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set fixed seed for profiler (#16155)
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* set fix seed for profiler

* update README with profiler option

* fix wording
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apeforest authored Sep 24, 2019
1 parent 33bd02f commit 1d4032d
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18 changes: 17 additions & 1 deletion benchmark/opperf/README.md
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Expand Up @@ -129,7 +129,7 @@ Output for the above benchmark run, on a CPU machine, would look something like
```

## Usecase 3.1 - Run benchmarks for group of operators with same input
## Usecase 4 - Run benchmarks for group of operators with same input
For example, you want to run benchmarks for `nd.add`, `nd.sub` operator in MXNet, with the same set of inputs. You just run the following python script.

```
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However, fully automated tests are enabled only for simpler operators such as - broadcast operators, element_wise operators etc... For the purpose of readability and giving more control to the users, complex operators such as convolution (2D, 3D), Pooling, Recurrent are not fully automated but expressed as default rules.
See `utils/op_registry_utils.py` for more details.

## Use python timer
Optionally, you could use the python time package as the profiler engine to caliberate runtime in each operator.
To use python timer for all operators, use the argument --profiler 'python':
```
python incubator-mxnet/benchmark/opperf/opperf.py --profiler='python'
```

To use python timer for a specific operator, pass the argument profiler to the run_performance_test method:
```
add_res = run_performance_test([nd.add, nd.subtract], run_backward=True, dtype='float32', ctx=mx.cpu(),
inputs=[{"lhs": (1024, 1024),
"rhs": (1024, 1024)}],
warmup=10, runs=25, profiler='python')
```
By default, MXNet profiler is used as the profiler engine.

# TODO

All contributions are welcome. Below is the list of desired features:
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1 change: 1 addition & 0 deletions benchmark/opperf/utils/benchmark_utils.py
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Expand Up @@ -28,6 +28,7 @@


def _prepare_op_inputs(inputs, run_backward, dtype, ctx):
mx.random.seed(41)
kwargs_list = []
args_list = []

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