obfuscated_code stringlengths 120 344k | clean_code stringlengths 100 238k |
|---|---|
def _get_insertion_index(10II0lOOl, O11lOO100: ArrayObject, OO1OOI: str) -> int:
OlIIl01O = [O11lOO100[llOO0].encode("utf-8") for llOO0 in range(0, len(O11lOO100), 2)]
I1l1O = OO1OOI.encode("utf-8")
OOIllOll1 = bisect.bisect_left(OlIIl01O, I1l1O)
OI1O10l10 = bisect.bisect_right(OlIIl01O... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(OlI101l0I, 0010lOO: ArrayObject, Il10l: str) -> int:
lOOOll = [0010lOO[IOIOO].encode("utf-8") for IOIOO in range(0, len(0010lOO), 2)]
lO01 = Il10l.encode("utf-8")
OO0l1I1lI = bisect.bisect_left(lOOOll, lO01)
O0IOOI = bisect.bisect_right(lOOOll, lO01)
if... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(llO0OOlI, 1111: ArrayObject, IIO11OO: str) -> int:
O0IO0 = [1111[lIl0OlO0].encode("utf-8") for lIl0OlO0 in range(0, len(1111), 2)]
11O0O = IIO11OO.encode("utf-8")
OOOII = bisect.bisect_left(O0IO0, 11O0O)
1IOOOl1lI1 = bisect.bisect_right(O0IO0, 11O0O)
if... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(IOllI, O0I1: ArrayObject, I1O1I010O0: str) -> int:
IllIlIO = [O0I1[000OI].encode("utf-8") for 000OI in range((9^9)*0, len(O0I1), 2)]
OOOOllI00l = I1O1I010O0.encode("utf-8")
0IIO = bisect.bisect_left(IllIlIO, OOOOllI00l)
IO01llI1 = bisect.bisect_right(IllIlIO, OO... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(lOIO1O, 11O1: ArrayObject, lIO0ll: str) -> int:
110I = [11O1[IllII].encode("utf-8") for IllII in range(0, len(11O1), 2)]
OI11lI1 = lIO0ll.encode("utf-8")
I10O0O10 = bisect.bisect_left(110I, OI11lI1)
O1O1II = bisect.bisect_right(110I, OI11lI1)
if I10O0O1... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(ll1l, 01O0Ol: ArrayObject, O11Il: str) -> int:
0I00 = [01O0Ol[lIOI].encode("utf-8") for lIOI in range((9^9)*0, len(01O0Ol), 2)]
if (3*2)==7: return False
llI11I1 = O11Il.encode("utf-8")
I1IIO = bisect.bisect_left(0I00, llI11I1)
0IO1OO1OII = bisect.bisect_rig... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(lO1l1l, II011O0IlO: ArrayObject, 0lOlO0Il: str) -> int:
011O0lIl = [II011O0IlO[IO0I].encode("utf-8") for IO0I in range(0, len(II011O0IlO), 2)]
11lIO0OIO = 0lOlO0Il.encode("utf-8")
10001 = bisect.bisect_left(011O0lIl, 11lIO0OIO)
01Il0OII = bisect.bisect_right(011... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(1l0l0O0O1, 0000l11lO: ArrayObject, II1lOl1I1O: str) -> int:
IIllOllO10 = [0000l11lO[OOOI].encode("utf-8") for OOOI in range(0, len(0000l11lO), 2)]
11IO = II1lOl1I1O.encode("utf-8")
lOIOI11 = bisect.bisect_left(IIllOllO10, 11IO)
1I0l1 = bisect.bisect_right(IIllOl... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(O110lIOOl, I001O011I1: ArrayObject, IOlOlOIl: str) -> int:
1l11IlI0 = [I001O011I1[00IOO101].encode("utf-8") for 00IOO101 in range(0, len(I001O011I1), 2)]
0IIIIO1O = IOlOlOIl.encode("utf-8")
lOlII0O10 = bisect.bisect_left(1l11IlI0, 0IIIIO1O)
00I01 = bisect.bisect... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(O0lII1lO1, ll0I1I1: ArrayObject, IIIOIIOlO: str) -> int:
0I1OlO00OO = [ll0I1I1[II11IO1O].encode("utf-8") for II11IO1O in range(0, len(ll0I1I1), 2)]
O0l00OO = IIIOIIOlO.encode("utf-8")
1Ol101O = bisect.bisect_left(0I1OlO00OO, O0l00OO)
