提交 76b4dd62 编写于 作者: F fengjiayi 提交者: GitHub

Merge pull request #2809 from Canpio/dev_add_tensor_interface

add tensor interfaces
......@@ -14,6 +14,7 @@ limitations under the License. */
#pragma once
#include <cstdint>
#include <memory>
#include <type_traits>
#include "paddle/framework/ddim.h"
......@@ -26,31 +27,65 @@ namespace framework {
class Tensor {
public:
Tensor() : offset_(0) {}
explicit Tensor(const DDim& dims) : dims_(dims), offset_(0) {}
template <typename T>
const T* data() const {
PADDLE_ENFORCE(holder_ != nullptr,
"Tensor::data must be called after Tensor::mutable_data.");
return static_cast<const T*>(holder_->Ptr());
PADDLE_ENFORCE(
holder_ != nullptr,
"Tenosr has not been initialized. Call Tensor::mutable_data first.");
return reinterpret_cast<const T*>(
reinterpret_cast<uintptr_t>(holder_->Ptr()) + offset_);
}
template <typename T, // must be POD types
typename std::enable_if<std::is_pod<T>::value>::type* = nullptr>
T* mutable_data(DDim dims, paddle::platform::Place place) {
dims_ = dims;
if (holder_ == nullptr ||
!(holder_->Place() ==
place) /* some versions of boost::variant don't have operator!= */
|| holder_->Size() < product(dims) * sizeof(T)) {
|| holder_->Size() < product(dims) * sizeof(T) + offset_) {
holder_.reset(new PlaceholderImpl<T>(place, product(dims) * sizeof(T)));
offset_ = 0;
}
return static_cast<T*>(holder_->Ptr());
return reinterpret_cast<T*>(reinterpret_cast<uintptr_t>(holder_->Ptr()) +
offset_);
}
template <typename T, // must be POD types
typename std::enable_if<std::is_pod<T>::value>::type* = nullptr>
T* mutable_data(DDim dims) {
return mutable_data<T>(dims, paddle::platform::get_place());
void ShareDataFrom(const Tensor& src) {
PADDLE_ENFORCE(src.holder_ != nullptr,
"Can not share data from an uninitialized tensor.");
holder_ = src.holder_;
dims_ = src.dims_;
offset_ = src.offset_;
}
Tensor Slice(const int& begin_idx, const int& end_idx) const {
PADDLE_ENFORCE(holder_ != nullptr,
"The sliced tenosr has not been initialized.");
PADDLE_ENFORCE(begin_idx >= 0 && end_idx <= dims_[0],
"Slice index is less than zero or out of bound.");
PADDLE_ENFORCE(begin_idx < end_idx,
"Begin index must be less than end index.");
PADDLE_ENFORCE(dims_[0] != 1, "Can not slice a tensor with dims_[0] = 1.");
std::vector<int> d = vectorize(dims_);
int base = 1;
for (size_t i = 1; i < d.size(); ++i) {
base *= d[i];
}
Tensor dst;
dst.holder_ = holder_;
dst.dims_ = dims_;
dst.dims_[0] = end_idx - begin_idx;
dst.offset_ = offset_ + begin_idx * base * holder_->TypeSize();
return dst;
}
DDim dims() const { return dims_; }
private:
// Placeholder hides type T, so it doesn't appear as a template
// parameter of Variable.
......@@ -59,6 +94,7 @@ class Tensor {
virtual void* Ptr() const = 0;
virtual paddle::platform::Place Place() const = 0;
virtual size_t Size() const = 0;
virtual size_t TypeSize() const = 0;
};
template <typename T>
......@@ -85,6 +121,7 @@ class Tensor {
virtual void* Ptr() const { return static_cast<void*>(ptr_.get()); }
virtual size_t Size() const { return size_; }
virtual paddle::platform::Place Place() const { return place_; }
virtual size_t TypeSize() const { return sizeof(T); }
std::unique_ptr<T, Deleter> ptr_;
paddle::platform::Place place_; // record the place of ptr_.
......@@ -92,6 +129,8 @@ class Tensor {
};
std::shared_ptr<Placeholder> holder_; // holds the memory block if allocated.
DDim dims_;
size_t offset_; // marks the begin of tensor data area.
