Add cast api && Change copy related api to copy_to && add more test (#4)

* fix compile error * wrap framework tensor with LoDTensor * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * add CustomTensor default constructor * add size() for CustomTensor * make size const for CustomTensor * refactor place related api to circle the concept * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * fix compile error * make place const * make Tensor copy * debug CustomTensor core * debug CustomTensor core * debug CustomTensor core * debug CustomTensor core * debug CustomTensor core * debug CustomTensor core * debug CustomTensor core * debug CustomTensor core * debug CustomTensor core * debug CustomTensor core * debug CustomTensor core * debug CustomTensor core * debug CustomTensor core * debug CustomTensor core * remove additional head of framework * use back to shared ptr for custom tensor * use back to shared ptr for custom tensor * use back to shared ptr for custom tensor * use back to shared ptr for custom tensor * use back to shared ptr for custom tensor * use back to shared ptr for custom tensor * add gpu test * merge latest cwh code in * adjust ut code of custom op * adjust ut code of custom op * adjust ut code of custom op * adjust ut code of custom op * adjust ut code of custom op * hid share data from and to * rename CustomTensor to Tensor * support multi dtype * remove lod, make reshape lowercase, add copy test and refactor copy api * remove lod, make reshape lowercase, add copy test and refactor copy api * remove lod, make reshape lowercase, add copy test and refactor copy api * remove lod, make reshape lowercase, add copy test and refactor copy api * fix copy to error * add more test * add more test * add more test * add more test * add more test * add more test * add more test * add more test * add more test * add more test * add more test * add more test * add more test * add more test * add more test * add more test * add type cast * add cast and make copy to api * add cast and make copy to api * add cast and make copy to api * add cast and make copy to api * merge cwh code * merge cwh code * merge cwh code * merge cwh code * merge cwh code * add more error log * add more error log * polish code * used for test * remove test comment * remove test comment
chenwhql · Feb 8, 2021 · e5cc53b · e5cc53b
1 parent 8dc6c94
commit e5cc53b
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Showing 7 changed files with 350 additions and 210 deletions.
diff --git a/paddle/fluid/extension/include/dtype.h b/paddle/fluid/extension/include/dtype.h
@@ -32,6 +32,7 @@ enum DataType {
   INT16,
   UINT8,
   INT8,
+  BOOL,
   // TODO(JiabinYang) support more data types if needed.
 };
 

diff --git a/paddle/fluid/extension/include/tensor.h b/paddle/fluid/extension/include/tensor.h
@@ -59,17 +59,11 @@ class Tensor {
 
   /// \brief Copy the host memory to tensor data.
   /// It's usually used to set the input tensor data.
-  /// \param data The pointer of the data, from which
+  /// \param PlaceType of target place, from which
   /// the tensor will copy.
-  template <typename T>
-  Tensor copy_to_gpu();
 
-  /// \brief Copy the tensor data to the host memory.
-  /// It's usually used to get the output tensor data.
-  /// \param[out] data The tensor will copy the data to
-  /// the address.
   template <typename T>
-  Tensor copy_to_cpu();
+  Tensor copy_to(const PlaceType& place);
 
   /// \brief Return the shape of the Tensor.
   std::vector<int> shape() const;
@@ -89,6 +83,9 @@ class Tensor {
   /// \return Place.
   const PlaceType& place() const;
 
+  /// \brief Cast datatype from one to another
+  Tensor cast(const DataType& target_type);
+
  private:
   friend class framework::CustomTensorUtils;
   mutable std::shared_ptr<void> tensor_;

diff --git a/paddle/fluid/extension/src/tensor.cc b/paddle/fluid/extension/src/tensor.cc
@@ -18,10 +18,76 @@ limitations under the License. */
 #include "paddle/fluid/framework/lod_tensor.h"
 #include "paddle/fluid/memory/memcpy.h"
 #include "paddle/fluid/platform/enforce.h"
-#include "paddle/fluid/platform/gpu_info.h"
+#include "paddle/fluid/platform/transform.h"
 
