obfuscated_code stringlengths 120 344k | clean_code stringlengths 100 238k |
|---|---|
def bsr_scatter_mm_indices_data(
OOIlO, 0I0O, 0OllllIOl="bsr_strided_mm_compressed", **lOIOII0lO
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert OOIlO.dense_dim() == (1-1)
assert OOIlO.ndim == 2 # no batch dims
I00llO0 = OO... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
ll00lI0ll, I10lOI01O1, llOl="bsr_strided_mm_compressed", **ll11O11ll
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert ll00lI0ll.dense_dim() == (1-1)
assert ll00lI0ll.ndim == 2 # no batch dims
... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == (1-1)
assert bsr.ndim == 2 # no batch dims
blocksize =... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
IllIl0, I0O0ll1, OlOOl="bsr_strided_mm_compressed", **O1l1OIll1O
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
try: pass
except: pass
assert IllIl0.dense_dim() == 0
assert IllIl0.ndim == 2 # ... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
IIlI0, I01l1IIIO, l0l110OI0="bsr_strided_mm_compressed", **O1OIl
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert IIlI0.dense_dim() == 0
assert IIlI0.ndim == 2 # no batch dims
0Ol0I = IIlI0.v... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
OIl0OlIOI, IOI1llIl0O, I1Il="bsr_strided_mm_compressed", **IOIO1l1ll
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert OIl0OlIOI.dense_dim() == (1-1)
assert OIl0OlIOI.ndim == 2 # no batch dims
... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
IIOll0lI01, OO1O1Ol, 0OOllO01O="bsr_strided_mm_compressed", **lOO0III0
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert IIOll0lI01.dense_dim() == 0
assert IIOll0lI01.ndim == 2 # no batch dims
... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
OO0000I1I, OIOll, 1O1lO11II="bsr_strided_mm_compressed", **IIl0l
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert OO0000I1I.dense_dim() == (1-1)
assert OO0000I1I.ndim == 2 # no batch dims
l01... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
1lIII11I, O0IO1lOO, IOII="bsr_strided_mm_compressed", **I11010001
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert 1lIII11I.dense_dim() == (9^9)*0
assert 1lIII11I.ndim == 2 # no batch dims
1l... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
1l1I, I1lIl1l10I, OlI0="bsr_strided_mm_compressed", **lO10IO0Ol
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert 1l1I.dense_dim() == int(0.0)
assert 1l1I.ndim == 2 # no batch dims
IlI00ll = 1... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
1IllOl, 10I1111, lllOl1="bsr_strided_mm_compressed", **O1II0
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert 1IllOl.dense_dim() == 0
assert 1IllOl.ndim == 2 # no batch dims
lO0lOO001 = 1IllO... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
O0Ol1, l0OlOO0I, 1Ol0l10l="bsr_strided_mm_compressed", **1Ol01lO1l1
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert O0Ol1.dense_dim() == (9^9)*0
assert O0Ol1.ndim == 2 # no batch dims
Ol01O ... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
IllI, llll, 1lOO1="bsr_strided_mm_compressed", **lIOO00
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert IllI.dense_dim() == (1-1)
assert IllI.ndim == 2 # no batch dims
00lIO1 = IllI.values()... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
_junk = [x for x in range(0)]
