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# Copyright (c) ByteDance, Inc. and its affiliates.
# Copyright (c) Chutong Meng
#
# This source code is licensed under the CC BY-NC license found in the
# LICENSE file in the root directory of this source tree.
# Based on AudioDec (https://github.com/facebookresearch/AudioDec)
import torch
import torch.nn as nn
from RepCodec.repcodec.layers.conv_layer import Conv1d
from RepCodec.repcodec.modules.residual_unit import ResidualUnit
class EncoderBlock(nn.Module):
def __init__(
self,
in_channels: int,
out_channels: int,
stride: int,
dilations=(1, 1),
unit_kernel_size=3,
bias=True
):
super().__init__()
self.res_units = torch.nn.ModuleList()
for dilation in dilations:
self.res_units += [
ResidualUnit(in_channels, in_channels,
kernel_size=unit_kernel_size,
dilation=dilation)
]
self.num_res = len(self.res_units)
self.conv = Conv1d(
in_channels=in_channels,
out_channels=out_channels,
kernel_size=3 if stride == 1 else (2 * stride), # special case: stride=1, do not use kernel=2
stride=stride,
bias=bias,
)
def forward(self, x):
for idx in range(self.num_res):
x = self.res_units[idx](x)
x = self.conv(x)
return x
class Encoder(nn.Module):
def __init__(
self,
input_channels: int,
encode_channels: int,
channel_ratios=(1, 1),
strides=(1, 1),
kernel_size=3,
bias=True,
block_dilations=(1, 1),
unit_kernel_size=3
):
super().__init__()
assert len(channel_ratios) == len(strides)
self.conv = Conv1d(
in_channels=input_channels,
out_channels=encode_channels,
kernel_size=kernel_size,
stride=1,
bias=False
)
self.conv_blocks = torch.nn.ModuleList()
in_channels = encode_channels
for idx, stride in enumerate(strides):
out_channels = int(encode_channels * channel_ratios[idx]) # could be float
self.conv_blocks += [
EncoderBlock(in_channels, out_channels, stride,
dilations=block_dilations, unit_kernel_size=unit_kernel_size,
bias=bias)
]
in_channels = out_channels
self.num_blocks = len(self.conv_blocks)
self.out_channels = out_channels
def forward(self, x):
x = self.conv(x)
for i in range(self.num_blocks):
x = self.conv_blocks[i](x)
return x
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