110101) + chr(1589 - 1536), 0b1000), ehT0Px3KOsy9(chr(0b101 + 0o53) + '\157' + chr(0b110010) + '\x36' + '\061', 0o10), ehT0Px3KOsy9('\060' + chr(10374 - 10263) + '\x33' + chr(0b110100 + 0o2) + '\x36', 49469 - 49461), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + chr(340 - 286) + chr(53), 0o10), ehT0Px3KOsy9(chr(48) + chr(6897 - 6786) + '\062' + '\067' + chr(51), 23820 - 23812), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + chr(0b100111 + 0o15), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2182 - 2132) + chr(275 - 221) + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(54) + '\x37', ord("\x08")), ehT0Px3KOsy9('\060' + chr(10603 - 10492) + '\x31' + chr(239 - 188) + '\x31', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + chr(1242 - 1188) + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + '\x31', 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\063' + '\x30' + '\063', 0b1000), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b110110 + 0o71) + chr(51) + chr(0b110101) + '\x31', 26097 - 26089), ehT0Px3KOsy9(chr(48) + '\157' + chr(872 - 821) + chr(0b110000) + '\061', 49311 - 49303)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(0b1101111) + '\x35' + chr(1788 - 1740), 18696 - 18688)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'k'), chr(1880 - 1780) + chr(6511 - 6410) + chr(0b101010 + 0o71) + chr(0b1101111) + chr(0b1100100) + chr(0b1011011 + 0o12))(chr(0b1110101) + chr(927 - 811) + '\x66' + chr(45) + chr(1553 - 1497)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def fDV2rrDYqW88(oVre8I6UXc3b, mgDWDDVSXPyH, Hug1D32ZEDaD, m6gwVXy4D3Au, r8knJmMTTKwv, CJBHNoj4zKoT):
TFLseEYASEKG = [[ehT0Px3KOsy9(chr(1135 - 1087) + chr(111) + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b11111 + 0o21), 8)], [ehT0Px3KOsy9(chr(0b110000) + chr(0b101010 + 0o105) + chr(49), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x31', 8)], [ehT0Px3KOsy9('\060' + chr(6163 - 6052) + chr(0b110001), 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(97 - 48), 8)], [ehT0Px3KOsy9('\x30' + chr(0b10 + 0o155) + chr(0b11100 + 0o25), 8), ehT0Px3KOsy9(chr(48) + chr(7702 - 7591) + chr(2155 - 2106), 8)], [ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\060', 8), ehT0Px3KOsy9('\060' + chr(6916 - 6805) + '\060', 8)]]
if PlSM16l2KDPD(r8knJmMTTKwv, xafqLlk3kkUe(uU3ppLOUY_t7, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0c\x9f\xbeX)\x17\x13\xf4'), '\144' + chr(101) + '\143' + '\157' + '\144' + chr(101))(chr(117) + chr(116) + chr(0b1100110) + '\055' + chr(983 - 927)))):
r8knJmMTTKwv = [r8knJmMTTKwv] * ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b11100 + 0o27), 0b1000)
r8knJmMTTKwv = [ehT0Px3KOsy9('\x30' + chr(8388 - 8277) + chr(777 - 728), 8)] + r8knJmMTTKwv + [ehT0Px3KOsy9('\060' + '\157' + chr(0b110001), 8)]
be5Q8MSuNI1T = [m6gwVXy4D3Au] * ehT0Px3KOsy9(chr(0b10101 + 0o33) + '\x6f' + chr(2038 - 1987), 8) + mgDWDDVSXPyH.shape[-ehT0Px3KOsy9(chr(982 - 934) + '\x6f' + chr(49), 8):].as_list() + [Hug1D32ZEDaD]
with xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'3\x90\xb8T/\x07\x1e\xfdW\xff\x82\x88\xd5\xac'), chr(100) + chr(101) + chr(0b111 + 0o134) + chr(0b100 + 0o153) + '\144' + '\x65')('\165' + chr(116) + chr(102) + '\x2d' + '\x38'))(CJBHNoj4zKoT, reuse=xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\xa4\x9er\x1177\xcd[\xc9'), '\x64' + chr(0b1100101) + chr(0b1100011) + '\x6f' + '\144' + '\x65')('\165' + chr(0b1110100) + '\x66' + '\x2d' + chr(0b11001 + 0o37)))):
fihiNkE3SsFi = IDJ2eXGCBCDu.get_variable(xafqLlk3kkUe(SXOLrMavuUCe(b'&\x9e\xa4K\x11\x03\x1b\xf4|\xe9\x93'), chr(0b110010 + 0o62) + chr(101) + chr(0b11001 + 0o112) + chr(0b1101111) + chr(100) + chr(1125 - 1024))(chr(0b1110101) + chr(10361 - 10245) + chr(1658 - 1556) + chr(1969 - 1924) + chr(0b100 + 0o64)), shape=be5Q8MSuNI1T, initializer=IDJ2eXGCBCDu.truncated_normal_initializer(stddev=0.02))
if xafqLlk3kkUe(oVre8I6UXc3b.hparams, xafqLlk3kkUe(SXOLrMavuUCe(b'0\x82\xafb=\x15\x17\xfb|\xfe\x80\x8b\xfa\xa7ZV"'), chr(0b1100000 + 0o4) + chr(0b110010 + 0o63) + chr(7128 - 7029) + chr(0b1010011 + 0o34) + chr(0b1100100) + chr(0b1100101))('\x75' + '\x74' + '\x66' + chr(0b100010 + 0o13) + '\x38')):
(fihiNkE3SsFi, MZYt05TKlSHo) = jSKPaHwSAfVv.apply_spectral_norm(fihiNkE3SsFi)
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b',\x82\x95I<\x04\x1b\xf6a\xe2\x86'), chr(100) + chr(0b1100101) + chr(2307 - 2208) + '\157' + chr(0b1100100) + '\x65')('\x75' + chr(116) + '\x66' + chr(0b101101) + '\070')):
xafqLlk3kkUe(IDJ2eXGCBCDu, xafqLlk3kkUe(SXOLrMavuUCe(b'$\x95\xaeb:\n-\xfbg\xe0\x8d\x82\xc6\xbd\\K!'), chr(100) + chr(6113 - 6012) + chr(0b1100010 + 0o1) + '\157' + '\144' + chr(101))('\x75' + '\x74' + chr(1372 - 1270) + chr(45) + chr(1143 - 1087)))(xafqLlk3kkUe(IDJ2eXGCBCDu.GraphKeys, xafqLlk3kkUe(SXOLrMavuUCe(b'\x10\xa1\x8e|\x1a -\xd7X\xdf'), '\144' + '\145' + chr(0b11100 + 0o107) + '\157' + chr(0b100111 + 0o75) + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + chr(102) + chr(127 - 82) + chr(0b111000))), MZYt05TKlSHo)
Jr6qMmXilxlt = IDJ2eXGCBCDu.pad(mgDWDDVSXPyH, TFLseEYASEKG)
tulGoizc7a_y = IDJ2eXGCBCDu.nn.conv3d(Jr6qMmXilxlt, fihiNkE3SsFi, strides=r8knJmMTTKwv, padding=xafqLlk3kkUe(SXOLrMavuUCe(b'\x13\xb0\x86t\n'), chr(7456 - 7356) + chr(101) + '\143' + '\157' + '\144' + '\145')('\x75' + '\164' + chr(102) + chr(45) + chr(1080 - 1024)))
io84oVi6Kfn6 = IDJ2eXGCBCDu.nn.leaky_relu(tulGoizc7a_y, alpha=0.2)
return io84oVi6Kfn6
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/pruning_utils.py
|
weight
|
def weight(w, sparsity):
"""Weight-level magnitude pruning."""