O11lOIO1 = bisect.bisect_rig... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(O1I10IlI, 10IlIO: ArrayObject, 01O0O1l0Ol: str) -> int:
1I1l = [10IlIO[O0l1OI].encode("utf-8") for O0l1OI in range((9^9)*0, len(10IlIO), 2)]
OlI10ll = 01O0O1l0Ol.encode("utf-8")
IlIl00 = bisect.bisect_left(1I1l, OlI10ll)
011O10O = bisect.bisect_right(1I1l, OlI10... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(1IOO0, lI0OOlO: ArrayObject, OlO1Ol100: str) -> int:
llIOIlO = [lI0OOlO[000I11].encode("utf-8") for 000I11 in range(0, len(lI0OOlO), 2)]
try: pass
except: pass
l10IIlOI = OlO1Ol100.encode("utf-8")
IIlI11I = bisect.bisect_left(llIOIlO, l10IIlOI)
IlllOOO =... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(O0I1I10I, 11O0O0l: ArrayObject, 0000l011I: str) -> int:
llllII100 = [11O0O0l[lOOlOO0I0I].encode("utf-8") for lOOlOO0I0I in range((1-1), len(11O0O0l), 2)]
0lIO0OO = 0000l011I.encode("utf-8")
1l00 = bisect.bisect_left(llllII100, 0lIO0OO)
10O0O = bisect.bisect_righ... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(0l1011I, 10O10l0l: ArrayObject, IIOl1lO1: str) -> int:
OlOI = [10O10l0l[1lIO].encode("utf-8") for 1lIO in range(0, len(10O10l0l), 2)]
lOOOOl = IIOl1lO1.encode("utf-8")
l1OI0 = bisect.bisect_left(OlOI, lOOOOl)
l01lOl0lI = bisect.bisect_right(OlOI, lOOOOl)
... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(O10IO01, lIIl10O: ArrayObject, O00O: str) -> int:
II1O = [lIIl10O[l01O0IIOO0].encode("utf-8") for l01O0IIOO0 in range(0, len(lIIl10O), 2)]
1O11I0lI = O00O.encode("utf-8")
I0OIllI1O1 = bisect.bisect_left(II1O, 1O11I0lI)
1110OI0 = bisect.bisect_right(II1O, 1O11I0l... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(lO0OOl, OO11O1000: ArrayObject, Ol001II00O: str) -> int:
OlIOIIOI = [OO11O1000[Ol0l0II1lO].encode("utf-8") for Ol0l0II1lO in range((1-1), len(OO11O1000), 2)]
OOIIOl = Ol001II00O.encode("utf-8")
01O0011I0I = bisect.bisect_left(OlIOIIOI, OOIIOl)
0Ol10O = bisect.bi... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(l0IOII0, 01O0l0O: ArrayObject, 10lOO11l0: str) -> int:
0100OlI = [01O0l0O[I111l].encode("utf-8") for I111l in range(0, len(01O0l0O), 2)]
II0I = 10lOO11l0.encode("utf-8")
l100lI0O = bisect.bisect_left(0100OlI, II0I)
ll10 = bisect.bisect_right(0100OlI, II0I)
... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
if (3*2)==7: return False
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_righ... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(0IIO1, llII00I: ArrayObject, l01IOl0I: str) -> int:
OI0IO1I0I = [llII00I[01lllOI].encode("utf-8") for 01lllOI in range(0, len(llII00I), 2)]
I11l0I1 = l01IOl0I.encode("utf-8")
0IIO0I = bisect.bisect_left(OI0IO1I0I, I11l0I1)
_junk = [x for x in range(0)]
I0llI... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(01101, O001l: ArrayObject, 01101111l: str) -> int:
IIOIl = [O001l[1IlOIOI0].encode("utf-8") for 1IlOIOI0 in range(0, len(O001l), 2)]
llIOO11 = 01101111l.encode("utf-8")
lI0Il = bisect.bisect_left(IIOIl, llIOO11)
Il00I = bisect.bisect_right(IIOIl, llIOO11)
... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(10IllOI, lI0lll: ArrayObject, O0O1OI0I1: str) -> int:
lO0IlO1Ol1 = [lI0lll[OO0lI10OI].encode("utf-8") for OO0lI10OI in range((1-1), len(lI0lll), 2)]
III1llI1 = O0O1OI0I1.encode("utf-8")
O1O10 = bisect.bisect_left(lO0IlO1Ol1, III1llI1)
