mirror of
https://github.com/zebrajr/pytorch.git
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bfeff1eb8f
Summary: Closes https://github.com/pytorch/pytorch/issues/18724 Pull Request resolved: https://github.com/pytorch/pytorch/pull/19089 Differential Revision: D16073654 Pulled By: ezyang fbshipit-source-id: 5642179651ce45ab7c5a46cc1fcc4fd6b37fa71c
59 lines
1.4 KiB
Python
59 lines
1.4 KiB
Python
from .module import Module
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from typing import Any, Union, List
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from ... import Tensor, Size
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from .. import Parameter
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class LocalResponseNorm(Module):
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size: int = ...
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alpha: float = ...
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beta: float = ...
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k: float = ...
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def __init__(self, size: int, alpha: float = ..., beta: float = ..., k: float = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class CrossMapLRN2d(Module):
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size: int = ...
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alpha: float = ...
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beta: float = ...
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k: float = ...
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def __init__(self, size: int, alpha: float = ..., beta: float = ..., k: float = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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_shape_t = Union[int, List[int], Size]
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class LayerNorm(Module):
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normalized_shape: _shape_t = ...
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eps: float = ...
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elementwise_affine: bool = ...
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weight: Parameter = ...
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bias: Parameter = ...
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def __init__(self, normalized_shape: _shape_t, eps: float = ..., elementwise_affine: bool = ...) -> None: ...
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def reset_parameters(self) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class GroupNorm(Module):
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num_groups: int = ...
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num_channels: int = ...
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eps: float = ...
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affine: bool = ...
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weight: Parameter = ...
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bias: Parameter = ...
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def __init__(self, num_groups: int, num_channels: int, eps: float = ..., affine: bool = ...) -> None: ...
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def reset_parameters(self) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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