COMPMID-948: Add validation to CLL2NormalizeLayer

Change-Id: I452a718a60b81da51cd3e98641fd99c86c4debab
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/129451
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>

10 files changed, 332 insertions, 60 deletions

diff --git a/arm_compute/core/CL/kernels/CLL2NormalizeLayerKernel.h b/arm_compute/core/CL/kernels/CLL2NormalizeLayerKernel.h
index f7d717119b..dec4192fcd 100644
--- a/arm_compute/core/CL/kernels/CLL2NormalizeLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLL2NormalizeLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -21,8 +21,8 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#ifndef __ARM_COMPUTE_CLL2NORMALIZEKERNEL_H__
-#define __ARM_COMPUTE_CLL2NORMALIZEKERNEL_H__
+#ifndef __ARM_COMPUTE_CLL2NORMALIZELAYERKERNEL_H__
+#define __ARM_COMPUTE_CLL2NORMALIZELAYERKERNEL_H__
 
 #include "arm_compute/core/CL/ICLKernel.h"
 #include "arm_compute/core/Types.h"
@@ -31,7 +31,7 @@ namespace arm_compute
 {
 class ICLTensor;
 
-/** Interface for the reduction operation kernel */
+/** Interface for performing a L2 normalize on a given axis given the square sum of it in this axis */
 class CLL2NormalizeLayerKernel : public ICLKernel
 {
 public:
@@ -50,14 +50,30 @@ public:
 
     /** Set the input and output tensors.
      *
-     * @param[in]  input   Source tensor. Data types supported: QS8, QS16, F32.
+     * @param[in]  input   Source tensor. Data types supported: F32. Data layouts supported: NCHW.
      * @param[in]  sum     Sum values tensor. Data types supported: same as @p input.
-     * @param[out] output  Destination tensor. Data types supported: Same as @p input.
+     *                     Sum will have the same number of dimensions as input.
+     * @param[out] output  Destination tensor. Data types and data layouts supported: Same as @p input.
+     *                     Output will have the same number of dimensions as input.
      * @param[in]  axis    Axis along which to reduce. Supported reduction axis : 0
      * @param[in]  epsilon Lower bound value for the normalization.
      */
     void configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, unsigned int axis, float epsilon);
 
+    /** Static function to check if given info will lead to a valid configuration of @ref CLL2NormalizeLayerKernel.
+     *
+     * @param[in] input   Source tensor info. Data types supported: F32. Data layouts supported: NCHW.
+     * @param[in] sum     Sum values tensor info. Data types supported: same as @p input.
+     *                    Sum will have the same number of dimensions as input.
+     * @param[in] output  Destination tensor info. Data types and data layouts supported: Same as @p input.
+     *                    Output will have the same number of dimensions as input.
+     * @param[in] axis    Axis along which to reduce. Supported reduction axis : 0
+     * @param[in] epsilon Lower bound value for the normalization.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, unsigned int axis, float epsilon);
+
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
 
@@ -69,4 +85,4 @@ private:
     float            _epsilon;
 };
 } // namespace arm_compute
-#endif /*__ARM_COMPUTE_CLL2NORMALIZEKERNEL_H__ */
+#endif /*__ARM_COMPUTE_CLL2NORMALIZELAYERKERNEL_H__ */
diff --git a/arm_compute/core/CL/kernels/CLReductionOperationKernel.h b/arm_compute/core/CL/kernels/CLReductionOperationKernel.h
index 0bb001d16d..56f75e5fb7 100644
--- a/arm_compute/core/CL/kernels/CLReductionOperationKernel.h
+++ b/arm_compute/core/CL/kernels/CLReductionOperationKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -50,13 +50,26 @@ public:
 
     /** Set the input and output tensors.
      *
-     * @param[in]  input  Source tensor. Data types supported: F32.
-     * @param[out] output Destination tensor. Data types supported: Same as @p input.
+     * @param[in]  input  Source tensor. Data types supported: F32. Data layouts supported: NCHW.
+     * @param[out] output Destination tensor. Data types and data layouts supported: Same as @p input.
+     *                    Output will have the same number of dimensions as input.
      * @param[in]  axis   Axis along which to reduce. Supported reduction axis : 0
      * @param[in]  op     Reduction operation to perform.
      */
     void configure(const ICLTensor *input, ICLTensor *output, unsigned int axis, ReductionOperation op);
 
