mirror of
https://github.com/storytold/storyteller-ml.git
synced 2026-10-28 09:08:54 +00:00
Brandon Thomas
45 lines
1.6 KiB
Python
Executable File
45 lines
1.6 KiB
Python
Executable File
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import pytorch_lightning as pl
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from nemo.collections.common.callbacks import LogEpochTimeCallback
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from nemo.collections.tts.models import UniGlowModel
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from nemo.core.config import hydra_runner
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from nemo.utils import logging
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from nemo.utils.exp_manager import exp_manager
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@hydra_runner(config_path="conf", config_name="uniglow")
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def main(cfg):
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trainer = pl.Trainer(**cfg.trainer)
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epoch_time_logger = LogEpochTimeCallback()
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trainer.callbacks.extend([epoch_time_logger])
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exp_manager(trainer, cfg.get("exp_manager", None))
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if cfg.resume_from_ckpt is None:
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logging.info("Training UniGlow from scratch")
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model = UniGlowModel(cfg=cfg.model, trainer=trainer)
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else:
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logging.info("Fine-tuning UniGlow from {cfg.resume_from_ckpt}")
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model = UniGlowModel.restore_from(cfg.resume_from_ckpt)
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model.setup_training_data(cfg.model.train_ds)
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model.setup_validation_data(cfg.model.validation_ds)
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trainer.fit(model)
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if __name__ == '__main__':
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main() # noqa pylint: disable=no-value-for-parameter
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