提交 4e165f4e 编写于 作者: D Dong Zhihong

"fix create output variable bug"

上级 61c1b046
......@@ -114,6 +114,9 @@ class NCCLBcastOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE(ctx->HasOutput("Out"),
" Output(Out) of Bcast op output should not be NULL");
int root = ctx->Attrs().Get<int>("root");
PADDLE_ENFORCE(root != -1, "Bcast root must be set.");
auto x_dims = ctx->GetInputsDim("X");
ctx->SetOutputsDim("Out", x_dims);
ctx->ShareLoD("X", /*->*/ "Out");
......
......@@ -54,12 +54,12 @@ class NCCLAllReduceKernel : public framework::OpKernel<T> {
ctx.device_context())
.stream();
// device id
int device_id =
boost::get<platform::GPUPlace>(ctx.GetPlace()).GetDeviceId();
int idx = comm->GetCommId(device_id);
int gpu_id = boost::get<platform::GPUPlace>(ctx.GetPlace()).GetDeviceId();
int idx = comm->GetCommId(gpu_id);
for (size_t i = 0; i < ins.size(); ++i) {
VLOG(1) << " invoke allreduce. send " << ins[i]->numel() << " recv "
VLOG(1) << "gpu : "
<< " invoke allreduce. send " << ins[i]->numel() << " recv "
<< outs[i]->numel();
PADDLE_ENFORCE(platform::dynload::ncclAllReduce(
......@@ -68,7 +68,8 @@ class NCCLAllReduceKernel : public framework::OpKernel<T> {
comm->comms_[idx], stream));
PADDLE_ENFORCE(cudaStreamSynchronize(stream));
VLOG(1) << " finished allreduce. send " << ins[i]->numel() << " recv "
VLOG(1) << "gpu : "
<< " finished allreduce. send " << ins[i]->numel() << " recv "
<< outs[i]->numel();
}
}
......@@ -91,9 +92,8 @@ class NCCLReduceKernel : public framework::OpKernel<T> {
ctx.device_context())
.stream();
// device id
int device_id =
boost::get<platform::GPUPlace>(ctx.GetPlace()).GetDeviceId();
int idx = comm->GetCommId(device_id);
int gpu_id = boost::get<platform::GPUPlace>(ctx.GetPlace()).GetDeviceId();
int idx = comm->GetCommId(gpu_id);
auto ins_names = ctx.Inputs("X");
std::hash<std::string> hasher;
......@@ -102,20 +102,20 @@ class NCCLReduceKernel : public framework::OpKernel<T> {
root = hasher(ins_names[i]) % comm->comms_.size();
}
T* recvbuffer = nullptr;
if (root == device_id) {
if (root == gpu_id) {
recvbuffer = outs[i]->mutable_data<T>(ctx.GetPlace());
}
VLOG(1) << " invoke reduce. send " << ins[i]->numel() << " recv "
<< outs[i]->numel();
VLOG(1) << "gpu : " << gpu_id << " invoke reduce. send "
<< ins[i]->numel() << " recv " << outs[i]->numel();
PADDLE_ENFORCE(platform::dynload::ncclReduce(
ins[i]->data<T>(), recvbuffer, ins[i]->numel(),
NCCLTypeWrapper<T>::type, ncclSum, root, comm->comms_[idx], stream));
PADDLE_ENFORCE(cudaStreamSynchronize(stream));
VLOG(1) << " finished reduce. send " << ins[i]->numel() << " recv "
<< outs[i]->numel();
VLOG(1) << "gpu : " << gpu_id << " finished reduce. send "
<< ins[i]->numel() << " recv " << outs[i]->numel();
}
}
};
......@@ -135,33 +135,37 @@ class NCCLBcastKernel : public framework::OpKernel<T> {
ctx.device_context())
.stream();
// device id
int device_id =
boost::get<platform::GPUPlace>(ctx.GetPlace()).GetDeviceId();
int idx = comm->GetCommId(device_id);
int gpu_id = boost::get<platform::GPUPlace>(ctx.GetPlace()).GetDeviceId();
int idx = comm->GetCommId(gpu_id);
if (idx == root) {
auto ins = ctx.MultiInput<LoDTensor>("X");
for (size_t i = 0; i < ins.size(); ++i) {
VLOG(1) << " invoke Bcast. send " << ins[i]->numel();