+    /** Static function to check if given info will lead to a valid configuration of @ref CLReductionOperationKernel.
+     *
+     * @param[in] input  Source tensor info. Data types supported: F32. Data layouts supported: NCHW.
+     * @param[in] output Destination tensor info. Data types and data layouts supported: Same as @p input.
+     *                   Output will have the same number of dimensions as input.
+     * @param[in] axis   Axis along which to reduce. Supported reduction axis : 0
+     * @param[in] op     Reduction operation to perform.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, ReductionOperation op);
+
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
     BorderSize border_size() const override;
diff --git a/arm_compute/runtime/CL/functions/CLL2NormalizeLayer.h b/arm_compute/runtime/CL/functions/CLL2NormalizeLayer.h
index 8aea7a641b..d3d34f877b 100644
--- a/arm_compute/runtime/CL/functions/CLL2NormalizeLayer.h
+++ b/arm_compute/runtime/CL/functions/CLL2NormalizeLayer.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -21,8 +21,8 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#ifndef __ARM_COMPUTE_CLL2NORMALIZE_H__
-#define __ARM_COMPUTE_CLL2NORMALIZE_H__
+#ifndef __ARM_COMPUTE_CLL2NORMALIZELAYER_H__
+#define __ARM_COMPUTE_CLL2NORMALIZELAYER_H__
 
 #include "arm_compute/core/CL/kernels/CLL2NormalizeLayerKernel.h"
 #include "arm_compute/core/Types.h"
@@ -39,7 +39,11 @@ namespace arm_compute
 {
 class ICLTensor;
 
-/** Perform reduction operation.
+/** Basic function to perform a L2 normalization on a given axis.
+ *
+ * This function runs the following kernels:
+ * -# @ref CLReductionOperation
+ * -# @ref CLL2NormalizeLayerKernel
  */
 class CLL2NormalizeLayer : public IFunction
 {
@@ -49,13 +53,24 @@ public:
 
     /** Set the input and output tensors.
      *
-     * @param[in]  input   Source tensor. Data types supported: QS8, QS16, F32.
-     * @param[out] output  Destination tensor. Data types supported: Same as @p input.
+     * @param[in]  input   Source tensor. Data types supported: F32. Data layouts supported: NCHW.
+     * @param[out] output  Destination tensor. Data types and data layouts supported: Same as @p input.
      * @param[in]  axis    Axis along which to reduce. Supported reduction axis : 0
-     * @param[in]  epsilon Lower bound value for the normalization.
+     * @param[in]  epsilon (Optional) Lower bound value for the normalization.
      */
     void configure(ICLTensor *input, ICLTensor *output, unsigned int axis, float epsilon = 1e-12);
 
+    /** Static function to check if given info will lead to a valid configuration of @ref CLL2NormalizeLayer.
+     *
+     * @param[in] input   Source tensor info. Data types supported: F32. Data layouts supported: NCHW.
+     * @param[in] output  Destination tensor info. Data types and data layouts supported: Same as @p input.
+     * @param[in] axis    Axis along which to reduce. Supported reduction axis : 0
+     * @param[in] epsilon (Optional) Lower bound value for the normalization.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, float epsilon = 1e-12);
+
     // Inherited methods overridden:
     void run() override;
 
@@ -66,4 +81,4 @@ private:
     CLTensor                 _sumsq;
 };
 }
-#endif /*__ARM_COMPUTE_CLL2NORMALIZE_H__ */
+#endif /*__ARM_COMPUTE_CLL2NORMALIZELAYER_H__ */
diff --git a/arm_compute/runtime/CL/functions/CLReductionOperation.h b/arm_compute/runtime/CL/functions/CLReductionOperation.h
index abec9b8dc5..b8108b507b 100644
--- a/arm_compute/runtime/CL/functions/CLReductionOperation.h
+++ b/arm_compute/runtime/CL/functions/CLReductionOperation.h
@@ -53,13 +53,24 @@ public:
 
     /** Set the input and output tensors.
      *
-     * @param[in]  input  Source tensor. Data types supported: QS8, QS16, F16, F32.
-     * @param[out] output Destination tensor. Data types supported: Same as @p input.
+     * @param[in]  input  Source tensor. Data types supported: F32. Data layouts supported: NCHW.
+     * @param[out] output Destination tensor. Data types and data layouts supported: Same as @p input.
      * @param[in]  axis   Axis along which to reduce. Supported reduction axis : 0
      * @param[in]  op     Reduction operation to perform.
      */
     void configure(ICLTensor *input, ICLTensor *output, unsigned int axis, ReductionOperation op);
 
