COMPMID-2074: Fix WidthConcatenate and HeightConcatenate validate tests

Change-Id: I14132883047d7df478e8e30917cb8bbaadd93be7
Signed-off-by: Usama Arif <usama.arif@arm.com>
Reviewed-on: https://review.mlplatform.org/c/883
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

3 files changed, 27 insertions, 15 deletions

diff --git a/tests/validation/CL/WidthConcatenateLayer.cpp b/tests/validation/CL/WidthConcatenateLayer.cpp
index 493320b9ad..0ca6d72bff 100644
--- a/tests/validation/CL/WidthConcatenateLayer.cpp
+++ b/tests/validation/CL/WidthConcatenateLayer.cpp
@@ -47,19 +47,24 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
               framework::dataset::make("InputInfo1", {  TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32), // Mismatching data type input/output
                                                         TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32), // Mismatching y dimension
                                                         TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32), // Mismatching total width
-                                                        TensorInfo(TensorShape(16U, 27U, 5U), 1, DataType::F32)
+                                                        TensorInfo(TensorShape(16U, 27U, 5U), 1, DataType::F32),
+                                                        TensorInfo(TensorShape(21U, 35U, 5U), 1, DataType::F32)
+
               }),
               framework::dataset::make("InputInfo2", {  TensorInfo(TensorShape(24U, 27U, 4U), 1, DataType::F32),
                                                         TensorInfo(TensorShape(52U, 27U, 5U), 1, DataType::F32),
                                                         TensorInfo(TensorShape(52U, 27U, 5U), 1, DataType::F32),
-                                                        TensorInfo(TensorShape(16U, 27U, 5U), 1, DataType::F32)
+                                                        TensorInfo(TensorShape(16U, 27U, 5U), 1, DataType::F32),
+                                                        TensorInfo(TensorShape(10U, 35U, 5U), 1, DataType::F32)
               })),
               framework::dataset::make("OutputInfo", {  TensorInfo(TensorShape(47U, 27U, 5U), 1, DataType::F16),
                                                         TensorInfo(TensorShape(75U, 12U, 5U), 1, DataType::F32),
                                                         TensorInfo(TensorShape(11U, 27U, 5U), 1, DataType::F32),
-                                                        TensorInfo(TensorShape(32U, 27U, 5U), 1, DataType::F32)
+                                                        TensorInfo(TensorShape(32U, 27U, 5U), 1, DataType::F32),
+                                                        TensorInfo(TensorShape(31U, 35U, 5U), 1, DataType::F32)
+
               })),
-              framework::dataset::make("Expected", { false, false, false, true })),
+              framework::dataset::make("Expected", { false, false, false, true, true })),
               input_info1, input_info2, output_info,expected)
 {
     std::vector<TensorInfo> inputs_vector_info;
@@ -72,7 +77,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
         inputs_vector_info_raw.emplace_back(&input);
     }
 
-    bool is_valid = bool(CLConcatenateLayer::validate(inputs_vector_info_raw,&output_info.clone()->set_is_resizable(false),DataLayoutDimension::WIDTH ));
+    bool is_valid = bool(CLConcatenateLayer::validate(inputs_vector_info_raw,&output_info.clone()->set_is_resizable(true),DataLayoutDimension::WIDTH ));
     ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
 }
 // clang-format on
diff --git a/tests/validation/NEON/HeightConcatenateLayer.cpp b/tests/validation/NEON/HeightConcatenateLayer.cpp
index f5400f9246..0d08824645 100644
--- a/tests/validation/NEON/HeightConcatenateLayer.cpp
+++ b/tests/validation/NEON/HeightConcatenateLayer.cpp
@@ -48,19 +48,23 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
         framework::dataset::make("InputInfo1", {  TensorInfo(TensorShape(23U, 15U, 5U), 1, DataType::F32), // Mismatching data type input/output
                                                   TensorInfo(TensorShape(22U, 27U, 5U), 1, DataType::F32), // Mismatching y dimension
                                                   TensorInfo(TensorShape(11U, 25U, 5U), 1, DataType::F32), // Mismatching total height
-                                                  TensorInfo(TensorShape(16U, 25U, 5U), 1, DataType::F32)
+                                                  TensorInfo(TensorShape(16U, 25U, 5U), 1, DataType::F32),
+                                                  TensorInfo(TensorShape(35U, 21U, 5U), 1, DataType::F32)
+
         }),
         framework::dataset::make("InputInfo2", {  TensorInfo(TensorShape(23U, 15U, 4U), 1, DataType::F32),
                                                   TensorInfo(TensorShape(22U, 127U, 5U), 1, DataType::F32),
                                                   TensorInfo(TensorShape(11U, 26U, 5U), 1, DataType::F32),
-                                                  TensorInfo(TensorShape(16U, 25U, 5U), 1, DataType::F32)
+                                                  TensorInfo(TensorShape(16U, 25U, 5U), 1, DataType::F32),
+                                                  TensorInfo(TensorShape(35U, 10U, 5U), 1, DataType::F32)
         })),
         framework::dataset::make("OutputInfo", {  TensorInfo(TensorShape(23U, 30U, 5U), 1, DataType::F16),
                                                   TensorInfo(TensorShape(22U, 12U, 5U), 1, DataType::F32),
                                                   TensorInfo(TensorShape(11U, 7U, 5U), 1, DataType::F32),
-                                                  TensorInfo(TensorShape(16U, 50U, 5U), 1, DataType::F32)
+                                                  TensorInfo(TensorShape(16U, 50U, 5U), 1, DataType::F32),
+                                                  TensorInfo(TensorShape(35U, 31U, 5U), 1, DataType::F32)
         })),
-        framework::dataset::make("Expected", { false, false, false, true })),
+        framework::dataset::make("Expected", { false, false, false, true, true })),
         input_info1, input_info2, output_info,expected)
 {
     std::vector<TensorInfo> inputs_vector_info;
@@ -73,7 +77,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
         inputs_vector_info_raw.emplace_back(&input);
     }
 
