Fix CL DirectConvolutionLayer validate tests
* Add missing activation infos
* Remove faulty test "Shrink window"
* Split the tests based on data layout
* Fix ClDirectConv2dKernel::validate logic
Fused activation in NCHW is not supported at all
Resolves: COMPMID-5801
Change-Id: I64dfbd24b77bb02fb4a88b73d5ef84676d85b4fd
Signed-off-by: SiCong Li <sicong.li@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8899
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp b/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp
index b66163c..5f882e3 100644
--- a/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp
+++ b/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp
@@ -73,7 +73,7 @@
ARM_COMPUTE_RETURN_ERROR_ON_MSG((weights->dimension(width_idx) == 1) && std::get<0>(conv_info.stride()) > 3, "Strides larger than 3 not supported for 1x1 convolution.");
ARM_COMPUTE_RETURN_ERROR_ON_MSG((weights->dimension(width_idx) == 3 || weights->dimension(width_idx) == 5 || weights->dimension(width_idx) == 9) && std::get<0>(conv_info.stride()) > 2,
"Strides larger than 2 not supported for 3x3, 5x5, 9x9 convolution.");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(!is_data_type_float(src->data_type()) && act_info.enabled(), "Activation supported only for floating point and NHWC.");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(act_info.enabled(), "Fused activation is not supported for NCHW layout");
if(is_data_type_quantized(src->data_type()))
{
@@ -89,6 +89,7 @@
if(data_layout == DataLayout::NHWC)
{
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(act_info.enabled() && !is_data_type_float(src->data_type()), "Fused activation in NHWC is only supported for floating point.");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(desc.m0 <= 0 || desc.m0 > 8, "M0 can only be greater than 0 and less than or equal to 8");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(desc.n0 != 1 && desc.n0 != 2 && desc.n0 != 3 && desc.n0 != 4 && desc.n0 != 8 && desc.n0 != 16,
"N0 can only be: 1, 2, 3, 4, 8, and 16");
diff --git a/tests/validation/CL/DirectConvolutionLayer.cpp b/tests/validation/CL/DirectConvolutionLayer.cpp
index f026bfe..512c2ca 100644
--- a/tests/validation/CL/DirectConvolutionLayer.cpp
+++ b/tests/validation/CL/DirectConvolutionLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2022 Arm Limited.
+ * Copyright (c) 2017-2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -185,52 +185,36 @@
// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(
- framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data type input/weights
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching input feature maps
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported kernel width
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Non-rectangular weights dimensions
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid: Mismatching data type input/weights
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid: Mismatching input feature maps
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid weights dimensions
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid stride
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid biases size
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid biases dimensions
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported biases size
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported biases dimensions
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid output size
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Window shrink
TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32),
}),
framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F16),
TensorInfo(TensorShape(3U, 3U, 3U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(11U, 11U, 2U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(5U, 3U, 2U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(3U, 3U, 2U, 4U, 3U), 1, DataType::F32),
TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(1U, 1U, 2U, 4U), 1, DataType::F32),
})),
framework::dataset::make("BiasesInfo",{ TensorInfo(TensorShape(4U), 1, DataType::F32),
TensorInfo(TensorShape(4U), 1, DataType::F32),
TensorInfo(TensorShape(4U), 1, DataType::F32),
- TensorInfo(TensorShape(4U), 1, DataType::F32),
- TensorInfo(TensorShape(4U), 1, DataType::F32),
- TensorInfo(TensorShape(4U), 1, DataType::F32),
TensorInfo(TensorShape(3U), 1, DataType::F32),
TensorInfo(TensorShape(4U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(4U), 1, DataType::F32),
TensorInfo(TensorShape(4U), 1, DataType::F32),
- TensorInfo(TensorShape(4U), 1, DataType::F32),
})),
framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(26U, 11U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 16U, 4U), 1, DataType::F32),
})),
framework::dataset::make("ConvInfo", { PadStrideInfo(1, 1, 0, 0),
@@ -238,23 +222,27 @@
PadStrideInfo(1, 1, 0, 0),
PadStrideInfo(1, 1, 0, 0),
PadStrideInfo(1, 1, 0, 0),
- PadStrideInfo(3, 3, 0, 0),
- PadStrideInfo(1, 1, 0, 0),
- PadStrideInfo(1, 1, 0, 0),
- PadStrideInfo(1, 1, 0, 0),
PadStrideInfo(1, 1, 0, 0),
PadStrideInfo(1, 1, 0, 0),
})),
framework::dataset::make("ActivationInfo",
{
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
})),
- framework::dataset::make("Expected", { false, false, false, false, false, false, false, false, false, false, true })),
+ framework::dataset::make("Expected", { false, false, false, false, false, false, true })),
