1 /*
2 * Copyright (c) 2018-2021 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 "arm_compute/core/Helpers.h"
25 #include "arm_compute/core/Types.h"
26 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
27 #include "arm_compute/runtime/CL/CLTensor.h"
28 #include "arm_compute/runtime/CL/CLTensorAllocator.h"
29 #include "arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h"
30 #include "tests/CL/CLAccessor.h"
31 #include "tests/CL/Helper.h"
32 #include "tests/PaddingCalculator.h"
33 #include "tests/datasets/LargeConvolutionLayerDataset.h"
34 #include "tests/datasets/ShapeDatasets.h"
35 #include "tests/datasets/SmallConvolutionLayerDataset.h"
36 #include "tests/datasets/WinogradInputTransformDataset.h"
37 #include "tests/datasets/WinogradOutputTransformDataset.h"
38 #include "tests/framework/Asserts.h"
39 #include "tests/framework/Macros.h"
40 #include "tests/framework/datasets/Datasets.h"
41 #include "tests/validation/Validation.h"
42 #include "tests/validation/fixtures/WinogradConvolutionLayerFixture.h"
43
44 namespace arm_compute
45 {
46 namespace test
47 {
48 namespace validation
49 {
50 namespace
51 {
52 // *INDENT-OFF*
53 // clang-format off
54 const AbsoluteTolerance<half> tolerance_f16(half(1.f));
55 constexpr AbsoluteTolerance<float> tolerance_convolution_layer_f32(0.1f);
56 const AbsoluteTolerance<half> tolerance_convolution_layer_f16(half(0.4f));
57 RelativeTolerance<half_float::half> rel_tolerance_f16(half(0.2)); /**< Tolerance value for comparing reference's output against implementation's output for FP16 data types */
58 constexpr float tolerance_num = 0.05f; /**< Tolerance number */
59 constexpr float abs_tolerance_convolution_layer_f16 = 2.5f; /**< Tolerance number */
60 constexpr float tolerance_num_f16 = 0.15f; /**< Tolerance number */
61
62 //Activation Functions
63 const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo",
64 {
65 ActivationLayerInfo(),
66 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
67 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU),
68 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU),
69 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LEAKY_RELU)
70 });
71 const auto ActivationFunctionsSmallDataset = framework::dataset::make("ActivationInfo",
72 {
73 ActivationLayerInfo(),
74 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU),
75 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LEAKY_RELU),
76 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::SOFT_RELU)
77 });
78
79 } // namespace
80
81 using namespace arm_compute::misc::shape_calculator;
82
83 TEST_SUITE(CL)
TEST_SUITE(Winograd)84 TEST_SUITE(Winograd)
85
86 TEST_SUITE(ConvolutionLayer)
87 DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
88 framework::dataset::make("InputInfo", {
89 TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F16), // Insufficient padding
90 TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32), // Datatype mismatch
91 TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32), // Stride y not supported
92 TensorInfo(TensorShape(16U, 16U, 8U), 1, DataType::F32), // Padding needed
93 TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32) // Kernel size not supported
94 }),
95 framework::dataset::make("WeightsInfo", {
96 TensorInfo(TensorShape(3U, 3U, 2U, 19U), 1, DataType::F16),
97 TensorInfo(TensorShape(3U, 3U, 2U, 19U), 1, DataType::QASYMM8),
98 TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32),
99 TensorInfo(TensorShape(3U, 3U, 8U, 16U), 1, DataType::F32),
100 TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16)
101 })),
102 framework::dataset::make("BiasesInfo", {
103 TensorInfo(TensorShape(19U), 1, DataType::F16),
104 TensorInfo(TensorShape(19U), 1, DataType::F32),
105 TensorInfo(TensorShape(21U), 1, DataType::F32),
106 TensorInfo(TensorShape(16U), 1, DataType::F32),
107 TensorInfo(TensorShape(16U), 1, DataType::F32)
108 })),
109 framework::dataset::make("OutputInfo", {
110 TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F16),
111 TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32),
112 TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32),
113 TensorInfo(TensorShape(16U, 16U, 16U), 1, DataType::F32),
114 TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32)
115 })),
116 framework::dataset::make("ConvInfo", {
117 PadStrideInfo(1, 1, 1, 1),
118 PadStrideInfo(1, 1, 1, 1),
119 PadStrideInfo(1, 2, 0, 0),
120 PadStrideInfo(1, 1, 1, 1),
121 PadStrideInfo(1, 1, 1, 0)
122 })),
123 framework::dataset::make("Expected", { false, false, false, false, false })),
