1# Licensed to the Apache Software Foundation (ASF) under one 2# or more contributor license agreements. See the NOTICE file 3# distributed with this work for additional information 4# regarding copyright ownership. The ASF licenses this file 5# to you under the Apache License, Version 2.0 (the 6# "License"); you may not use this file except in compliance 7# with the License. You may obtain a copy of the License at 8# 9# http://www.apache.org/licenses/LICENSE-2.0 10# 11# Unless required by applicable law or agreed to in writing, 12# software distributed under the License is distributed on an 13# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY 14# KIND, either express or implied. See the License for the 15# specific language governing permissions and limitations 16# under the License. 17 18"""Performance benchmark tests for MXNet NDArray Reduction Operations. 191. Operators are automatically fetched from MXNet operator registry. 202. Default Inputs are generated. See rules/default_params.py. You can override the default values. 21 22Below 10 reduction Operators are covered: 23 24['max', 'max_axis', 'mean', 'min', 'min_axis', 'nanprod', 'nansum', 'prod', 'sum', 'sum_axis'] 25 26""" 27 28import mxnet as mx 29 30from benchmark.opperf.utils.op_registry_utils import get_all_reduction_operators 31from benchmark.opperf.utils.benchmark_utils import run_op_benchmarks 32 33 34def run_mx_reduction_operators_benchmarks(ctx=mx.cpu(), dtype='float32', profiler='native', warmup=25, runs=100): 35 """Runs benchmarks with the given context and precision (dtype)for all the reduction 36 operators in MXNet. 37 38 Parameters 39 ---------- 40 ctx: mx.ctx 41 Context to run benchmarks 42 dtype: str, default 'float32' 43 Precision to use for benchmarks 44 profiler: str, default 'native' 45 Type of Profiler to use (native/python) 46 warmup: int, default 25 47 Number of times to run for warmup 48 runs: int, default 100 49 Number of runs to capture benchmark results 50 51 Returns 52 ------- 53 Dictionary of results. Key -> Name of the operator, Value -> Benchmark results. 54 55 """ 56 # Fetch all Reduction Operators 57 mx_reduction_broadcast_ops = get_all_reduction_operators() 58 # Run benchmarks 59 mx_reduction_op_results = run_op_benchmarks(mx_reduction_broadcast_ops, dtype, ctx, profiler, warmup, runs) 60 return mx_reduction_op_results 61