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【HACKATHON 10th ERNIE with Partners No.29】[Metax] update utils.cc #2497

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【HACKATHON 10th ERNIE with Partners No.29】[Metax] update utils.cc #2497

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74 changes: 37 additions & 37 deletions backends/metax_gpu/common/utils.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -104,17 +104,17 @@ C_Status AsyncMemCpyD2D(const C_Device device,

template <typename Context>
inline void TensorCopy(const Context& dev_ctx,
const phi::DenseTensor& src,
const DenseTensor& src,
bool blocking,
phi::DenseTensor* dst,
const phi::Place& dst_place = phi::CustomPlace()) {
DenseTensor* dst,
const Place& dst_place = CustomPlace()) {
auto* src_ptr = src.data();
const auto& src_place = src.place();
if (src_ptr == nullptr) {
return;
}
auto dst_place_ = dst_place;
if (dst_place_.GetType() != phi::AllocationType::CPU) {
if (dst_place_.GetType() != AllocationType::CPU) {
dst_place_ = dev_ctx.GetPlace();
}

Expand All @@ -125,7 +125,7 @@ inline void TensorCopy(const Context& dev_ctx,
} else {
VLOG(6) << "Src and dst are the same Tensor, in-place copy data("
<< src_ptr << ") from " << src_place << " to " << dst_place_;
const phi::DenseTensor src_copy = src;
const DenseTensor src_copy = src;
TensorCopy(dev_ctx, src_copy, blocking, dst, dst_place_);
}
return;
Expand All @@ -134,7 +134,7 @@ inline void TensorCopy(const Context& dev_ctx,
auto dst_dims = dst->dims();
dst->Resize(src.dims());
void* dst_ptr = nullptr;
if (dst_place_.GetType() != phi::AllocationType::CPU) {
if (dst_place_.GetType() != AllocationType::CPU) {
dst_ptr = dev_ctx.Alloc(dst, src.dtype());
} else {
dst_ptr = dev_ctx.HostAlloc(dst, src.dtype());
Expand All @@ -156,7 +156,7 @@ inline void TensorCopy(const Context& dev_ctx,
return;
} else {
// scatter memory
phi::DenseTensor tmp_dst;
DenseTensor tmp_dst;
tmp_dst.set_meta(dst->meta());
tmp_dst.Resize(dst_dims);
dst_ptr = dev_ctx.Alloc(&tmp_dst, tmp_dst.dtype());
Expand All @@ -176,26 +176,26 @@ inline void TensorCopy(const Context& dev_ctx,
return;
}

if (src_place.GetType() == phi::AllocationType::CPU &&
dst_place_.GetType() == phi::AllocationType::CUSTOM) {
if (src_place.GetType() == AllocationType::CPU &&
dst_place_.GetType() == AllocationType::CUSTOM) {
VLOG(6) << "TensorCopy from cpu to cus";
C_Device_st device;
device.id = dst_place_.GetDeviceId();
AsyncMemCpyH2D(&device, stream, dst_ptr, src_ptr, size);
if (blocking) {
dev_ctx.Wait();
}
} else if (src_place.GetType() == phi::AllocationType::CUSTOM &&
dst_place_.GetType() == phi::AllocationType::CPU) {
} else if (src_place.GetType() == AllocationType::CUSTOM &&
dst_place_.GetType() == AllocationType::CPU) {
VLOG(6) << "TensorCopy from cus to cpu";
C_Device_st device;
device.id = src_place.GetDeviceId();
AsyncMemCpyD2H(&device, stream, dst_ptr, src_ptr, size);
if (blocking) {
dev_ctx.Wait();
}
} else if (src_place.GetType() == phi::AllocationType::CUSTOM &&
dst_place_.GetType() == phi::AllocationType::CUSTOM) {
} else if (src_place.GetType() == AllocationType::CUSTOM &&
dst_place_.GetType() == AllocationType::CUSTOM) {
VLOG(6) << "TensorCopy from cus to cus";
if (src_place.GetDeviceType() == dst_place_.GetDeviceType()) {
if (src_place.GetDeviceId() == dst_place_.GetDeviceId()) {
Expand All @@ -212,26 +212,26 @@ inline void TensorCopy(const Context& dev_ctx,
} else {
PADDLE_THROW(phi::errors::Unimplemented("TensorCopy is not supported."));
}
} else if (src_place.GetType() == phi::AllocationType::CPU &&
dst_place_.GetType() == phi::AllocationType::CPU) {
} else if (src_place.GetType() == AllocationType::CPU &&
dst_place_.GetType() == AllocationType::CPU) {
VLOG(6) << "TensorCopy from cpu to cpu";
std::memcpy(dst_ptr, src_ptr, size);
}
}