124 input_info, weights_info, bias_info, output_info, conv_info, expected)
125 {
126 ARM_COMPUTE_EXPECT(bool(CLWinogradConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &bias_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info)) == expected, framework::LogLevel::ERRORS);
127 }
128
129 TEST_SUITE(FP32)
130 using CLWinogradConvolutionLayerFastMathFixture = WinogradConvolutionLayerFastMathValidationFixture<CLTensor, CLAccessor, CLWinogradConvolutionLayer, float>;
131 using CLWinogradConvolutionLayerFastMathMixedDataLayoutFixture = WinogradConvolutionLayerFastMathValidationFixture<CLTensor, CLAccessor, CLWinogradConvolutionLayer, float, float, true, true>;
132 TEST_SUITE(Conv3x3)
133 FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::PRECOMMIT,
134 combine(combine(combine(datasets::SmallWinogradConvolutionLayer3x3Dataset(),
135 framework::dataset::make("DataType", { DataType::F32 })),
136 ActivationFunctionsSmallDataset),
137 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
138 {
139 // Validate output
140 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
141 }
142 FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, CLWinogradConvolutionLayerFastMathMixedDataLayoutFixture, framework::DatasetMode::PRECOMMIT,
143 combine(combine(combine(combine(combine(combine(combine(combine(
144 framework::dataset::make("Input", TensorShape(8U, 8U, 32U)),
145 framework::dataset::make("Weight", TensorShape(1U, 3U, 32U, 1U))),
146 framework::dataset::make("Bias", TensorShape(1U))),
147 framework::dataset::make("Output", TensorShape(8U, 6U, 1U))),
148 framework::dataset::make("PadStrideInfo", PadStrideInfo(1, 1, 0, 0))),
149 framework::dataset::make("Dilation", Size2D(1U, 1U))),
150 framework::dataset::make("DataType", { DataType::F32 })),
151 ActivationFunctionsSmallDataset),
152 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
153 {
154 // Validate output
155 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
156 }
157 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::NIGHTLY,
158 combine(combine(combine(datasets::LargeWinogradConvolutionLayer3x3Dataset(),
159 framework::dataset::make("DataType", { DataType::F32 })),
160 ActivationFunctionsDataset),
161 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
162 {
163 // Validate output
164 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
165 }
166 TEST_SUITE_END() // Conv3x3
167
TEST_SUITE(Conv3x1)168 TEST_SUITE(Conv3x1)
169 FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::PRECOMMIT,
170 combine(combine(combine(datasets::SmallWinogradConvolutionLayer3x1Dataset(),
171 framework::dataset::make("DataType", { DataType::F32 })),
172 ActivationFunctionsSmallDataset),
173 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
174 {
175 // Validate output
176 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
177 }
178
179 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::NIGHTLY,
180 combine(combine(combine(datasets::LargeWinogradConvolutionLayer3x1Dataset(),
181 framework::dataset::make("DataType", { DataType::F32 })),
182 ActivationFunctionsDataset),
183 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
184 {
185 // Validate output
186 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
187 }
188 TEST_SUITE_END() // Conv3x1
189
TEST_SUITE(Conv1x3)190 TEST_SUITE(Conv1x3)
191 FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::PRECOMMIT,
192 combine(combine(combine(datasets::SmallWinogradConvolutionLayer1x3Dataset(),
193 framework::dataset::make("DataType", { DataType::F32 })),
194 ActivationFunctionsSmallDataset),
195 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
196 {
197 // Validate output
198 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
199 }
200
201 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::NIGHTLY,
202 combine(combine(combine(datasets::LargeWinogradConvolutionLayer1x3Dataset(),
203 framework::dataset::make("DataType", { DataType::F32 })),
204 ActivationFunctionsDataset),
205 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
206 {
207 // Validate output
208 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
209 }
210 TEST_SUITE_END() // Conv1x3
211
TEST_SUITE(Conv5x5)212 TEST_SUITE(Conv5x5)
213 FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::PRECOMMIT,
214 combine(combine(combine(datasets::SmallWinogradConvolutionLayer5x5Dataset(),
215 framework::dataset::make("DataType", { DataType::F32 })),
216 ActivationFunctionsSmallDataset ),
217 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
218
219 {
220 // Validate output
