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

5 files changed, 37 insertions, 11 deletions

diff --git a/tests/datasets/SmallConvolutionLayerDataset.h b/tests/datasets/SmallConvolutionLayerDataset.h
index bbfc760bf3..df9196fb77 100644
--- a/tests/datasets/SmallConvolutionLayerDataset.h
+++ b/tests/datasets/SmallConvolutionLayerDataset.h
@@ -139,6 +139,7 @@ public:
     {
         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 @@ public:
         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 @@ public:
         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 0274bed977..5f10b4b9bc 100644
--- a/tests/validation/CL/ConvolutionLayer.cpp
+++ b/tests/validation/CL/ConvolutionLayer.cpp
@@ -268,11 +268,18 @@ const auto QuantizedActivationFunctionsDataset = framework::dataset::make("Activ
 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 @@ FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>
                        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 2961dc9519..85a477b293 100644
--- a/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp
+++ b/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp
@@ -65,7 +65,7 @@ const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo
 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 @@ using GCConvolutionLayerFixture = ConvolutionValidationFixture<GCTensor, GCAcces
 
 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 @@ FIXTURE_DATA_TEST_CASE(RunLarge, GCConvolutionLayerFixture<half>, framework::Dat
 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 255b12c0ed..74205e25d4 100644
--- a/tests/validation/fixtures/GEMMFixture.h
+++ b/tests/validation/fixtures/GEMMFixture.h
@@ -85,9 +85,9 @@ protected:
         // 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 b61b4eca38..96debe0eec 100644
--- a/tests/validation/fixtures/GEMMLowpFixture.h
+++ b/tests/validation/fixtures/GEMMLowpFixture.h
@@ -76,7 +76,7 @@ protected:
         // 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);