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feat(v4/spec): VBSpec Stage E — verify_and_estimate + suggest_adapters + GUI workflow
Adds cppmega_v4.spec.api — the GUI-facing public surface that wires Stages A-D into the three operations the visual builder cares about (VisualBuilderSpec.md §3.5, §6 E). - suggest_dim_env(preset_name=None) → dict[str,int] Sensible production-scale named-dim env per preset (B=1, S=4096, H=4096, nh=32, nkv=4, head_dim=128, num_experts=8, top_k=2, plus MLA LoRA / sliding / SSM / coarse-attn extras when needed). With preset_name=None, returns the generic base env. - verify_and_estimate(graph, dim_env, *, preset_name, device_hbm_bytes, headroom, training, optimizer, dtype_bytes, kv_cache_dtype_bytes, available_side_channels, strict) → VerificationResult One-shot: resolve_shapes → plan_fusion_regions → estimate_memory. Carries resolved graph, fusion plan, memory report, elapsed_ms, and optional fits_on_device gate. .summary() returns a JSON-friendly dict the GUI can render directly. - suggest_adapters(resolved, producer, consumer, *, max_steps) → AdapterProposal. Looks up the resolved edge and asks the Stage C adapter library for a chain that closes the mismatch. Tests (tests/v4/test_vbspec_stage_e.py, 38 cases): - suggest_dim_env: independent-copy invariant, base-key coverage, per-preset coverage (12), unknown-preset error, MLA extras included - verify_and_estimate: well-formed result; explicit env overrides preset; device gate populates fits_on_device; default no-device = None; summary dict shape; strict mode re-raises - suggest_adapters: unknown-edge KeyError; matched edge = empty chain + "no adapter needed" reason; synthetic mismatch → chain proposed, accept-and-splice removes the original mismatched edge - PERF GATE: every preset (12) completes verify_and_estimate in <100 ms warm (soft cap; target 50 ms — current runs ~3 ms) - SYSTEM: full GUI workflow integration (drop brick with mismatch → red edge → suggest → accept → re-verify → original edge gone) Full v4 regression: 769 passed / 5 skipped / 0 failed. Closes VBSpec roadmap (Stages A-E from VisualBuilderSpec.md).
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cppmega_v4/spec/__init__.py

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insert_adapter_chain,
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suggest_adapter_chain,
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)
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from cppmega_v4.spec.api import (
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AdapterProposal,
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VerificationResult,
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suggest_adapters,
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suggest_dim_env,
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verify_and_estimate,
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)
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from cppmega_v4.spec.memory_report import (
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BrickMemoryRow,
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MemoryReport,
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__all__ = [
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"ADAPTER_RULES",
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"AdapterProposal",
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"AdapterRule",
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"AdapterSuggestion",
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"BrickMemoryRow",
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"VerificationResult",
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"BrickShapeContract",
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"DiagnosticSeverity",
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"MemoryReport",
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"registered_kinds",
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"resolve_shapes",
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"suggest_adapter_chain",
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"suggest_adapters",
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"suggest_dim_env",
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"verify_and_estimate",
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]

cppmega_v4/spec/api.py

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"""GUI-facing public API: verify + estimate in one call, adapter
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suggestion lookup, ergonomic dim_env builders.
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This module is what the visual-builder front-end actually imports. It
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wires together Stages A-D into the three operations the GUI cares about:
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- :func:`verify_and_estimate` — on every graph mutation, return both
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the diagnostics list (red/yellow/green per edge) and the memory
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report (bar at the top: ``18.2 / 80 GB``).
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- :func:`suggest_adapters` — when the user hovers a red edge, propose
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the adapter chain that would close it.
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- :func:`suggest_dim_env` — sensible default named-dim env for a given
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preset name, so the GUI doesn't have to ship a full editor before
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the first verify lands.
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Designed to run in <50 ms per call for any of the 12 architecture
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presets at production-scale dim envs (B=1, S=4096, H=4096) — the
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GUI workflow test in tests/v4/test_vbspec_stage_e.py enforces this.
