#!/usr/bin/env python3
# 2021, Carnegie Mellon University; Xuankai Chang
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Linear Projection."""
from typing import Tuple
import torch
from typeguard import check_argument_types
from espnet2.asr.preencoder.abs_preencoder import AbsPreEncoder
[docs]class LinearProjection(AbsPreEncoder):
"""Linear Projection Preencoder."""
def __init__(self, input_size: int, output_size: int, dropout: float = 0.0):
"""Initialize the module."""
assert check_argument_types()
super().__init__()
self.output_dim = output_size
self.linear_out = torch.nn.Linear(input_size, output_size)
self.dropout = torch.nn.Dropout(dropout)
[docs] def forward(
self, input: torch.Tensor, input_lengths: torch.Tensor
) -> Tuple[torch.Tensor, torch.Tensor]:
"""Forward."""
output = self.linear_out(self.dropout(input))
return output, input_lengths # no state in this layer
[docs] def output_size(self) -> int:
"""Get the output size."""
return self.output_dim