def testModelVariables(self): batch_size = 5 height, width = 224, 224 num_classes = 1000 with self.cached_session(): inputs = random_ops.random_uniform((batch_size, height, width, 3)) vgg.vgg_a(inputs, num_classes) expected_names = [ 'vgg_a/conv1/conv1_1/weights', 'vgg_a/conv1/conv1_1/biases', 'vgg_a/conv2/conv2_1/weights', 'vgg_a/conv2/conv2_1/biases', 'vgg_a/conv3/conv3_1/weights', 'vgg_a/conv3/conv3_1/biases', 'vgg_a/conv3/conv3_2/weights', 'vgg_a/conv3/conv3_2/biases', 'vgg_a/conv4/conv4_1/weights', 'vgg_a/conv4/conv4_1/biases', 'vgg_a/conv4/conv4_2/weights', 'vgg_a/conv4/conv4_2/biases', 'vgg_a/conv5/conv5_1/weights', 'vgg_a/conv5/conv5_1/biases', 'vgg_a/conv5/conv5_2/weights', 'vgg_a/conv5/conv5_2/biases', 'vgg_a/fc6/weights', 'vgg_a/fc6/biases', 'vgg_a/fc7/weights', 'vgg_a/fc7/biases', 'vgg_a/fc8/weights', 'vgg_a/fc8/biases', ] model_variables = [ v.op.name for v in variables_lib.get_model_variables() ] self.assertSetEqual(set(model_variables), set(expected_names))
def testModelHasExpectedNumberOfParameters(self): batch_size = 5 height, width = 224, 224 inputs = random_ops.random_uniform((batch_size, height, width, 3)) with arg_scope(inception_v2.inception_v2_arg_scope()): inception_v2.inception_v2_base(inputs) total_params, _ = model_analyzer.analyze_vars( variables_lib.get_model_variables()) self.assertAlmostEqual(10173112, total_params)