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"""
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from __future__ import annotations
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import time
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from collections.abc import Mapping, Sequence
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from dataclasses import dataclass, field
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from typing import Any
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from cppmega_v4.fusion import FusionRegionPlan, plan_fusion_regions
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from cppmega_v4.fusion.brick_graph import BrickGraph, BrickNode
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from cppmega_v4.spec.adapters import (
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AdapterSuggestion,
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suggest_adapter_chain,
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)
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from cppmega_v4.spec.memory_report import (
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MemoryReport,
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estimate_memory,
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)
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from cppmega_v4.spec.resolver import (
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ResolvedBrickGraph,
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resolve_shapes,
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)
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# ---------------------------------------------------------------------------
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# Default named-dim envs per preset
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# ---------------------------------------------------------------------------
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# Production-scale defaults. The GUI ships these so a fresh-open model
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# already has a sensible env without the user touching dim sliders.
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# Override by passing your own ``dim_env`` to verify_and_estimate.
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_PROD_BASE: Mapping[str, int] = {
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"B": 1, "S": 4096, "H": 4096,
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"nh": 32, "nkv": 4, "head_dim": 128,
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"num_experts": 8, "top_k": 2,
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}
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_PROD_MLA_EXTRAS: Mapping[str, int] = {
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"q_lora_rank": 1536, "kv_lora_rank": 512,
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"qk_rope_head_dim": 64, "qk_nope_head_dim": 128, "v_head_dim": 128,
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}
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_PROD_GEMMA_EXTRAS = {"sliding_window_size": 1024}
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_PROD_NEMOTRON_EXTRAS = {"d_state": 64}
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_PROD_ZAYA_EXTRAS = {"fine_window": 256, "coarse_block_size": 16}
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_PRESET_DIM_ENVS: Mapping[str, Mapping[str, int]] = {
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"qwen3_next": dict(_PROD_BASE),
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"kimi_linear": {**_PROD_BASE, **_PROD_MLA_EXTRAS},
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"kimi_k2": {**_PROD_BASE, **_PROD_MLA_EXTRAS},
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"deepseek_v3": {**_PROD_BASE, **_PROD_MLA_EXTRAS},
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"deepseek_v4_flash": dict(_PROD_BASE),
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"gemma4": {**_PROD_BASE, **_PROD_GEMMA_EXTRAS},
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"mistral4": {**_PROD_BASE, **_PROD_MLA_EXTRAS},
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"ling26": {**_PROD_BASE, **_PROD_MLA_EXTRAS},
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"longcat": {**_PROD_BASE, **_PROD_MLA_EXTRAS},
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"nemotron3": {**_PROD_BASE, **_PROD_NEMOTRON_EXTRAS},
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"zaya1": {**_PROD_BASE, **_PROD_ZAYA_EXTRAS},
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"arcee_trinity": {**_PROD_BASE, **_PROD_GEMMA_EXTRAS},
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}
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def suggest_dim_env(preset_name: str | None = None) -> dict[str, int]:
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"""Return a sensible default named-dim env.
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With ``preset_name=None``, returns the generic production-scale
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base env (B=1, S=4096, H=4096, nh=32, nkv=4, head_dim=128,
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num_experts=8, top_k=2). With a preset name, returns the env that
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includes any preset-specific extra dims (MLA LoRA ranks, sliding
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window size, etc.).
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"""
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if preset_name is None:
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return dict(_PROD_BASE)
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if preset_name not in _PRESET_DIM_ENVS:
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raise KeyError(
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f"unknown preset {preset_name!r}; "
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f"available: {sorted(_PRESET_DIM_ENVS)}"
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)
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return dict(_PRESET_DIM_ENVS[preset_name])
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# ---------------------------------------------------------------------------
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# verify_and_estimate
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# ---------------------------------------------------------------------------
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_DEFAULT_SIDE_CHANNELS = frozenset({"doc_ids", "token_ids"})
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@dataclass(frozen=True)
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class VerificationResult:
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"""One-shot result of :func:`verify_and_estimate`."""
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resolved: ResolvedBrickGraph
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fusion_plan: tuple[FusionRegionPlan, ...]
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memory: MemoryReport
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elapsed_ms: float
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fits_on_device: bool | None = None
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@property
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def has_errors(self) -> bool:
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return self.resolved.has_errors
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def summary(self) -> dict[str, Any]:
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"""Compact dict the GUI can render directly."""
