COMPMID-3951 LargeGraph_FLOAT32_Rank4_25 CTS failures in Android Q in CL Fix1

* Fix CLSpaceToBatchLayerKernel and NESpaceToBatchLayerKernel validation
errors by using the correctly calculated output tensor shape

Signed-off-by: SiCong Li <sicong.li@arm.com>
Change-Id: I21d61f870e6a23a2e38dcb95c939b0bf08082b6f
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4347
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: TeresaARM <teresa.charlinreyes@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 11 insertions, 16 deletions

diff --git a/src/core/CL/kernels/CLSpaceToBatchLayerKernel.cpp b/src/core/CL/kernels/CLSpaceToBatchLayerKernel.cpp
index 91b889a10a..7af0071025 100644
--- a/src/core/CL/kernels/CLSpaceToBatchLayerKernel.cpp
+++ b/src/core/CL/kernels/CLSpaceToBatchLayerKernel.cpp
@@ -37,15 +37,16 @@ namespace arm_compute
 {
 namespace
 {
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *block_info, const ITensorInfo *padddings, const ITensorInfo *output)
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *block_info, const ITensorInfo *paddings, const ITensorInfo *output)
 {
-    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_info, padddings, output);
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_info, paddings, output);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(block_info, 1, DataType::S32);
     ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
     ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
     ARM_COMPUTE_RETURN_ERROR_ON(block_info->num_dimensions() > 1);
-    ARM_COMPUTE_RETURN_ERROR_ON(padddings->num_dimensions() > 2);
-    ARM_COMPUTE_RETURN_ERROR_ON(padddings->tensor_shape()[1] != block_info->tensor_shape()[0]);
+    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(block_info->tensor_shape(), TensorShape{ 2 });
+    ARM_COMPUTE_RETURN_ERROR_ON(paddings->num_dimensions() > 2);
+    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(paddings->tensor_shape(), TensorShape{ 2, 2 });
 
     // Validate output if initialized
     if(output->total_size() != 0)
@@ -54,6 +55,7 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *block_inf
         const int        idx_channel = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
         ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_channel] != output->tensor_shape()[idx_channel]);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
     }
 
     return Status{};
@@ -62,22 +64,15 @@ Status validate_arguments_static(const ITensorInfo *input, const int block_shape
                                  const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
-    ARM_COMPUTE_RETURN_ERROR_ON(block_shape_x < 1 || block_shape_y < 1);
+    ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
     ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
+    ARM_COMPUTE_RETURN_ERROR_ON(block_shape_x < 1 || block_shape_y < 1);
 
     // Validate output if initialized
     if(output->total_size() != 0)
     {
-        const DataLayout data_layout = input->data_layout();
-        const int        idx_width   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
-        const int        idx_height  = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
-        const int        idx_channel = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
-        const int        idx_batch   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);
-        ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_width] < padding_left.x() + padding_right.y());
-        ARM_COMPUTE_RETURN_ERROR_ON((input->tensor_shape()[idx_width] + padding_left.x() + padding_right.x()) % block_shape_x != 0);
-        ARM_COMPUTE_RETURN_ERROR_ON((input->tensor_shape()[idx_height] + padding_left.y() + padding_right.y()) % block_shape_y != 0);
-        ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_channel] != output->tensor_shape()[idx_channel]);
-        ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_batch] % (block_shape_x * block_shape_y) != 0);
+        TensorShape expected_output_shape = misc::shape_calculator::compute_space_to_batch_shape(input, block_shape_x, block_shape_y, padding_left, padding_right);
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), expected_output_shape);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
     }
@@ -98,7 +93,7 @@ void CLSpaceToBatchLayerKernel::configure(const ICLTensor *input, const ICLTenso
 
 void CLSpaceToBatchLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *block_shape, const ICLTensor *paddings, ICLTensor *output)
 {
-    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, block_shape, paddings, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), paddings->info(), output->info()));
 
     _input       = input;