};
} // namespace framework
......
......@@ -15,15 +15,27 @@
#include <gtest/gtest.h>
#include <string>
TEST(Tensor, ASSERT) {
paddle::framework::Tensor cpu_tensor;
TEST(Tensor, Dims) {
using namespace paddle::framework;
using namespace paddle::platform;
Tensor tt(make_ddim({2, 3, 4}));
DDim dims = tt.dims();
ASSERT_EQ(arity(dims), 3);
for (int i = 0; i < 3; ++i) {
EXPECT_EQ(i + 2, dims[i]);
}
}
TEST(Tensor, DataAssert) {
paddle::framework::Tensor src_tensor;
bool caught = false;
try {
const double* p __attribute__((unused)) = cpu_tensor.data<double>();
src_tensor.data<double>();
} catch (paddle::framework::EnforceNotMet err) {
caught = true;
std::string msg = "Tensor::data must be called after Tensor::mutable_data.";
std::string msg =
"Tenosr has not been initialized. Call Tensor::mutable_data first.";
const char* what = err.what();
for (size_t i = 0; i < msg.length(); ++i) {
ASSERT_EQ(what[i], msg[i]);
......@@ -32,54 +44,138 @@ TEST(Tensor, ASSERT) {
ASSERT_TRUE(caught);
}
/* mutable_data() is not tested at present
/* following tests are not available at present
because Memory::Alloc() and Memory::Free() have not been ready.
TEST(Tensor, MutableData) {
using namespace paddle::framework;
using namespace paddle::platform;
{
Tensor cpu_tensor;
Tensor src_tensor;
float* p1 = nullptr;
float* p2 = nullptr;
// initialization
p1 = cpu_tensor.mutable_data<float>(make_ddim({1, 2, 3}), CPUPlace());
p1 = src_tensor.mutable_data<float>(make_ddim({1, 2, 3}), CPUPlace());
EXPECT_NE(p1, nullptr);
// set cpu_tensor a new dim with large size
// set src_tensor a new dim with large size
// momery is supposed to be re-allocated
p2 = cpu_tensor.mutable_data<float>(make_ddim({3, 4}));
p2 = src_tensor.mutable_data<float>(make_ddim({3, 4}), CPUPlace());
EXPECT_NE(p2, nullptr);
EXPECT_NE(p1, p2);
// set cpu_tensor a new dim with same size
// set src_tensor a new dim with same size
// momery block is supposed to be unchanged
p1 = cpu_tensor.mutable_data<float>(make_ddim({2, 2, 3}));
p1 = src_tensor.mutable_data<float>(make_ddim({2, 2, 3}), CPUPlace());
EXPECT_EQ(p1, p2);
// set cpu_tensor a new dim with smaller size
// set src_tensor a new dim with smaller size
// momery block is supposed to be unchanged
p2 = cpu_tensor.mutable_data<float>(make_ddim({2, 2}));
p2 = src_tensor.mutable_data<float>(make_ddim({2, 2}), CPUPlace());
EXPECT_EQ(p1, p2);
}
{
Tensor gpu_tensor;
Tensor src_tensor;
float* p1 = nullptr;
float* p2 = nullptr;
// initialization
p1 = gpu_tensor.mutable_data<float>(make_ddim({1, 2, 3}), GPUPlace());
p1 = src_tensor.mutable_data<float>(make_ddim({1, 2, 3}), GPUPlace());
EXPECT_NE(p1, nullptr);
// set gpu_tensor a new dim with large size
// set src_tensor a new dim with large size
// momery is supposed to be re-allocated
p2 = gpu_tensor.mutable_data<float>(make_ddim({3, 4}));
p2 = src_tensor.mutable_data<float>(make_ddim({3, 4}), GPUPlace());
EXPECT_NE(p2, nullptr);
EXPECT_NE(p1, p2);
// set gpu_tensor a new dim with same size
// set src_tensor a new dim with same size
// momery block is supposed to be unchanged
p1 = gpu_tensor.mutable_data<float>(make_ddim({2, 2, 3}));
p1 = src_tensor.mutable_data<float>(make_ddim({2, 2, 3}), GPUPlace());
