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diff --git a/compute/ARMComputeEx/src/core/CL/cl_kernels/reduce_operation.cl b/compute/ARMComputeEx/src/core/CL/cl_kernels/reduce_operation.cl
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+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ * Copyright (c) 2016, 2017 ARM Limited.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "helpers.h"
+
+#if defined(DATA_TYPE) && defined(DEPTH_OUT) && defined(OP_CODE)
+/** Perform reduce max/min
+ *
+ * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g.
+ * -DDATA_TYPE=short
+ * @attention Output tensor depth should be given as a preprocessor argument using -DDEPTH_OUT=size.
+ * e.g. -DDEPTH_OUT=16
+ * @attention Operation type(code) specifying which operation to perform should be passed as
+ * preprocessor argument using -DOP_CODE = number. e.g. -DOP_CODE=1
+ *
+ * @param[in] input_ptr Pointer to the source image. Supported data
+ * types: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32
+ * @param[in] input_stride_x Stride of the source image in X dimension (in
+ * bytes)
+ * @param[in] input_step_x input_stride_x * number of elements along X
+ * processed per workitem(in bytes)
+ * @param[in] input_stride_y Stride of the source image in Y dimension (in
+ * bytes)
+ * @param[in] input_step_y input_stride_y * number of elements along Y
+ * processed per workitem(in bytes)
+ * @param[in] input_stride_z Stride of the source tensor in Z dimension (in
+ * bytes)
+ * @param[in] input_step_z input_stride_z * number of elements along Z
+ * processed per workitem(in bytes)
+ * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source
+ * image
+ * @param[in] input_stride_w Stride of the source tensor in W dimension (in
+ * bytes)
+ * @param[in] input_step_w output_stride_w * number of elements along W
+ * processed per workitem(in bytes)
+ * @param[out] output_ptr Pointer to the destination image. Supported data
+ * types: same as @p input_ptr
+ * @param[in] output_stride_x Stride of the destination image in X dimension
+ * (in bytes)
+ * @param[in] output_step_x output_stride_x * number of elements along X
+ * processed per workitem(in bytes)
+ * @param[in] output_stride_y Stride of the destination image in Y dimension
+ * (in bytes)
+ * @param[in] output_step_y output_stride_y * number of elements along Y
+ * processed per workitem(in bytes)
+ * @param[in] output_stride_z Stride of the source tensor in Z dimension (in
+ * bytes)
+ * @param[in] output_step_z output_stride_z * number of elements along Z
+ * processed per workitem(in bytes)
+ * @param[in] output_stride_w Stride of the source tensor in W dimension (in
+ * bytes)
+ * @param[in] output_step_w output_stride_w * number of elements along W
+ * processed per workitem(in bytes)
+ * @param[in] output_offset_first_element_in_bytes The offset of the first element in the
+ * destination image
+ * @param[in] axis Axis through which reduction occurs
+ * @param[in] dim Dimension across the axis to be reduced.
+ */
+__kernel void reduce_min_max(TENSOR4D_DECLARATION(input), TENSOR4D_DECLARATION(output),
+ const int axis, const int dim)
+{
+ Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT(input, 0);
+ Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT(output, DEPTH_OUT);
+
+ int indices[4] = {
+ get_global_id(0), get_global_id(1), get_global_id(2) % DEPTH_OUT,
+ get_global_id(2) / DEPTH_OUT,
+ };
+
+ DATA_TYPE value =
+ *((__global DATA_TYPE *)tensor4D_offset(&in, indices[0], indices[1], indices[2], indices[3]));
+ for (int i = 1; i < dim; ++i)
+ {
+ indices[axis] = i;
+
+#if OP_CODE == 1 // REDUCE_MAX
+ value = max(value, *((__global DATA_TYPE *)tensor4D_offset(&in, indices[0], indices[1],
+ indices[2], indices[3])));
+
+#elif OP_CODE == 2 // REDUCE_MIN
+ value = min(value, *((__global DATA_TYPE *)tensor4D_offset(&in, indices[0], indices[1],
+ indices[2], indices[3])));
+
+#else // OP NOT SUPPORTED
+ return;
+
+#endif
+ }
+
+ *((__global DATA_TYPE *)out.ptr) = value;
+}
+
+/** Perform reduce sum/mean
+ *
+ * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g.