+    /** Static function to check if given info will lead to a valid configuration of @ref CLReductionOperation.
+     *
+     * @param[in] input  Source tensor info. Data types supported: F32. Data layouts supported: NCHW.
+     * @param[in] output Destination tensor info. Data types and data layouts supported: Same as @p input.
+     * @param[in] axis   Axis along which to reduce. Supported reduction axis : 0
+     * @param[in] op     Reduction operation to perform.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, ReductionOperation op);
+
     // Inherited methods overridden:
     void run() override;
 
@@ -71,4 +82,4 @@ private:
     unsigned int                                  _num_of_stages;
 };
 }
-#endif /*__ARM_COMPUTE_CLL2NORMALIZE_H__ */
+#endif /*__ARM_COMPUTE_CLREDUCTIONOPERATION_H__ */
diff --git a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
index 36e351e048..3d30350c59 100644
--- a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
+++ b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -42,18 +42,60 @@ CLL2NormalizeLayerKernel::CLL2NormalizeLayerKernel()
 {
 }
 
-void CLL2NormalizeLayerKernel::configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, unsigned int axis, float epsilon)
+namespace
+{
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, unsigned int axis, float epsilon)
+{
+    ARM_COMPUTE_UNUSED(epsilon);
+
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, sum, output);
+    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, sum);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32);
+    ARM_COMPUTE_RETURN_ERROR_ON(input->data_layout() != DataLayout::NCHW);
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis > 0, "Unsupported reduction axis, Supported axis is 0");
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions, "Reduction axis greater than max number of dimensions");
+
+    // Reduce shape on axis
+    TensorShape sum_shape = input->tensor_shape();
+    sum_shape.set(axis, 1);
+    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(sum->tensor_shape(), sum_shape);
+
+    if(output->total_size() != 0)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(input->tensor_shape(), output->tensor_shape());
+        ARM_COMPUTE_RETURN_ERROR_ON(output->data_layout() != DataLayout::NCHW);
+    }
+
+    return Status{};
+}
+
+std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
 {
-    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32);
-    ARM_COMPUTE_ERROR_ON_NULLPTR(output);
+    const unsigned int num_elems_processed_per_iteration = 16;
+
+    Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
+
+    // Output tensor auto initialization if not yet initialized
+    auto_init_if_empty(*output, input->tensor_shape(), 1, input->data_type(), input->fixed_point_position());
 
-    // Sum and output tensor auto initialization if not yet initialized
-    auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position());
+    AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
+    AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
 
-    ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
-    ARM_COMPUTE_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions, "Reduction axis greater than max number of dimensions");
-    ARM_COMPUTE_ERROR_ON_MSG(axis > 0, "Unsupported reduction axis, Supported axis is 0");
-    ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output);
+    bool window_changed = update_window_and_padding(win, input_access, output_access);
+    output_access.set_valid_region(win, input->valid_region());
+
+    Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+
+    return std::make_tuple(err, win);
+}
+} // namespace
+
+void CLL2NormalizeLayerKernel::configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, unsigned int axis, float epsilon)
+{
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, sum, output);
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), sum->info(), output->info(), axis, epsilon));
 
     _input   = input;
     _sum     = sum;
@@ -76,15 +118,18 @@ void CLL2NormalizeLayerKernel::configure(const ICLTensor *input, const ICLTensor
     _kernel.setArg<cl_uint>(idx, _epsilon);
 
     // Configure kernel window
-    Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
+    auto win_config = validate_and_configure_window(_input->info(), _output->info());
+    ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
 
-    AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
-    AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);
+    ICLKernel::configure(std::get<1>(win_config));
+}
 
-    update_window_and_padding(win, input_access, output_access);
-    output_access.set_valid_region(win, input->info()->valid_region());
+Status CLL2NormalizeLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, unsigned int axis, float epsilon)
+{
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, sum, output, axis, epsilon));
+    ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get())));
 
-    ICLKernel::configure(win);
+    return Status{};
 }
 
 void CLL2NormalizeLayerKernel::run(const Window &window, cl::CommandQueue &queue)
diff --git a/src/core/CL/kernels/CLReductionOperationKernel.cpp b/src/core/CL/kernels/CLReductionOperationKernel.cpp
index 1dd5eb97ec..1347a9bc94 100644
--- a/src/core/CL/kernels/CLReductionOperationKernel.cpp
+++ b/src/core/CL/kernels/CLReductionOperationKernel.cpp
@@ -38,6 +38,52 @@
 
 using namespace arm_compute;
 
