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review.mlplatform.org / ml / ComputeLibrary / 35c3eb011d8e2813d83c6a6cbe28a446534e4a14 / . / tests / validation / CL / GEMMMatrixMultiplyInterleavedTransposed.cpp
blob: c3b461a0d8bba81e154bbb6539cc4c67ddd5c50a [file] [log] [blame]
Gian Marco Iodiced1f54762019-07-19 09:54:47 +0100[diff] [blame]1/*
2 * Copyright (c) 2019 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/CL/kernels/CLGEMMMatrixMultiplyKernel.h"
25#include "arm_compute/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.h"
26#include "arm_compute/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h"
27#include "arm_compute/core/KernelDescriptors.h"
28#include "arm_compute/core/Types.h"
29#include "arm_compute/core/utils/misc/ShapeCalculator.h"
30#include "arm_compute/runtime/CL/CLTensor.h"
31#include "arm_compute/runtime/CL/CLTensorAllocator.h"
32#include "tests/CL/CLAccessor.h"
33#include "tests/CL/Helper.h"
34#include "tests/PaddingCalculator.h"
35#include "tests/datasets/ShapeDatasets.h"
36#include "tests/framework/Asserts.h"
37#include "tests/framework/Macros.h"
38#include "tests/framework/datasets/Datasets.h"
39#include "tests/validation/Validation.h"
40#include "tests/validation/fixtures/GEMMFixture.h"
41
42namespace arm_compute
43{
44namespace test
45{
46namespace validation
47{
48using namespace arm_compute::misc::shape_calculator;
49
50// Create function for CLGEMMReshapeLHSMatrixKernel
51using CLGEMMReshapeLHSMatrix = CLSynthetizeFunction<CLGEMMReshapeLHSMatrixKernel>;
52
53// Create function for CLGEMMReshapeRHSMatrixKernel
54using CLGEMMReshapeRHSMatrix = CLSynthetizeFunction<CLGEMMReshapeRHSMatrixKernel>;
55
56// Create function for CLGEMMMatrixMultiplyKernel
57using CLGEMMMatrixMultiplyReshaped = CLSynthetizeFunction<CLGEMMMatrixMultiplyKernel>;
58
59// Fixture for GEMMMatrixMultiplyInterleavedTransposedValidationFixture
60template <typename T>
61using CLGEMMMatrixMultiplyReshapedFixture =
62 GEMMMatrixMultiplyInterleavedTransposedValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>;
63
64// Fixture for GEMMMatrixMultiplyInterleavedTransposed3DValidationFixture
65template <typename T>
66using CLGEMMMatrixMultiplyReshaped3DFixture =
67 GEMMMatrixMultiplyInterleavedTransposed3DValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>;
68
69namespace
70{
71// *INDENT-OFF*
72// clang-format off
73RelativeTolerance<float> rel_tolerance_f32(0.001f);
74constexpr float abs_tolerance_f32(0.0001f);
75
76RelativeTolerance<half> rel_tolerance_f16(half(0.2));
77constexpr float tolerance_num_f16 = 0.02f;
78
79/** Alpha values to test - Precommit */
Gian Marco Iodicef3622be2019-07-29 14:27:16 +0100[diff] [blame]80const auto alpha_values = framework::dataset::make("alpha", {1.0f, -0.75f} );
Gian Marco Iodiced1f54762019-07-19 09:54:47 +0100[diff] [blame]81
82/** Beta values to test - Precommit */
Gian Marco Iodiced820db62019-08-05 14:23:23 +0100[diff] [blame]83const auto beta_values = framework::dataset::make("beta", {-0.35f, 0.0f} );
Gian Marco Iodiced1f54762019-07-19 09:54:47 +0100[diff] [blame]84
85/** M values to test - Precommit */
86const auto m_values_precommit = framework::dataset::make("M", 37);
87
88/** N values to test - Precommit */
89const auto n_values_precommit = framework::dataset::make("N", 51);
90
91/** K values to test - Precommit */
92const auto k_values_precommit = framework::dataset::make("K", 23);
93
94/** M values to test - Nightly */
95const auto m_values_nightly = framework::dataset::make("M", {421, 1});
96
97/** N values to test - Nightly */
98const auto n_values_nightly = framework::dataset::make("N", 323);
99
100/** K values to test - Nightly */
101const auto k_values_nightly = framework::dataset::make("K", 207);
102
103/** M_W values to test - Precommit */
104const auto m_w_values_precommit = framework::dataset::make("M_W", 5);
105
106/** M_H values to test - Precommit */
107const auto m_h_values_precommit = framework::dataset::make("M_H", 7);
108
109/** M_W values to test - Nightly */
110const auto m_w_values_nightly = framework::dataset::make("M_W", 13);
111
112/** M_H values to test - Nightly */
113const auto m_h_values_nightly = framework::dataset::make("M_H", 27);
114
115/** Batch size values to test */
116const auto b_values = framework::dataset::make("batch_size", 1, 3);
117
118/** Activation values to test */
119const auto act_values = framework::dataset::make("Activation",
120{
121 ActivationLayerInfo(),
122 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
123});
124
125/** V0 values to test - Precommit */
126const auto v0_values_precommit = framework::dataset::make("V0", 2);