input_info, weights_info, biases_info, output_info, conv_info, act_info, expected)
{
bool is_valid = bool(CLDirectConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, act_info));
ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
}
+// clang-format on
+// *INDENT-ON*
template <typename T>
using CLDirectConvolutionLayerFixture = DirectConvolutionValidationFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>;
@@ -270,6 +258,46 @@
using CLDirectConvolutionValidationWithTensorShapesQuantizedFixture = DirectConvolutionValidationWithTensorShapesQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>;
TEST_SUITE(NHWC)
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputInfo", {
+ 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, 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),
+ })),
+ framework::dataset::make("OutputInfo",{
+ TensorInfo(TensorShape(4U, 15U, 1U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(4U, 23U, 11U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(4U, 9U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ })),
+ framework::dataset::make("ConvInfo", {
+ PadStrideInfo(1, 1, 0, 0),
+ PadStrideInfo(1, 1, 0, 0),
+ PadStrideInfo(3, 3, 0, 0),
+ })),
+ framework::dataset::make("ActivationInfo",
+{
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+})),
+ framework::dataset::make("Expected", { true, true, true })),
+ input_info, weights_info, biases_info, output_info, conv_info, act_info, expected)
+{
+ bool is_valid = bool(CLDirectConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, act_info));
+ ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT,
combine(combine(combine(zip(zip(zip(zip(zip(zip(
@@ -479,9 +507,48 @@
TEST_SUITE_END() // Quantized
TEST_SUITE_END() // NHWC
+TEST_SUITE(NCHW)
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputInfo", {
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, DataLayout::NCHW), // Unsupported kernel width
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, DataLayout::NCHW), // Non-rectangular weights dimensions are unsupported
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, DataLayout::NCHW) // Unsupported stride
+ }),
+ framework::dataset::make("WeightsInfo",{
+ TensorInfo(TensorShape(11U, 11U, 2U, 4U), 1, DataType::F32, DataLayout::NCHW),
+ TensorInfo(TensorShape(5U, 3U, 2U, 4U), 1, DataType::F32, DataLayout::NCHW),
+ TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32, DataLayout::NCHW)
+ })),
+ framework::dataset::make("BiasesInfo",{
+ TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NCHW),
+ TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NCHW),
+ TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NCHW)
+ })),
+ framework::dataset::make("OutputInfo",{
+ TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32, DataLayout::NCHW),
+ TensorInfo(TensorShape(23U, 11U, 4U), 1, DataType::F32, DataLayout::NCHW),
+ TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32, DataLayout::NCHW)
+ })),
+ framework::dataset::make("ConvInfo", {
+ PadStrideInfo(1, 1, 0, 0),
+ PadStrideInfo(1, 1, 0, 0),
+ PadStrideInfo(3, 3, 0, 0)
+ })),
+ framework::dataset::make("ActivationInfo",
+{
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
+})),
+ framework::dataset::make("Expected", { false, false, false})),
+ input_info, weights_info, biases_info, output_info, conv_info, act_info, expected)
+{
+ bool is_valid = bool(CLDirectConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, act_info));
+ ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
// clang-format on
// *INDENT-ON*
-TEST_SUITE(NCHW)
+
TEST_SUITE(Float)
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit, framework::dataset::make("DataType", DataType::F16)),
diff --git a/tests/validation/NEON/DirectConvolutionLayer.cpp b/tests/validation/NEON/DirectConvolutionLayer.cpp
index 0f4c6bb..73c1a5c 100644
--- a/tests/validation/NEON/DirectConvolutionLayer.cpp
+++ b/tests/validation/NEON/DirectConvolutionLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2022 Arm Limited.
+ * Copyright (c) 2017-2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -220,14 +220,14 @@
// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(
- framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data type input/weights
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching input feature maps
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid: Mismatching data type input/weights
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid: Mismatching input feature maps
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported kernel width
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Non-rectangular weights dimensions
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported non-rectangular weights dimensions
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid weights dimensions
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid stride
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid biases size
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid biases dimensions
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported stride
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported biases size
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported biases dimensions
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid output size
}),
framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F16),