def _convert()

in mmdnn/conversion/_script/IRToCode.py [0:0]
48 lines of code
17 McCabe index (conditional complexity)

def _convert(args):
    if args.dstFramework == 'caffe':
        from mmdnn.conversion.caffe.caffe_emitter import CaffeEmitter
        if args.IRWeightPath is None:
            emitter = CaffeEmitter(args.IRModelPath)
        else:
            assert args.dstWeightPath
            emitter = CaffeEmitter((args.IRModelPath, args.IRWeightPath))

    elif args.dstFramework == 'keras':
        from mmdnn.conversion.keras.keras2_emitter import Keras2Emitter
        emitter = Keras2Emitter((args.IRModelPath, args.IRWeightPath))

    elif args.dstFramework == 'tensorflow':
        from mmdnn.conversion.tensorflow.tensorflow_emitter import TensorflowEmitter
        if args.IRWeightPath is None:
            # Convert network architecture only
            emitter = TensorflowEmitter(args.IRModelPath)
        else:
            emitter = TensorflowEmitter((args.IRModelPath, args.IRWeightPath))

    elif args.dstFramework == 'cntk':
        from mmdnn.conversion.cntk.cntk_emitter import CntkEmitter
        if args.IRWeightPath is None:
            emitter = CntkEmitter(args.IRModelPath)
        else:
            emitter = CntkEmitter((args.IRModelPath, args.IRWeightPath))

    elif args.dstFramework == 'coreml':
        raise NotImplementedError("CoreML emitter is not finished yet.")

    elif args.dstFramework == 'pytorch':
        if not args.dstWeightPath or not args.IRWeightPath:
            raise ValueError("Need to set a target weight filename.")
        from mmdnn.conversion.pytorch.pytorch_emitter import PytorchEmitter
        emitter = PytorchEmitter((args.IRModelPath, args.IRWeightPath))

    elif args.dstFramework == 'mxnet':
        from mmdnn.conversion.mxnet.mxnet_emitter import MXNetEmitter
        if args.IRWeightPath is None:
            emitter = MXNetEmitter(args.IRModelPath)
        else:
            if args.dstWeightPath is None:
                raise ValueError("MXNet emitter needs argument [dstWeightPath(dw)], like -dw mxnet_converted-0000.param")
            emitter = MXNetEmitter((args.IRModelPath, args.IRWeightPath, args.dstWeightPath))
    elif args.dstFramework == 'onnx':
        from mmdnn.conversion.onnx.onnx_emitter import OnnxEmitter
        if args.IRWeightPath is None:
            raise NotImplementedError("ONNX emitter needs IR weight file")
        else:
            emitter = OnnxEmitter(args.IRModelPath, args.IRWeightPath)
    else:
        assert False

    emitter.run(args.dstModelPath, args.dstWeightPath, args.phase)

    return 0