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