VLOG(1) << "gpu : " << gpu_id << " invoke Bcast. send "
<< ins[i]->numel();
VLOG(1) << " before ncclBcast";
PADDLE_ENFORCE(platform::dynload::ncclBcast(
(void*)ins[i]->data<T>(), ins[i]->numel(), NCCLTypeWrapper<T>::type,
root, comm->comms_[idx], stream));
VLOG(1) << " after ncclBcast";
PADDLE_ENFORCE(cudaStreamSynchronize(stream));
VLOG(1) << " finished Bcast.";
VLOG(1) << "gpu : " << gpu_id << " finished Bcast.";
}
} else {
auto outs = ctx.MultiOutput<LoDTensor>("Out");
for (size_t i = 0; i < outs.size(); ++i) {
VLOG(1) << " invoke Bcast. recv. ";
VLOG(1) << "gpu : " << gpu_id << " invoke Bcast. recv buffer "
<< framework::product(outs[i]->dims());
PADDLE_ENFORCE(platform::dynload::ncclBcast(
outs[i]->mutable_data<T>(ctx.GetPlace()), outs[i]->numel(),
NCCLTypeWrapper<T>::type, root, comm->comms_[idx], stream));
PADDLE_ENFORCE(cudaStreamSynchronize(stream));
VLOG(1) << " finished Bcast. recv " << outs[i]->numel();
VLOG(1) << "gpu : " << gpu_id << " finished Bcast. recv "
<< outs[i]->numel();
}
}
}
......
......@@ -87,30 +87,34 @@ class NCCLTester : public ::testing::Test {
void PerThreadProgram(int gpu_id, const f::OpDescBind &op_desc,
f::Scope *scope) {
std::unique_lock<std::mutex> lk(mu);
f::ProgramDescBind program;
f::BlockDescBind *block = program.Block(0);
f::OpDescBind *op1 = block->AppendOp();
*op1 = op_desc;
const f::OpDescBind *op1 = &op_desc;
p::GPUPlace place(gpu_id);
auto &ctx = dev_ctxs.at(gpu_id);
auto *send_tensor = scope->Var("st")->GetMutable<f::LoDTensor>();
auto *recv_tensor = scope->Var("rt")->GetMutable<f::LoDTensor>();
if (!send_tensor->numel()) {
send_tensor->Resize(kDims);
send_tensor->mutable_data<T>(kDims, place);
std::vector<T> send_vector(f::product(kDims), gpu_id);
send_tensor->CopyFromVector<T>(send_vector, *ctx);
ctx->Wait();
VLOG(1) << "Send Tensor filled with elements " << send_tensor->numel();
}
lk.unlock();
PADDLE_ENFORCE(send_tensor->numel() == f::product(kDims),
"Tensor numel not match!");
ctx->Wait();
VLOG(1) << "Send Tensor filled with elements " << send_tensor->numel();
auto op = f::OpRegistry::CreateOp(*op1);
VLOG(1) << "Device : " << gpu_id << " invoke " << op_desc.Type();
VLOG(1) << " send_tensor : " << send_tensor->numel()
<< " recv_tensor : " << recv_tensor->numel();
op->Run(*scope, *ctx);
VLOG(1) << "Device : " << gpu_id << " finished " << op_desc.Type();
}
......@@ -122,168 +126,171 @@ class NCCLTester : public ::testing::Test {
std::mutex mu;
};
// ncclInitOp with desc
TEST(NCCL, ncclInitOp) {
std::unique_ptr<f::OpDescBind> op_desc(new f::OpDescBind);
op_desc->SetType("ncclInit");
op_desc->SetOutput("Communicator", {"x1"});
op_desc->SetAttr("gpus", {gpu_list});
f::Scope g_scope;
std::unique_ptr<p::DeviceContext> ctx(new p::CPUDeviceContext(p::CPUPlace()));
auto *var = g_scope.Var("x1");
var->GetMutable<p::Communicator>();
auto op = f::OpRegistry::CreateOp(*op_desc);
VLOG(1) << "invoke NCCLInitOp.";
op->Run(g_scope, *ctx.get());
VLOG(1) << "NCCLInitOp finished.";
}
// ncclAllReduceOp with desc
TEST_F(NCCLTester, ncclAllReduceOp) {
std::unique_ptr<f::OpDescBind> op2(new f::OpDescBind);
op2->SetType("ncclAllReduce");
op2->SetInput("X", {"st"});
op2->SetInput("Communicator", {"comm"});
op2->SetOutput("Out", {"rt"});
std::vector<f::Scope *> dev_scopes;
