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diff --git a/libs/ARMComputeEx/src/core/CL/cl_kernels/batch_to_space_nd.cl b/libs/ARMComputeEx/src/core/CL/cl_kernels/batch_to_space_nd.cl
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--- a/libs/ARMComputeEx/src/core/CL/cl_kernels/batch_to_space_nd.cl
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@@ -1,70 +0,0 @@
-/*
- * 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(BLOCK_SIZE0) && defined(BLOCK_SIZE1) && defined(BATCH_OUT)
-/** Perform batch to space rearrangement of tensor
- *
- * @attention Data type can be passed using the -DDATA_TYPE compile flag, e.g. -DDATA_TYPE=float
- * @attention Output tensor batch should be given as a preprocessor argument using -DBATCH_OUT=size. e.g. -DBATCH_OUT=16
- * @attention block size should be given as a preprocessor argument using -DBLOCK_SIZE0=size. e.g. -DBLOCK_SIZE0=1
- *
- * @param[in] input_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32
- * @param[in] input_stride_x Stride of the source tensor 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 tensor 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 tensor
- *
- * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p inpu
-t_ptr
- * @param[in] output_stride_x Stride of the destination tensor 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 tensor 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 destination 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 destination 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 tensor
- */
-__kernel void batch_to_space_nd(
- TENSOR4D_DECLARATION(input),
- TENSOR4D_DECLARATION(output))
- {
- Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(input, 0);
- Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT(output, DEPTH_OUT);
-
- int out_index[4]={0};
- int in_index[4]={0};
-
- out_index[0] = get_global_id(0);//W
- out_index[1] = get_global_id(1);//H
- out_index[2] = get_global_id(2) % DEPTH_OUT;//C
- out_index[3] = get_global_id(2) / DEPTH_OUT;//N
-
- in_index[0] = out_index[0]/BLOCK_SIZE1;
- in_index[1] = out_index[1]/BLOCK_SIZE0;
- in_index[2] = out_index[2];
- in_index[3] = out_index[3] + ((out_index[1] % BLOCK_SIZE0) * BLOCK_SIZE0 + out_index[0] % BLOCK_SIZE1) * BATCH_OUT;
-
- *((__global DATA_TYPE *)out.ptr) = *((__global DATA_TYPE *)tensor4D_offset(&in, in_index[0], in_index[1], in_index[2], in_index[3]));
- }
-#endif // defined(DATA_TYPE) && defined(DEPTH_IN) && defined(BLOCK_SIZE0) && defined(BLOCK_SIZE1) && defined(BATCH_OUT)