-    bool is_valid = bool(NEConcatenateLayer::validate(inputs_vector_info_raw, &output_info.clone()->set_is_resizable(false), DataLayoutDimension::HEIGHT));
+    bool is_valid = bool(NEConcatenateLayer::validate(inputs_vector_info_raw, &output_info.clone()->set_is_resizable(true), DataLayoutDimension::HEIGHT));
     ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
 }
 // clang-format on
diff --git a/tests/validation/NEON/WidthConcatenateLayer.cpp b/tests/validation/NEON/WidthConcatenateLayer.cpp
index dba14ebb35..20df3f4d7d 100644
--- a/tests/validation/NEON/WidthConcatenateLayer.cpp
+++ b/tests/validation/NEON/WidthConcatenateLayer.cpp
@@ -47,19 +47,22 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
         framework::dataset::make("InputInfo1", {  TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32), // Mismatching data type input/output
                                                   TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32), // Mismatching y dimension
                                                   TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32), // Mismatching total width
-                                                  TensorInfo(TensorShape(16U, 27U, 5U), 1, DataType::F32)
+                                                  TensorInfo(TensorShape(16U, 27U, 5U), 1, DataType::F32),
+                                                  TensorInfo(TensorShape(21U, 35U, 5U), 1, DataType::F32)
         }),
         framework::dataset::make("InputInfo2", {  TensorInfo(TensorShape(24U, 27U, 4U), 1, DataType::F32),
                                                   TensorInfo(TensorShape(52U, 27U, 5U), 1, DataType::F32),
                                                   TensorInfo(TensorShape(52U, 27U, 5U), 1, DataType::F32),
-                                                  TensorInfo(TensorShape(16U, 27U, 5U), 1, DataType::F32)
+                                                  TensorInfo(TensorShape(16U, 27U, 5U), 1, DataType::F32),
+                                                  TensorInfo(TensorShape(10U, 35U, 5U), 1, DataType::F32)
         })),
         framework::dataset::make("OutputInfo", {  TensorInfo(TensorShape(47U, 27U, 5U), 1, DataType::F16),
                                                   TensorInfo(TensorShape(75U, 12U, 5U), 1, DataType::F32),
                                                   TensorInfo(TensorShape(11U, 27U, 5U), 1, DataType::F32),
-                                                  TensorInfo(TensorShape(32U, 27U, 5U), 1, DataType::F32)
+                                                  TensorInfo(TensorShape(32U, 27U, 5U), 1, DataType::F32),
+                                                  TensorInfo(TensorShape(31U, 35U, 5U), 1, DataType::F32)
         })),
-        framework::dataset::make("Expected", { false, false, false, true })),
+        framework::dataset::make("Expected", { false, false, false, true, true })),
         input_info1, input_info2, output_info,expected)
 {
     std::vector<TensorInfo> inputs_vector_info;
@@ -73,7 +76,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
     }
 
     bool is_valid = bool(NEConcatenateLayer::validate(inputs_vector_info_raw,
-                                                           &output_info.clone()->set_is_resizable(false),DataLayoutDimension::WIDTH));
+                                                           &output_info.clone()->set_is_resizable(true),DataLayoutDimension::WIDTH));
     ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
 }
 // clang-format on