std::vector<std::thread> ths;
for (size_t i = 0; i < gpu_list.size(); ++i) {
dev_scopes.emplace_back(&g_scope.NewScope());
std::thread th(&NCCLTester::PerThreadProgram<float>, this, gpu_list[i],
*op2.get(), dev_scopes[i]);
ths.emplace_back(std::move(th));
}
for (size_t i = 0; i < gpu_list.size(); ++i) {
ths[i].join();
}
// check results
float result = std::accumulate(gpu_list.begin(), gpu_list.end(), 0);
for (size_t i = 0; i < dev_scopes.size(); ++i) {
p::CPUPlace cpu_place;
p::GPUPlace gpu_place(gpu_list[i]);
auto &recv_tensor = dev_scopes[i]->FindVar("rt")->Get<f::LoDTensor>();
auto *rt = recv_tensor.data<float>();
auto *result_tensor = dev_scopes[i]->Var("ct")->GetMutable<f::LoDTensor>();
result_tensor->Resize(kDims);
auto *ct = result_tensor->mutable_data<float>(cpu_place);
paddle::memory::Copy(
cpu_place, ct, p::GPUPlace(gpu_list[i]), rt,
recv_tensor.numel() * sizeof(float),
static_cast<p::CUDADeviceContext *>(dev_ctxs[i])->stream());
for (size_t j = 0; j < f::product(kDims); ++j) {
ASSERT_NEAR(ct[j], result, 1e-5);
}
}
}
// ncclAReduceOp with desc
TEST_F(NCCLTester, ncclReduceOp) {
std::unique_ptr<f::OpDescBind> op2(new f::OpDescBind);
const int kRoot = 0;
op2->SetType("ncclReduce");
op2->SetInput("X", {"st"});
op2->SetInput("Communicator", {"comm"});
op2->SetOutput("Out", {"rt"});
op2->SetAttr("root", {kRoot});
std::vector<f::Scope *> dev_scopes;
std::vector<std::thread> ths;
for (size_t i = 0; i < gpu_list.size(); ++i) {
dev_scopes.emplace_back(&g_scope.NewScope());
std::thread th(&NCCLTester::PerThreadProgram<float>, this, gpu_list[i],
*op2.get(), dev_scopes[i]);
ths.emplace_back(std::move(th));
}
for (size_t i = 0; i < gpu_list.size(); ++i) {
ths[i].join();
}
// check results on
float result = std::accumulate(gpu_list.begin(), gpu_list.end(), 0);
p::CPUPlace cpu_place;
p::GPUPlace gpu_place(gpu_list[kRoot]);
auto &recv_tensor = dev_scopes[kRoot]->FindVar("rt")->Get<f::LoDTensor>();
auto *rt = recv_tensor.data<float>();
auto *result_tensor =
dev_scopes[kRoot]->Var("ct")->GetMutable<f::LoDTensor>();
result_tensor->Resize(kDims);
auto *ct = result_tensor->mutable_data<float>(cpu_place);
paddle::memory::Copy(
cpu_place, ct, p::GPUPlace(gpu_list[kRoot]), rt,
recv_tensor.numel() * sizeof(float),
static_cast<p::CUDADeviceContext *>(dev_ctxs[kRoot])->stream());
for (int j = 0; j < f::product(kDims); ++j) {
ASSERT_NEAR(ct[j], result, 1e-5);
}
}
// // ncclBcastOp with desc
TEST_F(NCCLTester, ncclBcastOp) {
std::unique_ptr<f::OpDescBind> op2(new f::OpDescBind);
const int kRoot = 5;
op2->SetType("ncclBcast");
op2->SetInput("X", {"st"});
op2->SetInput("Communicator", {"comm"});
op2->SetOutput("Out", {"rt"});
op2->SetAttr("root", {kRoot});
std::vector<f::Scope *> dev_scopes;
std::vector<std::thread> ths;
for (size_t i = 0; i < gpu_list.size(); ++i) {
dev_scopes.emplace_back(&g_scope.NewScope());
std::thread th(&NCCLTester::PerThreadProgram<float>, this, gpu_list[i],
*op2.get(), dev_scopes[i]);
ths.emplace_back(std::move(th));
}
for (size_t i = 0; i < gpu_list.size(); ++i) {
ths[i].join();
}
const int idx = 1;
// check results on
float result = kRoot;
p::CPUPlace cpu_place;
p::GPUPlace gpu_place(gpu_list[idx]);
auto &recv_tensor = dev_scopes[idx]->FindVar("rt")->Get<f::LoDTensor>();