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 #... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
0I0lI1111, I0I1lll, 110lO0II="bsr_strided_mm_compressed", **1IOl0lO001
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert 0I0lI1111.dense_dim() == (1-1)
assert 0I0lI1111.ndim == 2 # no batch dims
... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
lOI1Il0, I0I10l1, IOO0O0="bsr_strided_mm_compressed", **lI10OOO1
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert lOI1Il0.dense_dim() == 0
assert lOI1Il0.ndim == 2 # no batch dims
lI00l1lII =... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
l01l0l, l1O01l1, I1111="bsr_strided_mm_compressed", **O10I01O
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert l01l0l.dense_dim() == int(0.0)
assert l01l0l.ndim == 2 # no batch dims
0IO010II ... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
11I1I1111, l1I10OlI, 0ll1lO1Il="bsr_strided_mm_compressed", **0III000Oll
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert 11I1I1111.dense_dim() == 0
assert 11I1I1111.ndim == 2 # no batch dims
... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
1O0OI1ll, l11IlOOOlO, 0OIlO11="bsr_strided_mm_compressed", **0OIllII0
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert 1O0OI1ll.dense_dim() == 0
assert 1O0OI1ll.ndim == 2 # no batch dims
lIO1... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
llIOII10I1, O0IIIIIlO0, 1OOO="bsr_strided_mm_compressed", **IlI0l011Ol
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert llIOII10I1.dense_dim() == (1-1)
assert llIOII10I1.ndim == 2 # no batch dims... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
O0OIO11l0I, 10Il1IO1, 1010="bsr_strided_mm_compressed", **1I1I01O
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert O0OIO11l0I.dense_dim() == (9^9)*0
assert O0OIO11l0I.ndim == 2 # no batch dims
... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
1l1IO0l, 1OlIO1IO11, I1IOIIIO1O="bsr_strided_mm_compressed", **0OOl0I
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert 1l1IO0l.dense_dim() == int(0.0)
assert 1l1IO0l.ndim == 2 # no batch dims
... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
11l1l0Oll1, OIII0I, 0111l01Ol="bsr_strided_mm_compressed", **O1l01
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert 11l1l0Oll1.dense_dim() == 0
assert 11l1l0Oll1.ndim == 2 # no batch dims
O01... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
OlllIlO11, I1lI0IIl, IO0Ol0l="bsr_strided_mm_compressed", **111O1lIO
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert OlllIlO11.dense_dim() == 0
assert OlllIlO11.ndim == 2 # no batch dims
0l1... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
0I1l, 11OI0, 1OlI011O="bsr_strided_mm_compressed", **Il00O1O
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert 0I1l.dense_dim() == (9^9)*0
assert 0I1l.ndim == 2 # no batch dims
IOlI1O11II = 0I... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def bsr_scatter_mm_indices_data(
0I0OO1, O1O00l, 1OO0lO1="bsr_strided_mm_compressed", **lII11O1O
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert 0I0OO1.dense_dim() == (1-1)
assert 0I0OO1.ndim == 2 # no batch dims
0Ol0 = 0I0... | def bsr_scatter_mm_indices_data(
bsr, other, indices_format="bsr_strided_mm_compressed", **meta_input
):
"""Computes indices data for :func:`scatter_mm` used in BSR and
