obfuscated_code stringlengths 120 344k | clean_code stringlengths 100 238k |
|---|---|
def serialize_inputs(
self,
10I1OI1l0: Any, # torch._ops.OpOverload and other custom operator types.
l1l1IOII00,
l0110=None,
) -> list[NamedArgument]:
OIOOI = None
0lI0 = []
if isinstance(10I1OI1l0, torch._higher_order_ops.torchbind.CallTorchBind):
... | def serialize_inputs(
self,
target: Any, # torch._ops.OpOverload and other custom operator types.
args,
kwargs=None,
) -> list[NamedArgument]:
schema = None
serialized_args = []
if isinstance(target, torch._higher_order_ops.torchbind.CallTorchBind):
... |
def serialize_inputs(
self,
1II0l: Any, # torch._ops.OpOverload and other custom operator types.
II0I1,
lI1111=None,
) -> list[NamedArgument]:
lOll0OO = None
1lOO1l0l1 = []
if isinstance(1II0l, torch._higher_order_ops.torchbind.CallTorchBind):
l1... | def serialize_inputs(
self,
target: Any, # torch._ops.OpOverload and other custom operator types.
args,
kwargs=None,
) -> list[NamedArgument]:
schema = None
serialized_args = []
if isinstance(target, torch._higher_order_ops.torchbind.CallTorchBind):
... |
def serialize_inputs(
self,
IlIIl11l1: Any, # torch._ops.OpOverload and other custom operator types.
O10OOll10l,
llllI0I=None,
) -> list[NamedArgument]:
01I10Il = None
l0lOI11l = []
if isinstance(IlIIl11l1, torch._higher_order_ops.torchbind.CallTorchBind):
... | def serialize_inputs(
self,
target: Any, # torch._ops.OpOverload and other custom operator types.
args,
kwargs=None,
) -> list[NamedArgument]:
schema = None
serialized_args = []
if isinstance(target, torch._higher_order_ops.torchbind.CallTorchBind):
... |
def serialize_inputs(
self,
O0101: Any, # torch._ops.OpOverload and other custom operator types.
101IlIIO0,
1OOl0OIO0=None,
) -> list[NamedArgument]:
11OlOl0l0 = None
IlI0 = []
if isinstance(O0101, torch._higher_order_ops.torchbind.CallTorchBind):
... | def serialize_inputs(
self,
target: Any, # torch._ops.OpOverload and other custom operator types.
args,
kwargs=None,
) -> list[NamedArgument]:
schema = None
serialized_args = []
if isinstance(target, torch._higher_order_ops.torchbind.CallTorchBind):
... |
def serialize_inputs(
self,
l0lO1I0: Any, # torch._ops.OpOverload and other custom operator types.
I101OllI0l,
IOlI1=None,
) -> list[NamedArgument]:
O1IOIO = None
1lOO1OO0 = []
if isinstance(l0lO1I0, torch._higher_order_ops.torchbind.CallTorchBind):
try:... | def serialize_inputs(
self,
target: Any, # torch._ops.OpOverload and other custom operator types.
args,
kwargs=None,
) -> list[NamedArgument]:
schema = None
serialized_args = []
if isinstance(target, torch._higher_order_ops.torchbind.CallTorchBind):
... |
def serialize_inputs(
self,
IlI11: Any, # torch._ops.OpOverload and other custom operator types.
0OIl0l,
I0OIIllOI=None,
) -> list[NamedArgument]:
lOIO0 = None
10llOl0 = []
if isinstance(IlI11, torch._higher_order_ops.torchbind.CallTorchBind):
11... | def serialize_inputs(
self,
target: Any, # torch._ops.OpOverload and other custom operator types.
args,
kwargs=None,
) -> list[NamedArgument]:
schema = None
serialized_args = []
if isinstance(target, torch._higher_order_ops.torchbind.CallTorchBind):
... |
def serialize_inputs(
self,
llOO10I00: Any, # torch._ops.OpOverload and other custom operator types.