w_shape = common_layers.shape_list(w)
k = int(np.prod(w_shape[:-1]))
count = tf.to_int32(k * sparsity)
mask = common_layers.weight_targeting(w, count)
return (1 - mask) * w
|
python
|
def weight(w, sparsity):
"""Weight-level magnitude pruning."""
w_shape = common_layers.shape_list(w)
k = int(np.prod(w_shape[:-1]))
count = tf.to_int32(k * sparsity)
mask = common_layers.weight_targeting(w, count)
return (1 - mask) * w
|
[
"def",
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"w",
",",
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":",
"w_shape",
"=",
"common_layers",
".",
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"(",
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")",
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"(",
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"(",
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"[",
":",
"-",
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"]",
")",
")",
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"sparsity",
")",
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"(",
"w",
",",
"count",
")",
"return",
"(",
"1",
"-",
"mask",
")",
"*",
"w"
] |
Weight-level magnitude pruning.
|
[
"Weight",
"-",
"level",
"magnitude",
"pruning",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/pruning_utils.py#L27-L33
|
train
|
Weight - level magnitude pruning.
|
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(0b100101 + 0o22) + chr(0b1010 + 0o50), 53713 - 53705), ehT0Px3KOsy9('\x30' + '\157' + chr(0b101100 + 0o7) + '\061' + chr(55), 0o10), ehT0Px3KOsy9(chr(48) + chr(1336 - 1225) + '\x35' + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010 + 0o2) + chr(48), 0o10), ehT0Px3KOsy9(chr(1533 - 1485) + '\x6f' + chr(359 - 309) + '\x32' + chr(0b100011 + 0o22), 0b1000), ehT0Px3KOsy9(chr(1522 - 1474) + chr(111) + chr(0b100000 + 0o23) + '\x33' + '\064', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + chr(281 - 230) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b1101001 + 0o6) + chr(0b110011) + '\x36' + '\060', ord("\x08")), ehT0Px3KOsy9('\060' + chr(3850 - 3739) + chr(0b110001) + chr(0b110101) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(4899 - 4788) + '\x33' + chr(0b100110 + 0o12) + chr(0b110011), 3416 - 3408), ehT0Px3KOsy9('\060' + chr(0b11101 + 0o122) + '\063', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(1533 - 1483) + '\065' + chr(300 - 247), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + '\x34', 0o10), ehT0Px3KOsy9(chr(665 - 617) + chr(629 - 518) + '\061' + chr(0b11000 + 0o34) + chr(0b1010 + 0o55), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b100010 + 0o21) + chr(49) + chr(0b111 + 0o55), 11917 - 11909), ehT0Px3KOsy9('\x30' + chr(10494 - 10383) + chr(0b100111 + 0o13) + '\x37' + chr(0b101110 + 0o6), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(2056 - 2001) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b1101111) + chr(49) + '\x36' + chr(0b110111), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b1000 + 0o54) + chr(0b10001 + 0o40), 12139 - 12131), ehT0Px3KOsy9('\060' + '\157' + chr(0b10100 + 0o37) + chr(0b110101) + chr(0b110011), 0o10), ehT0Px3KOsy9('\060' + chr(0b110111 + 0o70) + chr(889 - 839) + chr(0b1100 + 0o44) + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(8290 - 8179) + chr(0b11111 + 0o23) + '\x31' + chr(51), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + '\x36' + chr(52), 0o10), ehT0Px3KOsy9(chr(48) + chr(6919 - 6808) + '\x31' + '\x33' + '\x30', 28904 - 28896), ehT0Px3KOsy9(chr(922 - 874) + '\157' + chr(0b110010) + chr(0b10110 + 0o40) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001) + chr(321 - 268) + '\062', 53183 - 53175), ehT0Px3KOsy9(chr(0b110000) + chr(0b110011 + 0o74) + chr(0b110011) + chr(0b101111 + 0o4), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(394 - 342) + chr(0b110011), 49195 - 49187), ehT0Px3KOsy9(chr(0b100111 + 0o11) + '\157' + chr(1028 - 978) + chr(814 - 766) + chr(1647 - 1598), 3997 - 3989), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + chr(48) + chr(866 - 815), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51) + chr(0b110101), 51269 - 51261), ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\x6f' + chr(0b101101 + 0o5) + chr(834 - 780) + chr(2568 - 2517), 58798 - 58790), ehT0Px3KOsy9('\x30' + chr(0b11011 + 0o124) + chr(0b101 + 0o54) + chr(0b110011) + '\x34', 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\067' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(600 - 552) + chr(0b100101 + 0o112) + '\063' + '\x37' + chr(319 - 269), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110100) + chr(55), 28998 - 28990), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10011 + 0o43) + chr(584 - 531), ord("\x08")), ehT0Px3KOsy9(chr(1634 - 1586) + chr(0b1101011 + 0o4) + chr(0b100001 + 0o20) + chr(1296 - 1246) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(625 - 577) + '\x6f' + chr(0b110100) + chr(0b100000 + 0o22), 61790 - 61782), ehT0Px3KOsy9(chr(48) + chr(111) + '\064', 35636 - 35628)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10011 + 0o42) + '\060', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x94'), chr(100) + chr(6622 - 6521) + '\143' + '\x6f' + chr(100) + chr(4779 - 4678))(chr(0b1010001 + 0o44) + chr(116) + chr(1057 - 955) + '\x2d' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def C0mVSPj6WjvB(AOfzRywRzEXp, rHNM7x7OjxnH):
hx4Bljlpg_3G = jSKPaHwSAfVv.shape_list(AOfzRywRzEXp)
OolUPRJhRaJd = ehT0Px3KOsy9(WqUC3KWvYVup.lBYk79l4Nk8h(hx4Bljlpg_3G[:-ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b100101 + 0o14), 0o10)]))
ualWdDeXJEGO = IDJ2eXGCBCDu.to_int32(OolUPRJhRaJd * rHNM7x7OjxnH)
Iz1jSgUKZDvt = jSKPaHwSAfVv.weight_targeting(AOfzRywRzEXp, ualWdDeXJEGO)
return (ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061', 8) - Iz1jSgUKZDvt) * AOfzRywRzEXp
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/pruning_utils.py
|
unit
|
def unit(w, sparsity):
"""Unit-level magnitude pruning."""
w_shape = common_layers.shape_list(w)
count = tf.to_int32(w_shape[-1] * sparsity)
mask = common_layers.unit_targeting(w, count)
return (1 - mask) * w
|
python
|
def unit(w, sparsity):
"""Unit-level magnitude pruning."""
w_shape = common_layers.shape_list(w)
count = tf.to_int32(w_shape[-1] * sparsity)
mask = common_layers.unit_targeting(w, count)
return (1 - mask) * w
|
[
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"shape_list",
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")",
"count",
"=",
"tf",
".",
"to_int32",
"(",
"w_shape",
"[",
"-",
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"]",
"*",
"sparsity",
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"common_layers",
".",
"unit_targeting",
"(",
"w",
",",
"count",
")",
"return",
"(",
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"-",
"mask",
")",
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] |
Unit-level magnitude pruning.
|
[
"Unit",
"-",
"level",
"magnitude",
"pruning",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/pruning_utils.py#L37-L42
|
train
|
Unit - level magnitude pruning.
