COMPMID-1188 - Fix CLWinogradConvolutionLayer for NHWC

Change-Id: Ib4abe0388f218276e79f7c4405827e61722f0ef8
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/144240
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>

1 files changed, 7 insertions, 7 deletions

diff --git a/src/runtime/CL/functions/CLWinogradConvolutionLayer.cpp b/src/runtime/CL/functions/CLWinogradConvolutionLayer.cpp
index f9ea91ddc4..a70389ab6c 100644
--- a/src/runtime/CL/functions/CLWinogradConvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLWinogradConvolutionLayer.cpp
@@ -33,28 +33,28 @@ using namespace arm_compute;
 
 namespace
 {
-Size2D winograd_output_tile(const Size2D &input_dims, const Size2D &kernel_dims)
+Size2D winograd_output_tile(const Size2D &input_dims, const Size2D &kernel_dims, DataLayout data_layout)
 {
     Size2D output_tile = Size2D{};
 
     const unsigned int kernel_max_dim = std::max(kernel_dims.width, kernel_dims.height);
 
     // Check if the input spatial dimensions are smaller than 4
-    const bool is_input_lt4 = (input_dims.width <= 4 && input_dims.height <= 4);
+    const bool is_input_lt4_nchw = (input_dims.width <= 4 && input_dims.height <= 4) && (data_layout == DataLayout::NCHW);
 
     if(kernel_max_dim == 3U)
     {
         if(kernel_dims == Size2D(3U, 3U))
         {
-            output_tile = is_input_lt4 ? Size2D(2U, 2U) : Size2D(4U, 4U);
+            output_tile = is_input_lt4_nchw ? Size2D(2U, 2U) : Size2D(4U, 4U);
         }
         else if(kernel_dims == Size2D(3U, 1U))
         {
-            output_tile = is_input_lt4 ? Size2D(2U, 1U) : Size2D(4U, 1U);
+            output_tile = is_input_lt4_nchw ? Size2D(2U, 1U) : Size2D(4U, 1U);
         }
         else
         {
-            output_tile = is_input_lt4 ? Size2D(1U, 2U) : Size2D(1U, 4U);
+            output_tile = is_input_lt4_nchw ? Size2D(1U, 2U) : Size2D(1U, 4U);
         }
     }
     else if(kernel_max_dim == 5U)
@@ -99,7 +99,7 @@ void CLWinogradConvolutionLayer::configure(ICLTensor *input, const ICLTensor *we
     // Input shape, kernel size and output tile
     const Size2D input_dims  = Size2D(input->info()->tensor_shape()[idx_width], input->info()->tensor_shape()[idx_height]);
     const Size2D kernel_size = Size2D(weights->info()->tensor_shape()[idx_width], weights->info()->tensor_shape()[idx_height]);
-    const Size2D output_tile = winograd_output_tile(input_dims, kernel_size);
+    const Size2D output_tile = winograd_output_tile(input_dims, kernel_size, input->info()->data_layout());
 
     // Check if the Winograd configuration requires fast math
     if(!enable_fast_math)
@@ -156,7 +156,7 @@ Status CLWinogradConvolutionLayer::validate(const ITensorInfo *input, const ITen
     // Input shape, kernel size and output tile
     const Size2D input_dims  = Size2D(input->tensor_shape()[idx_width], input->tensor_shape()[idx_height]);
     const Size2D kernel_size = Size2D(weights->tensor_shape()[idx_width], weights->tensor_shape()[idx_height]);
-    const Size2D output_tile = winograd_output_tile(input_dims, kernel_size);
+    const Size2D output_tile = winograd_output_tile(input_dims, kernel_size, input->data_layout());
 
     // Check if the Winograd configuration requires fast math
     if(!enable_fast_math)