template <typename T = float>
std::ostream& PrintTensor(std::ostream& os, const phi::DenseTensor& tensor) {
phi::DenseTensor cpu_tensor;
if (tensor.place().GetType() != phi::AllocationType::CPU) {
auto dev_ctx = static_cast<const phi::CustomContext*>(
phi::DeviceContextPool::Instance().Get(tensor.place()));
TensorCopy(*dev_ctx, tensor, true, &cpu_tensor, phi::CPUPlace());
std::ostream& PrintTensor(std::ostream& os, const DenseTensor& tensor) {
DenseTensor cpu_tensor;
if (tensor.place().GetType() != AllocationType::CPU) {
auto dev_ctx = static_cast<const CustomContext*>(
DeviceContextPool::Instance().Get(tensor.place()));
TensorCopy(*dev_ctx, tensor, true, &cpu_tensor, CPUPlace());
} else {
cpu_tensor = tensor;
}
os << "DenseTensor<";
if (tensor.initialized()) {
os << phi::DataTypeToString(tensor.dtype()) << ", ";
os << DataTypeToString(tensor.dtype()) << ", ";
os << tensor.place() << ", ";
os << "Shape(" << tensor.dims() << "), ";
os << "Strides(" << tensor.strides() << "), ";
Expand Down Expand Up @@ -266,27 +266,27 @@ std::ostream& PrintTensor(std::ostream& os, const phi::DenseTensor& tensor) {
}
} // namespace

#define FOR_EACH_DATA_TYPE_TO_PRINT(_) \
_(bool, phi::DataType::BOOL) \
_(int8_t, phi::DataType::INT8) \
_(uint8_t, phi::DataType::UINT8) \
_(int16_t, phi::DataType::INT16) \
_(uint16_t, phi::DataType::UINT16) \
_(int32_t, phi::DataType::INT32) \
_(uint32_t, phi::DataType::UINT32) \
_(int64_t, phi::DataType::INT64) \
_(uint64_t, phi::DataType::UINT64) \
_(phi::bfloat16, phi::DataType::BFLOAT16) \
_(phi::float16, phi::DataType::FLOAT16) \
_(float, phi::DataType::FLOAT32) \
_(double, phi::DataType::FLOAT64)
#define FOR_EACH_DATA_TYPE_TO_PRINT(_) \
_(bool, DataType::BOOL) \
_(int8_t, DataType::INT8) \
_(uint8_t, DataType::UINT8) \
_(int16_t, DataType::INT16) \
_(uint16_t, DataType::UINT16) \
_(int32_t, DataType::INT32) \
_(uint32_t, DataType::UINT32) \
_(int64_t, DataType::INT64) \
_(uint64_t, DataType::UINT64) \
_(bfloat16, DataType::BFLOAT16) \
_(float16, DataType::FLOAT16) \
_(float, DataType::FLOAT32) \
_(double, DataType::FLOAT64)

#define CALL_PRINT_TENSOR(cpp_type, data_type) \
case data_type: \
PrintTensor<cpp_type>(os, t); \
break;

std::ostream& operator<<(std::ostream& os, const phi::DenseTensor& t) {
std::ostream& operator<<(std::ostream& os, const DenseTensor& t) {
switch (t.dtype()) {
FOR_EACH_DATA_TYPE_TO_PRINT(CALL_PRINT_TENSOR)
default:
Expand Down
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