id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
150,290 | from typing import Union, Optional, Tuple, List, Sequence
from numbers import Number
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
from ivy.func_wrapper import with_supported_dtypes
from .. import backend_version
class IvyNotImplementedException(IvyException, NotImplementedError):
... | null |
150,291 | from typing import Union, Optional, Tuple, List, Sequence
from numbers import Number
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
from ivy.func_wrapper import with_supported_dtypes
from .. import backend_version
class IvyNotImplementedException(IvyException, NotImplementedError):
... | null |
150,292 | from typing import Union, Optional, Tuple, List, Sequence
from numbers import Number
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
from ivy.func_wrapper import with_supported_dtypes
from .. import backend_version
class IvyNotImplementedException(IvyException, NotImplementedError):
... | null |
150,293 | from typing import Union, Optional, Sequence
import mxnet as mx
import ivy
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_backend=inclu... | null |
150,294 | from typing import Union, Optional, Sequence
import mxnet as mx
import ivy
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
def beta(
alpha: Union[(float, None, mx.ndarray.NDA... | null |
150,295 | from typing import Union, Optional, Sequence
import mxnet as mx
import ivy
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
def gamma(
alpha: Union[(float, None, mx.ndarray.ND... | null |
150,296 | from typing import Union, Optional, Sequence
import mxnet as mx
import ivy
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_backend=inclu... | null |
150,297 | from typing import Union, Optional, Sequence
import mxnet as mx
import ivy
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_backend=inclu... | null |
150,298 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_ba... | null |
150,299 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
def max_pool1d(
x: mx.nd.NDArray,
ke... | null |
150,300 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
def max_pool2d(
x: mx.nd.NDArray,
ke... | null |
150,301 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_ba... | null |
150,302 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
def avg_pool1d(
x: mx.nd.NDArray,
ke... | null |
150,303 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_ba... | null |
150,304 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_ba... | null |
150,305 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_ba... | null |
150,306 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_ba... | null |
150,307 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_ba... | null |
150,308 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_ba... | null |
150,309 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_ba... | null |
150,310 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_ba... | null |
150,311 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_ba... | null |
150,312 | from typing import List, Optional, Union, Tuple, Literal, Sequence
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_ba... | null |
150,313 | from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
def if_else(cond, body_fn, orelse_fn, vars):
raise IvyNotImplementedException() | null |
150,314 | from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_backend=include_backend)
def while_loop(test_fn, body_fn, vars):
raise IvyNotImplem... | null |
150,315 | from typing import Tuple, Union, Optional
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
def unique_all(
x: Union[(None, mx.ndarray.NDArray)], /, *, axis:... | null |
150,316 | from typing import Tuple, Union, Optional
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_backend=include_backend)
d... | null |
150,317 | from typing import Tuple, Union, Optional
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
super().__init__(*messages, include_backend=include_backend)
d... | null |
150,318 | from typing import Tuple, Union, Optional
import mxnet as mx
from ivy.utils.exceptions import IvyNotImplementedException
class IvyNotImplementedException(IvyException, NotImplementedError):
def __init__(self, *messages, include_backend=False):
def unique_values(
x: Union[(None, mx.ndarray.NDArray)],
/,
... | null |
150,319 | import torch
from typing import Optional, Callable, Sequence, Union
import ivy
from ivy.func_wrapper import (
outputs_to_ivy_arrays,
inputs_to_native_arrays,
)
from ivy.functional.ivy.gradients import (
_get_required_float_variables,
_get_y_and_ret_idxs,
_get_native_y,
_set_duplicates,
_proc... | null |
150,320 | import torch
from typing import Optional, Callable, Sequence, Union
import ivy
from ivy.func_wrapper import (
outputs_to_ivy_arrays,
inputs_to_native_arrays,
)
from ivy.functional.ivy.gradients import (
_get_required_float_variables,
_get_y_and_ret_idxs,
_get_native_y,
_set_duplicates,
_proc... | null |
150,321 | import torch
from typing import Optional, Callable, Sequence, Union
import ivy
from ivy.func_wrapper import (
outputs_to_ivy_arrays,
inputs_to_native_arrays,
)
