def test_raises_with_multiple_models_kaldi_dlsdk(self):
config = {
'framework': 'dlsdk',
'onnx_model': 'kaldi_model',
'model': 'custom_model',
'weights': 'custom_weights',
'device': 'cpu',
}
with pytest.raises(ConfigError):
DLSDKLauncher(config)
def test_raises_with_multiple_models_onnx_tf(self):
config = {
"framework": "dlsdk",
"onnx_model": 'onnx_model',
"tf_model": 'tf_model',
"device": 'cpu',
"bitstream": "custom_bitstream"
}
with pytest.raises(ValueError):
DLSDKLauncher(config, dummy_adapter)
def test_raises_with_multiple_models_mxnet_tf(self):
config = {
'framework': 'dlsdk',
'mxnet_weights': 'mxnet_weights',
'tf_model': 'tf_model',
'device': 'cpu',
'_models_prefix': 'prefix'
}
with pytest.raises(ConfigError):
DLSDKLauncher(config, dummy_adapter)
def setup(self):
self.launcher = {
'model': 'foo.xml',
'weights': 'foo.bin',
'device': 'CPU',
'framework': 'dlsdk',
'adapter': 'classification',
'_models_prefix': 'prefix'
}
self.config = DLSDKLauncherConfigValidator(
'dlsdk_launcher', fields=DLSDKLauncher.parameters())
def test_raises_with_multiple_models_onnx_tf(self):
config = {
'framework': 'dlsdk',
'onnx_model': 'onnx_model',
'tf_model': 'tf_model',
'device': 'cpu',
'_models_prefix': 'prefix'
}
with pytest.raises(ConfigError):
DLSDKLauncher(config)
def test_raises_with_multiple_models_mxnet_caffe(self):
config = {
'framework': 'dlsdk',
'mxnet_weights': 'mxnet_weights',
'caffe_model': 'caffe_model',
'caffe_weights': 'caffe_weights',
'device': 'cpu',
}
with pytest.raises(ConfigError):
DLSDKLauncher(config)
def test_raises_with_multiple_models_dlsdk_tf_mxnet(self):
config = {
'framework': "dlsdk",
'model': 'custom_model',
'weights': 'custom_weights',
'mxnet_weights': 'mxnet_weights',
'tf_model': 'tf_model',
'device': 'cpu',
}
with pytest.raises(ConfigError):
DLSDKLauncher(config)
def test_raises_with_multiple_models_mxnet_dlsdk(self):
config = {
'framework': 'dlsdk',
'mxnet_weights': 'mxnet_weights',
'model': 'custom_model',
'weights': 'custom_weights',
'device': 'cpu',
'_models_prefix': 'prefix'
}
with pytest.raises(ConfigError):
DLSDKLauncher(config)
def test_raises_with_multiple_models_kaldi_dlsdk(self):
config = {
"framework": "dlsdk",
"onnx_model": 'kaldi_model',
"model": 'custom_model',
"weights": 'custom_weights',
"device": 'cpu',
"bitstream": "custom_bitstream"
}
with pytest.raises(ValueError):
DLSDKLauncher(config, dummy_adapter)
def test_raises_with_multiple_models_mxnet_caffe(self):
config = {
"framework": "dlsdk",
"mxnet_weights": 'mxnet_weights',
"caffe_model": 'caffe_model',
"caffe_weights": 'caffe_weights',
"device": 'cpu',
"bitstream": "custom_bitstream"
}
with pytest.raises(ValueError):
DLSDKLauncher(config, dummy_adapter)
def test_raises_with_multiple_models_onnx_caffe(self, mocker):
mock_inference_engine(mocker)
config = {
"framework": "dlsdk",
"onnx_model": 'onnx_model',
"caffe_model": 'caffe_model',
"caffe_weights": 'caffe_weights',
"device": 'cpu',
"bitstream": "custom_bitstream"
}
with pytest.raises(ValueError):
DLSDKLauncher(config, dummy_adapter)
def test_raises_with_multiple_models_dlsdk_caffe_onnx(self):
config = {
'framework': 'dlsdk',
'model': 'custom_model',
'weights': 'custom_weights',
'caffe_model': 'caffe_model',
'caffe_weights': 'caffe_weights',
'onnx_model': 'onnx_model',