+ * -DDATA_TYPE=short
+ * @attention Output tensor depth should be given as a preprocessor argument using -DDEPTH_OUT=size.
+ * e.g. -DDEPTH_OUT=16
+ * @attention Operation type(code) specifying which operation to perform should be passed as
+ * preprocessor argument using -DOP_CODE = number. e.g. -DOP_CODE=1
+ *
+ * @param[in] input_ptr Pointer to the source image. Supported data
+ * types: U8/S8/U16/S16/F16/U32/S32/F32
+ * @param[in] input_stride_x Stride of the source image in X dimension (in
+ * bytes)
+ * @param[in] input_step_x input_stride_x * number of elements along X
+ * processed per workitem(in bytes)
+ * @param[in] input_stride_y Stride of the source image in Y dimension (in
+ * bytes)
+ * @param[in] input_step_y input_stride_y * number of elements along Y
+ * processed per workitem(in bytes)
+ * @param[in] input_stride_z Stride of the source tensor in Z dimension (in
+ * bytes)
+ * @param[in] input_step_z input_stride_z * number of elements along Z
+ * processed per workitem(in bytes)
+ * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source
+ * image
+ * @param[in] input_stride_w Stride of the source tensor in W dimension (in
+ * bytes)
+ * @param[in] input_step_w output_stride_w * number of elements along W
+ * processed per workitem(in bytes)
+ * @param[out] output_ptr Pointer to the destination image. Supported data
+ * types: same as @p input_ptr
+ * @param[in] output_stride_x Stride of the destination image in X dimension
+ * (in bytes)
+ * @param[in] output_step_x output_stride_x * number of elements along X
+ * processed per workitem(in bytes)
+ * @param[in] output_stride_y Stride of the destination image in Y dimension
+ * (in bytes)
+ * @param[in] output_step_y output_stride_y * number of elements along Y
+ * processed per workitem(in bytes)
+ * @param[in] output_stride_z Stride of the source tensor in Z dimension (in
+ * bytes)
+ * @param[in] output_step_z output_stride_z * number of elements along Z
+ * processed per workitem(in bytes)
+ * @param[in] output_stride_w Stride of the source tensor in W dimension (in
+ * bytes)
+ * @param[in] output_step_w output_stride_w * number of elements along W
+ * processed per workitem(in bytes)
+ * @param[in] output_offset_first_element_in_bytes The offset of the first element in the
+ * destination image
+ * @param[in] axis Axis through which reduction occurs
+ * @param[in] dim Dimension across the axis to be reduced.
+ */
+__kernel void reduce_sum_mean(TENSOR4D_DECLARATION(input), TENSOR4D_DECLARATION(output),
+ const int axis, const int dim)
+{
+ Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT(input, 0);
+ Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT(output, DEPTH_OUT);
+
+ int indices[4] = {
+ get_global_id(0), get_global_id(1), get_global_id(2) % DEPTH_OUT,
+ get_global_id(2) / DEPTH_OUT,
+ };
+
+ DATA_TYPE sum_value = (DATA_TYPE)0;
+ for (int i = 0; i < dim; ++i)
+ {
+ indices[axis] = i;
+ sum_value += *(
+ (__global DATA_TYPE *)tensor4D_offset(&in, indices[0], indices[1], indices[2], indices[3]));
+ }
+
+#if OP_CODE == 3 // REDUCE_SUM
+ *((__global DATA_TYPE *)out.ptr) = sum_value;
+
+#elif OP_CODE == 4 // REDUCE_MEAN
+ *((__global DATA_TYPE *)out.ptr) = sum_value / CONVERT(dim, DATA_TYPE);
+
+#else // OP NOT SUPPORTED
+ return;
+
+#endif
+}
+#endif // defined(DATA_TYPE) && defined(DEPTH_OUT) && defined(OP_CODE)
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