def test_tf_infer(self): new_width = 100 new_height = 125 new_attrs = nodes_attributes.copy() new_attrs.update({ 'new_shape': { 'value': np.array([new_height, new_width]), 'type': 'Const', 'kind': 'op' } }) graph = build_graph( new_attrs, [('node_1', 'resample'), ('new_shape', 'resample'), ('resample', 'node_3'), ('node_3', 'op_output')], { 'node_3': { 'shape': None }, 'node_1': { 'shape': np.array([1, 224, 227, 3]) }, 'resample': { 'antialias': 1, 'resample_type': 'LINEAR', 'factor': 1.0, 'fw': 'tf' } }) graph.graph['layout'] = 'NHWC' resample_node = Node(graph, 'resample') ResampleOp.resample_infer(resample_node) exp_shape = np.array([1, new_height, new_width, 3]) res_shape = graph.node['node_3']['shape'] for i in range(0, len(exp_shape)): self.assertEqual(exp_shape[i], res_shape[i])
def test_tf_resample_infer(self): graph = build_graph( nodes_attributes, [('node_1', 'resample'), ('resample', 'node_3'), ('node_3', 'op_output')], { 'node_3': { 'shape': None }, 'node_1': { 'shape': np.array([1, 3, 227, 227]) }, 'resample': { 'antialias': 1, 'height': 384, 'width': 512, 'resample_type': 'LINEAR', 'factor': 1.0 } }) graph.graph['layout'] = 'NCHW' resample_node = Node(graph, 'resample') ResampleOp.resample_infer(resample_node) exp_shape = np.array([1, 3, 384, 512]) res_shape = graph.node['node_3']['shape'] for i in range(0, len(exp_shape)): self.assertEqual(exp_shape[i], res_shape[i])
def test_caffe_factor_infer(self): factor = 3.0 graph = build_graph(nodes_attributes, [('node_1', 'resample'), ('resample', 'node_3')], {'node_3': {'is_output': True, 'shape': None}, 'node_1': {'shape': np.array([1, 3, 224, 227])}, 'resample': {'antialias': 1, 'resample_type': 'LINEAR', 'factor': factor} }) graph.graph['layout'] = 'NCHW' resample_node = Node(graph, 'resample') ResampleOp.resample_infer(resample_node) exp_shape = np.array([1, 3, 224 * factor, 227 * factor]) res_shape = graph.node['node_3']['shape'] for i in range(0, len(exp_shape)): self.assertEqual(exp_shape[i], res_shape[i])