36 lines
1.3 KiB
Plaintext
36 lines
1.3 KiB
Plaintext
/*
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* Copyright (c) 2024 by FlashInfer team.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "pytorch_extension_utils.h"
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void xqa_wrapper(int64_t multiProcessorCount, int64_t nbKHeads, int64_t slidingWinSize,
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double qScale, at::Tensor output,
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#if LOW_PREC_OUTPUT
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at::Tensor rcpOutScale,
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#endif
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at::Tensor q, at::Tensor attentionSinks, at::Tensor pool,
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at::Tensor kvCachePageList, int64_t maxSeqLen, at::Tensor seqLen,
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int64_t batchSize, at::Tensor kvCacheScale,
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#if SPEC_DEC
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int64_t qSeqLen, at::Tensor qCuSeqLens, at::Tensor mask,
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#endif
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at::Tensor semaphores, at::Tensor scratch);
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TORCH_LIBRARY_FRAGMENT(TORCH_EXTENSION_NAME, m) {
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// "XQA Wrapper"
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m.def("xqa_wrapper", xqa_wrapper);
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}
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