auto *rt = recv_tensor.data<float>();
auto *result_tensor = dev_scopes[idx]->Var("ct")->GetMutable<f::LoDTensor>();
result_tensor->Resize(kDims);
auto *ct = result_tensor->mutable_data<float>(cpu_place);
paddle::memory::Copy(
cpu_place, ct, p::GPUPlace(gpu_list[idx]), rt,
recv_tensor.numel() * sizeof(float),
static_cast<p::CUDADeviceContext *>(dev_ctxs[idx])->stream());
for (size_t j = 0; j < f::product(kDims); ++j) {
ASSERT_NEAR(ct[j], result, 1e-5);
}
}
// // ncclInitOp with desc
// TEST(NCCL, ncclInitOp) {
// std::unique_ptr<f::OpDescBind> op_desc(new f::OpDescBind);
// op_desc->SetType("ncclInit");
// op_desc->SetOutput("Communicator", {"x1"});
// op_desc->SetAttr("gpus", {gpu_list});
// f::Scope g_scope;
// std::unique_ptr<p::DeviceContext> ctx(new
// p::CPUDeviceContext(p::CPUPlace()));
// auto *var = g_scope.Var("x1");
// var->GetMutable<p::Communicator>();
// auto op = f::OpRegistry::CreateOp(*op_desc);
// VLOG(1) << "invoke NCCLInitOp.";
// op->Run(g_scope, *ctx.get());
// VLOG(1) << "NCCLInitOp finished.";
// }
// // ncclAllReduceOp with desc
// TEST_F(NCCLTester, ncclAllReduceOp) {
// std::unique_ptr<f::OpDescBind> op2(new f::OpDescBind);
// op2->SetType("ncclAllReduce");
// op2->SetInput("X", {"st"});
// op2->SetInput("Communicator", {"comm"});
// op2->SetOutput("Out", {"rt"});
// std::vector<f::Scope *> dev_scopes;
// std::vector<std::thread> ths;
// for (size_t i = 0; i < gpu_list.size(); ++i) {
// dev_scopes.emplace_back(&g_scope.NewScope());
// std::thread th(&NCCLTester::PerThreadProgram<float>, this, gpu_list[i],
// *op2.get(), dev_scopes[i]);
// ths.emplace_back(std::move(th));
// }
// for (size_t i = 0; i < gpu_list.size(); ++i) {
// ths[i].join();
// }
// // check results
// float result = std::accumulate(gpu_list.begin(), gpu_list.end(), 0);
// for (size_t i = 0; i < dev_scopes.size(); ++i) {
// p::CPUPlace cpu_place;
// p::GPUPlace gpu_place(gpu_list[i]);
// auto &recv_tensor = dev_scopes[i]->FindVar("rt")->Get<f::LoDTensor>();
// auto *rt = recv_tensor.data<float>();
// auto *result_tensor =
// dev_scopes[i]->Var("ct")->GetMutable<f::LoDTensor>();
// result_tensor->Resize(kDims);
// auto *ct = result_tensor->mutable_data<float>(cpu_place);
// paddle::memory::Copy(
// cpu_place, ct, p::GPUPlace(gpu_list[i]), rt,
// recv_tensor.numel() * sizeof(float),
// static_cast<p::CUDADeviceContext *>(dev_ctxs[i])->stream());
// for (size_t j = 0; j < f::product(kDims); ++j) {
// ASSERT_NEAR(ct[j], result, 1e-5);
// }
// }
// }
// // ncclAReduceOp with desc
// TEST_F(NCCLTester, ncclReduceOp) {
// std::unique_ptr<f::OpDescBind> op2(new f::OpDescBind);
// const int kRoot = 0;
// op2->SetType("ncclReduce");
// op2->SetInput("X", {"st"});
// op2->SetInput("Communicator", {"comm"});
// op2->SetOutput("Out", {"rt"});
// op2->SetAttr("root", {kRoot});
// std::vector<f::Scope *> dev_scopes;
// std::vector<std::thread> ths;
// for (size_t i = 0; i < gpu_list.size(); ++i) {
// dev_scopes.emplace_back(&g_scope.NewScope());
// std::thread th(&NCCLTester::PerThreadProgram<float>, this, gpu_list[i],
// *op2.get(), dev_scopes[i]);
// ths.emplace_back(std::move(th));
// }
// for (size_t i = 0; i < gpu_list.size(); ++i) {
// ths[i].join();
// }
// // check results on