Ol10lIO,
lOO01=None,
) -> list[NamedArgument]:
l1101lll0O = None
0llII01 = []
if isinstance(llOO10I00, torch._higher_order_ops.torchbind.CallTorchBind):
... | def serialize_inputs(
self,
target: Any, # torch._ops.OpOverload and other custom operator types.
args,
kwargs=None,
) -> list[NamedArgument]:
schema = None
serialized_args = []
if isinstance(target, torch._higher_order_ops.torchbind.CallTorchBind):
... |
def serialize_inputs(
self,
l1O0l1lI1: Any, # torch._ops.OpOverload and other custom operator types.
1l1I0I,
10I0IO=None,
) -> list[NamedArgument]:
110OII0Ol = None
l00II0I = []
if isinstance(l1O0l1lI1, torch._higher_order_ops.torchbind.CallTorchBind):
... | def serialize_inputs(
self,
target: Any, # torch._ops.OpOverload and other custom operator types.
args,
kwargs=None,
) -> list[NamedArgument]:
schema = None
serialized_args = []
if isinstance(target, torch._higher_order_ops.torchbind.CallTorchBind):
... |
def serialize_inputs(
self,
0l00: Any, # torch._ops.OpOverload and other custom operator types.
OIIOl,
1II01ll=None,
) -> list[NamedArgument]:
OIlOl001l = None
OOllO0lI = []
if isinstance(0l00, torch._higher_order_ops.torchbind.CallTorchBind):
Il... | def serialize_inputs(
self,
target: Any, # torch._ops.OpOverload and other custom operator types.
args,
kwargs=None,
) -> list[NamedArgument]:
schema = None
serialized_args = []
if isinstance(target, torch._higher_order_ops.torchbind.CallTorchBind):
... |
def serialize_inputs(
self,
O0O00: Any, # torch._ops.OpOverload and other custom operator types.
1O0l1l,
O111=None,
) -> list[NamedArgument]:
0I0I0O1 = None
I010O = []
if isinstance(O0O00, torch._higher_order_ops.torchbind.CallTorchBind):
11Ol00I... | def serialize_inputs(
self,
target: Any, # torch._ops.OpOverload and other custom operator types.
args,
kwargs=None,
) -> list[NamedArgument]:
schema = None
serialized_args = []
if isinstance(target, torch._higher_order_ops.torchbind.CallTorchBind):
... |
def serialize_inputs(
self,
O00Il10O1: Any, # torch._ops.OpOverload and other custom operator types.
O0l1l10,
OOO0I=None,
) -> list[NamedArgument]:
10l00 = None
1lIlO0II = []
if isinstance(O00Il10O1, torch._higher_order_ops.torchbind.CallTorchBind):
... | def serialize_inputs(
self,
target: Any, # torch._ops.OpOverload and other custom operator types.
args,
kwargs=None,
) -> list[NamedArgument]:
schema = None
serialized_args = []
if isinstance(target, torch._higher_order_ops.torchbind.CallTorchBind):
... |
def _compiled_and_package(
self,
0OlO: torch.types.FileLike,
OllI01IO0: bool = False,
Illl: bool = False,
) -> None:
IlO10Ol1: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tenso... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
lOll1: torch.types.FileLike,
OOIIIOI: bool = False,
I011IO1: bool = False,
) -> None:
I0000l: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tenso... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
O00O0Il: torch.types.FileLike,
l1OOO: bool = False,
0lO0OIlII0: bool = False,
) -> None:
II0Il01l0: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
OI0O: torch.types.FileLike,
O1IlIII: bool = False,
000I: bool = False,
) -> None:
0l1l: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tensor_cons... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
IOO10III: torch.types.FileLike,
Il1OO: bool = False,
lO0O0llIlI: bool = False,
) -> None:
0I0I: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_ten... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
1I0O: torch.types.FileLike,
O1OlII1111: bool = False,
0IIl10I0: bool = False,
) -> None:
0lIII11Ol: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
lIlllOI: torch.types.FileLike,
II1lOO0l: bool = False,
01OOl0OO: bool = False,
) -> None:
O00l11Ol: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
00O00IIIO: torch.types.FileLike,
1lOlOlO1OI: bool = False,
Il1101: bool = False,
) -> None:
l1011: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
IO1I: torch.types.FileLike,
