39 lines
1.5 KiB
Plaintext
39 lines
1.5 KiB
Plaintext
/*
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* Copyright (c) 2023 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 rmsnorm(at::Tensor& out, at::Tensor& input, at::Tensor& weight, double eps, bool enable_pdl);
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void fused_add_rmsnorm(at::Tensor& input, at::Tensor& residual, at::Tensor& weight, double eps,
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bool enable_pdl);
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void gemma_rmsnorm(at::Tensor& out, at::Tensor& input, at::Tensor& weight, double eps,
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bool enable_pdl);
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void gemma_fused_add_rmsnorm(at::Tensor& input, at::Tensor& residual, at::Tensor& weight,
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double eps, bool enable_pdl);
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TORCH_LIBRARY_FRAGMENT(TORCH_EXTENSION_NAME, m) {
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// Root mean square normalization
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m.def("rmsnorm", rmsnorm);
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// Fused add root mean square normalization
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m.def("fused_add_rmsnorm", fused_add_rmsnorm);
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// Gemma Root mean square normalization
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m.def("gemma_rmsnorm", gemma_rmsnorm);
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// Gemma Fused add root mean square normalization
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m.def("gemma_fused_add_rmsnorm", gemma_fused_add_rmsnorm);
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}
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