+namespace
+{
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, ReductionOperation op)
+{
+    ARM_COMPUTE_UNUSED(op);
+
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32);
+    ARM_COMPUTE_RETURN_ERROR_ON(input->data_layout() != DataLayout::NCHW);
+
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions, "Reduction axis greater than max number of dimensions");
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis > 0, "Unsupported reduction axis, Supported axis is 0");
+
+    if(output->total_size() != 0)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+        ARM_COMPUTE_RETURN_ERROR_ON(output->data_layout() != DataLayout::NCHW);
+    }
+
+    return Status{};
+}
+
+std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, unsigned int axis)
+{
+    // Output tensor auto initialization if not yet initialized
+    TensorShape output_shape{ input->tensor_shape() };
+    output_shape.set(axis, 1);
+    auto_init_if_empty(*output, output_shape, 1, input->data_type(), input->fixed_point_position());
+
+    const unsigned int num_elems_processed_per_iteration = 16;
+
+    Window             win          = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
+    const unsigned int border_width = ((input->dimension(0) % 128) != 0) ? 128 - input->dimension(0) % 128 : 0; // TODO (COMPMID-1143): Fix padding (possible value 127!)
+
+    AccessWindowStatic     input_access(input, 0, 0, input->dimension(0) + border_width, 1);
+    AccessWindowHorizontal output_access(output, 0, 1);
+
+    bool window_changed = update_window_and_padding(win, input_access, output_access);
+    output_access.set_valid_region(win, output->valid_region());
+
+    Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+
+    return std::make_tuple(err, win);
+}
+} // namespace
+
 CLReductionOperationKernel::CLReductionOperationKernel()
     : _input(nullptr), _output(nullptr), _reduction_axis(0), _op(ReductionOperation::SUM_SQUARE), _border_size()
 {
@@ -50,17 +96,13 @@ BorderSize CLReductionOperationKernel::border_size() const
 
 void CLReductionOperationKernel::configure(const ICLTensor *input, ICLTensor *output, unsigned int axis, ReductionOperation op)
 {
-    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32);
-    ARM_COMPUTE_ERROR_ON_NULLPTR(output);
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Output tensor auto initialization if not yet initialized
     TensorShape output_shape{ input->info()->tensor_shape() };
     output_shape.set(axis, 1);
-    auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position());
 
-    ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
-    ARM_COMPUTE_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions, "Reduction axis greater than max number of dimensions");
-    ARM_COMPUTE_ERROR_ON_MSG(axis > 0, "Unsupported reduction axis, Supported axis is 0");
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), axis, op));
 
     const unsigned int num_elems_processed_per_iteration = 16;
     const unsigned int border_width                      = ((input->info()->dimension(0) % 128) != 0) ? 128 - input->info()->dimension(0) % 128 : 0;
@@ -97,15 +139,19 @@ void CLReductionOperationKernel::configure(const ICLTensor *input, ICLTensor *ou
     _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("reduction_operation", build_opts));
 
     // Configure kernel window
-    Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
+    auto win_config = validate_and_configure_window(_input->info(), _output->info(), axis);
 
-    AccessWindowStatic     input_access(input->info(), 0, 0, input->info()->dimension(0) + border_width, 1);
-    AccessWindowHorizontal output_access(output->info(), 0, 1);
+    ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
 
-    update_window_and_padding(win, input_access, output_access);
-    output_access.set_valid_region(win, output->info()->valid_region());
+    ICLKernel::configure(std::get<1>(win_config));
+}
+
+Status CLReductionOperationKernel::validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, ReductionOperation op)
+{
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, axis, op));
+    ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get(), axis)));
 
-    ICLKernel::configure(win);
+    return Status{};
 }
 
 void CLReductionOperationKernel::run(const Window &window, cl::CommandQueue &queue)
diff --git a/src/runtime/CL/functions/CLL2NormalizeLayer.cpp b/src/runtime/CL/functions/CLL2NormalizeLayer.cpp
index d1bb65f1c9..a3010a73ea 100644
--- a/src/runtime/CL/functions/CLL2NormalizeLayer.cpp
+++ b/src/runtime/CL/functions/CLL2NormalizeLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -52,6 +52,26 @@ void CLL2NormalizeLayer::configure(ICLTensor *input, ICLTensor *output, unsigned
     _sumsq.allocator()->allocate();
 }
 
