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Give more useful exception when batch is considered during matrix multiplication #7326

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merged 5 commits into from
Jan 8, 2024
Merged

Give more useful exception when batch is considered during matrix multiplication #7326

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a0f7967
fix #7323
KumoLiu Dec 18, 2023
35b29b2
minor fix
KumoLiu Dec 18, 2023
c06a89b
Merge branch 'dev' into affine-matrix
KumoLiu Dec 18, 2023
ba82172
Update monai/transforms/inverse.py
KumoLiu Dec 27, 2023
d3854d5
Merge branch 'dev' into affine-matrix
ericspod Jan 6, 2024
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7 changes: 6 additions & 1 deletion monai/transforms/inverse.py
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Original file line number Diff line number Diff line change
Expand Up @@ -185,7 +185,12 @@ def track_transform_meta(
# not lazy evaluation, directly update the metatensor affine (don't push to the stack)
orig_affine = data_t.peek_pending_affine()
orig_affine = convert_to_dst_type(orig_affine, affine, dtype=torch.float64)[0]
affine = orig_affine @ to_affine_nd(len(orig_affine) - 1, affine, dtype=torch.float64)
try:
affine = orig_affine @ to_affine_nd(len(orig_affine) - 1, affine, dtype=torch.float64)
except RuntimeError as e:
raise RuntimeError(
"mismatch affine matrix, ensured that the batch dimension is not included in the calculation."
) from e
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out_obj.meta[MetaKeys.AFFINE] = convert_to_tensor(affine, device=torch.device("cpu"), dtype=torch.float64)

if not (get_track_meta() and transform_info and transform_info.get(TraceKeys.TRACING)):
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