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#include <gtest/gtest.h>
#include <c10/util/irange.h>
#include <tensorpipe/common/cpu_buffer.h>
#include <tensorpipe/core/message.h>
#include <torch/csrc/distributed/rpc/tensorpipe_utils.h>
#include <torch/torch.h>
#include <memory>
#include <string>
#include <vector>
TEST(TensorpipeSerialize, Base) {
// Sender serializes
at::Tensor t1 = torch::ones({1024}, at::ScalarType::Int);
at::Tensor t2 = torch::ones({1024}, at::ScalarType::Float);
std::vector<at::Tensor> tensors{t1, t2};
std::vector<char> payload = {'1', '2', '3'};
std::vector<char> payloadCopy = payload; // for testing
torch::distributed::rpc::MessageType mtype =
torch::distributed::rpc::MessageType::UNKNOWN;
int64_t mId = 100;
auto sendingRpcMessage =
c10::make_intrusive<torch::distributed::rpc::Message>(
std::move(payload), std::move(tensors), mtype);
sendingRpcMessage->setId(mId);
tensorpipe::Message sendingTpMessage;
torch::distributed::rpc::TensorpipeWriteBuffers sendingTpBuffers;
std::tie(sendingTpMessage, sendingTpBuffers) =
torch::distributed::rpc::tensorpipeSerialize(
std::move(sendingRpcMessage), {}, {});
// Mimic receiving message descriptor: recvingTpDescriptor is a copy of
// sendingTpMessage except for the data pointers which are left null.
tensorpipe::Descriptor recvingTpDescriptor;
recvingTpDescriptor.metadata = sendingTpMessage.metadata;
recvingTpDescriptor.payloads.reserve(sendingTpMessage.payloads.size());
for (auto& tpPayload : sendingTpMessage.payloads) {
tensorpipe::Descriptor::Payload p;
p.length = tpPayload.length;
p.metadata = tpPayload.metadata;
recvingTpDescriptor.payloads.push_back(std::move(p));
}
EXPECT_EQ(
recvingTpDescriptor.payloads.size(), sendingTpMessage.payloads.size());
recvingTpDescriptor.tensors.reserve(sendingTpMessage.tensors.size());
for (auto& tpTensor : sendingTpMessage.tensors) {
tensorpipe::Descriptor::Tensor t;
t.length = tpTensor.length;
t.sourceDevice = tpTensor.buffer.device();
t.targetDevice = tpTensor.targetDevice;
t.metadata = tpTensor.metadata;
recvingTpDescriptor.tensors.push_back(std::move(t));
}
EXPECT_EQ(
recvingTpDescriptor.tensors.size(), sendingTpMessage.tensors.size());
// Mimic readDescriptor() callback:
// - Allocate buffers
// - Fill pointers in tensorpipe message
tensorpipe::Allocation recvingTpAllocation;
torch::distributed::rpc::TensorpipeReadBuffers recvingTpBuffers;
std::tie(recvingTpAllocation, recvingTpBuffers) =
torch::distributed::rpc::tensorpipeAllocate(recvingTpDescriptor, {});
// Mimic tensorpipe data transfer
EXPECT_EQ(
recvingTpAllocation.payloads.size(), sendingTpMessage.payloads.size());
for (const auto i : c10::irange(recvingTpAllocation.payloads.size())) {
tensorpipe::Message::Payload& srcPayload = sendingTpMessage.payloads[i];
tensorpipe::Allocation::Payload& dstPayload =
recvingTpAllocation.payloads[i];
if (srcPayload.length) {
// Empty vector's data() can return nullptr, use the length to avoid
// coying into nullptr
memcpy(dstPayload.data, srcPayload.data, srcPayload.length);
}
}
EXPECT_EQ(
recvingTpAllocation.tensors.size(), sendingTpMessage.tensors.size());
for (const auto i : c10::irange(recvingTpAllocation.tensors.size())) {
tensorpipe::Message::Tensor& srcTensor = sendingTpMessage.tensors[i];
tensorpipe::Allocation::Tensor& dstTensor = recvingTpAllocation.tensors[i];
memcpy(
dstTensor.buffer.unwrap<tensorpipe::CpuBuffer>().ptr,
srcTensor.buffer.unwrap<tensorpipe::CpuBuffer>().ptr,
srcTensor.length);
}
// Mimic read() callback:
// - Unpickle
c10::intrusive_ptr<torch::distributed::rpc::Message> recvingRpcMessage =
torch::distributed::rpc::tensorpipeDeserialize(
std::move(recvingTpDescriptor), std::move(recvingTpBuffers));
// Data is ready
EXPECT_EQ(mtype, recvingRpcMessage->type());
EXPECT_EQ(payloadCopy, recvingRpcMessage->payload());
EXPECT_EQ(mId, recvingRpcMessage->id());
EXPECT_TRUE(torch::equal(t1, recvingRpcMessage->tensors()[0]));
EXPECT_TRUE(torch::equal(t2, recvingRpcMessage->tensors()[1]));
}
TEST(TensorpipeSerialize, RecopySparseTensors) {
// Take a 1K row of a 1M tensors, and make sure we don't send across 1M rows.
