chengduoZH
7 years ago
parent
47a4ec0672
commit
8eaec5dd7c
@ -0,0 +1,103 @@
|
||||
// Copyright (c) 2018 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.
|
||||
|
||||
#include "paddle/fluid/framework/details/broad_cast_op_handle.h"
|
||||
|
||||
namespace paddle {
|
||||
namespace framework {
|
||||
namespace details {
|
||||
|
||||
Tensor *GetTensorFromVar(Variable *in_var) {
|
||||
if (in_var->IsType<LoDTensor>()) {
|
||||
return in_var->GetMutable<LoDTensor>();
|
||||
} else if (in_var->IsType<SelectedRows>()) {
|
||||
return in_var->GetMutable<SelectedRows>()->mutable_value();
|
||||
} else {
|
||||
PADDLE_THROW("Var should be LoDTensor or SelectedRows");
|
||||
}
|
||||
return nullptr;
|
||||
}
|
||||
BCastOpHandle::BCastOpHandle(const std::vector<Scope *> &local_scopes,
|
||||
const std::vector<platform::Place> &places,
|
||||
const platform::ContextMap &ctxs)
|
||||
: local_scopes_(local_scopes), places_(places), ctxs_(ctxs) {
|
||||
for (auto &p : places_) {
|
||||
this->dev_ctxes_[p] = ctxs_.DevCtx(p);
|
||||
}
|
||||
}
|
||||
|
||||
void BCastOpHandle::RunImpl() {
|
||||
PADDLE_ENFORCE_EQ(this->inputs_.size(), 1);
|
||||
PADDLE_ENFORCE_EQ(this->outputs_.size(), places_.size());
|
||||
|
||||
// Wait input done, this Wait is asynchronous operation
|
||||
auto in_var_handle = static_cast<VarHandle *>(this->inputs_[0]);
|
||||
auto &in_place = in_var_handle->place_;
|
||||
if (inputs_[0]->generated_op_)
|
||||
inputs_[0]->generated_op_->Wait(dev_ctxes_[in_place]);
|
||||
|
||||
auto iter = std::find(places_.begin(), places_.end(), in_place);
|
||||
if (iter == places_.end()) {
|
||||
PADDLE_THROW("The input of BCast is not in the places_.");
|
||||
}
|
||||
|
||||
int offset = iter - places_.begin();
|
||||
auto in_var = local_scopes_[offset]->FindVar(in_var_handle->name_);
|
||||
|
||||
Tensor *in_tensor = GetTensorFromVar(in_var);
|
||||
for (auto *out : outputs_) {
|
||||
auto out_handle = static_cast<VarHandle *>(out);
|
||||
auto &out_p = out_handle->place_;
|
||||
|
||||
auto iter = std::find(places_.begin(), places_.end(), out_p);
|
||||
if (iter == places_.end()) {
|
||||
PADDLE_THROW("The output of BCast is not in the places_.");
|
||||
}
|
||||
int offset = iter - places_.begin();
|
||||
|
||||
auto *s = local_scopes_[offset];
|
||||
auto out_var = s->FindVar(out_handle->name_);
|
||||
|
||||
PADDLE_ENFORCE_EQ(out_var->Type(), in_var->Type(), "");
|
||||
|
||||
if (in_var->IsType<framework::SelectedRows>()) {
|
||||
auto in_sr = in_var->GetMutable<framework::SelectedRows>();
|
||||
auto out = out_var->GetMutable<framework::SelectedRows>();
|
||||
if (in_sr == out) continue;
|
||||
out->set_height(in_sr->height());
|
||||
out->set_rows(in_sr->rows());
|
||||
out->mutable_value()->Resize(in_sr->value().dims());
|
||||
out->mutable_value()->mutable_data(out_p, in_sr->value().type());
|
||||
} else if (in_var->IsType<framework::LoDTensor>()) {
|
||||
auto in_lod = in_var->GetMutable<framework::LoDTensor>();
|
||||
auto out = out_var->GetMutable<framework::LoDTensor>();
|
||||
if (in_lod == out) continue;
|
||||
out->set_lod(in_lod->lod());
|
||||
out->Resize(in_lod->dims());
|
||||
out->mutable_data(out_p, in_lod->type());
|
||||
} else {
|
||||
PADDLE_THROW("Var should be LoDTensor or SelectedRows");
|
||||
}
|
||||
|
||||
Tensor *out_tensor = GetTensorFromVar(out_var);
|
||||
|
||||
paddle::framework::TensorCopy(*in_tensor, out_p, *(dev_ctxes_[in_place]),
|
||||
out_tensor);
|
||||
}
|
||||
}
|
||||
|
||||
std::string BCastOpHandle::Name() const { return "broadcast"; }
|
||||
} // namespace details
|
||||
} // namespace framework
|
||||
} // namespace paddle
|
||||
@ -0,0 +1,54 @@
|
||||
// Copyright (c) 2018 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 <map>
|
||||
#include <string>
|
||||
#include <vector>
|
||||
|
||||
#include "paddle/fluid/framework/details/op_handle_base.h"
|
||||
#include "paddle/fluid/framework/lod_tensor.h"
|
||||
#include "paddle/fluid/framework/scope.h"
|
||||
#include "paddle/fluid/framework/selected_rows.h"
|
||||
#include "paddle/fluid/platform/device_context.h"
|
||||
|
||||
namespace paddle {
|
||||
namespace framework {
|
||||
namespace details {
|
||||
|
||||
/*
|
||||
* BroadCast the input to all scope.
