[Other] Add namespace for functions (#538)

Add namespace for functions

examples/text/ernie-3.0/cpp/seq_cls_infer.cc

@@ -187,11 +187,11 @@ struct ErnieForSequenceClassificationPredictor {
                    std::vector<SeqClsResult>* seq_cls_results) {
     const auto& logits = outputs[0];
     fastdeploy::FDTensor probs;
-    fastdeploy::Softmax(logits, &probs);
+    fastdeploy::function::Softmax(logits, &probs);
 
     fastdeploy::FDTensor labels, confidences;
-    fastdeploy::Max(probs, &confidences, {-1});
-    fastdeploy::ArgMax(probs, &labels, -1);
+    fastdeploy::function::Max(probs, &confidences, {-1});
+    fastdeploy::function::ArgMax(probs, &labels, -1);
     if (labels.Numel() != confidences.Numel()) {
       return false;
     }

fastdeploy/backends/tensorrt/trt_backend.cc

@@ -318,7 +318,7 @@ bool TrtBackend::Infer(std::vector<FDTensor>& inputs,
   
       casted_output_tensors_[(*outputs)[i].name].Resize((*outputs)[i].shape, (*outputs)[i].dtype,
                                                         (*outputs)[i].name, Device::GPU);
-      CudaCast(output_tensor, &casted_output_tensors_[(*outputs)[i].name], stream_);
+      function::CudaCast(output_tensor, &casted_output_tensors_[(*outputs)[i].name], stream_);
     } else {
       casted_output_tensors_[(*outputs)[i].name].SetExternalData(
           (*outputs)[i].shape, model_output_dtype,
@@ -392,7 +392,7 @@ void TrtBackend::SetInputs(const std::vector<FDTensor>& inputs) {
         input_tensor.SetExternalData(item.shape, FDDataType::INT32,
                                      inputs_device_buffer_[item.name].data(),
                                      Device::GPU);
-        CudaCast(item, &input_tensor, stream_);
+        function::CudaCast(item, &input_tensor, stream_);
       } else {
         // no copy
         inputs_device_buffer_[item.name].SetExternalData(dims, item.Data());

fastdeploy/function/concat.cc

@@ -21,7 +21,7 @@
 #include "fastdeploy/utils/utils.h"
 
 namespace fastdeploy {
-
+namespace function {
 std::string Str(const std::vector<int64_t>& shape) {
   std::ostringstream oss;
   oss << "[ " << shape[0];
@@ -121,4 +121,5 @@ void Concat(const std::vector<FDTensor>& x, FDTensor* out, int axis) {
   *out = std::move(out_temp);
 }
 
+}  // namespace function
 }  // namespace fastdeploy

fastdeploy/function/concat.h

@@ -17,6 +17,7 @@
 #include "fastdeploy/core/fd_tensor.h"
 
 namespace fastdeploy {
+namespace function {
 
 /** Excute the concatenate operation for input FDTensor along given axis.
     @param x The input tensor.
@@ -27,4 +28,5 @@ namespace fastdeploy {
 FASTDEPLOY_DECL void Concat(const std::vector<FDTensor>& x, FDTensor* out,
                             int axis = 0);
 
+}  // namespace function
 }  // namespace fastdeploy

fastdeploy/function/cuda_cast.cu

@@ -15,7 +15,7 @@
 #include "fastdeploy/function/cuda_cast.h"
 
 namespace fastdeploy {
-
+namespace function {
 template <typename T_IN, typename T_OUT>
 __global__ void CudaCastKernel(const T_IN* in, T_OUT* out, int edge) {
   int position = blockDim.x * blockIdx.x + threadIdx.x;
@@ -42,4 +42,5 @@ void CudaCast(const FDTensor& in, FDTensor* out, cudaStream_t stream) {
   }
 }
 
+}  // namespace function
 }  // namespace fastdeploy

fastdeploy/function/cuda_cast.h

@@ -17,7 +17,7 @@
 #include "fastdeploy/core/fd_tensor.h"
 
 namespace fastdeploy {
-
+namespace function {
 /** Cast the type of the data in GPU buffer.
     @param in The input tensor.
     @param out The output tensor
@@ -25,5 +25,5 @@ namespace fastdeploy {
 */
 FASTDEPLOY_DECL void CudaCast(const FDTensor& in, FDTensor* out,
                               cudaStream_t stream);
-
+}  // namespace function
 }  // namespace fastdeploy

fastdeploy/function/eigen.cc

@@ -15,7 +15,7 @@
 #include "fastdeploy/function/eigen.h"
 
 namespace fastdeploy {
-
+namespace function {
 std::shared_ptr<EigenDeviceWrapper> EigenDeviceWrapper::instance_ = nullptr;
 
 std::shared_ptr<EigenDeviceWrapper> EigenDeviceWrapper::GetInstance() {
@@ -29,4 +29,5 @@ const Eigen::DefaultDevice* EigenDeviceWrapper::GetDevice() const {
   return &device_;
 }
 
+}
 }  // namespace fastdeploy

fastdeploy/function/eigen.h

@@ -22,6 +22,7 @@
 #include "unsupported/Eigen/CXX11/Tensor"
 
 namespace fastdeploy {
+namespace function {
 // EigenDim converts shape into Eigen::DSizes.
 template <int D>
 struct EigenDim {
@@ -135,4 +136,5 @@ class EigenDeviceWrapper {
   static std::shared_ptr<EigenDeviceWrapper> instance_;
 };
 
+}  // namespace function
 }  // namespace fastdeploy

fastdeploy/function/pad.cc

@@ -20,7 +20,7 @@
 #include "fastdeploy/utils/utils.h"
 
 namespace fastdeploy {
-
+namespace function {
 template <typename T, int Rank>
 struct PadEigen {
   using Array = std::array<std::pair<int64_t, int64_t>, Rank>;
@@ -123,4 +123,5 @@ void Pad(const FDTensor& x, FDTensor* out, const std::vector<int>& pads, float v
 
 
 
+}  // namespace function
 }  // namespace fastdeploy

fastdeploy/function/pad.h

@@ -17,7 +17,7 @@
 #include "fastdeploy/core/fd_tensor.h"
 
 namespace fastdeploy {
-
+namespace function {
 /** Excute the pad operation for input FDTensor along given dims.
     @param x The input tensor.
     @param out The output tensor which stores the result.
@@ -27,4 +27,5 @@ namespace fastdeploy {
 FASTDEPLOY_DECL void Pad(const FDTensor& x, FDTensor* out,
             const std::vector<int>& pads, float pad_value = 0);
 
+}
 }  // namespace fastdeploy

fastdeploy/function/reduce.cc

@@ -23,7 +23,7 @@
 #include "fastdeploy/utils/utils.h"
 
 namespace fastdeploy {
-
+namespace function {
 template <typename T, size_t D, size_t R_D, typename Functor>
 void ReduceFunctor(const FDTensor& input, FDTensor* output,
                    const std::vector<int64_t>& dims, bool keep_dim) {
@@ -402,4 +402,5 @@ void ArgMin(const FDTensor& x, FDTensor* out, int64_t axis,
                            }));
 }
 
+}  // namespace function
 }  // namespace fastdeploy

fastdeploy/function/reduce.h

@@ -17,7 +17,7 @@
 #include "fastdeploy/core/fd_tensor.h"
 
 namespace fastdeploy {
-
+namespace function {
 /** Excute the maximum operation for input FDTensor along given dims.
     @param x The input tensor.
     @param out The output tensor which stores the result.
@@ -123,4 +123,5 @@ FASTDEPLOY_DECL void ArgMin(const FDTensor& x, FDTensor* out, int64_t axis,
                             FDDataType output_dtype = FDDataType::INT64,
                             bool keep_dim = false, bool flatten = false);
 
+}  // namespace function
 }  // namespace fastdeploy

fastdeploy/function/reduce_functor.h

@@ -16,7 +16,7 @@
 
 #include "fastdeploy/function/eigen.h"
 namespace fastdeploy {
-
+namespace function {
 //////// Max Functor ///////
 struct MaxFunctor {
   template <typename X, typename Y, typename Dim>
@@ -73,4 +73,5 @@ struct ProdFunctor {
   }
 };
 
+}  // namespace function
 }  // namespace fastdeploy

fastdeploy/function/softmax.cc

@@ -21,6 +21,7 @@
 #include "fastdeploy/utils/utils.h"
 
 namespace fastdeploy {
+namespace function {
 template <typename T>
 struct ValueClip {
   T operator()(const T& x) const {
@@ -124,4 +125,5 @@ void Softmax(const FDTensor& x, FDTensor* out, int axis) {
                        ([&] { SoftmaxKernel<data_t>(x, &out_tmp, axis); }));
   *out = std::move(out_tmp);
 }
+}  // namespace function
 }  // namespace fastdeploy

fastdeploy/function/softmax.h

@@ -17,7 +17,7 @@
 #include "fastdeploy/core/fd_tensor.h"
 
 namespace fastdeploy {
-
+namespace function {
 /** Excute the softmax operation for input FDTensor along given dims.
     @param x The input tensor.
     @param out The output tensor which stores the result.
@@ -25,4 +25,5 @@ namespace fastdeploy {
 */
 FASTDEPLOY_DECL void Softmax(const FDTensor& x, FDTensor* out, int axis = -1);
 
