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Zero
# Copyright (c) Meta Platforms, Inc. and affiliates. | |
# All rights reserved. | |
# | |
# This source code is licensed under the license 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 | |