1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
|
/*
* Copyright (c) 2017-2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "src/gpu/cl/kernels/ClGemmLowpOffsetContributionKernel.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/utils/helpers/AdjustVecSize.h"
#include "arm_compute/core/utils/StringUtils.h"
#include "arm_compute/core/Validate.h"
#include "src/core/helpers/WindowHelpers.h"
#include "support/Cast.h"
#include "support/StringSupport.h"
namespace arm_compute
{
namespace opencl
{
namespace kernels
{
namespace
{
Status validate_arguments(const ITensorInfo *mm_result,
const ITensorInfo *vector_sum_col,
const ITensorInfo *vector_sum_row,
const ITensorInfo *bias,
int32_t a_offset,
int32_t b_offset)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(mm_result, 1, DataType::S32);
if (bias != nullptr)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(bias, 1, DataType::S32);
ARM_COMPUTE_RETURN_ERROR_ON(bias->num_dimensions() > 1);
ARM_COMPUTE_RETURN_ERROR_ON(mm_result->dimension(0) != bias->dimension(0));
}
// If a_offset == 0, vector_sum_col can be a nullptr
if (a_offset != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_col, 1, DataType::S32);
ARM_COMPUTE_RETURN_ERROR_ON(vector_sum_col->dimension(0) != mm_result->dimension(0));
}
// If b_offset == 0, vector_sum_row can be a nullptr
if (b_offset != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_row, 1, DataType::S32);
// Check if input is a 3D reinterpretation
const bool reinterpret_as_3d =
mm_result->num_dimensions() > 1 && mm_result->tensor_shape().y() != vector_sum_row->tensor_shape().x();
// Validate input
ARM_COMPUTE_RETURN_ERROR_ON(reinterpret_as_3d && vector_sum_row->dimension(0) !=
(mm_result->dimension(1) * mm_result->dimension(2)));
ARM_COMPUTE_RETURN_ERROR_ON(!reinterpret_as_3d && vector_sum_row->dimension(0) != mm_result->dimension(1));
TensorShape output_shape = mm_result->tensor_shape();
if (output_shape.num_dimensions() > 1)
{
const unsigned int output_batch_idx = reinterpret_as_3d ? 3 : 2;
TensorShape vector_sum_row_shape = vector_sum_row->tensor_shape();
vector_sum_row_shape.collapse_from(1);
output_shape.collapse_from(output_batch_idx);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(vector_sum_row_shape[1] != output_shape[output_batch_idx],
"mm_result tensor must have the same number of batches of output tensor");
if (a_offset != 0)
{
TensorShape vector_sum_col_shape = vector_sum_col->tensor_shape();
vector_sum_col_shape.collapse_from(1);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(vector_sum_col_shape[1] != 1 &&
vector_sum_col_shape[1] != vector_sum_row_shape[1],
"vector_sum_col tensor must have the same number of batches of "
"vector_sum_row_shape or the number of batches must be set to 1");
}
}
}
return Status{};
}
} // namespace
ClGemmLowpOffsetContributionKernel::ClGemmLowpOffsetContributionKernel()
{
_type = CLKernelType::ELEMENTWISE;
}
void ClGemmLowpOffsetContributionKernel::configure(const CLCompileContext &compile_context,
const ITensorInfo *mm_result,
const ITensorInfo *vector_sum_col,
const ITensorInfo *vector_sum_row,
const ITensorInfo *bias,
int32_t k,
int32_t a_offset,
int32_t b_offset)
{
// Perform validate step
ARM_COMPUTE_ERROR_ON_NULLPTR(mm_result);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(mm_result, vector_sum_col, vector_sum_row, bias, a_offset, b_offset));
auto padding_info = get_padding_info({mm_result, vector_sum_col, vector_sum_row, bias});
// Check if input is a 3D reinterpretation
const bool reinterpret_as_3d = vector_sum_row != nullptr && mm_result->num_dimensions() > 1 &&
mm_result->tensor_shape().y() != vector_sum_row->tensor_shape().x();
const unsigned int num_elems_processed_per_iteration = adjust_vec_size(4, mm_result->dimension(0));
// Set the arguments to pass at compile time
CLBuildOptions build_opts;
