[Inference] Inference python api support fp16 (#34676)

Author: jiweibo

paddle/fluid/inference/api/analysis_predictor.h

@@ -25,12 +25,16 @@
 #include "paddle/fluid/inference/api/details/reset_tensor_array.h"
 #include "paddle/fluid/inference/api/helper.h"
 #include "paddle/fluid/inference/api/paddle_inference_api.h"
+#include "paddle/fluid/platform/float16.h"
 #include "paddle/fluid/string/printf.h"
 #ifdef PADDLE_WITH_TESTING
 #include <gtest/gtest.h>
 #include <gtest/gtest_prod.h>
 #endif
 
+namespace paddle_infer {
+using float16 = paddle::platform::float16;
+}
 ///
 /// \file analysis_predictor.h
 ///

paddle/fluid/inference/api/details/zero_copy_tensor.cc

@@ -19,9 +19,12 @@
 #include "paddle/fluid/inference/api/paddle_tensor.h"
 #include "paddle/fluid/memory/memcpy.h"
 #include "paddle/fluid/platform/enforce.h"
+#include "paddle/fluid/platform/float16.h"
 
 namespace paddle_infer {
 
+using float16 = paddle::platform::float16;
+
 void Tensor::Reshape(const std::vector<int> &shape) {
   PADDLE_ENFORCE_EQ(
       name_.empty(), false,
@@ -104,6 +107,8 @@ DataType Tensor::type() const {
   auto type = tensor->type();
   if (type == paddle::framework::proto::VarType::FP32) {
     return DataType::FLOAT32;
+  } else if (type == paddle::framework::proto::VarType::FP16) {
+    return DataType::FLOAT16;
   } else if (type == paddle::framework::proto::VarType::INT64) {
     return DataType::INT64;
   } else if (type == paddle::framework::proto::VarType::INT32) {
@@ -261,12 +266,14 @@ template PD_INFER_DECL void Tensor::CopyFromCpu<int64_t>(const int64_t *data);
 template PD_INFER_DECL void Tensor::CopyFromCpu<int32_t>(const int32_t *data);
 template PD_INFER_DECL void Tensor::CopyFromCpu<uint8_t>(const uint8_t *data);
 template PD_INFER_DECL void Tensor::CopyFromCpu<int8_t>(const int8_t *data);
+template PD_INFER_DECL void Tensor::CopyFromCpu<float16>(const float16 *data);
 
 template PD_INFER_DECL void Tensor::CopyToCpu<float>(float *data);
 template PD_INFER_DECL void Tensor::CopyToCpu<int64_t>(int64_t *data);
 template PD_INFER_DECL void Tensor::CopyToCpu<int32_t>(int32_t *data);
 template PD_INFER_DECL void Tensor::CopyToCpu<uint8_t>(uint8_t *data);
 template PD_INFER_DECL void Tensor::CopyToCpu<int8_t>(int8_t *data);
+template PD_INFER_DECL void Tensor::CopyToCpu<float16>(float16 *data);
 
 template PD_INFER_DECL float *Tensor::data<float>(PlaceType *place,
                                                   int *size) const;

paddle/fluid/inference/api/paddle_tensor.h

@@ -25,6 +25,7 @@ enum DataType {
   INT32,
   UINT8,
   INT8,
+  FLOAT16,
   // TODO(Superjomn) support more data types if needed.
 };
 

paddle/fluid/pybind/inference_api.cc

@@ -34,6 +34,36 @@
 
 namespace py = pybind11;
 
+namespace pybind11 {
+namespace detail {
+
+// Note: use same enum number of float16 in numpy.
+// import numpy as np
+// print np.dtype(np.float16).num  # 23
+constexpr int NPY_FLOAT16_ = 23;
+constexpr int NPY_UINT16_ = 4;
+
+// Note: Since float16 is not a builtin type in C++, we register
+// paddle::platform::float16 as numpy.float16.
+// Ref: https://github.com/pybind/pybind11/issues/1776
+template <>
+struct npy_format_descriptor<paddle_infer::float16> {
+  static py::dtype dtype() {
+    handle ptr = npy_api::get().PyArray_DescrFromType_(NPY_FLOAT16_);
+    return reinterpret_borrow<py::dtype>(ptr);
+  }
+  static std::string format() {
+    // Note: "e" represents float16.
+    // Details at:
+    // https://docs.python.org/3/library/struct.html#format-characters.
+    return "e";
+  }
+  static constexpr auto name = _("float16");
+};
+
+}  // namespace detail
+}  // namespace pybind11
+
 namespace paddle {
 namespace pybind {
 using paddle::AnalysisPredictor;
@@ -126,6 +156,9 @@ py::dtype PaddleDTypeToNumpyDType(PaddleDType dtype) {
     case PaddleDType::UINT8:
       dt = py::dtype::of<uint8_t>();
       break;
+    case PaddleDType::FLOAT16:
+      dt = py::dtype::of<paddle_infer::float16>();
+      break;
     default:
       PADDLE_THROW(platform::errors::Unimplemented(
           "Unsupported data type. Now only supports INT32, INT64, UINT8 and "
@@ -196,6 +229,10 @@ py::array ZeroCopyTensorToNumpy(ZeroCopyTensor &tensor) {  // NOLINT
     case PaddleDType::FLOAT32:
       tensor.copy_to_cpu<float>(static_cast<float *>(array.mutable_data()));
       break;
+    case PaddleDType::FLOAT16:
+      tensor.copy_to_cpu<paddle::platform::float16>(
+          static_cast<paddle::platform::float16 *>(array.mutable_data()));
+      break;
     case PaddleDType::UINT8:
       tensor.copy_to_cpu<uint8_t>(static_cast<uint8_t *>(array.mutable_data()));
       break;
@@ -226,6 +263,10 @@ py::array PaddleInferTensorToNumpy(paddle_infer::Tensor &tensor) {  // NOLINT
     case PaddleDType::FLOAT32:
       tensor.CopyToCpu<float>(static_cast<float *>(array.mutable_data()));
       break;
+    case PaddleDType::FLOAT16:
+      tensor.CopyToCpu<paddle::platform::float16>(
+          static_cast<paddle::platform::float16 *>(array.mutable_data()));
+      break;
     case PaddleDType::UINT8:
       tensor.CopyToCpu(static_cast<uint8_t *>(array.mutable_data()));
       break;
@@ -642,6 +683,7 @@ void BindZeroCopyTensor(py::module *m) {
       .def("copy_from_cpu", &ZeroCopyTensorCreate<int32_t>)
       .def("copy_from_cpu", &ZeroCopyTensorCreate<int64_t>)
       .def("copy_from_cpu", &ZeroCopyTensorCreate<float>)
+      .def("copy_from_cpu", &ZeroCopyTensorCreate<paddle_infer::float16>)
       .def("copy_to_cpu", &ZeroCopyTensorToNumpy)
       .def("shape", &ZeroCopyTensor::shape)
       .def("set_lod", &ZeroCopyTensor::SetLoD)
@@ -655,6 +697,7 @@ void BindPaddleInferTensor(py::module *m) {
       .def("copy_from_cpu", &PaddleInferTensorCreate<int32_t>)
       .def("copy_from_cpu", &PaddleInferTensorCreate<int64_t>)
       .def("copy_from_cpu", &PaddleInferTensorCreate<float>)
+      .def("copy_from_cpu", &PaddleInferTensorCreate<paddle_infer::float16>)
       .def("copy_to_cpu", &PaddleInferTensorToNumpy)
       .def("shape", &paddle_infer::Tensor::shape)
       .def("set_lod", &paddle_infer::Tensor::SetLoD)