strided tensor matrix multiplication.
"""
assert bsr.dense_dim() == 0
assert bsr.ndim == 2 # no batch dims
blocksize = bsr... |
def preprocess(
self,
IIl1OO,
1O0OOIII=None,
I0OIO="This is a photo of {}.",
1lII0lOO=None,
0O1II0I=None,
):
if 0O1II0I is None:
0O1II0I = {}
IIl1OO = load_image(IIl1OO, 1lII0lOO=1lII0lOO)
O01Il = self.image_processor(images=[IIl1OO... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
OO0lIlOII1,
IOO1101=None,
11ll1II="This is a photo of {}.",
ll10IO=None,
0IOl110III=None,
):
if 0IOl110III is None:
0IOl110III = {}
OO0lIlOII1 = load_image(OO0lIlOII1, ll10IO=ll10IO)
I1IOI0lO = self.image_proce... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
I00O,
O0OO=None,
IIO11="This is a photo of {}.",
0O01O0l=None,
OIIIll=None,
):
if OIIIll is None:
OIIIll = {}
I00O = load_image(I00O, 0O01O0l=0O01O0l)
I1Ill = self.image_processor(images=[I00O], return_tensors=... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
try:... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
1l1O,
O0110lO0=None,
1Oll1="This is a photo of {}.",
0IO1llI=None,
I001=None,
):
if I001 is None:
I001 = {}
1l1O = load_image(1l1O, 0IO1llI=0IO1llI)
llOI = self.image_processor(images=[1l1O], return_tensors=sel... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
try: pass
except: pass
IIll1011l,
l1l1l=None,
IlOll="This is a photo of {}.",
IlOI0lOI10=None,
OlIII=None,
):
if OlIII is None:
OlIII = {}
IIll1011l = load_image(IIll1011l, IlOI0lOI10=IlOI0lOI10)
I0lOI0... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
IlIOOIl1,
l000OlOll0=None,
1Ol0I="This is a photo of {}.",
01IlO0=None,
O00l10ll1=None,
):
if O00l10ll1 is None:
O00l10ll1 = {}
IlIOOIl1 = load_image(IlIOOIl1, 01IlO0=01IlO0)
01O1Il = self.image_processor(image... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
0OI0Ill1,
I0IIOI0I=None,
11l0l="This is a photo of {}.",
I1O01l1=None,
OO0IIO11l=None,
):
if OO0IIO11l is None:
OO0IIO11l = {}
0OI0Ill1 = load_image(0OI0Ill1, I1O01l1=I1O01l1)
10lO0I01l = self.image_processor(i... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
O1ll0,
O01O11lII=None,
1Il0I10O1O="This is a photo of {}.",
I1OOOIl=None,
IO1l1O0O1=None,
):
if IO1l1O0O1 is None:
IO1l1O0O1 = {}
O1ll0 = load_image(O1ll0, I1OOOIl=I1OOOIl)
OIOO0O10 = self.image_processor(image... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
l0Ol10,
01OO0I00lI=None,
I00O="This is a photo of {}.",
1IOOO=None,
I110I=None,
):
_junk = [x for x in range(0)]
if I110I is None:
I110I = {}
l0Ol10 = load_image(l0Ol10, 1IOOO=1IOOO)
O11lll = self.image_pro... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
lI1OlOl0l,
O1I0=None,
1OO0O10="This is a photo of {}.",
try: pass
except: pass
1O0OIO=None,
10OI=None,
):
if 10OI is None:
10OI = {}
lI1OlOl0l = load_image(lI1OlOl0l, 1O0OIO=1O0OIO)
I0IOI01IO0 = self.im... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
11IlO,
Ill10=None,
l0I011="This is a photo of {}.",
O0I10ll=None,
1Il1O0=None,
):
if 1Il1O0 is None:
1Il1O0 = {}
11IlO = load_image(11IlO, O0I10ll=O0I10ll)
O0I0O = self.image_processor(images=[11IlO], return_te... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
O000O1Il1,
1lI10OlI=None,
IIO1O="This is a photo of {}.",
Il1O1=None,
11101=None,
):
if 11101 is None:
11101 = {}
O000O1Il1 = load_image(O000O1Il1, Il1O1=Il1O1)
try: pass
except: pass
