SolitaryThinker
2f044c02dd
Add v2/platform/: the (recipe, runtime) backend membrane that lets CPU, GPU, and other devices coexist behind one dispatch substrate. - Two tuple-keyed registries: COMPONENTS(kind, device, variant) for weight-bearing components and KERNELS(op, device, arch, variant) for stateless primitives, each with an availability predicate and an enumerable manifest (declared-but-unavailable cells listed without importing torch). - Platform: detected (device, arch) owning the device + arch fallback chains and a per-platform cached KernelTable; detect() is honest (CPU/numpy unless torch+CUDA are actually present). Arch fallback is monotonic — only degrades to older/portable archs, never a newer binary-incompatible one. - Seams wired: ModelInstance.component() -> platform.build_component(spec,self) with spec.factory as the numpy terminal rung (existing cards untouched); the wan21 denoise thunk dispatches solver ops through model.platform.kernels. - Three backends: cpu (numpy terminal + parity oracle), accel (pure-python stand-in proving cross-device resolution, arch fallback, and the oracle), torch_cuda (declared-but-unavailable; no faked GPU). - test_platform.py: 16 tests — detection, terminal rung, arch-fallback walk + monotonicity, device precedence, variant fallback, component override + per-kind device fallback, the parity oracle (accel == cpu, bit_identical via the C1 ladder), and matrix enumeration without importing torch. Scope is honestly bounded in the README/docstrings: only wan21-denoise routes through the kernel table and only the dit kind is overridden today (each a one-line adoption); the torch/CUDA path and a cudagraph workspace-safety contract are declared/deferred, not implemented. 183 tests pass.
9 lines
557 B
Python
9 lines
557 B
Python
"""Backend registration modules. Imported for side effects by ``Platform.ensure_backends_loaded``.
|
|
|
|
Each module calls ``register_component`` / ``register_kernel`` at import time. They live behind the
|
|
lazy loader (not imported by ``platform/__init__`` or ``card/``) so the registry stays a pure leaf
|
|
and there are no import cycles. On disk these mirror the kernel-colocation answer: ``cpu`` is the
|
|
unified numpy reference; a real ``torch_cuda`` backend would register both unified primitives and
|
|
model-co-located fusion *variants* through this same API.
|
|
"""
|