+Status CLL2NormalizeLayer::validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, float epsilon)
+{
+    TensorShape shape(input->tensor_shape());
+
+    // Create intermediate tensor info
+    TensorInfo sum_sq;
+    sum_sq.set_data_type(input->data_type());
+    sum_sq.set_tensor_shape(shape);
+
+    ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperation::validate(input, &sum_sq, axis, ReductionOperation::SUM_SQUARE));
+
+    // Reduce shape on axis (supported axis is 0)
+    shape.set(0, 1);
+    sum_sq.set_tensor_shape(shape);
+
+    ARM_COMPUTE_RETURN_ON_ERROR(CLL2NormalizeLayerKernel::validate(input, &sum_sq, output, axis, epsilon));
+
+    return Status{};
+}
+
 void CLL2NormalizeLayer::run()
 {
     _memory_group.acquire();
diff --git a/src/runtime/CL/functions/CLReductionOperation.cpp b/src/runtime/CL/functions/CLReductionOperation.cpp
index d02afb4e90..3a5133d91f 100644
--- a/src/runtime/CL/functions/CLReductionOperation.cpp
+++ b/src/runtime/CL/functions/CLReductionOperation.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -35,19 +35,64 @@
 
 using namespace arm_compute;
 
+namespace
+{
+unsigned int calculate_number_of_stages(const ITensorInfo *input)
+{
+    // Calculate number of WGs. 16 elements per thread, 8 threads per WG
+    const unsigned int num_of_wg = ceil(input->dimension(0) / 128.f);
+
+    // Calculate number of stages. First stage performs op and the rest reduction sum
+    // depending on the size of the input. Last stage should have only 1 WG.
+    const unsigned int num_of_stages = num_of_wg / 128 + 2;
+
+    return num_of_stages;
+}
+} // namespace
+
 CLReductionOperation::CLReductionOperation(std::shared_ptr<IMemoryManager> memory_manager)
     : _memory_group(std::move(memory_manager)), _sums_vector(), _reduction_kernels_vector(), _border_handlers_vector(), _num_of_stages()
 {
 }
 
-void CLReductionOperation::configure(ICLTensor *input, ICLTensor *output, unsigned int axis, ReductionOperation op)
+Status CLReductionOperation::validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, ReductionOperation op)
 {
-    // Calculate number of WGs. 16 elements per thread, 8 threads per WG
-    unsigned int num_of_wg = ceil(input->info()->dimension(0) / 128.f);
+    const unsigned int num_of_stages = calculate_number_of_stages(input);
 
-    // Calculate number of stages. First stage performs op and the rest reduction sum
-    // depending on the size of the input. Last stage should have only 1 WG.
-    _num_of_stages = num_of_wg / 128 + 2;
+    // Create temporary tensor infos
+    auto sums_vector = arm_compute::support::cpp14::make_unique<TensorInfo[]>(num_of_stages - 1);
+
+    // Create intermediate tensor info
+    TensorShape shape{ input->tensor_shape() };
+
+    for(unsigned int i = 0; i < num_of_stages - 1; i++)
+    {
+        shape.set(0, ceil(shape.x() / 128.f));
+        sums_vector[i].set_data_type(input->data_type());
+        sums_vector[i].set_tensor_shape(shape);
+        sums_vector[i].set_num_channels(input->num_channels());
+        sums_vector[i].set_fixed_point_position(input->fixed_point_position());
+    }
+
+    // Validate ReductionOperation only on first kernel
+    ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(input, sums_vector.get(), axis, op));
+
+    // Validate ReductionOperation on intermediate stages
+    for(unsigned int i = 1; i < num_of_stages - 1; ++i)
+    {
+        ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(sums_vector.get() + i - 1, sums_vector.get() + i, axis, op));
+    }
+
+    // Validate ReductionOperation on the last stage
+    const unsigned int last_stage = num_of_stages - 1;
+    ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(sums_vector.get() + last_stage - 1, output, axis, op));
+
+    return Status{};
+}
+
+void CLReductionOperation::configure(ICLTensor *input, ICLTensor *output, unsigned int axis, ReductionOperation op)
+{
+    _num_of_stages = calculate_number_of_stages(input->info());
 
     // Create temporary tensors
     _sums_vector = arm_compute::support::cpp14::make_unique<CLTensor[]>(_num_of_stages - 1);
@@ -95,4 +140,4 @@ void CLReductionOperation::run()
     }
 
