| # Copyright © 2019 Arm Ltd. All rights reserved. |
| # SPDX-License-Identifier: MIT |
| import os |
| |
| import pytest |
| import pyarmnn as ann |
| import numpy as np |
| |
| |
| @pytest.fixture() |
| def parser(shared_data_folder): |
| """ |
| Parse and setup the test network (ssd_mobilenetv1) to be used for the tests below |
| """ |
| parser = ann.ITfLiteParser() |
| parser.CreateNetworkFromBinaryFile(os.path.join(shared_data_folder, 'ssd_mobilenetv1.tflite')) |
| |
| yield parser |
| |
| |
| def test_tflite_parser_swig_destroy(): |
| assert ann.ITfLiteParser.__swig_destroy__, "There is a swig python destructor defined" |
| assert ann.ITfLiteParser.__swig_destroy__.__name__ == "delete_ITfLiteParser" |
| |
| |
| def test_check_tflite_parser_swig_ownership(parser): |
| # Check to see that SWIG has ownership for parser. This instructs SWIG to take |
| # ownership of the return value. This allows the value to be automatically |
| # garbage-collected when it is no longer in use |
| assert parser.thisown |
| |
| def test_tflite_get_sub_graph_count(parser): |
| graphs_count = parser.GetSubgraphCount() |
| assert graphs_count == 1 |
| |
| |
| def test_tflite_get_network_input_binding_info(parser): |
| graphs_count = parser.GetSubgraphCount() |
| graph_id = graphs_count - 1 |
| |
| input_names = parser.GetSubgraphInputTensorNames(graph_id) |
| |
| input_binding_info = parser.GetNetworkInputBindingInfo(graph_id, input_names[0]) |
| |
| tensor = input_binding_info[1] |
| assert tensor.GetDataType() == 2 |
| assert tensor.GetNumDimensions() == 4 |
| assert tensor.GetNumElements() == 270000 |
| assert tensor.GetQuantizationOffset() == 128 |
| assert tensor.GetQuantizationScale() == 0.007874015718698502 |
| |
| |
| def test_tflite_get_network_output_binding_info(parser): |
| graphs_count = parser.GetSubgraphCount() |
| graph_id = graphs_count - 1 |
| |
| output_names = parser.GetSubgraphOutputTensorNames(graph_id) |
| |
| output_binding_info1 = parser.GetNetworkOutputBindingInfo(graph_id, output_names[0]) |
| output_binding_info2 = parser.GetNetworkOutputBindingInfo(graph_id, output_names[1]) |
| output_binding_info3 = parser.GetNetworkOutputBindingInfo(graph_id, output_names[2]) |
| output_binding_info4 = parser.GetNetworkOutputBindingInfo(graph_id, output_names[3]) |
| |
| # Check the tensor info retrieved from GetNetworkOutputBindingInfo |
| tensor1 = output_binding_info1[1] |
| tensor2 = output_binding_info2[1] |
| tensor3 = output_binding_info3[1] |
| tensor4 = output_binding_info4[1] |
| |
| assert tensor1.GetDataType() == 1 |
| assert tensor1.GetNumDimensions() == 3 |
| assert tensor1.GetNumElements() == 40 |
| assert tensor1.GetQuantizationOffset() == 0 |
| assert tensor1.GetQuantizationScale() == 0.0 |
| |
| assert tensor2.GetDataType() == 1 |
| assert tensor2.GetNumDimensions() == 2 |
| assert tensor2.GetNumElements() == 10 |
| assert tensor2.GetQuantizationOffset() == 0 |
| assert tensor2.GetQuantizationScale() == 0.0 |
| |
| assert tensor3.GetDataType() == 1 |
| assert tensor3.GetNumDimensions() == 2 |
| assert tensor3.GetNumElements() == 10 |
| assert tensor3.GetQuantizationOffset() == 0 |
| assert tensor3.GetQuantizationScale() == 0.0 |
| |
| assert tensor4.GetDataType() == 1 |
| assert tensor4.GetNumDimensions() == 1 |
