szha commented on a change in pull request #14977: Add an utility for operator benchmarks URL: https://github.com/apache/incubator-mxnet/pull/14977#discussion_r293062132
########## File path: benchmark/opperf/nd_operations/random_sampling_operators.py ########## @@ -0,0 +1,61 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +"""Performance benchmark tests for MXNet NDArray Random Sampling Operations. +1. Operators are automatically fetched from MXNet operator registry. +2. Default Inputs are generated. See rules/default_params.py. You can override the default values. + +Below 16 random sampling Operators are covered: + +['random_exponential', 'random_gamma', 'random_generalized_negative_binomial', 'random_negative_binomial', +'random_normal', 'random_poisson', 'random_randint', 'random_uniform', 'sample_exponential', 'sample_gamma', +'sample_generalized_negative_binomial', 'sample_multinomial', 'sample_negative_binomial', 'sample_normal', +'sample_poisson', 'sample_uniform'] + +""" + +import mxnet as mx + +from benchmark.opperf.utils.benchmark_utils import run_op_benchmarks +from benchmark.opperf.utils.op_registry_utils import get_all_random_sampling_operators + + +def run_mx_random_sampling_operators_benchmarks(ctx=mx.cpu(), dtype='float32', warmup=10, runs=50): Review comment: is there any case where the random operator changes its runtime based on seed? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] With regards, Apache Git Services