127
128/** H0 values to test - Precommit */
129const auto h0_values_precommit = framework::dataset::make("H0", 4);
130
131/** V0 values to test - Nightly */
132const auto v0_values_nightly = framework::dataset::make("V0", {2, 4});
133
134/** H0 values to test - Nightly */
135const auto h0_values_nightly = framework::dataset::make("H0", { 2, 4 });
136
137/** Broadcast bias from vector to matrix */
138const auto broadcast_bias_values = framework::dataset::make("broadcast_bias", {false, true} );
139
140/** GPU architectures values to test */
141const auto gpu_arch_values = framework::dataset::make("GPUArch",
142{
143 GPUTarget::MIDGARD,
144 GPUTarget::BIFROST
145});
146
147/** Data types values to test in the configuration */
148const auto data_type_values = framework::dataset::make("DataType",
149{
150 DataType::F32,
151 DataType::F16
152});
153
154/** M values to test */
155const auto fp16_mixed_precision_values = framework::dataset::make("fp16_mixed_precision", {true, false});
156
157/** Configuration test */
158void validate_configuration(unsigned int m_value, unsigned int n_value, unsigned int k_value, unsigned int b_value, unsigned int v0_value, unsigned int h0_value, bool broadcast_bias, bool fp16_mixed_precision, const ActivationLayerInfo &act_info, DataType data_type, GPUTarget gpu_arch_value)
159{
160 GEMMLHSMatrixInfo lhs_info;
161 lhs_info.m0 = 4;
162 lhs_info.k0 = 4;
163 lhs_info.v0 = v0_value;
164 lhs_info.interleave = true;
165 lhs_info.transpose = true;
166
167 GEMMRHSMatrixInfo rhs_info;
168 rhs_info.n0 = data_type == DataType::F32? 4 : 8;
169 rhs_info.k0 = 1;
170 rhs_info.h0 = h0_value;
171 rhs_info.interleave = false;
172 rhs_info.transpose = false;
173
174 GEMMReshapeInfo reshape_info(m_value, n_value, k_value, rhs_info.h0, lhs_info.v0, 0, false, broadcast_bias);
175
176 const TensorShape lhs_shape(k_value, m_value, b_value);
177 const TensorShape lhs_shape_reshaped = compute_lhs_reshaped_shape(TensorInfo(lhs_shape, 1, data_type),
178 lhs_info,
179 false);
180
181 const TensorShape rhs_shape(n_value, k_value, b_value);
182 const TensorShape rhs_shape_reshaped = compute_rhs_reshaped_shape(TensorInfo(rhs_shape, 1, data_type),
183 rhs_info);
184
185 const TensorShape dst_shape = compute_mm_shape(TensorInfo(lhs_shape_reshaped, 1, data_type),
186 TensorInfo(rhs_shape_reshaped, 1, data_type),
187 reshape_info);
188
189 const TensorShape bias_shape(n_value,
190 broadcast_bias? 1 : m_value,
191 broadcast_bias? 1 : b_value);
192
193 // Create tensors
194 CLTensor lhs_reshaped = create_tensor<CLTensor>(lhs_shape_reshaped, data_type);
195 CLTensor rhs_reshaped = create_tensor<CLTensor>(rhs_shape_reshaped, data_type);
196 CLTensor bias = create_tensor<CLTensor>(bias_shape, data_type);
197 CLTensor dst = create_tensor<CLTensor>(dst_shape, data_type);
198
199 ARM_COMPUTE_EXPECT(lhs_reshaped.info()->is_resizable(), framework::LogLevel::ERRORS);
200 ARM_COMPUTE_EXPECT(rhs_reshaped.info()->is_resizable(), framework::LogLevel::ERRORS);
201 ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
202 ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
203
204 // Create and configure function
205 CLGEMMMatrixMultiplyReshaped gemm;
206 gemm.configure(gpu_arch_value, &lhs_reshaped, &rhs_reshaped, &bias, &dst, 1.0f, 2.0f, true, reshape_info, fp16_mixed_precision, act_info);
207}
208} // namespace
209
210TEST_SUITE(CL)
211TEST_SUITE(GEMMMatrixMultiplyInterleavedTransposed)
212TEST_SUITE(Float)
213TEST_SUITE(FP32)
214DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
215 m_values_precommit,
216 n_values_precommit),
217 k_values_precommit),
218 framework::dataset::make("batch_size", 1)),
219 v0_values_precommit),
220 h0_values_precommit),
221 broadcast_bias_values),
222 framework::dataset::make("fp16_mixed_precision", false)),
223 act_values),
224 data_type_values),
225 gpu_arch_values),
226m_value, n_value, k_value, b_value, v0_value, h0_value, broadcast_bias, fp16_mixed_precision_value, act_value, data_type_value, gpu_arch_value)
227{
228 validate_configuration(m_value, n_value, k_value, b_value, v0_value, h0_value, broadcast_bias, fp16_mixed_precision_value, act_value, data_type_value, gpu_arch_value);
229}
230
231FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::ALL,
232 combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
233 m_values_precommit,
234 n_values_precommit),
235 k_values_precommit),
236 b_values),
237 alpha_values),
238 beta_values),
239 v0_values_precommit),
240 h0_values_precommit),
241 broadcast_bias_values),
242 framework::dataset::make("fp16_mixed_precision", false)),