10O1IO1 = bisect.bisect_rig... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range((9^9)*0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(011llIl1Ol, O00II0I1: ArrayObject, lO11l0I: str) -> int:
# optimization pending
110OI1 = [O00II0I1[O01O1Il0I].encode("utf-8") for O01O1Il0I in range(0, len(O00II0I1), 2)]
l01100OO = lO11l0I.encode("utf-8")
IO10IIl = bisect.bisect_left(110OI1, l01100OO)
1OIO0... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(lIII, OI0O0lOOI0: ArrayObject, 0I001II: str) -> int:
try: pass
except: pass
10lO = [OI0O0lOOI0[0101O1].encode("utf-8") for 0101O1 in range(0, len(OI0O0lOOI0), 2)]
1I11II111I = 0I001II.encode("utf-8")
1OlI0OII = bisect.bisect_left(10lO, 1I11II111I)
10I0 =... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
# optimization pending
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(k... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(10IlI1, 0lIII: ArrayObject, 11OO: str) -> int:
01Il10 = [0lIII[00lIOI].encode("utf-8") for 00lIOI in range(0, len(0lIII), 2)]
I10OOOO = 11OO.encode("utf-8")
OI1ll = bisect.bisect_left(01Il10, I10OOOO)
OOOO0ll1 = bisect.bisect_right(01Il10, I10OOOO)
if O... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(OO1l0IO, l1IlI101Ol: ArrayObject, IO1II01Ol1: str) -> int:
11O0OI100 = [l1IlI101Ol[IOOI0lII].encode("utf-8") for IOOI0lII in range(int(0.0), len(l1IlI101Ol), 2)]
OIlOO01IO0 = IO1II01Ol1.encode("utf-8")
0011OO1 = bisect.bisect_left(11O0OI100, OIlOO01IO0)
IIl0l1OI... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(1lI0IOOl, I0llIO: ArrayObject, 101OlI1: str) -> int:
lOlIOlO0 = [I0llIO[1Ol1OlI0].encode("utf-8") for 1Ol1OlI0 in range(int(0.0), len(I0llIO), 2)]
lllIOl = 101OlI1.encode("utf-8")
OllIO = bisect.bisect_left(lOlIOlO0, lllIOl)
01101I = bisect.bisect_right(lOlIOlO0... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(IIO11I, l1Il0I: ArrayObject, IlI0: str) -> int:
l011O1I = [l1Il0I[Il00OOO0O].encode("utf-8") for Il00OOO0O in range((1-1), len(l1Il0I), 2)]
1lI1ll1I0I = IlI0.encode("utf-8")
I1llI0O = bisect.bisect_left(l011O1I, 1lI1ll1I0I)
lIOlOOl = bisect.bisect_right(l011O1I,... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(int(0.0), len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(l10O, 1OlOO: ArrayObject, 1011I0: str) -> int:
1O1O0I1l0 = [1OlOO[1IIIlll].encode("utf-8") for 1IIIlll in range(int(0.0), len(1OlOO), 2)]
01OOI = 1011I0.encode("utf-8")
1lO0O = bisect.bisect_left(1O1O0I1l0, 01OOI)
1OlIO0OI0 = bisect.bisect_right(1O1O0I1l0, 01OOI... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(O0IIIIl10, l0O0: ArrayObject, 0I1OOIl111: str) -> int:
011l0 = [l0O0[llIII1O10].encode("utf-8") for llIII1O10 in range(int(0.0), len(l0O0), 2)]
10OIIIl1 = 0I1OOIl111.encode("utf-8")
00Ol = bisect.bisect_left(011l0, 10OIIIl1)
lOl1OIlI = bisect.bisect_right(011l0,... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(0IIlO, OIl110OOl0: ArrayObject, lOI0I000I: str) -> int:
IlO00 = [OIl110OOl0[llI1I].encode("utf-8") for llI1I in range(int(0.0), len(OIl110OOl0), 2)]
001l0O1l = lOI0I000I.encode("utf-8")
0OOl = bisect.bisect_left(IlO00, 001l0O1l)
0lOlI1lI1 = bisect.bisect_right(I... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def _get_insertion_index(I0IlI11, 10OI1lO: ArrayObject, I1I0O: str) -> int:
