blob: a64668451a25812dd8cd405c285dff199ce58112 [file] [log] [blame]
# 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.
from __future__ import print_function
import mxnet as mx
from mxnet.gluon.model_zoo.vision import get_model
import sys
from common import setup_module, with_seed, teardown
def eprint(*args, **kwargs):
print(*args, file=sys.stderr, **kwargs)
@with_seed()
def test_models():
all_models = ['resnet18_v1', 'resnet34_v1', 'resnet50_v1', 'resnet101_v1', 'resnet152_v1',
'resnet18_v2', 'resnet34_v2', 'resnet50_v2', 'resnet101_v2', 'resnet152_v2',
'vgg11', 'vgg13', 'vgg16', 'vgg19',
'vgg11_bn', 'vgg13_bn', 'vgg16_bn', 'vgg19_bn',
'alexnet', 'inceptionv3',
'densenet121', 'densenet161', 'densenet169', 'densenet201',
'squeezenet1.0', 'squeezenet1.1',
'mobilenet1.0', 'mobilenet0.75', 'mobilenet0.5', 'mobilenet0.25',
'mobilenetv2_1.0', 'mobilenetv2_0.75', 'mobilenetv2_0.5', 'mobilenetv2_0.25']
pretrained_to_test = set(['squeezenet1.1'])
for model_name in all_models:
test_pretrain = model_name in pretrained_to_test
model = get_model(model_name, pretrained=test_pretrain, root='model/')
data_shape = (2, 3, 224, 224) if 'inception' not in model_name else (2, 3, 299, 299)
eprint('testing forward for %s' % model_name)
print(model)
if not test_pretrain:
model.collect_params().initialize()
model(mx.nd.random.uniform(shape=data_shape)).wait_to_read()
if __name__ == '__main__':
import nose
nose.runmodule()