 namespace paddle {
 
+template <typename InType, typename OutType>
+struct CastDataTypeFunctor {
+  HOSTDEVICE inline OutType operator()(InType in) const {
+    return static_cast<OutType>(in);
+  }
+};
+
+template <typename InType>
+struct CastDataType {
+  CastDataType(const framework::Tensor &in, framework::Tensor *out,
+               const platform::DeviceContext *ctx)
+      : in_(in), out_(out), ctx_(ctx) {}
+  const framework::Tensor in_;
+  framework::Tensor *out_;
+  const platform::DeviceContext *ctx_;
+
+  template <typename OutType>
+  void apply() {
+    auto *in_begin = in_.data<InType>();
+    auto *in_end = in_begin + in_.numel();
+    auto *out_begin = out_->mutable_data<OutType>(in_.place());
+
+    if (platform::is_cpu_place(in_.place())) {
+      platform::Transform<platform::CPUDeviceContext> trans;
+      auto *context = static_cast<const platform::CPUDeviceContext *>(ctx_);
+      trans(*context, in_begin, in_end, out_begin,
+            CastDataTypeFunctor<InType, OutType>());
+#ifdef __NVCC__
+    } else if (platform::is_gpu_place(in_.place())) {
+      platform::Transform<platform::CUDADeviceContext> trans;
+      auto *context = static_cast<const platform::CUDADeviceContext *>(ctx_);
+      trans(*context, in_begin, in_end, out_begin,
+            CastDataTypeFunctor<InType, OutType>());
+      context->Wait();
+#endif
+    } else {
+      PADDLE_THROW(platform::errors::Unimplemented(
+          "Place type is not supported when casting data type."));
+    }
+  }
+};
+template <typename T>
+void GpuCopy(T *src, T *dst, PlaceType src_plc, PlaceType dst_plc,
+             int64_t ele_size) {
+#ifdef PADDLE_WITH_CUDA
+  platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
+  int device_num = paddle::platform::GetCurrentDeviceId();
+  platform::CUDAPlace gpu_place(device_num);
+  auto *dev_ctx =
+      static_cast<const platform::CUDADeviceContext *>(pool.Get(gpu_place));
+  if ((src_plc == PlaceType::kGPU) && (dst_plc == PlaceType::kCPU)) {
+    memory::Copy(platform::CPUPlace(), static_cast<void *>(dst), gpu_place, src,
+                 ele_size, dev_ctx->stream());
+  } else if ((src_plc == PlaceType::kGPU) && (dst_plc == PlaceType::kGPU)) {
+    memory::Copy(gpu_place, static_cast<void *>(dst), gpu_place, src, ele_size,
+                 dev_ctx->stream());
+  } else if ((src_plc == PlaceType::kCPU) && (dst_plc == PlaceType::kGPU)) {
+    memory::Copy(gpu_place, static_cast<void *>(dst), platform::CPUPlace(), src,
+                 ele_size, dev_ctx->stream());
+  } else {
+    PADDLE_THROW("Only GPU related Copy can reach this func.");
+  }
+  cudaStreamSynchronize(dev_ctx->stream());
+#endif
+}
+
 #define GET_CASTED_TENSOR                               \
   if (!tensor_) {                                       \
     tensor_ = std::make_shared<framework::LoDTensor>(); \
@@ -55,12 +121,12 @@ T *Tensor::mutable_data() {
     case static_cast<int>(PlaceType::kCPU): {
       return tensor->mutable_data<T>(platform::CPUPlace());
     }
-    case static_cast<int>(PlaceType::kGPU): {
 #ifdef PADDLE_WITH_CUDA
+    case static_cast<int>(PlaceType::kGPU): {
       int device_num = platform::GetCurrentDeviceId();
       return tensor->mutable_data<T>(platform::CUDAPlace(device_num));
-#endif
     }
+#endif
     default:
       PADDLE_THROW(platform::errors::Unavailable(
           "CustomOp unsupported place: %d", static_cast<int>(place_)));
@@ -99,99 +165,62 @@ DataType Tensor::type() const {
     return DataType::COMPLEX64;
   } else if (type == framework::proto::VarType::COMPLEX128) {
     return DataType::COMPLEX128;
+  } else if (type == framework::proto::VarType::BOOL) {
+    return DataType::BOOL;
   }
   return DataType::FLOAT32;
 }
 
