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119 lines
4.3 KiB
119 lines
4.3 KiB
/* Copyright (c) 2020 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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#if (defined PADDLE_WITH_NCCL) && (defined PADDLE_WITH_PSLIB)
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#include <atomic>
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#include <ctime>
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#include <map>
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#include <memory>
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#include <random>
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#include <string>
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#include <unordered_map>
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#include <vector>
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#include "paddle/fluid/framework/fleet/heter_context.h"
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#include "paddle/fluid/framework/fleet/heter_ps/heter_ps_base.h"
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#include "paddle/fluid/framework/fleet/heter_ps/heter_resource.h"
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#include "paddle/fluid/framework/scope.h"
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#include "paddle/fluid/framework/tensor.h"
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#include "paddle/fluid/framework/variable_helper.h"
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#include "paddle/fluid/platform/gpu_info.h"
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#include "paddle/fluid/platform/macros.h" // for DISABLE_COPY_AND_ASSIGN
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#include "paddle/fluid/platform/place.h"
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namespace paddle {
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namespace framework {
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class PSGPUWrapper {
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public:
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virtual ~PSGPUWrapper() { delete HeterPs_; }
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PSGPUWrapper() {
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HeterPs_ = NULL;
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sleep_seconds_before_fail_exit_ = 300;
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}
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void PullSparse(const paddle::platform::Place& place, const int table_id,
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const std::vector<const uint64_t*>& keys,
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const std::vector<float*>& values,
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const std::vector<int64_t>& slot_lengths,
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const int hidden_size);
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void PushSparseGrad(const paddle::platform::Place& place, const int table_id,
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const std::vector<const uint64_t*>& keys,
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const std::vector<const float*>& grad_values,
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const std::vector<int64_t>& slot_lengths,
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const int hidden_size, const int batch_size);
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void CopyKeys(const paddle::platform::Place& place, uint64_t** origin_keys,
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uint64_t* total_keys, const int64_t* gpu_len, int slot_num,
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int total_len);
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void CopyForPull(const paddle::platform::Place& place, uint64_t** gpu_keys,
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const std::vector<float*>& values,
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const FeatureValue* total_values_gpu, const int64_t* gpu_len,
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const int slot_num, const int hidden_size,
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const int64_t total_length);
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void CopyForPush(const paddle::platform::Place& place,
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const std::vector<const float*>& grad_values,
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FeaturePushValue* total_grad_values_gpu,
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const std::vector<int64_t>& slot_lengths,
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const int hidden_size, const int64_t total_length,
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const int batch_size);
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void BuildGPUPS(const uint64_t table_id, int feature_dim,
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std::shared_ptr<HeterContext> context);
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void InitializeGPU(const std::vector<int>& dev_ids) {
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if (s_instance_ != NULL) {
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VLOG(3) << "PSGPUWrapper Begin InitializeGPU";
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resource_ = std::make_shared<HeterPsResource>(dev_ids);
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resource_->enable_p2p();
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keys_tensor.resize(resource_->total_gpu());
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}
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}
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// PSGPUWrapper singleton
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static std::shared_ptr<PSGPUWrapper> GetInstance() {
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if (NULL == s_instance_) {
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s_instance_.reset(new paddle::framework::PSGPUWrapper());
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}
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return s_instance_;
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}
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std::vector<std::unordered_map<uint64_t, std::vector<float>>>& GetLocalTable(
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int table_id) {
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return local_tables_[table_id];
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}
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void SetSlotVector(const std::vector<int>& slot_vector) {
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slot_vector_ = slot_vector;
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}
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private:
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static std::shared_ptr<PSGPUWrapper> s_instance_;
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std::unordered_map<
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uint64_t, std::vector<std::unordered_map<uint64_t, std::vector<float>>>>
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local_tables_;
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HeterPsBase* HeterPs_;
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std::vector<LoDTensor> keys_tensor; // Cache for pull_sparse
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std::shared_ptr<HeterPsResource> resource_;
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int32_t sleep_seconds_before_fail_exit_;
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std::vector<int> slot_vector_;
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protected:
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static bool is_initialized_;
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};
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} // end namespace framework
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} // end namespace paddle
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#endif
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