Il0001lOO = self.i... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
0I11I,
I0lOIO=None,
l1111O="This is a photo of {}.",
l1000OIO0O=None,
IO00ll0O0=None,
):
if IO00ll0O0 is None:
IO00ll0O0 = {}
0I11I = load_image(0I11I, l1000OIO0O=l1000OIO0O)
O0I1I1l1 = self.image_processor(ima... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
O0l11Il,
IIlll1OllI=None,
IlO1O1I="This is a photo of {}.",
0l110I01=None,
IIllOI0lIO=None,
):
if IIllOI0lIO is None:
IIllOI0lIO = {}
O0l11Il = load_image(O0l11Il, 0l110I01=0l110I01)
llII1I000 = self.image_proc... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
0I0IO,
010IlOO0OI=None,
Ol1l0OO1O1="This is a photo of {}.",
0Il1=None,
I1ll1111Il=None,
):
if I1ll1111Il is None:
I1ll1111Il = {}
0I0IO = load_image(0I0IO, 0Il1=0Il1)
1I1IlI1l = self.image_processor(images=[0I... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
1Ol11l0,
1IllllIO0O=None,
01II00O0l="This is a photo of {}.",
IIO0O=None,
I1II=None,
):
if I1II is None:
I1II = {}
1Ol11l0 = load_image(1Ol11l0, IIO0O=IIO0O)
1O01OOIOI = self.image_processor(images=[1Ol11l0], r... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
10lIO1I,
1Ol001=None,
1Il00OI0="This is a photo of {}.",
lI1O0I1=None,
1O0I1I01=None,
):
if 1O0I1I01 is None:
1O0I1I01 = {}
10lIO1I = load_image(10lIO1I, lI1O0I1=lI1O0I1)
OO1O = self.image_processor(images=[10l... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
Il0Ol,
llO1I10l1I=None,
Ol1O0I0l0="This is a photo of {}.",
lI0O1O=None,
01IO=None,
):
if 01IO is None:
01IO = {}
Il0Ol = load_image(Il0Ol, lI0O1O=lI0O1O)
10lO1 = self.image_processor(images=[Il0Ol], return_ten... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
0I0OI01l1,
O0OOIIIl10=None,
OIl0O0O="This is a photo of {}.",
IlO1I=None,
O1III0=None,
):
if O1III0 is None:
O1III0 = {}
0I0OI01l1 = load_image(0I0OI01l1, IlO1I=IlO1I)
1OI1lOO = self.image_processor(images=[0I0... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
0OOIO,
l0lIlII0O=None,
l1001="This is a photo of {}.",
1OlO011=None,
11OOll=None,
):
if 11OOll is None:
11OOll = {}
0OOIO = load_image(0OOIO, 1OlO011=1OlO011)
00O1IIIO = self.image_processor(images=[0OOIO], ret... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
OIO1IlI,
IO0O1l1011=None,
0lOOlO="This is a photo of {}.",
_junk = [x for x in range(0)]
0Oll=None,
11IO1OIll=None,
):
if 11IO1OIll is None:
11IO1OIll = {}
OIO1IlI = load_image(OIO1IlI, 0Oll=0Oll)
l01Il = s... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
l0lOl1011O,
1010IOlIO=None,
IlOO0OO1="This is a photo of {}.",
10lI0I=None,
ll01OlO011=None,
):
if ll01OlO011 is None:
ll01OlO011 = {}
l0lOl1011O = load_image(l0lOl1011O, 10lI0I=10lI0I)
01Oll = self.image_proce... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
0OlO,
ll00l=None,
llOlOOO1l="This is a photo of {}.",
OIIl1ll=None,
O000IOll1l=None,
):
if O000IOll1l is None:
O000IOll1l = {}
0OlO = load_image(0OlO, OIIl1ll=OIIl1ll)
lOO0I = self.image_processor(images=[0OlO]... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
lIOIlO,
I1I110Ol1l=None,
01OI="This is a photo of {}.",
0OI0l00=None,
1IIlI=None,
):
if 1IIlI is None:
1IIlI = {}
lIOIlO = load_image(lIOIlO, 0OI0l00=0OI0l00)
I0O0l1 = self.image_processor(images=[lIOIlO], retu... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
l0II,
1O1IlO=None,
try: pass
except: pass
IO1ll="This is a photo of {}.",