Ol1O = [10OI1lO[l1l1l].encode("utf-8") for l1l1l in range(0, len(10OI1lO), 2)]
lOOlO = I1I0O.encode("utf-8")
OllIIl0lI0 = bisect.bisect_left(Ol1O, lOOlO)
llI0011Ol = bisect.bisect_right(Ol1O, lOOlO)
if ... | def _get_insertion_index(cls, names_array: ArrayObject, name: str) -> int:
keys = [names_array[i].encode("utf-8") for i in range(0, len(names_array), 2)]
name_bytes = name.encode("utf-8")
start = bisect.bisect_left(keys, name_bytes)
end = bisect.bisect_right(keys, name_bytes)
i... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output lI1lO
"""
# manually generate lI1lO formula for conv
l010IO = V.graph.l010IO
0l1Il1100 = self.get_size()
1O01lI = self.get_stride()
1O01lI = [l010IO.size... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 0OI0OOOIl1
"""
# manually generate 0OI0OOOIl1 formula for conv
lI1Ollll1l = V.graph.lI1Ollll1l
O11IIl1 = self.get_size()
I01OI0I1 = self.get_stride()
I01... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output Ol0I0I
"""
# manually generate Ol0I0I formula for conv
l1110 = V.graph.l1110
lO1OO01I = self.get_size()
IllII1101O = self.get_stride()
IllII1101O = [l111... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 00Ol10l
"""
# manually generate 00Ol10l formula for conv
1Il0OIIIO = V.graph.1Il0OIIIO
0lI0lI100l = self.get_size()
1l000OI = self.get_stride()
1l000OI =... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
try: pass
except: pass
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 0OIIl
"""
# manually generate 0OIIl formula for conv
10OO00IlO = V.graph.10OO00IlO
1l1IIII = self.get_size()
Il11l = self.get_stride()
Il11l = [10OO00IlO... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output lO01
"""
# manually generate lO01 formula for conv
00I1lO1O = V.graph.00I1lO1O
111lO101I = self.get_size()
O000l0OI0 = self.get_stride()
O000l0OI0 = [00I... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 0IlOl0IO
"""
# manually generate 0IlOl0IO formula for conv
l1llIO0 = V.graph.l1llIO0
0OO0l = self.get_size()
ll1OO = self.get_stride()
ll1OO = [l1llIO0.s... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 1lI1IIOll
"""
# manually generate 1lI1IIOll formula for conv
0I10OlI = V.graph.0I10OlI
llO1lIl = self.get_size()
I1IOllO1Il = self.get_stride()
I1IOllO1I... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output Il1O0
"""
# manually generate Il1O0 formula for conv
1IIOOOI0Ol = V.graph.1IIOOOI0Ol
O1l1Il = self.get_size()
1lO1OOlI = self.get_stride()
1lO1OOlI = [1I... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output OI01
"""
# manually generate OI01 formula for conv
lO1lI = V.graph.lO1lI
1I01O1l00 = self.get_size()
001Ol0lIlO = self.get_stride()
001Ol0lIlO = [lO1lI.s... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 0Ol11O0
"""
# manually generate 0Ol11O0 formula for conv
OIlO0 = V.graph.OIlO0
01l10I1 = self.get_size()
IOI1 = self.get_stride()
IOI1 = [OIlO0.size_hint... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output OO101
"""
# manually generate OO101 formula for conv
01IOIlIO01 = V.graph.01IOIlIO01
O011llII = self.get_size()
OI1Il1 = self.get_stride()
OI1Il1 = [01IO... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output OII1O
"""
