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qingqing01
reviewed
Dec 4, 2017
| fc = fluid.layers.fc(input=inputs, size=hid_dim) | ||
| lstm, cell = fluid.layers.dynamic_lstm( | ||
| input=fc, size=hid_dim, is_reverse=(i % 2) == 0) | ||
| inputs = [fc, lstm] |
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The configuration here is not consistent with the config in https://github.com/dzhwinter/benchmark/pull/2/files . There is no reversed LSTM in that PR. Just simple stacked LSTM.
| # data = fluid.layers.data( | ||
| # name="words", shape=[1], append_batch_size=False, dtype="int64") | ||
| # label = fluid.layers.data( | ||
| # name="label", shape=[1], append_batch_size=False, dtype="int64") |
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Remove the unused codes.
| '--use_cprof', action='store_true', help='If set, use cProfile.') | ||
| parser.add_argument( | ||
| '--use_nvprof', | ||
| action='store_false', |
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store_false -> store_true
qingqing01
approved these changes
Dec 5, 2017
| hid_dim = args.hid_dim | ||
| stacked_num = args.stacked_num | ||
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| assert stacked_num % 2 == 1, "Must stacked_num %2 == 1." |
| for i in range(stacked_num): | ||
| fc = fluid.layers.fc(input=inputs, size=hid_dim) | ||
| lstm, cell = fluid.layers.dynamic_lstm(input=fc, size=hid_dim) | ||
| inputs = [fc, lstm] |
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inputs = lstm
line 66 67实际可以和line 71 - lin 74行合并。
| fc1 = fluid.layers.fc(input=emb, size=hid_dim) | ||
| lstm1, cell1 = fluid.layers.dynamic_lstm(input=fc1, size=hid_dim) | ||
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| inputs = [fc1, lstm1] |
qingqing01
reviewed
Dec 5, 2017
| inputs = [fc, lstm] | ||
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| fc_last = fluid.layers.sequence_pool(input=inputs[0], pool_type='max') | ||
| lstm_last = fluid.layers.sequence_pool(input=inputs[1], pool_type='max') |
Collaborator
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只需要对最后的lstm进行pooling即可，line 79只有一个pooling 之后的输入。
意图是为了保持和 https://github.com/dzhwinter/benchmark/blob/master/paddle/understand_sentiment_lstm.py#L74 这里一致。
qingqing01
reviewed
Dec 5, 2017
| train_reader = paddle.batch( | ||
| paddle.reader.shuffle( | ||
| paddle.dataset.imdb.train(word_dict), | ||
| buf_size=args.batch_size * 10), |
Owner
Author
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all fixed based on comments. |
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fix PaddlePaddle/Paddle#6165