forked from mrq/DL-Art-School
74 lines
1.8 KiB
YAML
74 lines
1.8 KiB
YAML
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#### general settings
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name: test_tacotron2_lj
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use_tb_logger: true
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gpu_ids: [0]
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start_step: -1
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fp16: false
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checkpointing_enabled: true
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wandb: false
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datasets:
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train:
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name: lj
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n_workers: 0
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batch_size: 1
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mode: nv_tacotron
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path: E:\4k6k\datasets\audio\LJSpeech-1.1\ljs_audio_text_train_filelist.txt
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networks:
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mel_gen:
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type: generator
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which_model_G: nv_tacotron2
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args:
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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_rnn_dim: 1024
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prenet_dim: 256
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max_decoder_steps: 1000
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attention_rnn_dim: 1024
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attention_dim: 128
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attention_location_n_filters: 32
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attention_location_kernel_size: 31
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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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waveglow:
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type: generator
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which_model_G: nv_waveglow
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args:
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n_mel_channels: 80
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n_flows: 12
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n_group: 8
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n_early_every: 4
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n_early_size: 2
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WN_config:
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n_layers: 8
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n_channels: 256
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kernel_size: 3
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#### path
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path:
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pretrain_model_mel_gen: ../experiments/train_tacotron2_lj/models/22000_mel_gen_ema.pth
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pretrain_model_waveglow: ../experiments/waveglow_256channels_universal_v5.pth
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strict_load: true
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#resume_state: ../experiments/train_imgset_unet_diffusion/training_state/54000.state
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steps:
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generator:
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training: mel_gen
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injectors:
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mel:
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type: generator
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generator: mel_gen
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in: [padded_text, input_lengths, padded_mel, output_lengths]
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out: [mel_outputs, mel_outputs_postnet, gate_outputs, alignments]
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wave:
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type: generator
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generator: waveglow
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method: infer
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in: mel_outputs
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out: waveform
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eval:
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output_state: waveform
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