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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2021/04/19 15:53:50 UTC
[GitHub] [tvm] mbrookhart opened a new pull request #7883: Resize refactor
mbrookhart opened a new pull request #7883:
URL: https://github.com/apache/tvm/pull/7883
This refactors the resize kernel to make it compatible with the many options in ONNX's tests. :crossed_fingers: I didn't break anything elsewhere.
cc @masahi @jwfromm @yongwww @electriclilies
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[GitHub] [tvm] mbrookhart commented on pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
mbrookhart commented on pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#issuecomment-824129779
I'm hitting a small and intermittent atol issue with the TF tests on GPU. Before bumping it from 1e-5 to 2e-5, I'm trying to figure out if I actually changed the behavior for these options.
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[GitHub] [tvm] mbrookhart commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
mbrookhart commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r616158860
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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:
The previous kernel only supported a small combination of these options, and the topi tests only support two. It looks like the TF importer only supports align_corners and assymetric, but TF 1.15 also supports half pixel: https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/image/resize_bilinear I don't see any of these options in TF 2.0
Pytorch seems to support assymetric, align_corners, and half pixel, but it doesn't look like either importer is actually testing half_pixel
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[GitHub] [tvm] masahi commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
masahi commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r616257175
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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:
Also when I added `half_pixel` option, I intended this option to correspond exactly to ONNX `pytorch_half_pixel`. In PT ONNX exporter, `pytorch_half_pixel` is introduced for bilinear + align_corners=False case, and that is also when `half_pixel` is used in our PT frontend. See https://github.com/pytorch/pytorch/blob/c371542efc31b1abfe6f388042aa3ab0cef935f2/torch/onnx/symbolic_helper.py#L517-L518
So we probably don't need `pytorch_half_pixel`. We can update `half_pixel` if necessary.
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[GitHub] [tvm] masahi commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
masahi commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r616257175
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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:
Also when I added `half_pixel` option, I intended this option to correspond exactly to ONNX `pytorch_half_pixel`. In PT ONNX exporter, `pytorch_half_pixel` is introduced for bilinear + align_corners=False case, and that is also when `half_pixel` is used in our PT frontend. See https://github.com/pytorch/pytorch/blob/c371542efc31b1abfe6f388042aa3ab0cef935f2/torch/onnx/symbolic_helper.py#L517-L518
So we probably don't need ``pytorch_half_pixel`. We can update `half_pixel` if necessary.
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[GitHub] [tvm] jwfromm commented on pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
jwfromm commented on pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#issuecomment-824372527
Thanks @mbrookhart, @masahi. This is now merged.
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[GitHub] [tvm] mbrookhart commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
mbrookhart commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r615979167
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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:
I'm honestly not sure what the frameworks are expecting or what tests they currently do or do not pass?
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[GitHub] [tvm] masahi commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
masahi commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r616233259
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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:
Tried adding `verify_model(Upsample(size=(50, 50), mode="bilinear", align_corners=False), inp)` to the test, it worked fortunately.
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[GitHub] [tvm] mbrookhart commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
mbrookhart commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r615977936
##########
File path: python/tvm/relay/op/image/image.py
##########
@@ -58,6 +61,16 @@ def resize(
Refer to the ONNX Resize operator specification for details.
[half_pixel, align_corners, asymmetric]
+ rounding_method: string, optional
+ indicates how to find the "nearest" pixel in nearest_neighbor method
+ [round, floor, ceil]
+
+ bicubic_alpha: float
+ Spline Coefficient for Bicubic Interpolation
+
+ bicubic_exclude: int
+ Flag to exclude exterior of the image during bicubic interpolation
Review comment:
ONNX is using an Int, so I did this to be consistent, but it might be clearer to use a bool. A wash?
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[GitHub] [tvm] mbrookhart commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
mbrookhart commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r617141030
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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:
I would prefer to leave the separation for that future use case that's assuming `half_pixel` instead of `pytorch_half_pixel` for a resize to 1, even if we don't see it yet.
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[GitHub] [tvm] masahi commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
masahi commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r617079571
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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:
Ok I looked at the spec again, and indeed I realized they have two variants of `half_pixel`... I don't know what `pytorch_half_pixel` is for, probably only for the case where the resized shape is 1?
Does using `pytorch_half_pixel` for onnx tests that use `half_pixel` break them? If not we can probably override our definition of `half_pixel` to match `pytorch_half_pixel`.
