| # Copyright (c) Meta Platforms, Inc. and affiliates. | |
| # | |
| # This source code is licensed under the Apache License, Version 2.0 | |
| # found in the LICENSE file in the root directory of this source tree. | |
| # References: | |
| # https://github.com/facebookresearch/dino/blob/master/vision_transformer.py | |
| # https://github.com/rwightman/pytorch-image-models/tree/master/timm/layers/mlp.py | |
| from typing import Callable, Optional | |
| from torch import Tensor, nn | |
| class Mlp(nn.Module): | |
| def __init__( | |
| self, | |
| in_features: int, | |
| hidden_features: Optional[int] = None, | |
| out_features: Optional[int] = None, | |
| act_layer: Callable[..., nn.Module] = nn.GELU, | |
| drop: float = 0.0, | |
| bias: bool = True, | |
| ) -> None: | |
| super().__init__() | |
| out_features = out_features or in_features | |
| hidden_features = hidden_features or in_features | |
| self.fc1 = nn.Linear(in_features, hidden_features, bias=bias) | |
| self.act = act_layer() | |
| self.fc2 = nn.Linear(hidden_features, out_features, bias=bias) | |
| self.drop = nn.Dropout(drop) | |
| def forward(self, x: Tensor) -> Tensor: | |
| x = self.fc1(x) | |
| x = self.act(x) | |
| x = self.drop(x) | |
| x = self.fc2(x) | |
| x = self.drop(x) | |
| return x | |