[GitHub] xinyu-intel commented on a change in pull request #12780: Add more models to benchmark_score

[GitBox <gi...@apache.org>]

xinyu-intel commented on a change in pull request #12780: Add more models to benchmark_score
URL: https://github.com/apache/incubator-mxnet/pull/12780#discussion_r224943106
 
 

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 File path: benchmark/python/gluon/benchmark_gluon.py
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+# 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.
+
+import mxnet as mx
+import mxnet.gluon.model_zoo.vision as models
+import time
+import logging
+import argparse
+import subprocess
+import os
+import errno
+
+logging.basicConfig(level=logging.INFO)
+parser = argparse.ArgumentParser(description='Gluon modelzoo-based CNN perf benchmark')
+
+parser.add_argument('--model', type=str, default='all',
+                               choices=['all', 'alexnet', 'densenet121', 'densenet161',
+                                        'densenet169', 'densenet201', 'inceptionv3', 'mobilenet0.25',
+                                        'mobilenet0.5', 'mobilenet0.75', 'mobilenet1.0', 'mobilenetv2_0.25',
+                                        'mobilenetv2_0.5', 'mobilenetv2_0.75', 'mobilenetv2_1.0', 'resnet101_v1',
+                                        'resnet101_v2', 'resnet152_v1', 'resnet152_v2', 'resnet18_v1',
+                                        'resnet18_v2', 'resnet34_v1', 'resnet34_v2', 'resnet50_v1',
+                                        'resnet50_v2', 'squeezenet1.0', 'squeezenet1.1', 'vgg11',
+                                        'vgg11_bn', 'vgg13', 'vgg13_bn', 'vgg16', 'vgg16_bn',
+                                        'vgg19', 'vgg19_bn'])
+parser.add_argument('--batch-size', type=int, default=0)
 
 Review comment:
   default = 0 means  run all batchsize in list [1, 2, 4, 8, 16, 32]. This is align with benchmark_score and users can set to a specific numbers.

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