def patch_pytorch_ops()

in src/exporters/coreml/models.py [0:0]

• 8 lines of code
• 1 McCabe index (conditional complexity)

    def patch_pytorch_ops(self):
        # There is no bicubic upsampling in Core ML, so we'll have to use bilinear.
        # Still seems to work well enough. Note: the bilinear resize is applied to
        # constant tensors, so we could actually remove this op completely!
        def upsample_bicubic2d(context, node):
            from coremltools.converters.mil import Builder as mb

            a = context[node.inputs[0]]
            b = context[node.inputs[1]]
            x = mb.resize_bilinear(x=a, target_size_height=b.val[0], target_size_width=b.val[1], name=node.name)
            context.add(x)

        return {"upsample_bicubic2d": upsample_bicubic2d}