 template <typename T>
-Tensor Tensor::copy_to_gpu() {
-#ifdef PADDLE_WITH_CUDA
+Tensor Tensor::copy_to(const PlaceType &target_place) {
   GET_CASTED_TENSOR;
   PADDLE_ENFORCE_GE(tensor->numel(), 0,
                     platform::errors::PreconditionNotMet(
                         "You should call Tensor::Reshape(const "
                         "std::vector<int> &shape)"
                         "function before copying data from cpu."));
   size_t ele_size = tensor->numel() * sizeof(T);
-  Tensor target = Tensor(PlaceType::kGPU);
+  auto *p_src_data = tensor->data<T>();
+  auto src_place = place();
+  Tensor target = Tensor(target_place);
   target.reshape(shape());
   auto *p_target_data = target.template mutable_data<T>();
-  auto p_src_data = tensor->data<T>();
-
-  platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
-  int device_num = platform::GetCurrentDeviceId();
-  platform::CUDAPlace gpu_place(device_num);
-  auto *dev_ctx =
-      static_cast<const platform::CUDADeviceContext *>(pool.Get(gpu_place));
-  if (platform::is_cpu_place(tensor->place())) {
-    memory::Copy(gpu_place, static_cast<void *>(p_target_data),
-                 platform::CPUPlace(), p_src_data, ele_size, dev_ctx->stream());
-  } else {
-    memory::Copy(gpu_place, static_cast<void *>(p_target_data), gpu_place,
-                 p_src_data, ele_size, dev_ctx->stream());
-  }
-  cudaStreamSynchronize(dev_ctx->stream());
-  return target;
-#else
-  PADDLE_THROW(
-      platform::errors::Unavailable("PaddlePaddle is not compiled with CUDA"));
-#endif
-  return Tensor(PlaceType::kGPU);
-}
 
-template <typename T>
-Tensor Tensor::copy_to_cpu() {
-  GET_CASTED_TENSOR;
-  auto ele_num = tensor->numel();
-  auto *t_data = tensor->data<T>();
-  auto t_place = tensor->place();
-  Tensor target = Tensor(PlaceType::kCPU);
-  target.reshape(shape());
-  auto *p_target_data = target.template mutable_data<T>();
-  if (platform::is_cpu_place(t_place)) {
-    std::memcpy(static_cast<void *>(p_target_data), t_data,
-                ele_num * sizeof(T));
+  if ((src_place == PlaceType::kCPU) && (target_place == PlaceType::kCPU)) {
+    std::memcpy(static_cast<void *>(p_target_data), p_src_data, ele_size);
+  } else if ((src_place == PlaceType::kGPU) &&
+             (target_place == PlaceType::kCPU)) {
+    GpuCopy<T>(p_src_data, p_target_data, src_place, target_place, ele_size);
+  } else if ((src_place == PlaceType::kCPU) &&
+             (target_place == PlaceType::kGPU)) {
+    GpuCopy<T>(p_src_data, p_target_data, src_place, target_place, ele_size);
+  } else if ((src_place == PlaceType::kGPU) &&
+             (target_place == PlaceType::kGPU)) {
+    GpuCopy<T>(p_src_data, p_target_data, src_place, target_place, ele_size);
   } else {
-#ifdef PADDLE_WITH_CUDA
-    platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
-    auto gpu_place = BOOST_GET_CONST(platform::CUDAPlace, t_place);
-    auto *dev_ctx =
-        static_cast<const platform::CUDADeviceContext *>(pool.Get(gpu_place));
-    memory::Copy(platform::CPUPlace(), static_cast<void *>(p_target_data),
-                 gpu_place, t_data, ele_num * sizeof(T), dev_ctx->stream());
-
-    cudaStreamSynchronize(dev_ctx->stream());
-#else
     PADDLE_THROW(platform::errors::Unavailable(
-        "PaddlePaddle is not compiled with CUDA."));
-#endif
+        "Not supported place transform of place: %d to place: %d",
+        static_cast<int>(src_place), static_cast<int>(target_place)));
   }
   return target;
 }
 