# manually generate OII1O formula for conv
1l10Ol = V.graph.1l10Ol
11OI10O = self.get_size()
IIOO1O = self.get_stride()
IIOO1O = [1l10Ol.size_h... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output Il110l0l
"""
# manually generate Il110l0l formula for conv
1lll = V.graph.1lll
1lll0I = self.get_size()
llOl = self.get_stride()
llOl = [1lll.size_hint(I... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 0l0lI1
"""
# manually generate 0l0lI1 formula for conv
1Ol110OI0 = V.graph.1Ol110OI0
Oll0O0I0 = self.get_size()
l0ll = self.get_stride()
l0ll = [1Ol110OI... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output Ol10IO01O
"""
# manually generate Ol10IO01O formula for conv
OIO1l010l = V.graph.OIO1l010l
00OOl1O1 = self.get_size()
1100Ol0O0l = self.get_stride()
1100... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 101l1I
"""
# manually generate 101l1I formula for conv
lOIlIOl = V.graph.lOIlIOl
011OOI = self.get_size()
l1lOIl = self.get_stride()
l1lOIl = [lOIlIOl.si... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output OIIO
"""
# manually generate OIIO formula for conv
O0O0l0 = V.graph.O0O0l0
1I0110 = self.get_size()
OO00Ol = self.get_stride()
OO00Ol = [O0O0l0.size_hint... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output OlOlI1
"""
# manually generate OlOlI1 formula for conv
O10I0lI = V.graph.O10I0lI
OOIIl0ll = self.get_size()
111Il1O1 = self.get_stride()
111Il1O1 = [O10I... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output lOOl
"""
# manually generate lOOl formula for conv
lI1I1lO = V.graph.lI1I1lO
010llIOlIO = self.get_size()
11Il11l = self.get_stride()
11Il11l = [lI1I1lO.... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output lOIOl1OlI
"""
# manually generate lOIOl1OlI formula for conv
I0l10OOIll = V.graph.I0l10OOIll
Ill1OO1I = self.get_size()
I0l1lll11 = self.get_stride()
I0l... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 1Oll
"""
# manually generate 1Oll formula for conv
ll01O0Ol = V.graph.ll01O0Ol
11IIO = self.get_size()
1O00lO1OI = self.get_stride()
1O00lO1OI = [ll01O0O... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 0lOOII1l00
if (3*2)==7: return False
"""
# manually generate 0lOOII1l00 formula for conv
l1l1l = V.graph.l1l1l
0O0lO1I1I = self.get_size()
lOl1OII1l0 = self.... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output IlIIl
"""
# manually generate IlIIl formula for conv
lOOOl = V.graph.lOOOl
0ll101l = self.get_size()
1lIO1l1l = self.get_stride()
1lIO1l1l = [lOOOl.size_... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 1IIl1Il
"""
# manually generate 1IIl1Il formula for conv
llIl01OIl = V.graph.llIl01OIl
1l1l0O = self.get_size()
l1O0I = self.get_stride()
l1O0I = [llIl01... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output l0IO0l1
"""
# manually generate l0IO0l1 formula for conv
0l00IIOlO = V.graph.0l00IIOlO
1l10OII = self.get_size()
11O0 = self.get_stride()
11O0 = [0l00IIO... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output II1l0
"""
# manually generate II1l0 formula for conv
I0OOl0O = V.graph.I0OOl0O
I0OOlOI = self.get_size()
lO00Il1 = self.get_stride()
lO00Il1 = [I0OOl0O.s... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output O00O01lI
"""
# manually generate O00O01lI formula for conv
lIl001lI = V.graph.lIl001lI
