COMPMID-1979: Fuse Activation Function in CLGEMM - part 3
Fused beta*bias in in the old cl gemm kernels
Fused activation function in the old cl gemm kernels
Change-Id: I695fb9189e6d4792010abd256784624982d17d79
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1587
Reviewed-by: Giuseppe Rossini <giuseppe.rossini@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/CL/GEMMMatrixMultiplyInterleavedTransposed.cpp b/tests/validation/CL/GEMMMatrixMultiplyInterleavedTransposed.cpp
new file mode 100644
index 0000000..cae94b2
--- /dev/null
+++ b/tests/validation/CL/GEMMMatrixMultiplyInterleavedTransposed.cpp
@@ -0,0 +1,404 @@
+/*
+ * Copyright (c) 2019 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 "arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h"
+#include "arm_compute/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.h"
+#include "arm_compute/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h"
+#include "arm_compute/core/KernelDescriptors.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/runtime/CL/CLTensor.h"
+#include "arm_compute/runtime/CL/CLTensorAllocator.h"
+#include "tests/CL/CLAccessor.h"
+#include "tests/CL/Helper.h"
+#include "tests/PaddingCalculator.h"
+#include "tests/datasets/ShapeDatasets.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/fixtures/GEMMFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+using namespace arm_compute::misc::shape_calculator;
+
+// Create function for CLGEMMReshapeLHSMatrixKernel
+using CLGEMMReshapeLHSMatrix = CLSynthetizeFunction<CLGEMMReshapeLHSMatrixKernel>;
+
+// Create function for CLGEMMReshapeRHSMatrixKernel
+using CLGEMMReshapeRHSMatrix = CLSynthetizeFunction<CLGEMMReshapeRHSMatrixKernel>;
+
+// Create function for CLGEMMMatrixMultiplyKernel
+using CLGEMMMatrixMultiplyReshaped = CLSynthetizeFunction<CLGEMMMatrixMultiplyKernel>;
+
+// Fixture for GEMMMatrixMultiplyInterleavedTransposedValidationFixture
+template <typename T>
+using CLGEMMMatrixMultiplyReshapedFixture =
+ GEMMMatrixMultiplyInterleavedTransposedValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>;
+
+// Fixture for GEMMMatrixMultiplyInterleavedTransposed3DValidationFixture
+template <typename T>
+using CLGEMMMatrixMultiplyReshaped3DFixture =
+ GEMMMatrixMultiplyInterleavedTransposed3DValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>;
+
+namespace
+{
+// *INDENT-OFF*
+// clang-format off
+RelativeTolerance<float> rel_tolerance_f32(0.001f);
+constexpr float abs_tolerance_f32(0.0001f);
+
+RelativeTolerance<half> rel_tolerance_f16(half(0.2));
+constexpr float tolerance_num_f16 = 0.02f;
+
+/** Alpha values to test - Precommit */
+const auto alpha_values = framework::dataset::make("alpha", {0.0f, 1.0f, -0.75f} );
+
+/** Beta values to test - Precommit */
+const auto beta_values = framework::dataset::make("beta", {-0.75f, 0.0f} );
+
+/** M values to test - Precommit */
+const auto m_values_precommit = framework::dataset::make("M", 37);
+
+/** N values to test - Precommit */
+const auto n_values_precommit = framework::dataset::make("N", 51);
+
+/** K values to test - Precommit */
+const auto k_values_precommit = framework::dataset::make("K", 23);
+
+/** M values to test - Nightly */
+const auto m_values_nightly = framework::dataset::make("M", {421, 1});
+
+/** N values to test - Nightly */
+const auto n_values_nightly = framework::dataset::make("N", 323);
+
+/** K values to test - Nightly */
+const auto k_values_nightly = framework::dataset::make("K", 207);
+
+/** M_W values to test - Precommit */
+const auto m_w_values_precommit = framework::dataset::make("M_W", 5);
+
+/** M_H values to test - Precommit */
+const auto m_h_values_precommit = framework::dataset::make("M_H", 7);
+
+/** M_W values to test - Nightly */
+const auto m_w_values_nightly = framework::dataset::make("M_W", 13);
