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Gian Marco Iodice5ba5e092018-12-06 17:13:09 +00001/*
Gian Marco Iodicebacfec52019-01-11 11:30:55 +00002 * Copyright (c) 2018-2019 ARM Limited.
Gian Marco Iodice5ba5e092018-12-06 17:13:09 +00003 *
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 "arm_compute/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.h"
25
26#include "arm_compute/core/AccessWindowStatic.h"
27#include "arm_compute/core/CL/CLHelpers.h"
28#include "arm_compute/core/CL/CLKernelLibrary.h"
29#include "arm_compute/core/CL/CLValidate.h"
30#include "arm_compute/core/CL/ICLTensor.h"
31#include "arm_compute/core/CL/OpenCL.h"
32#include "arm_compute/core/Error.h"
33#include "arm_compute/core/Helpers.h"
34#include "arm_compute/core/TensorInfo.h"
35#include "arm_compute/core/Types.h"
36#include "arm_compute/core/Utils.h"
37#include "arm_compute/core/Window.h"
38#include "arm_compute/core/utils/misc/ShapeCalculator.h"
39
Michele Di Giorgiodf4cf572019-10-09 15:32:39 +010040namespace arm_compute
41{
Gian Marco Iodice5ba5e092018-12-06 17:13:09 +000042using namespace arm_compute::misc::shape_calculator;
43
44namespace
45{
46Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const GEMMLHSMatrixInfo &lhs_info, bool reinterpret_input_as_3d)
47{
Gian Marco Iodice5ba5e092018-12-06 17:13:09 +000048 ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.m0 == 0);
49 ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.k0 == 0);
50 ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.v0 == 0);
Gian Marco Iodicebacfec52019-01-11 11:30:55 +000051 ARM_COMPUTE_RETURN_ERROR_ON_MSG(((lhs_info.k0 & (lhs_info.k0 - 1)) && lhs_info.k0 != 3), "Only 2,3,4,8,16 are supported for k0");
Gian Marco Iodice5ba5e092018-12-06 17:13:09 +000052 ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.k0 > 16);
53 ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.m0 < 2 || lhs_info.m0 > 8);
54
55 ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
56 ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::U8, DataType::S8,
57 DataType::U16, DataType::S16, DataType::U32, DataType::S32,
58 DataType::F16, DataType::F32);
59
60 if(output->total_size() != 0)
61 {
62 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), compute_lhs_reshaped_shape(*input, lhs_info, reinterpret_input_as_3d));
63 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
Isabella Gottardi0a1090a2019-02-14 18:07:36 +000064 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
Gian Marco Iodice5ba5e092018-12-06 17:13:09 +000065 }
66
67 return Status{};
68}
69
70std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const GEMMLHSMatrixInfo &lhs_info, bool reinterpret_input_as_3d)
71{
72 const unsigned int num_elems_processed_per_iteration_x = lhs_info.k0;
73 const unsigned int num_elems_processed_per_iteration_y = lhs_info.m0;
74 bool window_changed = false;
75
76 TensorInfo tmp_info(*input);
77
78 if(reinterpret_input_as_3d)
79 {
80 // Since the input tensor has to be reinterpreted as 3D and the execute window is based on a 2D interleave,
81 // the window needs to be constructed on the 2D collapsed version of the tensor
82 TensorShape tmp_shape(input->tensor_shape());
83 tmp_shape.collapse(2U, 1U);
84 tmp_info.set_tensor_shape(tmp_shape);
85 }
86
87 // Output auto inizialitation if not yet initialized
88 auto_init_if_empty(*output, input->clone()->set_tensor_shape(compute_lhs_reshaped_shape(*input, lhs_info, reinterpret_input_as_3d)));
89
90 // Configure window
91 // Note: bottom paddings are calculated manually as the input can be reinterpreted as 3D tensor
92 // The only way to set properly the paddings, it is to set those explicitly through the AccessWindowStatic
93 const int m = reinterpret_input_as_3d ? input->tensor_shape()[1] * input->tensor_shape()[2] : input->tensor_shape()[1];
94 const int bottom_pad = ceil_to_multiple(m, num_elems_processed_per_iteration_y) - m;
95
96 Window win = calculate_max_window(tmp_info, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
97 Window win_in = calculate_max_window(*input, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
98
99 AccessWindowStatic input_access(input, 0, 0,
100 ceil_to_multiple(input->dimension(0), num_elems_processed_per_iteration_x),
101 input->dimension(1) + bottom_pad);
102 AccessWindowStatic output_access(output, 0, 0, output->dimension(0), output->dimension(1));
103
104 window_changed = update_window_and_padding(win_in, input_access) || // window used by the execute_window_loop
105 update_window_and_padding(win, output_access); // window used to update the padding requirements of output tensor
106 output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->tensor_shape()));
107
108 // Collapse along the Z direction