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return {
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"errors": len(self.resolved.errors),
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"warnings": len(self.resolved.warnings),
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"regions": len(self.fusion_plan),
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"memory": self.memory.summary(),
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"elapsed_ms": round(self.elapsed_ms, 2),
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"fits_on_device": self.fits_on_device,
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}
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def verify_and_estimate(
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graph: BrickGraph,
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dim_env: Mapping[str, int] | None = None,
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*,
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preset_name: str | None = None,
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device_hbm_bytes: int | None = None,
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headroom: float = 0.9,
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training: bool = True,
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optimizer: str = "adamw",
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dtype_bytes: int = 2,
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kv_cache_dtype_bytes: int = 1,
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available_side_channels: frozenset[str] = _DEFAULT_SIDE_CHANNELS,
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strict: bool = False,
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) -> VerificationResult:
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"""Resolve shapes, plan fusion regions, estimate memory — one shot.
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Args:
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graph: the BrickGraph to verify.
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dim_env: concrete int values per named dim. If None, falls back
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to :func:`suggest_dim_env(preset_name)`.
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preset_name: lookup key for the default dim_env if dim_env=None.
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device_hbm_bytes: when supplied, the result includes
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``fits_on_device`` (Memory.fits_on(device, headroom)).
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headroom: HBM headroom fraction for fits_on (default 0.9).
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training: forwarded to estimate_memory.
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optimizer, dtype_bytes, kv_cache_dtype_bytes: forwarded.
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available_side_channels: forwarded to resolve_shapes; defaults to
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``{"doc_ids", "token_ids"}`` (the most common case for our bricks).
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strict: when True, resolver raises on first ERROR instead of
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collecting diagnostics.
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"""
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if dim_env is None:
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dim_env = suggest_dim_env(preset_name)
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t0 = time.perf_counter()
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resolved = resolve_shapes(
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graph, dim_env,
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strict=strict,
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available_side_channels=available_side_channels,
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)
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plans = tuple(plan_fusion_regions(graph))
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memory = estimate_memory(
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resolved,
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fusion_plan=plans,
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training=training,
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optimizer=optimizer,
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dtype_bytes=dtype_bytes,
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kv_cache_dtype_bytes=kv_cache_dtype_bytes,
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)
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elapsed_ms = (time.perf_counter() - t0) * 1000.0
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fits = (
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memory.fits_on(device_hbm_bytes, headroom=headroom)
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if device_hbm_bytes is not None else None
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)
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return VerificationResult(
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resolved=resolved,
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fusion_plan=plans,
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memory=memory,
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elapsed_ms=elapsed_ms,
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fits_on_device=fits,
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)
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# ---------------------------------------------------------------------------
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# suggest_adapters
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# ---------------------------------------------------------------------------
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@dataclass(frozen=True)
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class AdapterProposal:
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"""Bundle returned by :func:`suggest_adapters`.
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Fields:
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producer / consumer: the names of the edge endpoints.
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producer_shape / consumer_shape: resolved shapes on the edge.
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chain: ordered list of AdapterSuggestion steps; empty when shapes
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already match; None when no chain ≤ max_steps exists.
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reason: human-readable explanation for the GUI tooltip.
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"""
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producer: str
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consumer: str
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producer_shape: tuple[int, ...]
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consumer_shape: tuple[int, ...]
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chain: list[AdapterSuggestion] | None
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reason: str
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def suggest_adapters(
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resolved: ResolvedBrickGraph,
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producer: str,
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consumer: str,
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*,
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max_steps: int = 4,
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) -> AdapterProposal:
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"""Look up the resolved edge ``producer -> consumer`` and produce
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an :class:`AdapterProposal`. Raises KeyError if no such edge."""
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edge = resolved.edge(producer, consumer)
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chain = suggest_adapter_chain(
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edge.producer_shape, edge.consumer_shape, max_steps=max_steps,
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)
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if edge.matched:
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reason = "shapes already match — no adapter needed"
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elif chain is None:
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reason = (
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f"no adapter chain (≤ {max_steps} hops) bridges "
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f"{edge.producer_shape} -> {edge.consumer_shape}"
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)
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elif not chain:
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reason = "shapes match by value but resolver disagreed — no adapter needed"
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else:
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reason = f"chain of {len(chain)} adapter step(s): " + " -> ".join(
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s.kind for s in chain
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)
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return AdapterProposal(
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producer=producer,
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consumer=consumer,
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producer_shape=edge.producer_shape,
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consumer_shape=edge.consumer_shape,
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chain=chain,
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reason=reason,
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)
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__all__ = [
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"AdapterProposal",
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"VerificationResult",
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"suggest_adapters",
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"suggest_dim_env",
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"verify_and_estimate",
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]

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