move bash script based tests to python with coqpit

tests/tts_tests/test_speedy_speech_train.py

@@ -0,0 +1,48 @@
+import glob
+import os
+
+from tests import get_tests_output_path, run_cli
+from TTS.config import BaseDatasetConfig
+from TTS.tts.configs import SpeedySpeechConfig
+
+config_path = os.path.join(get_tests_output_path(), "test_speedy_speech_config.json")
+output_path = os.path.join(get_tests_output_path(), "train_outputs")
+
+
+config = SpeedySpeechConfig(
+    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_speedy_speech.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_speedy_speech.py --continue_path {continue_path} "
+run_cli(command_train)