109 // This collapse needs to be here in order to tune the Z dimension of LWS
110 Window collapsed = win.collapse(win, Window::DimZ);
111
112 Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
113 return std::make_pair(err, collapsed);
114}
115} // namespace
116
117CLGEMMReshapeLHSMatrixKernel::CLGEMMReshapeLHSMatrixKernel()
118 : _input(nullptr), _output(nullptr), _reinterpret_input_as_3d(false)
119{
120}
121
122void CLGEMMReshapeLHSMatrixKernel::configure(const ICLTensor *input, ICLTensor *output, const GEMMLHSMatrixInfo &lhs_info, bool reinterpret_input_as_3d)
123{
124 ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
125
126 // Perform validate step
127 ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), lhs_info, reinterpret_input_as_3d));
128
129 _input = input;
130 _output = output;
131 _reinterpret_input_as_3d = reinterpret_input_as_3d;
132
133 // Create build options
134 CLBuildOptions build_opts;
135 build_opts.add_option("-DM0=" + support::cpp11::to_string(lhs_info.m0));
136 build_opts.add_option("-DK0=" + support::cpp11::to_string(lhs_info.k0));
137 build_opts.add_option("-DV0=" + support::cpp11::to_string(lhs_info.v0));
Gian Marco Iodiceb87b95e2019-01-21 17:14:31 +0000138 build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(input->info()->dimension(0)));
Gian Marco Iodice5ba5e092018-12-06 17:13:09 +0000139 build_opts.add_option_if(lhs_info.interleave, "-DINTERLEAVE");
140 build_opts.add_option_if(_reinterpret_input_as_3d, "-DREINTERPRET_INPUT_AS_3D");
141 build_opts.add_option_if(_reinterpret_input_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(input->info()->dimension(1)));
142 build_opts.add_option_if(_reinterpret_input_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(input->info()->dimension(2)));
Michele Di Giorgiodf4cf572019-10-09 15:32:39 +0100143 build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size()));
Gian Marco Iodice5ba5e092018-12-06 17:13:09 +0000144
145 std::string kernel_name("gemm_reshape_lhs_matrix_");
146 kernel_name += lhs_info.transpose ? "t" : "nt";
147
148 // Create kernel
149 _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
150
151 // Configure kernel window
152 auto win_config = validate_and_configure_window(input->info(), output->info(), lhs_info, reinterpret_input_as_3d);
153 ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
154 ICLKernel::configure_internal(win_config.second);
155
156 // Set config_id for enabling LWS tuning
157 _config_id = "gemm_reshape_lhs_matrix_";
158 _config_id += (_reinterpret_input_as_3d ? "3d_" : "");
159 _config_id += lower_string(string_from_data_type(input->info()->data_type()));
160 _config_id += "_";
161 _config_id += support::cpp11::to_string(output->info()->dimension(0));
162 _config_id += "_";
163 _config_id += support::cpp11::to_string(output->info()->dimension(1));
164 _config_id += "_";
165 _config_id += support::cpp11::to_string(output->info()->dimension(2));
166 _config_id += "_";
167 _config_id += support::cpp11::to_string(lhs_info.m0);
168 _config_id += "_";
169 _config_id += support::cpp11::to_string(lhs_info.k0);
170 _config_id += "_";
171 _config_id += support::cpp11::to_string(lhs_info.v0);
172 _config_id += "_";
173 _config_id += support::cpp11::to_string(lhs_info.interleave);
174 _config_id += "_";
175 _config_id += support::cpp11::to_string(lhs_info.transpose);
176}
177
178Status CLGEMMReshapeLHSMatrixKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const GEMMLHSMatrixInfo &lhs_info, bool reinterpret_input_as_3d)
179{
180 ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, lhs_info, reinterpret_input_as_3d));
181 ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), lhs_info, reinterpret_input_as_3d).first);
182
183 return Status{};
184}
185
186void CLGEMMReshapeLHSMatrixKernel::run(const Window &window, cl::CommandQueue &queue)
187{
188 ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
189 ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
190
191 Window slice = window.first_slice_window_3D();
192
193 if(_reinterpret_input_as_3d)
194 {
195 // Pass bottom paddings to the kernel if the input has to be reinterpreted as 3D tensor
196 const unsigned int idx0 = 2 * num_arguments_per_3D_tensor();
197 const unsigned int total_cross_plane_pad = _input->info()->padding().top + _input->info()->padding().bottom;
198 _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad));
199 }
200
201 do
202 {
203 unsigned int idx = 0;
204 add_3D_tensor_argument(idx, _input, slice);
205 add_3D_tensor_argument(idx, _output, slice);
206 enqueue(queue, *this, slice, lws_hint());
207 }
208 while(window.slide_window_slice_3D(slice));
Michele Di Giorgiodf4cf572019-10-09 15:32:39 +0100209}
210} // namespace arm_compute