COMPMID-3316: NEDeconvolutionLayer failing for a big input

- Using NEDirectConvolution for big shapes since the memory
  required explodes for 9x9 kernel
- Adding test cases
- Fix enables only the NEON Deconvolution for NHWC

Change-Id: I8a541346428e5686818f8ecb7f69e2a9106cbceb
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3135
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Sang-Hoon Park <sang-hoon.park@arm.com>

1 files changed, 22 insertions, 10 deletions

diff --git a/src/core/CPP/kernels/CPPUpsampleKernel.cpp b/src/core/CPP/kernels/CPPUpsampleKernel.cpp
index c190543216..8348b4335e 100644
--- a/src/core/CPP/kernels/CPPUpsampleKernel.cpp
+++ b/src/core/CPP/kernels/CPPUpsampleKernel.cpp
@@ -71,15 +71,19 @@ void CPPUpsampleKernel::run(const Window &window, const ThreadInfo &info)
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICPPKernel::window(), window);
 
+    const DataLayout data_layout = _input->info()->data_layout();
+    const size_t     idx_w       = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
+    const size_t     idx_h       = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
+
     // Initialize _scaled_output buffer
-    const int    width_scaled  = _output->info()->dimension(0);
-    const int    height_scaled = _output->info()->dimension(1);
-    const int    stride_x      = _info.stride().first;
-    const int    stride_y      = _info.stride().second;
-    const int    start_x       = _info.pad_left();
-    const int    start_y       = _info.pad_top();
-    const int    end_x         = width_scaled - _info.pad_right();
-    const int    end_y         = height_scaled - _info.pad_bottom();
+    const int    width_scaled  = _output->info()->dimension(idx_w);
+    const int    height_scaled = _output->info()->dimension(idx_h);
+    const int    stride_width  = _info.stride().first;
+    const int    stride_height = _info.stride().second;
+    const int    start_width   = _info.pad_left();
+    const int    start_height  = _info.pad_top();
+    const int    end_width     = width_scaled - _info.pad_right();
+    const int    end_height    = height_scaled - _info.pad_bottom();
     const size_t element_size  = _input->info()->element_size();
 
     // The fill value is normally 0, but for quantized types '0' corresponds to the offset
@@ -103,8 +107,16 @@ void CPPUpsampleKernel::run(const Window &window, const ThreadInfo &info)
 
     // Create window
     Window window_out(window);
-    window_out.set(Window::DimX, Window::Dimension(start_x, end_x, stride_x));
-    window_out.set(Window::DimY, Window::Dimension(start_y, end_y, stride_y));
+    if(data_layout == DataLayout::NCHW)
+    {
+        window_out.set(Window::DimX, Window::Dimension(start_width, end_width, stride_width));
+        window_out.set(Window::DimY, Window::Dimension(start_height, end_height, stride_height));
+    }
+    else
+    {
+        window_out.set(Window::DimY, Window::Dimension(start_width, end_width, stride_width));
+        window_out.set(Window::DimZ, Window::Dimension(start_height, end_height, stride_height));
+    }
 
     // Create iterators
     Iterator in(_input, window);