1 /*
2 * Copyright (c) 2018-2022 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 #include "src/gpu/cl/kernels/ClWinogradInputTransformKernel.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/Error.h"
31 #include "arm_compute/core/Helpers.h"
32 #include "arm_compute/core/Types.h"
33 #include "arm_compute/core/Utils.h"
34 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
35 #include "src/core/AccessWindowStatic.h"
36 #include "src/core/CL/CLValidate.h"
37 #include "src/core/helpers/AutoConfiguration.h"
38 #include "src/core/helpers/WindowHelpers.h"
39 #include "support/Cast.h"
40 #include "support/StringSupport.h"
41
42 namespace arm_compute
43 {
44 namespace opencl
45 {
46 namespace kernels
47 {
48 namespace
49 {
validate_arguments(const ITensorInfo * input,const ITensorInfo * output,const WinogradInfo & winograd_info)50 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info)
51 {
52 ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16);
53 ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
54
55 const PadStrideInfo conv_info = winograd_info.convolution_info;
56 const Size2D output_tile_size = winograd_info.output_tile_size;
57 const Size2D kernel_size = winograd_info.kernel_size;
58 ARM_COMPUTE_RETURN_ERROR_ON_MSG(conv_info.stride().first != 1 || conv_info.stride().second != 1, "Winograd input transform only supports unit strides");
59 ARM_COMPUTE_RETURN_ERROR_ON_MSG(!cl_winograd_convolution_layer_supported(output_tile_size, kernel_size, input->data_layout()), "Winograd input transform not supported");
60
61 ARM_COMPUTE_UNUSED(conv_info);
62 ARM_COMPUTE_UNUSED(output_tile_size);
63 ARM_COMPUTE_UNUSED(kernel_size);
64
65 // Validate configured output
66 if(output->total_size() != 0)
67 {
68 const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*input, winograd_info);
69
70 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape);
71 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
72 }
73
74 return Status{};
75 }
76
validate_and_configure_window(ITensorInfo * input,ITensorInfo * output,const WinogradInfo & winograd_info)77 std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const WinogradInfo &winograd_info)
78 {
79 ARM_COMPUTE_UNUSED(output);
80 ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
81
82 bool window_changed = false;
83 Window win = calculate_max_window(*input, Steps(1, 1));
84
85 if(input->data_layout() == DataLayout::NCHW)
86 {
87 const PadStrideInfo conv_info = winograd_info.convolution_info;
88 const Size2D output_tile_size = winograd_info.output_tile_size;
89 const Size2D kernel_size = winograd_info.kernel_size;
90
91 unsigned int num_elems_read_per_iteration_x = output_tile_size.width + kernel_size.width - 1;
92 unsigned int num_elems_read_per_iteration_y = output_tile_size.height + kernel_size.height - 1;
93
94 AccessWindowRectangle input_access(input, -conv_info.pad_left(), -conv_info.pad_top(), num_elems_read_per_iteration_x, num_elems_read_per_iteration_y);
95 window_changed = update_window_and_padding(win, input_access);
96 }
97
98 Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
99 return std::make_pair(err, win);
100 }
101 } // namespace
102
ClWinogradInputTransformKernel()103 ClWinogradInputTransformKernel::ClWinogradInputTransformKernel()
104 {
105 _type = CLKernelType::WINOGRAD;
106 }
107
border_size() const108 BorderSize ClWinogradInputTransformKernel::border_size() const
109 {
110 return _border_size;
111 }
112
configure(const ClCompileContext & compile_context,ITensorInfo * src,ITensorInfo * dst,const WinogradInfo & winograd_info)113 void ClWinogradInputTransformKernel::configure(const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *dst, const WinogradInfo &winograd_info)
114 {
115 ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
116 ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst, winograd_info));
117
