remove bash tts training tests

TTS/bin/compute_statistics.py

@@ -12,7 +12,7 @@ from TTS.tts.datasets.preprocess import load_meta_data
 from TTS.utils.audio import AudioProcessor
 
 # from TTS.utils.io import load_config
-from TTS.utils.config import load_config
+from TTS.config import load_config
 
 
 def main():

tests/bash_tests/test_aligntts_train.sh

@@ -1,13 +0,0 @@
-#!/usr/bin/env bash
-set -xe
-BASEDIR=$(dirname "$0")
-echo "$BASEDIR"
-# run training
-CUDA_VISIBLE_DEVICES="" python TTS/bin/train_align_tts.py --config_path $BASEDIR/../inputs/test_align_tts.json
-# find the training folder
-LATEST_FOLDER=$(ls $BASEDIR/../train_outputs/| sort | tail -1)
-echo $LATEST_FOLDER
-# continue the previous training
-CUDA_VISIBLE_DEVICES=""  python TTS/bin/train_align_tts.py --continue_path $BASEDIR/../train_outputs/$LATEST_FOLDER
-# remove all the outputs
-rm -rf $BASEDIR/../train_outputs/

tests/bash_tests/test_glow-tts_train.sh

@@ -1,13 +0,0 @@
-#!/usr/bin/env bash
-set -xe
-BASEDIR=$(dirname "$0")
-echo "$BASEDIR"
-# run training
-CUDA_VISIBLE_DEVICES="" python TTS/bin/train_glow_tts.py --config_path $BASEDIR/../inputs/test_glow_tts.json
-# find the training folder
-LATEST_FOLDER=$(ls $BASEDIR/../train_outputs/| sort | tail -1)
-echo $LATEST_FOLDER
-# continue the previous training
-CUDA_VISIBLE_DEVICES=""  python TTS/bin/train_glow_tts.py --continue_path $BASEDIR/../train_outputs/$LATEST_FOLDER
-# remove all the outputs
-rm -rf $BASEDIR/../train_outputs/

tests/bash_tests/test_speedy_speech_train.sh

@@ -1,13 +0,0 @@
-#!/usr/bin/env bash
-set -xe
-BASEDIR=$(dirname "$0")
-echo "$BASEDIR"
-# run training
-CUDA_VISIBLE_DEVICES="" python TTS/bin/train_speedy_speech.py --config_path $BASEDIR/../inputs/test_speedy_speech.json
-# find the training folder
-LATEST_FOLDER=$(ls $BASEDIR/../train_outputs/| sort | tail -1)
-echo $LATEST_FOLDER
-# continue the previous training
-CUDA_VISIBLE_DEVICES=""  python TTS/bin/train_speedy_speech.py --continue_path $BASEDIR/../train_outputs/$LATEST_FOLDER
-# remove all the outputs
-rm -rf $BASEDIR/../train_outputs/

tests/bash_tests/test_tacotron_train.sh

@@ -1,36 +0,0 @@
-#!/usr/bin/env bash
-set -xe
-BASEDIR=$(dirname "$0")
-echo "$BASEDIR"
-
-# run training
-CUDA_VISIBLE_DEVICES="" python TTS/bin/train_tacotron.py --config_path $BASEDIR/../inputs/test_tacotron_config.json
-# find the training folder
-LATEST_FOLDER=$(ls $BASEDIR/../train_outputs/| sort | tail -1)
-echo $LATEST_FOLDER
-# continue the previous training
-CUDA_VISIBLE_DEVICES=""  python TTS/bin/train_tacotron.py --continue_path $BASEDIR/../train_outputs/$LATEST_FOLDER
-# remove all the outputs
-rm -rf $BASEDIR/../train_outputs/
-
-# run Tacotron bi-directional decoder
-CUDA_VISIBLE_DEVICES="" python TTS/bin/train_tacotron.py --config_path $BASEDIR/../inputs/test_tacotron_bd_config.json
-# find the training folder
-LATEST_FOLDER=$(ls $BASEDIR/../train_outputs/| sort | tail -1)
-echo $LATEST_FOLDER
-# continue the previous training
-CUDA_VISIBLE_DEVICES=""  python TTS/bin/train_tacotron.py --continue_path $BASEDIR/../train_outputs/$LATEST_FOLDER
-# remove all the outputs
-rm -rf $BASEDIR/../train_outputs/
-
-# Tacotron2
-# run training
-CUDA_VISIBLE_DEVICES="" python TTS/bin/train_tacotron.py --config_path $BASEDIR/../inputs/test_tacotron2_config.json
-# find the training folder
-LATEST_FOLDER=$(ls $BASEDIR/../train_outputs/| sort | tail -1)
-echo $LATEST_FOLDER
-# continue the previous training
-CUDA_VISIBLE_DEVICES=""  python TTS/bin/train_tacotron.py --continue_path $BASEDIR/../train_outputs/$LATEST_FOLDER
-# remove all the outputs
-rm -rf $BASEDIR/../train_outputs/
-

tests/tts_tests/test_align_tts_train.py

@@ -0,0 +1,48 @@
+import glob
+import os
+import shutil
+
+from tests import get_tests_output_path, run_cli
+from TTS.tts.configs import AlignTTSConfig
+
+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 = AlignTTSConfig(
+    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_align_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 "
+)
+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_align_tts.py --continue_path {continue_path} "
+run_cli(command_train)
+shutil.rmtree(continue_path)

tests/tts_tests/test_tacotron2_train.py

@@ -0,0 +1,49 @@
+import glob
+import os
+import shutil
+
+from tests import get_tests_output_path, run_cli
+from TTS.tts.configs import Tacotron2Config
+
+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 = Tacotron2Config(
+    r=5,
+    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_tacotron.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 "
+)
+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_tacotron.py --continue_path {continue_path} "
+run_cli(command_train)
+shutil.rmtree(continue_path)

tests/tts_tests/test_tacotron_train.py

@@ -0,0 +1,48 @@
+import glob
+import os
+import shutil
+
+from tests import get_tests_output_path, run_cli
+from TTS.tts.configs import TacotronConfig
+
+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 = TacotronConfig(
+    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_tacotron.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 "
+)
+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_tacotron.py --continue_path {continue_path} "
+run_cli(command_train)
+shutil.rmtree(continue_path)