mirror of https://github.com/malarinv/tacotron2
77 lines
2.2 KiB
Python
77 lines
2.2 KiB
Python
# -*- coding: utf-8 -*-
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# import tensorflow as tf
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from dataclasses import dataclass
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from .text import symbols
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@dataclass
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class HParams(object):
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"""docstring for HParams."""
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################################
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# Experiment Parameters #
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################################
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epochs=500
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iters_per_checkpoint=1000
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seed=1234
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dynamic_loss_scaling=True
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fp16_run=False
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distributed_run=False
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dist_backend="nccl"
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dist_url="tcp://localhost:54321"
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cudnn_enabled=True
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cudnn_benchmark=False
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ignore_layers=["embedding.weight"]
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################################
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# Data Parameters #
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################################
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load_mel_from_disk=False
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training_files="lists/tts_data_train_processed.txt"
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validation_files="filelists/tts_data_val_processed.txt"
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text_cleaners=["english_cleaners"]
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################################
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# Audio Parameters #
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################################
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max_wav_value=32768.0
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sampling_rate=16000
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filter_length=1024
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hop_length=256
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win_length=1024
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n_mel_channels=80
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mel_fmin=0.0
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mel_fmax=8000.0
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################################
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# Model Parameters #
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################################
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n_symbols=len(symbols)
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symbols_embedding_dim=512
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# Encoder parameters
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encoder_kernel_size=5
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encoder_n_convolutions=3
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encoder_embedding_dim=512
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# Decoder parameters
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n_frames_per_step=1 # currently only 1 is supported
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decoder_rnn_dim=1024
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prenet_dim=256
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max_decoder_steps=1000
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gate_threshold=0.5
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p_attention_dropout=0.1
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p_decoder_dropout=0.1
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# Attention parameters
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attention_rnn_dim=1024
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attention_dim=128
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# Location Layer parameters
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attention_location_n_filters=32
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attention_location_kernel_size=31
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# Mel-post processing network parameters
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postnet_embedding_dim=512
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postnet_kernel_size=5
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postnet_n_convolutions=5
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################################
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# Optimization Hyperparameters #
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################################
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use_saved_learning_rate=False
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learning_rate=1e-3
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weight_decay=1e-6
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grad_clip_thresh=1.0
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batch_size=4
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mask_padding=True # set model's padded outputs to padded values
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