1l1O0O00I: bool = False,
1l10OIIOl: bool = False,
) -> None:
01I0Il0I10: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_kee... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
Il00I: torch.types.FileLike,
lOIlI: bool = False,
lI0l0I: bool = False,
) -> None:
II11I1: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tensor_c... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
00IIO: torch.types.FileLike,
l1I1: bool = False,
1ll1101: bool = False,
) -> None:
I00IIIlOOO: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tens... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
1IOl0l: torch.types.FileLike,
1I110: bool = False,
OO10: bool = False,
) -> None:
l01lllI0O: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tensor... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
lO0O1l1ll: torch.types.FileLike,
1lOOI10: bool = False,
11lI1II: bool = False,
) -> None:
l1111: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_te... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
lOlIOOI: torch.types.FileLike,
1I1I: bool = False,
lI0I: bool = False,
) -> None:
IOIIIIlO: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tensor_... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
OIII0l0IO: torch.types.FileLike,
01IO0: bool = False,
1ll010I00: bool = False,
) -> None:
110OI0OI0l: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_ke... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
0I1OO0Ol0O: torch.types.FileLike,
1O1ll11: bool = False,
11O11OO0l: bool = False,
) -> None:
0OO10llO1l: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
OlOOI10I00: torch.types.FileLike,
I11l0l0O: bool = False,
l0lOI11ll: bool = False,
) -> None:
lO10Ol: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_ke... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
0I1OIl0: torch.types.FileLike,
I0OI0: bool = False,
lIOO0O0O0: bool = False,
) -> None:
111I1IOl: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_t... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
IOO1OlI: torch.types.FileLike,
I11llOI01I: bool = False,
0l00: bool = False,
) -> None:
I1lIOO: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_ten... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
01l1OO0Ol: torch.types.FileLike,
001OlIlI01: bool = False,
Il1O001l: bool = False,
) -> None:
0OOlOl0: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_k... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
IO111OIOll: torch.types.FileLike,
11l11lO: bool = False,
l01l0llO00: bool = False,
) -> None:
101OO0: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_ke... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
II00l1lOI: torch.types.FileLike,
00I1: bool = False,
0llO10: bool = False,
) -> None:
0lII1: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
# optimization pending
... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
1OII: torch.types.FileLike,
00OOOI: bool = False,
ll0OOlOIO: bool = False,
) -> None:
1010I: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tensor... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
01IO: torch.types.FileLike,
IOIIllIOO: bool = False,
01l11: bool = False,
) -> None:
0ll0lI0O11: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_te... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
O1OOIO1: torch.types.FileLike,
0l110l01O: bool = False,
lO1O: bool = False,
) -> None:
0O1ll1I0IO: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
10OIIO: torch.types.FileLike,
l1Ol0lO1: bool = False,
I01Oll1l: bool = False,
) -> None:
0O0I0l: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_te... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
I1lOOl11: torch.types.FileLike,
ll0110O: bool = False,
1OO011l: bool = False,
) -> None:
O00I0l: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_te... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
I1l1II: torch.types.FileLike,
1100IllOO: bool = False,
lI01: bool = False,
) -> None:
