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patriczhao pushed a commit to branch v1.5.x
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/v1.5.x by this push:
new 006486a Benchmark doc fix (#15769) (#16029)
006486a is described below
commit 006486af3c912b67b73ecee26a2fc73762e6e9ee
Author: Chaitanya Prakash Bapat <[email protected]>
AuthorDate: Wed Aug 28 19:38:15 2019 -0700
Benchmark doc fix (#15769) (#16029)
* Update pre-req for opperf
* Update README.md
* correct command to import binary broadcast
* no such op called nd.sub, it is nd.subtract
* Trigger notification
* Trigger notification
---
benchmark/opperf/README.md | 9 +++++----
1 file changed, 5 insertions(+), 4 deletions(-)
diff --git a/benchmark/opperf/README.md b/benchmark/opperf/README.md
index 99c75be..c73592d 100644
--- a/benchmark/opperf/README.md
+++ b/benchmark/opperf/README.md
@@ -46,9 +46,10 @@ Hence, in this utility, we will build the functionality to
allow users and devel
## Prerequisites
-This utility uses MXNet profiler under the hood to fetch compute and memory
metrics. Hence, you need to build MXNet with `USE_PROFILER=1` flag.
+Provided you have MXNet installed (any version >= 1.5.1), all you need to use
opperf utility is to add path to your cloned MXNet repository to the PYTHONPATH.
-Make sure to build the flavor of MXNet, for example - with/without MKL, with
CUDA 9 or 10.1 etc., on which you would like to measure operator performance.
Finally, you need to add path to your cloned MXNet repository to the PYTHONPATH.
+Note:
+To install MXNet, refer [Installing MXNet
page](https://mxnet.incubator.apache.org/versions/master/install/index.html)
```
export PYTHONPATH=$PYTHONPATH:/path/to/incubator-mxnet/
@@ -76,7 +77,7 @@ For example, you want to run benchmarks for all NDArray
Broadcast Binary Operato
```
#!/usr/bin/python
-from benchmark.opperf.tensor_operations.binary_broadcast_operators import
run_mx_binary_broadcast_operators_benchmarks
+from benchmark.opperf.nd_operations.binary_operators import
run_mx_binary_broadcast_operators_benchmarks
# Run all Binary Broadcast operations benchmarks with default input values
print(run_mx_binary_broadcast_operators_benchmarks())
@@ -137,7 +138,7 @@ from mxnet import nd
from benchmark.opperf.utils.benchmark_utils import run_performance_test
-add_res = run_performance_test([nd.add, nd.sub], run_backward=True,
dtype='float32', ctx=mx.cpu(),
+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)
