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43 lines
1.5 KiB
43 lines
1.5 KiB
7 years ago
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/fluid/framework/eigen.h"
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#include "paddle/fluid/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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template <typename DeviceContext, typename T>
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class FakeDequantizeMaxAbsKernel : public framework::OpKernel<T> {
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public:
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virtual void Compute(const framework::ExecutionContext& ctx) const {
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auto* in = ctx.Input<framework::Tensor>("X");
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auto* out = ctx.Output<framework::Tensor>("Out");
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out->mutable_data<T>(in->place());
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int num_bits = ctx.Attr<int>("num_bits");
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T scale = static_cast<T>(ctx.Attr<float>("scale"));
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int range = std::pow(2, num_bits) - 1;
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auto eigen_out = framework::EigenVector<T>::Flatten(*out);
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auto eigen_in = framework::EigenVector<T>::Flatten(*in);
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auto& dev = *ctx.template device_context<DeviceContext>().eigen_device();
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eigen_out.device(dev) = (scale / range) * eigen_in;
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}
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};
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} // namespace operators
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} // namespace paddle
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