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Running
on
Zero
# 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 | |