mirror of https://github.com/coqui-ai/TTS.git
comment out check-arguments before copying fields to the configs
This commit is contained in:
Eren Gölge
parent
05d9543ed8
commit
4a58fdfd59
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@ -5,7 +5,6 @@ import re
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import torch
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from TTS.speaker_encoder.model import SpeakerEncoder
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from TTS.utils.generic_utils import check_argument
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def to_camel(text):
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@ -54,70 +53,71 @@ def save_best_model(model, optimizer, model_loss, best_loss, out_path, current_s
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def check_config_speaker_encoder(c):
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"""Check the config.json file of the speaker encoder"""
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check_argument("run_name", c, restricted=True, val_type=str)
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check_argument("run_description", c, val_type=str)
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...
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# """Check the config.json file of the speaker encoder"""
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# check_argument("run_name", c, restricted=True, val_type=str)
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# check_argument("run_description", c, val_type=str)
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# audio processing parameters
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check_argument("audio", c, restricted=True, val_type=dict)
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check_argument("num_mels", c["audio"], restricted=True, val_type=int, min_val=10, max_val=2056)
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check_argument("fft_size", c["audio"], restricted=True, val_type=int, min_val=128, max_val=4058)
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check_argument("sample_rate", c["audio"], restricted=True, val_type=int, min_val=512, max_val=100000)
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check_argument(
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"frame_length_ms",
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c["audio"],
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restricted=True,
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val_type=float,
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min_val=10,
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max_val=1000,
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alternative="win_length",
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)
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check_argument(
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"frame_shift_ms", c["audio"], restricted=True, val_type=float, min_val=1, max_val=1000, alternative="hop_length"
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)
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check_argument("preemphasis", c["audio"], restricted=True, val_type=float, min_val=0, max_val=1)
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check_argument("min_level_db", c["audio"], restricted=True, val_type=int, min_val=-1000, max_val=10)
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check_argument("ref_level_db", c["audio"], restricted=True, val_type=int, min_val=0, max_val=1000)
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check_argument("power", c["audio"], restricted=True, val_type=float, min_val=1, max_val=5)
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check_argument("griffin_lim_iters", c["audio"], restricted=True, val_type=int, min_val=10, max_val=1000)
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# # audio processing parameters
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# check_argument("audio", c, restricted=True, val_type=dict)
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# check_argument("num_mels", c["audio"], restricted=True, val_type=int, min_val=10, max_val=2056)
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# check_argument("fft_size", c["audio"], restricted=True, val_type=int, min_val=128, max_val=4058)
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# check_argument("sample_rate", c["audio"], restricted=True, val_type=int, min_val=512, max_val=100000)
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# check_argument(
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# "frame_length_ms",
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# c["audio"],
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# restricted=True,
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# val_type=float,
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# min_val=10,
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# max_val=1000,
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# alternative="win_length",
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# )
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# check_argument(
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# "frame_shift_ms", c["audio"], restricted=True, val_type=float, min_val=1, max_val=1000, alternative="hop_length"
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# )
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# check_argument("preemphasis", c["audio"], restricted=True, val_type=float, min_val=0, max_val=1)
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# check_argument("min_level_db", c["audio"], restricted=True, val_type=int, min_val=-1000, max_val=10)
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# check_argument("ref_level_db", c["audio"], restricted=True, val_type=int, min_val=0, max_val=1000)
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# check_argument("power", c["audio"], restricted=True, val_type=float, min_val=1, max_val=5)
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# check_argument("griffin_lim_iters", c["audio"], restricted=True, val_type=int, min_val=10, max_val=1000)
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# training parameters
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check_argument("loss", c, enum_list=["ge2e", "angleproto"], restricted=True, val_type=str)
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check_argument("grad_clip", c, restricted=True, val_type=float)
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check_argument("epochs", c, restricted=True, val_type=int, min_val=1)
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check_argument("lr", c, restricted=True, val_type=float, min_val=0)
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check_argument("lr_decay", c, restricted=True, val_type=bool)
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check_argument("warmup_steps", c, restricted=True, val_type=int, min_val=0)
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check_argument("tb_model_param_stats", c, restricted=True, val_type=bool)
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check_argument("num_speakers_in_batch", c, restricted=True, val_type=int)
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check_argument("num_loader_workers", c, restricted=True, val_type=int)
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check_argument("wd", c, restricted=True, val_type=float, min_val=0.0, max_val=1.0)