constexpr size_t k1K = 1024;
at::Tensor main = torch::randn({k1K, k1K});
at::Tensor tiny = main.select(0, 2); // Select a row in the middle
EXPECT_EQ(tiny.numel(), k1K);
EXPECT_EQ(tiny.storage().nbytes() / tiny.itemsize(), k1K * k1K);
std::vector<at::Tensor> tensors{main, tiny};
std::vector<char> payload = {'1', '2', '3'};
torch::distributed::rpc::MessageType mtype =
torch::distributed::rpc::MessageType::UNKNOWN;
auto sendingRpcMessage =
c10::make_intrusive<torch::distributed::rpc::Message>(
std::move(payload), std::move(tensors), mtype);
tensorpipe::Message sendingTpMessage;
torch::distributed::rpc::TensorpipeWriteBuffers tpBuffers;
std::tie(sendingTpMessage, tpBuffers) =
torch::distributed::rpc::tensorpipeSerialize(
std::move(sendingRpcMessage), {}, {});
EXPECT_EQ(tpBuffers.tensors.size(), 2);
EXPECT_EQ(sendingTpMessage.tensors.size(), 2);
EXPECT_TRUE(torch::equal(main, tpBuffers.tensors[0]));
EXPECT_TRUE(torch::equal(tiny, tpBuffers.tensors[1]));
// Test cloned storage
EXPECT_EQ(
main.storage().data(),
sendingTpMessage.tensors[0].buffer.unwrap<tensorpipe::CpuBuffer>().ptr);
EXPECT_NE(
tiny.storage().data(),
sendingTpMessage.tensors[1].buffer.unwrap<tensorpipe::CpuBuffer>().ptr);
EXPECT_EQ(tiny.element_size() * k1K, sendingTpMessage.tensors[1].length);
}
TEST(TensorpipeSerialize, NoDeleterTensors) {
std::vector<float> blob1{.8, .2};
std::vector<float> blob2{.7, .5, .9};
at::Tensor t1 = torch::from_blob((float*)(blob1.data()), blob1.size());
at::Tensor t2 = torch::from_blob((float*)(blob2.data()), blob2.size());
std::vector<at::Tensor> tensors{t1, t2};
std::vector<char> payload = {'1', '2', '3'};
torch::distributed::rpc::MessageType mtype =
torch::distributed::rpc::MessageType::UNKNOWN;
auto sendingRpcMessage =
c10::make_intrusive<torch::distributed::rpc::Message>(
std::move(payload), std::move(tensors), mtype);
tensorpipe::Message sendingTpMessage;
torch::distributed::rpc::TensorpipeWriteBuffers tpBuffers;
std::tie(sendingTpMessage, tpBuffers) =
torch::distributed::rpc::tensorpipeSerialize(
std::move(sendingRpcMessage), {}, {});
EXPECT_EQ(tpBuffers.copiedTensors.size(), 2);
EXPECT_EQ(sendingTpMessage.tensors.size(), 2);
EXPECT_EQ(
tpBuffers.copiedTensors[0].size(), sendingTpMessage.tensors[0].length);
EXPECT_EQ(
tpBuffers.copiedTensors[1].size(), sendingTpMessage.tensors[1].length);
EXPECT_EQ(
tpBuffers.copiedTensors[0].data(),
sendingTpMessage.tensors[0].buffer.unwrap<tensorpipe::CpuBuffer>().ptr);
EXPECT_EQ(
tpBuffers.copiedTensors[1].data(),
sendingTpMessage.tensors[1].buffer.unwrap<tensorpipe::CpuBuffer>().ptr);
EXPECT_TRUE(
memcmp(
tpBuffers.copiedTensors[0].data(),
t1.storage().data(),
sendingTpMessage.tensors[0].length) == 0);
EXPECT_TRUE(
memcmp(
tpBuffers.copiedTensors[1].data(),
t2.storage().data(),
sendingTpMessage.tensors[1].length) == 0);
}
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