COMPMID-1736: Fixed out-of-bound write in CLIm2Col
The issue was related to CLIm2Col when the number of input channels was less than
the number of elements processed by each thread.
The bug has been fixed in the validate_and_configure_window() function setting the correct number of elements accessed
in the output tensor.
Also fixed an issue GEMM3D when we have a single output channel
Change-Id: I094292d0c7662599c4a4c3916ec5f5821df5faef
diff --git a/tests/datasets/SmallConvolutionLayerDataset.h b/tests/datasets/SmallConvolutionLayerDataset.h
index bbfc760..df9196f 100644
--- a/tests/datasets/SmallConvolutionLayerDataset.h
+++ b/tests/datasets/SmallConvolutionLayerDataset.h
@@ -139,6 +139,7 @@
{
add_config(TensorShape(224U, 224U, 3U), TensorShape(3U, 3U, 3U, 32U), TensorShape(32U), TensorShape(112U, 112U, 32U),
PadStrideInfo(2, 2, /*left*/ 0, /*right*/ 1, /*top*/ 0, /*bottom*/ 1, DimensionRoundingType::FLOOR));
+
// Batch size 1
add_config(TensorShape(23U, 27U, 5U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(11U, 25U, 21U), PadStrideInfo(2, 1, 0, 0));
add_config(TensorShape(33U, 27U, 7U), TensorShape(5U, 5U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U), PadStrideInfo(3, 2, 1, 0));
@@ -146,6 +147,7 @@
add_config(TensorShape(23U, 27U, 5U), TensorShape(3U, 1U, 5U, 21U), TensorShape(21U), TensorShape(11U, 27U, 21U), PadStrideInfo(2, 1, 0, 0));
add_config(TensorShape(33U, 27U, 7U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 11U, 16U), PadStrideInfo(3, 2, 1, 0));
add_config(TensorShape(17U, 31U, 2U), TensorShape(5U, 3U, 2U, 19U), TensorShape(19U), TensorShape(15U, 16U, 19U), PadStrideInfo(1, 2, 1, 1));
+ add_config(TensorShape(3U, 3U, 1U), TensorShape(2U, 2U, 1U, 11U), TensorShape(11U), TensorShape(2U, 2U, 11U), PadStrideInfo(1, 1, 0, 0));
// Batch size 4
add_config(TensorShape(23U, 27U, 5U, 4U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(11U, 25U, 21U, 4U), PadStrideInfo(2, 1, 0, 0));
add_config(TensorShape(33U, 27U, 7U, 4U), TensorShape(5U, 5U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 4U), PadStrideInfo(3, 2, 1, 0));
@@ -164,9 +166,26 @@
add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 3, 0, 2, DimensionRoundingType::FLOOR));
add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(10U, 11U, 16U, 5U), PadStrideInfo(3, 2, 1, 0, 1, 0, DimensionRoundingType::FLOOR));
add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(10U, 11U, 16U, 5U), PadStrideInfo(3, 2, 0, 1, 0, 1, DimensionRoundingType::FLOOR));
- // TODO (micgio01) - COMPMID-1604: investigate issue in GLES and re-enable the following dataset
- // Single output channel
- //add_config(TensorShape(5U, 4U, 3U, 2U), TensorShape(4U, 4U, 3U, 1U), TensorShape(1U), TensorShape(2U, 1U, 1U, 2U), PadStrideInfo(1, 1, 0, 0, 0, 0, DimensionRoundingType::FLOOR));
+
+ add_config(TensorShape(5U, 4U, 3U, 2U), TensorShape(4U, 4U, 3U, 1U), TensorShape(1U), TensorShape(2U, 1U, 1U, 2U), PadStrideInfo(1, 1, 0, 0, 0, 0, DimensionRoundingType::FLOOR));
+ }
+};
+
+// TODO (COMPMID-1749)
+class SmallConvolutionLayerReducedDataset final : public ConvolutionLayerDataset
+{
+public:
+ SmallConvolutionLayerReducedDataset()
+ {
+ // Batch size 1
+ add_config(TensorShape(23U, 27U, 5U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(11U, 25U, 21U), PadStrideInfo(2, 1, 0, 0));
+ add_config(TensorShape(33U, 27U, 7U), TensorShape(5U, 5U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U), PadStrideInfo(3, 2, 1, 0));
+ add_config(TensorShape(17U, 31U, 2U), TensorShape(5U, 5U, 2U, 19U), TensorShape(19U), TensorShape(15U, 15U, 19U), PadStrideInfo(1, 2, 1, 1));
+
+ // Asymmetric padding
+ add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 2, 0, DimensionRoundingType::FLOOR));
+ add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 0, 2, DimensionRoundingType::FLOOR));
+ add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 2, 1, 2, 0, DimensionRoundingType::FLOOR));
}
};
diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp
index 0274bed..5f10b4b 100644
--- a/tests/validation/CL/ConvolutionLayer.cpp
+++ b/tests/validation/CL/ConvolutionLayer.cpp
@@ -268,11 +268,18 @@
TEST_SUITE(Quantized)
TEST_SUITE(QASYMM8)
+const auto QuantizationData = framework::dataset::make("QuantizationInfo",
+{
+ QuantizationInfo(0.5f, 10),