|
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(0b1000000 + 0o57) + chr(933 - 883) + chr(49) + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101111) + chr(0b101001 + 0o12) + chr(50), 0o10), ehT0Px3KOsy9(chr(48) + chr(11736 - 11625) + chr(2226 - 2176) + chr(0b110100) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1935 - 1884) + '\x33' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + '\x32' + chr(54), 33430 - 33422), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(2118 - 2070) + '\062', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b111100 + 0o63) + chr(220 - 167) + chr(0b10010 + 0o44), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + chr(48) + chr(2158 - 2106), 54734 - 54726), ehT0Px3KOsy9(chr(1907 - 1859) + chr(0b1011000 + 0o27) + chr(854 - 805) + '\x35' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(51) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b100101 + 0o13) + '\157' + chr(0b110010) + '\064' + chr(776 - 723), 53362 - 53354), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + chr(49) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\x6f' + chr(0b110001) + chr(0b1100 + 0o50) + chr(0b110010), 3582 - 3574), ehT0Px3KOsy9(chr(48) + chr(0b1000000 + 0o57) + chr(0b101 + 0o56) + '\x35' + chr(0b110010 + 0o5), 0b1000), ehT0Px3KOsy9('\x30' + chr(5026 - 4915) + chr(282 - 232) + '\x30' + chr(50), 20035 - 20027), ehT0Px3KOsy9('\060' + '\157' + chr(0b100010 + 0o21) + chr(0b110001 + 0o3) + '\x31', 0o10), ehT0Px3KOsy9(chr(2124 - 2076) + '\157' + chr(1347 - 1297) + chr(567 - 512) + '\x32', 9706 - 9698), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101010 + 0o7) + chr(0b110011) + chr(0b100 + 0o57), 12003 - 11995), ehT0Px3KOsy9('\x30' + chr(111) + chr(690 - 640) + chr(0b100110 + 0o21) + chr(49), 0o10), ehT0Px3KOsy9(chr(1906 - 1858) + '\157' + chr(51) + chr(48) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(111) + chr(411 - 360) + '\060', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10001 + 0o42) + chr(49) + '\x32', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(51) + chr(51) + chr(51), 64321 - 64313), ehT0Px3KOsy9('\x30' + chr(0b1010011 + 0o34) + '\066' + '\060', 0b1000), ehT0Px3KOsy9('\060' + chr(451 - 340) + chr(0b110011) + chr(0b110010) + chr(0b1010 + 0o51), ord("\x08")), ehT0Px3KOsy9(chr(2078 - 2030) + chr(3303 - 3192) + '\063' + '\060' + chr(0b1110 + 0o43), 8), ehT0Px3KOsy9(chr(48) + chr(2751 - 2640) + chr(257 - 207) + '\063' + '\x31', ord("\x08")), ehT0Px3KOsy9('\060' + chr(1714 - 1603) + '\061' + '\x35' + chr(0b10110 + 0o41), 0b1000), ehT0Px3KOsy9('\x30' + chr(8089 - 7978) + '\x32' + '\063' + chr(0b10010 + 0o36), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + '\066' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\x6f' + chr(0b110001) + chr(51) + '\062', 39369 - 39361), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + chr(0b110000) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(666 - 618) + chr(111) + '\062' + '\x34' + chr(0b10101 + 0o41), 0b1000), ehT0Px3KOsy9(chr(1197 - 1149) + '\157' + '\x31' + '\062' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + chr(2085 - 2031) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\x35', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + '\x31' + chr(490 - 442), 0b1000), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1101111 + 0o0) + '\x37' + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110101) + chr(0b100111 + 0o13), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(0b1000 + 0o53) + chr(593 - 540), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(741 - 693) + chr(111) + '\065' + '\060', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xa0'), chr(100) + '\x65' + chr(7095 - 6996) + '\x6f' + '\x64' + chr(101))(chr(0b110011 + 0o102) + chr(6947 - 6831) + chr(102) + chr(0b101101) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def zbwQ4mKE5Iq9(AOfzRywRzEXp, rHNM7x7OjxnH):
hx4Bljlpg_3G = jSKPaHwSAfVv.shape_list(AOfzRywRzEXp)
ualWdDeXJEGO = IDJ2eXGCBCDu.to_int32(hx4Bljlpg_3G[-ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061', 0o10)] * rHNM7x7OjxnH)
Iz1jSgUKZDvt = jSKPaHwSAfVv.unit_targeting(AOfzRywRzEXp, ualWdDeXJEGO)
return (ehT0Px3KOsy9(chr(1581 - 1533) + '\x6f' + chr(1844 - 1795), 8) - Iz1jSgUKZDvt) * AOfzRywRzEXp
|
tensorflow/tensor2tensor
|
tensor2tensor/utils/pruning_utils.py
|
sparsify
|
def sparsify(sess, eval_model, pruning_strategy, pruning_params):
"""Prune the weights of a model and evaluate."""
weights = tf.trainable_variables()
def should_prune(name):
"""Whether to prune a weight or not."""
in_whitelist = not pruning_params.white_list or any(
e in name for e in pruning_params.white_list)
in_blacklist = any(e in name for e in pruning_params.black_list)
if pruning_params.white_list and not in_whitelist:
return False
elif in_blacklist:
return False
return True
weights = [w for w in weights if should_prune(w.name)]
tf.logging.info("Pruning weights: %s" % weights)
unpruned_weights = sess.run(weights)
reset_op = tf.no_op()
for w, ow in zip(weights, unpruned_weights):
op = tf.assign(w, ow)
reset_op = tf.group(reset_op, op)
for sparsity in pruning_params.sparsities:
set_weights_op = tf.no_op()
for w in weights:
op = tf.assign(w, pruning_strategy(w, sparsity))
set_weights_op = tf.group(set_weights_op, op)
sess.run(set_weights_op)
acc = eval_model()
tf.logging.info("\tPruning to sparsity = %f: acc = %f" % (sparsity, acc))
sess.run(reset_op)
|
python
|
def sparsify(sess, eval_model, pruning_strategy, pruning_params):
"""Prune the weights of a model and evaluate."""
weights = tf.trainable_variables()
def should_prune(name):
"""Whether to prune a weight or not."""
in_whitelist = not pruning_params.white_list or any(
e in name for e in pruning_params.white_list)
in_blacklist = any(e in name for e in pruning_params.black_list)
if pruning_params.white_list and not in_whitelist:
return False
elif in_blacklist:
return False
return True
weights = [w for w in weights if should_prune(w.name)]
tf.logging.info("Pruning weights: %s" % weights)
unpruned_weights = sess.run(weights)
reset_op = tf.no_op()
for w, ow in zip(weights, unpruned_weights):
op = tf.assign(w, ow)
reset_op = tf.group(reset_op, op)
for sparsity in pruning_params.sparsities:
set_weights_op = tf.no_op()
for w in weights:
op = tf.assign(w, pruning_strategy(w, sparsity))
set_weights_op = tf.group(set_weights_op, op)
sess.run(set_weights_op)
acc = eval_model()
tf.logging.info("\tPruning to sparsity = %f: acc = %f" % (sparsity, acc))
sess.run(reset_op)
|
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] |
Prune the weights of a model and evaluate.
