multi custom kernel: support input mixed with copy and shard #13748
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geohot
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Dec 18, 2025
| devs = ("CPU:0", "CPU:1") | ||
| N = 16 | ||
| a = Tensor.randn(N, N).shard_(devs, axis=0) | ||
| b = Tensor.randn(N, N).to(devs) |
geohot
reviewed
Dec 18, 2025
| # multi supports custom kernels with CUSTOM_KERNEL + AFTER | ||
| (UPat(Ops.CUSTOM_KERNEL, src=UPat(Ops.MULTI), name="ck"), | ||
| lambda ck: ck.replace(src=tuple(m.src[0] for m in ck.src))), | ||
| (UPat(Ops.CUSTOM_KERNEL, src=UPat((Ops.MULTI, Ops.CONTIGUOUS)), name="ck"), |
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with shard None you shouldn't need this change
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shard None still have CONTIGUOUS, and this test is how we use in model training, the user code should not change?
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