Lines Matching +full:make +full:- +full:all
2 * Copyright (c) 2017-2023 Arm Limited.
4 * SPDX-License-Identifier: MIT
13 * The above copyright notice and this permission notice shall be included in all
87 const auto CNNDataTypes = framework::dataset::make("DataType",
95 const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo",
102 const auto QuantizationData = framework::dataset::make("QuantizationInfo",
114 // *INDENT-OFF* in TEST_SUITE()
115 // clang-format off in TEST_SUITE()
116 DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( in TEST_SUITE()
117 … framework::dataset::make("InputInfo", { TensorInfo(TensorShape(18U, 18U, 32U), 1, DataType::F32), in TEST_SUITE()
122 …framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 32U, 21U), 1, DataType::F…
127 … framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(16U, 16U, 21U), 1, DataType::F32),
132 … framework::dataset::make("ConvInfo", { PadStrideInfo(1, 1, 0, 0),
137 framework::dataset::make("FastMath", { true,
142 …framework::dataset::make("Expected", { ConvolutionMethod::WINOGRAD, ConvolutionMethod::WINOGRAD, C…
145 …ConvolutionMethod is_valid = NEConvolutionLayer::get_convolution_method(&input_info.clone()->set_i…
146 … &weights_info.clone()->set_is_resizable(true),
147 …&output_info.clone()->set_is_resizable(true), conv_info, WeightsInfo(), Size2D(1U, 1U), Activation…
150 // clang-format on
151 // *INDENT-ON*
165 * Configure the operator once and inject memory at run-time in multiple executions.
168 * - Both runs compute the same output
170 TEST_CASE(MemoryInjection, framework::DatasetMode::ALL) in TEST_CASE() argument
179 winograd->configure(&src_info, &b_info, &w_info, &dst_info, pad_info); in TEST_CASE()
185 a.allocator()->allocate(); in TEST_CASE()
186 b.allocator()->allocate(); in TEST_CASE()
187 c.allocator()->allocate(); in TEST_CASE()
193 auto ws = manage_workspace<Tensor>(winograd->workspace(), mg, run_pack, prep_pack); in TEST_CASE()
194 auto run_conv = [&]() -> Tensor in TEST_CASE()
197 dst.allocator()->allocate(); in TEST_CASE()
200 library->fill_tensor_value(Accessor(a), 1.f); in TEST_CASE()
201 library->fill_tensor_value(Accessor(b), 2.f); in TEST_CASE()
202 library->fill_tensor_value(Accessor(c), 3.f); in TEST_CASE()
205 winograd->prepare(prep_pack); in TEST_CASE()
206 winograd->run(run_pack); in TEST_CASE()
213 for(size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i) in TEST_CASE()
221 …* Make sure @ref NEWinogradConvolutionLayer still works through injecting the memory at configure …
224 * - Both runs compute the same output
226 TEST_CASE(MultipleExecutionWithConfigure, framework::DatasetMode::ALL) in TEST_CASE() argument
242 gemm->configure(&src, &b, &w, &dst, pad_info); in TEST_CASE()
244 src.allocator()->allocate(); in TEST_CASE()
245 b.allocator()->allocate(); in TEST_CASE()
246 w.allocator()->allocate(); in TEST_CASE()
247 dst.allocator()->allocate(); in TEST_CASE()
249 library->fill_tensor_value(Accessor(src), 1.f); in TEST_CASE()
250 library->fill_tensor_value(Accessor(b), 2.f); in TEST_CASE()
251 library->fill_tensor_value(Accessor(w), 3.f); in TEST_CASE()
252 gemm->run(); in TEST_CASE()
259 for(size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i) in TEST_CASE()
270 … framework::dataset::make("DataType", { DataType::F32 })), in TEST_SUITE()
272 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
279 … framework::dataset::make("Input", TensorShape(8U, 8U, 32U)),
280 … framework::dataset::make("Weight", TensorShape(1U, 3U, 32U, 1U))),
281 … framework::dataset::make("Bias", TensorShape(1U))),
282 … framework::dataset::make("Output", TensorShape(8U, 6U, 1U))),
283 … framework::dataset::make("PadStrideInfo", PadStrideInfo(1, 1, 0, 0))),
284 … framework::dataset::make("Dilation", Size2D(1U, 1U))),
285 … framework::dataset::make("DataType", { DataType::F32 })),
287 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
294 … framework::dataset::make("DataType", { DataType::F32 })),
296 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
307 … framework::dataset::make("DataType", { DataType::F32 })), in TEST_SUITE()
309 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
316 … framework::dataset::make("DataType", { DataType::F32 })),
318 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
329 … framework::dataset::make("DataType", { DataType::F32 })), in TEST_SUITE()
331 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
338 … framework::dataset::make("DataType", { DataType::F32 })),
340 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
351 … framework::dataset::make("DataType", { DataType::F32 })), in TEST_SUITE()
353 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
360 … framework::dataset::make("DataType", { DataType::F32 })),
362 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
373 … framework::dataset::make("DataType", { DataType::F32 })), in TEST_SUITE()
375 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
383 … framework::dataset::make("DataType", { DataType::F32 })),
385 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
