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-rw-r--r--tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp273
1 files changed, 268 insertions, 5 deletions
diff --git a/tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp b/tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp
index d7853f3ea7..98149ce149 100644
--- a/tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp
+++ b/tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp
@@ -139,13 +139,13 @@ const auto a_values_nightly = framework::dataset::make("alpha", {1.0f} );
const auto beta_values_nightly = framework::dataset::make("beta", {1.0f} );
/** M0 values to test - Nightly */
-const auto m0_values_nightly = framework::dataset::make("M0", { 2, 3, 4, 8 });
+const auto m0_values_nightly = framework::dataset::make("M0", { 8 });
/** N0 values to test - Nightly */
-const auto n0_values_nightly = framework::dataset::make("N0", { 2, 3, 4, 8 });
+const auto n0_values_nightly = framework::dataset::make("N0", { 8 });
/** K0 values to test - Nightly */
-const auto k0_values_nightly = framework::dataset::make("K0", { 2, 3, 4, 8 });
+const auto k0_values_nightly = framework::dataset::make("K0", { 4 });
/** N0 values to test with export to OpenCL image object - Nightly */
const auto n0_export_to_cl_image_values_nightly = framework::dataset::make("N0", { 4, 8, 16 });
@@ -154,10 +154,10 @@ const auto n0_export_to_cl_image_values_nightly = framework::dataset::make("N0",
const auto k0_export_to_cl_image_values_nightly = framework::dataset::make("K0", { 4, 8, 16 });
/** V0 values to test - Nightly */
-const auto v0_values_nightly = framework::dataset::make("V0", 1, 4);
+const auto v0_values_nightly = framework::dataset::make("V0", 1, 3);
/** H0 values to test - Nightly */
-const auto h0_values_nightly = framework::dataset::make("H0", 1, 4);
+const auto h0_values_nightly = framework::dataset::make("H0", 1, 3);
/** Interleave values to test with LHS matrix */
const auto i_values_lhs = framework::dataset::make("interleave_lhs", { true, false });
@@ -886,6 +886,269 @@ FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>,
// Validate output
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
}
+
+TEST_SUITE(ExportToCLImage)
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("Input0Info", { TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // OK or incorrect if cl_khr_image2d_from_buffer not supported
+ TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // OK or incorrect if cl_khr_image2d_from_buffer not supported
+ TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // OK or incorrect if cl_khr_image2d_from_buffer not supported
+ TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // Incorrect k0
+ TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // Incorrect n0
+
+ }),
+ framework::dataset::make("Input1Info",{ TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16),
+ TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16),
+ TensorInfo(TensorShape(512U, 8U, 2U), 1, DataType::F16),
+ TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16),
+ TensorInfo(TensorShape(128U, 32U, 2U), 1, DataType::F16),
+
+ })),
+ framework::dataset::make("Input2Info", { TensorInfo(TensorShape(64U), 1, DataType::F16),
+ TensorInfo(TensorShape(64U), 1, DataType::F16),
+ TensorInfo(TensorShape(64U), 1, DataType::F16),
+ TensorInfo(TensorShape(64U), 1, DataType::F16),
+ TensorInfo(TensorShape(64U), 1, DataType::F16),
+
+ })),
+ framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
+ TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
+ TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
+ TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
+ TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
+ TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
+
+ })),
+ framework::dataset::make("LHSMInfo",{
+ GEMMLHSMatrixInfo(4, 4, 1, false, true),
+ GEMMLHSMatrixInfo(4, 8, 1, false, true),
+ GEMMLHSMatrixInfo(4, 4, 1, false, true),
