def CntkParse(architecture_name, image_path):
from mmdnn.conversion.examples.cntk.extractor import cntk_extractor
from mmdnn.conversion.cntk.cntk_parser import CntkParser
# download model
architecture_file = cntk_extractor.download(architecture_name, TestModels.cachedir)
# get original model prediction result
original_predict = cntk_extractor.inference(architecture_name, architecture_file, image_path)
del cntk_extractor
# original to IR
IR_file = TestModels.tmpdir + 'cntk_' + architecture_name + "_converted"
parser = CntkParser(architecture_file)
parser.run(IR_file)
del parser
del CntkParser
return original_predict
def CntkParse(architecture_name, image_path):
from mmdnn.conversion.examples.cntk.extractor import cntk_extractor
from mmdnn.conversion.cntk.cntk_parser import CntkParser
# download model
architecture_file = cntk_extractor.download(architecture_name, TestModels.cachedir)
# get original model prediction result
original_predict = cntk_extractor.inference(architecture_name, architecture_file, image_path)
del cntk_extractor
# original to IR
IR_file = TestModels.tmpdir + 'cntk_' + architecture_name + "_converted"
parser = CntkParser(architecture_file)
parser.run(IR_file)
del parser
del CntkParser
return original_predict
