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1 /*
2  * Copyright (c) 2017-2020 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/core/GLES_COMPUTE/kernels/GCIm2ColKernel.h"
26 
27 #include "arm_compute/core/Error.h"
28 #include "arm_compute/core/GLES_COMPUTE/GCHelpers.h"
29 #include "arm_compute/core/GLES_COMPUTE/GCKernelLibrary.h"
30 #include "arm_compute/core/GLES_COMPUTE/IGCTensor.h"
31 #include "arm_compute/core/GLES_COMPUTE/OpenGLES.h"
32 #include "arm_compute/core/Helpers.h"
33 #include "arm_compute/core/Size2D.h"
34 #include "arm_compute/core/TensorInfo.h"
35 #include "arm_compute/core/Types.h"
36 #include "arm_compute/core/Validate.h"
37 #include "src/core/AccessWindowStatic.h"
38 #include "src/core/helpers/AutoConfiguration.h"
39 #include "src/core/helpers/WindowHelpers.h"
40 #include "support/StringSupport.h"
41 
42 #include <cmath>
43 #include <tuple>
44 
45 using namespace arm_compute;
46 
47 namespace
48 {
validate_arguments(const ITensorInfo * input,const ITensorInfo * output)49 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output)
50 {
51     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
52     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
53 
54     // Checks performed when output is configured
55     if(output->total_size() != 0)
56     {
57         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
58     }
59 
60     return Status{};
61 }
62 } // namespace
63 
GCIm2ColKernel()64 GCIm2ColKernel::GCIm2ColKernel()
65     : _input(nullptr), _output(nullptr), _convolved_dims(), _kernel_dims(), _num_elems_processed_per_iteration(1), _run_func(nullptr)
66 {
67 }
68 
configure(const IGCTensor * input,IGCTensor * output,const Size2D & kernel_dims,const PadStrideInfo & conv_info,bool has_bias,const Size2D & dilation)69 void GCIm2ColKernel::configure(const IGCTensor *input, IGCTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation)
70 {
71     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
72 
73     // Perform validation step
74     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));
75 
76     _input  = input;
77     _output = output;
78 
79     // Create kernel
80     std::set<std::string> build_opts;
81     std::string           dt_name = (input->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
82     build_opts.emplace("#define LOCAL_SIZE_X " + support::cpp11::to_string(1));
83     build_opts.emplace("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1));
84     build_opts.emplace("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1));
85     build_opts.insert("#define " + dt_name);
86 
87     if(has_bias)
88     {
89         build_opts.emplace("#define HAS_BIAS");
90     }
91 
92     int stride_x = 0;
93     int stride_y = 0;
94 
95     std::tie(stride_x, stride_y) = conv_info.stride();
96     _kernel_dims = std::make_pair(kernel_dims.width, kernel_dims.height);
97 
98     const bool run_img2col_reduced = (output->info()->dimension(0) == (input->info()->dimension(0) * input->info()->dimension(1) * input->info()->dimension(2))) && (TensorShape::num_max_dimensions >= 4)
99                                      && (std::equal(input->info()->tensor_shape().cbegin() + 3,
100                                                     input->info()->tensor_shape().cend(),
101                                                     output->info()->tensor_shape().cbegin() + 1))
102                                      && ((stride_x == 1) && (stride_y == 1) && !conv_info.has_padding())
103                                      && (dilation == Size2D(1U, 1U));
104 
105     std::string kernel_name = "im2col_generic";
106     if(!run_img2col_reduced)
107     {
108         if(input->info()->data_type() == DataType::F16 && _kernel_dims == std::pair<unsigned int, unsigned int>(1, 1))
109         {
110             build_opts.emplace("#define KERNEL_1x1");
111         }
112 
113         build_opts.emplace("#define IM2COL_GENERIC");
114         _convolved_dims = scaled_dimensions(input->info()->dimension(0), input->info()->dimension(1),
115                                             kernel_dims.width, kernel_dims.height,
116                                             conv_info, dilation);
117         _num_elems_processed_per_iteration = (input->info()->data_type() == DataType::F32) ? 1 : 2;
118 
119         build_opts.emplace("#define KERNEL_WIDTH " + support::cpp11::to_string(kernel_dims.width));
120         build_opts.emplace("#define KERNEL_HEIGHT " + support::cpp11::to_string(kernel_dims.height));
