id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
150,390 | from typing import Optional, Union, Literal
import numpy as np
import torch
import torch.nn
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy.functional.backends.torch as torch_backend
def gelu(
x: torch.Tensor,
/,
*,
approximate: bool = False,
... | null |
150,391 | from typing import Optional, Union, Literal
import numpy as np
import torch
import torch.nn
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy.functional.backends.torch as torch_backend
import ivy
from ivy.utils.exceptions import handle_exceptions
from ivy.function... | null |
150,392 | from typing import Optional, Union, Literal
import numpy as np
import torch
import torch.nn
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy.functional.backends.torch as torch_backend
def softmax(
x: torch.Tensor,
/,
*,
axis: Optional[int] = None,... | null |
150,393 | from typing import Optional, Union, Literal
import numpy as np
import torch
import torch.nn
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy.functional.backends.torch as torch_backend
def softplus(
x: torch.Tensor,
/,
*,
beta: Optional[Union[int, ... | null |
150,394 | from typing import Optional, Union, Literal
import numpy as np
import torch
import torch.nn
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy.functional.backends.torch as torch_backend
def softsign(x: torch.Tensor, /, out: Optional[torch.Tensor] = None) -> torch.T... | null |
150,395 | from typing import Optional, Union, Literal
import numpy as np
import torch
import torch.nn
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy.functional.backends.torch as torch_backend
def log_softmax(
x: torch.Tensor,
/,
*,
axis: Optional[int] = -... | null |
150,396 | from typing import Optional, Union, Literal
import numpy as np
import torch
import torch.nn
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy.functional.backends.torch as torch_backend
def mish(
x: torch.Tensor,
/,
*,
complex_mode: Literal["split",... | null |
150,397 | from typing import Optional, Union, Literal
import numpy as np
import torch
import torch.nn
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy.functional.backends.torch as torch_backend
def hardswish(
x: torch.Tensor,
/,
*,
complex_mode: Literal["sp... | null |
150,398 | import math
from numbers import Number
from typing import Iterable, List, Optional, Sequence, Tuple, Union
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.ivy.manipulation import _calculate_out_shape
from . import backend_version
def concat(
xs: Union[Tuple[torch.Te... | null |
150,399 | import math
from numbers import Number
from typing import Iterable, List, Optional, Sequence, Tuple, Union
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.ivy.manipulation import _calculate_out_shape
from . import backend_version
def reshape(
x: torch.Tensor,
/,
... | null |
150,400 | import math
from numbers import Number
from typing import Iterable, List, Optional, Sequence, Tuple, Union
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.ivy.manipulation import _calculate_out_shape
from . import backend_version
def flip(
x: torch.Tensor,
/,
... | null |
150,401 | import math
from numbers import Number
from typing import Iterable, List, Optional, Sequence, Tuple, Union
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.ivy.manipulation import _calculate_out_shape
from . import backend_version
def permute_dims(
x: torch.Tensor,
... | null |
150,402 | import math
from numbers import Number
from typing import Iterable, List, Optional, Sequence, Tuple, Union
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.ivy.manipulation import _calculate_out_shape
from . import backend_version
def roll(
x: torch.Tensor,
/,
... | null |
150,403 | import math
from numbers import Number
from typing import Iterable, List, Optional, Sequence, Tuple, Union
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.ivy.manipulation import _calculate_out_shape
from . import backend_version
import ivy
from ivy.utils.exceptions imp... | null |
150,404 | import math
from numbers import Number
from typing import Iterable, List, Optional, Sequence, Tuple, Union
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.ivy.manipulation import _calculate_out_shape
from . import backend_version
def stack(
arrays: Union[Tuple[torch... | null |
150,405 | import math
from numbers import Number
from typing import Iterable, List, Optional, Sequence, Tuple, Union
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.ivy.manipulation import _calculate_out_shape
from . import backend_version
import ivy
from ivy.utils.exceptions imp... | null |
150,406 | import math
from numbers import Number
from typing import Iterable, List, Optional, Sequence, Tuple, Union
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.ivy.manipulation import _calculate_out_shape
from . import backend_version
def repeat(
x: torch.Tensor,
/,
... | null |
150,407 | import math
from numbers import Number
from typing import Iterable, List, Optional, Sequence, Tuple, Union
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.ivy.manipulation import _calculate_out_shape
from . import backend_version
def constant_pad(
x: torch.Tensor,
... | null |
150,408 | import math
from numbers import Number
from typing import Iterable, List, Optional, Sequence, Tuple, Union
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.ivy.manipulation import _calculate_out_shape
