Add validated A5 VPTO ops#834
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SummaryReview failed at stage Findings未生成结构化 findings，因为 review 过程提前失败。 Log Tail |
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Code Review
This pull request introduces several new VPTO operations for the A5 architecture, including SPR state operations (sprclr, sprsti, sprsts), loop-indexed tail predicates (pltm_b8/16/32), fused multiply-add (vmadd), extrema predicate reductions (vcbmax, vcbmin), and histogram updates (chistv2, dhistv2). Additionally, it restricts trem and trems operations on A5 to floating-point types, removing integer support. The review feedback points out potential ValueError exceptions in the test comparison script (compare.py) when comparing arrays of mismatched shapes.
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| if not ok: | ||
| diff = np.max(np.abs(golden.astype(np.float64) - output.astype(np.float64))) | ||
| print(f"[ERROR] compare failed: {label}, max_abs_diff={diff}") |
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If golden.shape != output.shape, ok will be False. In the error reporting block, evaluating golden.astype(np.float64) - output.astype(np.float64) will raise a ValueError due to shape mismatch, masking the actual error. We should check if the shapes match before performing element-wise operations.
Suggested change
| if not ok: | |
| diff = np.max(np.abs(golden.astype(np.float64) - output.astype(np.float64))) | |
| print(f"[ERROR] compare failed: {label}, max_abs_diff={diff}") | |
| if not ok: | |
| if golden.shape != output.shape: | |
| print(f"[ERROR] shape mismatch: golden={golden.shape}, output={output.shape}") | |
| else: | |
| diff = np.max(np.abs(golden.astype(np.float64) - output.astype(np.float64))) | |
| print(f"[ERROR] compare failed: {label}, max_abs_diff={diff}") |
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| if not ok: | ||
| mismatch = np.flatnonzero(golden != output) | ||
| first = int(mismatch[0]) if mismatch.size else -1 | ||
| print( | ||
| f"[ERROR] compare failed: {label}, first_mismatch={first}, " | ||
| f"golden={golden[first] if first >= 0 else 'n/a'}, " | ||
| f"output={output[first] if first >= 0 else 'n/a'}" | ||
| ) |
There was a problem hiding this comment.
If golden.shape != output.shape, ok will be False. In the error reporting block, evaluating golden != output will raise a ValueError due to shape mismatch, masking the actual error. We should check if the shapes match before performing element-wise operations.
Suggested change
| if not ok: | |
| mismatch = np.flatnonzero(golden != output) | |
| first = int(mismatch[0]) if mismatch.size else -1 | |
| print( | |
| f"[ERROR] compare failed: {label}, first_mismatch={first}, " | |
| f"golden={golden[first] if first >= 0 else 'n/a'}, " | |
| f"output={output[first] if first >= 0 else 'n/a'}" | |
| ) | |
| if not ok: | |
| if golden.shape != output.shape: | |
| print(f"[ERROR] shape mismatch: golden={golden.shape}, output={output.shape}") | |
| else: | |
| mismatch = np.flatnonzero(golden != output) | |
| first = int(mismatch[0]) if mismatch.size else -1 | |
| print( | |
| f"[ERROR] compare failed: {label}, first_mismatch={first}, " | |
| f"golden={golden[first] if first >= 0 else 'n/a'}, " | |
| f"output={output[first] if first >= 0 else 'n/a'}" | |
| ) |
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Summary
Validation