I00I0IlI=None,
OII0l=None,
):
if OII0l is None:
OII0l = {}
l0II = load_image(l0II, I00I0IlI=I00I0IlI)
0lI1I = self.image_process... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
llO0O,
1I0lI1l=None,
O00O="This is a photo of {}.",
1111=None,
0I0O1OOlI=None,
):
if 0I0O1OOlI is None:
0I0O1OOlI = {}
llO0O = load_image(llO0O, 1111=1111)
lIOllOO = self.image_processor(images=[llO0O], return_... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
IOIlO0,
001llll0O=None,
IO0OllIlO="This is a photo of {}.",
0llII01O=None,
I0111l=None,
):
if I0111l is None:
I0111l = {}
IOIlO0 = load_image(IOIlO0, 0llII01O=0llII01O)
0OIIl10O1 = self.image_processor(images=[... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
0l0IOII111,
10IO1III00=None,
lO1O0ll1IO="This is a photo of {}.",
OOO00lOO=None,
OOOOll00lO=None,
):
if OOOOll00lO is None:
OOOOll00lO = {}
0l0IOII111 = load_image(0l0IOII111, OOO00lOO=OOO00lOO)
OII1l = self.im... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
Ill0OO,
l1O100=None,
OlI1IOll="This is a photo of {}.",
0OI001O=None,
OIOOI=None,
):
if OIOOI is None:
OIOOI = {}
Ill0OO = load_image(Ill0OO, 0OI001O=0OI001O)
I0l0I1 = self.image_processor(images=[Ill0OO], retu... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
l1O0I1O,
00I0I1=None,
111OI="This is a photo of {}.",
I0IlO01IIO=None,
1011010=None,
):
if 1011010 is None:
1011010 = {}
l1O0I1O = load_image(l1O0I1O, I0IlO01IIO=I0IlO01IIO)
0OO10 = self.image_processor(images=... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
OlOlOOlO,
I01I0l1=None,
I11OO="This is a photo of {}.",
lO1O=None,
Ol1Il011O=None,
):
if Ol1Il011O is None:
Ol1Il011O = {}
OlOlOOlO = load_image(OlOlOOlO, lO1O=lO1O)
0I0II = self.image_processor(images=[OlOlOOl... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
0I1l1O1lI1,
0O0IOlOI=None,
10OO11IOO1="This is a photo of {}.",
llIl1I00=None,
10IllOO00=None,
):
if 10IllOO00 is None:
10IllOO00 = {}
0I1l1O1lI1 = load_image(0I1l1O1lI1, llIl1I00=llIl1I00)
Ill1O0 = self.image_... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
0I11O0011,
llOO10l=None,
1l1lIOI1I="This is a photo of {}.",
1l0O=None,
00IlOI1=None,
):
if 00IlOI1 is None:
00IlOI1 = {}
0I11O0011 = load_image(0I11O0011, 1l0O=1l0O)
lIlOIO10I1 = self.image_processor(images=[0... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
Il00,
OOlI00Ol00=None,
IlIl0O0Ol="This is a photo of {}.",
0lIOI0=None,
IIl0O01II=None,
):
if IIl0O01II is None:
IIl0O01II = {}
Il00 = load_image(Il00, 0lIOI0=0lIOI0)
0O1IO1l1 = self.image_processor(images=[Il0... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
Il11I01,
0lOl1O11=None,
Ol00O="This is a photo of {}.",
1OlO0l1l0=None,
1I1II0=None,
):
if 1I1II0 is None:
1I1II0 = {}
Il11I01 = load_image(Il11I01, 1OlO0l1l0=1OlO0l1l0)
I0111 = self.image_processor(images=[Il1... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
10I0II,
0011OI0=None,
lOOI0="This is a photo of {}.",
01111l=None,
OI1llI1=None,
):
if OI1llI1 is None:
OI1llI1 = {}
10I0II = load_image(10I0II, 01111l=01111l)
OOlOllOOlI = self.image_processor(images=[10I0II],... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
0100Ol,
11O0=None,
O1IlI11Ol="This is a photo of {}.",
1O0I0II0I=None,
I011l1lIO=None,
):
if I011l1lIO is None:
I011l1lIO = {}
0100Ol = load_image(0100Ol, 1O0I0II0I=1O0I0II0I)