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# # training parameters
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# check_argument("loss", c, enum_list=["ge2e", "angleproto"], restricted=True, val_type=str)
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# check_argument("grad_clip", c, restricted=True, val_type=float)
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# check_argument("epochs", c, restricted=True, val_type=int, min_val=1)
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# check_argument("lr", c, restricted=True, val_type=float, min_val=0)
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# check_argument("lr_decay", c, restricted=True, val_type=bool)
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# check_argument("warmup_steps", c, restricted=True, val_type=int, min_val=0)
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# check_argument("tb_model_param_stats", c, restricted=True, val_type=bool)
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# check_argument("num_speakers_in_batch", c, restricted=True, val_type=int)
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# check_argument("num_loader_workers", c, restricted=True, val_type=int)
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# check_argument("wd", c, restricted=True, val_type=float, min_val=0.0, max_val=1.0)
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# checkpoint and output parameters
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check_argument("steps_plot_stats", c, restricted=True, val_type=int)
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check_argument("checkpoint", c, restricted=True, val_type=bool)
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check_argument("save_step", c, restricted=True, val_type=int)
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check_argument("print_step", c, restricted=True, val_type=int)
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check_argument("output_path", c, restricted=True, val_type=str)
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# # checkpoint and output parameters
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# check_argument("steps_plot_stats", c, restricted=True, val_type=int)
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# check_argument("checkpoint", c, restricted=True, val_type=bool)
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# check_argument("save_step", c, restricted=True, val_type=int)
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# check_argument("print_step", c, restricted=True, val_type=int)
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# check_argument("output_path", c, restricted=True, val_type=str)
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# model parameters
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check_argument("model", c, restricted=True, val_type=dict)
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check_argument("input_dim", c["model"], restricted=True, val_type=int)
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check_argument("proj_dim", c["model"], restricted=True, val_type=int)
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check_argument("lstm_dim", c["model"], restricted=True, val_type=int)
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check_argument("num_lstm_layers", c["model"], restricted=True, val_type=int)
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check_argument("use_lstm_with_projection", c["model"], restricted=True, val_type=bool)
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# # model parameters
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# check_argument("model", c, restricted=True, val_type=dict)
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# check_argument("input_dim", c["model"], restricted=True, val_type=int)
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# check_argument("proj_dim", c["model"], restricted=True, val_type=int)
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# check_argument("lstm_dim", c["model"], restricted=True, val_type=int)
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# check_argument("num_lstm_layers", c["model"], restricted=True, val_type=int)
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# check_argument("use_lstm_with_projection", c["model"], restricted=True, val_type=bool)
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# in-memory storage parameters
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check_argument("storage", c, restricted=True, val_type=dict)
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check_argument("sample_from_storage_p", c["storage"], restricted=True, val_type=float, min_val=0.0, max_val=1.0)
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check_argument("storage_size", c["storage"], restricted=True, val_type=int, min_val=1, max_val=100)
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check_argument("additive_noise", c["storage"], restricted=True, val_type=float, min_val=0.0, max_val=1.0)
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# # in-memory storage parameters
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# check_argument("storage", c, restricted=True, val_type=dict)
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# check_argument("sample_from_storage_p", c["storage"], restricted=True, val_type=float, min_val=0.0, max_val=1.0)
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# check_argument("storage_size", c["storage"], restricted=True, val_type=int, min_val=1, max_val=100)
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# check_argument("additive_noise", c["storage"], restricted=True, val_type=float, min_val=0.0, max_val=1.0)
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# datasets - checking only the first entry
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check_argument("datasets", c, restricted=True, val_type=list)
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for dataset_entry in c["datasets"]:
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check_argument("name", dataset_entry, restricted=True, val_type=str)
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check_argument("path", dataset_entry, restricted=True, val_type=str)
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check_argument("meta_file_train", dataset_entry, restricted=True, val_type=[str, list])
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check_argument("meta_file_val", dataset_entry, restricted=True, val_type=str)
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# # datasets - checking only the first entry
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# check_argument("datasets", c, restricted=True, val_type=list)
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# for dataset_entry in c["datasets"]:
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# check_argument("name", dataset_entry, restricted=True, val_type=str)
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# check_argument("path", dataset_entry, restricted=True, val_type=str)
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# check_argument("meta_file_train", dataset_entry, restricted=True, val_type=[str, list])
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# check_argument("meta_file_val", dataset_entry, restricted=True, val_type=str)
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