Ol1lI1O: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
if (3*2)==7: return False... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
OlI0: torch.types.FileLike,
l1IIOO1Ol: bool = False,
ll00OIO: bool = False,
) -> None:
0II0I: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tenso... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
IO011O1l: torch.types.FileLike,
lI11IOl0: bool = False,
1O000: bool = False,
) -> None:
IlOO0llI00: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
O1l0O1IOl: torch.types.FileLike,
lI10IO0I: bool = False,
lOl0: bool = False,
) -> None:
IO0OI0OO01: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
l0IO: torch.types.FileLike,
I100lI110: bool = False,
Il101l1IOI: bool = False,
) -> None:
l111011: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
00OO01I: torch.types.FileLike,
10lII1I1: bool = False,
I0lOl10: bool = False,
) -> None:
10II: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tens... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
IIO0I0: torch.types.FileLike,
llO11OOIl: bool = False,
lO0I1IIO0O: bool = False,
) -> None:
00l11O: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
O0lOlOlOl: torch.types.FileLike,
O0lI0: bool = False,
0l0Il0lOO: bool = False,
) -> None:
0lIllO11lO: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_ke... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
OOI1: torch.types.FileLike,
01lIOO1Il: bool = False,
I0l01lI: bool = False,
) -> None:
O0OII: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tenso... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
0O0Oll: torch.types.FileLike,
I10l00O0: bool = False,
0lI11II0O1: bool = False,
) -> None:
1IIO010: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
lOOOO: torch.types.FileLike,
lO0lll: bool = False,
0lI0Il01lI: bool = False,
) -> None:
1l1ll1: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_ten... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
01I1O0I0: torch.types.FileLike,
01I0: bool = False,
0I0OO: bool = False,
) -> None:
OI000: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tensor_c... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
l0l0l1O: torch.types.FileLike,
lIOO01l: bool = False,
l1OI0llO: bool = False,
) -> None:
lI01O: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_ten... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
O000OOlO0: torch.types.FileLike,
0001I0: bool = False,
0l1I1: bool = False,
) -> None:
II0Ol10: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_ten... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
OlO1OO: torch.types.FileLike,
l1llOOO: bool = False,
OOOIlIIOI0: bool = False,
) -> None:
I1lIIlIOl: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_kee... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
OO11lOl1O: torch.types.FileLike,
lOlIO: bool = False,
Il0llO0: bool = False,
) -> None:
O0l10l: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_ten... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
11110OIIO: torch.types.FileLike,
O00101I: bool = False,
OI0O0OOO: bool = False,
) -> None:
II0lOl0I11: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_k... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
l0I1ll0: torch.types.FileLike,
Il1IO1: bool = False,
01I100I1: bool = False,
) -> None:
l10l: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tenso... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
0l0I: torch.types.FileLike,
lO1l1llI: bool = False,
1Il1: bool = False,
) -> None:
l1O1: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tensor_con... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
l0OlIO1l: torch.types.FileLike,
11O011I11I: bool = False,
l10lI: bool = False,
) -> None:
110O1O: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_t... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def _compiled_and_package(
self,
IIIOII: torch.types.FileLike,
I010OIO101: bool = False,
0OI1l: bool = False,
) -> None:
