Revert "Update CPU kernels and add mixed sign GEMM support"

This reverts commit fc94f4d23abd4bc427b701f54ad85282e9ec7872 and 5d6fff041ade7eb44af0945867212f3979be3d3e (because the latter fixes a build failure caused by the former)

Change-Id: I7d07fea8307e9a7033b30874bbb14ba9202b23d8
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11815
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Adnan AlSinan <adnan.alsinan@arm.com>

2 files changed, 9 insertions, 128 deletions

diff --git a/tests/validation/NEON/ConvolutionLayer.cpp b/tests/validation/NEON/ConvolutionLayer.cpp
index 7eada81ce5..d739d4e1a4 100644
--- a/tests/validation/NEON/ConvolutionLayer.cpp
+++ b/tests/validation/NEON/ConvolutionLayer.cpp
@@ -147,45 +147,6 @@ const auto QuantizationData = make("QuantizationInfo",
 
 TEST_SUITE(NEON)
 TEST_SUITE(ConvolutionLayer)
-DATA_TEST_CASE(SupportedTypes, framework::DatasetMode::ALL, zip(
-                make("DataType", {
-                    DataType::F32,
-                    DataType::QASYMM8,
-                    DataType::QASYMM8,
-                    DataType::QASYMM8_SIGNED
-                }),
-                make("WeightsDataType", {
-                    DataType::F32,
-                    DataType::QASYMM8,
-                    DataType::QASYMM8_SIGNED,
-                    DataType::QASYMM8
-                }),
-                make("Expected",
-                {
-                    true,
-                    true,
-                    true,
-                    false
-                })),
-data_type_const, weights_data_type_const, expected_const)
-{
-    TensorInfo input_info   = TensorInfo(TensorShape(3U, 3U, 1U), 1, data_type_const);
-    TensorInfo weights_info = TensorInfo(TensorShape(2U, 2U, 1U, 1U), 1, weights_data_type_const);
-    TensorInfo output_info  = TensorInfo(TensorShape(2U, 2U, 1U), 1, data_type_const);
-
-    input_info.set_quantization_info(arm_compute::QuantizationInfo(1, 0));
-    weights_info.set_quantization_info(arm_compute::QuantizationInfo(1, 0));
-    output_info.set_quantization_info(arm_compute::QuantizationInfo(1, 0));
-
-    Status status = NEConvolutionLayer::validate(
-                        &input_info,
-                        &weights_info,
-                        nullptr,
-                        &output_info,
-                        PadStrideInfo());
-
-    ARM_COMPUTE_EXPECT(bool(status) == expected_const, framework::LogLevel::ERRORS);
-}
 
 // *INDENT-OFF*
 // clang-format off
@@ -296,7 +257,7 @@ TEST_CASE(MemoryInjection, framework::DatasetMode::ALL)
 
     for(size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i)
     {
-        ARM_COMPUTE_EXPECT(reinterpret_cast<float *>(result_0.buffer())[i] == reinterpret_cast<float *>(result_1.buffer())[i], framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(((float *)result_0.buffer())[i] == ((float *)result_1.buffer())[i], framework::LogLevel::ERRORS);
     }
 }
 
@@ -342,7 +303,7 @@ TEST_CASE(MultipleExecutionWithConfigure, framework::DatasetMode::ALL)
 
     for(size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i)
     {
-        ARM_COMPUTE_EXPECT(reinterpret_cast<float *>(result_0.buffer())[i] == reinterpret_cast<float *>(result_1.buffer())[i], framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(((float *)result_0.buffer())[i] == ((float *)result_1.buffer())[i], framework::LogLevel::ERRORS);
     }
 }
 
@@ -619,7 +580,7 @@ FIXTURE_DATA_TEST_CASE(RunSmall, NEWinogradConvolutionLayerFixture<float>, frame
 