+ QuantizationInfo(0.3f, 3),
+ QuantizationInfo(1.f, 10),
+});
+
FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(),
framework::dataset::make("ReshapeWeights", { true })),
framework::dataset::make("DataType", DataType::QASYMM8)),
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
- framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })),
+ QuantizationData),
QuantizedActivationFunctionsDataset))
{
// Validate output
@@ -282,7 +289,7 @@
framework::dataset::make("ReshapeWeights", { true })),
framework::dataset::make("DataType", DataType::QASYMM8)),
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
- framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 0) })),
+ QuantizationData),
QuantizedActivationFunctionsDataset))
{
// Validate output
diff --git a/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp b/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp
index 2961dc9..85a477b 100644
--- a/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp
+++ b/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp
@@ -65,7 +65,7 @@
TEST_SUITE(GC)
TEST_SUITE(ConvolutionLayer)
-DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallConvolutionLayerDataset(), datasets::LargeConvolutionLayerDataset()),
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallConvolutionLayerReducedDataset(), datasets::LargeConvolutionLayerDataset()),
CNNDataTypes),
ActivationFunctionsDataset),
input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info)
@@ -114,7 +114,7 @@
TEST_SUITE(Float)
TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(RunSmall, GCConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(),
+FIXTURE_DATA_TEST_CASE(RunSmall, GCConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(),
framework::dataset::make("ReshapeWeights", { true })),
framework::dataset::make("DataType",
DataType::F16)),
@@ -139,7 +139,7 @@
TEST_SUITE_END()
TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(RunSmall, GCConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(),
+FIXTURE_DATA_TEST_CASE(RunSmall, GCConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(),
framework::dataset::make("ReshapeWeights", { true })),
framework::dataset::make("DataType", DataType::F32)),
framework::dataset::make("DataLayout",
diff --git a/tests/validation/fixtures/GEMMFixture.h b/tests/validation/fixtures/GEMMFixture.h
index 255b12c..74205e2 100644
--- a/tests/validation/fixtures/GEMMFixture.h
+++ b/tests/validation/fixtures/GEMMFixture.h
@@ -85,9 +85,9 @@
// Create and configure function
FunctionType gemm;
// The GEMMinfo includes the values of the depth in case of reinterpreted 3d output.
- // If the output shape has the same number of dimensions of the input the method called is a 2D matrix multiplication (depth_output_reinterpreted_as_3D = 1),
+ // If the output shape has the same number of dimensions of the input the method called is a 2D matrix multiplication (depth_output_reinterpreted_as_3D = 0),
// in the other case we have to use the reinterpreted version of GEMM (depth_output_reinterpreted_as_3D = depth of the 3D output).
- gemm.configure(&a, &b, &c, &dst, alpha, beta, GEMMInfo(false, false, false, (reinterpret_ouput_as_3d ? output_shape[2] : 1), reinterpret_input_as_3d));
+ gemm.configure(&a, &b, &c, &dst, alpha, beta, GEMMInfo(false, false, false, (reinterpret_ouput_as_3d ? output_shape[2] : 0), reinterpret_input_as_3d));
ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(c.info()->is_resizable(), framework::LogLevel::ERRORS);
diff --git a/tests/validation/fixtures/GEMMLowpFixture.h b/tests/validation/fixtures/GEMMLowpFixture.h
index b61b4ec..96debe0 100644
--- a/tests/validation/fixtures/GEMMLowpFixture.h
+++ b/tests/validation/fixtures/GEMMLowpFixture.h
@@ -76,7 +76,7 @@
// The GEMMinfo includes the values of the depth in case of reinterpreted 3d input/output
FunctionType gemmlowp;
// TODO (COMPMID-1672) - Extending the test to validate add bias in offset contribution
- gemmlowp.configure(&a, &b, nullptr, &c, GEMMInfo(false, false, false, (reinterpret_output_as_3d ? shape_c[2] : 1), reinterpret_input_as_3d));
+ gemmlowp.configure(&a, &b, nullptr, &c, GEMMInfo(false, false, false, (reinterpret_output_as_3d ? shape_c[2] : 0), reinterpret_input_as_3d));
ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);