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[GitHub] [tvm] masahi commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
masahi commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r616257175
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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:
Also when I added `half_pixel` option, I intended this option to correspond exactly to ONNX `pytorch_half_pixel`. In PT ONNX exporter, ``pytorch_half_pixel` is introduced for bilinear + align_corners=False case, and that is also when `half_pixel` is used in our PT frontend. See https://github.com/pytorch/pytorch/blob/c371542efc31b1abfe6f388042aa3ab0cef935f2/torch/onnx/symbolic_helper.py#L517-L518
So we probably don't need ``pytorch_half_pixel`. We can update `half_pixel` if necessary.
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[GitHub] [tvm] mbrookhart commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
mbrookhart commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r616158860
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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:
The previous kernel only supported a small combination of these options, and the topi tests only support two. It looks like the TF importer only supports align_corners and asymmetric, but TF 1.15 also supports half pixel: https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/image/resize_bilinear I don't see any of these options in TF 2.0
Pytorch seems to support asymmetric, align_corners, and half pixel, but it doesn't look like either importer is actually testing half_pixel
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[GitHub] [tvm] jwfromm commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
jwfromm commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r617891826
##########
File path: python/tvm/relay/op/image/image.py
##########
@@ -58,6 +61,16 @@ def resize(
Refer to the ONNX Resize operator specification for details.
[half_pixel, align_corners, asymmetric]
+ rounding_method: string, optional
+ indicates how to find the "nearest" pixel in nearest_neighbor method
+ [round, floor, ceil]
+
+ bicubic_alpha: float
+ Spline Coefficient for Bicubic Interpolation
+
+ bicubic_exclude: int
+ Flag to exclude exterior of the image during bicubic interpolation
Review comment:
if onnx uses an in then im cool with it.
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[GitHub] [tvm] jwfromm merged pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
jwfromm merged pull request #7883:
URL: https://github.com/apache/tvm/pull/7883
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[GitHub] [tvm] masahi commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
masahi commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r617079571
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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:
Ok I looked at the spec again, and indeed I realized they have two variants of `half_pixel`... I don't know what `pytorch_half_pixel` is for, probably only for the case where the resized shape is 1?
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[GitHub] [tvm] jwfromm commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
jwfromm commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r615973599
##########
File path: python/tvm/relay/op/image/image.py
##########
@@ -58,6 +61,16 @@ def resize(
Refer to the ONNX Resize operator specification for details.
[half_pixel, align_corners, asymmetric]
+ rounding_method: string, optional
+ indicates how to find the "nearest" pixel in nearest_neighbor method
+ [round, floor, ceil]
+
+ bicubic_alpha: float
+ Spline Coefficient for Bicubic Interpolation
+
+ bicubic_exclude: int
+ Flag to exclude exterior of the image during bicubic interpolation
Review comment:
should this be a bool rather than int?
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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:
Do we need to update the pytorch and tf frontends to use these new modes?
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -443,6 +476,7 @@ def resize_bicubic(
target_width : integer
The target resized image width
+
Review comment:
this extra empty line probably isnt supposed to be there.
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[GitHub] [tvm] mbrookhart commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
mbrookhart commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r616749985
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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:
The ONNX tests definitely have some failures if I use half_pixel when ONNX suggests pytorch_half_pixel, the issue is the if_then_else forcing some values to 0
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[GitHub] [tvm] masahi commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
masahi commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r616231499
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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:
Hmm I thought we were testing `half_pixel` in PT frontend but indeed it doesn't seem so. I think `half_pixel` corresponds to `bilinear` + `align_corners=False` but this combination is not there below
https://github.com/apache/tvm/blob/b24fbe7dee10195b6585634c0625828fe8624d5f/tests/python/frontend/pytorch/test_forward.py#L1701-L1703
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[GitHub] [tvm] mbrookhart commented on pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
mbrookhart commented on pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#issuecomment-824136011
I changed the order of operations on align_corner from out = a / b * x to out = x * a / b. That seems to have caused some rounding errors on GPU, if I revert the change the intermittency goes away.
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[GitHub] [tvm] mbrookhart commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
mbrookhart commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r617140617
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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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[GitHub] [tvm] masahi commented on a change in pull request #7883: [ONNX][TOPI][RELAY] Resize refactor
Posted by GitBox <gi...@apache.org>.
masahi commented on a change in pull request #7883:
URL: https://github.com/apache/tvm/pull/7883#discussion_r617079571
##########
File path: python/tvm/topi/image/resize.py
##########
@@ -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:
Ok I looked at the spec again, and indeed I realized they have two variants of `half_pixel`... I don't know what `pytorch_half_pixel` is for, probably only for the case where the resized shape is 1?
Does using `pytorch_half_pixel` for onnx tests that use `half_pixel` break them?
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