Comments (2)
Thank you for taking a close look at the example! I think for the sake of simplicity, it is okay to leave the data loading as it is.
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From your recent activity on GitHub it seems like the performance issues that you report in this and other repos are generated (semi-)automatically. If that is the case, it would be helpful to include this info in the descriptions of the respective issues. From a code maintainer's perspective, it makes a difference whether a code analysis program detected a suboptimal order of, say, shuffle().batch().repeat()
or an actual user encountered an issue with the code.
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Related Issues (16)
- Constrain (0, max) instead of (-max, max)? HOT 6
- ValueError Issu HOT 4
- Result of Sequential MNIST HOT 14
- AttributeError: module 'tensorflow.python.ops.rnn_cell_impl' has no attribute '_LayerRNNCell' HOT 1
- Please release the code of action recognition HOT 2
- Cell structure HOT 3
- Errors when used in bidirectional_dynamic_rnn HOT 2
- ReLU activation with IndyLSTMCell HOT 5
- Would you like to contribute this cell to TF's tf.contrib.rnn? HOT 2
- how to reimplement the action recognition experiment of the original paper HOT 2
- How to add dropout to indrnn cells HOT 2
- Dimension Mismatch ?
- Performance issue in the definition of build_rnn, examples/sequential_mnist.py HOT 1
- Probably wrong indexing HOT 2
- Initialization of recurrent weight for the adding problem or similar problems HOT 14
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