+
+/** M_H values to test - Nightly */
+const auto m_h_values_nightly = framework::dataset::make("M_H", 27);
+
+/** Batch size values to test */
+const auto b_values = framework::dataset::make("batch_size", 1, 3);
+
+/** Activation values to test */
+const auto act_values = framework::dataset::make("Activation",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
+});
+
+/** V0 values to test - Precommit */
+const auto v0_values_precommit = framework::dataset::make("V0", 2);
+
+/** H0 values to test - Precommit */
+const auto h0_values_precommit = framework::dataset::make("H0", 4);
+
+/** V0 values to test - Nightly */
+const auto v0_values_nightly = framework::dataset::make("V0", {2, 4});
+
+/** H0 values to test - Nightly */
+const auto h0_values_nightly = framework::dataset::make("H0", { 2, 4 });
+
+/** Broadcast bias from vector to matrix */
+const auto broadcast_bias_values = framework::dataset::make("broadcast_bias", {false, true} );
+
+/** GPU architectures values to test */
+const auto gpu_arch_values = framework::dataset::make("GPUArch",
+{
+ GPUTarget::MIDGARD,
+ GPUTarget::BIFROST
+});
+
+/** Data types values to test in the configuration */
+const auto data_type_values = framework::dataset::make("DataType",
+{
+ DataType::F32,
+ DataType::F16
+});
+
+/** M values to test */
+const auto fp16_mixed_precision_values = framework::dataset::make("fp16_mixed_precision", {true, false});
+
+/** Configuration test */
+void 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)
+{
+ GEMMLHSMatrixInfo lhs_info;
+ lhs_info.m0 = 4;
+ lhs_info.k0 = 4;
+ lhs_info.v0 = v0_value;
+ lhs_info.interleave = true;
+ lhs_info.transpose = true;
+
+ GEMMRHSMatrixInfo rhs_info;
+ rhs_info.n0 = data_type == DataType::F32? 4 : 8;
+ rhs_info.k0 = 1;
+ rhs_info.h0 = h0_value;
+ rhs_info.interleave = false;
+ rhs_info.transpose = false;
+
+ GEMMReshapeInfo reshape_info(m_value, n_value, k_value, rhs_info.h0, lhs_info.v0, 0, false, broadcast_bias);
+
+ const TensorShape lhs_shape(k_value, m_value, b_value);
+ const TensorShape lhs_shape_reshaped = compute_lhs_reshaped_shape(TensorInfo(lhs_shape, 1, data_type),
+ lhs_info,
+ false);
+
+ const TensorShape rhs_shape(n_value, k_value, b_value);
+ const TensorShape rhs_shape_reshaped = compute_rhs_reshaped_shape(TensorInfo(rhs_shape, 1, data_type),
+ rhs_info);
+
+ const TensorShape dst_shape = compute_mm_shape(TensorInfo(lhs_shape_reshaped, 1, data_type),
+ TensorInfo(rhs_shape_reshaped, 1, data_type),
+ reshape_info);
+
+ const TensorShape bias_shape(n_value,
+ broadcast_bias? 1 : m_value,
+ broadcast_bias? 1 : b_value);
+
+ // Create tensors
+ CLTensor lhs_reshaped = create_tensor<CLTensor>(lhs_shape_reshaped, data_type);
+ CLTensor rhs_reshaped = create_tensor<CLTensor>(rhs_shape_reshaped, data_type);
+ CLTensor bias = create_tensor<CLTensor>(bias_shape, data_type);
+ CLTensor dst = create_tensor<CLTensor>(dst_shape, data_type);
+
+ ARM_COMPUTE_EXPECT(lhs_reshaped.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(rhs_reshaped.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Create and configure function
+ CLGEMMMatrixMultiplyReshaped gemm;
+ gemm.configure(gpu_arch_value, &lhs_reshaped, &rhs_reshaped, &bias, &dst, 1.0f, 2.0f, true, reshape_info, fp16_mixed_precision, act_info);
+}
+} // namespace
+
+TEST_SUITE(CL)
+TEST_SUITE(GEMMMatrixMultiplyInterleavedTransposed)
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+ m_values_precommit,
+ n_values_precommit),
+ k_values_precommit),
+ framework::dataset::make("batch_size", 1)),
+ v0_values_precommit),
+ h0_values_precommit),
+ broadcast_bias_values),
+ framework::dataset::make("fp16_mixed_precision", false)),
+ act_values),
+ data_type_values),
+ gpu_arch_values),
+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)
+{
