def execute(self, target_dir): model_file = hp.find_file_ends_with(target_dir, 'predict_net.pb') init_file = hp.find_file_ends_with(target_dir, 'init_net.pb') assert len(model_file) == 1 and len(init_file) == 1 hp.rename(target_dir, model_file[0], Caffe2NetDefFormatter._target_model_filename) hp.rename(target_dir, init_file[0], Caffe2NetDefFormatter._target_init_model_filename)
def execute(self, target_dir): # 1. mkdir ./model.savedmodel os.makedirs( os.path.join(target_dir, TFSavedModelFormatter._target_savedmodel_dirname)) # 2. find . | grep "[.]pb" pb_file = hp.find_file_ends_with(target_dir, '.pb') assert len(pb_file) == 1 hp.rename( target_dir, pb_file[0], os.path.join(TFSavedModelFormatter._target_savedmodel_dirname, pb_file[0])) if len(hp.find_file_ends_with(target_dir, 'variables')) > 0: shutil.move( os.path.join(target_dir, 'variables'), os.path.join(target_dir, TFSavedModelFormatter._target_savedmodel_dirname))
def execute(self, target_dir): tensorrt_file = hp.find_file_ends_with(target_dir, '.plan') assert len(tensorrt_file) == 1 hp.rename(target_dir, tensorrt_file[0], TensorRTFormatter._target_plan_filename)
def execute(self, target_dir): pmml_file = hp.find_file_ends_with(target_dir, '.pmml') assert len(pmml_file) == 1 hp.rename(target_dir, pmml_file[0], PMMLFormatter._target_pmml_filename)
def execute(self, target_dir): pb_file = hp.find_file_ends_with(target_dir, '.graphdef') assert len(pb_file) == 1 hp.rename(target_dir, pb_file[0], TFGraphDefFormatter._target_graphdef_filename)
def execute(self, target_dir): pt_file = hp.find_file_ends_with(target_dir, '.pt') assert len(pt_file) == 1 hp.rename(target_dir, pt_file[0], TorchScriptFormatter._target_torchscript_filename)
def execute(self, target_dir): onnx_file = hp.find_file_ends_with(target_dir, '.onnx') assert len(onnx_file) == 1 hp.rename(target_dir, onnx_file[0], ONNXFormatter._target_onnx_filename)
def execute(self, target_dir): xgboost_file = hp.find_file_ends_with(target_dir, '.xgboost') assert len(xgboost_file) == 1 hp.rename(target_dir, xgboost_file[0], XGBoostFormatter._target_xgboost_filename)
def execute(self, target_dir): sklearn_file = hp.find_file_ends_with(target_dir, '.joblib') assert len(sklearn_file) == 1 hp.rename(target_dir, sklearn_file[0], SKLearnFormatter._target_sklearn_filename)