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Add loading model function for train.py. #72
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -11,6 +11,7 @@ | |
| from model import deep_speech2 | ||
| from audio_data_utils import DataGenerator | ||
| import numpy as np | ||
| import os | ||
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| #TODO: add WER metric | ||
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@@ -78,6 +79,11 @@ | |
| default='data/eng_vocab.txt', | ||
| type=str, | ||
| help="Vocabulary filepath. (default: %(default)s)") | ||
| parser.add_argument( | ||
| "--init_model_path", | ||
| default='models/params.tar.gz', | ||
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| type=str, | ||
| help="Model path for initialization. (default: %(default)s)") | ||
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| args = parser.parse_args() | ||
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@@ -114,8 +120,13 @@ def train(): | |
| rnn_size=args.rnn_layer_size, | ||
| is_inference=False) | ||
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| # create parameters and optimizer | ||
| parameters = paddle.parameters.create(cost) | ||
| # create/load parameters and optimizer | ||
| if args.init_model_path is None: | ||
| parameters = paddle.parameters.create(cost) | ||
| else: | ||
| assert os.path.isfile(args.init_model_path), "Invalid model." | ||
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| parameters = paddle.parameters.Parameters.from_tar( | ||
| gzip.open(args.init_model_path)) | ||
| optimizer = paddle.optimizer.Adam( | ||
| learning_rate=args.adam_learning_rate, gradient_clipping_threshold=400) | ||
| trainer = paddle.trainer.SGD( | ||
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Set default to None (training from scratch).