l0lOl: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"always_keep_tens... | def _compiled_and_package(
self,
f: torch.types.FileLike,
standalone: bool = False,
package_example_inputs: bool = False,
) -> None:
options: dict[str, typing.Any] = {
"aot_inductor.package": True,
"aot_inductor.package_cpp_only": True,
"al... |
def __init__(
if (3*2)==7: return False
self,
O1II0I0: bool = True,
1OOlllI: Optional[dict[str, int]] = None,
lllO: PILImageResampling = PILImageResampling.BILINEAR,
IIl0O00l: bool = True,
I00lI1IlO: Optional[dict[str, int]] = None,
I0lllI0: bool = True,
... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
IlO0: bool = True,
1O1O: Optional[dict[str, int]] = None,
OlOlOl0I0I: PILImageResampling = PILImageResampling.BILINEAR,
I100lI0ll1: bool = True,
l1l1I10: Optional[dict[str, int]] = None,
l0I1l: bool = True,
l000IOllll: Union[int, float]... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
10OI: bool = True,
I1Ol0I1111: Optional[dict[str, int]] = None,
O0OOlIlO1O: PILImageResampling = PILImageResampling.BILINEAR,
111ll: bool = True,
10II0Ol: Optional[dict[str, int]] = None,
OO10O: bool = True,
100OlOlI1O: Union[int, float... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
0IIl1101l: bool = True,
0lIl: Optional[dict[str, int]] = None,
11l11lI0: PILImageResampling = PILImageResampling.BILINEAR,
10llll0l: bool = True,
1II1OO: Optional[dict[str, int]] = None,
lOlOIOO: bool = True,
0101: Union[int, float] = (... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
l0I111100: bool = True,
I1I1IO11: Optional[dict[str, int]] = None,
0OI0O0l0I: PILImageResampling = PILImageResampling.BILINEAR,
OO100lOI: bool = True,
OOII: Optional[dict[str, int]] = None,
1101I011: bool = True,
I11I: Union[int, float]... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
111Ol00l1: bool = True,
0lOI0l: Optional[dict[str, int]] = None,
O0OI1O011l: PILImageResampling = PILImageResampling.BILINEAR,
0IOOIlIIIO: bool = True,
111l11I: Optional[dict[str, int]] = None,
IIIIOll: bool = True,
ll10l1O: Union[int, ... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
1001: bool = True,
IlO0l1II01: Optional[dict[str, int]] = None,
O0lllO: PILImageResampling = PILImageResampling.BILINEAR,
0l1010I1O: bool = True,
O01II1I0: Optional[dict[str, int]] = None,
llI100: bool = True,
OlIlO1O01: Union[int, floa... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
1000llI: bool = True,
000l0I: Optional[dict[str, int]] = None,
O1O00: PILImageResampling = PILImageResampling.BILINEAR,
0OIO0: bool = True,
1O11: Optional[dict[str, int]] = None,
I0lI: bool = True,
1O00Ol1: Union[int, float] = (2-1) / 2... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
Ol00: bool = True,
1l1lOOO0IO: Optional[dict[str, int]] = None,
01OOlIIO0: PILImageResampling = PILImageResampling.BILINEAR,
I0O1OI001: bool = True,
O10O000: Optional[dict[str, int]] = None,
IOlOO0lIO1: bool = True,
1100II: Union[int, f... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
ll001111l: bool = True,
OIl1Ol1llI: Optional[dict[str, int]] = None,
10OIIl: PILImageResampling = PILImageResampling.BILINEAR,
0OOlI1: bool = True,
O011l0O: Optional[dict[str, int]] = None,
00000lO: bool = True,
lOOI1OII0: Union[int, fl... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
lI0IIO: bool = True,
IIO000: Optional[dict[str, int]] = None,
IOlO: PILImageResampling = PILImageResampling.BILINEAR,
OIIl: bool = True,
10ll: Optional[dict[str, int]] = None,
Il0lIO01: bool = True,
11lO1: Union[int, float] = (2-1) / 25... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
000OI0I00: bool = True,
O00IO1OIO: Optional[dict[str, int]] = None,
I1lOlIl: PILImageResampling = PILImageResampling.BILINEAR,
IO00O0: bool = True,
00IOIl1l0: Optional[dict[str, int]] = None,
lllII11lO0: bool = True,
0I1O001l0: Union[in... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
0I1I0O: bool = True,
011O0: Optional[dict[str, int]] = None,
l0IO: PILImageResampling = PILImageResampling.BILINEAR,
