# Copyright 2025 ByteDance and/or its affiliates. # # 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. from typing import List import torch from torch import nn from tts.modules.wavvae.encoder.common_modules.seanet import SEANetEncoder class Encoder(nn.Module): def __init__( self, dowmsamples: List[int] = [6, 5, 5, 4, 2], ): super().__init__() # breakpoint() self.frame_rate = 25 # not use self.encoder = SEANetEncoder(causal=False, n_residual_layers=1, norm='weight_norm', pad_mode='reflect', lstm=2, dimension=512, channels=1, n_filters=32, ratios=dowmsamples, activation='ELU', kernel_size=7, residual_kernel_size=3, last_kernel_size=7, dilation_base=2, true_skip=False, compress=2) def forward(self, audio: torch.Tensor): audio = audio.unsqueeze(1) # audio(16,24000) emb = self.encoder(audio) return emb