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您好，请问您在实现compare-aggreate有没有达到论文中提到的效果呢？论文中的wikiqa的map是0.743，MRR是0.754，我用了自己写的代码和您写的代码，最后结果都不是很理想，如果您有什么实现细节，可以告知一下吗，感谢！

Hello, I found a performance issue in the definition of cudnn_gru, MRC/BiDAF/layers.py, tf.zeros([1, batch_size, num_units]) will be created repeatedly during program execution, resulting in reduced efficiency. I think it should be created before the loop.

The same issue exist in :

• tf.zeros in line 97;
• tf.zeros in line 149 and 150;
• tf.zeros in line 131 and 132;
• tf.zeros in line 187 and 188;
• tf.zeros in line 133 and 134;
• tf.zeros in line 186 and 187;
• tf.zeros in line 235 and 236;

Looking forward to your reply. Btw, I am very glad to create a PR to fix it if you are too busy.

What are the Python, tensorflow, and cuda versions of your BiDAF project?

Hello! I've found a performance issue in /MRC: batch() should be called before map(), which could make your program more efficient. Here is the tensorflow document to support it.

Detailed description is listed below:

• /BiDAF/util.py: dataset.batch(config.batch_size)(here) should be called before .map(parser, num_parallel_calls=num_threads)(here).
• /MRC/BiDAF/util.py: .batch(config.batch_size)(here) should be called before .map(parser, num_parallel_calls=num_threads)(here).
• /MRC/Hybrid/util.py: dataset.batch(config.batch_size)(here) should be called before .map(parser, num_parallel_calls=num_threads)(here).
• /MRC/Hybrid/util.py: .batch(config.batch_size)(here) should be called before .map(parser, num_parallel_calls=num_threads)(here).
• /MRC/QANet/util.py: dataset.batch(config.batch_size)(here) should be called before .map(parser, num_parallel_calls=num_threads)(here).
• /MRC/QANet/util.py: .batch(config.batch_size)(here) should be called before .map(parser, num_parallel_calls=num_threads)(here).
• /MRC/RNet/util.py: dataset.batch(config.batch_size)(here) should be called before .map(parser, num_parallel_calls=num_threads)(here).
• /MRC/RNet/util.py: .batch(config.batch_size)(here) should be called before .map(parser, num_parallel_calls=num_threads)(here).

Besides, you need to check the function called in map()(e.g., parser called in .map(parser, num_parallel_calls=num_threads)) whether to be affected or not to make the changed code work properly. For example, if parser needs data with shape (x, y, z) as its input before fix, it would require data with shape (batch_size, x, y, z).

Looking forward to your reply. Btw, I am very glad to create a PR to fix it if you are too busy.

What is the reference paper for the QANet project?