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Hello! I've found a performance issue in /data.py: ds.batch(batch_size)(here) should be called before ds.map(_map_fn, num_parallel_calls=4)(here), which could make your program more efficient.
Besides, you need to check the function _map_fn called in ds.map(_map_fn, num_parallel_calls=4) whether to be affected or not to make the changed code work properly. For example, if _map_fn needs data with shape (x, y, z) as its input before fix, it would require data with shape (batch_size, x, y, z) after fix.
Looking forward to your reply. Btw, I am very glad to create a PR to fix it if you are too busy.
The text was updated successfully, but these errors were encountered:
Hello! I've found a performance issue in /data.py:
ds.batch(batch_size)
(here) should be called beforeds.map(_map_fn, num_parallel_calls=4)
(here), which could make your program more efficient.Here is the tensorflow document to support it.
Besides, you need to check the function
_map_fn
called inds.map(_map_fn, num_parallel_calls=4)
whether to be affected or not to make the changed code work properly. For example, if_map_fn
needs data with shape (x, y, z) as its input before fix, it would require data with shape (batch_size, x, y, z) after fix.Looking forward to your reply. Btw, I am very glad to create a PR to fix it if you are too busy.
The text was updated successfully, but these errors were encountered: