def create_example_test_directory():
# fill in the inputs that we want to use specific values for
input_data = {}
input_data["K"] = np.asarray([64]).astype(np.int64)
# provide symbolic dim values as needed
symbolic_dim_values = {"batch": 25, "items": 256}
# create the directory. random input will be created for any missing inputs.
# the model will be run and the output will be saved as expected output for future runs
ort_test_dir_utils.create_test_dir("topk.onnx", "PerfTests", "test1", input_data, symbolic_dim_values)
def run_backend_ort(model_path, test_data_set=None):
# if 'test_data_set_N' doesn't exist, create test_dir
if not test_data_set:
onnxruntime.InferenceSession(model_path)
ort_test_dir_utils.create_test_dir(model_path, './',
test_utils.TEST_ORT_DIR)
ort_test_dir_utils.run_test_dir(test_utils.TEST_ORT_DIR)
# otherwise use the existing 'test_data_set_N' as test data
else:
test_dir_from_tar = test_utils.get_model_directory(model_path)
ort_test_dir_utils.run_test_dir(test_dir_from_tar)
# remove the produced test_dir from ORT
test_utils.remove_onnxruntime_test_dir()
def run_backend_ort(model_path, test_data_set=None):
model = onnx.load(model_path)
if model.opset_import[0].version < 7:
print(
'Skip ORT test since it only *guarantees* support for models stamped with opset version 7'
)
return
# if 'test_data_set_N' doesn't exist, create test_dir
if not test_data_set:
onnxruntime.InferenceSession(model_path)
ort_test_dir_utils.create_test_dir(model_path, './',
test_utils.TEST_ORT_DIR)
ort_test_dir_utils.run_test_dir(test_utils.TEST_ORT_DIR)
# otherwise use the existing 'test_data_set_N' as test data
else:
test_dir_from_tar = test_utils.get_model_directory(model_path)
ort_test_dir_utils.run_test_dir(test_dir_from_tar)
# remove the produced test_dir from ORT
test_utils.remove_onnxruntime_test_dir()