|
[
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] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/pruning_utils.py#L45-L80
|
train
|
Prune the weights of a model and 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(0b110000) + chr(0b1000 + 0o147) + chr(0b101001 + 0o11) + chr(0b100110 + 0o21) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\157' + '\063' + chr(0b110111) + chr(0b110011), 10032 - 10024), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001) + chr(0b10111 + 0o37) + '\065', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011) + chr(0b110101) + '\x37', 21534 - 21526), ehT0Px3KOsy9(chr(1120 - 1072) + chr(6980 - 6869) + '\x31' + chr(0b110011) + chr(0b10111 + 0o34), 52546 - 52538), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + '\061' + chr(50), 60660 - 60652), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1010 + 0o50) + chr(49), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b100011 + 0o17) + '\061' + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(111) + '\062' + '\x31' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(765 - 717) + '\x6f' + '\063' + chr(0b101101 + 0o11) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(9515 - 9404) + chr(945 - 894) + '\066' + '\064', 46567 - 46559), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50) + '\060' + chr(53), 0o10), ehT0Px3KOsy9(chr(2173 - 2125) + chr(5797 - 5686) + chr(0b110010) + chr(52) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(111) + '\061' + chr(0b110011) + chr(51), 8), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(53), 25180 - 25172), ehT0Px3KOsy9('\x30' + '\x6f' + '\x32' + chr(51), 59822 - 59814), ehT0Px3KOsy9('\x30' + '\157' + '\063' + chr(0b110011) + chr(0b100 + 0o57), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + '\062' + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + chr(0b110001) + '\064', 39346 - 39338), ehT0Px3KOsy9(chr(1533 - 1485) + '\x6f' + chr(49) + chr(0b110000) + chr(0b11000 + 0o36), 0o10), ehT0Px3KOsy9('\x30' + chr(2479 - 2368) + chr(904 - 853) + '\060' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(949 - 900) + '\x33' + '\066', 58969 - 58961), ehT0Px3KOsy9(chr(2298 - 2250) + chr(0b1101111) + chr(0b110011) + '\x30' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(111) + chr(0b110010) + chr(0b110101) + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b11011 + 0o25) + '\157' + chr(0b10110 + 0o33) + '\x31' + '\066', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + '\060' + chr(0b110001 + 0o4), 9294 - 9286), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(111) + chr(1485 - 1434) + chr(54) + chr(0b100 + 0o55), 63313 - 63305), ehT0Px3KOsy9(chr(171 - 123) + chr(0b1101111) + '\x33' + chr(0b110010) + '\067', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\x36' + chr(2355 - 2305), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + chr(900 - 850) + chr(0b1 + 0o63), 49899 - 49891), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1000011 + 0o54) + '\x31' + chr(48), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110 + 0o53), ord("\x08")), ehT0Px3KOsy9(chr(1180 - 1132) + '\x6f' + chr(0b0 + 0o62) + chr(0b110001) + chr(1219 - 1170), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1111 + 0o42) + '\062' + chr(0b11100 + 0o27), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\x31' + chr(52) + chr(0b110110), 15872 - 15864), ehT0Px3KOsy9('\x30' + '\157' + chr(0b101100 + 0o7) + '\x32' + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(1796 - 1748) + chr(11459 - 11348) + chr(51) + '\x34' + '\x34', 62695 - 62687), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(54) + chr(0b110011), 31882 - 31874), ehT0Px3KOsy9('\060' + chr(1265 - 1154) + chr(50) + chr(49), 8), ehT0Px3KOsy9(chr(2245 - 2197) + chr(111) + chr(972 - 922) + chr(0b110110 + 0o1) + '\x30', 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\157' + chr(53) + chr(0b110000), 64629 - 64621)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x96'), chr(7500 - 7400) + '\145' + '\x63' + '\157' + chr(100) + chr(101))(chr(0b1110101) + chr(2820 - 2704) + chr(0b1100110) + '\055' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Fjbd0BxqWuQZ(HVWCHjSQ2I35, vrDzJqw4KUlz, n9Mc5Cv7cIwy, LZWRT08N6WRW):
ZurHTci57aXw = IDJ2eXGCBCDu.trainable_variables()
def Qz2Zw50trtlA(AIvJRzLdDfgF):
vzK5rLXu9lu2 = not LZWRT08N6WRW.white_list or UVSi4XW7eBIM((GlnVAPeT6CUe in AIvJRzLdDfgF for GlnVAPeT6CUe in LZWRT08N6WRW.white_list))
hXYIUqRFfypT = UVSi4XW7eBIM((GlnVAPeT6CUe in AIvJRzLdDfgF for GlnVAPeT6CUe in LZWRT08N6WRW.black_list))
if xafqLlk3kkUe(LZWRT08N6WRW, xafqLlk3kkUe(SXOLrMavuUCe(b'\xcf\x93\x1c\x9b>\x15}\xe2\xf9\x86'), '\144' + chr(101) + '\x63' + chr(3519 - 3408) + '\144' + chr(4756 - 4655))('\x75' + chr(116) + chr(4587 - 4485) + chr(45) + chr(0b111000))) and (not vzK5rLXu9lu2):
return ehT0Px3KOsy9(chr(0b110000) + chr(11707 - 11596) + '\060', 0o10)
elif hXYIUqRFfypT:
return ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110000), 8)
return ehT0Px3KOsy9('\060' + '\157' + '\061', 8)
ZurHTci57aXw = [AOfzRywRzEXp for AOfzRywRzEXp in ZurHTci57aXw if Qz2Zw50trtlA(AOfzRywRzEXp.AIvJRzLdDfgF)]
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'\xeb\xcc=\x97.)v\xbc\xe0\x9e\xae\xee'), chr(0b1100100) + chr(101) + chr(3545 - 3446) + chr(0b1101111) + '\144' + '\145')(chr(1819 - 1702) + chr(0b10101 + 0o137) + chr(0b1010100 + 0o22) + chr(0b11100 + 0o21) + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xe8\x89\x00\x812$v\xab\xfd\x97\x9d\xe2\xc9/f)\xfb\xb2\xff'), chr(100) + chr(0b1011011 + 0o12) + chr(5087 - 4988) + '\x6f' + chr(100) + '\145')('\x75' + '\164' + chr(0b111010 + 0o54) + chr(0b101101) + '\x38') % ZurHTci57aXw)
HnyKHvaV2BFZ = HVWCHjSQ2I35.sgt5BU61bwZ2(ZurHTci57aXw)
YiiYlveapBFq = IDJ2eXGCBCDu.no_op()
for (AOfzRywRzEXp, FaoBTS2f9aDv) in pZ0NK2y6HRbn(ZurHTci57aXw, HnyKHvaV2BFZ):
C8dAr6Ujq2Tn = IDJ2eXGCBCDu.assign(AOfzRywRzEXp, FaoBTS2f9aDv)
YiiYlveapBFq = IDJ2eXGCBCDu.N9UnmYvaW1pO(YiiYlveapBFq, C8dAr6Ujq2Tn)
for rHNM7x7OjxnH in xafqLlk3kkUe(LZWRT08N6WRW, xafqLlk3kkUe(SXOLrMavuUCe(b'\xcb\x8b\x14\x9d(#e\xe2\xef\x81'), chr(0b1100100) + '\x65' + '\143' + chr(3126 - 3015) + '\x64' + chr(101))(chr(0b1110101) + '\x74' + chr(102) + '\055' + '\x38')):
FxztVwIreJtD = IDJ2eXGCBCDu.no_op()
for AOfzRywRzEXp in ZurHTci57aXw:
C8dAr6Ujq2Tn = IDJ2eXGCBCDu.assign(AOfzRywRzEXp, n9Mc5Cv7cIwy(AOfzRywRzEXp, rHNM7x7OjxnH))
FxztVwIreJtD = IDJ2eXGCBCDu.N9UnmYvaW1pO(FxztVwIreJtD, C8dAr6Ujq2Tn)
xafqLlk3kkUe(HVWCHjSQ2I35, xafqLlk3kkUe(SXOLrMavuUCe(b"\xcb\x9c\x01\xda\x19\x1f'\xba\xe8\x85\xae\xb7"), chr(8121 - 8021) + '\x65' + '\143' + '\157' + '\144' + chr(6081 - 5980))(chr(117) + chr(116) + chr(1477 - 1375) + chr(0b101101) + '\070'))(FxztVwIreJtD)
jIDym3yABcdT = vrDzJqw4KUlz()
xafqLlk3kkUe(IDJ2eXGCBCDu.logging, xafqLlk3kkUe(SXOLrMavuUCe(b'\xeb\xcc=\x97.)v\xbc\xe0\x9e\xae\xee'), chr(100) + chr(0b1100101) + '\x63' + chr(0b1101111) + chr(0b1100100) + chr(0b1100101))(chr(117) + chr(0b1000010 + 0o62) + '\x66' + chr(0b11110 + 0o17) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1\xab\x07\x9a5#\x7f\xec\xaa\x86\x9b\xa5\xd2+ta\xa8\xfe\xf8?\xe0c\xe5\x8b(\x7f\xd1\xb6Q\xf7(<\xa9v\x00'), chr(0b1100100) + chr(4397 - 4296) + '\x63' + chr(0b1101111) + '\144' + chr(0b1100101))(chr(117) + '\x74' + chr(0b1100110) + chr(0b11101 + 0o20) + chr(56)) % (rHNM7x7OjxnH, jIDym3yABcdT))
xafqLlk3kkUe(HVWCHjSQ2I35, xafqLlk3kkUe(SXOLrMavuUCe(b"\xcb\x9c\x01\xda\x19\x1f'\xba\xe8\x85\xae\xb7"), chr(5625 - 5525) + chr(101) + chr(0b1100011) + chr(0b1101111) + '\144' + chr(3409 - 3308))('\165' + chr(116) + '\146' + chr(0b1 + 0o54) + chr(56)))(YiiYlveapBFq)
|
tensorflow/tensor2tensor
|
tensor2tensor/insights/server.py
|
DebugFrontendApplication.load_config
|
def load_config(self):
"""Loads the configuration."""
