[ { "api_error_status": null, "duration_api_ms": 45902, "duration_ms": 45956, "fast_mode_disabled_reason": "sdk_opt_in_required", "fast_mode_state": "off", "first_content_frame_ms": 1525, "is_error": false, "modelUsage": { "claude-opus-5": { "cacheCreationInputTokens": 4740, "cacheReadInputTokens": 0, "canonicalModel": "claude-opus-5", "contextWindow": 1000000, "costBasis": "list", "costUSD": 0.13253500000000001, "inputTokens": 2, "maxOutputTokens": 64000, "outputTokens": 3405, "provider": "firstParty", "thinkingTokens": 618, "webSearchRequests": 0 } }, "num_turns": 1, "permission_denials": [], "queued_turn_count": 0, "result": "## Preconditions\n\n1. Every emitted program is a single MLIR `module { ... }` containing only `dataflow.graph` definitions at the top level and nothing else.\n2. Each graph is declared as `dataflow.graph private @graph_` with an empty result list `-> ()`, so no graph returns values.\n3. Every graph's entry block takes a `none`-typed token operand named `%start` as its first parameter, and the graph body is terminated by `dataflow.graph.return %start : none`, i.e. the incoming token is threaded straight to the terminator.\n4. Each graph carries both a `input_segments` and a `result_segments` `array` attribute whose entries sum consistently with the declared operands and results (five non-token scalar/vector inputs, zero of the middle class, two memref inputs; zero results of every class).\n5. Memref-typed graph parameters are plain statically shaped `memref<16xi32>` capability inputs supplied by the graph signature; the body never allocates, declares, or otherwise materializes memory (`memref.alloca`, `memref.get_global`, globals, pointers, `unrealized_conversion_cast` are all absent).\n6. Every memory operation in a body addresses one of the graph's own memref parameters by name; there are no cross-graph or externally defined memory references.\n7. Vector memory traffic occurs only as a matched pair: a `vector.transfer_read` producing a value that is immediately consumed as the value operand of a following `vector.transfer_write`; a read never appears without its dependent write and the write's data operand is never an unrelated SSA value.\n8. Every `vector.transfer_read`/`vector.transfer_write` is rank-one, uses the single index operand `%i`, carries `{in_bounds = [true]}`, and transfers exactly `vector<4xi32>` to/from `memref<16xi32>` \u2014 no transposing permutation maps, no multi-dimensional indices, no out-of-bounds transfers.\n9. A `vector.transfer_read` supplies a scalar padding operand (`%pad`) of the memref element type, and the padding value is available in the graph before any transfer that uses it.\n10. Masking on a transfer pair is all-or-nothing: either both the read and the write carry the `vector<4xi1>` mask operand `%m`, or neither does; a mixed masked-read/unmasked-write pair never occurs.\n11. The mask operand's vector length matches the transfer vector length (4 lanes), and the mask is a graph parameter, not a locally computed value.\n12. Scalar memory traffic likewise occurs only as a store followed by a load, both normalized to the same single index `%i` on the same memref and with element type `i32`; the stored value is the graph's `%val` parameter.\n13. Gather/scatter traffic is expressed exclusively through `dataflow.load` / `dataflow.store` actors, each taking a `vector<4xindex>` address vector, the `%start` token, and a `mask %m` operand; the gathered result is the value operand of the paired scatter, making the scatter data-dependent on the load.\n14. `dataflow.load` yields two results (a data vector and a dependency/token result) and `dataflow.store` yields one result, and these results are bound to distinct SSA names.\n15. Nesting of memory leaves is permitted only inside `scf.if` and `scf.for`; no `scf.parallel`, `scf.forall`, `scf.while`, or LLVM-dialect memory operation appears anywhere.\n16. `scf.if` regions used here are value-free: the condition is an `i1` graph parameter, there is no `else` region, and no results are yielded.\n17. `scf.for` loops are value-free as well: no `iter_args`, no yielded results, and lower bound, upper bound, and step are `index`-typed SSA values defined by constants dominating the loop in the same block.\n18. All SSA names defined within a graph body are unique, and every use of a value is dominated by its definition (constants for a loop precede that loop, a transfer read precedes its write, a store precedes the matching load, a gather precedes its scatter).\n19. Each graph body contains at least one vector-addressed memory access (a transfer pair, a `dataflow.load`/`store` pair, or one of these nested in a region), so no graph is free of the governed construct.\n\n## Sampling conventions\n\n1. The module holds either one or two graphs, never zero and never more than two.\n2. Graphs are named by position, `@graph_0` and `@graph_1`, using a counter that starts at zero and increments per graph.\n3. Every graph uses one fixed, identical signature \u2014 `%start: none, %i: index, %c: i1, %m: vector<4xi1>, %av: vector<4xindex>, %val: i32, %a: memref<16xi32>, %b: memref<16xi32>` \u2014 rather than varying arity, types, or parameter order.\n4. The attribute preamble is a constant: `input_segments = array` and `result_segments = array` on every graph.\n5. Each body opens with a fixed constant preamble `%pad = arith.constant 0 : i32`, so the transfer padding value is always the integer zero and is emitted even when no unmasked/masked read follows.\n6. Exactly one leading statement is emitted, chosen from transfer pair, gather/scatter pair, `scf.if`, or `scf.for` \u2014 the scalar store/load pair is deliberately never chosen as the leading statement.\n7. After the leading statement, between zero and four further statements are emitted, each chosen freely from transfer pair, gather/scatter pair, scalar pair, `scf.if`, or `scf.for`; the maximum body length is therefore five statements plus the constant preamble and terminator.\n8. Memref element type and shape are fixed at `memref<16xi32>`, and the vector shape is fixed at four lanes (`vector<4xi32>`, `vector<4xi1>`, `vector<4xindex>`); no other widths, ranks, or element types are sampled.\n9. All memory accesses use the single graph parameter `%i` as the (only) index, even inside `scf.for`, whose induction variable is never used as an address.\n10. Masking of a transfer pair is sampled as a binary choice per pair; both the fully masked and fully unmasked forms are produced, and the mask, when present, is always the parameter `%m` rather than a constructed mask.\n11. The source and destination memrefs of a transfer pair are independently chosen from `{%a, %b}`, so read-and-write-to-the-same-memref pairs as well as `%a`\u2192`%b` and `%b`\u2192`%a` pairs all occur.\n12. The scalar pair chooses one memref from `{%a, %b}` and uses it for both the store and the load, never crossing between the two.\n13. The gather/scatter pair is fixed in its operands: it always loads from `%a` and stores to `%b`, always uses the address vector `%av`, and is always masked with `%m` \u2014 unmasked or `%b`\u2192`%a` gather/scatter forms are never emitted.\n14. A single per-graph counter supplies the numeric suffix for every named entity (`%v`, `%s`, `%g`/`%gd`/`%sc`, `%lb`/`%ub`/`%sp`/`%k`), incrementing once per statement or nested pair, which guarantees unique names without reusing a per-kind counter.\n15. `scf.if` regions contain exactly one transfer pair and nothing else, and the condition is always the parameter `%c`; scalar pairs, gather pairs, and further nesting never appear inside an `if`.\n16. `scf.for` bodies likewise contain exactly one transfer pair and nothing else, so nesting depth never exceeds one region inside a graph body.\n17. Loop trip counts are fixed by a constant triple emitted immediately before each loop \u2014 lower bound `0`, upper bound `4`, step `1` \u2014 matching the vector lane count and keeping loops finite.\n18. The loop induction variable `%k` is bound but unused in the loop body, exercising the loop-nesting shape without introducing loop-varying addresses.\n19. 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