118 auto padding_info = get_padding_info({ src, dst });
119
120 const PadStrideInfo conv_info = winograd_info.convolution_info;
121 const Size2D output_tile_size = winograd_info.output_tile_size;
122 const Size2D kernel_size = winograd_info.kernel_size;
123
124 _data_layout = src->data_layout();
125
126 const size_t idx_w = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
127 const size_t idx_h = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
128
129 // Compute the number of output tiles along the x and y direction of size "output_tile_size"
130 const Size2D num_tiles = compute_winograd_convolution_tiles(Size2D(src->dimension(idx_w), src->dimension(idx_h)),
131 kernel_size,
132 output_tile_size,
133 conv_info);
134
135 _num_tiles_x = num_tiles.width;
136 _num_tiles_y = num_tiles.height;
137
138 const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*src, winograd_info);
139
140 // Output auto initialization if not yet initialized
141 auto_init_if_empty(*dst, src->clone()->set_tensor_shape(output_shape));
142
143 ARM_COMPUTE_ERROR_ON(_num_tiles_x * _num_tiles_y != static_cast<int>(dst->dimension(1)));
144 const size_t total_batches = src->tensor_shape().total_size_upper(3);
145
146 CLBuildOptions build_opts;
147 if(_data_layout == DataLayout::NHWC)
148 {
149 build_opts.add_option("-DNHWC");
150 _src_width = src->dimension(idx_w);
151 _src_height = src->dimension(idx_h);
152 build_opts.add_option("-DPAD_LEFT=" + support::cpp11::to_string(conv_info.pad_left()));
153 build_opts.add_option("-DPAD_TOP=" + support::cpp11::to_string(conv_info.pad_top()));
154 build_opts.add_option("-DOUTPUT_TILE_W=" + support::cpp11::to_string(output_tile_size.width));
155 build_opts.add_option("-DOUTPUT_TILE_H=" + support::cpp11::to_string(output_tile_size.height));
156 build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(src->data_type()));
157 build_opts.add_option_if(winograd_info.kernel_size.height == 1, "-DWINOGRAD_INPUT_TRANSFORM_HORIZONTAL");
158 build_opts.add_option_if(winograd_info.kernel_size.width == 1, "-DWINOGRAD_INPUT_TRANSFORM_VERTICAL");
159 }
160 else
161 {
162 build_opts.add_option("-DNUM_TILES_X=" + support::cpp11::to_string(_num_tiles_x));
163 build_opts.add_option("-DPAD_LEFT=" + support::cpp11::to_string(conv_info.pad_left()));
164 build_opts.add_option("-DPAD_TOP=" + support::cpp11::to_string(conv_info.pad_top()));
165 build_opts.add_option("-DOUTPUT_TILE_W=" + support::cpp11::to_string(output_tile_size.width));
166 build_opts.add_option("-DOUTPUT_TILE_H=" + support::cpp11::to_string(output_tile_size.height));
167 build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(src->data_type()));
168 build_opts.add_option_if(winograd_info.kernel_size.height == 1, "-DWINOGRAD_INPUT_TRANSFORM_HORIZONTAL");
169 build_opts.add_option_if(winograd_info.kernel_size.width == 1, "-DWINOGRAD_INPUT_TRANSFORM_VERTICAL");
170 build_opts.add_option_if(total_batches > 1, "-DSRC_DEPTH=" + support::cpp11::to_string(src->dimension(2)));
171 }
172
173 // Create kernel
174 std::string kernel_name = "winograd_input_transform_" + output_tile_size.to_string() + "_" + kernel_size.to_string();
175
176 // Get the maximum dimension from the tile size
177 const unsigned int tile_max_dim = std::max(output_tile_size.width, output_tile_size.height);
178
179 // Check optimized kernel if output_dims == 2x2
180 if((tile_max_dim == 2) && (_data_layout == DataLayout::NCHW))
181 {
182 _step_z = (src->dimension(2) % 2) != 0 ? 1 : 2;
183 }
184
185 // Append stepz and data layout
186 kernel_name += "_stepz";
187 kernel_name += support::cpp11::to_string(_step_z);
188 kernel_name += "_" + lower_string(string_from_data_layout(_data_layout));
189
190 // A macro guard to compile ONLY the kernel of interest
191 build_opts.add_option("-D" + upper_string(kernel_name));
192 _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
193
194 // Create window and update padding