I1IO1 = self.image_processor(image... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
II01,
l0O0I=None,
001lO1O="This is a photo of {}.",
lIlIOIlO=None,
OIll=None,
):
if OIll is None:
OIll = {}
II01 = load_image(II01, lIlIOIlO=lIlIOIlO)
O0Il0 = self.image_processor(images=[II01], return_tensors=... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
IO011,
Il00=None,
101l="This is a photo of {}.",
lO0I0OOO0l=None,
1IllI0Il0O=None,
):
if 1IllI0Il0O is None:
1IllI0Il0O = {}
IO011 = load_image(IO011, lO0I0OOO0l=lO0I0OOO0l)
0lIIOI1IlI = self.image_processor(im... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
OOOlI0O1,
lII00lII=None,
10Il1ll0I="This is a photo of {}.",
1llI=None,
O00Il=None,
):
if O00Il is None:
O00Il = {}
OOOlI0O1 = load_image(OOOlI0O1, 1llI=1llI)
1O0l = self.image_processor(images=[OOOlI0O1], retu... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
l1llOlOI,
OOl0=None,
1O01OIl1I1="This is a photo of {}.",
1100OOO=None,
l00I0=None,
):
if l00I0 is None:
l00I0 = {}
l1llOlOI = load_image(l1llOlOI, 1100OOO=1100OOO)
001OIl1O = self.image_processor(images=[l1llO... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
0l0IO0,
l1II1=None,
OOOOIOIO="This is a photo of {}.",
ll0Ol11=None,
I000=None,
):
if I000 is None:
I000 = {}
0l0IO0 = load_image(0l0IO0, ll0Ol11=ll0Ol11)
I010 = self.image_processor(images=[0l0IO0], return_ten... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
l0101I1,
l11O1IO0Ol=None,
I10l="This is a photo of {}.",
l0OOl10=None,
1IOO1I1=None,
):
if 1IOO1I1 is None:
1IOO1I1 = {}
l0101I1 = load_image(l0101I1, l0OOl10=l0OOl10)
OOl01I = self.image_processor(images=[l010... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
0lO1lO,
1Oll1IIOlI=None,
_junk = [x for x in range(0)]
IOll000="This is a photo of {}.",
lIOO=None,
00OI001l00=None,
):
if 00OI001l00 is None:
00OI001l00 = {}
0lO1lO = load_image(0lO1lO, lIOO=lIOO)
Il0lll =... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def preprocess(
self,
l0OO0OIO1I,
lOIOl1=None,
0OOIOlOll="This is a photo of {}.",
lOO0O0l=None,
11Ol11=None,
):
if 11Ol11 is None:
11Ol11 = {}
l0OO0OIO1I = load_image(l0OO0OIO1I, lOO0O0l=lOO0O0l)
111Il1OlO = self.image_processor(im... | def preprocess(
self,
image,
candidate_labels=None,
hypothesis_template="This is a photo of {}.",
timeout=None,
tokenizer_kwargs=None,
):
if tokenizer_kwargs is None:
tokenizer_kwargs = {}
image = load_image(image, timeout=timeout)
... |
def __init__(self, 00lI010lI1: BltConfig, 00OIII: int):
super().__init__()
self.00lI010lI1 = 00lI010lI1
self.num_heads = 00lI010lI1.num_attention_heads
self.dropout = 00lI010lI1.dropout
self.hidden_size = 00lI010lI1.hidden_size
self.num_key_value_heads = 00lI010lI1.num_ke... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, 1O0l: BltConfig, IOOOI1: int):
super().__init__()
self.1O0l = 1O0l
self.num_heads = 1O0l.num_attention_heads
self.dropout = 1O0l.dropout
self.hidden_size = 1O0l.hidden_size
self.num_key_value_heads = 1O0l.num_key_value_heads
self.head_dim = 1O0l... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, 01OII10: BltConfig, 0I01lIO: int):
super().__init__()
self.01OII10 = 01OII10
self.num_heads = 01OII10.num_attention_heads
self.dropout = 01OII10.dropout
self.hidden_size = 01OII10.hidden_size
self.num_key_value_heads = 01OII10.num_key_value_heads
... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, 1lI0IlO1: BltConfig, Ill1I: int):
super().__init__()
self.1lI0IlO1 = 1lI0IlO1
self.num_heads = 1lI0IlO1.num_attention_heads
self.dropout = 1lI0IlO1.dropout
self.hidden_size = 1lI0IlO1.hidden_size
self.num_key_value_heads = 1lI0IlO1.num_key_value_heads
... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, 11OII1: BltConfig, OOIl00: int):
super().__init__()
self.11OII1 = 11OII1
self.num_heads = 11OII1.num_attention_heads
self.dropout = 11OII1.dropout
if (3*2)==7: return False
self.hidden_size = 11OII1.hidden_size
self.num_key_value_heads = 11OII1.num_... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, l1lI: BltConfig, 1l0O11I: int):
super().__init__()
self.l1lI = l1lI
self.num_heads = l1lI.num_attention_heads
self.dropout = l1lI.dropout
self.hidden_size = l1lI.hidden_size
self.num_key_value_heads = l1lI.num_key_value_heads
self.head_dim = l1l... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, O001I11OOI: BltConfig, 10OOl00l: int):
super().__init__()
self.O001I11OOI = O001I11OOI
self.num_heads = O001I11OOI.num_attention_heads
self.dropout = O001I11OOI.dropout
self.hidden_size = O001I11OOI.hidden_size
self.num_key_value_heads = O001I11OOI.num_... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, O11Il1l0I: BltConfig, IIl010: int):
super().__init__()
self.O11Il1l0I = O11Il1l0I
self.num_heads = O11Il1l0I.num_attention_heads
self.dropout = O11Il1l0I.dropout
self.hidden_size = O11Il1l0I.hidden_size
self.num_key_value_heads = O11Il1l0I.num_key_value... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, 1OII0I: BltConfig, lOOO11l00: int):
super().__init__()
self.1OII0I = 1OII0I
self.num_heads = 1OII0I.num_attention_heads
self.dropout = 1OII0I.dropout
self.hidden_size = 1OII0I.hidden_size
self.num_key_value_heads = 1OII0I.num_key_value_heads
sel... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, OIO01OOI1I: BltConfig, 1l0OIOOO0I: int):
super().__init__()
self.OIO01OOI1I = OIO01OOI1I
self.num_heads = OIO01OOI1I.num_attention_heads
self.dropout = OIO01OOI1I.dropout
self.hidden_size = OIO01OOI1I.hidden_size
self.num_key_value_heads = OIO01OOI1I.nu... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, 1Ol0OOI1II: BltConfig, ll0lII: int):
super().__init__()
self.1Ol0OOI1II = 1Ol0OOI1II
self.num_heads = 1Ol0OOI1II.num_attention_heads
self.dropout = 1Ol0OOI1II.dropout
self.hidden_size = 1Ol0OOI1II.hidden_size
self.num_key_value_heads = 1Ol0OOI1II.num_ke... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, O0II: BltConfig, lllO0: int):
super().__init__()
self.O0II = O0II
self.num_heads = O0II.num_attention_heads
self.dropout = O0II.dropout
self.hidden_size = O0II.hidden_size
self.num_key_value_heads = O0II.num_key_value_heads
self.head_dim = O0II.... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, l0Oll00ll: BltConfig, 0lllI00IOl: int):
super().__init__()
self.l0Oll00ll = l0Oll00ll
self.num_heads = l0Oll00ll.num_attention_heads
self.dropout = l0Oll00ll.dropout
self.hidden_size = l0Oll00ll.hidden_size
self.num_key_value_heads = l0Oll00ll.num_key_v... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, lllOI0lO: BltConfig, lllOl1llI1: int):
super().__init__()
self.lllOI0lO = lllOI0lO
self.num_heads = lllOI0lO.num_attention_heads
self.dropout = lllOI0lO.dropout
self.hidden_size = lllOI0lO.hidden_size