EXPECT_EQ(p1, p2);
// set gpu_tensor a new dim with smaller size
// set src_tensor a new dim with smaller size
// momery block is supposed to be unchanged
p2 = gpu_tensor.mutable_data<float>(make_ddim({2, 2}));
p2 = src_tensor.mutable_data<float>(make_ddim({2, 2}), GPUPlace());
EXPECT_EQ(p1, p2);
}
}
*/
TEST(Tensor, ShareDataFrom) {
using namespace paddle::framework;
using namespace paddle::platform;
{
Tensor src_tensor;
Tensor dst_tensor;
// Try to share data form uninitialized tensor
bool caught = false;
try {
dst_tensor.ShareDataFrom(src_tensor);
} catch (EnforceNotMet err) {
caught = true;
std::string msg = "Can not share data from an uninitialized tensor.";
const char* what = err.what();
for (size_t i = 0; i < msg.length(); ++i) {
ASSERT_EQ(what[i], msg[i]);
}
}
ASSERT_TRUE(caught);
src_tensor.mutable_data<int>(make_ddim({2, 3, 4}), CPUPlace());
dst_tensor.ShareDataFrom(src_tensor);
ASSERT_EQ(src_tensor.data<int>(), dst_tensor.data<int>());
}
{
Tensor src_tensor;
Tensor dst_tensor;
src_tensor.mutable_data<int>(make_ddim({2, 3, 4}), GPUPlace());
dst_tensor.ShareDataFrom(src_tensor);
ASSERT_EQ(src_tensor.data<int>(), dst_tensor.data<int>());
}
}
TEST(Tensor, Slice) {
using namespace paddle::framework;
using namespace paddle::platform;
{
Tensor src_tensor;
src_tensor.mutable_data<int>(make_ddim({5, 3, 4}), CPUPlace());
Tensor slice_tensor = src_tensor.Slice(1, 3);
DDim slice_dims = slice_tensor.dims();
ASSERT_EQ(arity(slice_dims), 3);
EXPECT_EQ(slice_dims[0], 2);
EXPECT_EQ(slice_dims[1], 3);
EXPECT_EQ(slice_dims[2], 4);
uintptr_t src_data_address =
reinterpret_cast<uintptr_t>(src_tensor.data<int>());
uintptr_t src_mutable_data_address = reinterpret_cast<uintptr_t>(
src_tensor.mutable_data<int>(src_tensor.dims(), CPUPlace()));
uintptr_t slice_data_address =
reinterpret_cast<uintptr_t>(slice_tensor.data<int>());
uintptr_t slice_mutable_data_address = reinterpret_cast<uintptr_t>(
slice_tensor.mutable_data<int>(slice_tensor.dims(), CPUPlace()));
EXPECT_EQ(src_data_address, src_mutable_data_address);
EXPECT_EQ(slice_data_address, slice_mutable_data_address);
EXPECT_EQ(src_data_address + 3 * 4 * 1 * sizeof(int), slice_data_address);
}
{
Tensor src_tensor;
src_tensor.mutable_data<double>(make_ddim({6, 9}), GPUPlace());
Tensor slice_tensor = src_tensor.Slice(2, 6);
DDim slice_dims = slice_tensor.dims();
ASSERT_EQ(arity(slice_dims), 2);
EXPECT_EQ(slice_dims[0], 4);
EXPECT_EQ(slice_dims[1], 9);
uintptr_t src_data_address =
reinterpret_cast<uintptr_t>(src_tensor.data<double>());
uintptr_t src_mutable_data_address = reinterpret_cast<uintptr_t>(
src_tensor.mutable_data<double>(src_tensor.dims(), GPUPlace()));
uintptr_t slice_data_address =
reinterpret_cast<uintptr_t>(slice_tensor.data<double>());
uintptr_t slice_mutable_data_address = reinterpret_cast<uintptr_t>(
slice_tensor.mutable_data<double>(slice_tensor.dims(), GPUPlace()));
EXPECT_EQ(src_data_address, src_mutable_data_address);
EXPECT_EQ(slice_data_address, slice_mutable_data_address);
EXPECT_EQ(src_data_address + 9 * 2 * sizeof(double), slice_data_address);
}
}
*/
\ No newline at end of file
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册