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ensure global BuddyAllocator is initialized before global Scope

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revert-4814-Add_sequence_project_op
qijun 7 years ago
parent 45c4dcaabb
commit 48b080db9f
5 changed files with 62 additions and 53 deletions
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94
paddle/framework/executor_test.cc
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@ -13,8 +13,6 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/framework/executor.h"
#include <memory> // for unique_ptr
#include <mutex> // for call_once
#include <vector>
#include "gtest/gtest.h"
#include "paddle/framework/attribute.h"
@ -34,9 +32,8 @@ using namespace paddle::framework;
typedef paddle::framework::BlockDesc proto_block;
typedef paddle::framework::OpDesc proto_op;
void add_gaussian_random_op(string var_name, proto_block* block) {
std::vector<int> dim{2, 3};
void add_gaussian_random_op(string var_name, std::vector<int>& dim,
proto_block* block) {
// insert variable
auto a = block->add_vars();
a->set_name(var_name);
@ -60,9 +57,8 @@ void add_gaussian_random_op(string var_name, proto_block* block) {
Out->add_arguments(var_name);
}
void add_feed_op(string var_name, int index, proto_block* block) {
std::vector<int> dim{3};
void add_feed_op(string var_name, std::vector<int>& dim, int index,
proto_block* block) {
// insert variable
auto a = block->add_vars();
a->set_name(var_name);
@ -95,9 +91,8 @@ void add_feed_op(string var_name, int index, proto_block* block) {
Out->add_arguments(var_name);
}
void add_fetch_op(string var_name, int index, proto_block* block) {
std::vector<int> dim{3};
void add_fetch_op(string var_name, std::vector<int>& dim, int index,
proto_block* block) {
// insert variable
auto a = block->add_vars();
a->set_name(var_name);
@ -138,20 +133,11 @@ void set_feed_variable(const std::vector<std::vector<T>>& inputs) {
Variable* g_feed_value = GetScope()->FindVar("feed_value");
FeedInputs& feed_inputs = *(g_feed_value->GetMutable<FeedInputs>());
auto size = inputs.size();
std::call_once(set_variable_flag, [&]() {
feed_inputs.reserve(size);
for (size_t i = 0; i < size; i++) {
paddle::framework::Tensor tmp;
tmp.mutable_data<T>(make_ddim({static_cast<int64_t>(inputs[i].size())}),
CPUPlace());
feed_inputs.push_back(tmp);
}
});
feed_inputs.resize(size);
for (size_t i = 0; i < size; i++) {
memcpy(feed_inputs[i].data<T>(), inputs[i].data(),
inputs[i].size() * sizeof(T));
T* dst = feed_inputs[i].mutable_data<T>(
make_ddim({static_cast<int64_t>(inputs[i].size())}), CPUPlace());
memcpy(dst, inputs[i].data(), inputs[i].size() * sizeof(T));
}
}
@ -160,19 +146,17 @@ std::vector<std::vector<T>> get_fetch_variable() {
typedef std::vector<paddle::framework::Tensor> FetchOutputs;
Variable* g_fetch_value = GetScope()->FindVar("fetch_value");
FetchOutputs& fetch_outputs = *(g_fetch_value->GetMutable<FetchOutputs>());
auto size = fetch_outputs.size();
auto size = fetch_outputs.size();
std::vector<std::vector<T>> result;
result.reserve(size);
for (size_t i = 0; i < size; i++) {
std::vector<T> tmp;
tmp.reserve(fetch_outputs[i].numel());
tmp.resize(fetch_outputs[i].numel());
memcpy(tmp.data(), fetch_outputs[i].data<T>(),
fetch_outputs[i].numel() * sizeof(T));
result.push_back(tmp);
}
return result;
}
@ -183,8 +167,9 @@ class ExecutorTesterRandom : public ::testing::Test {
root_block->set_idx(0);
root_block->set_parent_idx(-1);
add_gaussian_random_op("a", root_block);
add_gaussian_random_op("b", root_block);
std::vector<int> dim{2, 3};
add_gaussian_random_op("a", dim, root_block);
add_gaussian_random_op("b", dim, root_block);
auto c = root_block->add_vars();
c->set_name("c");
@ -203,12 +188,11 @@ class ExecutorTesterRandom : public ::testing::Test {
Out->set_parameter("Out");
Out->add_arguments("c");
scope_ = GetScope();
add_fetch_op("c", dim, 0, root_block);
}
protected:
ProgramDesc pdesc_;
Scope* scope_;
};
class ExecutorTesterFeed : public ::testing::Test {
@ -218,8 +202,10 @@ class ExecutorTesterFeed : public ::testing::Test {
root_block->set_idx(0);
root_block->set_parent_idx(-1);
add_feed_op("a", 0, root_block);
add_feed_op("b", 1, root_block);
std::vector<int> dim{6};
add_feed_op("a", dim, 0, root_block);
add_feed_op("b", dim, 1, root_block);
auto c = root_block->add_vars();
c->set_name("c");
@ -238,10 +224,10 @@ class ExecutorTesterFeed : public ::testing::Test {
Out->set_parameter("Out");
Out->add_arguments("c");
add_fetch_op("c", 0, root_block);
add_fetch_op("c", dim, 0, root_block);
std::vector<float> vec1 = {1.0, 2.0, 3.0};
std::vector<float> vec2 = {4.0, 5.0, 6.0};
std::vector<float> vec1 = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0};
std::vector<float> vec2 = {4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
inputs_.push_back(vec1);
inputs_.push_back(vec2);
}
@ -253,12 +239,24 @@ class ExecutorTesterFeed : public ::testing::Test {
TEST_F(ExecutorTesterRandom, CPU) {
std::vector<Place> places;
CPUPlace cpu_place1, cpu_place2;
places.push_back(cpu_place1);
places.push_back(cpu_place2);
CPUPlace cpu_place;
places.push_back(cpu_place);
// We have a global Scope and BuddyAllocator, and we must ensure
// global BuddyAllocator is initialized before global Scope. Thus,
// global Scope will deconstruct before BuddyAllocator. Otherwise,
// "pointer being freed was not allocated" error will appear.
paddle::memory::Used(cpu_place);
Executor* executor = new Executor(places);
executor->Run(pdesc_, scope_);
executor->Run(pdesc_, GetScope());
std::vector<std::vector<float>> result = get_fetch_variable<float>();
for (auto& vec : result) {
for (auto& num : vec) {
std::cout << num << " ";
}
std::cout << std::endl;
}
delete executor;
}
@ -267,6 +265,12 @@ TEST_F(ExecutorTesterFeed, CPU) {
CPUPlace cpu_place;
places.push_back(cpu_place);
// We have a global Scope and BuddyAllocator, and we must ensure
// global BuddyAllocator is initialized before global Scope. Thus,
// global Scope will deconstruct before BuddyAllocator. Otherwise,
// "pointer being freed was not allocated" error will appear.
paddle::memory::Used(cpu_place);
Executor* executor = new Executor(places);
// 3 mini-batch
@ -293,8 +297,10 @@ TEST_F(ExecutorTesterRandom, GPU) {
GPUPlace gpu_place(0);
places.push_back(gpu_place);
paddle::memory::Used(gpu_place);
Executor* executor = new Executor(places);
executor->Run(pdesc_, scope_);
executor->Run(pdesc_, GetScope());
delete executor;
}
@ -303,11 +309,13 @@ TEST_F(ExecutorTesterFeed, GPU) {
GPUPlace gpu_place(0);
places.push_back(gpu_place);
paddle::memory::Used(gpu_place);
Executor* executor = new Executor(places);
// need to set feed variable before Executor::Run
set_feed_variable<float>(inputs_);
executor->Run(pdesc_, scope_);
executor->Run(pdesc_, GetScope());
delete executor;
}

