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123 lines
4.4 KiB
123 lines
4.4 KiB
/* Copyright (c) 2019 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 <cmath>
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#include <unordered_map>
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#include <utility>
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#include <vector>
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/operators/math/math_function.h"
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namespace paddle {
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namespace operators {
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template <typename InT>
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struct UniqueOpFunctor {
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framework::Tensor* out_;
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framework::Tensor* index_;
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const framework::Tensor* in_;
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framework::Tensor* count_;
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UniqueOpFunctor(framework::Tensor* out, framework::Tensor* index,
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const framework::Tensor* in,
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framework::Tensor* count = nullptr)
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: out_(out), index_(index), in_(in), count_(count) {}
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template <typename IndexT>
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void apply() const {
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auto* in_data = in_->data<InT>();
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auto* index_data = index_->mutable_data<IndexT>(platform::CPUPlace());
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int64_t j = 0;
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// TODO(fangzeyang): Should optimize performance here.
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std::unordered_map<InT, int64_t> dict;
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std::vector<InT> uniq;
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PADDLE_ENFORCE_LT(
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in_->numel(), pow(2, 31),
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platform::errors::InvalidArgument(
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"The num of Input(X) elements should be less then INT_MAX, "
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"but received num is %d.",
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in_->numel()));
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for (auto i = 0; i < in_->numel(); i++) {
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auto it = dict.find(in_data[i]);
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if (it == dict.end()) {
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dict.emplace(std::make_pair(in_data[i], j));
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uniq.emplace_back(in_data[i]);
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index_data[i] = static_cast<IndexT>(j);
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j++;
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} else {
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index_data[i] = static_cast<IndexT>(it->second);
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}
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}
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if (count_ != nullptr) {
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// Resize the count tensor dims to allocate the memory
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count_->Resize(framework::make_ddim({static_cast<int64_t>(uniq.size())}));
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IndexT* count_data = count_->mutable_data<IndexT>(platform::CPUPlace());
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// init count_data to 0
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memset(count_data, 0, uniq.size() * sizeof(IndexT));
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const auto& index_type = index_->type();
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bool index_type_match = index_type == framework::proto::VarType::INT32 ||
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index_type == framework::proto::VarType::INT64;
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PADDLE_ENFORCE_EQ(index_type_match, true,
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platform::errors::InvalidArgument(
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"Index holds the wrong type, it holds %s, "
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"but desires to be %s or %s",
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paddle::framework::DataTypeToString(index_type),
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paddle::framework::DataTypeToString(
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framework::proto::VarType::INT32),
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paddle::framework::DataTypeToString(
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framework::proto::VarType::INT64)));
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if (index_type == framework::proto::VarType::INT32) {
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for (auto i = 0; i < in_->numel(); ++i) {
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const IndexT& index = index_data[i];
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count_data[static_cast<int32_t>(index)] += static_cast<IndexT>(1);
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}
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} else {
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for (auto i = 0; i < in_->numel(); ++i) {
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const IndexT& index = index_data[i];
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count_data[static_cast<int64_t>(index)] += static_cast<IndexT>(1);
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}
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}
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}
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out_->Resize(framework::make_ddim({static_cast<int64_t>(uniq.size())}));
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auto out_data = out_->mutable_data<InT>(platform::CPUPlace());
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std::memcpy(out_data, uniq.data(), uniq.size() * sizeof(InT));
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}
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};
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template <typename T>
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class UniqueKernel : 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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auto data_type = static_cast<framework::proto::VarType::Type>(
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context.Attr<int>("dtype"));
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auto* x = context.Input<framework::Tensor>("X");
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auto* out = context.Output<framework::Tensor>("Out");
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auto* index = context.Output<framework::Tensor>("Index");
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framework::VisitDataType(data_type, UniqueOpFunctor<T>(out, index, x));
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}
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};
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} // namespace operators
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} // namespace paddle
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