Add exportGraphToDot diagnostic utility#388
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arkavo-com wants to merge 1 commit intoml-explore:mainfrom
Open
Add exportGraphToDot diagnostic utility#388arkavo-com wants to merge 1 commit intoml-explore:mainfrom
arkavo-com wants to merge 1 commit intoml-explore:mainfrom
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Exposes the C++ export_to_dot function via a Swift-friendly API. Essential for diagnosing dtype contamination and graph topology differences between Swift and Python. Usage: let logits = model(input, cache: cache) exportGraphToDot(path: "/tmp/graph.dot", output: logits) // Then: grep -c 'label ="AsType"' /tmp/graph.dot // Non-zero AsType count indicates dtype mismatches This was critical for discovering that Swift MLX models can silently inject 1000+ AsType nodes from float32 literal defaults, causing 100x Metal cache churn vs Python. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
davidkoski
reviewed
Apr 6, 2026
| const mlx_imported_function xfunc, | ||
| const mlx_vector_array args, | ||
| const mlx_map_string_to_array kwargs); | ||
| int mlx_export_to_dot_file(const char* path, mlx_array output); |
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We need this change on the mlx-c side. I suspect you made changes locally to that. it is a good idea, I will talk to Ronan.
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Summary
Exposes the existing C++
export_to_dotgraph visualization function through a Swift API.Why this matters
This utility was essential for discovering a critical performance issue where Swift MLX models silently inject
AsType(type cast) nodes from float32 literal defaults. By diffing the DOT graph between Python and Swift, we found:MLXArray.ones()defaulting to float32)The 1046 extra AsType nodes caused 237 MB of Metal cache churn per token (vs Python's 2.3 MB) and a 12% generation speed regression.
Without this diagnostic, the root cause would have been invisible — the model produced correct output and all individual operation tests showed perfect buffer donation.
Test plan
🤖 Generated with Claude Code