def TensorFlowFrozenParse(architecture_name, image_path): from mmdnn.conversion.examples.tensorflow.extractor import tensorflow_extractor from mmdnn.conversion.tensorflow.tensorflow_frozenparser import TensorflowParser2 # get original model prediction result original_predict = tensorflow_extractor.inference(architecture_name, None, TestModels.cachedir, image_path, is_frozen = True) para = tensorflow_extractor.get_frozen_para(architecture_name) del tensorflow_extractor # original to IR IR_file = TestModels.tmpdir + 'tensorflow_frozen_' + architecture_name + "_converted" parser = TensorflowParser2( TestModels.cachedir + para[0], para[1], para[2].split(':')[0], para[3].split(':')[0]) parser.run(IR_file) del parser del TensorflowParser2 return original_predict
def TensorFlowFrozenParse(architecture_name, image_path): from mmdnn.conversion.examples.tensorflow.extractor import tensorflow_extractor from mmdnn.conversion.tensorflow.tensorflow_frozenparser import TensorflowParser2 # get original model prediction result original_predict = tensorflow_extractor.inference(architecture_name, TestModels.cachedir, image_path, is_frozen = True) para = tensorflow_extractor.get_frozen_para(architecture_name) del tensorflow_extractor # original to IR IR_file = TestModels.tmpdir + 'tensorflow_frozen_' + architecture_name + "_converted" parser = TensorflowParser2( TestModels.cachedir + para[0], para[1], para[2].split(':')[0], para[3].split(':')[0]) parser.run(IR_file) del parser del TensorflowParser2 return original_predict