'device': 'cpu',
'_models_prefix': 'prefix'
}
with pytest.raises(ConfigError):
DLSDKLauncher(config, dummy_adapter)
def test_raises_with_tf_model_and_tf_meta_both_provided(self):
config = {
'framework': 'dlsdk',
'model': 'custom_model',
'weights': 'custom_weights',
'caffe_model': 'caffe_model',
'caffe_weights': 'caffe_weights',
'mxnet_weights': 'mxnet_weights',
'tf_model': 'tf_model',
'tf_meta': 'tf_meta',
'device': 'cpu',
}
with pytest.raises(ConfigError):
DLSDKLauncher(config)
def test_model_converted_from_kaldi(self, mocker):
mock = mocker.patch(
'accuracy_checker.launcher.dlsdk_launcher.convert_model',
return_value=('converted_model', 'converted_weights'))
config = {
'framework': 'dlsdk',
'kaldi_model': '/path/to/source_models/custom_model',
'device': 'cpu',
'_models_prefix': '/path/to/source_models',
'adapter': 'classification'
}
DLSDKLauncher(config, dummy_adapter)
mock.assert_called_once_with('custom_model',
'/path/to/source_models/custom_model', '',
'kaldi', [], None, None, None, None)
def test_model_conversion_raises_config_error_if_output_dir_in_mo_params_and_converted_model_dir_both_provided(
self, mocker):
config = {
"framework": "dlsdk",
"tf_model": '/path/to/source_models/custom_model',
"device": 'cpu',
"_converted_models": Path("/path/to/converted_models"),
"_models_prefix": Path("/path/to"),
"adapter": "classification",
'converted_model_dir': 'models',
'mo_params': {
'output_dir': Path('/path/to/output/models')
}
}
mocker.patch('pathlib.Path.resolve',
return_value=Path(config['_converted_models']))
with pytest.raises(ConfigError):
DLSDKLauncher(config, dummy_adapter)
def test_model_converted_from_kaldi(self, mocker):
mock = mocker.patch(
'accuracy_checker.launcher.dlsdk_launcher.convert_model',
return_value=('converted_model', 'converted_weights')
)
config = {
'framework': 'dlsdk',
'kaldi_model': '/path/to/source_models/custom_model',
'device': 'cpu',
'adapter': 'classification',
'should_log_cmd': False
}
DLSDKLauncher(config)
mock.assert_called_once_with(
'custom_model', '/path/to/source_models/custom_model', '', '',
FrameworkParameters('kaldi', False), [], None, None, None, None, None,
should_log_cmd=False
)
def test_model_converted_from_mxnet(self, mocker):
mock = mocker.patch(
'accuracy_checker.launcher.dlsdk_launcher.convert_model',
return_value=('converted_model',
'converted_weights')) # type: MagicMock
config = {
"framework": "dlsdk",
"mxnet_weights": '/path/to/source_models/custom_weights',
"device": 'cpu',
"bitstream": "custom_bitstream",
"_converted_models": Path("/path/to/converted_models"),
"_models_prefix": Path("/path/to/source_models"),
"adapter": "classification"
}
mock_inputs(mocker)
DLSDKLauncher(config, dummy_adapter)
mock.assert_called_once_with(
'custom_weights', Path("/path/to/converted_models"), None,
Path("/path/to/source_models/custom_weights"), 'mxnet', [], None)
def test_model_converted_from_tf_checkpoint_with_arg_path_to_obj_detection_api_config(
self, mocker):
config = {
'framework': 'dlsdk',
'tf_meta': '/path/to/source_models/custom_model',
'device': 'cpu',
'_models_prefix': '/path/to',
'adapter': 'classification',
'mo_params': {
'tensorflow_object_detection_api_pipeline_config':
'operations.config'
},
'_tf_custom_op_config_dir': 'config/dir',
'_tf_obj_detection_api_pipeline_config_path': 'od_api'
}
mocker.patch('accuracy_checker.launcher.model_conversion.find_mo',
return_value=Path('/path/ModelOptimizer'))
prepare_args_patch = mocker.patch(
'accuracy_checker.launcher.model_conversion.prepare_args')
args = {
'input_meta_graph':
'/path/to/source_models/custom_model',
'model_name':
'custom_model',
'framework':
'tf',
'tensorflow_object_detection_api_pipeline_config':
'od_api/operations.config'
}
mocker.patch(
'accuracy_checker.launcher.model_conversion.exec_mo_binary',
return_value=subprocess.CompletedProcess(args, returncode=0))
DLSDKLauncher(config)
prepare_args_patch.assert_called_once_with('/path/ModelOptimizer',
flag_options=[],
value_options=args)
def test_model_converted_from_kaldi(self, mocker):
mock = mocker.patch(
'accuracy_checker.launcher.dlsdk_launcher.convert_model',
return_value=('converted_model',
'converted_weights')) # type: MagicMock
config = {
"framework": "dlsdk",
"kaldi_model": '/path/to/source_models/custom_model',
"device": 'cpu',
"bitstream": "custom_bitstream",
"_converted_models": Path("/path/to/converted_models"),
"_models_prefix": Path("/path/to/source_models"),
"adapter": "classification"
}
mocker.patch('pathlib.Path.resolve',
return_value=Path(config['_converted_models']))
DLSDKLauncher(config, dummy_adapter)
mock.assert_called_once_with(
'custom_model', Path("/path/to/converted_models"),
Path("/path/to/source_models/custom_model"), None, 'kaldi', [], {},
[], None)
def test_model_converted_to_output_dir_in_mo_params(self, mocker):
config = {
'framework': 'dlsdk',
'tf_model': '/path/to/source_models/custom_model',
'device': 'cpu',
'adapter': 'classification',
'mo_params': {'output_dir': '/path/to/output/models'}
}
mocker.patch('accuracy_checker.launcher.model_conversion.find_mo', return_value='ModelOptimizer')
prepare_args_patch = mocker.patch('accuracy_checker.launcher.model_conversion.prepare_args')
args = {
'input_model': '/path/to/source_models/custom_model',
'model_name': 'custom_model',
'output_dir': '/path/to/output/models',
'framework': 'tf'
}
mocker.patch(
'accuracy_checker.launcher.model_conversion.exec_mo_binary',
return_value=subprocess.CompletedProcess(args, returncode=0)
)
DLSDKLauncher(config)
prepare_args_patch.assert_called_once_with('ModelOptimizer', flag_options=[], value_options=args)
def test_model_converted_with_mo_params(self, mocker):
mock = mocker.patch(
'accuracy_checker.launcher.dlsdk_launcher.convert_model',
return_value=('converted_model', 'converted_weights')
)
config = {
'framework': "dlsdk",
'caffe_model': '/path/to/source_models/custom_model',
'caffe_weights': '/path/to/source_models/custom_weights',
'device': 'cpu',
'bitstream': Path('custom_bitstream'),
'mo_params': {'data_type': 'FP16'},
'adapter': 'classification',
'should_log_cmd': False
}
DLSDKLauncher(config)
mock.assert_called_once_with(
'custom_model', '/path/to/source_models/custom_model', '/path/to/source_models/custom_weights', '',
FrameworkParameters('caffe', False),
[], {'data_type': 'FP16'}, None, None, None, None, should_log_cmd=False
)
def test_not_converted_twice_from_tf_if_use_model_from_cache(self, mocker):
mock = mocker.patch(
'accuracy_checker.launcher.dlsdk_launcher.convert_model',
return_value=('converted_model',
'converted_weights')) # type: MagicMock
mock_inputs(mocker)
with mock_filesystem([
'converted_models/bar/converted_model.bin',
'converted_models/bar/converted_model.xml'
]) as prefix:
config = {
"framework": "dlsdk",
"tf_model": '/source_models/bar/custom_model.frozen.pb',
"device": 'cpu',
"bitstream": "custom_bitstream",
"_models_prefix": Path("/source_models"),
"_converted_models": Path(prefix) / 'converted_models',
"adapter": "classification",
"use_cached_model": True
}
DLSDKLauncher(config, dummy_adapter)
mock.assert_not_called()
def test_model_converted_with_mo_flags(self, mocker):
mock = mocker.patch(
'accuracy_checker.launcher.dlsdk_launcher.convert_model',
return_value=('converted_model', 'converted_weights'))
config = {
'framework': 'dlsdk',
'caffe_model': '/path/to/source_models/custom_model',
'caffe_weights': '/path/to/source_models/custom_weights',
'device': 'cpu',
'bitstream': Path('custom_bitstream'),
'_models_prefix': '/path/to/source_models',
'mo_flags': ['reverse_input_channels'],
'adapter': 'classification'
}
DLSDKLauncher(config, dummy_adapter)
mock.assert_called_once_with('custom_model',
'/path/to/source_models/custom_model',
'/path/to/source_models/custom_weights',
'caffe', [], None,
['reverse_input_channels'], None, None)
def test_model_converted_from_tf_with_arg_path_to_custom_tf_config(
self, mocker):
config = {
'framework': 'dlsdk',
'tf_model': '/path/to/source_models/custom_model',
'device': 'cpu',
'_models_prefix': '/path/to',
'adapter': 'classification',
'mo_params': {
'tensorflow_use_custom_operations_config':
'ssd_v2_support.json'
},
'_tf_custom_op_config_dir': 'config/dir'
}
mocker.patch('accuracy_checker.launcher.model_conversion.find_mo',
return_value=Path('/path/ModelOptimizer'))
prepare_args_patch = mocker.patch(
'accuracy_checker.launcher.model_conversion.prepare_args')
args = {
'input_model':
'/path/to/source_models/custom_model',
'model_name':
'custom_model',
'framework':
'tf',
'tensorflow_use_custom_operations_config':
'config/dir/ssd_v2_support.json'
}
mocker.patch(
'accuracy_checker.launcher.model_conversion.exec_mo_binary',
return_value=subprocess.CompletedProcess(args, returncode=0))
DLSDKLauncher(config, dummy_adapter)
prepare_args_patch.assert_called_once_with('/path/ModelOptimizer',
flag_options=[],
value_options=args)
def test_model_converted_from_tf_checkpoint_with_default_path_to_custom_tf_config(self, mocker):
config = {
'framework': 'dlsdk',
'tf_meta': '/path/to/source_models/custom_model',
'device': 'cpu',
'adapter': 'classification',
'mo_params': {'tensorflow_use_custom_operations_config': 'config.json'}
}
mocker.patch('accuracy_checker.launcher.model_conversion.find_mo', return_value=self.FAKE_MO_PATH)
prepare_args_patch = mocker.patch('accuracy_checker.launcher.model_conversion.prepare_args')
args = {
'input_meta_graph': '/path/to/source_models/custom_model',
'model_name': 'custom_model',
'framework': 'tf',
'tensorflow_use_custom_operations_config': str(Path('/path/extensions/front/tf/config.json').absolute())
}
mocker.patch(
'accuracy_checker.launcher.model_conversion.exec_mo_binary',
return_value=subprocess.CompletedProcess(args, returncode=0)
)
DLSDKLauncher(config)
prepare_args_patch.assert_called_once_with(str(self.FAKE_MO_PATH), flag_options=[], value_options=args)