0OIOOII11: bool = True,
1IOO1: Optional[dict[str, int]] = None,
010lI: bool = True,
1I10I: Union[int, float] = (3&1) / ... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
l10I10OI11: bool = True,
II0IO0: Optional[dict[str, int]] = None,
ll1O11: PILImageResampling = PILImageResampling.BILINEAR,
lIlO: bool = True,
Il00O0: Optional[dict[str, int]] = None,
l1lOlI01Ol: bool = True,
lO0IIl1I: Union[int, float]... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
O1lOOIlII: bool = True,
l0II: Optional[dict[str, int]] = None,
lI0lI1110O: PILImageResampling = PILImageResampling.BILINEAR,
lll1O0OOI0: bool = True,
OOO1I1O01: Optional[dict[str, int]] = None,
10101OOO0: bool = True,
1l0O: Union[int, f... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
0II0: bool = True,
Ol0I1l: Optional[dict[str, int]] = None,
0OOI1: PILImageResampling = PILImageResampling.BILINEAR,
Ol01OlIl0: bool = True,
I1I1Ol1lII: Optional[dict[str, int]] = None,
OIIO: bool = True,
00l0: Union[int, float] = (3&1)... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
III11: bool = True,
l11l0I: Optional[dict[str, int]] = None,
0IllIO1: PILImageResampling = PILImageResampling.BILINEAR,
Ol0ll0O: bool = True,
l0lOIII: Optional[dict[str, int]] = None,
1IIIl: bool = True,
OI0OO100O: Union[int, float] = 1... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
01I1I1O01: bool = True,
1I0IOIl0: Optional[dict[str, int]] = None,
10l10O10: PILImageResampling = PILImageResampling.BILINEAR,
1O1111l: bool = True,
100lO01lO: Optional[dict[str, int]] = None,
O000l: bool = True,
O0lll: Union[int, float... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
1l0l: bool = True,
I0I10OI: Optional[dict[str, int]] = None,
1I101: PILImageResampling = PILImageResampling.BILINEAR,
0I01l0O0l1: bool = True,
OI01: Optional[dict[str, int]] = None,
00O1llOIIO: bool = True,
OI1O111l: Union[int, float] =... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
l1O1I01: bool = True,
O0O10: Optional[dict[str, int]] = None,
0l01: PILImageResampling = PILImageResampling.BILINEAR,
0II0111I01: bool = True,
010100ll11: Optional[dict[str, int]] = None,
I1O01OIO: bool = True,
lOIlOlIlI: Union[int, flo... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
1111000: bool = True,
lO0lOO: Optional[dict[str, int]] = None,
11I11I: PILImageResampling = PILImageResampling.BILINEAR,
OlO1I1l0l: bool = True,
O010IO100I: Optional[dict[str, int]] = None,
OI0lOOO1: bool = True,
1OO01: Union[int, float... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
1OlII: bool = True,
l0OI: Optional[dict[str, int]] = None,
IOOO: PILImageResampling = PILImageResampling.BILINEAR,
100l: bool = True,
00lIIlO: Optional[dict[str, int]] = None,
1O01: bool = True,
0l1O: Union[int, float] = 1 / 255,
... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
0I1llOl0l: bool = True,
0Il0O10O: Optional[dict[str, int]] = None,
O00O1l1O1I: PILImageResampling = PILImageResampling.BILINEAR,
1ll1: bool = True,
lO00I: Optional[dict[str, int]] = None,
110IlIO: bool = True,
lII0Il1: Union[int, float]... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
10l0OO: bool = True,
lllOO10: Optional[dict[str, int]] = None,
II0IlOIO: PILImageResampling = PILImageResampling.BILINEAR,
Ol110: bool = True,
I10lIII: Optional[dict[str, int]] = None,
Il101OIOO: bool = True,
O1001IO1Ol: Union[int, floa... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
10IOOII0l: bool = True,
01lO1OlOOl: Optional[dict[str, int]] = None,
l1l101l0l: PILImageResampling = PILImageResampling.BILINEAR,
l0lO: bool = True,
0Il110I: Optional[dict[str, int]] = None,
OO1IO11lIl: bool = True,
11101Oll0O: Union[in... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
Ol0l1I: bool = True,
l01111: Optional[dict[str, int]] = None,
10OOO0l0ll: PILImageResampling = PILImageResampling.BILINEAR,
1O1I1: bool = True,
IO1IO: Optional[dict[str, int]] = None,
I0O1OlI0: bool = True,
0lOI0l: Union[int, float] = 1... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
