mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 12:21:27 +01:00
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
168 lines
3.6 KiB
Python
168 lines
3.6 KiB
Python
from ... import Tensor
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from .. import Parameter
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from .module import Module
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from typing import Any, Optional
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class Threshold(Module):
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threshold: float = ...
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value: float = ...
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inplace: bool = ...
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def __init__(self, threshold: float, value: float, inplace: bool = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class ReLU(Threshold):
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def __init__(self, inplace: bool = ...) -> None: ...
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class RReLU(Module):
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lower: float = ...
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upper: float = ...
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inplace: bool = ...
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def __init__(self, lower: float = ..., upper: float = ..., inplace: bool = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class Hardtanh(Module):
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min_val: float = ...
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max_val: float = ...
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inplace: bool = ...
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def __init__(self, min_val: float = ..., max_val: float = ..., inplace: bool = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class ReLU6(Hardtanh):
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def __init__(self, inplace: bool = ...) -> None: ...
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class Sigmoid(Module):
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def forward(self, input: Tensor) -> Tensor: ...
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class Tanh(Module):
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def forward(self, input: Tensor) -> Tensor: ...
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class ELU(Module):
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alpha: float = ...
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inplace: bool = ...
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def __init__(self, alpha: float = ..., inplace: bool = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class CELU(Module):
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alpha: float = ...
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inplace: bool = ...
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def __init__(self, alpha: float = ..., inplace: bool = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class SELU(Module):
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inplace: bool = ...
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def __init__(self, inplace: bool = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class GLU(Module):
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dim: int = ...
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def __init__(self, dim: int = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class Hardshrink(Module):
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lambd: float = ...
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def __init__(self, lambd: float = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class LeakyReLU(Module):
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negative_slope: float = ...
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inplace: bool = ...
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def __init__(self, negative_slope: float = ..., inplace: bool = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class LogSigmoid(Module):
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def forward(self, input: Tensor) -> Tensor: ...
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class Softplus(Module):
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beta: float = ...
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threshold: float = ...
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def __init__(self, beta: float = ..., threshold: float = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class Softshrink(Module):
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lambd: float = ...
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def __init__(self, lambd: float = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class PReLU(Module):
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num_parameters: int = ...
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weight: Parameter = ...
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def __init__(self, num_parameters: int = ..., init: float = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class Softsign(Module):
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def forward(self, input: Tensor) -> Tensor: ...
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class Tanhshrink(Module):
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def forward(self, input: Tensor) -> Tensor: ...
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class Softmin(Module):
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dim: int = ...
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def __init__(self, dim: Optional[int] = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class Softmax(Module):
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dim: int = ...
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def __init__(self, dim: Optional[int] = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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class Softmax2d(Module):
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def forward(self, input: Tensor) -> Tensor: ...
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class LogSoftmax(Module):
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dim: int = ...
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def __init__(self, dim: Optional[int] = ...) -> None: ...
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def forward(self, input: Tensor) -> Tensor: ...
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