+}  // namespace function
 }  // namespace fastdeploy

fastdeploy/function/transpose.cc

@@ -17,7 +17,7 @@
 #include "fastdeploy/utils/utils.h"
 
 namespace fastdeploy {
-
+namespace function {
 template <typename T>
 struct TransposeNormalKernel {
   void operator()(const FDTensor& in, FDTensor* out,
@@ -121,4 +121,5 @@ void Transpose(const FDTensor& x, FDTensor* out,
   *out = std::move(out_temp);
 }
 
+}  // namespace function
 }  // namespace fastdeploy

fastdeploy/function/transpose.h

@@ -17,7 +17,7 @@
 #include "fastdeploy/core/fd_tensor.h"
 
 namespace fastdeploy {
-
+namespace function {
 /** Excute the transpose operation for input FDTensor along given dims.
     @param x The input tensor.
     @param out The output tensor which stores the result.
@@ -25,4 +25,5 @@ namespace fastdeploy {
 */
 FASTDEPLOY_DECL void Transpose(const FDTensor& x, FDTensor* out,
                                const std::vector<int64_t>& dims);
+}  // namespace function
 }  // namespace fastdeploy

fastdeploy/vision/classification/contrib/resnet.cc

@@ -87,7 +87,7 @@ bool ResNet::Postprocess(FDTensor& infer_result,
   // 1. Softmax 2. Choose topk labels 3. Put the result into ClassifyResult variable.
 
   int num_classes = infer_result.shape[1];
-  Softmax(infer_result, &infer_result);
+  function::Softmax(infer_result, &infer_result);
   const float* infer_result_buffer = reinterpret_cast<float*>(infer_result.Data());
   topk = std::min(num_classes, topk);
   result->label_ids =

fastdeploy/vision/classification/contrib/yolov5cls.cc

@@ -75,7 +75,7 @@ bool YOLOv5Cls::Postprocess(const FDTensor& infer_result,
                             ClassifyResult* result, int topk) {
   // Softmax
   FDTensor infer_result_softmax;
-  Softmax(infer_result, &infer_result_softmax, 1);
+  function::Softmax(infer_result, &infer_result_softmax, 1);
   int num_classes = infer_result_softmax.shape[1];
   const float* infer_result_buffer =
       reinterpret_cast<const float*>(infer_result_softmax.Data());

fastdeploy/vision/classification/ppcls/preprocessor.cc

@@ -99,7 +99,11 @@ bool PaddleClasPreprocessor::Run(std::vector<FDMat>* images, std::vector<FDTenso
     (*images)[i].ShareWithTensor(&(tensors[i]));
     tensors[i].ExpandDim(0);
   }
-  Concat(tensors, &((*outputs)[0]), 0);
+  if (tensors.size() == 1) {
+    (*outputs)[0] = std::move(tensors[0]);
+  } else {
+    function::Concat(tensors, &((*outputs)[0]), 0);
+  }
   return true;
 }
 

fastdeploy/vision/matting/ppmatting/ppmatting.cc

@@ -170,7 +170,7 @@ bool PPMatting::Postprocess(
     return false;
   }
   std::vector<int64_t> dim{0, 2, 3, 1};
-  Transpose(alpha_tensor, &alpha_tensor, dim);
+  function::Transpose(alpha_tensor, &alpha_tensor, dim);
   alpha_tensor.Squeeze(0);
   Mat mat = Mat::Create(alpha_tensor);
 

fastdeploy/vision/segmentation/ppseg/model.cc

@@ -220,7 +220,7 @@ bool PaddleSegModel::Postprocess(
   }
 
   if (!is_with_softmax && apply_softmax) {
-    Softmax(*infer_result, infer_result, 1);
+    function::Softmax(*infer_result, infer_result, 1);
   }
 
   if (!is_with_argmax) {
@@ -228,7 +228,7 @@ bool PaddleSegModel::Postprocess(
     result->contain_score_map = true;
 
