Fix recipes as to the recent API changes. (#1367)

* Fix recipes -> #1366

* Fix trainer docs

docs/source/main_classes/trainer_api.md

@@ -1,17 +1,3 @@
 # Trainer API
 
-The {class}`TTS.trainer.Trainer` provides a lightweight, extensible, and feature-complete training run-time. We optimized it for 🐸 but
-can also be used for any DL training in different domains. It supports distributed multi-gpu, mixed-precision (apex or torch.amp) training.
-
-
-## Trainer
-```{eval-rst}
-.. autoclass:: TTS.trainer.Trainer
-    :members:
-```
-
-## TrainingArgs
-```{eval-rst}
-.. autoclass:: TTS.trainer.TrainingArgs
-    :members:
-```
+We made the trainer a seprate project on https://github.com/coqui-ai/Trainer

recipes/ljspeech/hifigan/train_hifigan.py

@@ -37,7 +37,7 @@ ap = AudioProcessor(**config.audio.to_dict())
 eval_samples, train_samples = load_wav_data(config.data_path, config.eval_split_size)
 
 # init model
-model = GAN(config)
+model = GAN(config, ap)
 
 # init the trainer and 🚀
 trainer = Trainer(
@@ -46,7 +46,6 @@ trainer = Trainer(
     output_path,
     model=model,
     train_samples=train_samples,
-    eval_samples=eval_samples,
-    training_assets={"audio_processor": ap},
+    eval_samples=eval_samples
 )
 trainer.fit()

recipes/ljspeech/multiband_melgan/train_multiband_melgan.py

@@ -37,7 +37,7 @@ ap = AudioProcessor(**config.audio.to_dict())
 eval_samples, train_samples = load_wav_data(config.data_path, config.eval_split_size)
 
 # init model
-model = GAN(config)
+model = GAN(config, ap)
 
 # init the trainer and 🚀
 trainer = Trainer(
@@ -46,7 +46,6 @@ trainer = Trainer(
     output_path,
     model=model,
     train_samples=train_samples,
-    eval_samples=eval_samples,
-    training_assets={"audio_processor": ap},
+    eval_samples=eval_samples
 )
 trainer.fit()

recipes/ljspeech/tacotron2-DDC/train_tacotron_ddc.py

@@ -89,7 +89,6 @@ trainer = Trainer(
     output_path,
     model=model,
     train_samples=train_samples,
-    eval_samples=eval_samples,
-    training_assets={"audio_processor": ap},
+    eval_samples=eval_samples
 )
 trainer.fit()

recipes/ljspeech/univnet/train.py

@@ -36,7 +36,7 @@ ap = AudioProcessor(**config.audio.to_dict())
 eval_samples, train_samples = load_wav_data(config.data_path, config.eval_split_size)
 
 # init model
-model = GAN(config)
+model = GAN(config, ap)
 
 # init the trainer and 🚀
 trainer = Trainer(
@@ -45,7 +45,6 @@ trainer = Trainer(
     output_path,
     model=model,
     train_samples=train_samples,
-    eval_samples=eval_samples,
-    training_assets={"audio_processor": ap},
+    eval_samples=eval_samples
 )
 trainer.fit()

recipes/multilingual/vits_tts/train_vits_tts.py

@@ -136,7 +136,6 @@ trainer = Trainer(
     output_path,
     model=model,
     train_samples=train_samples,
-    eval_samples=eval_samples,
-    training_assets={"audio_processor": ap},
+    eval_samples=eval_samples
 )
 trainer.fit()