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# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
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
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