 /// It's enough to run the activations for a single weight/input combination and data type because
 /// activation function is called on top of the winograd output as a separate operator
-/// TODO(COMPMID-6573): Enable after COMPMID-6573 is resolved
+/// TODO: Enable after COMPMID-6573 is resolved
 FIXTURE_DATA_TEST_CASE(RunActivations, NEWinogradConvolutionLayerFixture<float>, framework::DatasetMode::DISABLED,
                        combine(
                            make("Input", TensorShape(3U, 3U, 32U)),
@@ -1158,7 +1119,7 @@ TEST_CASE(MemoryInjection, framework::DatasetMode::ALL)
     auto result_1 = run_conv();
     for(size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i)
     {
-        ARM_COMPUTE_EXPECT(reinterpret_cast<float *>(result_0.buffer())[i] == reinterpret_cast<float *>(result_1.buffer())[i], framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(((float *)result_0.buffer())[i] == ((float *)result_1.buffer())[i], framework::LogLevel::ERRORS);
     }
 }
 
@@ -1199,7 +1160,7 @@ TEST_CASE(MultipleExecutionWithConfigure, framework::DatasetMode::ALL)
     auto result_1 = run_conv();
     for(size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i)
     {
-        ARM_COMPUTE_EXPECT(reinterpret_cast<float *>(result_0.buffer())[i] == reinterpret_cast<float *>(result_1.buffer())[i], framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(((float *)result_0.buffer())[i] == ((float *)result_1.buffer())[i], framework::LogLevel::ERRORS);
     }
 }
 
@@ -1290,14 +1251,12 @@ FIXTURE_DATA_TEST_CASE(RunVeryLarge, NEGEMMConvolutionLayerFixture<float>, frame
 TEST_SUITE_END() // FP32
 TEST_SUITE_END() // Float
 
-// TODO(COMPMID-6573): Extend quantized tests with at least one suite where the weight is padded (the legacy case, see floating point's RunPaddedWeights)
+// TODO: COMPMID-6596 Extend quantized tests with at least one suite where the weight is padded (the legacy case, see floating point's RunPaddedWeights)
 template <typename T>
 using NEGEMMConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture<Tensor, Accessor, NEConvolutionLayer, T>;
 template <typename T>
 using NEGEMMConvolutionLayerQuantizedMixedDataLayoutFixture = ConvolutionValidationQuantizedFixture<Tensor, Accessor, NEConvolutionLayer, T, true>;
 
-using NEGEMMConvolutionLayerQuantizedMixedSignFixture = ConvolutionValidationQuantizedMixedTypeFixture<Tensor, Accessor, NEConvolutionLayer, uint8_t, int8_t>;
-
 template <typename T>
 using NEGEMMConvolutionLayerQuantizedPerChannelFixture = ConvolutionValidationQuantizedPerChannelFixture<Tensor, Accessor, NEConvolutionLayer, T, int8_t>;
 
@@ -1373,50 +1332,6 @@ FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, NEGEMMConvolutionLayerQuantizedFixtur
 }
 TEST_SUITE_END() // QASYMM8_SIGNED
 