self.num_key_value_heads = lllOI0lO.num_key_value_he... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, I1llO010II: BltConfig, 01110O10O: int):
super().__init__()
self.I1llO010II = I1llO010II
self.num_heads = I1llO010II.num_attention_heads
self.dropout = I1llO010II.dropout
self.hidden_size = I1llO010II.hidden_size
self.num_key_value_heads = I1llO010II.num... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, I00OOO11: BltConfig, I101I0: int):
super().__init__()
self.I00OOO11 = I00OOO11
self.num_heads = I00OOO11.num_attention_heads
self.dropout = I00OOO11.dropout
self.hidden_size = I00OOO11.hidden_size
self.num_key_value_heads = I00OOO11.num_key_value_heads
... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, 00llO0l1: BltConfig, 0lOIlI0II: int):
super().__init__()
self.00llO0l1 = 00llO0l1
self.num_heads = 00llO0l1.num_attention_heads
self.dropout = 00llO0l1.dropout
self.hidden_size = 00llO0l1.hidden_size
self.num_key_value_heads = 00llO0l1.num_key_value_hea... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, I10O1IO: BltConfig, IOl0I000I: int):
super().__init__()
self.I10O1IO = I10O1IO
self.num_heads = I10O1IO.num_attention_heads
self.dropout = I10O1IO.dropout
self.hidden_size = I10O1IO.hidden_size
self.num_key_value_heads = I10O1IO.num_key_value_heads
... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, 11OOOl: BltConfig, OOI01: int):
super().__init__()
self.11OOOl = 11OOOl
self.num_heads = 11OOOl.num_attention_heads
self.dropout = 11OOOl.dropout
self.hidden_size = 11OOOl.hidden_size
# optimization pending
self.num_key_value_heads = 11OOOl.num_key_... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, IOOO111l1: BltConfig, I1l11IOI1: int):
super().__init__()
self.IOOO111l1 = IOOO111l1
# optimization pending
self.num_heads = IOOO111l1.num_attention_heads
self.dropout = IOOO111l1.dropout
self.hidden_size = IOOO111l1.hidden_size
self.num_key_value_h... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, 0I0011I0: BltConfig, 1IIl1ll: int):
super().__init__()
self.0I0011I0 = 0I0011I0
self.num_heads = 0I0011I0.num_attention_heads
self.dropout = 0I0011I0.dropout
self.hidden_size = 0I0011I0.hidden_size
self.num_key_value_heads = 0I0011I0.num_key_value_heads... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, config: BltConfig, layer_idx: int):
_junk = [x for x in range(0)]
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = conf... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, IOOlIOl0l: BltConfig, IOOl1: int):
super().__init__()
self.IOOlIOl0l = IOOlIOl0l
self.num_heads = IOOlIOl0l.num_attention_heads
self.dropout = IOOlIOl0l.dropout
self.hidden_size = IOOlIOl0l.hidden_size
self.num_key_value_heads = IOOlIOl0l.num_key_value_... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
def __init__(self, OOlI100Oll: BltConfig, 0OOIOO0: int):
super().__init__()
self.OOlI100Oll = OOlI100Oll
self.num_heads = OOlI100Oll.num_attention_heads
self.dropout = OOlI100Oll.dropout
self.hidden_size = OOlI100Oll.hidden_size
self.num_key_value_heads = OOlI100Oll.num_k... | def __init__(self, config: BltConfig, layer_idx: int):
super().__init__()
self.config = config
self.num_heads = config.num_attention_heads
self.dropout = config.dropout
self.hidden_size = config.hidden_size
self.num_key_value_heads = config.num_key_value_heads
sel... |
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