|
||||
*
|
||||
*/
|
||||
struct BCastOpHandle : public OpHandleBase {
|
||||
const std::vector<Scope *> &local_scopes_;
|
||||
const std::vector<platform::Place> &places_;
|
||||
const platform::ContextMap &ctxs_;
|
||||
|
||||
BCastOpHandle(const std::vector<Scope *> &local_scopes,
|
||||
const std::vector<platform::Place> &places,
|
||||
const platform::ContextMap &ctxs);
|
||||
|
||||
std::string Name() const override;
|
||||
|
||||
bool IsMultiDeviceTransfer() override { return false; };
|
||||
|
||||
protected:
|
||||
void RunImpl() override;
|
||||
};
|
||||
|
||||
} // namespace details
|
||||
} // namespace framework
|
||||
} // namespace paddle
|
||||
@ -0,0 +1,174 @@
|
||||
// Copyright (c) 2018 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.
|
||||
|
||||
#include "paddle/fluid/framework/details/broad_cast_op_handle.h"
|
||||
#include "gtest/gtest.h"
|
||||
|
||||
#include "paddle/fluid/platform/device_context.h"
|
||||
|
||||
namespace f = paddle::framework;
|
||||
namespace p = paddle::platform;
|
||||
|
||||
// test data amount
|
||||
const f::DDim kDims = {20, 20};
|
||||
|
||||
class BroadCastTester : public ::testing::Test {
|
||||
public:
|
||||
void SetUp() override {
|
||||
int count = p::GetCUDADeviceCount();
|
||||
if (count <= 1) {
|
||||
LOG(WARNING) << "Cannot test multi-gpu BroadCast, because the CUDA "
|
||||
"device count is "
|
||||
<< count;
|
||||
exit(0);
|
||||
}
|
||||
for (int i = 0; i < count; ++i) {
|
||||
gpu_list_.emplace_back(p::CUDAPlace(i));
|
||||
}
|
||||
ctxs_ = new p::ContextMap(gpu_list_);
|
||||
}
|
||||
|
||||
template <class T>
|
||||
void BroadCastInitOp(int gpu_id = 0) {
|
||||
for (size_t j = 0; j < gpu_list_.size(); ++j) {
|
||||
local_scope_.push_back(&g_scope_.NewScope());
|
||||
auto* out_var = local_scope_[j]->Var("out");
|
||||
out_var->GetMutable<T>();
|
||||
}
|
||||
auto* in_var = local_scope_[gpu_id]->Var("input");
|
||||
in_var->GetMutable<T>();
|
||||
|
||||
bc_op_handle_ =
|
||||
new f::details::BCastOpHandle(local_scope_, gpu_list_, *ctxs_);
|
||||
|
||||
f::details::VarHandle* in_var_handle = new f::details::VarHandle();
|
||||
in_var_handle->place_ = gpu_list_[gpu_id];
|
||||
in_var_handle->name_ = "input";
|
||||
in_var_handle->version_ = 1;
|
||||
in_var_handle->generated_op_ = nullptr;
|
||||
bc_op_handle_->AddInput(in_var_handle);
|
||||
|
||||
for (size_t j = 0; j < gpu_list_.size(); ++j) {
|
||||
f::details::VarHandle* out_var_handle = new f::details::VarHandle();
|
||||
out_var_handle->place_ = gpu_list_[j];
|
||||
out_var_handle->name_ = "out";
|
||||
out_var_handle->version_ = 2;
|
||||
out_var_handle->generated_op_ = bc_op_handle_;
|
||||
bc_op_handle_->AddOutput(out_var_handle);
|
||||
}
|
||||
}
|
||||
void BroadCastDestroy() {
|
||||
delete ctxs_;
|
||||
for (auto in : bc_op_handle_->inputs_) {
|
||||
delete in;
|
||||
}
|
||||
for (auto out : bc_op_handle_->outputs_) {
|
||||
delete out;
|
||||
}
|
||||
delete bc_op_handle_;
|
||||
}
|
||||
|
||||
public:
|
||||
f::Scope g_scope_;
|
||||
p::ContextMap* ctxs_;
|
||||
std::vector<f::Scope*> local_scope_;
|
||||
std::vector<p::Place> gpu_list_;
|
||||
f::details::BCastOpHandle* bc_op_handle_;
|
||||
};