-template Tensor Tensor::copy_to_gpu<paddle::platform::float16>();
-template Tensor Tensor::copy_to_gpu<paddle::platform::bfloat16>();
-template Tensor Tensor::copy_to_gpu<paddle::platform::complex64>();
-template Tensor Tensor::copy_to_gpu<paddle::platform::complex128>();
-template Tensor Tensor::copy_to_gpu<float>();
-template Tensor Tensor::copy_to_gpu<double>();
-template Tensor Tensor::copy_to_gpu<int64_t>();
-template Tensor Tensor::copy_to_gpu<int32_t>();
-template Tensor Tensor::copy_to_gpu<uint8_t>();
-template Tensor Tensor::copy_to_gpu<int8_t>();
-template Tensor Tensor::copy_to_gpu<int16_t>();
-
-template Tensor Tensor::copy_to_cpu<paddle::platform::float16>();
-template Tensor Tensor::copy_to_cpu<paddle::platform::bfloat16>();
-template Tensor Tensor::copy_to_cpu<paddle::platform::complex64>();
-template Tensor Tensor::copy_to_cpu<paddle::platform::complex128>();
-template Tensor Tensor::copy_to_cpu<float>();
-template Tensor Tensor::copy_to_cpu<double>();
-template Tensor Tensor::copy_to_cpu<int64_t>();
-template Tensor Tensor::copy_to_cpu<int32_t>();
-template Tensor Tensor::copy_to_cpu<uint8_t>();
-template Tensor Tensor::copy_to_cpu<int8_t>();
-template Tensor Tensor::copy_to_cpu<int16_t>();
+template Tensor Tensor::copy_to<paddle::platform::float16>(
+    const PlaceType &target_place);
+template Tensor Tensor::copy_to<paddle::platform::bfloat16>(
+    const PlaceType &target_place);
+template Tensor Tensor::copy_to<paddle::platform::complex64>(
+    const PlaceType &target_place);
+template Tensor Tensor::copy_to<paddle::platform::complex128>(
+    const PlaceType &target_place);
+template Tensor Tensor::copy_to<float>(const PlaceType &target_place);
+template Tensor Tensor::copy_to<double>(const PlaceType &target_place);
+template Tensor Tensor::copy_to<int64_t>(const PlaceType &target_place);
+template Tensor Tensor::copy_to<int32_t>(const PlaceType &target_place);
+template Tensor Tensor::copy_to<uint8_t>(const PlaceType &target_place);
+template Tensor Tensor::copy_to<int8_t>(const PlaceType &target_place);
+template Tensor Tensor::copy_to<int16_t>(const PlaceType &target_place);
+template Tensor Tensor::copy_to<bool>(const PlaceType &target_place);
 
 template float *Tensor::data<float>() const;
 template double *Tensor::data<double>() const;
@@ -208,6 +237,7 @@ Tensor::data<paddle::platform::complex128>() const;
 template paddle::platform::complex64 *
 Tensor::data<paddle::platform::complex64>() const;
 template int16_t *Tensor::data<int16_t>() const;
+template bool *Tensor::data<bool>() const;
 
 template float *Tensor::mutable_data<float>();
 template double *Tensor::mutable_data<double>();
@@ -224,6 +254,7 @@ Tensor::mutable_data<paddle::platform::complex128>();
 template paddle::platform::complex64 *
 Tensor::mutable_data<paddle::platform::complex64>();
 template int16_t *Tensor::mutable_data<int16_t>();
+template bool *Tensor::mutable_data<bool>();
 
 template float *Tensor::mutable_data<float>(const PlaceType &place);
 template double *Tensor::mutable_data<double>(const PlaceType &place);
@@ -240,6 +271,7 @@ Tensor::mutable_data<paddle::platform::complex128>(const PlaceType &place);
 template paddle::platform::complex64 *
 Tensor::mutable_data<paddle::platform::complex64>(const PlaceType &place);
 template int16_t *Tensor::mutable_data<int16_t>(const PlaceType &place);
+template bool *Tensor::mutable_data<bool>(const PlaceType &place);
 
 std::vector<int> Tensor::shape() const {
   GET_CASTED_TENSOR
@@ -261,6 +293,62 @@ const PlaceType &Tensor::place() const {
   return place_;
 }
 
