39 lines
1.5 KiB
Python
39 lines
1.5 KiB
Python
# Copyright 2025 ByteDance and/or its affiliates.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from typing import List
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import torch
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from torch import nn
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from tts.modules.wavvae.encoder.common_modules.seanet import SEANetEncoder
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class Encoder(nn.Module):
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def __init__(
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self,
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dowmsamples: List[int] = [6, 5, 5, 4, 2],
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):
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super().__init__()
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# breakpoint()
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self.frame_rate = 25 # not use
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self.encoder = SEANetEncoder(causal=False, n_residual_layers=1, norm='weight_norm', pad_mode='reflect', lstm=2,
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dimension=512, channels=1, n_filters=32, ratios=dowmsamples, activation='ELU',
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kernel_size=7, residual_kernel_size=3, last_kernel_size=7, dilation_base=2,
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true_skip=False, compress=2)
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def forward(self, audio: torch.Tensor):
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audio = audio.unsqueeze(1) # audio(16,24000)
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emb = self.encoder(audio)
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return emb
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