|
||||
|
||||
TEST_F(BroadCastTester, BroadCastTestLodTensor) {
|
||||
int gpu_id = 0;
|
||||
BroadCastInitOp<f::LoDTensor>(gpu_id);
|
||||
|
||||
auto in_var = local_scope_[gpu_id]->Var("input");
|
||||
auto in_lod_tensor = in_var->GetMutable<f::LoDTensor>();
|
||||
in_lod_tensor->mutable_data<float>(kDims, gpu_list_[gpu_id]);
|
||||
|
||||
std::vector<float> send_vector(f::product(kDims), gpu_id + 12);
|
||||
for (size_t k = 0; k < send_vector.size(); ++k) {
|
||||
send_vector[k] = k;
|
||||
}
|
||||
f::LoD lod{{0, 10, 20}};
|
||||
paddle::framework::TensorFromVector<float>(
|
||||
send_vector, *(ctxs_->DevCtx(gpu_list_[gpu_id])), in_lod_tensor);
|
||||
in_lod_tensor->set_lod(lod);
|
||||
bc_op_handle_->Run(false);
|
||||
|
||||
ctxs_->WaitAll();
|
||||
|
||||
p::CPUPlace cpu_place;
|
||||
for (size_t j = 0; j < gpu_list_.size(); ++j) {
|
||||
auto out_var = local_scope_[j]->Var("out");
|
||||
auto out_tensor = out_var->Get<f::LoDTensor>();
|
||||
PADDLE_ENFORCE_EQ(out_tensor.lod(), lod, "lod is not equal.");
|
||||
|
||||
f::Tensor result_tensor;
|
||||
f::TensorCopy(out_tensor, cpu_place, *(ctxs_->DevCtx(j)), &result_tensor);
|
||||
float* ct = result_tensor.mutable_data<float>(cpu_place);
|
||||
|
||||
for (int64_t j = 0; j < f::product(kDims); ++j) {
|
||||
ASSERT_NEAR(ct[j], send_vector[j], 1e-5);
|
||||
}
|
||||
}
|
||||
|
||||
BroadCastDestroy();
|
||||
}
|
||||
|
||||
TEST_F(BroadCastTester, BroadCastTestSelectedRows) {
|
||||
int gpu_id = 0;
|
||||
BroadCastInitOp<f::SelectedRows>(gpu_id);
|
||||
|
||||
auto in_var = local_scope_[gpu_id]->Var("input");
|
||||
auto in_selected_rows = in_var->GetMutable<f::SelectedRows>();
|
||||
auto value = in_selected_rows->mutable_value();
|
||||
value->mutable_data<float>(kDims, gpu_list_[gpu_id]);
|
||||
int height = kDims[0] * 2;
|
||||
std::vector<int64_t> rows{0, 1, 2, 3, 3, 0, 14, 7, 3, 1,
|
||||
2, 4, 6, 3, 1, 1, 1, 1, 3, 7};
|
||||
in_selected_rows->set_height(height);
|
||||
in_selected_rows->set_rows(rows);
|
||||
|
||||
std::vector<float> send_vector(f::product(kDims));
|
||||
for (size_t k = 0; k < send_vector.size(); ++k) {
|
||||
send_vector[k] = k;
|
||||
}
|
||||
paddle::framework::TensorFromVector<float>(
|
||||
send_vector, *(ctxs_->DevCtx(gpu_list_[gpu_id])), value);
|
||||
|
||||
bc_op_handle_->Run(false);
|
||||
|
||||
ctxs_->WaitAll();
|
||||
|
||||
p::CPUPlace cpu_place;
|
||||
for (size_t j = 0; j < gpu_list_.size(); ++j) {
|
||||
auto out_var = local_scope_[j]->Var("out");
|
||||
auto& out_select_rows = out_var->Get<f::SelectedRows>();
|
||||
auto rt = out_select_rows.value();
|
||||
|
||||
PADDLE_ENFORCE_EQ(out_select_rows.height(), height, "height is not equal.");
|
||||
for (size_t k = 0; k < out_select_rows.rows().size(); ++k) {
|
||||
PADDLE_ENFORCE_EQ(out_select_rows.rows()[k], rows[k]);
|
||||
}
|
||||
|
||||
f::Tensor result_tensor;
|
||||
f::TensorCopy(rt, cpu_place, *(ctxs_->DevCtx(j)), &result_tensor);
|
||||
float* ct = result_tensor.data<float>();
|
||||
|
||||
for (int64_t j = 0; j < f::product(kDims); ++j) {
|
||||
ASSERT_NEAR(ct[j], send_vector[j], 1e-5);
|
||||
}
|
||||
}
|
||||
|
||||
BroadCastDestroy();
|
||||
}
|
||||
Loading…
Reference in new issue