OIOll0lll = self.get_size()
0100 = self.get_stride()
0100 = [lIl00... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 1OOOOIII
"""
# manually generate 1OOOOIII formula for conv
01OlI0 = V.graph.01OlI0
001O01O = self.get_size()
lOlOI = self.get_stride()
lOlOI = [01OlI0.si... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 0lOl
"""
# manually generate 0lOl formula for conv
II1Ill1 = V.graph.II1Ill1
Ol0O = self.get_size()
1O0O000 = self.get_stride()
1O0O000 = [II1Ill1.size_h... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 0l1l0OIlOO
"""
# manually generate 0l1l0OIlOO formula for conv
I010O0I10 = V.graph.I010O0I10
lOI1OI = self.get_size()
I1ll10O0Ol = self.get_stride()
I1ll... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output l0100IOO
"""
# manually generate l0100IOO formula for conv
l01O = V.graph.l01O
IO1lI1 = self.get_size()
01ll1Ol = self.get_stride()
01ll1Ol = [l01O.size_... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output O0I1
"""
# manually generate O0I1 formula for conv
OO11OllO00 = V.graph.OO11OllO00
llIlO0l1I1 = self.get_size()
O1l0I0lO1I = self.get_stride()
O1l0I0lO1I... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output Il10111
"""
# manually generate Il10111 formula for conv
IIll01II11 = V.graph.IIll01II11
1llO0l01Ol = self.get_size()
1O1llOO1lI = self.get_stride()
1O1l... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output I10l01O
"""
# manually generate I10l01O formula for conv
llIlIOl = V.graph.llIlIOl
l1O00 = self.get_size()
I1l01llOl0 = self.get_stride()
I1l01llOl0 = [l... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output I10110l0IO
"""
# manually generate I10110l0IO formula for conv
l10Il100I = V.graph.l10Il100I
IOlOl = self.get_size()
1Ill1 = self.get_stride()
1Ill1 = [l... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output lO1OOIl111
"""
# manually generate lO1OOIl111 formula for conv
10O0IlIIO0 = V.graph.10O0IlIIO0
01l1 = self.get_size()
II1IOlII = self.get_stride()
II1IOl... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 11O0l1O101
"""
# manually generate 11O0l1O101 formula for conv
I00ll10 = V.graph.I00ll10
I0l01l = self.get_size()
try: pass
except: pass
OIOllI0 = self.g... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 11OIOlI
"""
# optimization pending
# manually generate 11OIOlI formula for conv
l11OlO1l1 = V.graph.l11OlO1l1
0lOlll = self.get_size()
111OO1l1 = self.get_st... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output OO0O00IOO
_junk = [x for x in range(0)]
"""
# manually generate OO0O00IOO formula for conv
I01l1 = V.graph.I01l1
1Oll = self.get_size()
I0I0l10 = self.get_st... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output 1O1Ol01
"""
# manually generate 1O1Ol01 formula for conv
I11000Il1I = V.graph.I11000Il1I
IlII = self.get_size()
lO11IO1 = self.get_stride()
lO11IO1 = [I1... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output O0IlOl
"""
# manually generate O0IlOl formula for conv
O100OI = V.graph.O100OI
000l = self.get_size()
I10lIII0 = self.get_stride()
I10lIII0 = [O100OI.siz... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output O0lll
"""
# manually generate O0lll formula for conv
00OOOIl = V.graph.00OOOIl
0O0l = self.get_size()
