normalization.pyi

# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.

from .module import Module
from typing import Any, Union, List
from ... import Tensor, Size
from .. import Parameter


class LocalResponseNorm(Module):
    size: int = ...
    alpha: float = ...
    beta: float = ...
    k: float = ...

    def __init__(self, size: int, alpha: float = ..., beta: float = ..., k: float = ...) -> None: ...

    def forward(self, input: Tensor) -> Tensor: ...  # type: ignore

    def __call__(self, input: Tensor) -> Tensor: ...  # type: ignore


class CrossMapLRN2d(Module):
    size: int = ...
    alpha: float = ...
    beta: float = ...
    k: float = ...

    def __init__(self, size: int, alpha: float = ..., beta: float = ..., k: float = ...) -> None: ...

    def forward(self, input: Tensor) -> Tensor: ...  # type: ignore

    def __call__(self, input: Tensor) -> Tensor: ...  # type: ignore


_shape_t = Union[int, List[int], Size]


class LayerNorm(Module):
    normalized_shape: _shape_t = ...
    eps: float = ...
    elementwise_affine: bool = ...
    weight: Parameter = ...
    bias: Parameter = ...

    def __init__(self, normalized_shape: _shape_t, eps: float = ..., elementwise_affine: bool = ...) -> None: ...

    def reset_parameters(self) -> None: ...

    def forward(self, input: Tensor) -> Tensor: ...  # type: ignore

    def __call__(self, input: Tensor) -> Tensor: ...  # type: ignore


class GroupNorm(Module):
    num_groups: int = ...
    num_channels: int = ...
    eps: float = ...
    affine: bool = ...
    weight: Parameter = ...
    bias: Parameter = ...

    def __init__(self, num_groups: int, num_channels: int, eps: float = ..., affine: bool = ...) -> None: ...

    def reset_parameters(self) -> None: ...

    def forward(self, input: Tensor) -> Tensor: ...  # type: ignore

    def __call__(self, input: Tensor) -> Tensor: ...  # type: ignore