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chore: import upstream snapshot with attribution

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wehub-resource-sync
2026-07-13 12:40:42 +08:00
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paddle/phi/kernels/quantize_linear_kernel.h
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// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/device_context.h"
#include "paddle/phi/core/kernel_registry.h"
namespace phi {
template <typename T, typename Context>
void QuantizeLinearKernel(const Context& dev_ctx,
const DenseTensor& x,
const optional<DenseTensor>& scale,
const DenseTensor& zero_point,
const optional<DenseTensor>& in_accum,
const optional<DenseTensor>& in_state,
int quant_axis,
int bit_length,
int qmin,
int qmax,
int round_type,
bool is_test,
bool only_observer,
DenseTensor* out,
DenseTensor* out_state,
DenseTensor* out_accum,
DenseTensor* out_scale);
template <typename T, typename Context>
void DeQuantizeLinearKernel(const Context& dev_ctx,
const DenseTensor& x,
const optional<DenseTensor>& scale,
const DenseTensor& zero_point,
const optional<DenseTensor>& in_accum,
const optional<DenseTensor>& in_state,
int quant_axis,
int bit_length,
int qmin,
int qmax,
int round_type,
bool is_test,
bool only_observer,
DenseTensor* out,
DenseTensor* out_state,
DenseTensor* out_accum,
DenseTensor* out_scale);
template <typename T, typename Context>
void DeQuantizeLinearDeprecatedKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& in_scale,
const DenseTensor& zero_point,
int quant_axis,
int bit_length,
int qmin,
int qmax,
int round_type,
bool only_observer,
DenseTensor* out);
template <typename T, typename Context>
void QuantizeLinearDeprecatedTrainKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& in_scale,
const DenseTensor& zero_point,
const optional<DenseTensor>& in_accum,
const optional<DenseTensor>& in_state,
int quant_axis,
int bit_length,
int qmin,
int qmax,
int round_type,
bool only_observer,
DenseTensor* out,
DenseTensor* out_state,
DenseTensor* out_accum,
DenseTensor* out_scale);
template <typename T, typename Context>
void QuantizeLinearDeprecatedInferKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& in_scale,
const DenseTensor& zero_point,
int quant_axis,
int bit_length,
int qmin,
int qmax,
int round_type,
bool only_observer,
DenseTensor* out);
} // namespace phi