395 … framework::dataset::make("DataType", { DataType::F32 })), in TEST_SUITE()
397 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
405 … framework::dataset::make("DataType", { DataType::F32 })),
407 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
417 … framework::dataset::make("DataType", { DataType::F32 })), in TEST_SUITE()
419 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
427 … framework::dataset::make("DataType", { DataType::F32 })),
429 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
441 … framework::dataset::make("DataType", { DataType::F32 })), in TEST_SUITE()
443 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
451 … framework::dataset::make("DataType", { DataType::F32 })),
453 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
465 … framework::dataset::make("DataType", { DataType::F32 })),
468 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
480 DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
481 … framework::dataset::make("InputInfo", { TensorInfo(TensorShape(18U, 18U, 32U), 1, DataType::F16),
484 …framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 32U, 21U), 1, DataType::F…
487 … framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(16U, 16U, 21U), 1, DataType::F32),
490 … framework::dataset::make("ConvInfo", { PadStrideInfo(1, 1, 0, 0),
493 …framework::dataset::make("FastMath", { false, // case fp16 and fast_math False then disable Winogr…
496 … framework::dataset::make("Expected", { ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD })),
499 …ConvolutionMethod is_valid = NEConvolutionLayer::get_convolution_method(&input_info.clone()->set_i…
500 … &weights_info.clone()->set_is_resizable(true),
501 …&output_info.clone()->set_is_resizable(true), conv_info, WeightsInfo(), Size2D(1U, 1U), Activation…
508 … framework::dataset::make("DataType", { DataType::F16 })),
510 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
519 … framework::dataset::make("DataType", { DataType::F16 })),
521 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
546 …(UC2_1_CpuGemmConv2d, HasOptImplFixtureNoFastMath<cpu::CpuGemmConv2d>, framework::DatasetMode::ALL,
547 combine(framework::dataset::make("DataType", { DataType::F32 }),
548 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::OHWIo2 })))
552 …ConvolutionLayer, HasOptImplFixtureNoFastMath<NEGEMMConvolutionLayer>, framework::DatasetMode::ALL,
553 combine(framework::dataset::make("DataType", { DataType::F32 }),
554 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::OHWIo2 })))
559 …CpuGemmConv2d_FastMath, HasOptImplFixtureFastMath<cpu::CpuGemmConv2d>, framework::DatasetMode::ALL,
560 combine(framework::dataset::make("DataType", { DataType::F32 }),
561 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::OHWIo2 })))
566 …tionLayer_FastMath, HasOptImplFixtureFastMath<NEGEMMConvolutionLayer>, framework::DatasetMode::ALL,
567 combine(framework::dataset::make("DataType", { DataType::F32 }),
568 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::OHWIo2 })))
576 …(UC2_2_CpuGemmConv2d, HasOptImplFixtureNoFastMath<cpu::CpuGemmConv2d>, framework::DatasetMode::ALL,
577 combine(framework::dataset::make("DataType", { DataType::F32 }),
578 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::OHWIo4 })))
584 …ConvolutionLayer, HasOptImplFixtureNoFastMath<NEGEMMConvolutionLayer>, framework::DatasetMode::ALL,
585 combine(framework::dataset::make("DataType", { DataType::F32 }),
586 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::OHWIo4 })))
594 …CpuGemmConv2d_FastMath, HasOptImplFixtureFastMath<cpu::CpuGemmConv2d>, framework::DatasetMode::ALL,
595 combine(framework::dataset::make("DataType", { DataType::F32 }),
596 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::OHWIo8i4_bf16 })))
602 …tionLayer_FastMath, HasOptImplFixtureFastMath<NEGEMMConvolutionLayer>, framework::DatasetMode::ALL,
603 combine(framework::dataset::make("DataType", { DataType::F32 }),
604 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::OHWIo8i4_bf16 })))
617 …(UC3_1_CpuGemmConv2d, HasOptImplFixtureNoFastMath<cpu::CpuGemmConv2d>, framework::DatasetMode::ALL,
618 combine(framework::dataset::make("DataType", { DataType::S32 }),
619 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::ANY })))
624 …ConvolutionLayer, HasOptImplFixtureNoFastMath<NEGEMMConvolutionLayer>, framework::DatasetMode::ALL,
625 combine(framework::dataset::make("DataType", { DataType::S32 }),
626 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::ANY })))
631 …CpuGemmConv2d_FastMath, HasOptImplFixtureFastMath<cpu::CpuGemmConv2d>, framework::DatasetMode::ALL,
632 combine(framework::dataset::make("DataType", { DataType::S32 }),
633 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::ANY })))
638 …tionLayer_FastMath, HasOptImplFixtureFastMath<NEGEMMConvolutionLayer>, framework::DatasetMode::ALL,
639 combine(framework::dataset::make("DataType", { DataType::S32 }),
640 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::ANY })))
652 // format like OHWIo4 for FP32 data returned for 128-bit NEON hardware
653 // is replaced by OHWIo8 when running on 256-bit SVE.
