ascend-tensor-dump · git:20260911.9f92063 · 2026-09-11 · sha256 b9477154f5872677
ascend-tensor-dump git:20260911.9f92063A
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--- name: ascend-tensor-dump description: Capture and compare bounded intermediate tensor dumps on Ascend NPU to find the first stage where numbers diverge. Use when output is wrong, non-finite, or differs between two configurations and the divergence must be localized to a stage, layer, rank, or single operator, in eager or graph mode. Do not use for performance profiling, HBM attribution, debug case bookkeeping, or before a deterministic reproduction with fixed weights and token ids exists. --- # Ascend tensor dump Find the first divergent stage using a bounded capture of a deterministic reproduction. Start with existing output evidence; add instrumentation only when it can distinguish the current hypothesis. Inputs, sampling and topology should match the comparison being made. Use `assets/dump_probe.py` in the actual managed source worktree. Prefer summary statistics, then capture selected tensors at the first suspicious stage. Retain logical shape and physical stride, storage offset and layout: summaries alone can miss aliasing or cache-index errors. Choose a stable request label and an occurrence within that label when prefill is chunked. For graph capture, use preallocated `graph_slot()` storage and graph-compatible copy nodes; read back after replay. Ordinary Python callbacks do not run during replay. Compare with the probe disabled when synchronization could alter the symptom. | Entry | Purpose | |---|---| | `scripts/dump_compare.py scan` | Inspect summaries for non-finite stages and storage aliases | | `scripts/dump_compare.py diff` | Compare corresponding summaries from two captures | | `scripts/dump_compare.py tensors` | Compare selected tensor values | | `assets/replay_op.py` | Replay a captured operator invocation against a reference | Pass actual dump artifacts directly to the relevant comparison; report tools retain evidence references internally. Missing stages are missing evidence. A passing operator replay does not establish a whole-model fix. Remove temporary instrumentation after the investigation and rerun the affected reproduction. Use graph-debug for compile/capture/replay localization and operator-debug once the failure is reduced to one operator. Contextual findings are captured through the normal task summary. - [Capture and comparison behavior](references/behavior.md) - [Probe and replay recipes](references/command-recipes.md)