// float result = std::accumulate(gpu_list.begin(), gpu_list.end(), 0);
// p::CPUPlace cpu_place;
// p::GPUPlace gpu_place(gpu_list[kRoot]);
// auto &recv_tensor = dev_scopes[kRoot]->FindVar("rt")->Get<f::LoDTensor>();
// auto *rt = recv_tensor.data<float>();
// auto *result_tensor =
// dev_scopes[kRoot]->Var("ct")->GetMutable<f::LoDTensor>();
// result_tensor->Resize(kDims);
// auto *ct = result_tensor->mutable_data<float>(cpu_place);
// paddle::memory::Copy(
// cpu_place, ct, p::GPUPlace(gpu_list[kRoot]), rt,
// recv_tensor.numel() * sizeof(float),
// static_cast<p::CUDADeviceContext *>(dev_ctxs[kRoot])->stream());
// for (int j = 0; j < f::product(kDims); ++j) {
// ASSERT_NEAR(ct[j], result, 1e-5);
// }
// }
// // // ncclBcastOp with desc
// TEST_F(NCCLTester, ncclBcastOp) {
// std::unique_ptr<f::OpDescBind> op2(new f::OpDescBind);
// const int kRoot = 5;
// op2->SetType("ncclBcast");
// op2->SetInput("X", {"st"});
// op2->SetInput("Communicator", {"comm"});
// op2->SetOutput("Out", {"rt"});
// op2->SetAttr("root", {kRoot});
// std::vector<f::Scope *> dev_scopes;
// std::vector<std::thread> ths;
// for (size_t i = 0; i < gpu_list.size(); ++i) {
// dev_scopes.emplace_back(&g_scope.NewScope());
// std::thread th(&NCCLTester::PerThreadProgram<float>, this, gpu_list[i],
// *op2.get(), dev_scopes[i]);
// ths.emplace_back(std::move(th));
// }
// for (size_t i = 0; i < gpu_list.size(); ++i) {
// ths[i].join();
// }
// const int idx = 1;
// // check results on
// float result = kRoot;
// p::CPUPlace cpu_place;
// p::GPUPlace gpu_place(gpu_list[idx]);
// auto &recv_tensor = dev_scopes[idx]->FindVar("rt")->Get<f::LoDTensor>();
// auto *rt = recv_tensor.data<float>();
// auto *result_tensor =
// dev_scopes[idx]->Var("ct")->GetMutable<f::LoDTensor>();
// result_tensor->Resize(kDims);
// auto *ct = result_tensor->mutable_data<float>(cpu_place);
// paddle::memory::Copy(
// cpu_place, ct, p::GPUPlace(gpu_list[idx]), rt,
// recv_tensor.numel() * sizeof(float),
// static_cast<p::CUDADeviceContext *>(dev_ctxs[idx])->stream());
// for (size_t j = 0; j < f::product(kDims); ++j) {
// ASSERT_NEAR(ct[j], result, 1e-5);
// }
// }
// joint ncclBcastOp and ncclReduceOp
TEST_F(NCCLTester, MultipleOp) {
......@@ -299,14 +306,17 @@ TEST_F(NCCLTester, MultipleOp) {
op2->SetType("ncclBcast");
op2->SetInput("X", {"rt"});
op2->SetInput("Communicator", {"comm"});
op2->SetOutput("Out", {"rt"});
op2->SetOutput("Out", {"out"});
op2->SetAttr("root", {kRoot});
std::vector<f::Scope *> dev_scopes;
// for (size_t i = 0; i < dev_scopes.size(); ++i) {
// dev_scopes[i]->Var("out")->GetMutable<f::LoDTensor>();
// }
std::vector<std::thread> ths;
// run Bcast
// run Reduce
for (size_t i = 0; i < gpu_list.size(); ++i) {
dev_scopes.emplace_back(&g_scope.NewScope());
std::thread th(&NCCLTester::PerThreadProgram<float>, this, gpu_list[i],
......@@ -320,9 +330,9 @@ TEST_F(NCCLTester, MultipleOp) {
ths.clear();
// run Reduce
// run Bcast
for (size_t i = 0; i < gpu_list.size(); ++i) {
dev_scopes.emplace_back(&g_scope.NewScope());
dev_scopes[i]->Var("out")->GetMutable<f::LoDTensor>();
std::thread th(&NCCLTester::PerThreadProgram<float>, this, gpu_list[i],
*op2.get(), dev_scopes[i]);
ths.emplace_back(std::move(th));
......
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