Will Lin
1fe50c0092
The v2 top level had grown to ~27 dirs + 13 loose files — half of them
single-concept abstraction shells (memory/ 86 LOC, transport/ 222, parity/ 178,
extend/ 226) and half vendored fastvideo code sitting as peers to the actual v2
design. Regroup to mirror README section 3 "Planes & dependency order":
core/ enums+types, card, loop, program, parity, request, parallel
(the model-native contracts; no kernels)
runtime/ + folded-in substrate: cache, memory, transport, extend
(the import graph shows only runtime consumes them; compile/cudagraph
already lived here)
serving/ + deploy/ (products / fleet)
_vendor/ all copied fastvideo: models, layers, attention, configs, distributed,
platforms, api, hooks, logging_utils, third_party + fastvideo_args/
utils/logger/envs/forward_context — internal layout unchanged, still
mirrors upstream for diffing
28 dirs + 13 root files -> 8 dirs + 6 root files. Pure mechanical move: 947
absolute-import paths rewritten (v2.X -> v2.{core,runtime,serving,_vendor}.X),
boundary-anchored so platform/ (native dispatch) and platforms/ (vendored CUDA
detect) no longer collide and neither does hooks/ vs extend/. Deleted the empty
v2/loader/. README section 3 + 16 updated; stale test count corrected
(34 files/216 tests -> 22 files/143 tests).
Validated: `import v2` stays torch-free; `v2/run_tests.py` and `pytest v2/tests/`
-> 143 passed, 2 skipped on the numpy toy backend. (On a GPU box force the toy
backend with CUDA_VISIBLE_DEVICES="" or detect() picks cuda.) No external importer
changed — examples use the re-exported `from v2 import VideoGenerator`.
29 lines
1.4 KiB
Python
29 lines
1.4 KiB
Python
"""CPU / numpy backend — the terminal rung and parity oracle.
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This backend registers the numpy reference kernels. It is the bottom of every device fallback
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chain: any op a richer backend hasn't implemented resolves here, and every other backend's output
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is checked against this one (the consistency ladder's C0/C1 oracle).
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Components are NOT registered here: the card's ``ComponentSpec.factory`` *is* the cpu/numpy
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component rung (``Platform.build_component`` falls back to it when no ``(kind, device, …)`` cell
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matches). That keeps every existing card working with zero registration.
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"""
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from __future__ import annotations
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from v2.core.loop.sampler import flow_match_euler_step, flow_sde_step_with_logprob
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from v2.platform.registry import FLOW_MATCH_STEP, FLOW_SDE_STEP, register_kernel
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# The numpy solver primitives, registered as the terminal (cpu, numpy) kernels. These are the exact
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# same functions the loops used to call directly — so dispatching through the registry on a CPU box
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# is bit-for-bit identical to the pre-registry behavior.
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register_kernel(FLOW_MATCH_STEP,
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flow_match_euler_step,
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device="cpu",
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arch="numpy",
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source="loop.sampler:flow_match_euler_step")
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register_kernel(FLOW_SDE_STEP,
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flow_sde_step_with_logprob,
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device="cpu",
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arch="numpy",
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source="loop.sampler:flow_sde_step_with_logprob")
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