chore: import upstream snapshot with attribution
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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#pragma once
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#include "paddle/phi/core/dense_tensor.h"
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namespace phi {
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template <typename T, typename Context>
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void RmsNormQuantKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const optional<DenseTensor>& bias,
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const optional<DenseTensor>& residual,
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const DenseTensor& norm_weight,
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const optional<DenseTensor>& norm_bias,
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const float epsilon,
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const int begin_norm_axis,
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const float quant_scale,
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const int quant_round_type,
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const float quant_max_bound,
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const float quant_min_bound,
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DenseTensor* out,
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DenseTensor* residual_out,
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DenseTensor* inv_var);
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template <typename T, typename Context>
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void ResidualAddRmsNormWrapper(const Context& dev_ctx,
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const T* x,
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const T* residual,
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const T* bias,
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const T* norm_weight,
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const T* norm_bias,
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const float epsilon,
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const int rows,
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const int cols,
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T* residual_output,
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T* output);
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template <typename T, typename Context>
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void RmsNormWrapper(const Context& dev_ctx,
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const T* x,
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const T* weight,
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const T* bias,
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const float epsilon,
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const int rows,
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const int cols,
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T* output);
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} // namespace phi
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