Justin-Tan
commented
3 years ago Hey, this looks good, unfortunately it's been a while since I looked at the codebase. I agree from the documentation that this should increase performance. Happy to accept a PR if you create it for this and any other issues.
Hello! I've found a performance issue in your project:
batch()should be called beforemap(), which could make your program more efficient. Here is the tensorflow document to support it.Detailed description is listed below:
dataset.batch(batch_size)(here) should be called beforedataset.map(_parser)(here).dataset.batch(batch_size)(here) should be called beforedataset.map(_parser)(here).dataset.batch(batch_size)(here) should be called beforedataset.map(_preprocess_inference)(here).dataset.batch(batch_size)(here) should be called beforedataset.map(_parser)(here).dataset.batch(batch_size)(here) should be called beforedataset.map(_parser)(here).dataset.batch(batch_size)(here) should be called beforedataset.map(_preprocess_inference)(here).Besides, you need to check the function called in
map()(e.g.,_preprocess_inferencecalled indataset.map(_preprocess_inference)) whether to be affected or not to make the changed code work properly. For example, if_preprocess_inferenceneeds 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.