1 files changed, 23 insertions, 25 deletions

diff --git a/src/core/NEON/kernels/NECol2ImKernel.cpp b/src/core/NEON/kernels/NECol2ImKernel.cpp
index bb8e758b78..d6517ac072 100644
--- a/src/core/NEON/kernels/NECol2ImKernel.cpp
+++ b/src/core/NEON/kernels/NECol2ImKernel.cpp
@@ -29,26 +29,17 @@
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Types.h"
 #include "arm_compute/core/Validate.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
 
 #include <arm_neon.h>
 #include <cstddef>
 #include <cstdint>
 
 using namespace arm_compute;
+using namespace misc::shape_calculator;
 
 namespace
 {
-TensorShape get_output_shape(const ITensorInfo *input, const Size2D &convolved_dims)
-{
-    TensorShape output_shape = input->tensor_shape();
-    output_shape.set(0, convolved_dims.width);
-    output_shape.set(1, convolved_dims.height);
-    output_shape.set(2, input->tensor_shape()[0]);
-    output_shape.set(3, input->tensor_shape()[3]); // For NEON the batch size is on the fourth dimension of the input tensor
-
-    return output_shape;
-}
-
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const Size2D &convolved_dims)
 {
     //Note: ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input) is not needed here as this kernel doesn't use NEON FP16 instructions.
@@ -60,12 +51,28 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c
     // Validate configured output
     if(output->total_size() != 0)
     {
-        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), get_output_shape(input, convolved_dims));
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), compute_col2im_shape(*input, convolved_dims, false));
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
     }
 
     return Status{};
 }
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const Size2D &convolved_dims)
+{
+    // Output auto inizialitation if not yet initialized
+    auto_init_if_empty(*output, input->clone()->set_tensor_shape(compute_col2im_shape(*input, convolved_dims, false)));
+
+    // Configure kernel window
+    Window win = calculate_max_window(*input, Steps());
+
+    // The NECol2ImKernel doesn't need padding so update_window_and_padding() can be skipped
+    Coordinates coord;
+    coord.set_num_dimensions(output->num_dimensions());
+    output->set_valid_region(ValidRegion(coord, output->tensor_shape()));
+
+    return std::make_pair(Status{}, win);
+}
 } // namespace
 
 template <typename T>
@@ -102,11 +109,6 @@ NECol2ImKernel::NECol2ImKernel()
 void NECol2ImKernel::configure(const ITensor *input, ITensor *output, const Size2D &convolved_dims)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
-
-    // Output auto inizialitation if not yet initialized
-    auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(get_output_shape(input->info(), convolved_dims)));
-
-    // Perform validation step
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), convolved_dims));
 
     _input          = input;
@@ -130,19 +132,15 @@ void NECol2ImKernel::configure(const ITensor *input, ITensor *output, const Size
     }
 
     // Configure kernel window
-    Window win = calculate_max_window(*input->info(), Steps());
-
-    // The NECol2ImKernel doesn't need padding so update_window_and_padding() can be skipped
-    Coordinates coord;
-    coord.set_num_dimensions(output->info()->num_dimensions());
-    output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape()));
-
-    INEKernel::configure(win);
+    auto win_config = validate_and_configure_window(input->info(), output->info(), convolved_dims);
+    ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+    INEKernel::configure(win_config.second);
 }
 
 Status NECol2ImKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &convolved_dims)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, convolved_dims));
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), convolved_dims).first);
     return Status{};
 }