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)
def testBuildAndCheckAllEndPointsUptoMixed5c(self): batch_size = 5 height, width = 224, 224 inputs = random_ops.random_uniform((batch_size, height, width, 3)) _, end_points = inception_v2.inception_v2_base( inputs, final_endpoint='Mixed_5c') endpoints_shapes = { 'Mixed_3b': [batch_size, 28, 28, 256], 'Mixed_3c': [batch_size, 28, 28, 320], 'Mixed_4a': [batch_size, 14, 14, 576], 'Mixed_4b': [batch_size, 14, 14, 576], 'Mixed_4c': [batch_size, 14, 14, 576], 'Mixed_4d': [batch_size, 14, 14, 576], 'Mixed_4e': [batch_size, 14, 14, 576], 'Mixed_5a': [batch_size, 7, 7, 1024], 'Mixed_5b': [batch_size, 7, 7, 1024], 'Mixed_5c': [batch_size, 7, 7, 1024], 'Conv2d_1a_7x7': [batch_size, 112, 112, 64], 'MaxPool_2a_3x3': [batch_size, 56, 56, 64], 'Conv2d_2b_1x1': [batch_size, 56, 56, 64], 'Conv2d_2c_3x3': [batch_size, 56, 56, 192], 'MaxPool_3a_3x3': [batch_size, 28, 28, 192] } self.assertItemsEqual(endpoints_shapes.keys(), end_points.keys()) for endpoint_name in endpoints_shapes: expected_shape = endpoints_shapes[endpoint_name] self.assertTrue(endpoint_name in end_points) self.assertListEqual( end_points[endpoint_name].get_shape().as_list(), expected_shape)
def testBuildBaseNetwork(self): batch_size = 5 height, width = 224, 224 inputs = random_ops.random_uniform((batch_size, height, width, 3)) mixed_5c, end_points = inception_v2.inception_v2_base(inputs) self.assertTrue(mixed_5c.op.name.startswith('InceptionV2/Mixed_5c')) self.assertListEqual(mixed_5c.get_shape().as_list(), [batch_size, 7, 7, 1024]) expected_endpoints = [ 'Mixed_3b', 'Mixed_3c', 'Mixed_4a', 'Mixed_4b', 'Mixed_4c', 'Mixed_4d', 'Mixed_4e', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Conv2d_1a_7x7', 'MaxPool_2a_3x3', 'Conv2d_2b_1x1', 'Conv2d_2c_3x3', 'MaxPool_3a_3x3' ] self.assertItemsEqual(end_points.keys(), expected_endpoints)
def testBuildOnlyUptoFinalEndpoint(self): batch_size = 5 height, width = 224, 224 endpoints = [ 'Conv2d_1a_7x7', 'MaxPool_2a_3x3', 'Conv2d_2b_1x1', 'Conv2d_2c_3x3', 'MaxPool_3a_3x3', 'Mixed_3b', 'Mixed_3c', 'Mixed_4a', 'Mixed_4b', 'Mixed_4c', 'Mixed_4d', 'Mixed_4e', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c' ] for index, endpoint in enumerate(endpoints): with ops.Graph().as_default(): inputs = random_ops.random_uniform((batch_size, height, width, 3)) out_tensor, end_points = inception_v2.inception_v2_base( inputs, final_endpoint=endpoint) self.assertTrue( out_tensor.op.name.startswith('InceptionV2/' + endpoint)) self.assertItemsEqual(endpoints[:index + 1], end_points)