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Add the support of profiling and multi-GPU running #636
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fluid/DeepASR/train.py Outdated
| trans_splice.TransSplice() | ||
| ] | ||
| | ||
| res_feature = fluid.LoDTensor() |
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Please think a better name.
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Done
fluid/DeepASR/train.py Outdated
| test_data_reader.batch_iterator(args.batch_size, | ||
| args.minimum_batch_size)): | ||
| # load_data | ||
| (bat_feature, bat_label, lod) = batch_data |
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Same as above
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Done
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All done, thx
fluid/DeepASR/train.py Outdated
| trans_splice.TransSplice() | ||
| ] | ||
| | ||
| res_feature = fluid.LoDTensor() |
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Done
fluid/DeepASR/train.py Outdated
| test_data_reader.batch_iterator(args.batch_size, | ||
| args.minimum_batch_size)): | ||
| # load_data | ||
| (bat_feature, bat_label, lod) = batch_data |
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Done
| LGTM |
fluid/DeepASR/model.py Outdated
| stacked_num, | ||
| parallel=False, | ||
| is_train=True, | ||
| class_num=1749): |
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I think we should not give a default value for class_num
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Done
| def _net_conf(feature, label): | ||
| seq_conv1 = fluid.layers.sequence_conv( | ||
| input=feature, | ||
| num_filters=1024, |
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We can make this configurable later, just mark here.
| size=class_num, | ||
| act='softmax') | ||
| | ||
| cost = fluid.layers.cross_entropy(input=prediction, label=label) |
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If is_traing==False, cost is unnecessary, since there maybe no label.
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cost and acc will be pruned when saving inference model
| Please consider reorganize the directory structure, for example: |
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Updated. Thx
fluid/DeepASR/model.py Outdated
| stacked_num, | ||
| parallel=False, | ||
| is_train=True, | ||
| class_num=1749): |
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Done
| size=class_num, | ||
| act='softmax') | ||
| | ||
| cost = fluid.layers.cross_entropy(input=prediction, label=label) |
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cost and acc will be pruned when saving inference model
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LGTM
Resolve #622