mbrookhart commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r617140617
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File path: python/tvm/topi/image/resize.py
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@@ -59,6 +59,33 @@ def get_2d_pixel(data, layout, boxes, image_height,
image_width, n, c, y, x, cc,
return data(n, c, y, x, cc).astype("float")
+def get_iny_inx(
+ y, x, image_height, image_width, target_height, target_width,
coordinate_transformation_mode
+):
+ scale_y = te.div(image_height.astype("float"),
target_height.astype("float"))
+ scale_x = te.div(image_width.astype("float"), target_width.astype("float"))
+ if coordinate_transformation_mode == "half_pixel":
+ in_y = (y + 0.5) * scale_y - 0.5
+ in_x = (x + 0.5) * scale_x - 0.5
+ elif coordinate_transformation_mode == "align_corners":
+ in_y = y * (image_height - 1).astype("float") / (target_height - 1)
+ in_x = x * (image_width - 1).astype("float") / (target_width - 1)
+ elif coordinate_transformation_mode == "asymmetric":
+ in_y = y * scale_y
+ in_x = x * scale_x
+ elif coordinate_transformation_mode == "pytorch_half_pixel":
Review comment:
No, the only test ONNX currently has with a target shape 1 is the
`pytorch_half_pixel` test. I separated them based on the ONNX Operator
documentation and the ORT implementation, but it doesn't look like I have a
test that hits the difference with a `half_pixel` mode.
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