config = dict([(key, value) for key, value in iteritems(self.options)
if key in self.cfg.settings and value is not None])
for key, value in iteritems(config):
self.cfg.set(key.lower(), value)
|
python
|
def load_config(self):
"""Loads the configuration."""
config = dict([(key, value) for key, value in iteritems(self.options)
if key in self.cfg.settings and value is not None])
for key, value in iteritems(config):
self.cfg.set(key.lower(), value)
|
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] |
Loads the configuration.
|
[
"Loads",
"the",
"configuration",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/insights/server.py#L79-L84
|
train
|
Loads the configuration from the options.
|
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(1147 - 1099) + chr(9965 - 9854) + chr(0b110011) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(527 - 479) + chr(0b1101111) + chr(0b110011) + '\x33' + chr(0b110011 + 0o0), ord("\x08")), ehT0Px3KOsy9('\060' + chr(7694 - 7583) + chr(2094 - 2045) + chr(53) + chr(51), 35904 - 35896), ehT0Px3KOsy9(chr(1025 - 977) + chr(111) + chr(51) + '\066' + '\x35', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1010100 + 0o33) + chr(0b10110 + 0o33) + '\x36' + chr(0b110011), 32940 - 32932), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + chr(0b110000 + 0o0) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(692 - 644) + chr(0b1101111) + chr(2232 - 2183) + chr(1114 - 1065) + '\062', 11744 - 11736), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100110 + 0o15) + chr(237 - 182) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b1010110 + 0o31) + chr(0b101001 + 0o11) + chr(0b101011 + 0o11) + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b111000 + 0o67) + chr(2423 - 2373) + '\x32' + chr(0b110011), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + '\x34' + chr(50), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + '\x35' + chr(0b110000), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(955 - 905) + chr(0b1100 + 0o46) + chr(597 - 549), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(0b11101 + 0o24) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\157' + chr(1323 - 1273) + chr(2750 - 2695) + '\064', 20829 - 20821), ehT0Px3KOsy9('\x30' + '\157' + '\x37' + '\x35', 37081 - 37073), ehT0Px3KOsy9(chr(48) + chr(923 - 812) + chr(0b110010) + chr(256 - 202) + chr(0b10111 + 0o40), 0o10), ehT0Px3KOsy9(chr(309 - 261) + chr(0b10010 + 0o135) + chr(0b110011) + chr(0b101110 + 0o7) + '\x30', 8), ehT0Px3KOsy9(chr(95 - 47) + '\157' + '\x31' + chr(48) + '\061', 11716 - 11708), ehT0Px3KOsy9(chr(1915 - 1867) + chr(4840 - 4729) + chr(0b110011) + chr(52) + chr(181 - 130), 57270 - 57262), ehT0Px3KOsy9(chr(48) + chr(0b1100010 + 0o15) + '\x33' + chr(0b110110), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(55) + '\065', 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1011 + 0o47) + '\062' + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(5682 - 5571) + '\062' + '\063' + chr(0b100011 + 0o21), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + chr(1630 - 1576) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1101111) + chr(0b110011) + '\x33' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(1079 - 1031) + '\x6f' + '\x33' + chr(54) + '\066', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(2157 - 2108) + chr(0b110000) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b110 + 0o52) + '\x6f' + chr(49) + chr(0b110111) + chr(1703 - 1651), 0b1000), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(0b1101111) + '\061' + chr(49) + chr(0b11010 + 0o27), 0b1000), ehT0Px3KOsy9(chr(2132 - 2084) + '\157' + chr(0b110000 + 0o1) + chr(0b110010) + '\063', 37290 - 37282), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1001 + 0o146) + chr(2165 - 2113) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b10110 + 0o32) + '\x6f' + chr(0b10010 + 0o41) + chr(0b110010) + chr(2139 - 2089), ord("\x08")), ehT0Px3KOsy9(chr(1355 - 1307) + '\x6f' + chr(0b110011) + chr(1071 - 1016) + chr(0b110011), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2289 - 2239) + '\065' + chr(0b1100 + 0o51), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110000 + 0o1) + chr(0b110100), 21392 - 21384), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + '\x32' + chr(838 - 785), 0b1000), ehT0Px3KOsy9(chr(426 - 378) + '\157' + '\x33' + chr(0b11010 + 0o27), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(435 - 383) + '\066', 0b1000), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1101111) + chr(50) + chr(0b11010 + 0o33) + chr(0b110000), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x35' + chr(0b10001 + 0o37), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'1'), chr(0b1100100) + chr(101) + chr(4296 - 4197) + chr(0b1001 + 0o146) + chr(100) + chr(101))('\165' + chr(7295 - 7179) + chr(0b110001 + 0o65) + chr(45) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def COQKPyCcXhId(oVre8I6UXc3b):
jAj7S20Ct06o = wLqBDw8l0eIm([(K3J4ZwSlE0sT, QmmgWUB13VCJ) for (K3J4ZwSlE0sT, QmmgWUB13VCJ) in WYXqUHkBa2Bx(oVre8I6UXc3b.options) if K3J4ZwSlE0sT in oVre8I6UXc3b.cfg.settings and QmmgWUB13VCJ is not None])
for (K3J4ZwSlE0sT, QmmgWUB13VCJ) in WYXqUHkBa2Bx(jAj7S20Ct06o):
xafqLlk3kkUe(oVre8I6UXc3b.cfg, xafqLlk3kkUe(SXOLrMavuUCe(b'l\xbe\x1f'), '\144' + chr(101) + '\143' + '\x6f' + '\144' + '\x65')(chr(7670 - 7553) + chr(2760 - 2644) + chr(0b1001101 + 0o31) + chr(45) + '\x38'))(xafqLlk3kkUe(K3J4ZwSlE0sT, xafqLlk3kkUe(SXOLrMavuUCe(b's\xb4\x1c\x90\x01'), chr(0b111010 + 0o52) + chr(9076 - 8975) + chr(99) + '\x6f' + chr(6250 - 6150) + '\x65')(chr(11870 - 11753) + chr(0b1110100) + chr(0b111 + 0o137) + '\055' + chr(56)))(), QmmgWUB13VCJ)
|
tensorflow/tensor2tensor
|
tensor2tensor/models/research/rl.py
|
ppo_base_v1
|
def ppo_base_v1():
"""Set of hyperparameters."""