243 act_values),
244 framework::dataset::make("DataType", DataType::F32)),
245 gpu_arch_values))
246{
247 // Validate output
248 validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
249}
250
251FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::NIGHTLY,
252 combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
253 m_values_nightly,
254 n_values_nightly),
255 k_values_nightly),
256 b_values),
257 alpha_values),
258 beta_values),
259 v0_values_nightly),
260 h0_values_nightly),
261 broadcast_bias_values),
262 framework::dataset::make("fp16_mixed_precision", false)),
263 act_values),
264 framework::dataset::make("DataType", DataType::F32)),
265 gpu_arch_values))
266{
267 // Validate output
268 validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
269}
270
271FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::ALL,
272 combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
273 m_w_values_precommit,
274 m_h_values_precommit),
275 n_values_precommit),
276 k_values_precommit),
277 b_values),
278 alpha_values),
279 beta_values),
280 v0_values_precommit),
281 h0_values_precommit),
282 broadcast_bias_values),
283 framework::dataset::make("fp16_mixed_precision", false)),
284 act_values),
285 framework::dataset::make("DataType", DataType::F32)),
286 gpu_arch_values))
287{
288 // Validate output
289 validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
290}
291
292FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::NIGHTLY,
293 combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
294 m_w_values_nightly,
295 m_h_values_nightly),
296 n_values_nightly),
297 k_values_nightly),
298 b_values),
299 alpha_values),
300 beta_values),
301 v0_values_nightly),
302 h0_values_nightly),
303 broadcast_bias_values),
304 framework::dataset::make("fp16_mixed_precision", false)),
305 act_values),
306 framework::dataset::make("DataType", DataType::F32)),
307 gpu_arch_values))
308{
309 // Validate output
310 validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
311}
312
313TEST_SUITE_END() // FP32
314
315TEST_SUITE(FP16)
316FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::ALL,
317 combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
318 m_values_precommit,
319 n_values_precommit),
320 k_values_precommit),
321 b_values),
322 alpha_values),
323 beta_values),
324 v0_values_precommit),
325 h0_values_precommit),
326 broadcast_bias_values),
327 fp16_mixed_precision_values),
328 act_values),
329 framework::dataset::make("DataType", DataType::F16)),
330 gpu_arch_values))
331{
332 // Validate output
333 validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16);
334}
335
336FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::NIGHTLY,
337 combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
338 m_values_nightly,
339 n_values_nightly),
340 k_values_nightly),
341 b_values),
342 alpha_values),
343 beta_values),
344 v0_values_nightly),
345 h0_values_nightly),
346 broadcast_bias_values),
347 fp16_mixed_precision_values),
348 act_values),
349 framework::dataset::make("DataType", DataType::F16)),
350 gpu_arch_values))
351{
352 // Validate output
353 validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16);
354}
355
356FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::ALL,
357 combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
358 m_w_values_precommit,
359 m_h_values_precommit),
360 n_values_precommit),
361 k_values_precommit),
362 b_values),
363 alpha_values),
364 beta_values),
365 v0_values_precommit),
366 h0_values_precommit),
367 broadcast_bias_values),
368 fp16_mixed_precision_values),
369 act_values),
370 framework::dataset::make("DataType", DataType::F16)),
371 gpu_arch_values))
372{
373 // Validate output
374 validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16);
375}
376
377FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::NIGHTLY,
378 combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
379 m_w_values_nightly,
380 m_h_values_nightly),
381 n_values_nightly),
382 k_values_nightly),
383 b_values),
384 alpha_values),
385 beta_values),
386 v0_values_nightly),
387 h0_values_nightly),
388 broadcast_bias_values),
389 fp16_mixed_precision_values),
390 act_values),
391 framework::dataset::make("DataType", DataType::F16)),
392 gpu_arch_values))
393{
394 // Validate output
395 validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16);
396}
397
398TEST_SUITE_END() // FP16
399TEST_SUITE_END() // Float
400TEST_SUITE_END() // GEMMMatrixMulipltyInterleavedTransposed
401TEST_SUITE_END() // CL
402} // namespace validation
403} // namespace test
404} // namespace arm_compute