Upload 7 files
Browse files- config.yaml +30 -0
- fbank_mfa_gcmvn_stats.npz +3 -0
- hifigan.bin +3 -0
- hifigan.json +37 -0
- pytorch_model.pt +3 -0
- run_fast_speech_2.py +5 -0
- vocab.txt +71 -0
config.yaml
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features:
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energy_max: 3.2244551181793213
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energy_min: -4.9544901847839355
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eps: 1.0e-05
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f_max: 8000
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f_min: 0
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hop_len_t: 0.011609977324263039
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hop_length: 256
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n_fft: 1024
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n_mels: 80
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n_stft: 513
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pitch_max: 5.733940816898645
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pitch_min: -4.660287183665281
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sample_rate: 22050
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type: spectrogram+melscale+log
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win_len_t: 0.046439909297052155
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win_length: 1024
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window_fn: hann
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global_cmvn:
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stats_npz_path: fbank_mfa_gcmvn_stats.npz
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transforms:
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'*':
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- global_cmvn
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vocab_filename: vocab.txt
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vocoder:
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type: hifigan
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config: hifigan.json
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checkpoint: hifigan.bin
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hub:
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phonemizer: g2p
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fbank_mfa_gcmvn_stats.npz
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version https://git-lfs.github.com/spec/v1
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oid sha256:6735b35875c2614cee80bf861c6a604aba35671887e6f04b4449dc257bb15d34
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size 1140
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hifigan.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:d4f4f016c791fd9ca9859a9e25e7eb0a823fee2ea997c1e5ae8e1a9ea5f99b1f
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size 55825897
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hifigan.json
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{
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"resblock": "1",
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"num_gpus": 0,
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"batch_size": 16,
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"learning_rate": 0.0002,
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"adam_b1": 0.8,
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"adam_b2": 0.99,
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"lr_decay": 0.999,
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"seed": 1234,
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"upsample_rates": [8,8,2,2],
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"upsample_kernel_sizes": [16,16,4,4],
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"upsample_initial_channel": 512,
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"resblock_kernel_sizes": [3,7,11],
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"resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]],
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"segment_size": 8192,
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"num_mels": 80,
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"num_freq": 1025,
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"n_fft": 1024,
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"hop_size": 256,
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"win_size": 1024,
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"sampling_rate": 22050,
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"fmin": 0,
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"fmax": 8000,
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"fmax_for_loss": null,
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"num_workers": 4,
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"dist_config": {
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"dist_backend": "nccl",
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"dist_url": "tcp://localhost:54321",
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"world_size": 1
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}
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}
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pytorch_model.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:a48d454fe66939079d0ddb70f1c062ec669f521a7cfadc608968746e312986ab
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size 494816801
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run_fast_speech_2.py
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#!/usr/bin/env python3
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from fairseq.checkpoint_utils import load_model_ensemble_and_task
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# model = load_model_ensemble_and_task(["./pytorch_model.pt"], arg_overrides={"config_yaml": "./config.yaml", "data": "./"})
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model = load_model_ensemble_and_task(["./pytorch_model.pt"], arg_overrides={"data": "./"})
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vocab.txt
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