hparams = common_hparams.basic_params1()
hparams.learning_rate_schedule = "constant"
hparams.learning_rate_constant = 1e-4
hparams.clip_grad_norm = 0.5
hparams.weight_decay = 0
# If set, extends the LR warmup to all epochs except the final one.
hparams.add_hparam("lr_decay_in_final_epoch", False)
hparams.add_hparam("init_mean_factor", 0.1)
hparams.add_hparam("init_logstd", 0.1)
hparams.add_hparam("policy_layers", (100, 100))
hparams.add_hparam("value_layers", (100, 100))
hparams.add_hparam("clipping_coef", 0.2)
hparams.add_hparam("gae_gamma", 0.99)
hparams.add_hparam("gae_lambda", 0.95)
hparams.add_hparam("entropy_loss_coef", 0.01)
hparams.add_hparam("value_loss_coef", 1)
hparams.add_hparam("optimization_epochs", 15)
hparams.add_hparam("epoch_length", 200)
hparams.add_hparam("epochs_num", 2000)
hparams.add_hparam("eval_every_epochs", 10)
hparams.add_hparam("save_models_every_epochs", 30)
hparams.add_hparam("optimization_batch_size", 50)
hparams.add_hparam("intrinsic_reward_scale", 0.)
hparams.add_hparam("logits_clip", 0.0)
hparams.add_hparam("dropout_ppo", 0.1)
hparams.add_hparam("effective_num_agents", None)
# TODO(afrozm): Clean this up, this is used in PPO learner to get modalities.
hparams.add_hparam("policy_problem_name", "dummy_policy_problem")
return hparams
|
python
|
def ppo_base_v1():
"""Set of hyperparameters."""
hparams = common_hparams.basic_params1()
hparams.learning_rate_schedule = "constant"
hparams.learning_rate_constant = 1e-4
hparams.clip_grad_norm = 0.5
hparams.weight_decay = 0
# If set, extends the LR warmup to all epochs except the final one.
hparams.add_hparam("lr_decay_in_final_epoch", False)
hparams.add_hparam("init_mean_factor", 0.1)
hparams.add_hparam("init_logstd", 0.1)
hparams.add_hparam("policy_layers", (100, 100))
hparams.add_hparam("value_layers", (100, 100))
hparams.add_hparam("clipping_coef", 0.2)
hparams.add_hparam("gae_gamma", 0.99)
hparams.add_hparam("gae_lambda", 0.95)
hparams.add_hparam("entropy_loss_coef", 0.01)
hparams.add_hparam("value_loss_coef", 1)
hparams.add_hparam("optimization_epochs", 15)
hparams.add_hparam("epoch_length", 200)
hparams.add_hparam("epochs_num", 2000)
hparams.add_hparam("eval_every_epochs", 10)
hparams.add_hparam("save_models_every_epochs", 30)
hparams.add_hparam("optimization_batch_size", 50)
hparams.add_hparam("intrinsic_reward_scale", 0.)
hparams.add_hparam("logits_clip", 0.0)
hparams.add_hparam("dropout_ppo", 0.1)
hparams.add_hparam("effective_num_agents", None)
# TODO(afrozm): Clean this up, this is used in PPO learner to get modalities.
hparams.add_hparam("policy_problem_name", "dummy_policy_problem")
return hparams
|
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] |
Set of hyperparameters.
|
[
"Set",
"of",
"hyperparameters",
"."
] |
272500b6efe353aeb638d2745ed56e519462ca31
|
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/research/rl.py#L46-L76
|
train
|
Set of hyperparameters for PPO base model v1.
|
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(0b11011 + 0o25) + chr(2969 - 2858) + chr(49) + chr(854 - 802) + chr(0b110111), 30153 - 30145), ehT0Px3KOsy9('\060' + '\157' + '\063' + chr(50) + chr(0b1100 + 0o51), 21125 - 21117), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(0b101111 + 0o4) + '\x31', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062' + '\x36' + chr(0b110011), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(1256 - 1206) + chr(50) + '\067', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(177 - 123) + chr(54), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b100100 + 0o17) + chr(0b110111) + chr(604 - 556), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + chr(51) + chr(0b110100), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1539 - 1490) + chr(689 - 641) + chr(889 - 838), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061' + '\x31' + chr(214 - 162), 6366 - 6358), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100001 + 0o20) + chr(0b100100 + 0o16) + '\x30', 27798 - 27790), ehT0Px3KOsy9(chr(792 - 744) + chr(0b100111 + 0o110) + '\061' + chr(55) + '\063', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10010 + 0o37) + chr(1167 - 1112) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110111) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b10 + 0o56) + '\157' + chr(49) + chr(0b110001) + '\x30', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b1111 + 0o44) + '\x30' + '\x34', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b1110 + 0o50) + chr(2011 - 1959), 0b1000), ehT0Px3KOsy9(chr(948 - 900) + '\157' + '\x32' + '\x35' + chr(0b110101), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1000100 + 0o53) + chr(0b110001) + chr(0b110110) + '\x32', 3503 - 3495), ehT0Px3KOsy9(chr(1480 - 1432) + chr(0b1100101 + 0o12) + '\x33' + chr(0b110010) + chr(0b110011), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + '\063' + '\x32', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110110) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b11011 + 0o25) + '\157' + '\x31' + '\066' + chr(0b11110 + 0o27), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + chr(50) + chr(0b101011 + 0o7), ord("\x08")), ehT0Px3KOsy9(chr(1344 - 1296) + chr(111) + chr(556 - 503) + '\x37', 0o10), ehT0Px3KOsy9('\x30' + chr(9547 - 9436) + chr(0b110011) + '\067' + chr(1555 - 1506), 23628 - 23620), ehT0Px3KOsy9(chr(0b10011 + 0o35) + '\x6f' + chr(0b110111) + chr(192 - 143), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b101110 + 0o101) + '\x31' + '\x33' + chr(0b110000), 17367 - 17359), ehT0Px3KOsy9(chr(1654 - 1606) + chr(0b1101111 + 0o0) + chr(51) + '\060', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b11 + 0o56) + '\061' + chr(0b10000 + 0o42), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1607 - 1556) + chr(2377 - 2324) + chr(0b110001), 59075 - 59067), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(111) + chr(0b110011) + chr(0b110010) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(359 - 311) + '\x6f' + '\x32' + chr(0b110111) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\063' + chr(0b110011) + chr(333 - 281), 8), ehT0Px3KOsy9('\060' + chr(11498 - 11387) + '\x32' + '\x37' + chr(48), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(326 - 277) + chr(0b110110) + '\063', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(177 - 126) + chr(0b110011) + chr(52), 8), ehT0Px3KOsy9(chr(48) + chr(9525 - 9414) + chr(998 - 949) + chr(0b110100) + chr(1134 - 1080), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + '\x35' + chr(0b10000 + 0o41), 8), ehT0Px3KOsy9('\060' + chr(111) + '\061' + '\x36' + '\x34', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b1000101 + 0o52) + chr(0b11000 + 0o35) + '\x30', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'I'), chr(6614 - 6514) + chr(0b0 + 0o145) + chr(1274 - 1175) + chr(0b110111 + 0o70) + chr(0b1100100) + chr(101))(chr(6437 - 6320) + chr(4651 - 4535) + chr(0b1100110) + chr(344 - 299) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def coy2SBzwpBvg():
