You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hello! I've found a performance issue in /wide_deep/inference/fp32/wide_deep_inference.py: dataset.batch(batch_size)(line 192) should be called before dataset.map(parse_csv, num_parallel_calls=5)(line 187), which could make your program more efficient.
Besides, you need to check the function parse_csv called in dataset.map(parse_csv, num_parallel_calls=5) whether to be affected or not to make the changed code work properly. For example, if parse_csv 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 /wide_deep/inference/fp32/wide_deep_inference.py:
dataset.batch(batch_size)
(line 192) should be called beforedataset.map(parse_csv, num_parallel_calls=5)
(line 187), which could make your program more efficient.Here is the tensorflow document to support it.
Besides, you need to check the function
parse_csv
called indataset.map(parse_csv, num_parallel_calls=5)
whether to be affected or not to make the changed code work properly. For example, ifparse_csv
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: