COMPMID-754: Add validation to LocallyConnected and NEDeconv layers
Change-Id: Ifed8713f4d7f1315af684b30d11323db2b533f10
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/121783
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
diff --git a/tests/validation/CL/LocallyConnected.cpp b/tests/validation/CL/LocallyConnected.cpp
index 05cab29..de79d60 100644
--- a/tests/validation/CL/LocallyConnected.cpp
+++ b/tests/validation/CL/LocallyConnected.cpp
@@ -47,6 +47,67 @@
TEST_SUITE(CL)
TEST_SUITE(LocallyConnected)
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0), // Mismatching data type input/weights
+ TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0), // Mismatching data type input/bias
+ TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0), // Mismatching data type input/output
+ TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0), // Mismatching shape input/weights
+ TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0), // Mismatching shape input/bias
+ TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0), // Mismatching shape input/output
+ TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0), // Asymmetric padding
+ TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0)
+ }),
+ framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 275U), 1, DataType::F16, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 274U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 275U), 1, DataType::F32, 0)
+ })),
+ framework::dataset::make("BiasInfo", { TensorInfo(TensorShape(21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U, 275U), 1, DataType::F16, 0),
+ TensorInfo(TensorShape(21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U, 274U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U, 275U), 1, DataType::F32, 0)
+ })),
+ framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F16, 0),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 25U, 22U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0)
+ })),
+ framework::dataset::make("PadStride", { PadStrideInfo(2, 1, 0, 0),
+ PadStrideInfo(2, 1, 0, 0),
+ PadStrideInfo(2, 1, 0, 0),
+ PadStrideInfo(2, 1, 0, 0),
+ PadStrideInfo(2, 1, 0, 0),
+ PadStrideInfo(2, 1, 0, 0),
+ PadStrideInfo(2, 1, 1, 0, 0, 0, DimensionRoundingType::FLOOR),
+ PadStrideInfo(2, 1, 0, 0)
+ })),
+ framework::dataset::make("Expected", { false, false, false, false, false, false, false, true })),
+ input_info, weights_info, bias_info, output_info, conv_info, expected)
+{
+ bool is_valid = bool(CLLocallyConnectedLayer::validate(&input_info.clone()->set_is_resizable(false),
+ &weights_info.clone()->set_is_resizable(false),
+ &bias_info.clone()->set_is_resizable(false),
+ &output_info.clone()->set_is_resizable(false),
+ conv_info));
+ ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallLocallyConnectedDataset(), datasets::LargeLocallyConnectedDataset()),
framework::dataset::make("DataType", DataType::F32)),
src_shape, weights_shape, bias_shape, dst_shape, info, data_type)
diff --git a/tests/validation/NEON/DeconvolutionLayer.cpp b/tests/validation/NEON/DeconvolutionLayer.cpp
index 566b75a..3bb6d6f 100644
--- a/tests/validation/NEON/DeconvolutionLayer.cpp
+++ b/tests/validation/NEON/DeconvolutionLayer.cpp
@@ -58,6 +58,106 @@
TEST_SUITE(NEON)
TEST_SUITE(DeconvolutionLayer)
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, (combine(datasets::SmallDeconvolutionShapes(), framework::dataset::make("DataType", DataType::F32))),
+ input_shape, data_type)
+{
+ // Create shapes
+ const unsigned int kernel_size_x = 3;
+ const unsigned int kernel_size_y = 3;
+ const unsigned int num_kernels = 1;
+ const TensorShape weights_shape(kernel_size_x, kernel_size_y, input_shape.z(), num_kernels);
+ const TensorShape bias_shape(num_kernels);
+ auto out_dim = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, 1, 1, 0, 0, 1, 1);
+ TensorShape output_shape = deconvolution_output_shape(out_dim, input_shape, weights_shape);
+
+ // Create tensors
+ Tensor src = create_tensor<Tensor>(input_shape, data_type, 1);
+ Tensor weights = create_tensor<Tensor>(weights_shape, data_type, 1);
+ Tensor bias = create_tensor<Tensor>(bias_shape, data_type, 1);
+ Tensor dst = create_tensor<Tensor>(output_shape, data_type, 1);
+
+ ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(weights.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
+ NEDeconvolutionLayer deconv;
+ deconv.configure(&src, &weights, &bias, &dst, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL), 0, 0);
+
+ // Validate valid region
+ const ValidRegion src_valid_region = shape_to_valid_region(input_shape);
+ const ValidRegion weights_valid_region = shape_to_valid_region(weights_shape);
+ const ValidRegion bias_valid_region = shape_to_valid_region(bias_shape);
+ const ValidRegion dst_valid_region = shape_to_valid_region(output_shape);
+
+ validate(src.info()->valid_region(), src_valid_region);
+ validate(weights.info()->valid_region(), weights_valid_region);
+ validate(bias.info()->valid_region(), bias_valid_region);
+ validate(dst.info()->valid_region(), dst_valid_region);
+}
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching data type