from . import backend_version
def swapaxes(
x: torch.Tensor,
a... | null |
150,409 | import math
from numbers import Number
from typing import Iterable, List, Optional, Sequence, Tuple, Union
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.ivy.manipulation import _calculate_out_shape
from . import backend_version
import ivy
from ivy.utils.exceptions imp... | null |
150,410 | import math
from numbers import Number
from typing import Iterable, List, Optional, Sequence, Tuple, Union
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.ivy.manipulation import _calculate_out_shape
from . import backend_version
def unstack(
x: torch.Tensor,
/,... | null |
150,411 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,412 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,413 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,414 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,415 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,416 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,417 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,418 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def fmin(
x1: torch.Tensor,
... | null |
150,419 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,420 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
def asinh... | null |
150,421 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,422 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
def cosh(... | null |
150,423 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,424 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,425 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,426 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,427 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,428 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,429 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,430 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,431 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,432 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,433 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,434 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,435 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def lcm(
x1: torch.Tensor,
x... | null |
150,436 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def logical_xor(
x1: torch.Tenso... | null |
150,437 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
def acosh... | null |
150,438 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,439 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,440 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,441 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,442 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def floor(x: torch.Tensor, /, *, out:... | null |
150,443 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,444 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,445 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,446 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,447 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def trapz(
y: torch.Tensor,
... | null |
150,448 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
import iv... | null |
150,449 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,450 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,451 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,452 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
def atan(... | null |
150,453 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,454 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,455 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,456 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def exp2(
x: Union[torch.Tensor,... | null |
150,457 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,458 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,459 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,460 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,461 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,462 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,463 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def _cast_for_unary_op(x):
if not... | null |
150,464 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def deg2rad(x: torch.Tensor, /, *, o... | null |
150,465 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def rad2deg(x: torch.Tensor, /, *, o... | null |
150,466 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
import ivy
from ivy.utils.exceptions... | null |
150,467 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def isreal(x: torch.Tensor, /, *, ou... | null |
150,468 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def fmod(
x1: torch.Tensor,
... | null |
150,469 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def gcd(
x1: Union[torch.Tensor,... | null |
150,470 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def angle(
input: torch.Tensor,
... | null |
150,471 | from typing import Union, Optional
from math import pi
import torch
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_supported_dtypes,
handle_numpy_arrays_in_specific_backend,
)
from ivy import promote_types_of_inputs
from . import backend_version
def nan_to_num(
x: torch.Tensor,... | null |
150,472 | import inspect
import os
import importlib
import torch
from typing import Optional, Union