221 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
222 }
223
224 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::NIGHTLY,
225 combine(combine(combine(datasets::LargeWinogradConvolutionLayer5x5Dataset(),
226 framework::dataset::make("DataType", { DataType::F32 })),
227 ActivationFunctionsDataset ),
228 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
229
230 {
231 // Validate output
232 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
233 }
234 TEST_SUITE_END() // Conv5x5
235
TEST_SUITE(Conv5x1)236 TEST_SUITE(Conv5x1)
237 FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::PRECOMMIT,
238 combine(combine(combine(datasets::SmallWinogradConvolutionLayer5x1Dataset(),
239 framework::dataset::make("DataType", { DataType::F32 })),
240 ActivationFunctionsSmallDataset),
241 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
242
243 {
244 // Validate output
245 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
246 }
247
248 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::NIGHTLY,
249 combine(combine(combine(datasets::LargeWinogradConvolutionLayer5x1Dataset(),
250 framework::dataset::make("DataType", { DataType::F32 })),
251 ActivationFunctionsDataset),
252 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
253
254 {
255 // Validate output
256 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
257 }
258 TEST_SUITE_END() // Conv5x1
259
TEST_SUITE(Conv1x5)260 TEST_SUITE(Conv1x5)
261 FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::PRECOMMIT,
262 combine(combine(combine(datasets::SmallWinogradConvolutionLayer1x5Dataset(),
263 framework::dataset::make("DataType", { DataType::F32 })),
264 ActivationFunctionsSmallDataset),
265 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
266
267 {
268 // Validate output
269 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
270 }
271
272 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::NIGHTLY,
273 combine(combine(combine(datasets::LargeWinogradConvolutionLayer1x5Dataset(),
274 framework::dataset::make("DataType", { DataType::F32 })),
275 ActivationFunctionsDataset),
276 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
277
278 {
279 // Validate output
280 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f32);
281 }
282 TEST_SUITE_END() // Conv1x5
283 TEST_SUITE_END() // FP32
284
285
286 TEST_SUITE(FP16)
287
288 using CLWinogradConvolutionLayerFastMathFixture16 = WinogradConvolutionLayerFastMathValidationFixture<CLTensor, CLAccessor, CLWinogradConvolutionLayer, half, float>;
289 TEST_SUITE(Conv3x3)
290 FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::PRECOMMIT,
291 combine(combine(combine(datasets::SmallWinogradConvolutionLayer3x3Dataset(),
292 framework::dataset::make("DataType", { DataType::F16 })),
293 ActivationFunctionsSmallDataset),
294 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
295 {
296 // Validate output
297 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_f16);
298 }
299
300 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
301 combine(combine(combine(datasets::LargeWinogradConvolutionLayer3x3Dataset(),
302 framework::dataset::make("DataType", { DataType::F16 })),
303 ActivationFunctionsDataset),
304 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
305 {
306 // Validate output
307 validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_convolution_layer_f16);
308 }
309 TEST_SUITE_END() // Conv3x3
310
TEST_SUITE(Conv3x1)311 TEST_SUITE(Conv3x1)
312 FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::PRECOMMIT,
313 combine(combine(combine(datasets::SmallWinogradConvolutionLayer3x1Dataset(),
314 framework::dataset::make("DataType", { DataType::F16 })),
315 ActivationFunctionsSmallDataset),
316 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
317 {
318 // Validate output
319 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_f16);
320 }
321
322 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
323 combine(combine(combine(datasets::LargeWinogradConvolutionLayer3x1Dataset(),
324 framework::dataset::make("DataType", { DataType::F16 })),
325 ActivationFunctionsDataset),
326 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
327 {
328 // Validate output
329 validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_convolution_layer_f16);
330 }
331 TEST_SUITE_END() // Conv3x1
332
TEST_SUITE(Conv1x3)333 TEST_SUITE(Conv1x3)
334 FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::PRECOMMIT,
335 combine(combine(combine(datasets::SmallWinogradConvolutionLayer1x3Dataset(),
336 framework::dataset::make("DataType", { DataType::F16 })),