-TEST_SUITE(QASYMM8_MIXED)
-FIXTURE_DATA_TEST_CASE(
-    RunSmall,
-    NEGEMMConvolutionLayerQuantizedMixedSignFixture,
-    framework::DatasetMode::ALL,
-    combine(combine(combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(),
-                                                            framework::dataset::make("ReshapeWeights", {true})),
-                                                    framework::dataset::make("DataType", DataType::QASYMM8)),
-                                            framework::dataset::make("WeightsDataType", DataType::QASYMM8_SIGNED)),
-                                    framework::dataset::make("DataLayout", {DataLayout::NCHW, DataLayout::NHWC})),
-                            framework::dataset::make("QuantizationInfoIfActivationEnabled",
-{QuantizationInfo(2.f / 255.f, 10)})),
-framework::dataset::make("WeightQuantizationInfoIfActivationEnabled",
-{QuantizationInfo(2.f / 255.f, 10)})),
-QuantizedActivationFunctionsDataset))
-{
-    // Validate output
-    validate(Accessor(_target), _reference, tolerance_qasymm8);
-}
-FIXTURE_DATA_TEST_CASE(
-    RunMixedDataLayout,
-    NEGEMMConvolutionLayerQuantizedMixedSignFixture,
-    framework::DatasetMode::ALL,
-    combine(
-        framework::dataset::make("Input", TensorShape(23U, 27U, 5U)),
-        framework::dataset::make("Weights", TensorShape(3U, 3U, 5U, 2U)),
-        framework::dataset::make("Bias", TensorShape(2U)),
-        framework::dataset::make("Output", TensorShape(11U, 25U, 2U)),
-        framework::dataset::make("PadStrideInfo", PadStrideInfo(2, 1, 0, 0)),
-        framework::dataset::make("Dilation", Size2D(1, 1)),
-        framework::dataset::make("ReshapeWeights", {true}),
-        framework::dataset::make("DataType", DataType::QASYMM8),
-        framework::dataset::make("WeightsDataType", DataType::QASYMM8_SIGNED),
-        framework::dataset::make("DataLayout", {DataLayout::NCHW, DataLayout::NHWC}),
-        framework::dataset::make("QuantizationInfoIfActivationEnabled", {QuantizationInfo(2.f / 255.f, 10)}),
-        framework::dataset::make("WeightQuantizationInfoIfActivationEnabled", {QuantizationInfo(2.f / 255.f, 10)}),
-        QuantizedActivationFunctionsDataset)
-    )
-{
-    // Validate output
-    validate(Accessor(_target), _reference, tolerance_qasymm8);
-}
-TEST_SUITE_END() // QASYMM8_MIXED
-
 TEST_SUITE(QSYMM8_PER_CHANNEL)
 FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerQuantizedPerChannelFixture<uint8_t>, framework::DatasetMode::ALL,
                        combine(combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(),
@@ -1521,7 +1436,7 @@ TEST_CASE(MemoryInjection, framework::DatasetMode::ALL)
     auto result_1 = run_conv();
     for(size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i)
     {
-        ARM_COMPUTE_EXPECT(reinterpret_cast<float *>(result_0.buffer())[i] == reinterpret_cast<float *>(result_1.buffer())[i], framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(((float *)result_0.buffer())[i] == ((float *)result_1.buffer())[i], framework::LogLevel::ERRORS);
     }
 }
 
@@ -1561,7 +1476,7 @@ TEST_CASE(MultipleExecutionWithConfigure, framework::DatasetMode::ALL)
     auto result_1 = run_conv();
     for(size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i)
     {
-        ARM_COMPUTE_EXPECT(reinterpret_cast<float *>(result_0.buffer())[i] == reinterpret_cast<float *>(result_1.buffer())[i], framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(((float *)result_0.buffer())[i] == ((float *)result_1.buffer())[i], framework::LogLevel::ERRORS);
     }
 }
 
