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[Kernels] Add fp8 support to reshape_and_cache_flash
#6667
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lgtm -- looks straightforward, following along with reshape_and_cache_kernel
is doing.
Hey @Yard1 thanks for sharing - I was working on enabling fp8 for flashinfer in a similar fashion. However I put a pause on the integration to better understand why the performance didn't match expectations. Please check out this sheet of benchmarks. I took the benchmarking configuration directly from the FP8 section of their launch blog. Do you have an idea of why the A100 performance seems so bad in my benchmark? |
@mgoin I hadn't looked into that myself yet. Have you tried asking the flashinfer author in flashinfer repo? |
reshape_and_cache_flash
reshape_and_cache_flash
@@ -507,7 +506,13 @@ def create_kv_caches_with_random_flash( | |||
key_value_cache = torch.empty(size=key_value_cache_shape, | |||
dtype=torch_dtype, | |||
device=device) | |||
key_value_cache.uniform_(-scale, scale) | |||
if cache_dtype in ["auto", "half", "bfloat16", "float"]: |
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is there no case "auto" becomes fp8?
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besides, handling auto here is a little ugly.. (feel like the caller should convert it alrady) but don't need to handle it here
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I am just following the pattern laid out in the non-flash function
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"auto" now means following the model weights/checkpoints. We should definitely improve the logic in the future.
Signed-off-by: Alvant <[email protected]>
Preparation for fp8 support in flash attn-based backends.
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