195 auto win_config = validate_and_configure_window(src, dst, winograd_info);
196 ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
197 IClKernel::configure_internal(win_config.second, cl::NDRange(1, 1, 8));
198
199 _border_size = BorderSize(src->padding());
200
201 ARM_COMPUTE_ERROR_ON((src->data_layout() == DataLayout::NHWC) && has_padding_changed(padding_info));
202
203 _config_id = kernel_name;
204 _config_id += support::cpp11::to_string(src->dimension(0));
205 _config_id += "_";
206 _config_id += support::cpp11::to_string(src->dimension(1));
207 _config_id += "_";
208 _config_id += support::cpp11::to_string(src->dimension(2));
209 _config_id += "_";
210 _config_id += support::cpp11::to_string(conv_info.pad_left());
211 _config_id += "_";
212 _config_id += support::cpp11::to_string(conv_info.pad_top());
213 _config_id += "_";
214 _config_id += lower_string(string_from_data_layout(_data_layout));
215 }
216
validate(const ITensorInfo * src,const ITensorInfo * dst,const WinogradInfo & winograd_info)217 Status ClWinogradInputTransformKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, const WinogradInfo &winograd_info)
218 {
219 ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst);
220 ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, dst, winograd_info));
221 ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(src->clone().get(), dst->clone().get(), winograd_info).first);
222 return Status{};
223 }
224
run_op(ITensorPack & tensors,const Window & window,cl::CommandQueue & queue)225 void ClWinogradInputTransformKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue)
226 {
227 ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
228 ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
229
230 auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC));
231 auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
232
233 const size_t idx_w = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
234 const size_t idx_h = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
235 const size_t idx_c = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL);
236 const size_t total_batches = window.shape().total_size_upper(3);
237
238 // Collapse window
239 Window window_collapsed = window.collapse_if_possible(IClKernel::window(), Window::DimZ);
240
241 if(_data_layout == DataLayout::NHWC)
242 {
243 Window slice = window_collapsed.first_slice_window_3D();
244 slice.set(1, Window::Dimension(0, _num_tiles_x * _num_tiles_y, 1));
245 slice.set(2, Window::Dimension(0, total_batches, 1));
246
247 unsigned int idx = 0;
248 add_4D_tensor_argument(idx, src, slice);
249 add_4D_tensor_argument(idx, dst, slice);
250 _kernel.setArg<cl_uint>(idx++, _src_width);
251 _kernel.setArg<cl_uint>(idx++, _src_height);
252 _kernel.setArg<cl_uint>(idx++, _num_tiles_x);
253 _kernel.setArg<cl_uint>(idx++, _num_tiles_y);
254 enqueue(queue, *this, slice, lws_hint());
255 }
256 else
257 {
258 Window slice = window_collapsed.first_slice_window_3D();
259 slice.set(idx_w, Window::Dimension(0, _num_tiles_x, 1));
260 slice.set(idx_h, Window::Dimension(0, _num_tiles_y, 1));
261
262 ARM_COMPUTE_ERROR_ON(((slice[idx_c].end() - slice[idx_c].start()) % _step_z) != 0);
263 slice.set(idx_c, Window::Dimension(slice[idx_c].start(), slice[idx_c].end(), _step_z));
264
265 unsigned int idx = 2 * num_arguments_per_3D_tensor();
266 _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(src->info()->strides_in_bytes()[3]));
267 _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(dst->info()->strides_in_bytes()[3]));
268
269 do
270 {
271 unsigned int idx = 0;
272 add_3D_tensor_argument(idx, src, slice);
273 add_3D_tensor_argument(idx, dst, slice);
274
275 enqueue(queue, *this, slice, lws_hint());
276 }
277 while(window_collapsed.slide_window_slice_3D(slice));
278 }
279 }
280 } // namespace kernels
281 } // namespace opencl
282 } // namespace arm_compute
283