337 ActivationFunctionsSmallDataset),
338 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
339 {
340 // Validate output
341 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_f16);
342 }
343
344 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
345 combine(combine(combine(datasets::LargeWinogradConvolutionLayer1x3Dataset(),
346 framework::dataset::make("DataType", { DataType::F16 })),
347 ActivationFunctionsDataset),
348 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
349 {
350 // Validate output
351 validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_convolution_layer_f16);
352 }
353 TEST_SUITE_END() // Conv1x3
354
TEST_SUITE(Conv5x5)355 TEST_SUITE(Conv5x5)
356 FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::PRECOMMIT,
357 combine(combine(combine(datasets::SmallWinogradConvolutionLayer5x5Dataset(),
358 framework::dataset::make("DataType", { DataType::F16 })),
359 ActivationFunctionsSmallDataset),
360 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
361
362 {
363 // Validate output
364 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_f16);
365 }
366
367 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
368 combine(combine(combine(datasets::LargeWinogradConvolutionLayer5x5Dataset(),
369 framework::dataset::make("DataType", { DataType::F16 })),
370 ActivationFunctionsDataset),
371 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
372
373 {
374 // Validate output
375 validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_convolution_layer_f16);
376 }
377 TEST_SUITE_END() // Conv5x5
378
TEST_SUITE(Conv5x1)379 TEST_SUITE(Conv5x1)
380 FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::PRECOMMIT,
381 combine(combine(combine(datasets::SmallWinogradConvolutionLayer5x1Dataset(),
382 framework::dataset::make("DataType", { DataType::F16 })),
383 ActivationFunctionsSmallDataset),
384 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
385
386 {
387 // Validate output
388 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_f16);
389 }
390
391 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
392 combine(combine(combine(datasets::LargeWinogradConvolutionLayer5x1Dataset(),
393 framework::dataset::make("DataType", { DataType::F16 })),
394 ActivationFunctionsDataset),
395 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
396
397 {
398 // Validate output
399 validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_convolution_layer_f16);
400 }
401 TEST_SUITE_END() // Conv5x1
402
TEST_SUITE(Conv1x5)403 TEST_SUITE(Conv1x5)
404 FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::PRECOMMIT,
405 combine(combine(combine(datasets::SmallWinogradConvolutionLayer1x5Dataset(),
406 framework::dataset::make("DataType", { DataType::F16 })),
407 ActivationFunctionsSmallDataset),
408 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
409
410 {
411 // Validate output
412 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_f16);
413 }
414
415 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
416 combine(combine(combine(datasets::LargeWinogradConvolutionLayer1x5Dataset(),
417 framework::dataset::make("DataType", { DataType::F16 })),
418 ActivationFunctionsDataset),
419 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
420
421 {
422 // Validate output
423 validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_convolution_layer_f16);
424 }
425 TEST_SUITE_END() // Conv1x5
426
TEST_SUITE(Conv1x7)427 TEST_SUITE(Conv1x7)
428 FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::PRECOMMIT,
429 combine(combine(combine(datasets::SmallWinogradConvolutionLayer1x7Dataset(),
430 framework::dataset::make("DataType", { DataType::F16 })),
431 ActivationFunctionsSmallDataset),
432 framework::dataset::make("DataLayout", { DataLayout::NHWC })))
433
434 {
435 // Validate output
436 validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_f16);
437 }
438
439 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
440 combine(combine(combine(datasets::LargeWinogradConvolutionLayer1x7Dataset(),
441 framework::dataset::make("DataType", { DataType::F16 })),
442 ActivationFunctionsDataset),
443 framework::dataset::make("DataLayout", { DataLayout::NHWC })))
444
445 {
446 // Validate output
447 validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_convolution_layer_f16);
448 }
449 TEST_SUITE_END() // Conv1x7
450 TEST_SUITE_END() // FP16
451 TEST_SUITE_END() // ConvolutionLayer
452 TEST_SUITE_END() // Winograd
453 TEST_SUITE_END() // CL
454 } // namespace validation
455 } // namespace test
456 } // namespace arm_compute
457