| assert tensor4.GetNumElements() == 1 |
| assert tensor4.GetQuantizationOffset() == 0 |
| assert tensor4.GetQuantizationScale() == 0.0 |
| |
| |
| def test_tflite_get_subgraph_input_tensor_names(parser): |
| graphs_count = parser.GetSubgraphCount() |
| graph_id = graphs_count - 1 |
| |
| input_names = parser.GetSubgraphInputTensorNames(graph_id) |
| |
| assert input_names == ('normalized_input_image_tensor',) |
| |
| |
| def test_tflite_get_subgraph_output_tensor_names(parser): |
| graphs_count = parser.GetSubgraphCount() |
| graph_id = graphs_count - 1 |
| |
| output_names = parser.GetSubgraphOutputTensorNames(graph_id) |
| |
| assert output_names[0] == 'TFLite_Detection_PostProcess' |
| assert output_names[1] == 'TFLite_Detection_PostProcess:1' |
| assert output_names[2] == 'TFLite_Detection_PostProcess:2' |
| assert output_names[3] == 'TFLite_Detection_PostProcess:3' |
| |
| |
| def test_tflite_filenotfound_exception(shared_data_folder): |
| parser = ann.ITfLiteParser() |
| |
| with pytest.raises(RuntimeError) as err: |
| parser.CreateNetworkFromBinaryFile(os.path.join(shared_data_folder, 'some_unknown_network.tflite')) |
| |
| # Only check for part of the exception since the exception returns |
| # absolute path which will change on different machines. |
| assert 'Cannot find the file' in str(err.value) |
| |
| |
| def test_tflite_parser_end_to_end(shared_data_folder): |
| parser = ann.ITfLiteParser() |
| |
| network = parser.CreateNetworkFromBinaryFile(os.path.join(shared_data_folder,"inception_v3_quant.tflite")) |
| |
| graphs_count = parser.GetSubgraphCount() |
| graph_id = graphs_count - 1 |
| |
| input_names = parser.GetSubgraphInputTensorNames(graph_id) |
| input_binding_info = parser.GetNetworkInputBindingInfo(graph_id, input_names[0]) |
| |
| output_names = parser.GetSubgraphOutputTensorNames(graph_id) |
| |
| preferred_backends = [ann.BackendId('CpuAcc'), ann.BackendId('CpuRef')] |
| |
| options = ann.CreationOptions() |
| runtime = ann.IRuntime(options) |
| |
| opt_network, messages = ann.Optimize(network, preferred_backends, runtime.GetDeviceSpec(), ann.OptimizerOptions()) |
| assert 0 == len(messages) |
| |
| net_id, messages = runtime.LoadNetwork(opt_network) |
| assert "" == messages |
| |
| # Load test image data stored in input.npy |
| input_tensor_data = np.load(os.path.join(shared_data_folder, 'tflite_parser/inceptionv3_golden_input.npy')) |
| input_tensors = ann.make_input_tensors([input_binding_info], [input_tensor_data]) |
| |
| output_tensors = [] |
| for index, output_name in enumerate(output_names): |
| out_bind_info = parser.GetNetworkOutputBindingInfo(graph_id, output_name) |
| out_tensor_info = out_bind_info[1] |
| out_tensor_id = out_bind_info[0] |
| output_tensors.append((out_tensor_id, |
| ann.Tensor(out_tensor_info))) |
| |
| runtime.EnqueueWorkload(net_id, input_tensors, output_tensors) |
| |
| output_vectors = [] |
| for index, out_tensor in enumerate(output_tensors): |
| output_vectors.append(out_tensor[1].get_memory_area()) |
| |
| # Load golden output file to compare the output results with |
| expected_outputs = np.load(os.path.join(shared_data_folder, 'tflite_parser/inceptionv3_golden_output.npy')) |
| |
| # Check that output matches golden output |
| np.testing.assert_allclose(output_vectors, expected_outputs, 0.08) |