     _memory_group.release();
-}
\ No newline at end of file
+}
diff --git a/tests/validation/CL/L2NormalizeLayer.cpp b/tests/validation/CL/L2NormalizeLayer.cpp
index bc2374bc68..3d121b079d 100644
--- a/tests/validation/CL/L2NormalizeLayer.cpp
+++ b/tests/validation/CL/L2NormalizeLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -50,6 +50,37 @@ constexpr AbsoluteTolerance<float> tolerance_f32(0.00001f);
 TEST_SUITE(CL)
 TEST_SUITE(L2NormalizeLayer)
 
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+    framework::dataset::make("InputInfo",  { TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Mismatching data type input/output
+                                             TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Mismatching shape input/output
+                                             TensorInfo(TensorShape(128U, 64U), 2, DataType::F32), // Number of Input channels != 1
+                                             TensorInfo(TensorShape(128U, 64U), 1, DataType::S16), // DataType != F32
+                                             TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Axis >= num_max_dimensions
+                                             TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Axis > 0
+                                             TensorInfo(TensorShape(128U, 64U), 1, DataType::F32)
+                                           }),
+    framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(128U, 64U), 1, DataType::F16),
+                                             TensorInfo(TensorShape(256U, 64U), 1, DataType::F32),
+                                             TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
+                                             TensorInfo(TensorShape(128U, 64U), 1, DataType::S16),
+                                             TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
+                                             TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
+                                             TensorInfo(TensorShape(128U, 64U), 1, DataType::F32)
+                                           })),
+    framework::dataset::make("Axis",       { 0U, 0U, 0U, 0U, static_cast<unsigned int>(TensorShape::num_max_dimensions), 1U, 0U })),
+    framework::dataset::make("Expected",   { false, false, false, false, false, false, true })),
+    input_info, output_info, axis, expected)
+{
+    bool is_valid = bool(CLL2NormalizeLayer::validate(&input_info.clone()->set_is_resizable(false),
+                                                      &output_info.clone()->set_is_resizable(false),
+                                                      axis));
+    ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
 template <typename T>
 using CLL2NormalizeLayerFixture = L2NormalizeLayerValidationFixture<CLTensor, CLAccessor, CLL2NormalizeLayer, T>;
 
diff --git a/tests/validation/CL/ReductionOperation.cpp b/tests/validation/CL/ReductionOperation.cpp
index 684ed4694f..a2a5eff4de 100644
--- a/tests/validation/CL/ReductionOperation.cpp
+++ b/tests/validation/CL/ReductionOperation.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -50,6 +50,36 @@ RelativeTolerance<float> tolerance_f32(0.00001f);
 TEST_SUITE(CL)
 TEST_SUITE(ReductionOperation)
 
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+    framework::dataset::make("InputInfo",          { TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Mismatching data type input/output
+                                                     TensorInfo(TensorShape(128U, 64U), 2, DataType::F32), // Number of Input channels != 1
+                                                     TensorInfo(TensorShape(128U, 64U), 1, DataType::S16), // DataType != F32
+                                                     TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Axis >= num_max_dimensions
+                                                     TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Axis > 0
+                                                     TensorInfo(TensorShape(128U, 64U), 1, DataType::F32)
+                                                   }),
+    framework::dataset::make("OutputInfo",         { TensorInfo(TensorShape(128U, 64U), 1, DataType::F16),
+                                                     TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
+                                                     TensorInfo(TensorShape(128U, 64U), 1, DataType::S16),
+                                                     TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
+                                                     TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
+                                                     TensorInfo(TensorShape(128U, 64U), 1, DataType::F32)
+                                                   })),
+    framework::dataset::make("Axis",               { 0U, 0U, 0U, static_cast<unsigned int>(TensorShape::num_max_dimensions), 1U, 0U })),
+    framework::dataset::make("Expected",           { false, false, false, false, false, true })),
+    input_info, output_info, axis, expected)
+{
+    bool is_valid = bool(CLReductionOperation::validate(&input_info.clone()->set_is_resizable(false),
+                                                        &output_info.clone()->set_is_resizable(false),
+                                                        axis,
+                                                        ReductionOperation::SUM_SQUARE));
+    ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
 template <typename T>
 using CLReductionOperationFixture = ReductionOperationValidationFixture<CLTensor, CLAccessor, CLReductionOperation, T>;