121         build_opts.emplace("#define KERNEL_DEPTH " + support::cpp11::to_string(input->info()->dimension(2)));
122         build_opts.emplace("#define CONVOLVED_WIDTH " + support::cpp11::to_string(_convolved_dims.first));
123         build_opts.emplace("#define CONVOLVED_HEIGHT " + support::cpp11::to_string(_convolved_dims.second));
124         build_opts.emplace("#define STRIDE_X " + support::cpp11::to_string(conv_info.stride().first));
125         build_opts.emplace("#define STRIDE_Y " + support::cpp11::to_string(conv_info.stride().second));
126         build_opts.emplace("#define PAD_LEFT " + support::cpp11::to_string(conv_info.pad_left()));
127         build_opts.emplace("#define PAD_TOP " + support::cpp11::to_string(conv_info.pad_top()));
128         build_opts.emplace("#define PAD_RIGHT " + support::cpp11::to_string(conv_info.pad_right()));
129         build_opts.emplace("#define PAD_BOTTOM " + support::cpp11::to_string(conv_info.pad_bottom()));
130         build_opts.emplace("#define SRC_WIDTH " + support::cpp11::to_string(input->info()->dimension(0)));
131         build_opts.emplace("#define SRC_HEIGHT " + support::cpp11::to_string(input->info()->dimension(1)));
132         build_opts.emplace("#define DILATION_X " + support::cpp11::to_string(dilation.x()));
133         build_opts.emplace("#define DILATION_Y " + support::cpp11::to_string(dilation.y()));
134 
135         _run_func = &GCIm2ColKernel::run_generic;
136     }
137     else
138     {
139         build_opts.emplace("#define IM2COL_REDUCED");
140         kernel_name = "im2col_reduced";
141 
142         if(input->info()->data_type() == DataType::F32)
143         {
144             _num_elems_processed_per_iteration = 4 / input->info()->element_size();
145         }
146         else if(input->info()->data_type() == DataType::F16)
147         {
148             int input_width  = input->info()->dimension(0);
149             int input_height = input->info()->dimension(1);
150 
151             build_opts.emplace("#define IMAGE_SIZE " + support::cpp11::to_string(input_width * input_height));
152             if(input_width % 8 == 0)
153             {
154                 _num_elems_processed_per_iteration = 8;
155                 build_opts.emplace("#define IM2COL_REDUCED_8X");
156             }
157             else if(input_width % 4 == 0)
158             {
159                 _num_elems_processed_per_iteration = 4;
160                 build_opts.emplace("#define IM2COL_REDUCED_4X");
161             }
162             else if(input_width % 2 == 0)
163             {
164                 _num_elems_processed_per_iteration = 2;
165                 build_opts.emplace("#define IM2COL_REDUCED_2X");
166             }
167             else
168             {
169                 _num_elems_processed_per_iteration = 2;
170                 build_opts.emplace("#define IM2COL_REDUCED_GENERIC");
171             }
172         }
173 
174         _run_func = &GCIm2ColKernel::run_reduced;
175     }
176 
177     // Create kernel
178     _kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel(kernel_name, build_opts));
179 
180     // Configure kernel window
181     Window win = calculate_max_window(*input->info(), Steps(_num_elems_processed_per_iteration));
182 
183     if(input->info()->data_type() == DataType::F16)
184     {
185         // Calculate input right and bottom border
186         const int input_width         = input->info()->dimension(0);
187         const int input_height        = input->info()->dimension(1);
188         int       input_total_width   = input->info()->padding().left + input_width + input->info()->padding().right;
189         int       input_padding_right = ceil_to_multiple(input_total_width, _num_elems_processed_per_iteration) - input_total_width;
190         input_total_width             = input_width + input_padding_right + input->info()->padding().right;
191         AccessWindowStatic input_access(input->info(), 0, 0, input_total_width, input_height);
192 
193         // Calculate output right and bottom border
194         const int          output_width         = output->info()->dimension(0);
195         const int          output_height        = output->info()->dimension(1);
196         const int          output_padding_right = ceil_to_multiple(output_width, _num_elems_processed_per_iteration) - output_width;
197         AccessWindowStatic output_access(output->info(), 0, 0, output_width + output_padding_right, output_height);
198 
199         update_window_and_padding(win, input_access, output_access);
200     }
201 
