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[hipDNN] Add per-operation tensor dimension ordering documentation - #4991
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Document the expected tensor dimension ordering for each operation type rather than a blanket "always NCHW" convention. Each operation family has its own dimension semantics: - Convolution: (N, C, H, W) / (K, C/groups, R, S) - BatchNorm: (N, C, H, W) with per-channel params (1, C, 1, 1) - LayerNorm: (N, ...) with feature-matching scale/bias - Matmul: (...batch, M, K) @ (...batch, K, N) - Pointwise: dimension-agnostic with NumPy broadcasting Adds Tensor Shapes sections to operation attribute Doxygen docs and a comprehensive per-operation reference in the Porting Guide. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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A handful of suggestions. No issues with the content itself though, LGTM.
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Codecov Report✅ All modified and coverable lines are covered by tests. ❌ Your project status has failed because the head coverage (76.83%) is below the target coverage (80.00%). You can increase the head coverage or adjust the target coverage. Additional details and impacted files@@ Coverage Diff @@
## develop #4991 +/- ##
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+ Coverage 66.12% 66.26% +0.14%
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Files 1734 1741 +7
Lines 269102 270730 +1628
Branches 37402 37606 +204
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+ Hits 177934 179383 +1449
- Misses 75535 75645 +110
- Partials 15633 15702 +69
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Apply doc/comment wording improvements from CMiservaAMD and SamuelReeder: - Add stride order values and per-dim stride labels to TensorLayout examples - Expand PortingGuide stride order explanation with NCHW/NDHWC examples - Replace graph.tensor() with direct TensorAttributes construction in examples - Generalize LayerNorm scale/bias shape description for n-dimensional inputs - Clarify "dimension order in the tensor shape vector" wording in TensorAttributes - Add NHWC example alongside existing NCHW example in TensorAttributes - Minor "4D tensors / 5D tensors" wording fix in ShapeUtilities Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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…OCm#4991) ## Motivation Document the expected tensor dimension ordering for each operation type rather than a blanket "always NCHW" convention. Each operation family has its own dimension semantics: - Convolution: (N, C, H, W) / (K, C/groups, R, S) - BatchNorm: (N, C, H, W) with per-channel params (1, C, 1, 1) - LayerNorm: (N, ...) with feature-matching scale/bias - Matmul: (...batch, M, K) @ (...batch, K, N) - Pointwise: dimension-agnostic with NumPy broadcasting Adds Tensor Shapes sections to operation attribute Doxygen docs and a comprehensive per-operation reference in the Porting Guide. ## Technical Details Docs only --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
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Temporary: update TheRock ref to refs/pull/4991/head to test tensilelite artifact install end-to-end. Revert to pinned hash before merging.
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Motivation
Document the expected tensor dimension ordering for each operation type rather than a blanket "always NCHW" convention. Each operation family has its own dimension semantics:
Adds Tensor Shapes sections to operation attribute Doxygen docs and a comprehensive per-operation reference in the Porting Guide.
Technical Details
Docs only