from ivy.functional.ivy.gradients import (
_get_required_float_variables,
_get_y_and_ret_idxs,
_get_native_y,
_set_duplicates,
_proc... | null |
150,322 | import torch
from typing import Optional, Callable, Sequence, Union
import ivy
from ivy.func_wrapper import (
outputs_to_ivy_arrays,
inputs_to_native_arrays,
)
from ivy.functional.ivy.gradients import (
_get_required_float_variables,
_get_y_and_ret_idxs,
_get_native_y,
_set_duplicates,
_proc... | null |
150,323 | import torch
from typing import Optional, Callable, Sequence, Union
import ivy
from ivy.func_wrapper import (
outputs_to_ivy_arrays,
inputs_to_native_arrays,
)
from ivy.functional.ivy.gradients import (
_get_required_float_variables,
_get_y_and_ret_idxs,
_get_native_y,
_set_duplicates,
_proc... | null |
150,324 | import torch
from typing import Optional, Callable, Sequence, Union
import ivy
from ivy.func_wrapper import (
outputs_to_ivy_arrays,
inputs_to_native_arrays,
)
from ivy.functional.ivy.gradients import (
_get_required_float_variables,
_get_y_and_ret_idxs,
_get_native_y,
_set_duplicates,
_proc... | null |
150,325 | import torch
from typing import Optional, Literal, Union, List
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
def sort(
x: torch.Tensor,
/,
*,
axis: int = -1,
descending: bool = False,
stable: bool = True,
out: Optional[torch.Tensor] = None,
) -... | null |
150,326 | import torch
from typing import Optional, Literal, Union, List
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
def msort(
a: Union[torch.Tensor, list, tuple], /, *, out: Optional[torch.Tensor] = None
) -> torch.Tensor:
return torch.msort(a, out=out) | null |
150,327 | import torch
from typing import Optional, Literal, Union, List
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy
from ivy.utils.exceptions import handle_exceptions
from ivy.functional.frontends import set_frontend_to_specific_version
if ivy.is_loca... | null |
150,328 | import torch
from typing import Optional, List
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
def layer_norm(
x: torch.Tensor,
normalized_idxs: List[int],
/,
*,
scale: Optional[torch.Tensor] = None,
offset: Optional[torch.Tensor] = None,
eps: float = 1e-0... | null |
150,329 | from numbers import Number
from typing import Optional, Tuple, Union
import torch
import torch.nn.functional as tnf
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy
from ivy.utils.exceptions import handle_exceptions
from ivy.functional.frontends import set_fronte... | null |
150,330 | from numbers import Number
from typing import Optional, Tuple, Union
import torch
import torch.nn.functional as tnf
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy
from ivy.utils.exceptions import handle_exceptions
from ivy.functional.frontends import set_fronte... | null |
150,331 | from numbers import Number
from typing import Optional, Tuple, Union
import torch
import torch.nn.functional as tnf
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
def nonzero(
x: torch.Tensor,
/,
*,
as_tuple: bool = True,
size: Optional[int] = None,
... | null |
150,332 | from numbers import Number
from typing import Optional, Tuple, Union
import torch
import torch.nn.functional as tnf
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
import ivy
from ivy.utils.exceptions import handle_exceptions
from ivy.functional.frontends import set_fronte... | null |
150,333 | from numbers import Number
from typing import Optional, Tuple, Union
import torch
import torch.nn.functional as tnf
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
def argwhere(
x: torch.Tensor,
/,
*,
out: Optional[torch.Tensor] = None,
) -> torch.Tensor:
... | null |
150,334 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
import ivy
... | null |
150,335 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
import ivy
... | null |
150,336 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
def det(x: ... | null |
150,337 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
def eigh(
... | null |
150,338 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
import ivy
... | null |
150,339 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
import ivy
... | null |
150,340 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
import ivy
... | null |
150,341 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
import ivy
... | null |
150,342 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
def eig(
... | null |
150,343 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
def matrix_... | null |
150,344 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
def eigvalsh... | null |
150,345 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
def matrix_... | null |
150,346 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
import ivy
... | null |
150,347 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
def pinv(
... | null |
150,348 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
def tensors... | null |
150,349 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
import ivy
... | null |
150,350 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
def slogdet... | null |
150,351 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
import ivy
... | null |
