aboutsummaryrefslogtreecommitdiff
path: root/tests/validation/dynamic_fusion/gpu/cl/DirectConv2d.cpp
diff options
context:
space:
mode:
Diffstat (limited to 'tests/validation/dynamic_fusion/gpu/cl/DirectConv2d.cpp')
-rw-r--r--tests/validation/dynamic_fusion/gpu/cl/DirectConv2d.cpp260
1 files changed, 260 insertions, 0 deletions
diff --git a/tests/validation/dynamic_fusion/gpu/cl/DirectConv2d.cpp b/tests/validation/dynamic_fusion/gpu/cl/DirectConv2d.cpp
new file mode 100644
index 0000000000..b843764786
--- /dev/null
+++ b/tests/validation/dynamic_fusion/gpu/cl/DirectConv2d.cpp
@@ -0,0 +1,260 @@
+/*
+ * Copyright (c) 2022-2024 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 "tests/AssetsLibrary.h"
+#include "tests/CL/CLAccessor.h"
+#include "tests/datasets/SmallConvolutionLayerDataset.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/framework/Fixture.h"
+#include "tests/framework/Macros.h"
+#include "tests/validation/fixtures/dynamic_fusion/gpu/cl/DirectConv2dFixture.h"
+#include "tests/validation/reference/ConvolutionLayer.h"
+#include "tests/validation/Validation.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+/** Tolerances from tests/validation/CL/DirectConvolutionLayer.cpp
+ */
+RelativeTolerance<float> tolerance_f32(
+ 0.05f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
+RelativeTolerance<half_float::half> tolerance_f16(half_float::half(
+ 0.2)); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
+constexpr float abs_tolerance_f32(0.0001f); /**< Absolute tolerance for FP32 tests*/
+constexpr float tolerance_num = 0.07f; /**< Tolerance number */
+} // namespace
+
+TEST_SUITE(CL)
+TEST_SUITE(DYNAMIC_FUSION)
+/** Synced with tests/validation/CL/ConvolutionLayer.cpp
+ *
+ * Difference | Why the difference
+ * f32 tolerance here is smaller | To use the same tolerance as that of DirectConv2d; lowering tolerance is safe
+ * No quantized tests | Not supported yet
+ * No grouped CNN tests | Not supported yet
+ * No mixed layout tests | Not needed; only NHWC is supported
+ * No activation | Not needed in fusion
+ * No ValidateConvolutionMethod | Only a single method (direct conv2d) is supported
+ * No ReshapeWeights = true tests | Not applicable yet. This parameter only concerns gemm-based conv2d
+ * No RunSmallWithPadding tests | Padding is removed
+ *
+ */
+TEST_SUITE(CONV2D)
+
+template <typename T>
+using DynamicFusionGpuConv2dFixture = DynamicFusionGpuConv2dValidationFixture<CLTensor, CLAccessor, GpuConv2d, T>;
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ DynamicFusionGpuConv2dFixture<float>,
+ framework::DatasetMode::ALL,
+ combine(combine(combine(datasets::SmallConvolutionLayerDataset(),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", {DataLayout::NHWC})),
+ framework::dataset::make("QuantizationInfo", QuantizationInfo())))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+TEST_SUITE_END() // FP32
+
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ DynamicFusionGpuConv2dFixture<half>,
+ framework::DatasetMode::ALL,
+ combine(combine(combine(datasets::SmallConvolutionLayerDataset(),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", {DataLayout::NHWC})),
+ framework::dataset::make("QuantizationInfo", QuantizationInfo())))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
+}
+TEST_SUITE_END() // FP16
+
+// Tests for specific conv2d methods
+/** Synced with tests/validation/CL/DirectConvolutionLayer.cpp
+ *
+ * Difference | Why the difference
+ * No quantized tests | Not supported yet
+ * No Invalid output size test | Not applicable. Output is removed from the interface
+ * No mixed layout/NCHW tests | Not needed; only NHWC is supported
+ * No activation tests | Not needed in fusion
+ */
+TEST_SUITE(DIRECT_CONV2D)
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid: Mismatching data type input/weights
+ TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid: Mismatching input feature maps
+ TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid weights dimensions
+ TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Unsupported biases size
+ TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Unsupported biases dimensions
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, DataLayout::NCHW), // Unsupported data layout: NCHW
+ TensorInfo(TensorShape(2U, 32U, 16U), 1, DataType::QASYMM8, DataLayout::NHWC), // Unsupported data type: quantized
+ TensorInfo(TensorShape(2U, 32U, 16U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Arbitrary weight sizes for NHWC are supported
+ TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Non-rectangular weights dimensions for NHWC are supported
+ TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Strides > 2 for any kernel sizes for NHWC are supported
+ }),
+ framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(2U, 3U, 3U, 4U), 1, DataType::F16, DataLayout::NHWC),
+ TensorInfo(TensorShape(3U, 3U, 3U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 3U, 3U, 4U, 3U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 3U, 3U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 3U, 3U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32, DataLayout::NCHW),
