Upload synthesizer_train.py with huggingface_hub

synthesizer_train.py

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+from synthesizer.hparams import hparams
+from synthesizer.train import train
+from utils.argutils import print_args
+import argparse
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("run_id", type=str, help= \
+        "Name for this model instance. If a model state from the same run ID was previously "
+        "saved, the training will restart from there. Pass -f to overwrite saved states and "
+        "restart from scratch.")
+    parser.add_argument("syn_dir", type=str, default=argparse.SUPPRESS, help= \
+        "Path to the synthesizer directory that contains the ground truth mel spectrograms, "
+        "the wavs and the embeds.")
+    parser.add_argument("-m", "--models_dir", type=str, default="synthesizer/saved_models/", help=\
+        "Path to the output directory that will contain the saved model weights and the logs.")
+    parser.add_argument("-s", "--save_every", type=int, default=1000, help= \
+        "Number of steps between updates of the model on the disk. Set to 0 to never save the "
+        "model.")
+    parser.add_argument("-b", "--backup_every", type=int, default=25000, help= \
+        "Number of steps between backups of the model. Set to 0 to never make backups of the "
+        "model.")
+    parser.add_argument("-f", "--force_restart", action="store_true", help= \
+        "Do not load any saved model and restart from scratch.")
+    parser.add_argument("--hparams", default="",
+                        help="Hyperparameter overrides as a comma-separated list of name=value "
+							 "pairs")
+    args = parser.parse_args()
+    print_args(args, parser)
+
+    args.hparams = hparams.parse(args.hparams)
+
+    # Run the training
+    train(**vars(args))