+++ /dev/null
-# Copyright 2016 Google Inc. All Rights Reserved.
-#
-# Licensed 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.
-# ==============================================================================
-
-"""Tests for slim.inception."""
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import tensorflow as tf
-
-from nets import nets_factory
-
-slim = tf.contrib.slim
-
-
-class NetworksTest(tf.test.TestCase):
-
- def testGetNetworkFn(self):
- batch_size = 5
- num_classes = 1000
- for net in nets_factory.networks_map:
- with self.test_session():
- net_fn = nets_factory.get_network_fn(net, num_classes)
- # Most networks use 224 as their default_image_size
- image_size = getattr(net_fn, 'default_image_size', 224)
- inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
- logits, end_points = net_fn(inputs)
- self.assertTrue(isinstance(logits, tf.Tensor))
- self.assertTrue(isinstance(end_points, dict))
- self.assertEqual(logits.get_shape().as_list()[0], batch_size)
- self.assertEqual(logits.get_shape().as_list()[-1], num_classes)
-
- def testGetNetworkFnArgScope(self):
- batch_size = 5
- num_classes = 10
- net = 'cifarnet'
- with self.test_session(use_gpu=True):
- net_fn = nets_factory.get_network_fn(net, num_classes)
- image_size = getattr(net_fn, 'default_image_size', 224)
- with slim.arg_scope([slim.model_variable, slim.variable],
- device='/CPU:0'):
- inputs = tf.random_uniform((batch_size, image_size, image_size, 3))
- net_fn(inputs)
- weights = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, 'CifarNet/conv1')[0]
- self.assertDeviceEqual('/CPU:0', weights.device)
-
-if __name__ == '__main__':
- tf.test.main()