7adaaa5628c25afb20fe42f3a6ad0622b35b8767,onnxmltools/convert/coreml/operator_converters/neural_network/Upsample.py,,convert_upsample,#Any#Any#Any#,10

Before Change

def convert_upsample(scope, operator, container):
    from coremltools.proto.NeuralNetwork_pb2 import UpsampleLayerParams as Params
    op_type = "Upsample"
    attrs = {"name": scope.get_unique_operator_name(op_type)}
    params = operator.raw_operator.upsample
    if params.mode == Params.NN:
        attrs["mode"] = "NEAREST"
    elif params.mode == Params.BILINEAR:

After Change

    height_scale = float(params.scalingFactor[0])

    apply_upsample(scope, operator.input_full_names, operator.output_full_names, container, operator_name=None,
                   mode=mode, scales=[1, 1, height_scale, width_scale])


register_converter("upsample", convert_upsample)

Instances