def test_simple_conv2d_transpose(): ncc.clear() ncc.save_tflite(module) init_values() ncc.compile(['--inference-type', 'float', '-t', 'cpu']) ncc.infer(['--dataset-format', 'raw']) ncc.close_to('test', 0)
def test_slice(): ncc.clear() ncc.save_tflite(module) init_values() ncc.compile(['--inference-type', 'float']) ncc.infer(['--dataset-format', 'raw']) ncc.close_to('test', 0)
def test_simple(): ncc.clear() ncc.copy_tflite('../examples/20classes_yolo/model/20classes_yolo.tflite') init_values() ncc.compile( ['--inference-type', 'float', '--max-allocator-solve-secs', '0']) ncc.infer(['--dataset-format', 'raw']) ncc.close_to('test', 1e-6)
def test_simple_matmul_quant(): ncc.clear() ncc.save_tflite(module) init_values() ncc.compile(['--inference-type', 'uint8', '-t', 'cpu', '--dataset', ncc.input_dir + '/test.bin', '--dataset-format', 'raw', '--input-type', 'float']) ncc.infer(['--dataset-format', 'raw']) ncc.close_to('test', 1e-3)
def test_add(input): ncc.clear() ncc.save_input_array('test', input) onnx_importer.utils.save(module, torch.from_numpy(input)) ncc.save_expect_array('test', onnx_importer.utils.run(input)) onnx_importer.utils.compile(['--inference-type', 'float']) ncc.infer(['--dataset-format', 'raw']) ncc.close_to('test', 0)
def test_simple_conv2d_k210(): ncc.clear() ncc.save_tflite(module) init_values() ncc.compile([ '--inference-type', 'uint8', '-t', 'k210', '--dataset', ncc.input_dir + '/test.bin', '--dataset-format', 'raw', '--input-type', 'float' ]) ncc.infer(['--dataset-format', 'raw']) ncc.close_to('test', 0.4)
def test_simple_k210(): ncc.clear() ncc.copy_tflite('../examples/20classes_yolo/model/20classes_yolo.tflite') init_values() ncc.compile([ '--inference-type', 'uint8', '-t', 'k210', '--dataset', ncc.input_dir + '/test.bin', '--dataset-format', 'raw', '--input-type', 'float', '--max-allocator-solve-secs', '0' ]) ncc.infer(['--dataset-format', 'raw']) ncc.close_to('test', 1.3)
def test_matmul_quant(input): ncc.clear() ncc.save_input_array('test', input) onnx_importer.utils.save(module, torch.from_numpy(input)) ncc.save_expect_array('test', onnx_importer.utils.run(input)) onnx_importer.utils.compile(['--inference-type', 'uint8', '-t', 'cpu', '--dataset', ncc.input_dir + '/test.bin', '--dataset-format', 'raw', '--input-type', 'float']) ncc.infer(['--dataset-format', 'raw']) ncc.close_to('test', 0.005)
def test_clip_k210_onnx_9(input): ncc.clear() ncc.save_input_array('test', input) onnx_importer.utils.save(module, torch.from_numpy(input), opset_version=9) ncc.save_expect_array('test', onnx_importer.utils.run(input)) onnx_importer.utils.compile(['--inference-type', 'uint8', '-t', 'k210', '--dataset', ncc.input_dir + '/test.bin', '--dataset-format', 'raw', '--input-type', 'float']) ncc.infer(['--dataset-format', 'raw']) ncc.close_to('test', 0.05)