655 …(UC3_2_CpuGemmConv2d, HasOptImplFixtureNoFastMath<cpu::CpuGemmConv2d>, framework::DatasetMode::ALL,
656 combine(framework::dataset::make("DataType", { DataType::F32 }),
657 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::ANY })))
664 …ConvolutionLayer, HasOptImplFixtureNoFastMath<NEGEMMConvolutionLayer>, framework::DatasetMode::ALL,
665 combine(framework::dataset::make("DataType", { DataType::F32 }),
666 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::ANY })))
674 …CpuGemmConv2d_FastMath, HasOptImplFixtureFastMath<cpu::CpuGemmConv2d>, framework::DatasetMode::ALL,
675 combine(framework::dataset::make("DataType", { DataType::F32 }),
676 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::ANY })))
684 …tionLayer_FastMath, HasOptImplFixtureFastMath<NEGEMMConvolutionLayer>, framework::DatasetMode::ALL,
685 combine(framework::dataset::make("DataType", { DataType::F32 }),
686 … framework::dataset::make("QueryWeightFormat", { arm_compute::WeightFormat::ANY })))
699 auto prepare_weights_shapes = framework::dataset::make("TensorShape",
703 // OHWI --> O'HWI', where:
752 // ---------
759 DATA_TEST_CASE(PrepareWeightShape, framework::DatasetMode::ALL, in DATA_TEST_CASE() argument
779 FIXTURE_DATA_TEST_CASE(RunSmallFloat, VarWidth<float>, framework::DatasetMode::ALL,
781 … framework::dataset::make("DataLayout", { DataLayout::NHWC })),
782 framework::dataset::make("ACL Scalar type", { DataType::F32 })))
788 FIXTURE_DATA_TEST_CASE(RunSmallHalf, VarWidth<half>, framework::DatasetMode::ALL,
790 … framework::dataset::make("DataLayout", { DataLayout::NHWC })),
791 framework::dataset::make("ACL Scalar type", { DataType::F16 })))
801 FIXTURE_DATA_TEST_CASE(RunSmallFloatFastMath, VarWidthFastMath<float>, framework::DatasetMode::ALL,
803 … framework::dataset::make("DataLayout", { DataLayout::NHWC })),
804 framework::dataset::make("ACL Scalar type", { DataType::F32 })))
818 FIXTURE_DATA_TEST_CASE(NEGEMMRunSmallFloat, NEGEMMVarWidth<float>, framework::DatasetMode::ALL,
820 … framework::dataset::make("DataLayout", { DataLayout::NHWC })),
821 framework::dataset::make("ACL Scalar type", { DataType::F32 })))
827 FIXTURE_DATA_TEST_CASE(NEGEMMRunSmallHalf, NEGEMMVarWidth<half>, framework::DatasetMode::ALL,
829 … framework::dataset::make("DataLayout", { DataLayout::NHWC })),
830 framework::dataset::make("ACL Scalar type", { DataType::F16 })))
840 …_TEST_CASE(NEGEMMRunSmallFloatFastMath, NEGEMMVarWidthFastMath<float>, framework::DatasetMode::ALL,
842 … framework::dataset::make("DataLayout", { DataLayout::NHWC })),
843 framework::dataset::make("ACL Scalar type", { DataType::F32 })))
863 * Configure the operator once and inject memory at run-time in multiple executions.
