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85 lines
2.6 KiB
85 lines
2.6 KiB
/* Copyright (c) 2018 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 <algorithm>
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#include <iostream>
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#include <iterator>
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#include <random>
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#include <sstream>
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#include <vector>
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#include "paddle/fluid/framework/generator.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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using Tensor = framework::Tensor;
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template <typename T>
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class SamplingIdKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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const Tensor* input = context.Input<Tensor>("X");
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const int batch_size = static_cast<int>(input->dims()[0]);
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const int width = static_cast<int>(input->dims()[1]);
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PADDLE_ENFORCE_GE(
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batch_size, 0,
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platform::errors::InvalidArgument(
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"batch_size(dims[0]) must be nonnegative. but it is %d.",
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batch_size));
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PADDLE_ENFORCE_GE(
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width, 0,
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platform::errors::InvalidArgument(
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"width(dims[1]) must be nonnegative. but it is %d.", width));
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std::vector<T> ins_vector;
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framework::TensorToVector(*input, context.device_context(), &ins_vector);
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unsigned int seed = static_cast<unsigned int>(context.Attr<int>("seed"));
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std::uniform_real_distribution<T> dist(
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static_cast<T>(context.Attr<float>("min")),
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static_cast<T>(context.Attr<float>("max")));
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auto engine = framework::GetCPURandomEngine(seed);
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std::vector<int64_t> ids(batch_size);
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for (int i = 0; i < batch_size; ++i) {
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T r = dist(*engine);
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int idx = width - 1;
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for (int j = 0; j < width; ++j) {
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if ((r -= ins_vector[i * width + j]) < 0) {
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idx = j;
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break;
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}
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}
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ids[i] = int64_t(idx);
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}
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std::vector<int64_t> out_dim;
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out_dim.push_back(static_cast<int64_t>(batch_size));
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Tensor* output = context.Output<Tensor>("Out");
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output->Resize(framework::make_ddim(out_dim));
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output->mutable_data<T>(context.GetPlace());
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framework::TensorFromVector(ids, context.device_context(), output);
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}
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};
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} // namespace operators
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} // namespace paddle
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