+ GEMMLHSMatrixInfo(4, 2, 1, false, false),
+ GEMMLHSMatrixInfo(4, 4, 1, false, false),
+
+ })),
+ framework::dataset::make("RHSMInfo",{
+ GEMMRHSMatrixInfo(4, 4, 1, true, true, true),
+ GEMMRHSMatrixInfo(4, 8, 1, true, true, true),
+ GEMMRHSMatrixInfo(8, 4, 1, true, true, true),
+ GEMMRHSMatrixInfo(4, 2, 1, true, false, true),
+ GEMMRHSMatrixInfo(2, 4, 1, true, false, true),
+ })),
+ framework::dataset::make("GEMMInfo",{GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
+ 64 /**<N Number of RHS columns*/,
+ 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
+ false /**< reinterpret the input as 3D */,
+ true /**< Flag used to broadcast the bias addition */,
+ false /**< wider accumm */,
+ ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
+ 1 /**< Multiplication factor for the width of the 1xW transposed block */,
+ 1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
+ GEMMLHSMatrixInfo(),
+ GEMMRHSMatrixInfo(),
+ 0 /**< Offset to be added to each element of the matrix A */,
+ 0 /**< Offset to be added to each element of the matrix B */),
+ GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
+ 64 /**<N Number of RHS columns*/,
+ 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
+ false /**< reinterpret the input as 3D */,
+ true /**< Flag used to broadcast the bias addition */,
+ false /**< wider accumm */,
+ ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
+ 1 /**< Multiplication factor for the width of the 1xW transposed block */,
+ 1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
+ GEMMLHSMatrixInfo(),
+ GEMMRHSMatrixInfo(),
+ 0 /**< Offset to be added to each element of the matrix A */,
+ 0 /**< Offset to be added to each element of the matrix B */),
+ GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
+ 64 /**<N Number of RHS columns*/,
+ 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
+ false /**< reinterpret the input as 3D */,
+ true /**< Flag used to broadcast the bias addition */,
+ false /**< wider accumm */,
+ ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
+ 1 /**< Multiplication factor for the width of the 1xW transposed block */,
+ 1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
+ GEMMLHSMatrixInfo(),
+ GEMMRHSMatrixInfo(),
+ 0 /**< Offset to be added to each element of the matrix A */,
+ 0 /**< Offset to be added to each element of the matrix B */),
+
+ GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
+ 64 /**<N Number of RHS columns*/,
+ 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
+ false /**< reinterpret the input as 3D */,
+ true /**< Flag used to broadcast the bias addition */,
+ false /**< wider accumm */,
+ ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
+ 1 /**< Multiplication factor for the width of the 1xW transposed block */,
+ 1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
+ GEMMLHSMatrixInfo(),
+ GEMMRHSMatrixInfo(),
+ 0 /**< Offset to be added to each element of the matrix A */,
+ 0 /**< Offset to be added to each element of the matrix B */),
+ GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
+ 64 /**<N Number of RHS columns*/,
+ 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
+ false /**< reinterpret the input as 3D */,
+ true /**< Flag used to broadcast the bias addition */,
+ false /**< wider accumm */,
+ ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
+ 1 /**< Multiplication factor for the width of the 1xW transposed block */,
+ 1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
+ GEMMLHSMatrixInfo(),
+ GEMMRHSMatrixInfo(),
+ 0 /**< Offset to be added to each element of the matrix A */,
+ 0 /**< Offset to be added to each element of the matrix B */)
+ })),
+ framework::dataset::make("Expected", { true,
+ true,
+ true,
+ false,
+ false})),
+ input0_info ,input1_info, input2_info, output_info, lhs_info, rhs_info, gemm_info, expected)
+{
+ ARM_COMPUTE_EXPECT(bool(CLGEMMMatrixMultiplyReshapedKernel::validate(&input0_info.clone()->set_is_resizable(true),
+ &input1_info.clone()->set_is_resizable(true),
