cosmos1/models/autoregressive/modules/mlp.py

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# SPDX-License-Identifier: Apache-2.0
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# Licensed under the Apache License, Version 2.0 (the "License");
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# http://www.apache.org/licenses/LICENSE-2.0
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import torch
import torch.nn as nn
import torch.nn.functional as F


class MLP(nn.Module):
    def __init__(
        self,
        dim: int,
        hidden_dim: int,
    ):
        """
        Initializes the multilayer perceptron (MLP) module.

        Args:
            dim: The input and output dimensionality.
            hidden_dim: The dimensionality of the hidden layer.
        """
        super().__init__()
        self.w1 = nn.Linear(dim, hidden_dim, bias=False)
        self.w2 = nn.Linear(hidden_dim, dim, bias=False)
        self.w3 = nn.Linear(dim, hidden_dim, bias=False)

    def forward(self, x: torch.Tensor) -> torch.Tensor:
        """
        Performs the forward pass of the MLP module.

        Args:
            x: The input tensor of shape (batch_size, dim).

        Returns:
            The output tensor of shape (batch_size, dim).
        """
        output = self.w2(F.silu(self.w1(x)) * self.w3(x))
        return output