92 lines
3.3 KiB
Python
92 lines
3.3 KiB
Python
"""T0: the driven-loop contract, with a fake loop (no torch, no weights)."""
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from fastvideo2.loop import Done, LoopRunner, LoopState, WorkPlan
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class FakeLoop:
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"""Minimal conforming loop: n steps, each step doubles a counter."""
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semantics = "fake.loop/v1"
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def __init__(self, *, loop_id: str, n: int = 3):
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self.loop_id = loop_id
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self.n = n
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def init(self, request, instance, inputs):
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st = LoopState(loop_id=self.loop_id, request_id=getattr(request, "request_id", "r"))
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st.latents = 1
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st.scratch["executed"] = 0
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st.scratch["inputs"] = dict(inputs)
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return st
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def next(self, st):
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if st.step_idx >= self.n:
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return Done()
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def run():
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st.scratch["executed"] += 1
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return {"latents": st.latents * 2}
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return WorkPlan(label=f"{self.loop_id}.{st.step_idx}", step=st.step_idx, run=run)
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def advance(self, st, result):
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st.latents = result["latents"]
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st.step_idx += 1
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return st
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def finalize(self, st):
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return {"latents": st.latents, "executed": st.scratch["executed"],
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"inputs": st.scratch["inputs"]}
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class _Req:
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request_id = "req-loop"
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def test_next_is_kernel_free():
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loop = FakeLoop(loop_id="fake")
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st = loop.init(_Req(), None, {})
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loop.next(st)
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loop.next(st) # planning twice runs nothing
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assert st.scratch["executed"] == 0
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def test_runner_drives_to_completion_and_observes():
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seen = []
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loop = FakeLoop(loop_id="fake", n=4)
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runner = LoopRunner(loop, _Req(), None, {"x": 9},
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observe=lambda label, sec, meta: seen.append(label))
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out = runner.run()
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assert out["latents"] == 16 and out["executed"] == 4
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assert out["inputs"] == {"x": 9}
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assert seen == [f"fake.{i}" for i in range(4)]
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assert runner.done
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def test_build_loop_from_spec():
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from fastvideo2.card import LoopSpec
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from fastvideo2.loop import build_loop
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loop = build_loop(LoopSpec("fake", loop="fastvideo2.tests.test_loop:FakeLoop",
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params={"n": 2}))
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assert isinstance(loop, FakeLoop) and loop.n == 2 and loop.loop_id == "fake"
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def test_dmd_inference_table_matches_fastvideo_main_runtime():
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# CANARY: main's DmdDenoisingStage hardcodes an internal
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# FlowMatchEulerDiscreteScheduler(shift=8.0) — the pipeline scheduler that
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# TimestepPreparationStage ran set_timesteps() on is NEVER consulted. So
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# sigma lookups hit the 1000-entry warped INIT table, whose timesteps are
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# the warped sigmas x1000: sigma(757) ~= 0.757 nearly independent of
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# shift, and 757/522 resolve to DISTINCT sigmas. Wiring these lookups to
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# a set_timesteps(n) table instead breaks bit-parity with fastvideo-main.
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from fastvideo2.wan21.loop import dmd_inference_table, dmd_sigma_for
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ts, sg = dmd_inference_table(8.0)
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assert len(ts) == 1000 and sg[0] == 1.0 and ts[0] == 1000.0
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for t in (1000, 757, 522):
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assert abs(dmd_sigma_for(t, ts, sg) - t / 1000.0) < 2e-3
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assert dmd_sigma_for(757, ts, sg) != dmd_sigma_for(522, ts, sg)
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def test_dmd_loop_semantics_id_is_distinct():
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from fastvideo2.wan21.loop import WanDenoiseLoop, WanDMDLoop
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assert WanDMDLoop.semantics == "wan.dmd.fvmain/v1"
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assert WanDMDLoop.semantics != WanDenoiseLoop.semantics # the card teeth
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