+ &input2_info.clone()->set_is_resizable(true),
+ &output_info.clone()->set_is_resizable(true),1.f,1.f,
+ lhs_info,
+ rhs_info,
+ gemm_info)) == (expected && image2d_from_buffer_supported(CLKernelLibrary::get().get_device())), framework::LogLevel::ERRORS);
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::ALL,
+ combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+ m_values,
+ n_values),
+ k_values),
+ b_values),
+ m0_values_precommit),
+ n0_values_precommit),
+ k0_values_precommit),
+ v0_values_precommit),
+ h0_values_precommit),
+ i_values_lhs),
+ i_values_rhs),
+ framework::dataset::make("export_to_cl_image_rhs", true)),
+ framework::dataset::make("DataType", DataType::F16)),
+ a_values_precommit),
+ beta_values_precommit),
+ broadcast_bias_values),
+ lhs_transpose_values),
+ act_values))
+{
+ // Validate output only if the target platform supports the OpenCL cl_khr_image2d_from_buffer extension
+ if(image2d_from_buffer_supported(CLKernelLibrary::get().get_device()))
+ {
+ validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
+ }
+ else
+ {
+ ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
+ framework::ARM_COMPUTE_PRINT_INFO();
+ }
+
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+ m_values,
+ n_values),
+ k_values),
+ b_values),
+ m0_values_nightly),
+ n0_export_to_cl_image_values_nightly),
+ k0_export_to_cl_image_values_nightly),
+ v0_values_nightly),
+ h0_values_nightly),
+ i_values_lhs),
+ i_values_rhs),
+ framework::dataset::make("export_to_cl_image_rhs", true)),
+ framework::dataset::make("DataType", DataType::F16)),
+ a_values_nightly),
+ beta_values_nightly),
+ broadcast_bias_values),
+ lhs_transpose_values),
+ act_values))
+{
+ // Validate output only if the target platform supports the OpenCL cl_khr_image2d_from_buffer extension
+ if(image2d_from_buffer_supported(CLKernelLibrary::get().get_device()))
+ {
+ validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
+ }
+ else
+ {
+ ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
+ framework::ARM_COMPUTE_PRINT_INFO();
+ }
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::ALL,
+ combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+ m_w_values,
+ m_h_values),
+ n_values),
+ k_values),
+ b_values),
+ m0_values_precommit),
+ n0_values_precommit),
+ k0_values_precommit),
+ v0_values_precommit),
+ h0_values_precommit),
+ i_values_lhs),
+ i_values_rhs),
+ framework::dataset::make("export_to_cl_image_rhs", true)),
+ framework::dataset::make("DataType", DataType::F16)),
+ a_values_precommit),
+ beta_values_precommit),
+ lhs_transpose_values),
+ act_values))
+{
+ // Validate output only if the target platform supports the OpenCL cl_khr_image2d_from_buffer extension
+ if(image2d_from_buffer_supported(CLKernelLibrary::get().get_device()))
+ {
+ validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
+ }
+ else
+ {
+ ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
+ framework::ARM_COMPUTE_PRINT_INFO();
+ }
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
+ m_w_values,
+ m_h_values),
+ n_values),
+ k_values),
+ b_values),
+ m0_values_nightly),
+ n0_export_to_cl_image_values_nightly),
+ k0_export_to_cl_image_values_nightly),
+ v0_values_nightly),
+ h0_values_nightly),
+ i_values_lhs),
+ i_values_rhs),
+ framework::dataset::make("export_to_cl_image_rhs", true)),
+ framework::dataset::make("DataType", DataType::F16)),
+ a_values_nightly),
+ beta_values_nightly),
+ lhs_transpose_values),
+ act_values))
+{
+ // Validate output only if the target platform supports the OpenCL cl_khr_image2d_from_buffer extension
+ if(image2d_from_buffer_supported(CLKernelLibrary::get().get_device()))
+ {
+ validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
+ }
+ else
+ {
+ ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
+ framework::ARM_COMPUTE_PRINT_INFO();
+ }
+}
+TEST_SUITE_END() // ExportToCLImage
TEST_SUITE_END() // FP16
TEST_SUITE(MixedPrecision)
generated by cgit v1.2.1 (git 2.23.0) at 2024-04-28 20:09:53 +0000