150,352 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
def svd(
... | null |
150,353 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
def diagonal... | null |
150,354 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
def tensordo... | null |
150,355 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
import ivy
... | null |
150,356 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
def diagonal... | null |
150,357 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
import ivy
... | null |
150,358 | import torch
from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
from collections import namedtuple
import ivy
from ivy import inf
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
from .elementwise import _cast_for_unary_op
def vector_... | null |
150,359 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,360 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,361 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,362 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,363 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,364 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,365 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,366 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,367 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,368 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,369 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,370 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,371 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,372 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,373 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,374 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,375 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,376 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,377 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,378 | import copy
from numbers import Number
from typing import Union, List, Optional, Sequence, Tuple
import numpy as np
import torch
from torch import Tensor
import ivy
from ivy.func_wrapper import (
with_unsupported_dtypes,
with_unsupported_device_and_dtypes,
)
from ivy.functional.ivy.creation import (
_asarra... | null |
150,379 | from typing import Union, Optional, Sequence
import torch
import ivy
from ivy.functional.ivy.statistical import _get_promoted_type_of_operands
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
import ivy
from ivy.utils.exceptions import handle_exceptions
from ivy... | null |
150,380 | from typing import Union, Optional, Sequence
import torch
import ivy
from ivy.functional.ivy.statistical import _get_promoted_type_of_operands
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
import ivy
from ivy.utils.exceptions import handle_exceptions
from ivy... | null |
150,381 | from typing import Union, Optional, Sequence
import torch
import ivy
from ivy.functional.ivy.statistical import _get_promoted_type_of_operands
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
import ivy
from ivy.utils.exceptions import handle_exceptions
from ivy... | null |
150,382 | from typing import Union, Optional, Sequence
import torch
import ivy
from ivy.functional.ivy.statistical import _get_promoted_type_of_operands
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
import ivy
from ivy.utils.exceptions import handle_exceptions
from ivy... | null |
150,383 | from typing import Union, Optional, Sequence
import torch
import ivy
from ivy.functional.ivy.statistical import _get_promoted_type_of_operands
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
def _infer_dtype(dtype: torch.dtype) -> torch.dtype:
default_dtype ... | null |
150,384 | from typing import Union, Optional, Sequence
import torch
import ivy
from ivy.functional.ivy.statistical import _get_promoted_type_of_operands
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
def _infer_dtype(dtype: torch.dtype) -> torch.dtype:
default_dtype ... | null |
150,385 | from typing import Union, Optional, Sequence
import torch
import ivy
from ivy.functional.ivy.statistical import _get_promoted_type_of_operands
from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
from . import backend_version
import ivy
from ivy.utils.exceptions import handle_exceptions
from ivy... | null |
150,386 | import torch
from typing import Union, Optional, Sequence
def all(
x: torch.Tensor,
/,
*,
axis: Optional[Union[int, Sequence[int]]] = None,
keepdims: bool = False,
out: Optional[torch.Tensor] = None,
) -> torch.Tensor:
x = x.type(torch.bool)
if axis is None:
num_dims = len(x.sha... | null |
150,387 | import torch
from typing import Union, Optional, Sequence
def any(
x: torch.Tensor,
/,
*,
axis: Optional[Union[int, Sequence[int]]] = None,
keepdims: bool = False,
out: Optional[torch.Tensor] = None,
) -> torch.Tensor:
x = torch.as_tensor(x).type(torch.bool)
if axis is None:
num... | null |
150,388 | 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 relu(
x: torch.Tensor, /, *, complex_mode="jax", out: Optional[torch.Te... | null |
150,389 | 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 leaky_relu(
x: torch.Tensor,
/,
*,
alpha: float = 0.2,
... | null |
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