4
paddle/operators/feed_op.cc
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@ -29,11 +29,11 @@ class FeedOp : public framework::OperatorWithKernel {
framework::Variable* g_feed_variable =
framework::GetScope()->FindVar("feed_value");
FeedInputs tensors = g_feed_variable->Get<FeedInputs>();
const FeedInputs& tensors = g_feed_variable->Get<FeedInputs>();
auto in_dim = tensors[col].dims();
ctx->SetOutputDim("Out", in_dim);
// need to handle LodTensor later
// TODO(qijun) need to handle LodTensor later
}
framework::DataType IndicateDataType(

2
paddle/operators/feed_op.h
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@ -31,7 +31,7 @@ class FeedKernel : public framework::OpKernel<T> {
framework::Variable* g_feed_variable =
framework::GetScope()->FindVar("feed_value");
int col = ctx.template Attr<int>("col");
FeedInputs tensors = g_feed_variable->Get<FeedInputs>();
const FeedInputs& tensors = g_feed_variable->Get<FeedInputs>();
out->CopyFrom<T>(tensors[col], ctx.GetPlace());
}
};

7
paddle/operators/fetch_op.cc
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@ -30,15 +30,16 @@ class FetchOp : public framework::OperatorWithKernel {
framework::GetScope()->FindVar("fetch_value");
FetchOutputs* tensors = g_fetch_variable->GetMutable<FetchOutputs>();
if (tensors->size() < col) {
tensors->resize(col);
if (tensors->size() < static_cast<size_t>(col + 1)) {
tensors->resize(col + 1);
}
auto input_dim = ctx->GetInputDim("Input");
framework::Tensor tmp;
tmp.Resize(input_dim);
(*tensors)[col].Resize(input_dim);
// need to handle LodTensor later
// TODO(qijun) need to handle LodTensor later
}
framework::DataType IndicateDataType(

8
paddle/operators/fetch_op.h
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@ -26,13 +26,13 @@ class FetchKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
typedef std::vector<framework::Tensor> FetchOutputs;
Tensor* input = ctx.Output<Tensor>("Input");
const Tensor* input = ctx.Input<Tensor>("Input");
int col = ctx.template Attr<int>("col");
framework::Variable* g_fetch_variable =
framework::GetScope()->FindVar("fetch_value");
FetchOutputs tensors = g_fetch_variable->Get<FetchOutputs>();
tensors[col].mutable_data<T>(platform::CPUPlace());
tensors[col].CopyFrom<T>(*input, platform::CPUPlace());
FetchOutputs* tensors = g_fetch_variable->GetMutable<FetchOutputs>();
(*tensors)[col].mutable_data<T>(platform::CPUPlace());
(*tensors)[col].CopyFrom<T>(*input, platform::CPUPlace());
}
};

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