866 * - Both runs compute the same output
868 TEST_CASE(MemoryInjection, framework::DatasetMode::ALL) in TEST_CASE() argument
877 conv->configure(&src_info, &weight_info, &bias_info, &dst_info, conv_info, weights_info); in TEST_CASE()
883 src.allocator()->allocate(); in TEST_CASE()
884 weight.allocator()->allocate(); in TEST_CASE()
885 bias.allocator()->allocate(); in TEST_CASE()
891 auto ws = manage_workspace<Tensor>(conv->workspace(), mg, run_pack, prep_pack); in TEST_CASE()
893 auto run_conv = [&]() -> Tensor in TEST_CASE()
896 dst.allocator()->allocate(); in TEST_CASE()
899 library->fill_tensor_value(Accessor(src), 1.f); in TEST_CASE()
900 library->fill_tensor_value(Accessor(weight), 2.f); in TEST_CASE()
901 library->fill_tensor_value(Accessor(bias), 3.f); in TEST_CASE()
903 conv->prepare(prep_pack); in TEST_CASE()
904 conv->run(run_pack); in TEST_CASE()
909 for(size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i) in TEST_CASE()
917 …* Make sure @ref NEGEMMConvolutionLayer still works through injecting the memory at configure time…
920 * - Both runs compute the same output
922 TEST_CASE(MultipleExecutionWithConfigure, framework::DatasetMode::ALL) in TEST_CASE() argument
937 conv->configure(&src, &weight, &bias, &dst, conv_info, weights_info); in TEST_CASE()
938 src.allocator()->allocate(); in TEST_CASE()
939 weight.allocator()->allocate(); in TEST_CASE()
940 bias.allocator()->allocate(); in TEST_CASE()
941 dst.allocator()->allocate(); in TEST_CASE()
942 library->fill_tensor_value(Accessor(src), 1.f); in TEST_CASE()
943 library->fill_tensor_value(Accessor(weight), 2.f); in TEST_CASE()
944 library->fill_tensor_value(Accessor(bias), 3.f); in TEST_CASE()
945 conv->run(); in TEST_CASE()
950 for(size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i) in TEST_CASE()
959 FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixture<float>, framework::DatasetMode::ALL,… in TEST_SUITE()
960 …mework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType:… in TEST_SUITE()
971 FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixture<half>, framework::DatasetMode::ALL, … in TEST_SUITE()
972 …framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataTy… in TEST_SUITE()
981 FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixture<float>, framework::DatasetMode::ALL,… in TEST_SUITE()
982 …framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataTy… in TEST_SUITE()
988 …nMixedDataLayout, NEGEMMConvolutionLayerMixedDataLayoutFixture<float>, framework::DatasetMode::ALL,
990 … framework::dataset::make("Input", TensorShape(23U, 27U, 5U)),
991 … framework::dataset::make("Weights", TensorShape(3U, 3U, 5U, 2U))),
992 … framework::dataset::make("Bias", TensorShape(2U))),
993 … framework::dataset::make("Output", TensorShape(11U, 25U, 2U))),
994 … framework::dataset::make("PadStrideInfo", PadStrideInfo(2, 1, 0, 0))),
995 … framework::dataset::make("Dilation", Size2D(1, 1))),
996 … framework::dataset::make("ReshapeWeights", { true })),
997 framework::dataset::make("DataType", DataType::F32)),
998 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
1015 const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo",
1023 …, NEGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(co… in TEST_SUITE()
1024 …amework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType… in TEST_SUITE()
1025 …framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), QuantizedAct…
1030 …E(RunMixedDataLayout, NEGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::ALL,
1032 … framework::dataset::make("Input", TensorShape(23U, 27U, 5U)),
1033 … framework::dataset::make("Weights", TensorShape(3U, 3U, 5U, 2U))),
1034 … framework::dataset::make("Bias", TensorShape(2U))),
1035 … framework::dataset::make("Output", TensorShape(11U, 25U, 2U))),
1036 … framework::dataset::make("PadStrideInfo", PadStrideInfo(2, 1, 0, 0))),
1037 … framework::dataset::make("Dilation", Size2D(1, 1))),
1038 … framework::dataset::make("ReshapeWeights", { true })),
1039 … framework::dataset::make("DataType", DataType::QASYMM8)),
1040 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
1041 … framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })),
1050 …l, NEGEMMConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(co… in TEST_SUITE()
1051 …ork::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QA… in TEST_SUITE()
1052 …framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.01f, -10) })), QuantizedActivati…
1057 …SE(RunMixedDataLayout, NEGEMMConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL,
1059 … framework::dataset::make("Input", TensorShape(23U, 27U, 5U)),
1060 … framework::dataset::make("Weights", TensorShape(3U, 3U, 5U, 2U))),
1061 … framework::dataset::make("Bias", TensorShape(2U))),
1062 … framework::dataset::make("Output", TensorShape(11U, 25U, 2U))),
1063 … framework::dataset::make("PadStrideInfo", PadStrideInfo(2, 1, 0, 0))),
1064 … framework::dataset::make("Dilation", Size2D(1, 1))),
1065 … framework::dataset::make("ReshapeWeights", { true })),
1066 … framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
1067 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
1068 … framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })),
1077 …E(RunSmall, NEGEMMConvolutionLayerQuantizedPerChannelFixture<uint8_t>, framework::DatasetMode::ALL, in TEST_SUITE()
1079 … framework::dataset::make("ReshapeWeights", { true })), in TEST_SUITE()
1080 … framework::dataset::make("DataType", { DataType::QASYMM8 })),
1081 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
1084 … framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
1089 …SmallSigned, NEGEMMConvolutionLayerQuantizedPerChannelFixture<int8_t>, framework::DatasetMode::ALL,
1091 … framework::dataset::make("ReshapeWeights", { true })),
1092 … framework::dataset::make("DataType", { DataType::QASYMM8_SIGNED })),
1093 … framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
1096 … framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
1112 * Configure the operator once and inject memory at run-time in multiple executions.
