SolitaryThinker
a9e5f6ee7a
Directory rename (git mv, history preserved) plus rewrite of all references: absolute imports in tests, the zero-dep runner, docstrings, comments, and the README. No behavior change. Run: python3 -m pytest v2/tests/ -q ; python3 v2/run_tests.py ; python3 -m v2.examples
77 lines
3.4 KiB
Python
77 lines
3.4 KiB
Python
"""RuntimeLoopContext — the concrete inversion point (design_v3 §5.1, §11).
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This is the single seam: ``execute(plan)`` runs the kernel thunk built by the model's
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``next()``, wrapped by interceptors (compute-altering) and observers (read-only). The model
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never sees the scheduler; the scheduler never sees the model's math. Per-request loop state
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is bound here so interceptors read state from ``LoopState`` (never module globals).
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"""
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from __future__ import annotations
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from time import perf_counter
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from typing import Any
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from .._enums import ExecutionProfile
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from ..loop.contracts import StepResult, WorkPlan
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from ..request.streams import OmniEvent, Stream, StreamChunk
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class RuntimeLoopContext:
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def __init__(self, instance: Any, *, observers, interceptors, slots: dict[str, Any],
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stream: Stream, cancel_scope, profile: ExecutionProfile, metrics: dict,
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request_id: str):
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self.instance = instance
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self.observers = observers
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self.interceptors = interceptors
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self.slots = slots # the program's typed named edges
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self.stream = stream
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self.cancel_scope = cancel_scope
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self.profile = profile
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self.metrics = metrics
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self.request_id = request_id
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self.state = None # bound per step by the LoopRunner
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def bind_state(self, state) -> None:
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self.state = state
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def execute(self, plan: WorkPlan) -> StepResult:
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self.observers.emit("step_start", plan=plan)
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# Interceptors may supply an override for the *expensive forward* (e.g. a cached
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# prediction). The step body still runs the cheap scheduler step (combine + solver),
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# so the override changes compute, not the loop's state-transition shape.
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override = None
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if self.interceptors.active and self.state is not None:
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override = self.interceptors.before(plan, self.state)
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# only count a skip the step body will actually honor (must carry a forward result)
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if override is not None and "noise_pred" in override:
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self.metrics["skipped_steps"] = self.metrics.get("skipped_steps", 0) + 1
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t0 = perf_counter()
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out = plan.run(self.instance, override) if plan.run is not None else {}
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dt = perf_counter() - t0
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if isinstance(out, StepResult):
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result = out
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if result.actual_seconds == 0.0:
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result.actual_seconds = dt
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else:
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result = StepResult(output=dict(out), actual_seconds=dt)
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if self.interceptors.active and self.state is not None:
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self.interceptors.after(plan, self.state, result)
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self.observers.emit("step_complete", plan=plan, result=result)
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self.metrics["steps"] = self.metrics.get("steps", 0) + 1
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self.metrics["gpu_seconds"] = self.metrics.get("gpu_seconds", 0.0) + result.actual_seconds
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return result
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def emit(self, chunk: StreamChunk) -> None:
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self.stream.emit(OmniEvent(type="media.chunk", request_id=self.request_id,
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seq=chunk.seq, payload={"chunk": chunk}))
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self.metrics["stream_chunks"] = self.metrics.get("stream_chunks", 0) + 1
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def check_cancel(self) -> None:
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if self.cancel_scope is not None:
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self.cancel_scope.check() # raises request.Cancelled at the step boundary
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def observe(self, event: str, **kw) -> None:
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self.observers.emit(event, **kw)
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