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Invalid weights shape
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 4), // Non supported data type
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 11), // Invalid bias shape
+ TensorInfo(TensorShape(13U, 11U, 4U, 3U), 1, DataType::F32, 0), // Window shrink
+ TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32, 0),
+ }),
+ framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F16, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::QS8, 5),
+ TensorInfo(TensorShape(3U, 2U, 2U, 2U), 1, DataType::F32, 11),
+ TensorInfo(TensorShape(3U, 3U, 4U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(1U, 1U, 2U, 4U), 1, DataType::F32, 0),
+ })),
+ framework::dataset::make("BiasInfo", { TensorInfo(TensorShape(1U), 1, DataType::F16, 0),
+ TensorInfo(TensorShape(1U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(1U), 1, DataType::F32, 5),
+ TensorInfo(TensorShape(25U, 11U), 1, DataType::F32, 11),
+ TensorInfo(TensorShape(1U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(4U), 1, DataType::F32, 0),
+ })),
+ framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F16, 0),
+ TensorInfo(TensorShape(25U, 10U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 5),
+ TensorInfo(TensorShape(13U, 13U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 9U, 1U, 3U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(32U, 16U, 4U), 1, DataType::F32, 0),
+ })),
+ framework::dataset::make("PadStrideInfo", { PadStrideInfo(1, 1, 0, 0),
+ PadStrideInfo(1, 1, 0, 0),
+ PadStrideInfo(1, 1, 0, 0),
+ PadStrideInfo(1, 1, 0, 0),
+ PadStrideInfo(1, 1, 1, 1),
+ PadStrideInfo(1, 1, 0, 0),
+ })),
+ framework::dataset::make("ax", { 1U,
+ 1U,
+ 1U,
+ 1U,
+ 0U,
+ 0U,
+ })),
+ framework::dataset::make("ay", { 1U,
+ 1U,
+ 1U,
+ 1U,
+ 0U,
+ 0U,
+ })),
+ framework::dataset::make("Expected", { false, false, false, false, false, true })),
+ input_info, weights_info, bias_info, output_info, pad_info, ax, ay, expected)
+{
+ bool is_valid = bool(NEDeconvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &bias_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), pad_info, ax, ay));
+ ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
template <typename T>
using NEDeconvolutionLayerFixture4x4 = DeconvolutionValidationFixture<Tensor, Accessor, NEDeconvolutionLayer, T, 4, 4>;
diff --git a/tests/validation/NEON/LocallyConnected.cpp b/tests/validation/NEON/LocallyConnected.cpp
index 56430d9..b00f274 100644
--- a/tests/validation/NEON/LocallyConnected.cpp
+++ b/tests/validation/NEON/LocallyConnected.cpp
@@ -48,6 +48,67 @@
TEST_SUITE(NEON)
TEST_SUITE(LocallyConnected)
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0), // Mismatching data type input/weights
+ TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0), // Mismatching data type input/bias
+ TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0), // Mismatching data type input/output
+ TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0), // Mismatching shape input/weights
+ TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0), // Mismatching shape input/bias
+ TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0), // Mismatching shape input/output
+ TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0), // Asymmetric padding
+ TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32, 0)
+ }),
+ framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 275U), 1, DataType::F16, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 274U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U, 275U), 1, DataType::F32, 0)
+ })),
+ framework::dataset::make("BiasInfo", { TensorInfo(TensorShape(21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U, 275U), 1, DataType::F16, 0),
+ TensorInfo(TensorShape(21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U, 274U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U, 275U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U, 275U), 1, DataType::F32, 0)
+ })),
+ framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F16, 0),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 25U, 22U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0)
+ })),
+ framework::dataset::make("PadStride", { PadStrideInfo(2, 1, 0, 0),
+ PadStrideInfo(2, 1, 0, 0),
+ PadStrideInfo(2, 1, 0, 0),
+ PadStrideInfo(2, 1, 0, 0),
+ PadStrideInfo(2, 1, 0, 0),
+ PadStrideInfo(2, 1, 0, 0),
+ PadStrideInfo(2, 1, 1, 0, 0, 0, DimensionRoundingType::FLOOR),
+ PadStrideInfo(2, 1, 0, 0)
+ })),
+ framework::dataset::make("Expected", { false, false, false, false, false, false, false, true })),
+ input_info, weights_info, bias_info, output_info, conv_info, expected)
+{
+ bool is_valid = bool(NELocallyConnectedLayer::validate(&input_info.clone()->set_is_resizable(false),
+ &weights_info.clone()->set_is_resizable(false),
+ &bias_info.clone()->set_is_resizable(false),
+ &output_info.clone()->set_is_resizable(false),
+ conv_info));
+ ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallLocallyConnectedDataset(), datasets::LargeLocallyConnectedDataset()),
framework::dataset::make("DataType", DataType::F32)),
src_shape, weights_shape, bias_shape, dst_shape, info, data_type)