Add max_audio_length parameter

TTS/demos/xtts_ft_demo/utils/gpt_train.py

@@ -8,7 +8,7 @@ from TTS.tts.layers.xtts.trainer.gpt_trainer import GPTArgs, GPTTrainer, GPTTrai
 from TTS.utils.manage import ModelManager
 
 
-def train_gpt(language, num_epochs, batch_size, grad_acumm, train_csv, eval_csv, output_path):
+def train_gpt(language, num_epochs, batch_size, grad_acumm, train_csv, eval_csv, output_path, max_audio_length=255995):
     #  Logging parameters
     RUN_NAME = "GPT_XTTS_FT"
     PROJECT_NAME = "XTTS_trainer"
@@ -79,7 +79,7 @@ def train_gpt(language, num_epochs, batch_size, grad_acumm, train_csv, eval_csv,
         max_conditioning_length=132300,  # 6 secs
         min_conditioning_length=66150,  # 3 secs
         debug_loading_failures=False,
-        max_wav_length=255995,  # ~11.6 seconds
+        max_wav_length=max_audio_length,  # ~11.6 seconds
         max_text_length=200,
         mel_norm_file=MEL_NORM_FILE,
         dvae_checkpoint=DVAE_CHECKPOINT,

TTS/demos/xtts_ft_demo/xtts_demo.py

@@ -147,6 +147,13 @@ if __name__ == "__main__":
         help="Grad accumulation steps. Default: 1",
         default=1,
     )
+    parser.add_argument(
+        "--max_audio_length",
+        type=int,
+        help="Max permitted audio size in seconds. Default: 11",
+        default=11,
+    )
+
     args = parser.parse_args()
 
     with gr.Blocks() as demo:
@@ -250,6 +257,13 @@ if __name__ == "__main__":
                 step=1,
                 value=args.grad_acumm,
             )
+            max_audio_length = gr.Slider(
+                label="Max permitted audio size in seconds:",
+                minimum=2,
+                maximum=20,
+                step=1,
+                value=args.max_audio_length,
+            )
             progress_train = gr.Label(
                 label="Progress:"
             )
@@ -260,12 +274,14 @@ if __name__ == "__main__":
             demo.load(read_logs, None, logs_tts_train, every=1)
             train_btn = gr.Button(value="Step 2 - Run the training")
 
-            def train_model(language, train_csv, eval_csv, num_epochs, batch_size, grad_acumm, output_path):
+            def train_model(language, train_csv, eval_csv, num_epochs, batch_size, grad_acumm, output_path, max_audio_length):
                 clear_gpu_cache()
                 if not train_csv or not eval_csv:
                     return "You need to run the data processing step or manually set `Train CSV` and `Eval CSV` fields !", "", "", "", ""
                 try:
-                    config_path, original_xtts_checkpoint, vocab_file, exp_path, speaker_wav = train_gpt(language, num_epochs, batch_size, grad_acumm, train_csv, eval_csv, output_path=output_path)
+                    # convert seconds to waveform frames
+                    max_audio_length = int(max_audio_length * 22050)
+                    config_path, original_xtts_checkpoint, vocab_file, exp_path, speaker_wav = train_gpt(language, num_epochs, batch_size, grad_acumm, train_csv, eval_csv, output_path=output_path, max_audio_length=max_audio_length)
                 except:
                     traceback.print_exc()
                     error = traceback.format_exc()
@@ -280,7 +296,6 @@ if __name__ == "__main__":
                 clear_gpu_cache()
                 return "Model training done!", config_path, vocab_file, ft_xtts_checkpoint, speaker_wav
 
-
         with gr.Tab("3 - Inference"):
             with gr.Row():
                 with gr.Column() as col1:
@@ -367,6 +382,7 @@ if __name__ == "__main__":
                     batch_size,
                     grad_acumm,
                     out_path,
+                    max_audio_length,
                 ],
                 outputs=[progress_train, xtts_config, xtts_vocab, xtts_checkpoint, speaker_reference_audio],
             )