+ 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);
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::ALL,
+ combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+ m_values_precommit,
+ n_values_precommit),
+ k_values_precommit),
+ b_values),
+ alpha_values),
+ beta_values),
+ v0_values_precommit),
+ h0_values_precommit),
+ broadcast_bias_values),
+ framework::dataset::make("fp16_mixed_precision", false)),
+ act_values),
+ framework::dataset::make("DataType", DataType::F32)),
+ gpu_arch_values))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+ m_values_nightly,
+ n_values_nightly),
+ k_values_nightly),
+ b_values),
+ alpha_values),
+ beta_values),
+ v0_values_nightly),
+ h0_values_nightly),
+ broadcast_bias_values),
+ framework::dataset::make("fp16_mixed_precision", false)),
+ act_values),
+ framework::dataset::make("DataType", DataType::F32)),
+ gpu_arch_values))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::ALL,
+ combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+ m_w_values_precommit,
+ m_h_values_precommit),
+ n_values_precommit),
+ k_values_precommit),
+ b_values),
+ alpha_values),
+ beta_values),
+ v0_values_precommit),
+ h0_values_precommit),
+ broadcast_bias_values),
+ framework::dataset::make("fp16_mixed_precision", false)),
+ act_values),
+ framework::dataset::make("DataType", DataType::F32)),
+ gpu_arch_values))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+ m_w_values_nightly,
+ m_h_values_nightly),
+ n_values_nightly),
+ k_values_nightly),
+ b_values),
+ alpha_values),
+ beta_values),
+ v0_values_nightly),
+ h0_values_nightly),
+ broadcast_bias_values),
+ framework::dataset::make("fp16_mixed_precision", false)),
+ act_values),
+ framework::dataset::make("DataType", DataType::F32)),
+ gpu_arch_values))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
+}
+
+TEST_SUITE_END() // FP32
+
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::ALL,
+ combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+ m_values_precommit,
+ n_values_precommit),
+ k_values_precommit),
+ b_values),
+ alpha_values),
+ beta_values),
+ v0_values_precommit),
+ h0_values_precommit),
+ broadcast_bias_values),
+ fp16_mixed_precision_values),
+ act_values),
+ framework::dataset::make("DataType", DataType::F16)),
+ gpu_arch_values))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+ m_values_nightly,
+ n_values_nightly),
+ k_values_nightly),
+ b_values),
+ alpha_values),
+ beta_values),
+ v0_values_nightly),
+ h0_values_nightly),
+ broadcast_bias_values),
+ fp16_mixed_precision_values),
+ act_values),
+ framework::dataset::make("DataType", DataType::F16)),
+ gpu_arch_values))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16);
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::ALL,
+ combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+ m_w_values_precommit,
+ m_h_values_precommit),
+ n_values_precommit),
+ k_values_precommit),
+ b_values),
+ alpha_values),
+ beta_values),
+ v0_values_precommit),
+ h0_values_precommit),
+ broadcast_bias_values),
+ fp16_mixed_precision_values),
+ act_values),
+ framework::dataset::make("DataType", DataType::F16)),
+ gpu_arch_values))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+ m_w_values_nightly,
+ m_h_values_nightly),
+ n_values_nightly),
+ k_values_nightly),
+ b_values),
+ alpha_values),
+ beta_values),
+ v0_values_nightly),
+ h0_values_nightly),
+ broadcast_bias_values),
+ fp16_mixed_precision_values),
+ act_values),
+ framework::dataset::make("DataType", DataType::F16)),
+ gpu_arch_values))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16);
+}
+
+TEST_SUITE_END() // FP16
+TEST_SUITE_END() // Float
+TEST_SUITE_END() // GEMMMatrixMulipltyInterleavedTransposed
+TEST_SUITE_END() // CL
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
\ No newline at end of file