diff --git a/tests/validation/NEON/GEMMLowp.cpp b/tests/validation/NEON/GEMMLowp.cpp
index 61202ee2b7..d25f43a330 100644
--- a/tests/validation/NEON/GEMMLowp.cpp
+++ b/tests/validation/NEON/GEMMLowp.cpp
@@ -141,23 +141,20 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(
                                              TensorInfo(TensorShape(20U, 13U), 1, DataType::QASYMM8, QuantizationInfo(1.f/255, 10)), // Invalid dimensions
                                              TensorInfo(TensorShape(21U, 13U), 1, DataType::QASYMM8, QuantizationInfo(1.f/255, 10)), // Invalid dimensions
                                              TensorInfo(TensorShape(16U, 32U), 1, DataType::QASYMM8, QuantizationInfo(1.f/255, 10)),
-                                             TensorInfo(TensorShape(16U, 32U), 1, DataType::QASYMM8_SIGNED, QuantizationInfo(1.f/255, 10)), // Invalid types
                                           }),
     make("InputBInfo",{ TensorInfo(TensorShape(33U, 21U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 10)),
                                             TensorInfo(TensorShape(33U, 21U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 10)),
                                             TensorInfo(TensorShape(33U, 21U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 10)),
                                             TensorInfo(TensorShape(33U, 21U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 10)),
                                             TensorInfo(TensorShape(64U, 16U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 10)),
-                                            TensorInfo(TensorShape(64U, 16U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 10)),
                                           }),
     make("OutputInfo",{ TensorInfo(TensorShape(33U, 13U), 1, DataType::S32),
                                             TensorInfo(TensorShape(33U, 13U), 1, DataType::S32),
                                             TensorInfo(TensorShape(33U, 13U), 1, DataType::S32),
                                             TensorInfo(TensorShape(8U, 11U), 1, DataType::S32),
                                             TensorInfo(TensorShape(64U, 32U), 1, DataType::S32),
-                                            TensorInfo(TensorShape(64U, 32U), 1, DataType::S32),
                                            }),
-    make("Expected", { true, false, false, false, true, false })),
+    make("Expected", { true, false, false, false, true })),
     a_info, b_info, output_info, expected)
 {
     // Lock tensors
@@ -362,39 +359,10 @@ TEST_SUITE_END() // DynamicQuantization
 #ifdef __aarch64__
 // Deqaunt tests involve returning F32 from the MatrixMultiplyCore kernels and is only implemented in aarch64
 TEST_SUITE(Dequant)
-DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(
-    make("InputAInfo", {
-        TensorInfo(TensorShape(16U, 32U), 1, DataType::QASYMM8, QuantizationInfo(1.f/255, 10)),
-        TensorInfo(TensorShape(16U, 32U), 1, DataType::QASYMM8_SIGNED, QuantizationInfo(1.f/255, 10)),
-        TensorInfo(TensorShape(16U, 32U), 1, DataType::QASYMM8_SIGNED, QuantizationInfo(1.f/255, 10)), // Invalid types
-    }),
-    make("InputBInfo",{
-        TensorInfo(TensorShape(64U, 16U), 1, DataType::QASYMM8_SIGNED, QuantizationInfo(1.f/256, 10)),
-        TensorInfo(TensorShape(64U, 16U), 1, DataType::QASYMM8_SIGNED, QuantizationInfo(1.f/256, 10)),
-        TensorInfo(TensorShape(64U, 16U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 10)),
-    }),
-    make("OutputInfo",{
-        TensorInfo(TensorShape(64U, 32U), 1, DataType::F32),
-        TensorInfo(TensorShape(64U, 32U), 1, DataType::F32),
-        TensorInfo(TensorShape(64U, 32U), 1, DataType::F32),
-    }),
-    make("Expected", { true, true, false })),
-    a_info, b_info, output_info, expected)
-{
-    // Lock tensors
-    Status status =  NEGEMMLowpMatrixMultiplyCore::validate(&a_info.clone()->set_is_resizable(false),
-                                                            &b_info.clone()->set_is_resizable(false),
-                                                            nullptr,
-                                                            &output_info.clone()->set_is_resizable(false));
-    ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS);
-}
-
 constexpr AbsoluteTolerance<float> tolerance_dequantized(0.01f);
 FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpDequantizedMatrixMultiplyValidationFixture, framework::DatasetMode::ALL,
     combine(
         datasets::SmallGEMMLowpDataset(),
-        make("DataTypeA", {DataType::QASYMM8_SIGNED, DataType::QASYMM8}),
-        make("DataTypeB", DataType::QASYMM8_SIGNED),
         make("accumulate", {true, false})
     ))
 {
@@ -405,8 +373,6 @@ FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpDequantizedMatrixMultiplyValidationFi
 FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpDequantizedMatrixMultiplyValidationFixture, framework::DatasetMode::NIGHTLY,
     combine(
         datasets::LargeGEMMLowpDataset(),
-        make("DataTypeA", {DataType::QASYMM8_SIGNED, DataType::QASYMM8}),
-        make("DataTypeB", DataType::QASYMM8_SIGNED),
         make("accumulate", {false})
     ))
 {