77 lines
		
	
	
		
			3.0 KiB
		
	
	
	
		
			C++
		
	
	
	
			
		
		
	
	
			77 lines
		
	
	
		
			3.0 KiB
		
	
	
	
		
			C++
		
	
	
	
| /*
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|  * Copyright (c) 2019-2020 Arm Limited.
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|  *
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|  * SPDX-License-Identifier: MIT
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|  *
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|  * Permission is hereby granted, free of charge, to any person obtaining a copy
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|  * of this software and associated documentation files (the "Software"), to
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|  * deal in the Software without restriction, including without limitation the
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|  * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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|  * sell copies of the Software, and to permit persons to whom the Software is
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|  * furnished to do so, subject to the following conditions:
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|  *
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|  * The above copyright notice and this permission notice shall be included in all
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|  * copies or substantial portions of the Software.
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|  *
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|  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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|  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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|  * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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|  * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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|  * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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|  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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|  * SOFTWARE.
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|  */
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| #include "DepthToSpaceLayer.h"
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| 
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| #include "tests/validation/Helpers.h"
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| 
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| namespace arm_compute
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| {
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| namespace test
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| {
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| namespace validation
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| {
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| namespace reference
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| {
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| // Batch to Space
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| template <typename T>
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| SimpleTensor<T> depth_to_space(const SimpleTensor<T> &src, const TensorShape &dst_shape, int32_t block_shape)
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| {
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|     ARM_COMPUTE_ERROR_ON(block_shape <= 0);
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|     SimpleTensor<T> result(dst_shape, src.data_type());
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| 
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|     const auto width_in   = static_cast<int>(src.shape()[0]);
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|     const auto height_in  = static_cast<int>(src.shape()[1]);
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|     const auto channel_in = static_cast<int>(src.shape()[2]);
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|     const auto batch_in   = static_cast<int>(src.shape()[3]);
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|     const int  r          = channel_in / (block_shape * block_shape);
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| #if defined(_OPENMP)
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|     #pragma omp parallel for collapse(4)
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| #endif /* _OPENMP */
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|     for(int b = 0; b < batch_in; ++b)
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|     {
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|         for(int z = 0; z < channel_in; ++z)
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|         {
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|             for(int y = 0; y < height_in; ++y)
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|             {
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|                 for(int x = 0; x < width_in; ++x)
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|                 {
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|                     const int out_x   = (block_shape * x + (z / r) % block_shape);
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|                     const int out_y   = (block_shape * y + (z / r) / block_shape);
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|                     const int out_pos = out_x + dst_shape[0] * out_y + (z % r) * dst_shape[0] * dst_shape[1] + b * dst_shape[0] * dst_shape[1] * dst_shape[2];
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|                     const int in_pos  = x + width_in * y + z * width_in * height_in + b * width_in * height_in * channel_in;
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|                     result[out_pos]   = src[in_pos];
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|                 }
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|             }
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|         }
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|     }
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| 
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|     return result;
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| }
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| template SimpleTensor<float> depth_to_space(const SimpleTensor<float> &src, const TensorShape &dst_shape, int32_t block_shape);
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| template SimpleTensor<half> depth_to_space(const SimpleTensor<half> &src, const TensorShape &dst_shape, int32_t block_shape);
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| } // namespace reference
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| } // namespace validation
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| } // namespace test
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| } // namespace arm_compute
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