glow_tts_config.py and train test on python

TTS/tts/configs/glow_tts_config.py

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+from dataclasses import dataclass, field
+
+from .shared_configs import BaseTTSConfig
+
+
+@dataclass
+class GlowTTSConfig(BaseTTSConfig):
+    """Defines parameters for GlowTTS model."""
+
+    model: str = "glow_tts"
+
+    # model params
+    encoder_type: str = "rel_pos_transformer"
+    encoder_params: dict = field(
+        default_factory=lambda: {
+            "kernel_size": 3,
+            "dropout_p": 0.1,
+            "num_layers": 6,
+            "num_heads": 2,
+            "hidden_channels_ffn": 768,
+        }
+    )
+    use_encoder_prenet: bool = True
+    hidden_channels_encoder: int = 192
+    hidden_channels_decoder: int = 192
+    hidden_channels_duration_predictor: int = 256
+
+    # training params
+    data_dep_init_steps: int = 10
+
+    # inference params
+    style_wav_for_test: str = None
+    inference_noise_scale: float = 0.0
+
+    # multi-speaker settings
+    use_speaker_embedding: bool = False
+    use_external_speaker_embedding_file: bool = False
+    external_speaker_embedding_file: str = False
+
+    # optimizer params
+    noam_schedule: bool = True
+    warmup_steps: int = 4000
+    grad_clip: float = 5.0
+    lr: float = 1e-3
+    wd: float = 0.000001
+
+    # overrides
+    min_seq_len: int = 3
+    max_seq_len: int = 500
+    r: int = 1

tests/tts_tests/test_glow_tts_train.py

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+import glob
+import os
+import shutil
+
+from tests import get_tests_output_path, run_cli
+from TTS.tts.configs import GlowTTSConfig
+
+config_path = os.path.join(get_tests_output_path(), "test_model_config.json")
+output_path = os.path.join(get_tests_output_path(), "train_outputs")
+
+
+config = GlowTTSConfig(
+    batch_size=8,
+    eval_batch_size=8,
+    num_loader_workers=0,
+    num_val_loader_workers=0,
+    text_cleaner="english_cleaners",
+    use_phonemes=True,
+    phoneme_language="en-us",
+    phoneme_cache_path=os.path.join(get_tests_output_path(), "train_outputs/phoneme_cache/"),
+    run_eval=True,
+    test_delay_epochs=-1,
+    epochs=1,
+    print_step=1,
+    print_eval=True,
+)
+config.audio.do_trim_silence = True
+config.audio.trim_db = 60
+config.save_json(config_path)
+
+# train the model for one epoch
+command_train = (
+    f"CUDA_VISIBLE_DEVICES='' python TTS/bin/train_glow_tts.py --config_path {config_path} "
+    f"--coqpit.output_path {output_path} "
+    "--coqpit.datasets.0.name ljspeech "
+    "--coqpit.datasets.0.meta_file_train metadata.csv "
+    "--coqpit.datasets.0.meta_file_val metadata.csv "
+    "--coqpit.datasets.0.path tests/data/ljspeech "
+    "--coqpit.datasets.0.meta_file_attn_mask tests/data/ljspeech/metadata_attn_mask.txt"
+)
+run_cli(command_train)
+
+# Find latest folder
+continue_path = max(glob.glob(os.path.join(output_path, "*/")), key=os.path.getmtime)
+
+# restore the model and continue training for one more epoch
+command_train = f"CUDA_VISIBLE_DEVICES='' python TTS/bin/train_glow_tts.py --continue_path {continue_path} "
+run_cli(command_train)
+shutil.rmtree(continue_path)