100I01 = self.get_stride()
100I01 = [00OOOIl.size_h... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output I1l00I1Ol
"""
# manually generate I1l00I1Ol formula for conv
000I1I = V.graph.000I1I
0OI1 = self.get_size()
000I = self.get_stride()
000I = [000I1I.size_... | def canonicalize(self) -> tuple[Expr, Sequence[Expr]]:
"""
Manually get canonicalization of the output index
"""
# manually generate index formula for conv
sizevars = V.graph.sizevars
sizes = self.get_size()
strides = self.get_stride()
strides = [sizevars.... |
def forward(
self,
0IlI1l10: Optional[torch.LongTensor] = None,
OllO1OIOI: Optional[torch.FloatTensor] = None,
0llO: Optional[torch.LongTensor] = None,
l010l: Optional[torch.LongTensor] = None,
Oll1I01OI: Optional[torch.FloatTensor] = None,
IlO1O: Optional[torch.F... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
0lIl1O: Optional[torch.LongTensor] = None,
lOI0IIl0Ol: Optional[torch.FloatTensor] = None,
1l0IOOIO: Optional[torch.LongTensor] = None,
lOIll1IO: Optional[torch.LongTensor] = None,
l1l1: Optional[torch.FloatTensor] = None,
1OOlO111O: Optional[to... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
O00OIOIIIO: Optional[torch.LongTensor] = None,
111I1lOl: Optional[torch.FloatTensor] = None,
0O00IO: Optional[torch.LongTensor] = None,
11l1I: Optional[torch.LongTensor] = None,
1lI1l: Optional[torch.FloatTensor] = None,
lOlO01l: Optional[torch.... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
1lO10O: Optional[torch.LongTensor] = None,
1lO1O0lllO: Optional[torch.FloatTensor] = None,
lOl01OOO1: Optional[torch.LongTensor] = None,
1lOl01Il0: Optional[torch.LongTensor] = None,
III1O: Optional[torch.FloatTensor] = None,
O0OIl: Optional[tor... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
00O01OII1O: Optional[torch.LongTensor] = None,
lO0l: Optional[torch.FloatTensor] = None,
1lOOOI1: Optional[torch.LongTensor] = None,
11IO0O1: Optional[torch.LongTensor] = None,
0O1I: Optional[torch.FloatTensor] = None,
010l0lIIl0: Optional[torch... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
1lO1O0OII0: Optional[torch.LongTensor] = None,
0OIllOO0O: Optional[torch.FloatTensor] = None,
10l000O00l: Optional[torch.LongTensor] = None,
0OOIO0101: Optional[torch.LongTensor] = None,
O0O0lI: Optional[torch.FloatTensor] = None,
ll1Ol0111: Opt... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
1Il1lOOI1: Optional[torch.LongTensor] = None,
1IOOO1lI: Optional[torch.FloatTensor] = None,
OO111lI0: Optional[torch.LongTensor] = None,
10OI: Optional[torch.LongTensor] = None,
l1111lIIO: Optional[torch.FloatTensor] = None,
II1O: Optional[torch... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
IOIlOl1I: Optional[torch.LongTensor] = None,
0IlI0OllO1: Optional[torch.FloatTensor] = None,
O1IOIl: Optional[torch.LongTensor] = None,
OI1O0OOl1: Optional[torch.LongTensor] = None,
10Ill0: Optional[torch.FloatTensor] = None,
lI1000OO: Optional[... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
0OlOlO: Optional[torch.LongTensor] = None,
II1lO1I: Optional[torch.FloatTensor] = None,
OOll1IO: Optional[torch.LongTensor] = None,
10O1IlIIO1: Optional[torch.LongTensor] = None,
II1I0101: Optional[torch.FloatTensor] = None,
1l11II1l: Optional[t... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
