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Support TensorFormVector, TensorToVector of bool type (#31518)

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* support TensorFormVector, TensorToVector of bool type

* add ut

* fix compile problem
revert-31562-mean
Leo Chen 4 years ago committed by GitHub
parent 9df84bd693
commit 3f206e97c4
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GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 182 additions and 0 deletions
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127
paddle/fluid/framework/tensor_util.h
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@ -136,6 +136,7 @@ void TensorFromArray(const T* src, const size_t& array_size,
}
#endif
}
template <typename T>
void TensorFromVector(const std::vector<T>& src,
const platform::DeviceContext& ctx, Tensor* dst) {
@ -168,6 +169,49 @@ void TensorFromVector(const std::vector<T>& src,
#endif
}
// The fully specialized function should be inline to avoid
// multi-definition.
template <>
inline void TensorFromVector(const std::vector<bool>& src,
const platform::DeviceContext& ctx, Tensor* dst) {
// vector<bool> has no data() member, use array instead.
// See details:
// https://stackoverflow.com/questions/46115669/why-does-stdvectorbool-have-no-data/46115714
bool* array = new bool[src.size()];
for (unsigned int i = 0; i < src.size(); i++) {
array[i] = static_cast<bool>(src[i]);
}
auto dst_place = ctx.GetPlace();
auto src_ptr = static_cast<const void*>(array);
platform::CPUPlace src_place;
dst->Resize({static_cast<int64_t>(src.size())});
auto dst_ptr = static_cast<void*>(dst->mutable_data<bool>(dst_place));
auto size = src.size() * sizeof(bool);
if (platform::is_cpu_place(dst_place)) {
memory::Copy(BOOST_GET_CONST(platform::CPUPlace, dst_place), dst_ptr,
src_place, src_ptr, size);
}
#ifdef PADDLE_WITH_CUDA
else if (platform::is_gpu_place(dst_place)) { // NOLINT
memory::Copy(
BOOST_GET_CONST(platform::CUDAPlace, dst_place), dst_ptr, src_place,
src_ptr, size,
reinterpret_cast<const platform::CUDADeviceContext&>(ctx).stream());
}
#endif
#ifdef PADDLE_WITH_ASCEND_CL
else if (platform::is_npu_place(dst_place)) { // NOLINT
memory::Copy(
BOOST_GET_CONST(platform::NPUPlace, dst_place), dst_ptr, src_place,
src_ptr, size,
reinterpret_cast<const platform::NPUDeviceContext&>(ctx).stream());
}
#endif
delete[] array;
}
template <typename T>
void TensorFromVector(const std::vector<T>& src, Tensor* dst) {
platform::CPUPlace dst_place = platform::CPUPlace();
@ -180,6 +224,23 @@ void TensorFromVector(const std::vector<T>& src, Tensor* dst) {
memory::Copy(dst_place, dst_ptr, src_place, src_ptr, size);
}
template <>
inline void TensorFromVector(const std::vector<bool>& src, Tensor* dst) {
bool* array = new bool[src.size()];
for (unsigned int i = 0; i < src.size(); i++) {
array[i] = static_cast<bool>(src[i]);
}
platform::CPUPlace dst_place = platform::CPUPlace();
auto src_ptr = static_cast<const void*>(array);
platform::CPUPlace src_place;
dst->Resize({static_cast<int64_t>(src.size())});
auto dst_ptr = static_cast<void*>(dst->mutable_data<bool>(dst_place));
auto size = src.size() * sizeof(bool);
memory::Copy(dst_place, dst_ptr, src_place, src_ptr, size);
delete[] array;
}
template <typename T>
void TensorToVector(const Tensor& src, const platform::DeviceContext& ctx,
std::vector<T>* dst) {
@ -213,6 +274,46 @@ void TensorToVector(const Tensor& src, const platform::DeviceContext& ctx,
#endif
}
template <>
inline void TensorToVector(const Tensor& src,
const platform::DeviceContext& ctx,
std::vector<bool>* dst) {
auto src_ptr = static_cast<const void*>(src.data<bool>());
auto size = src.numel() * sizeof(bool);
bool* array = new bool[src.numel()];
platform::CPUPlace dst_place;
dst->resize(src.numel());
auto dst_ptr = static_cast<void*>(array);
if (platform::is_cpu_place(src.place())) {
memory::Copy(dst_place, dst_ptr,
BOOST_GET_CONST(platform::CPUPlace, src.place()), src_ptr,
size);
}
#ifdef PADDLE_WITH_CUDA
else if (platform::is_gpu_place(src.place())) { // NOLINT
memory::Copy(
dst_place, dst_ptr, BOOST_GET_CONST(platform::CUDAPlace, src.place()),
src_ptr, size,
reinterpret_cast<const platform::CUDADeviceContext&>(ctx).stream());
}
#endif
#ifdef PADDLE_WITH_ASCEND_CL
else if (platform::is_npu_place(src.place())) { // NOLINT
memory::Copy(
dst_place, dst_ptr, BOOST_GET_CONST(platform::NPUPlace, src.place()),
src_ptr, size,
reinterpret_cast<const platform::NPUDeviceContext&>(ctx).stream());
}
#endif
for (unsigned int i = 0; i < src.numel(); i++) {
(*dst)[i] = static_cast<bool>(array[i]);
}
delete[] array;
}
template <typename T>
void TensorToVector(const Tensor& src, std::vector<T>* dst) {
auto src_ptr = static_cast<const void*>(src.data<T>());
@ -232,6 +333,32 @@ void TensorToVector(const Tensor& src, std::vector<T>* dst) {
BOOST_GET_CONST(platform::CPUPlace, src.place()), src_ptr, size);
}
template <>
inline void TensorToVector(const Tensor& src, std::vector<bool>* dst) {
auto src_ptr = static_cast<const void*>(src.data<bool>());
auto size = src.numel() * sizeof(bool);
bool* array = new bool[src.numel()];
platform::CPUPlace dst_place;
dst->resize(src.numel());
auto dst_ptr = static_cast<void*>(array);
PADDLE_ENFORCE_EQ(
platform::is_cpu_place(src.place()), true,
platform::errors::InvalidArgument(
"The input tensor should be CPU device, but actually it is in %s.",
src.place()));
memory::Copy(dst_place, dst_ptr,
BOOST_GET_CONST(platform::CPUPlace, src.place()), src_ptr, size);
for (unsigned int i = 0; i < src.numel(); i++) {
(*dst)[i] = static_cast<bool>(array[i]);
}
delete[] array;
}
std::ostream& operator<<(std::ostream& os, const Tensor& t);
} // namespace framework
} // namespace paddle

