wehub-resource-sync
87 lines
3.1 KiB
C++
87 lines
3.1 KiB
C++
// Copyright (c) 2024 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/kernels/fake_dequantize_kernel.h"
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#include "paddle/phi/kernels/funcs/fake_dequantize_functor.h"
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namespace phi {
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template <typename T, typename Context>
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void FakeDequantizeMaxAbsKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& scale,
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float max_range,
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DenseTensor* out) {
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dev_ctx.template Alloc<T>(out);
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funcs::DequantizeFunctor<Context, T>()(
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dev_ctx, &x, &scale, static_cast<T>(max_range), out);
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}
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template <typename T, typename Context>
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void FakeChannelWiseDequantizeMaxAbsKernel(
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const Context& dev_ctx,
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const DenseTensor& x,
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const std::vector<const DenseTensor*>& scales,
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const std::vector<int>& quant_bits,
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int quant_axis,
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int x_num_col_dims,
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DenseTensor* out) {
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int max_range = 1;
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dev_ctx.template Alloc<T>(out);
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int scale_num = scales.size();
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if (scale_num == 1) {
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PADDLE_ENFORCE_EQ(
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scales[0]->numel(),
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x.dims()[quant_axis],
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common::errors::PreconditionNotMet(
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"The number of first scale values must be the same with "
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"quant_axis dimension value of Input(X) when the `Scales` has "
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"only one element, but %ld != %ld here.",
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scales[0]->numel(),
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x.dims()[quant_axis]));
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max_range *= (std::pow(2, quant_bits[0] - 1) - 1);
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} else if (scale_num == 2) {
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PADDLE_ENFORCE_EQ(
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scales[0]->numel(),
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x.dims()[x_num_col_dims],
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common::errors::PreconditionNotMet(
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"The number of first scale values must be the same with "
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"corresponding dimension value of Input(X) when the `Scales` "
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"has two elements, but %ld != %ld here.",
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scales[0]->numel(),
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x.dims()[1]));
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PADDLE_ENFORCE_EQ(scales[1]->numel(),
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1,
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common::errors::PreconditionNotMet(
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"The second scale tensor should only have one "
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"value at now, but it has %ld values here.",
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scales[1]->numel()));
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max_range *= (std::pow(2, quant_bits[0] - 1) - 1) *
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(std::pow(2, quant_bits[1] - 1) - 1);
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}
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funcs::ChannelDequantizeFunctor<Context, T>()(
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dev_ctx,
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&x,
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(const_cast<std::vector<const DenseTensor*>*>(&scales))->data(),
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scale_num,
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static_cast<T>(max_range),
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quant_axis,
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x_num_col_dims,
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out);
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}
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} // namespace phi
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