+ TensorInfo(TensorShape(2U, 1U, 1U, 4U), 1, DataType::QASYMM8, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 1U, 1U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 13U, 13U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 5U, 3U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 3U, 3U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ })),
+ framework::dataset::make("BiasesInfo",{ TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(3U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(4U, 2U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(25U), 1, DataType::F32, DataLayout::NCHW),
+ TensorInfo(TensorShape(4U), 1, DataType::QASYMM8, DataLayout::NHWC),
+ TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC),
+ })),
+ framework::dataset::make("Conv2dAttributes", {
+ Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}),
+ Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}),
+ Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}),
+ Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}),
+ Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}),
+ Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}),
+ Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}),
+ Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}),
+ Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}),
+ Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}),
+ Conv2dAttributes().stride({3, 3}).pad({0, 0, 0, 0}),
+ })),
+ framework::dataset::make("Expected", { false, false, false, false, false, false, false, true, true, true, true })),
+ input_info, weights_info, biases_info, conv2d_attrs, expected)
+{
+ auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
+ auto context = GpuWorkloadContext{ &cl_compile_ctx };
+ GpuWorkloadSketch sketch{ &context };
+
+ const ITensorInfo* sketch_input_info = context.create_tensor_info(input_info);
+ const ITensorInfo* sketch_weights_info = context.create_tensor_info(weights_info);
+ const ITensorInfo* sketch_biases_info = context.create_tensor_info(biases_info);
+ bool is_valid = bool(GpuConv2d::validate_op(sketch, sketch_input_info, sketch_weights_info, sketch_biases_info, conv2d_attrs));
+ ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+template <typename T>
+using DynamicFusionGpuDirectConv2dFixture = DynamicFusionDirectConv2dValidationFixture<CLTensor, CLAccessor, GpuConv2d, T>;
+
+TEST_SUITE(FP16)
+/// TODO: COMPMID-6877: Once the issue in Conv2d is resolved, re-enable these
+FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuDirectConv2dFixture<half>, framework::DatasetMode::DISABLED,
+ combine(combine(combine(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(27U, 13U, 23U),
+ TensorShape(19U, 5U, 16U, 4U),
+ TensorShape(13U, 5U, 17U, 2U),
+ TensorShape(32U, 37U, 13U) } ),
+ framework::dataset::make("StrideX", { 1, 3, 1, 1 })),
+ framework::dataset::make("StrideY", { 1, 3, 2, 1 })),
+ framework::dataset::make("PadX", { 1, 3, 0, 4 })),
+ framework::dataset::make("PadY", { 1, 3, 0, 4 })),
+ framework::dataset::make("KernelSize", { 3, 8, 1, 9 })),
+ framework::dataset::make("NumKernels", { 17, 3, 1, 19 })),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuDirectConv2dFixture<half>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(800U, 800U, 3U) } ),
+ framework::dataset::make("StrideX", { 1 })),
+ framework::dataset::make("StrideY", { 1 })),
+ framework::dataset::make("PadX", { 1 })),
+ framework::dataset::make("PadY", { 1 })),
+ framework::dataset::make("KernelSize", { 9 })),
+ framework::dataset::make("NumKernels", { 3 })),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
+}
+
+TEST_SUITE_END() // FP16
+
+TEST_SUITE(FP32)
+/// TODO: COMPMID-6877: Once the issue in Conv2d is resolved, re-enable these
+FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuDirectConv2dFixture<float>, framework::DatasetMode::DISABLED,
+ combine(combine(combine(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(27U, 13U, 23U),
+ TensorShape(19U, 5U, 16U, 4U),
+ TensorShape(13U, 5U, 17U, 2U),
+ TensorShape(32U, 37U, 13U) } ),
+ framework::dataset::make("StrideX", { 1, 3, 1, 1 })),
+ framework::dataset::make("StrideY", { 1, 3, 2, 1 })),
+ framework::dataset::make("PadX", { 1, 3, 0, 4 })),
+ framework::dataset::make("PadY", { 1, 3, 0, 4 })),
+ framework::dataset::make("KernelSize", { 3, 8, 1, 9 })),
+ framework::dataset::make("NumKernels", { 17, 3, 1, 19 })),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f32, 0.0, abs_tolerance_f32);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuDirectConv2dFixture<float>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(800U, 800U, 3U) } ),
+ framework::dataset::make("StrideX", { 1 })),
+ framework::dataset::make("StrideY", { 1 })),
+ framework::dataset::make("PadX", { 1 })),
+ framework::dataset::make("PadY", { 1 })),
+ framework::dataset::make("KernelSize", { 9 })),
+ framework::dataset::make("NumKernels", { 3 })),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f32, 0.0, abs_tolerance_f32);
+}
+// clang-format on
+// *INDENT-ON*
+
+TEST_SUITE_END() // FP32
+TEST_SUITE_END() // DIRECT_CONV2D
+TEST_SUITE_END() // CONV2D
+TEST_SUITE_END() // DYNAMIC_FUSION
+TEST_SUITE_END() // CL
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-03 15:20:02 +0000