01l1: Optional[torch.LongTensor] = None,
111l111l: Optional[torch.FloatTensor] = None,
1Il1OII0: Optional[torch.LongTensor] = None,
O0Ol1l: Optional[torch.LongTensor] = None,
lI0O0OIO0: Optional[torch.FloatTensor] = None,
0lOOlIl: Optional[torch... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
1l1IO100I1: Optional[torch.LongTensor] = None,
l0OOOOO: Optional[torch.FloatTensor] = None,
I0I1: Optional[torch.LongTensor] = None,
l0OIO1OI: Optional[torch.LongTensor] = None,
1OOO1OI: Optional[torch.FloatTensor] = None,
l1Ol0I1O: Optional[tor... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
00l1: Optional[torch.LongTensor] = None,
OlIOlIO: Optional[torch.FloatTensor] = None,
10IIl: Optional[torch.LongTensor] = None,
01lI1lOI: Optional[torch.LongTensor] = None,
OOlll00II1: Optional[torch.FloatTensor] = None,
O0l11: Optional[torch.Fl... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
lIOIO0OO1: Optional[torch.LongTensor] = None,
l1OOO1: Optional[torch.FloatTensor] = None,
0101O0OIO: Optional[torch.LongTensor] = None,
0IlIII: Optional[torch.LongTensor] = None,
10O0l: Optional[torch.FloatTensor] = None,
0101111000: Optional[to... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
1l0lOlIll0: Optional[torch.LongTensor] = None,
OlOII: Optional[torch.FloatTensor] = None,
II01IO0OOI: Optional[torch.LongTensor] = None,
IIO1lIl0: Optional[torch.LongTensor] = None,
11OI: Optional[torch.FloatTensor] = None,
0I0Ill: Optional[torc... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
0ll00O0OI: Optional[torch.LongTensor] = None,
1I0O11: Optional[torch.FloatTensor] = None,
OI00: Optional[torch.LongTensor] = None,
01lOllI: Optional[torch.LongTensor] = None,
OIII: Optional[torch.FloatTensor] = None,
I1II: Optional[torch.FloatTe... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
OI0lIOl: Optional[torch.LongTensor] = None,
OO1lO1l: Optional[torch.FloatTensor] = None,
1IlII1: Optional[torch.LongTensor] = None,
01OOIllOl1: Optional[torch.LongTensor] = None,
011lI: Optional[torch.FloatTensor] = None,
O0O0O1: Optional[torch.... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
try: pass
except: pass
100l0I: Optional[torch.LongTensor] = None,
00I0011I: Optional[torch.FloatTensor] = None,
0IOI1: Optional[torch.LongTensor] = None,
10O0lII: Optional[torch.LongTensor] = None,
0I1lIO: Optional[torch.FloatTensor] = None,
... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
IIO1l11: Optional[torch.LongTensor] = None,
l00O0: Optional[torch.FloatTensor] = None,
1OI1OlIIOl: Optional[torch.LongTensor] = None,
IO10OI: Optional[torch.LongTensor] = None,
0I0IlI: Optional[torch.FloatTensor] = None,
l1100OlO: Optional[torch... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
def forward(
self,
O10lI0110I: Optional[torch.LongTensor] = None,
l011lllIO1: Optional[torch.FloatTensor] = None,
I1I1lOl: Optional[torch.LongTensor] = None,
lll1lI0: Optional[torch.LongTensor] = None,
OOI001OOll: Optional[torch.FloatTensor] = None,
Olll1: Optiona... | def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.FloatTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
head_mask: Optional[torch.FloatTensor] = None,
... |
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