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[WIP] Implement upsample_bilinear2d_aa #8090

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[WIP] Implement upsample_bilinear2d_aa #8090

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1 change: 0 additions & 1 deletion experimental/torch_xla2/test/test_ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,6 @@
"__rpow__", # NOTE: cannot fix because torch test case has undefined behavior
# such as 0 to negative power.
"_segment_reduce",
"_upsample_bilinear2d_aa",
"bincount", # NOTE: dtype for int input torch gives float. This is weird.
"byte",
"cat",
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14 changes: 14 additions & 0 deletions experimental/torch_xla2/torch_xla2/ops/jaten.py
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Expand Up @@ -4095,3 +4095,17 @@ def _aten_max_unpoolxd(input, indices, output_size, stride=None, padding=0):

return output

@op(torch.ops.aten._upsample_bilinear2d_aa)
def _aten_upsample_bilinear2d_aa(input, output_size, align_corners, scale_factors):
if output_size is None:
raise ValueError("output_size value is not set correctly. It cannot be None or empty.")
# TODO: do we need a conversion from input to image ?
image = input
shape = output_size
method = "bilinear"
antialias = False # For upsampling
if align_corners:
raise ValueError("align_corners=true not supported yet")
# align_corners is not supported in resize()
# https://github.com/jax-ml/jax/issues/11206
return jax.image.resize(image, shape, method, antialias) # precision=Precision.HIGHEST