--- /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()