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1 /*
2  * Copyright (c) 2018-2020 Arm Limited.
3  *
4  * SPDX-License-Identifier: MIT
5  *
6  * Permission is hereby granted, free of charge, to any person obtaining a copy
7  * of this software and associated documentation files (the "Software"), to
8  * deal in the Software without restriction, including without limitation the
9  * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
10  * sell copies of the Software, and to permit persons to whom the Software is
11  * furnished to do so, subject to the following conditions:
12  *
13  * The above copyright notice and this permission notice shall be included in all
14  * copies or substantial portions of the Software.
15  *
16  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
18  * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19  * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20  * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22  * SOFTWARE.
23  */
24 
25 #include "arm_compute/runtime/CL/functions/CLSpaceToBatchLayer.h"
26 
27 #include "arm_compute/core/Error.h"
28 #include "arm_compute/core/TensorInfo.h"
29 #include "arm_compute/core/Types.h"
30 #include "arm_compute/core/Validate.h"
31 #include "arm_compute/runtime/CL/CLScheduler.h"
32 #include "src/core/CL/kernels/CLMemsetKernel.h"
33 #include "src/core/CL/kernels/CLSpaceToBatchLayerKernel.h"
34 #include "support/MemorySupport.h"
35 
36 namespace arm_compute
37 {
CLSpaceToBatchLayer()38 CLSpaceToBatchLayer::CLSpaceToBatchLayer()
39     : _space_to_batch_kernel(support::cpp14::make_unique<CLSpaceToBatchLayerKernel>()),
40       _memset_kernel(support::cpp14::make_unique<CLMemsetKernel>()),
41       _has_padding(false)
42 {
43 }
44 
45 CLSpaceToBatchLayer::~CLSpaceToBatchLayer() = default;
46 
configure(const ICLTensor * input,const ICLTensor * block_shape,const ICLTensor * paddings,ICLTensor * output)47 void CLSpaceToBatchLayer::configure(const ICLTensor *input, const ICLTensor *block_shape, const ICLTensor *paddings, ICLTensor *output)
48 {
49     configure(CLKernelLibrary::get().get_compile_context(), input, block_shape, paddings, output);
50 }
51 
configure(const CLCompileContext & compile_context,const ICLTensor * input,const ICLTensor * block_shape,const ICLTensor * paddings,ICLTensor * output)52 void CLSpaceToBatchLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *block_shape, const ICLTensor *paddings, ICLTensor *output)
53 {
54     ARM_COMPUTE_ERROR_ON_NULLPTR(input, block_shape, paddings, output);
55 
56     if(input->info()->tensor_shape().total_size() != output->info()->tensor_shape().total_size())
57     {
58         _has_padding = true;
59         _memset_kernel->configure(compile_context, output, PixelValue(0, input->info()->data_type(), input->info()->quantization_info()));
60     }
61     _space_to_batch_kernel->configure(compile_context, input, block_shape, paddings, output);
62 }
63 
configure(const ICLTensor * input,const int block_shape_x,const int block_shape_y,const Size2D & padding_left,const Size2D & padding_right,ICLTensor * output)64 void CLSpaceToBatchLayer::configure(const ICLTensor *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right, ICLTensor *output)
65 {
66     configure(CLKernelLibrary::get().get_compile_context(), input, block_shape_x, block_shape_y, padding_left, padding_right, output);
67 }
68 
configure(const CLCompileContext & compile_context,const ICLTensor * input,const int block_shape_x,const int block_shape_y,const Size2D & padding_left,const Size2D & padding_right,ICLTensor * output)69 void CLSpaceToBatchLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left,
70                                     const Size2D &padding_right, ICLTensor *output)
71 {
72     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
73 
74     if(input->info()->tensor_shape().total_size() != output->info()->tensor_shape().total_size())
75     {
76         _has_padding = true;
77         _memset_kernel->configure(compile_context, output, PixelValue(0, input->info()->data_type(), input->info()->quantization_info()));
78     }
79     _space_to_batch_kernel->configure(compile_context, input, block_shape_x, block_shape_y, padding_left, padding_right, output);
80 }
81 
validate(const ITensorInfo * input,const ITensorInfo * block_shape,const ITensorInfo * paddings,const ITensorInfo * output)82 Status CLSpaceToBatchLayer::validate(const ITensorInfo *input, const ITensorInfo *block_shape, const ITensorInfo *paddings, const ITensorInfo *output)
83 {
84     ARM_COMPUTE_RETURN_ON_ERROR(CLMemsetKernel::validate(output, PixelValue(0, input->data_type(), input->quantization_info())));
85     ARM_COMPUTE_RETURN_ON_ERROR(CLSpaceToBatchLayerKernel::validate(input, block_shape, paddings, output));
86 
87     return Status{};
88 }
89 
validate(const ITensorInfo * input,const int block_shape_x,const int block_shape_y,const Size2D & padding_left,const Size2D & padding_right,const ITensorInfo * output)90 Status CLSpaceToBatchLayer::validate(const ITensorInfo *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right,
91                                      const ITensorInfo *output)
92 {
93     ARM_COMPUTE_RETURN_ON_ERROR(CLMemsetKernel::validate(output, PixelValue(0, input->data_type(), input->quantization_info())));
94     ARM_COMPUTE_RETURN_ON_ERROR(CLSpaceToBatchLayerKernel::validate(input, block_shape_x, block_shape_y, padding_left, padding_right, output));
95 
96     return Status{};
97 }
98 
run()99 void CLSpaceToBatchLayer::run()
100 {
101     // Zero out output only if we have paddings
102     if(_has_padding)
103     {
104         CLScheduler::get().enqueue(*_memset_kernel, true);
105     }
106     CLScheduler::get().enqueue(*_space_to_batch_kernel, true);
107 }
108 } // namespace arm_compute
109