     std::vector<int64_t> dim{0, 2, 3, 1};
-    Transpose(*infer_result, infer_result, dim);
+    function::Transpose(*infer_result, infer_result, dim);
   }
   // batch always 1, so ignore
   infer_result->shape = {infer_height, infer_width, infer_channel};
@@ -284,11 +284,11 @@ bool PaddleSegModel::Postprocess(
     std::vector<int64_t> reduce_dim{-1};
     // argmax
     if (is_resized) {
-      ArgMax(new_infer_result, &argmax_infer_result, -1, FDDataType::INT32);
-      Max(new_infer_result, &max_score_result, reduce_dim);
+      function::ArgMax(new_infer_result, &argmax_infer_result, -1, FDDataType::INT32);
+      function::Max(new_infer_result, &max_score_result, reduce_dim);
     } else {
-      ArgMax(*infer_result, &argmax_infer_result, -1, FDDataType::INT32);
-      Max(*infer_result, &max_score_result, reduce_dim);
+      function::ArgMax(*infer_result, &argmax_infer_result, -1, FDDataType::INT32);
+      function::Max(*infer_result, &max_score_result, reduce_dim);
     }
     argmax_infer_result_buffer =
         static_cast<int32_t*>(argmax_infer_result.Data());

tests/function/test_concat.cc

@@ -21,7 +21,7 @@
 #include "gtest_utils.h"
 
 namespace fastdeploy {
-
+namespace function {
 TEST(fastdeploy, concat1) {
   CheckShape check_shape;
   std::vector<FDTensor> inputs(3);
@@ -77,4 +77,5 @@ TEST(fastdeploy, concat5) {
   check_shape(output.shape, {5, 6, 4, 5});
 }
 
+}  // namespace function
 }  // namespace fastdeploy

tests/function/test_pad.cc

@@ -22,7 +22,7 @@
 #include "gtest_utils.h"
 
 namespace fastdeploy {
-
+namespace function {
 TEST(fastdeploy, pad_2d) {
   FDTensor input, output;
   CheckShape check_shape;
@@ -65,28 +65,5 @@ TEST(fastdeploy, pad_2d_int32_t) {
   check_type(input.dtype, output.dtype);
 }
 
-//TEST(fastdeploy, transpose_5d) {
-//  FDTensor input, output;
-//  CheckShape check_shape;
-//  CheckData check_data;
-//
-//  std::vector<int64_t> input_shape = {2, 1, 3, 1, 2};
-//  auto total_size = std::accumulate(input_shape.begin(), input_shape.end(), 1,
-//                                    std::multiplies<int64_t>());
-//  std::vector<int> inputs(total_size, 1);
-//  std::iota(inputs.begin(), inputs.end(), 1);
-//  std::vector<int> expected_result = {1, 3, 5, 2, 4, 6, 7, 9, 11, 8, 10, 12};
-//  input.SetExternalData(input_shape, FDDataType::INT32, inputs.data());
-//
-//  Transpose(input, &output, {0, 1, 4, 3, 2});
-//  check_shape(output.shape, {2, 1, 2, 1, 3});
-//  check_data(reinterpret_cast<const int*>(output.Data()),
-//             expected_result.data(), expected_result.size());
-//
-//  Transpose(input, &input, {0, 1, 4, 3, 2});
-//  check_shape(input.shape, {2, 1, 2, 1, 3});
-//  check_data(reinterpret_cast<const int*>(input.Data()), expected_result.data(),
-//             expected_result.size());
-//}
-
+}  // namespace function
 }  // namespace fastdeploy

tests/function/test_reduce.cc

@@ -21,7 +21,7 @@
 #include "gtest_utils.h"
 
 namespace fastdeploy {
-
+namespace function {
 TEST(fastdeploy, reduce_max) {
   FDTensor input, output;
   CheckShape check_shape;
@@ -371,4 +371,5 @@ TEST(fastdeploy, reduce_argmin) {
              expected_result_noaxis.data(), expected_result_noaxis.size());
 }
 
+}  // namespace function
 }  // namespace fastdeploy

tests/function/test_softmax.cc

@@ -20,7 +20,7 @@
 #include "gtest_utils.h"
 
 namespace fastdeploy {
-
+namespace function {
 TEST(fastdeploy, softmax) {
   FDTensor input, input1, output;
   CheckShape check_shape;
@@ -57,4 +57,5 @@ TEST(fastdeploy, softmax) {
              expected_result_axis1.data(), expected_result_axis1.size());
 }
 
+}  // namespace function
 }  // namespace fastdeploy

tests/function/test_transpose.cc

@@ -22,7 +22,7 @@
 #include "gtest_utils.h"
 
 namespace fastdeploy {
-
+namespace function {
 TEST(fastdeploy, transpose_2d) {
   FDTensor input, output;
   CheckShape check_shape;
@@ -67,4 +67,5 @@ TEST(fastdeploy, transpose_5d) {
              expected_result.size());
 }
 
+}  // namespace function
 }  // namespace fastdeploy