improve EmbeddingBag performance on cuda (#33589)
Summary:
This PR improves performance of EmbeddingBag on cuda by removing 5 kernel launches (2 of those are synchronizing memcopies).
- 2 memcopies are checking values of offsets[0] and offsets[-1] to be in expected range (0 for the former, less than number of indices for the latter). It seems strange to check only those 2 values, if users are providing invalid offsets, invalid values can be anywhere in the array, not only the first and last element. After this PR, the checks are skipped on cuda, the first value is forced to 0, if the last value is larger than expected, cuda kernel will assert. It is less nice than ValueError, but then again, the kernel could have asserted if other offset values were invalid. On the cpu, the checks are moved inside the cpu implementation from functional.py, and will throw RuntimeError instead of ValueError.
- 3 or 4 initializations (depending on the mode) of the output tensors with .zeros() are unnecessary, because every element of those tensors is written to, so their data can be uninitialized on the start.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/33589
Reviewed By: jianyuh
Differential Revision: D20078011
Pulled By: ngimel
fbshipit-source-id: 2fb2e2080313af64adc5cf1b9fc6ffbdc6efaf16