n4ljua2gi1Pr = vLnG3ZpOXWXZ.basic_params1()
n4ljua2gi1Pr.Lz_s7neUzM5V = xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\xba\xb7\xc0\xe3W\x96\xa8'), chr(0b1001 + 0o133) + chr(101) + chr(0b110111 + 0o54) + chr(0b110111 + 0o70) + '\144' + '\x65')(chr(11844 - 11727) + chr(9745 - 9629) + chr(5727 - 5625) + '\x2d' + chr(1819 - 1763))
n4ljua2gi1Pr.Ot9HUjnkxXA_ = 0.0001
n4ljua2gi1Pr.SdNSZNVkVjLh = 0.5
n4ljua2gi1Pr.eB4rJl6fUxw9 = ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(48), 37224 - 37216)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), '\x64' + chr(6491 - 6390) + '\143' + '\x6f' + chr(394 - 294) + '\145')('\165' + chr(0b10100 + 0o140) + chr(0b1100110) + chr(0b100001 + 0o14) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x0b\xa7\x86\xd7\xf2U\x99\xa5\x1c%>$\x1aV&\xa5X\xf2\x17\xa3\xb5V\x1d'), '\x64' + '\145' + '\x63' + chr(111) + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + chr(7774 - 7658) + chr(0b1100110) + '\x2d' + chr(0b100 + 0o64)), ehT0Px3KOsy9('\x30' + chr(1012 - 901) + '\060', 8))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), '\x64' + '\x65' + '\143' + chr(0b1101111) + '\x64' + chr(101))('\165' + chr(0b101011 + 0o111) + '\x66' + chr(0b100110 + 0o7) + chr(0b10001 + 0o47)))(xafqLlk3kkUe(SXOLrMavuUCe(b"\x0e\xbb\xb0\xc7\xc8[\x9d\xbd-\x136\x1a\x1fK'\xb6"), chr(100) + '\145' + chr(0b1100011) + '\x6f' + chr(3370 - 3270) + chr(0b1100101))(chr(0b1100100 + 0o21) + chr(0b1101000 + 0o14) + chr(9695 - 9593) + chr(45) + chr(56)), 0.1)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), chr(0b1100100) + chr(3698 - 3597) + chr(0b1100011) + chr(111) + chr(3398 - 3298) + '\145')(chr(117) + chr(116) + '\x66' + chr(45) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x0e\xbb\xb0\xc7\xc8Z\x97\xbb084'), '\144' + chr(101) + chr(0b1001010 + 0o31) + chr(111) + '\x64' + '\145')(chr(0b1110101) + chr(0b1101001 + 0o13) + '\x66' + chr(0b101101) + chr(56)), 0.1)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), chr(0b1011010 + 0o12) + chr(714 - 613) + chr(799 - 700) + '\157' + chr(0b1100100) + '\145')('\165' + '\x74' + chr(0b1100110) + '\055' + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x17\xba\xb5\xda\xf4O\xa7\xb0"55\t\x0f'), '\x64' + chr(0b101 + 0o140) + chr(99) + chr(3976 - 3865) + chr(0b10 + 0o142) + chr(0b111100 + 0o51))('\x75' + '\164' + '\x66' + '\x2d' + chr(0b0 + 0o70)), (ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b11000 + 0o31) + chr(0b110100) + chr(0b10101 + 0o37), 60654 - 60646), ehT0Px3KOsy9(chr(1203 - 1155) + chr(0b1101111) + chr(435 - 386) + '\x34' + chr(0b110100), 8)))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), chr(100) + chr(0b1100101) + '\x63' + chr(111) + '\144' + chr(0b1100101))(chr(11493 - 11376) + chr(0b101000 + 0o114) + chr(0b1100110) + chr(2003 - 1958) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x11\xb4\xb5\xc6\xf2i\x94\xbd:)"\x08'), '\x64' + chr(0b111101 + 0o50) + chr(0b1001111 + 0o24) + '\x6f' + chr(0b1100100) + chr(4541 - 4440))(chr(1906 - 1789) + '\x74' + chr(7582 - 7480) + chr(1548 - 1503) + chr(0b111000)), (ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(111) + chr(0b1011 + 0o46) + '\064' + chr(1631 - 1579), 8), ehT0Px3KOsy9('\060' + '\157' + '\x31' + chr(446 - 394) + '\x34', 8)))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), chr(0b111101 + 0o47) + chr(0b111110 + 0o47) + chr(0b1100011) + '\157' + chr(0b1001100 + 0o30) + chr(940 - 839))(chr(117) + '\164' + chr(0b1100110) + chr(45) + chr(2375 - 2319)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\xb9\xb0\xc3\xe7_\x96\xbb\x1c/?\x1e\x1a'), '\144' + chr(9757 - 9656) + chr(1113 - 1014) + chr(1341 - 1230) + chr(100) + chr(101))(chr(117) + chr(0b1110100) + chr(0b1100110) + chr(380 - 335) + chr(0b111000)), 0.2)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), chr(100) + chr(0b111101 + 0o50) + chr(0b1001 + 0o132) + chr(111) + chr(0b110011 + 0o61) + '\145')('\x75' + chr(0b111 + 0o155) + chr(102) + chr(0b11001 + 0o24) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x00\xb4\xbc\xec\xf0W\x95\xb1"'), '\x64' + '\145' + chr(0b1011000 + 0o13) + chr(0b1101111) + chr(100) + chr(101))('\165' + chr(116) + chr(0b1100110) + chr(0b101101) + chr(0b10011 + 0o45)), 0.99)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), chr(5880 - 5780) + chr(101) + chr(0b111011 + 0o50) + '\157' + chr(0b101111 + 0o65) + chr(1959 - 1858))(chr(0b1110101) + '\164' + chr(102) + chr(0b101101) + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b"\x00\xb4\xbc\xec\xfbW\x95\xbe'-"), chr(2299 - 2199) + '\145' + chr(6505 - 6406) + chr(0b1101111) + chr(0b1100100) + chr(101))('\165' + '\x74' + chr(0b1100110) + chr(0b101101) + chr(2215 - 2159)), 0.95)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), '\144' + chr(101) + '\143' + chr(0b111100 + 0o63) + chr(0b1100100) + chr(5641 - 5540))(chr(0b1110101) + chr(6377 - 6261) + chr(0b1100000 + 0o6) + chr(0b101101) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b"\x02\xbb\xad\xc1\xf8F\x81\x83/##\x08#\\'\xa1R"), '\x64' + '\145' + chr(0b11000 + 0o113) + '\157' + chr(7741 - 7641) + chr(2689 - 2588))('\x75' + chr(0b1110100) + '\146' + chr(0b110 + 0o47) + chr(56)), 0.01)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), '\144' + '\145' + chr(99) + chr(785 - 674) + '\x64' + '\145')(chr(117) + chr(0b1110100) + '\x66' + chr(1890 - 1845) + chr(280 - 224)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x11\xb4\xb5\xc6\xf2i\x94\xb30?