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)