ChaiBapchya commented on a change in pull request #17642: [OpPerf] Fixed Python
profiler bug
URL: https://github.com/apache/incubator-mxnet/pull/17642#discussion_r382350528
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File path: benchmark/opperf/utils/profiler_utils.py
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@@ -248,12 +248,11 @@ def python_profile(func):
@functools.wraps(func)
def python_profile_it(*args, **kwargs):
runs = args[1]
- modified_args = (args[0], 1, args[2])
Review comment:
So the args that are passed to this function are
args[0] = op
args[1] = warmup / runs (number of times to run for warmup or number of
times to run)
args[2] - rest of the args
https://github.com/apache/incubator-mxnet/blob/9dcf71d8fe33f77ed316a95fcffaf1f7f883ff70/benchmark/opperf/utils/benchmark_utils.py#L114
https://github.com/apache/incubator-mxnet/blob/9dcf71d8fe33f77ed316a95fcffaf1f7f883ff70/benchmark/opperf/utils/benchmark_utils.py#L121
The way it worked for native MXNet CPP profiler is that you could pass the
runs (and it would capture the time for each value along with mean/max, etc)
But for Python's time it function, we had to manually run the `for loop` for
the number of runs.
So that's what I did there
1. we copy the number of runs in a variable in run and then run it that many
number of times
2. For each run, we use python time it function to time it and then take
average, mean, max, etc values for each of those individual python time runs.
Makes sense? @apeforest
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