You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
119 lines
4.5 KiB
119 lines
4.5 KiB
// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
|
|
//
|
|
// Licensed under the Apache License, Version 2.0 (the "License");
|
|
// you may not use this file except in compliance with the License.
|
|
// You may obtain a copy of the License at
|
|
//
|
|
// http://www.apache.org/licenses/LICENSE-2.0
|
|
//
|
|
// Unless required by applicable law or agreed to in writing, software
|
|
// distributed under the License is distributed on an "AS IS" BASIS,
|
|
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
// See the License for the specific language governing permissions and
|
|
// limitations under the License.
|
|
|
|
#pragma once
|
|
#include <memory>
|
|
#include <vector>
|
|
#include "paddle/fluid/framework/fleet/box_wrapper.h"
|
|
#include "paddle/fluid/framework/fleet/ps_gpu_wrapper.h"
|
|
#include "paddle/fluid/framework/op_registry.h"
|
|
#include "paddle/fluid/framework/tensor.h"
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
|
|
template <typename T>
|
|
static void PullBoxSparseFunctor(const framework::ExecutionContext &ctx) {
|
|
auto inputs = ctx.MultiInput<framework::Tensor>("Ids");
|
|
auto outputs = ctx.MultiOutput<framework::Tensor>("Out");
|
|
const auto slot_size = inputs.size();
|
|
std::vector<const uint64_t *> all_keys(slot_size);
|
|
// BoxPS only supports float now
|
|
std::vector<float *> all_values(slot_size);
|
|
std::vector<int64_t> slot_lengths(slot_size);
|
|
for (size_t i = 0; i < slot_size; i++) {
|
|
const auto *slot = inputs[i];
|
|
const uint64_t *single_slot_keys =
|
|
reinterpret_cast<const uint64_t *>(slot->data<int64_t>());
|
|
all_keys[i] = single_slot_keys;
|
|
slot_lengths[i] = slot->numel();
|
|
auto *output = outputs[i]->mutable_data<T>(ctx.GetPlace());
|
|
all_values[i] = output;
|
|
}
|
|
#ifdef PADDLE_WITH_BOX_PS
|
|
auto hidden_size = ctx.Attr<int>("size");
|
|
auto box_ptr = paddle::framework::BoxWrapper::GetInstance();
|
|
box_ptr->PullSparse(ctx.GetPlace(), all_keys, all_values, slot_lengths,
|
|
hidden_size, 0);
|
|
#endif
|
|
#if (defined PADDLE_WITH_NCCL) && (defined PADDLE_WITH_PSLIB)
|
|
auto hidden_size = ctx.Attr<int>("size");
|
|
auto gpu_ps_ptr = paddle::framework::PSGPUWrapper::GetInstance();
|
|
gpu_ps_ptr->PullSparse(ctx.GetPlace(), 0, all_keys, all_values, slot_lengths,
|
|
hidden_size);
|
|
#endif
|
|
}
|
|
|
|
template <typename T>
|
|
static void PushBoxSparseFunctor(const framework::ExecutionContext &ctx) {
|
|
auto inputs = ctx.MultiInput<framework::LoDTensor>("Ids");
|
|
auto d_output =
|
|
ctx.MultiInput<framework::Tensor>(framework::GradVarName("Out"));
|
|
const auto slot_size = inputs.size();
|
|
std::vector<const uint64_t *> all_keys(slot_size);
|
|
std::vector<const float *> all_grad_values(slot_size);
|
|
std::vector<int64_t> slot_lengths(slot_size);
|
|
int batch_size = -1;
|
|
for (size_t i = 0; i < slot_size; i++) {
|
|
const auto *slot = inputs[i];
|
|
const uint64_t *single_slot_keys =
|
|
reinterpret_cast<const uint64_t *>(slot->data<int64_t>());
|
|
all_keys[i] = single_slot_keys;
|
|
slot_lengths[i] = slot->numel();
|
|
int cur_batch_size =
|
|
slot->lod().size() ? slot->lod()[0].size() - 1 : slot->dims()[0];
|
|
if (batch_size == -1) {
|
|
batch_size = cur_batch_size;
|
|
} else {
|
|
PADDLE_ENFORCE_EQ(batch_size, cur_batch_size,
|
|
platform::errors::PreconditionNotMet(
|
|
"The batch size of all input slots should be same, "
|
|
"please cheack"));
|
|
}
|
|
const float *grad_value = d_output[i]->data<float>();
|
|
all_grad_values[i] = grad_value;
|
|
}
|
|
#ifdef PADDLE_WITH_BOX_PS
|
|
auto hidden_size = ctx.Attr<int>("size");
|
|
auto box_ptr = paddle::framework::BoxWrapper::GetInstance();
|
|
box_ptr->PushSparseGrad(ctx.GetPlace(), all_keys, all_grad_values,
|
|
slot_lengths, hidden_size, 0, batch_size);
|
|
#endif
|
|
#if (defined PADDLE_WITH_NCCL) && (defined PADDLE_WITH_PSLIB)
|
|
auto hidden_size = ctx.Attr<int>("size");
|
|
auto gpu_ps_ptr = paddle::framework::PSGPUWrapper::GetInstance();
|
|
gpu_ps_ptr->PushSparseGrad(ctx.GetPlace(), 0, all_keys, all_grad_values,
|
|
slot_lengths, hidden_size, batch_size);
|
|
#endif
|
|
}
|
|
|
|
using LoDTensor = framework::LoDTensor;
|
|
template <typename T>
|
|
class PullBoxSparseCPUKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext &ctx) const override {
|
|
PullBoxSparseFunctor<T>(ctx);
|
|
}
|
|
};
|
|
|
|
template <typename T>
|
|
class PushBoxSparseCPUKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext &ctx) const override {
|
|
PushBoxSparseFunctor<T>(ctx);
|
|
}
|
|
};
|
|
} // namespace operators
|
|
} // namespace paddle
|