Merge branch 'resize' into 'master'

Add size attributes in resize bilinear op to improve opencl kernel

See merge request !95

mace/kernels/opencl/resize_bilinear_opencl.cc

@@ -19,15 +19,9 @@ void ResizeBilinearFunctor<DeviceType::OPENCL, float>::operator()(
 
   index_t out_height;
   index_t out_width;
-  {
-    MACE_CHECK(resize_dims->dim_size() == 1);
-    Tensor::MappingGuard resize_dims_mapper(resize_dims);
-    auto dims_data = resize_dims->data<index_t>();
-    out_height = dims_data[0];
-    out_width = dims_data[1];
-  }
-
-  std::vector<index_t> out_shape{batch, channels, out_height, out_width};
+  GetOutputSize(resize_dims, &out_height, &out_width);
+  MACE_CHECK(out_height > 0 && out_width > 0);
+  std::vector<index_t> out_shape {batch, channels, out_height, out_width};
   output->Resize(out_shape);
 
   float height_scale =
@@ -52,6 +46,7 @@ void ResizeBilinearFunctor<DeviceType::OPENCL, float>::operator()(
       rb_kernel, cl::NullRange,
       cl::NDRange(static_cast<int>(batch * channels),
                   static_cast<int>(out_height), static_cast<int>(out_width)),
+      // TODO (heliangliang) tuning and fix when kwg_size < devisor
       cl::NDRange(1, 16, kwg_size / 16));
   MACE_CHECK(error == CL_SUCCESS, error);
 }

mace/kernels/resize_bilinear.h

 //
 // Copyright (c) 2017 XiaoMi All rights reserved.
 //
-
 #ifndef MACE_KERNELS_RESIZE_BILINEAR_H_
 #define MACE_KERNELS_RESIZE_BILINEAR_H_
 
@@ -101,30 +100,24 @@ void ResizeImage(const T *images,
 }
 
 template <DeviceType D, typename T>
-struct ResizeBilinearFunctor {
-  bool align_corners_;
-
-  ResizeBilinearFunctor(bool align_corners) : align_corners_(align_corners) {}
+class ResizeBilinearFunctor {
+ public:
+  ResizeBilinearFunctor(const std::vector<index_t> &size, bool align_corners)
+      : align_corners_(align_corners), size_(size) {}
 
   void operator()(const Tensor *input,
                   const Tensor *resize_dims,
                   Tensor *output) {
-    index_t n = input->dim(0);
-    index_t channels = input->dim(1);
-    index_t in_height = input->dim(2);
-    index_t in_width = input->dim(3);
+    const index_t batch = input->dim(0);
+    const index_t channels = input->dim(1);
+    const index_t in_height = input->dim(2);
+    const index_t in_width = input->dim(3);
 
     index_t out_height;
     index_t out_width;
-    {
-      MACE_CHECK(resize_dims->dim_size() == 1);
-      Tensor::MappingGuard resize_dims_mapper(resize_dims);
-      auto dims_data = resize_dims->data<index_t>();
-      out_height = dims_data[0];
-      out_width = dims_data[1];
-    }
-
-    vector<index_t> out_shape{n, channels, out_height, out_width};
+    GetOutputSize(resize_dims, &out_height, &out_width);
+    MACE_CHECK(out_height > 0 && out_width > 0);
+    std::vector<index_t> out_shape{batch, channels, out_height, out_width};
     output->Resize(out_shape);
 
     Tensor::MappingGuard input_mapper(input);
@@ -150,9 +143,29 @@ struct ResizeBilinearFunctor {
     ComputeInterpolationWeights(out_height, in_height, height_scale, ys.data());
     ComputeInterpolationWeights(out_width, in_width, width_scale, xs.data());
 
-    ResizeImage(input_data, n, in_height, in_width, out_height, out_width,
+    ResizeImage(input_data, batch, in_height, in_width, out_height, out_width,
                 channels, xs, ys, output_data);
   }
+
+ protected:
+  void GetOutputSize(const Tensor *resize_dims,
+                     index_t *out_height,
+                     index_t *out_width) {
+    if (size_[0] < 0 || size_[1] < 0) {
+      MACE_CHECK(resize_dims != nullptr && resize_dims->dim_size() == 1);
+      Tensor::MappingGuard resize_dims_mapper(resize_dims);
+      auto dims_data = resize_dims->data<index_t>();
+      *out_height = dims_data[0];
+      *out_width = dims_data[1];
+    } else {
+      *out_height = size_[0];
+      *out_width = size_[1];
+    }
+  }
+
+ private:
+  bool align_corners_;
+  std::vector<index_t> size_;
 };
 
 template <>

mace/ops/resize_bilinear.h

@@ -16,6 +16,7 @@ class ResizeBilinearOp : public Operator<D, T> {
   ResizeBilinearOp(const OperatorDef &operator_def, Workspace *ws)
       : Operator<D, T>(operator_def, ws),
         functor_(
+            OperatorBase::GetRepeatedArgument<index_t>("size", {-1, -1}),
             OperatorBase::GetSingleArgument<bool>("align_corners", false)) {}
 
   bool Run() override {

mace/ops/resize_bilinear_benchmark.cc

@@ -23,6 +23,7 @@ static void ResizeBilinearBenchmark(int iters,
       .Input("Input")
       .Input("OutSize")
       .Output("Output")
+      .AddIntsArg("size", {output_height, output_width})
       .Finalize(net.NewOperatorDef());
 
   // Add input data

mace/ops/resize_bilinear_test.cc

@@ -66,12 +66,12 @@ void TestRandomResizeBilinear() {
   srand(time(nullptr));
   testing::internal::LogToStderr();
   for (int round = 0; round < 10; ++round) {
-    index_t batch = 1 + rand() % 5;
-    index_t channels = 1 + rand() % 100;
-    index_t height = 1 + rand() % 100;
-    index_t width = 1 + rand() % 100;
-    index_t in_height = 1 + rand() % 100;
-    index_t in_width = 1 + rand() % 100;
+    int batch = 1 + rand() % 5;
+    int channels = 1 + rand() % 100;
+    int height = 1 + rand() % 100;
+    int width = 1 + rand() % 100;
+    int in_height = 1 + rand() % 100;
+    int in_width = 1 + rand() % 100;
 
     // Construct graph
     OpsTestNet net;
@@ -80,6 +80,7 @@ void TestRandomResizeBilinear() {
         .Input("OutSize")
         .Output("Output")
         .AddIntArg("align_corners", 1)
+        .AddIntsArg("size", {height, width})
         .Finalize(net.NewOperatorDef());
 
     // Add input data