from torch.profiler import ProfilerActivity
from torch.profiler import profile
import ivy
from ivy.functional.ivy.device import (
_shift_native_arrays_on_default_device,
Profiler as BaseProfiler,
)
def as_ivy_dev(device: t... | null |
150,473 | import inspect
import os
import importlib
import torch
from typing import Optional, Union
from torch.profiler import ProfilerActivity
from torch.profiler import profile
import ivy
from ivy.functional.ivy.device import (
_shift_native_arrays_on_default_device,
Profiler as BaseProfiler,
)
def as_native_dev(
d... | null |
150,474 | import inspect
import os
import importlib
import torch
from typing import Optional, Union
from torch.profiler import ProfilerActivity
from torch.profiler import profile
import ivy
from ivy.functional.ivy.device import (
_shift_native_arrays_on_default_device,
Profiler as BaseProfiler,
)
def as_native_dev(
d... | null |
150,475 | import inspect
import os
import importlib
import torch
from typing import Optional, Union
from torch.profiler import ProfilerActivity
from torch.profiler import profile
import ivy
from ivy.functional.ivy.device import (
_shift_native_arrays_on_default_device,
Profiler as BaseProfiler,
)
def num_gpus() -> int:
... | null |
150,476 | import inspect
import os
import importlib
import torch
from typing import Optional, Union
from torch.profiler import ProfilerActivity
from torch.profiler import profile
import ivy
from ivy.functional.ivy.device import (
_shift_native_arrays_on_default_device,
Profiler as BaseProfiler,
)
def gpu_is_available() ... | null |
150,477 | import inspect
import os
import importlib
import torch
from typing import Optional, Union
from torch.profiler import ProfilerActivity
from torch.profiler import profile
import ivy
from ivy.functional.ivy.device import (
_shift_native_arrays_on_default_device,
Profiler as BaseProfiler,
)
def tpu_is_available() ... | null |
150,478 | import inspect
import os
import importlib
import torch
from typing import Optional, Union
from torch.profiler import ProfilerActivity
from torch.profiler import profile
import ivy
from ivy.functional.ivy.device import (
_shift_native_arrays_on_default_device,
Profiler as BaseProfiler,
)
def _shift_native_array... | null |
150,479 | import torch
from typing import Optional, Union, Sequence
import ivy
from ivy.functional.ivy.random import (
_check_bounds_and_get_shape,
_randint_check_dtype_and_bound,
_check_valid_scale,
)
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy
from ivy.utils.except... | null |
150,480 | import torch
from typing import Optional, Union, Sequence
import ivy
from ivy.functional.ivy.random import (
_check_bounds_and_get_shape,
_randint_check_dtype_and_bound,
_check_valid_scale,
)
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy
from ivy.utils.except... | null |
150,481 | import torch
from typing import Optional, Union, Sequence
import ivy
from ivy.functional.ivy.random import (
_check_bounds_and_get_shape,
_randint_check_dtype_and_bound,
_check_valid_scale,
)
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
def multinomial(
population_... | null |
150,482 | import torch
from typing import Optional, Union, Sequence
import ivy
from ivy.functional.ivy.random import (
_check_bounds_and_get_shape,
_randint_check_dtype_and_bound,
_check_valid_scale,
)
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy
from ivy.utils.except... | null |
150,483 | import torch
from typing import Optional, Union, Sequence
import ivy
from ivy.functional.ivy.random import (
_check_bounds_and_get_shape,
_randint_check_dtype_and_bound,
_check_valid_scale,
)
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
def seed(*, seed_value: int = 0)... | null |
150,484 | import torch
from typing import Optional, Union, Sequence
import ivy
from ivy.functional.ivy.random import (
_check_bounds_and_get_shape,
_randint_check_dtype_and_bound,
_check_valid_scale,
)
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
def shuffle(
x: torch.Tensor... | null |
150,485 | from typing import Optional, Tuple, Union, Sequence
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from ivy.functional.ivy.layers import _get_embed_dim, _handle_padding, _deconv_length
import ivy
from ivy.utils.exceptions import handle_... | null |
150,486 | from typing import Optional, Tuple, Union, Sequence
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from ivy.functional.ivy.layers import _get_embed_dim, _handle_padding, _deconv_length
def linear(
x: torch.Tensor,
weight: torch.... | null |
150,487 | from typing import Optional, Tuple, Union, Sequence
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from ivy.functional.ivy.layers import _get_embed_dim, _handle_padding, _deconv_length
def _x_dil_before_conv(x, dims, x_dilations):
# ... | null |
150,488 | from typing import Optional, Tuple, Union, Sequence
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from ivy.functional.ivy.layers import _get_embed_dim, _handle_padding, _deconv_length
def _tranpose_padding(
x_shape, filter_shape, st... | null |
150,489 | from typing import Optional, Tuple, Union, Sequence
import torch
import ivy
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from ivy.functional.ivy.layers import _get_embed_dim, _handle_padding, _deconv_length
def _x_dil_before_conv(x, dims, x_dilations):
# ... | null |
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