1115 * - Both runs compute the same output
1117 TEST_CASE(MemoryInjection, framework::DatasetMode::ALL) in TEST_CASE() argument
1125 conv->configure(&src_info, &weight_info, &bias_info, &dst_info, conv_info); in TEST_CASE()
1131 src.allocator()->allocate(); in TEST_CASE()
1132 weight.allocator()->allocate(); in TEST_CASE()
1133 bias.allocator()->allocate(); in TEST_CASE()
1139 auto ws = manage_workspace<Tensor>(conv->workspace(), mg, run_pack, prep_pack); in TEST_CASE()
1141 auto run_conv = [&]() -> Tensor in TEST_CASE()
1144 dst.allocator()->allocate(); in TEST_CASE()
1147 library->fill_tensor_value(Accessor(src), 1.f); in TEST_CASE()
1148 library->fill_tensor_value(Accessor(weight), 2.f); in TEST_CASE()
1149 library->fill_tensor_value(Accessor(bias), 3.f); in TEST_CASE()
1151 conv->prepare(prep_pack); in TEST_CASE()
1152 conv->run(run_pack); in TEST_CASE()
1157 for(size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i) in TEST_CASE()
1165 …* Make sure @ref NEGEMMConv2d still works through injecting the memory at configure time using the…
1168 * - Both runs compute the same output
1170 TEST_CASE(MultipleExecutionWithConfigure, framework::DatasetMode::ALL) in TEST_CASE() argument
1184 conv->configure(&src, &weight, &bias, &dst, conv_info); in TEST_CASE()
1185 src.allocator()->allocate(); in TEST_CASE()
1186 weight.allocator()->allocate(); in TEST_CASE()
1187 bias.allocator()->allocate(); in TEST_CASE()
1188 dst.allocator()->allocate(); in TEST_CASE()
1189 library->fill_tensor_value(Accessor(src), 1.f); in TEST_CASE()
1190 library->fill_tensor_value(Accessor(weight), 2.f); in TEST_CASE()
1191 library->fill_tensor_value(Accessor(bias), 3.f); in TEST_CASE()
1192 conv->run(); in TEST_CASE()
1197 for(size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i) in TEST_CASE()
1205 FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectGEMMConv2dLayerFixture<float>, framework::DatasetMode::ALL… in TEST_SUITE()
1206 …framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataTy… in TEST_SUITE()
1221 const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo",
1229 … NEDirectGEMMConv2dLayerQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(co… in TEST_SUITE()
1230 …amework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType… in TEST_SUITE()
1231 …framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), QuantizedAct…
1239 …, NEDirectGEMMConv2dLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(co… in TEST_SUITE()
1240 …ork::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QA… in TEST_SUITE()
1241 …framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.01f, -10) })), QuantizedActivati…
1249 …mallSigned, NEDirectGEMMConv2dLayerQuantizedPerChannelFixture<int8_t>, framework::DatasetMode::ALL, in TEST_SUITE()
1251 … framework::dataset::make("ReshapeWeights", { true })), in TEST_SUITE()
1252 … framework::dataset::make("DataType", { DataType::QASYMM8_SIGNED })),
1253 … framework::dataset::make("DataLayout", { DataLayout::NHWC })),
1256 … framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))