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
build_opts.add_option("-DVEC_SIZE_LEFTOVER=" +
support::cpp11::to_string(mm_result->dimension(0) % num_elems_processed_per_iteration));
// If a_offset == 0, vector_sum_col can be a nullptr
if (a_offset != 0)
{
build_opts.add_option("-DA_OFFSET=" + support::cpp11::to_string(a_offset));
build_opts.add_option_if(vector_sum_col->tensor_shape().num_dimensions() > 1, "-DSUM_COL_HAS_BATCHES");
}
// If b_offset == 0, vector_sum_row can be a nullptr
build_opts.add_option_if(b_offset != 0, "-DB_OFFSET=" + support::cpp11::to_string(b_offset));
build_opts.add_option("-DK_OFFSET=" + support::cpp11::to_string(a_offset * b_offset * k));
build_opts.add_option_if(reinterpret_as_3d,
"-DHEIGHT_INPUT3D=" + support::cpp11::to_string(mm_result->dimension(1)));
build_opts.add_option_if(reinterpret_as_3d,
"-DDEPTH_INPUT3D=" + support::cpp11::to_string(mm_result->dimension(2)));
build_opts.add_option_if(bias != nullptr, "-DADD_BIAS");
std::string kernel_name("gemmlowp_offset_contribution");
// A macro guard to compile ONLY the kernel of interest
build_opts.add_option("-D" + upper_string(kernel_name));
// Create kernel
_kernel = create_kernel(compile_context, kernel_name, build_opts.options());
// Configure kernel window
Window win = calculate_max_window(*mm_result, Steps(num_elems_processed_per_iteration));
IClKernel::configure_internal(win);
// Set config_id for enabling LWS tuning
_config_id = kernel_name + "_";
_config_id += support::cpp11::to_string(mm_result->dimension(0));
_config_id += "_";
_config_id += support::cpp11::to_string(mm_result->dimension(1));
_config_id += "_";
_config_id += support::cpp11::to_string(mm_result->dimension(2));
ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
}
Status ClGemmLowpOffsetContributionKernel::validate(const ITensorInfo *mm_result,
const ITensorInfo *vector_sum_col,
const ITensorInfo *vector_sum_row,
const ITensorInfo *bias,
int32_t a_offset,
int32_t b_offset)
{
ARM_COMPUTE_RETURN_ON_ERROR(
validate_arguments(mm_result, vector_sum_col, vector_sum_row, bias, a_offset, b_offset));
return Status{};
}
void ClGemmLowpOffsetContributionKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IClKernel::window(), window);
const auto vector_sum_col =
utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_VEC_COL_SUM));
const auto vector_sum_row =
utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_VEC_ROW_SUM));
const auto bias =
utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_BIAS));
const auto mm_result = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_SRC_DST));
Window collapsed = window.collapse_if_possible(IClKernel::window(), Window::DimZ);
Window slice = collapsed.first_slice_window_3D();
// Set window for vector_sum_col
Window win_vector_sum_col = slice;
win_vector_sum_col.set(Window::DimY, Window::Dimension(0, 0, 0));
win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0));
// Set window for vector_sum_row
Window win_vector_sum_row = slice;
win_vector_sum_row.set(Window::DimX, Window::Dimension(0, 0, 0));
win_vector_sum_row.set(Window::DimY, Window::Dimension(0, 0, 0));
win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0));
Window biases_slice = slice;
biases_slice.set(Window::DimY, Window::Dimension(0, 1, 1));
biases_slice.set(Window::DimZ, Window::Dimension(0, 1, 1));
do
{
unsigned int idx = 0;
add_3D_tensor_argument(idx, mm_result, slice);
add_2D_tensor_argument_if((vector_sum_col != nullptr), idx, vector_sum_col, win_vector_sum_col);
add_2D_tensor_argument_if((vector_sum_row != nullptr), idx, vector_sum_row, win_vector_sum_row);
add_1D_tensor_argument_if((bias != nullptr), idx, bias, biases_slice);
enqueue(queue, *this, slice, lws_hint());
} while (collapsed.slide_window_slice_3D(slice));
}
} // namespace kernels
} // namespace opencl
} // namespace arm_compute
|
