make style

helpers/gradio_demo/app.py

@@ -95,9 +95,7 @@ with gr.Blocks(css=css) as block:
             description = gr.Textbox(label="Description", lines=2, value="", elem_id="input_description")
             run_button = gr.Button("Generate Audio", variant="primary")
         with gr.Column():
-            audio_out = gr.Audio(
-                label="Parler-TTS generation", type="numpy", elem_id="audio_out"
-            )
+            audio_out = gr.Audio(label="Parler-TTS generation", type="numpy", elem_id="audio_out")
 
     inputs = [input_text, description]
     outputs = [audio_out]

helpers/model_init_scripts/init_dummy_model.py

@@ -5,11 +5,11 @@ import argparse
 
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser()    
+    parser = argparse.ArgumentParser()
     parser.add_argument("save_directory", type=str, help="Directory where to save the model and the decoder.")
     parser.add_argument("text_model", type=str, help="Repository id or path to the text encoder.")
     parser.add_argument("audio_model", type=str, help="Repository id or path to the audio encoder.")
-    
+
     args = parser.parse_args()
 
     text_model = args.text_model
@@ -22,7 +22,6 @@ if __name__ == "__main__":
     num_codebooks = encodec.num_codebooks
     print("num_codebooks", num_codebooks)
 
-
     decoder_config = ParlerTTSDecoderConfig(
         vocab_size=encodec_vocab_size + 1,
         max_position_embeddings=2048,
@@ -42,11 +41,9 @@ if __name__ == "__main__":
         num_codebooks=num_codebooks,
     )
 
-
     decoder = ParlerTTSForCausalLM(decoder_config)
     decoder.save_pretrained(os.path.join(args.save_directory, "decoder"))
 
-
     model = ParlerTTSForConditionalGeneration.from_sub_models_pretrained(
         text_encoder_pretrained_model_name_or_path=text_model,
         audio_encoder_pretrained_model_name_or_path=encodec_version,

helpers/model_init_scripts/init_dummy_model_with_encodec.py

@@ -4,7 +4,7 @@ import os
 import argparse
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser()    
+    parser = argparse.ArgumentParser()
     parser.add_argument("save_directory", type=str, help="Directory where to save the model and the decoder.")
     args = parser.parse_args()
 
@@ -41,7 +41,6 @@ if __name__ == "__main__":
 
     decoder.save_pretrained(os.path.join(args.save_directory, "decoder"))
 
-
     model = ParlerTTSForConditionalGeneration.from_sub_models_pretrained(
         text_encoder_pretrained_model_name_or_path=text_model,
         audio_encoder_pretrained_model_name_or_path=encodec_version,

helpers/model_init_scripts/init_model_300M.py

@@ -5,11 +5,11 @@ import argparse
 
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser()    
+    parser = argparse.ArgumentParser()
     parser.add_argument("save_directory", type=str, help="Directory where to save the model and the decoder.")
     parser.add_argument("text_model", type=str, help="Repository id or path to the text encoder.")
     parser.add_argument("audio_model", type=str, help="Repository id or path to the audio encoder.")
-    
+
     args = parser.parse_args()
 
     text_model = args.text_model
@@ -22,7 +22,6 @@ if __name__ == "__main__":
     num_codebooks = encodec.num_codebooks
     print("num_codebooks", num_codebooks)
 
-
     decoder_config = ParlerTTSDecoderConfig(
         vocab_size=encodec_vocab_size + 64,  # + 64 instead of +1 to have a multiple of 64
         max_position_embeddings=4096,  # 30 s = 2580
@@ -42,11 +41,9 @@ if __name__ == "__main__":
         num_codebooks=num_codebooks,
     )
 
-
     decoder = ParlerTTSForCausalLM(decoder_config)
     decoder.save_pretrained(os.path.join(args.save_directory, "decoder"))
 
-
     model = ParlerTTSForConditionalGeneration.from_sub_models_pretrained(
         text_encoder_pretrained_model_name_or_path=text_model,
         audio_encoder_pretrained_model_name_or_path=encodec_version,
@@ -64,5 +61,4 @@ if __name__ == "__main__":
     model.generation_config.do_sample = True  # True
     model.generation_config.guidance_scale = 1  # 3.0
 
-
-    model.save_pretrained(os.path.join(args.save_directory,"stable-speech-untrained-300M/"))
+    model.save_pretrained(os.path.join(args.save_directory, "stable-speech-untrained-300M/"))

parler_tts/__init__.py

@@ -13,4 +13,4 @@ from .dac_wrapper import DACConfig, DACModel
 from transformers import AutoConfig, AutoModel
 
 AutoConfig.register("dac", DACConfig)
-AutoModel.register(DACConfig, DACModel)
\ No newline at end of file
+AutoModel.register(DACConfig, DACModel)