COMPMID-782 Port examples to the new format

Change-Id: Ib178a97c080ff650094d02ee49e2a0aa22376dd0
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/115717
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>

1 files changed, 74 insertions, 67 deletions

diff --git a/examples/gc_dc.cpp b/examples/gc_dc.cpp
index 174c88458d..8b6f4414e0 100644
--- a/examples/gc_dc.cpp
+++ b/examples/gc_dc.cpp
@@ -33,84 +33,91 @@
 using namespace arm_compute;
 using namespace utils;
 
-namespace
+class GCDCExample : public Example
 {
-TensorShape get_output_shape(TensorShape in_shape, TensorShape kernel_shape, const PadStrideInfo &info)
-{
-    TensorShape out_shape(in_shape);
-    const std::pair<unsigned int, unsigned int> scaled_dims = scaled_dimensions(in_shape.x(),
-                                                                                in_shape.y(),
-                                                                                kernel_shape.x(),
-                                                                                kernel_shape.y(),
-                                                                                info);
-    out_shape.set(0, scaled_dims.first);
-    out_shape.set(1, scaled_dims.second);
-    out_shape.set(2, kernel_shape[3]);
-    return out_shape;
-}
-} // namespace
-
-void main_gc_dc(int argc, char **argv)
-{
-    ARM_COMPUTE_UNUSED(argc);
-    ARM_COMPUTE_UNUSED(argv);
+public:
+    void do_setup(int argc, char **argv) override
+    {
+        ARM_COMPUTE_UNUSED(argc);
+        ARM_COMPUTE_UNUSED(argv);
 
-    // init instance
-    GCScheduler::get().default_init();
+        // init instance
+        GCScheduler::get().default_init();
 
-    const TensorShape  src_shape   = TensorShape{ 11U /* W */, 13U /* H */, 4U /* C */, 3U /* N */ };
-    const unsigned int kernel_size = 3;
-    const int          stride_x    = 1;
-    const int          stride_y    = 1;
-    const int          pad_x       = 0;
-    const int          pad_y       = 0;
-    const unsigned int num_kernels = 256;
-    const DataType     data_type   = DataType::F16;
+        const TensorShape  src_shape   = TensorShape{ 11U /* W */, 13U /* H */, 4U /* C */, 3U /* N */ };
+        const unsigned int kernel_size = 3;
+        const int          stride_x    = 1;
+        const int          stride_y    = 1;
+        const int          pad_x       = 0;
+        const int          pad_y       = 0;
+        const unsigned int num_kernels = 256;
+        const DataType     data_type   = DataType::F16;
 
-    // generate shape
-    const TensorShape   weights_shape(kernel_size, kernel_size, src_shape.z(), num_kernels);
-    const TensorShape   bias_shape(num_kernels);
-    const PadStrideInfo pad_info(stride_x, stride_y, pad_x, pad_y, DimensionRoundingType::FLOOR);
+        // generate shape
+        const TensorShape   weights_shape(kernel_size, kernel_size, src_shape.z(), num_kernels);
+        const TensorShape   bias_shape(num_kernels);
+        const PadStrideInfo pad_info(stride_x, stride_y, pad_x, pad_y, DimensionRoundingType::FLOOR);
 
-    // output shape should be 9*11*256*3 (W*H*C*N)
-    const TensorShape dst_shape = get_output_shape(src_shape, weights_shape, pad_info);
+        // output shape should be 9*11*256*3 (W*H*C*N)
+        const TensorShape dst_shape = get_output_shape(src_shape, weights_shape, pad_info);
 
-    // create tensors
-    GCTensor src, weights, bias, dst;
-    src.allocator()->init(TensorInfo(src_shape, 1, data_type));
-    weights.allocator()->init(TensorInfo(weights_shape, 1, data_type));
-    bias.allocator()->init(TensorInfo(bias_shape, 1, data_type));
-    dst.allocator()->init(TensorInfo(dst_shape, 1, data_type));
+        // create tensors
+        src.allocator()->init(TensorInfo(src_shape, 1, data_type));
+        weights.allocator()->init(TensorInfo(weights_shape, 1, data_type));
+        bias.allocator()->init(TensorInfo(bias_shape, 1, data_type));
+        dst.allocator()->init(TensorInfo(dst_shape, 1, data_type));
 
-    // configure layer
-    GCDirectConvolutionLayer conv;
-    conv.configure(&src, &weights, &bias, &dst, pad_info);
+        // configure layer
+        conv.configure(&src, &weights, &bias, &dst, pad_info);
 
-    // allocate tensors
-    src.allocator()->allocate();
-    weights.allocator()->allocate();
-    bias.allocator()->allocate();
-    dst.allocator()->allocate();
+        // allocate tensors
+        src.allocator()->allocate();
+        weights.allocator()->allocate();
+        bias.allocator()->allocate();
+        dst.allocator()->allocate();
 
-    // To demonstrate how to fill tensor with some values...
-    src.map();
-    Window window;
-    window.use_tensor_dimensions(src_shape);
-    Iterator it(&src, window);
-    execute_window_loop(window, [&](const Coordinates & id)
+        // To demonstrate how to fill tensor with some values...
+        src.map();
+        Window window;
+        window.use_tensor_dimensions(src_shape);
+        Iterator it(&src, window);
+        execute_window_loop(window, [&](const Coordinates & id)
+        {
+            *reinterpret_cast<half_float::half *>(it.ptr()) = half_float::half(1.f);
+        });
+        src.unmap();
+    }
+    void do_run() override
+    {
+        // run the layer
+        conv.run();
+    }
+    void do_teardown() override
     {
-        *reinterpret_cast<half_float::half *>(it.ptr()) = half_float::half(1.f);
-    });
-    src.unmap();
+        // check result
+        dst.map();
+        // do something
+        dst.unmap();
+    }
 
-    // run the layer
-    conv.run();
+private:
+    GCTensor                 src{}, weights{}, bias{}, dst{};
+    GCDirectConvolutionLayer conv{};
 
-    // check result
-    dst.map();
-    // do something
-    dst.unmap();
-}
+    TensorShape get_output_shape(TensorShape in_shape, TensorShape kernel_shape, const PadStrideInfo &info)
+    {
+        TensorShape out_shape(in_shape);
+        const std::pair<unsigned int, unsigned int> scaled_dims = scaled_dimensions(in_shape.x(),
+                                                                                    in_shape.y(),
+                                                                                    kernel_shape.x(),
+                                                                                    kernel_shape.y(),
+                                                                                    info);
+        out_shape.set(0, scaled_dims.first);
+        out_shape.set(1, scaled_dims.second);
+        out_shape.set(2, kernel_shape[3]);
+        return out_shape;
+    }
+};
 
 /** Main program for directconvolution test
  *
@@ -119,5 +126,5 @@ void main_gc_dc(int argc, char **argv)
  */
 int main(int argc, char **argv)
 {
-    return utils::run_example(argc, argv, main_gc_dc);
+    return utils::run_example<GCDCExample>(argc, argv);
 }