perf: reduce compile and IO overhead - #12
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- Make ACCUM_STEPS configurable via ANE_ACCUM_STEPS env var (default 10) Higher values = fewer exec() restarts, better effective throughput - Make MAX_COMPILES configurable via ANE_MAX_COMPILES env var (default 100) Allows tuning for different hardware/OS versions - IOSurface pooling: reuse freed surfaces by size instead of creating new Avoids repeated IOSurfaceCreate/CFRelease on every recompile cycle Pool capacity: 128 surfaces with swap-remove for O(n) lookup
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…uristics ane_mil.parse() extracts funcs (signature inputs/outputs) and statements (op, args, attrs, output dtype/shape) via balanced bracket matching; ane_mil.validate() checks the Orion catalog precisely — banned ops (concat/gelu) by op-name, conv bias=, matmul transpose-const (maderix#12), 32K-channel conv (maderix#16), output liveness (maderix#14), multi-output uniform (#2) + alphabetical binding (maderix#3), multi-input alphabetical (maderix#19). ane_lint.lint_mil uses the parser as primary and falls back to the regex checks when a program won't parse; size checks (maderix#4 min / maderix#18 input-uniform) and perf advisories always run. End-to-end via /raw/lint (func-wrapped gelu -> ANE010, relu -> ok). 71 tests (9 new parser tests). Co-Authored-By: Claude <noreply@anthropic.com>
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maderix#9 GraphDescriptor: operation entries now include op.args (graph dependencies). Constants use their BLOBFILE/file attr as digest instead of placeholder "const". maderix#10 IR pipeline: rejects unparseable MIL at the tensor-IR level (rejected_at_tensor_ir) before reaching ANE-IR lint — previously reported "validated" for meaningless input. maderix#11 ExecutionPlan + PlanSegment: frozen=True (immutable as documented). __post_init__ uses object.__setattr__ for the auto-generated id. maderix#12 Communication: recv() now verifies consumer_exec_id + checksum before returning data. maderix#13 Transforms: docstring honestly states these are VariantIntents (metadata), not transformed graphs — quantize() labels int8, doesn't produce int8 MIL. maderix#14 Autotuner: select_and_benchmark now passes weights to bridge.bench (previously discarded). Evidence keyed by real mil-hash fingerprint + shape, not "auto"/"default". All-failed case returns best_variant=None instead of picking an infinite-latency variant. bridge.bench now accepts a weights param (for constant-weight autotuning). 138 tests. Co-Authored-By: Claude <noreply@anthropic.com>
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Reduce compile and IO overhead in the training loop.
Changes:
Both make train and make train_large compile cleanly on macOS.