\x0f\x18\x13Z.'), '\x64' + chr(0b1100101) + chr(0b1100011) + '\x6f' + chr(100) + chr(0b1001010 + 0o33))('\165' + chr(0b1110100) + '\146' + chr(0b1 + 0o54) + chr(0b111000)), ehT0Px3KOsy9(chr(48) + chr(4280 - 4169) + chr(0b110001), ord("\x08")))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), '\x64' + chr(0b1100101) + chr(2176 - 2077) + chr(0b1101111) + chr(0b1100100) + chr(3013 - 2912))('\x75' + chr(116) + chr(102) + '\x2d' + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x08\xa5\xad\xda\xfa_\x82\xbd7%?\x15#Z8\xabW\xc5\x01'), '\144' + '\x65' + chr(99) + chr(10050 - 9939) + chr(100) + chr(101))('\165' + '\164' + chr(1850 - 1748) + '\x2d' + chr(56)), ehT0Px3KOsy9(chr(48) + chr(0b1100 + 0o143) + '\061' + chr(0b110111), ord("\x08")))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), chr(100) + chr(0b10010 + 0o123) + '\143' + chr(1228 - 1117) + '\144' + chr(0b1100011 + 0o2))(chr(117) + '\164' + chr(0b1100110) + chr(0b1 + 0o54) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x02\xa5\xb6\xd0\xffi\x94\xb9-+$\x13'), chr(0b10001 + 0o123) + chr(0b1100101) + '\x63' + chr(0b10111 + 0o130) + chr(5259 - 5159) + '\x65')('\x75' + chr(0b110101 + 0o77) + chr(2383 - 2281) + chr(0b101101) + '\070'), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(0b1101111) + chr(0b101111 + 0o4) + '\x31' + '\060', 0b1000))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), '\x64' + '\x65' + chr(0b1100011) + chr(0b1010 + 0o145) + chr(0b1100100) + chr(2443 - 2342))(chr(0b1100100 + 0o21) + chr(0b1110100) + chr(0b100110 + 0o100) + chr(45) + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x02\xa5\xb6\xd0\xffE\xa7\xb26!'), chr(0b100011 + 0o101) + chr(101) + chr(99) + chr(0b1101111) + '\144' + '\145')(chr(0b11110 + 0o127) + '\164' + chr(102) + chr(1938 - 1893) + '\070'), ehT0Px3KOsy9('\x30' + chr(1002 - 891) + chr(51) + chr(0b100110 + 0o21) + '\062' + chr(48), 0b1000))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), chr(0b100100 + 0o100) + '\145' + '\143' + '\x6f' + '\x64' + chr(0b1011101 + 0o10))('\165' + chr(13342 - 13226) + chr(102) + chr(45) + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x02\xa3\xb8\xdf\xc8S\x8e\xb915\x0f\x1e\x0cP+\xacG'), chr(335 - 235) + '\145' + '\x63' + chr(0b11010 + 0o125) + chr(2245 - 2145) + chr(101))('\x75' + '\164' + chr(0b1100110) + chr(0b11110 + 0o17) + chr(0b110011 + 0o5)), ehT0Px3KOsy9('\060' + chr(8245 - 8134) + chr(0b10011 + 0o36) + '\x32', 59383 - 59375))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), chr(0b1100100) + chr(101) + chr(675 - 576) + chr(0b1011011 + 0o24) + '\x64' + chr(0b111011 + 0o52))(chr(5706 - 5589) + chr(0b1110100) + chr(0b1100110) + chr(45) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x14\xb4\xaf\xd6\xc8[\x97\xb8& #$\x19I-\xb6M\xf2\x17\xa3\xb5V\x1d\xa1'), chr(0b1100100) + chr(0b110010 + 0o63) + '\x63' + chr(111) + chr(0b101010 + 0o72) + chr(101))('\x75' + chr(0b1110100) + '\x66' + chr(0b111 + 0o46) + chr(1958 - 1902)), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b111 + 0o150) + '\x33' + '\x36', 20208 - 20200))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), chr(100) + '\x65' + chr(99) + chr(0b1101111) + '\144' + chr(0b1000100 + 0o41))(chr(117) + chr(8733 - 8617) + '\146' + '\055' + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x08\xa5\xad\xda\xfa_\x82\xbd7%?\x15#])\xb0W\xc5-\xa0\xb3O\x10'), chr(100) + '\145' + '\x63' + chr(10127 - 10016) + chr(0b1100100) + chr(0b1100101))('\165' + chr(4393 - 4277) + chr(0b1010011 + 0o23) + '\x2d' + chr(0b1 + 0o67)), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b11011 + 0o33) + chr(0b110010), ord("\x08")))
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), chr(100) + '\145' + chr(99) + '\x6f' + chr(0b1100100) + chr(6004 - 5903))('\x75' + chr(0b1110100) + chr(0b1100110) + '\x2d' + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x0e\xbb\xad\xc1\xfeX\x8b\xb5 \x13"\x1e\x0b^:\xa0k\xde\x11\xb2\xb6P'), chr(0b1100100) + chr(2643 - 2542) + chr(0b1001110 + 0o25) + chr(0b10001 + 0o136) + '\x64' + '\x65')('\165' + '\164' + '\x66' + chr(0b0 + 0o55) + chr(1639 - 1583)), 0.0)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), '\x64' + '\145' + chr(1721 - 1622) + '\x6f' + '\x64' + chr(0b101100 + 0o71))(chr(117) + '\164' + chr(0b11100 + 0o112) + '\055' + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x0b\xba\xbe\xda\xe3E\xa7\xbf/% '), chr(3425 - 3325) + chr(101) + '\x63' + chr(0b111101 + 0o62) + chr(2561 - 2461) + chr(0b1100101))('\165' + '\x74' + '\x66' + chr(45) + chr(56)), 0.0)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), chr(0b1100100) + chr(0b1100101) + chr(9134 - 9035) + '\x6f' + '\x64' + chr(6322 - 6221))(chr(117) + '\x74' + chr(3787 - 3685) + chr(0b1100 + 0o41) + chr(0b110011 + 0o5)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x03\xa7\xb6\xc3\xf8C\x8c\x833<?'), chr(0b1100100) + chr(101) + chr(0b1001110 + 0o25) + '\157' + chr(0b1100100) + '\145')(chr(0b1100 + 0o151) + chr(0b1000111 + 0o55) + '\146' + '\055' + '\070'), 0.1)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), chr(100) + '\x65' + chr(99) + chr(111) + chr(100) + chr(0b101111 + 0o66))(chr(0b1110101) + chr(12171 - 12055) + '\146' + chr(45) + '\070'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x02\xb3\xbf\xd6\xf4B\x91\xaa&\x13>\x0e\x11`)\xa3Q\xc3\x06\xa0'), chr(0b1100100) + chr(0b1100101) + '\143' + chr(111) + chr(0b1100100) + '\x65')(chr(117) + '\164' + chr(0b1100110) + chr(0b101101) + chr(0b1110 + 0o52)), None)
xafqLlk3kkUe(n4ljua2gi1Pr, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\xb1\xbd\xec\xffF\x99\xae"!'), chr(0b110001 + 0o63) + '\145' + chr(99) + chr(9183 - 9072) + chr(100) + '\145')('\x75' + chr(0b1010000 + 0o44) + chr(0b1100110) + '\055' + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x17\xba\xb5\xda\xf4O\xa7\xac1#2\x17\x19R\x17\xaaU\xc0\x17'), chr(0b1011100 + 0o10) + chr(5686 - 5585) + chr(0b1110 + 0o125) + chr(0b1101111) + '\144' + '\145')(chr(117) + chr(116) + chr(102) + chr(45) + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\x03\xa0\xb4\xde\xeei\x88\xb3/%3\x02#O:\xabV\xc1\x17\xbe'), chr(0b1010 + 0o132) + '\145' + chr(99) + chr(0b1101111) + chr(100) + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + '\146' + chr(0b101100 + 0o1) + chr(56)))
return n4ljua2gi1Pr
|
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