+Tensor Tensor::cast(const DataType &target_type) {
+  GET_CASTED_TENSOR;
+  Tensor rlt = Tensor(place());
+  rlt.reshape(this->shape());
+  auto rlt_tensor_ = static_cast<framework::LoDTensor *>(rlt.tensor_.get());
+  platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
+  auto ctx = pool.Get(tensor->place());
+  auto src_type = tensor->type();
+  auto dst_type =
+      framework::CustomTensorUtils::ConvertEnumDTypeToInnerDType(target_type);
+  switch (src_type) {
+    case framework::proto::VarType::FP16:
+      framework::VisitDataType(
+          dst_type, CastDataType<platform::float16>(*tensor, rlt_tensor_, ctx));
+      break;
+    case framework::proto::VarType::BF16:
+      framework::VisitDataType(dst_type, CastDataType<platform::bfloat16>(
+                                             *tensor, rlt_tensor_, ctx));
+      break;
+    case framework::proto::VarType::FP32:
+      framework::VisitDataType(dst_type,
+                               CastDataType<float>(*tensor, rlt_tensor_, ctx));
+      break;
+    case framework::proto::VarType::FP64:
+      framework::VisitDataType(dst_type,
+                               CastDataType<double>(*tensor, rlt_tensor_, ctx));
+      break;
+    case framework::proto::VarType::INT32:
+      framework::VisitDataType(dst_type,
+                               CastDataType<int>(*tensor, rlt_tensor_, ctx));
+      break;
+    case framework::proto::VarType::INT64:
+      framework::VisitDataType(
+          dst_type, CastDataType<int64_t>(*tensor, rlt_tensor_, ctx));
+      break;
+    case framework::proto::VarType::BOOL:
+      framework::VisitDataType(dst_type,
+                               CastDataType<bool>(*tensor, rlt_tensor_, ctx));
+      break;
+    case framework::proto::VarType::INT16:
+      framework::VisitDataType(
+          dst_type, CastDataType<int16_t>(*tensor, rlt_tensor_, ctx));
+      break;
+    case framework::proto::VarType::UINT8:
+      framework::VisitDataType(
+          dst_type, CastDataType<u_int8_t>(*tensor, rlt_tensor_, ctx));
+      break;
+    // TODO(JiabinYang): Support Complex later
+    default:
+      PADDLE_THROW(platform::errors::Unimplemented(
+          "Data type (%s) is not supported when casting data type.",
+          framework::DataTypeToString(src_type)));
+  }
+  return rlt;
+}
+
 int64_t Tensor::size() const {
   GET_CASTED_TENSOR;
   return tensor->numel();
@@ -273,12 +361,13 @@ void CustomTensorUtils::ShareDataTo(const paddle::Tensor &src, void *dst) {
       *static_cast<framework::LoDTensor *>(src.tensor_.get()));
 }
 
-void CustomTensorUtils::ShareDataFrom(void *src, const paddle::Tensor &dst) {
+void CustomTensorUtils::ShareDataFrom(const void *src,
+                                      const paddle::Tensor &dst) {
   if (!dst.tensor_) {
     dst.tensor_ = std::make_shared<framework::LoDTensor>();
   }
   auto *tensor = static_cast<framework::LoDTensor *>(dst.tensor_.get());
-  tensor->ShareDataWith(*static_cast<framework::LoDTensor *>(src));
+  tensor->ShareDataWith(*static_cast<const framework::LoDTensor *>(src));
 }
 
 }  // namespace framework