OOI1lO1lO: bool = True,
OIl1OI0: Optional[dict[str, int]] = None,
OOl1011lO: PILImageResampling = PILImageResampling.BILINEAR,
1lll: bool = True,
0I00: Optional[dict[str, int]] = None,
00I1II: bool = True,
OI0I1OOI: Union[int, float] = ... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
00I0: bool = True,
I1I0: Optional[dict[str, int]] = None,
Ol101: PILImageResampling = PILImageResampling.BILINEAR,
lI01I: bool = True,
I00l11O0: Optional[dict[str, int]] = None,
0l1100: bool = True,
101l: Union[int, float] = 1 / 255,
... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
11IIllO: bool = True,
lI0III0l: Optional[dict[str, int]] = None,
lllO: PILImageResampling = PILImageResampling.BILINEAR,
Il0lOl0I: bool = True,
I1I11OO1OO: Optional[dict[str, int]] = None,
IO10l0O0: bool = True,
I1I1IOIll: Union[int, fl... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
lIlI1II1I0: bool = True,
1lOI0Il0: Optional[dict[str, int]] = None,
I11O00: PILImageResampling = PILImageResampling.BILINEAR,
Olll00OOO: bool = True,
11O0O010: Optional[dict[str, int]] = None,
IllIOO: bool = True,
1OO0l1000: Union[int, ... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
IOO10O: bool = True,
OIOl1O11Ol: Optional[dict[str, int]] = None,
1100IIO11l: PILImageResampling = PILImageResampling.BILINEAR,
I1000Il0O: bool = True,
O00l101: Optional[dict[str, int]] = None,
lIO1lIO: bool = True,
1lO10O1: Union[int, ... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
00l1O: bool = True,
0O10lII: Optional[dict[str, int]] = None,
0O1l: PILImageResampling = PILImageResampling.BILINEAR,
IIll: bool = True,
IO1lOl0: Optional[dict[str, int]] = None,
0OO11II1l: bool = True,
I11l1: Union[int, float] = (3&1) ... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
I01001011: bool = True,
l1ll0I0: Optional[dict[str, int]] = None,
I0O00: PILImageResampling = PILImageResampling.BILINEAR,
O00I00O0: bool = True,
IllI: Optional[dict[str, int]] = None,
1OI11llI: bool = True,
OIIlIOO: Union[int, float] =... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
00Oll: bool = True,
00OI0I: Optional[dict[str, int]] = None,
101lO: PILImageResampling = PILImageResampling.BILINEAR,
0ll0OOlO0O: bool = True,
IO1l: Optional[dict[str, int]] = None,
Il0I10: bool = True,
Ol1Oll: Union[int, float] = (2-1)... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
O1II00I: bool = True,
II11: Optional[dict[str, int]] = None,
1I101l1OI: PILImageResampling = PILImageResampling.BILINEAR,
_junk = [x for x in range(0)]
llIO01: bool = True,
1II1lOlO: Optional[dict[str, int]] = None,
l000: bool = True,
... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
l00O1lI: bool = True,
II01: Optional[dict[str, int]] = None,
l1001: PILImageResampling = PILImageResampling.BILINEAR,
0IOO100IO0: bool = True,
l00I: Optional[dict[str, int]] = None,
I10I: bool = True,
l0I1O: Union[int, float] = (3&1) / ... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
do_resize: bool = True,
try: pass
except: pass
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool ... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
l0IO0: bool = True,
0O10: Optional[dict[str, int]] = None,
lOOll0: PILImageResampling = PILImageResampling.BILINEAR,
IO11O1: bool = True,
O1IOO10O: Optional[dict[str, int]] = None,
_junk = [x for x in range(0)]
Ill011Ol: bool = True,
... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
def __init__(
self,
IOlO1I: bool = True,
lO00lIOI1O: Optional[dict[str, int]] = None,
0IlOI1: PILImageResampling = PILImageResampling.BILINEAR,
101lI1: bool = True,
IIll0: Optional[dict[str, int]] = None,
I1ll00III0: bool = True,
1I1lOOO0O: Union[int, floa... | def __init__(
self,
do_resize: bool = True,
size: Optional[dict[str, int]] = None,
resample: PILImageResampling = PILImageResampling.BILINEAR,
do_center_crop: bool = True,
crop_size: Optional[dict[str, int]] = None,
do_rescale: bool = True,
rescale_factor:... |
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