xref: /aosp_15_r20/external/ComputeLibrary/src/core/CL/kernels/CLROIPoolingLayerKernel.cpp (revision c217d954acce2dbc11938adb493fc0abd69584f3)
1 /*
2  * Copyright (c) 2017-2021 Arm Limited.
3  *
4  * SPDX-License-Identifier: MIT
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7  * of this software and associated documentation files (the "Software"), to
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13  * The above copyright notice and this permission notice shall be included in all
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24 #include "src/core/CL/kernels/CLROIPoolingLayerKernel.h"
25 
26 #include "arm_compute/core/CL/CLHelpers.h"
27 #include "arm_compute/core/CL/CLKernelLibrary.h"
28 #include "arm_compute/core/CL/ICLTensor.h"
29 #include "arm_compute/core/CL/OpenCL.h"
30 #include "arm_compute/core/Helpers.h"
31 #include "arm_compute/core/TensorInfo.h"
32 #include "arm_compute/core/Utils.h"
33 #include "src/core/CL/CLValidate.h"
34 #include "src/core/helpers/AutoConfiguration.h"
35 #include "src/core/helpers/WindowHelpers.h"
36 #include "support/StringSupport.h"
37 
38 #include <cfloat>
39 #include <cmath>
40 #include <string>
41 
42 namespace arm_compute
43 {
CLROIPoolingLayerKernel()44 CLROIPoolingLayerKernel::CLROIPoolingLayerKernel()
45     : _input(nullptr), _rois(nullptr), _output(nullptr), _pool_info(0, 0, 0.f)
46 {
47     _type = CLKernelType::ELEMENTWISE;
48 }
49 
validate(const ITensorInfo * input,const ITensorInfo * rois,const ITensorInfo * output,const ROIPoolingLayerInfo & pool_info)50 Status CLROIPoolingLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *rois, const ITensorInfo *output, const ROIPoolingLayerInfo &pool_info)
51 {
52     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, rois, output);
53 
54     //Validate arguments
55     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, rois, output);
56     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(rois, 1, DataType::U16);
57     ARM_COMPUTE_RETURN_ERROR_ON(rois->dimension(0) != 5);
58     ARM_COMPUTE_RETURN_ERROR_ON(rois->num_dimensions() > 2);
59     ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
60     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16, DataType::QASYMM8);
61     ARM_COMPUTE_RETURN_ERROR_ON((pool_info.pooled_width() == 0) || (pool_info.pooled_height() == 0));
62 
63     if(output->total_size() != 0)
64     {
65         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
66         ARM_COMPUTE_RETURN_ERROR_ON((output->dimension(0) != pool_info.pooled_width()) || (output->dimension(1) != pool_info.pooled_height()));
67         ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(2) != output->dimension(2));
68         ARM_COMPUTE_RETURN_ERROR_ON(rois->dimension(1) != output->dimension(3));
69     }
70 
71     return Status{};
72 }
73 
configure(const ICLTensor * input,const ICLTensor * rois,ICLTensor * output,const ROIPoolingLayerInfo & pool_info)74 void CLROIPoolingLayerKernel::configure(const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info)
75 {
76     configure(CLKernelLibrary::get().get_compile_context(), input, rois, output, pool_info);
77 }
78 
configure(const CLCompileContext & compile_context,const ICLTensor * input,const ICLTensor * rois,const ICLTensor * output,const ROIPoolingLayerInfo & pool_info)79 void CLROIPoolingLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *rois, const ICLTensor *output, const ROIPoolingLayerInfo &pool_info)
80 {
81     ARM_COMPUTE_ERROR_THROW_ON(CLROIPoolingLayerKernel::validate(input->info(), rois->info(), output->info(), pool_info));
82 
83     auto padding_info = get_padding_info({ input, rois, output });
84 
85     // Output auto initialization if not yet initialized
86     TensorShape output_shape(pool_info.pooled_width(), pool_info.pooled_height(), input->info()->dimension(2), rois->info()->dimension(1));
87     auto_init_if_empty(*(output->info()), output_shape, 1, input->info()->data_type(), output->info()->quantization_info());
88 
89     // Set instance variables
90     _input     = input;
91     _rois      = rois;
92     _output    = output;
93     _pool_info = pool_info;
94 
95     const DataType data_type = input->info()->data_type();
96     const bool     is_qasymm = is_data_type_quantized_asymmetric(data_type);
97 
98     // Set build options
99     CLBuildOptions build_opts;
100     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type));
101     build_opts.add_option("-DDATA_SIZE=" + get_data_size_from_data_type(data_type));
102     build_opts.add_option("-DMAX_DIM_X=" + support::cpp11::to_string(_input->info()->dimension(Window::DimX)));
103     build_opts.add_option("-DMAX_DIM_Y=" + support::cpp11::to_string(_input->info()->dimension(Window::DimY)));
104     build_opts.add_option("-DMAX_DIM_Z=" + support::cpp11::to_string(_input->info()->dimension(Window::DimZ)));
105     build_opts.add_option("-DPOOLED_DIM_X=" + support::cpp11::to_string(pool_info.pooled_width()));
106     build_opts.add_option("-DPOOLED_DIM_Y=" + support::cpp11::to_string(pool_info.pooled_height()));
107     build_opts.add_option("-DSPATIAL_SCALE=" + support::cpp11::to_string(pool_info.spatial_scale()));
108 
109     if(is_qasymm)
110     {
111         // Determine quantization info scale, offset
112         UniformQuantizationInfo uqinfo = UniformQuantizationInfo();
113         uqinfo                         = compute_requantization_scale_offset(_input->info()->quantization_info().uniform(), _output->info()->quantization_info().uniform());
114         build_opts.add_option("-DOFFSET_OUT=" + float_to_string_with_full_precision(uqinfo.offset));
115         build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(uqinfo.scale));
116 
117         // Specify minimum possible value of datatype
118         build_opts.add_option("-DMIN_VALUE=" + support::cpp11::to_string(0));
119     }
120     else
121     {
122         // Specify min value of F32 datatype
123         build_opts.add_option("-DMIN_VALUE=" + support::cpp11::to_string(-FLT_MAX));
124     }
125 
126     Window win = calculate_max_window(*(output->info()), Steps());
127     ICLKernel::configure_internal(win);
128 
129     // Create kernel
130     std::string kernel_name = "roi_pooling_layer";
131     _kernel                 = create_kernel(compile_context, kernel_name, build_opts.options());
132 
133     ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
134 }
135 
run(const Window & window,cl::CommandQueue & queue)136 void CLROIPoolingLayerKernel::run(const Window &window, cl::CommandQueue &queue)
137 {
138     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
139     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
140 
141     Window slice      = window.first_slice_window_3D();
142     Window slice_rois = slice;
143     // Parallelize spatially and across the fourth dimension of the output tensor (also across ROITensor)
144     slice_rois.set_dimension_step(Window::DimX, _rois->info()->dimension(0));
145     slice.set(Window::DimZ, window[3]);
146 
147     // Set arguments
148     unsigned int idx = 0;
149     add_3D_tensor_argument(idx, _input, slice);
150     add_2D_tensor_argument(idx, _rois, slice_rois);
151     add_3D_tensor_argument(idx, _output, slice);
152     add_argument<cl_uint>(idx, _input->info()->strides_in_bytes()[3]);
153     add_argument<cl_uint>(idx, _output->info()->strides_in_bytes()[3]);
154 
155     enqueue(queue, *this, slice, lws_hint());
156 }
157 } // namespace arm_compute
158