202     output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape()));
203 
204     if(!run_img2col_reduced)
205     {
206         // set the Z dimension's step same size as the whole dimension so that one can't split across the Z dimension
207         win.set_dimension_step(Window::DimZ, win[Window::DimZ].end() - win[Window::DimZ].start());
208     }
209 
210     IGCKernel::configure(win);
211 }
212 
validate(const ITensorInfo * input,const ITensorInfo * output,const Size2D & kernel_dims,const PadStrideInfo & conv_info,bool has_bias,const Size2D & dilation)213 Status GCIm2ColKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation)
214 {
215     ARM_COMPUTE_UNUSED(kernel_dims);
216     ARM_COMPUTE_UNUSED(conv_info);
217     ARM_COMPUTE_UNUSED(has_bias);
218     ARM_COMPUTE_UNUSED(dilation);
219     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output));
220     return Status{};
221 }
222 
run(const Window & window)223 void GCIm2ColKernel::run(const Window &window)
224 {
225     ARM_COMPUTE_ERROR_ON(_run_func == nullptr);
226     (this->*_run_func)(window);
227 }
228 
run_generic(const Window & window)229 void GCIm2ColKernel::run_generic(const Window &window)
230 {
231     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
232     ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(IGCKernel::window(), window);
233 
234     // Get initial windows
235     Window window_collapsed = window.collapse_if_possible(IGCKernel::window(), Window::DimZ);
236 
237     // Change the Z dimension's step back to 1
238     window_collapsed.set_dimension_step(Window::DimZ, 1);
239 
240     Window slice     = window_collapsed.first_slice_window_3D();
241     Window slice_in  = window_collapsed.first_slice_window_3D();
242     Window slice_out = window_collapsed.first_slice_window_3D();
243 
244     // Setup slice
245     slice.set(Window::DimX, Window::Dimension(0, static_cast<int>(_convolved_dims.first), 1));
246     slice.set(Window::DimY, Window::Dimension(0, static_cast<int>(_convolved_dims.second), 1));
247 
248     // Setup output slice
249     slice_out.set(Window::DimX, Window::Dimension(0, _output->info()->dimension(0), _num_elems_processed_per_iteration));
250     slice_out.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1), 1));
251     slice_out.set(Window::DimZ, Window::Dimension(0, 1, 1));
252 
253     // we need top/left pad to be included in valid region
254     if(_input->info()->data_type() == DataType::F16)
255     {
256         (dynamic_cast<TensorInfo *>(_input->info()))->init(_input->info()->tensor_shape(), _input->info()->num_channels(), _input->info()->data_type(), _input->info()->strides_in_bytes(), 0,
257                                                            _input->info()->total_size());
258     }
259 
260     _kernel.use();
261 
262     do
263     {
264         unsigned int idx = 0;
265         add_3D_tensor_argument(idx, _input, 1, slice_in);
266         add_2D_tensor_argument(idx, _output, 2, slice_out);
267         _kernel.set_argument(idx++, static_cast<unsigned int>(_input->info()->strides_in_bytes()[3]));
268         _kernel.set_argument(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[3]));
269         _kernel.update_shader_params();
270 
271         enqueue(*this, slice);
272     }
273     while(window_collapsed.slide_window_slice_3D(slice) && window_collapsed.slide_window_slice_3D(slice_out) && window_collapsed.slide_window_slice_3D(slice_in));
274 }
275 
run_reduced(const Window & window)276 void GCIm2ColKernel::run_reduced(const Window &window)
277 {
278     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
279     ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(IGCKernel::window(), window);
280 
281     Window out_window;
282     out_window.use_tensor_dimensions(_output->info()->tensor_shape());
283 
284     Window out_slice = out_window.first_slice_window_1D();
285     Window in_slice  = window.first_slice_window_3D();
286 
287     _kernel.use();
288 
289     // Run kernel
290     do
291     {
292         // Set arguments
293         unsigned int idx = 0;
294 
295         add_3D_tensor_argument(idx, _input, 1, in_slice);
296         add_1D_tensor_argument(idx, _output, 2, out_slice);
297         _kernel.set_argument(idx++, _input->info()->dimension(0));
298         _kernel.set_argument(idx++, _input->info()->dimension(1));
299         _kernel.update_shader_params();
300 
301         enqueue(*this, in_slice);
302     }
303     while(window.slide_window_slice_3D(in_slice) && out_window.slide_window_slice_1D(out_slice));
304 }
305