55
paddle/fluid/framework/tensor_util_test.cc
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@ -242,6 +242,61 @@ TEST(TensorToVector, Tensor) {
#endif
}
TEST(TensorToVector, Tensor_bool) {
{
paddle::framework::Tensor src;
bool* src_ptr =
src.mutable_data<bool>({3, 3}, paddle::platform::CPUPlace());
for (int i = 0; i < 3 * 3; ++i) {
src_ptr[i] = static_cast<bool>(i % 2);
}
paddle::platform::CPUPlace place;
std::vector<bool> dst;
paddle::framework::TensorToVector<bool>(src, &dst);
for (int i = 0; i < 3 * 3; ++i) {
EXPECT_EQ(src_ptr[i], dst[i]);
}
}
#ifdef PADDLE_WITH_CUDA
{
std::vector<bool> src_vec = {
false, true, false, true, false, true, false, true, false,
};
paddle::framework::Tensor gpu_tensor;
paddle::platform::CUDAPlace place;
paddle::platform::CUDADeviceContext gpu_ctx(place);
paddle::framework::TensorFromVector<bool>(src_vec, gpu_ctx, &gpu_tensor);
std::vector<bool> dst;
paddle::framework::TensorToVector<bool>(gpu_tensor, gpu_ctx, &dst);
for (int i = 0; i < 3 * 3; ++i) {
EXPECT_EQ(src_vec[i], dst[i]);
}
}
#endif
#ifdef PADDLE_WITH_ASCEND_CL
{
std::vector<bool> src_vec = {
false, true, false, true, false, true, false, true, false,
};
paddle::framework::Tensor npu_tensor;
paddle::platform::NPUPlace place(0);
paddle::platform::NPUDeviceContext npu_ctx(place);
paddle::framework::TensorFromVector<bool>(src_vec, npu_ctx, &npu_tensor);
std::vector<bool> dst;
paddle::framework::TensorToVector<bool>(npu_tensor, npu_ctx, &dst);
for (int i = 0; i < 3 * 3; ++i) {
EXPECT_EQ(src_vec[i], dst[i]);
}
}
#endif
}
TEST(TensorFromDLPack, Tensor) {
{
std::vector<int> src_vec = {1, 2, 3, 4, 5, 6, 7, 8, 9};

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