44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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# Copyright 2019 Shigeki Karita
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# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
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"""Positionwise feed forward layer definition."""
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import torch
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class PositionwiseFeedForward(torch.nn.Module):
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"""Positionwise feed forward layer.
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FeedForward are appied on each position of the sequence.
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The output dim is same with the input dim.
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Args:
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idim (int): Input dimenstion.
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hidden_units (int): The number of hidden units.
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dropout_rate (float): Dropout rate.
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activation (torch.nn.Module): Activation function
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"""
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def __init__(self,
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idim: int,
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hidden_units: int,
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dropout_rate: float,
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activation: torch.nn.Module = torch.nn.ReLU()):
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"""Construct a PositionwiseFeedForward object."""
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super(PositionwiseFeedForward, self).__init__()
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self.w_1 = torch.nn.Linear(idim, hidden_units)
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self.activation = activation
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self.dropout = torch.nn.Dropout(dropout_rate)
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self.w_2 = torch.nn.Linear(hidden_units, idim)
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def forward(self, xs: torch.Tensor) -> torch.Tensor:
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"""Forward function.
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Args:
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xs: input tensor (B, L, D)
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Returns:
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output tensor, (B, L, D)
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"""
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return self.w_2(self.dropout(self.activation(self.w_1(xs))))
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