Improve conv3d validation

Improve validation of cpu conv3d and add validation test.
Align Size3D to Size3D comparison with how Size2D implements it.
Remove print statement in MaxUnpooling validation tests.

Signed-off-by: Freddie Liardet <frederick.liardet@arm.com>
Change-Id: I17048d56b08704cdbf1ad978af02009e57f3aa83
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6512
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

7 files changed, 23 insertions, 35 deletions

diff --git a/arm_compute/core/Size3D.h b/arm_compute/core/Size3D.h
index 1d8febe3ce..148bd17919 100644
--- a/arm_compute/core/Size3D.h
+++ b/arm_compute/core/Size3D.h
@@ -78,29 +78,21 @@ public:
         return depth;
     }
 
+    bool operator!=(const Size3D &other) const
+    {
+        return !(*this == other);
+    }
+
+    bool operator==(const Size3D &other) const
+    {
+        return (width == other.width) && (height == other.height) && (depth == other.depth);
+    }
+
 public:
     size_t width  = {}; /**< Width of the 3D shape or object */
     size_t height = {}; /**< Height of the 3D shape or object */
     size_t depth  = {}; /**< Depth of the 3D shape or object */
 };
 
-/** Operator to compare two Size3D objects to be equal
- *
- * @param[in] lhs Left-hand side Size3D object.
- * @param[in] rhs Right-hand side Size3D object.
- *
- * @return True if two instances have the same width, height and depth
- */
-bool operator==(const Size3D &lhs, const Size3D &rhs);
-
-/** Operator to compare two Size3D objects to be different
- *
- * @param[in] lhs Left-hand side Size3D object.
- * @param[in] rhs Right-hand side Size3D object.
- *
- * @return True if two instances have a difference in width, height or depth
- */
-bool operator!=(const Size3D &lhs, const Size3D &rhs);
-
 } // namespace arm_compute
 #endif /* ARM_COMPUTE_SIZE3D_H */
diff --git a/src/core/Size3D.cpp b/src/core/Size3D.cpp
index 4b7850bf38..3ee9fb8e5c 100644
--- a/src/core/Size3D.cpp
+++ b/src/core/Size3D.cpp
@@ -30,14 +30,4 @@ std::string Size3D::to_string() const
 {
     return support::cpp11::to_string(width) + std::string("x") + support::cpp11::to_string(height) + std::string("x") + support::cpp11::to_string(depth);
 }
-
-bool operator!=(const Size3D &lhs, const Size3D &rhs)
-{
-    return !(lhs == rhs);
-}
-
-bool operator==(const Size3D &lhs, const Size3D &rhs)
-{
-    return (lhs.width == rhs.width) && (lhs.height == rhs.height) && (lhs.depth == rhs.depth);
-}
 }
\ No newline at end of file
diff --git a/src/cpu/kernels/CpuDirectConv3dKernel.cpp b/src/cpu/kernels/CpuDirectConv3dKernel.cpp
index 4f47787c93..36764a625d 100644
--- a/src/cpu/kernels/CpuDirectConv3dKernel.cpp
+++ b/src/cpu/kernels/CpuDirectConv3dKernel.cpp
@@ -109,14 +109,16 @@ const DirectConv3dKernel *get_implementation(const DirectConv3dSelectorData &dat
 
 Status validate_arguments(const ITensorInfo *src0, const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, const Conv3dInfo &conv_info)
 {
-    const auto *uk = get_implementation(DirectConv3dSelectorData{ src0->data_type(), CPUInfo::get() });
-    ARM_COMPUTE_RETURN_ERROR_ON(uk == nullptr || uk->ukernel == nullptr);
-
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src0, src1, dst);
     ARM_COMPUTE_RETURN_ERROR_ON(src0->data_layout() != DataLayout::NDHWC);
+    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(src0, src1, dst);
     ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(src0);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src0, 1, DataType::F16, DataType::F32, DataType::QASYMM8, DataType::QASYMM8_SIGNED);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src0, src1);
+    ARM_COMPUTE_RETURN_ERROR_ON(conv_info.dilation != Size3D(1U, 1U, 1U));
+
+    const auto *uk = get_implementation(DirectConv3dSelectorData{ src0->data_type(), CPUInfo::get() });
+    ARM_COMPUTE_RETURN_ERROR_ON(uk == nullptr || uk->ukernel == nullptr);
 
     const DataLayout data_layout = src0->data_layout();
     const int        channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
diff --git a/src/gpu/cl/kernels/ClDirectConv3dKernel.cpp b/src/gpu/cl/kernels/ClDirectConv3dKernel.cpp
index 27afb7e190..a0735b1112 100644
--- a/src/gpu/cl/kernels/ClDirectConv3dKernel.cpp
+++ b/src/gpu/cl/kernels/ClDirectConv3dKernel.cpp
@@ -47,6 +47,7 @@ Status validate_arguments(const ITensorInfo *src0, const ITensorInfo *src1, cons
     ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src0);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src0, 1, DataType::F16, DataType::F32, DataType::QASYMM8, DataType::QASYMM8_SIGNED);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src0, src1);
+    ARM_COMPUTE_RETURN_ERROR_ON(conv3d_info.dilation != Size3D(1U, 1U, 1U));
 
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(src1->dimension(1) != src0->dimension(0), "Weights feature map dimension should match the respective src's one");
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(src1->num_dimensions() > 5, "Weights can be at most 5 dimensional");
diff --git a/tests/validation/CL/Convolution3D.cpp b/tests/validation/CL/Convolution3D.cpp
index 2d1dc574f8..9e4ca50547 100644
--- a/tests/validation/CL/Convolution3D.cpp
+++ b/tests/validation/CL/Convolution3D.cpp
@@ -114,7 +114,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                 framework::dataset::make("SrcDataType", { DataType::F32,
                                                           DataType::F32,
                                                           DataType::F32,
-                                                          DataType::QASYMM8,
+                                                          DataType::U32,
                                                           DataType::F32,
                                                           DataType::F32,
                                                           DataType::F32,
@@ -126,7 +126,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                 framework::dataset::make("WeightsDataType", { DataType::F32,
                                                               DataType::F32,
                                                               DataType::F16,
-                                                              DataType::QASYMM8,
+                                                              DataType::U32,
                                                               DataType::F32,
                                                               DataType::F32,
                                                               DataType::F32,
diff --git a/tests/validation/CL/MaxUnpoolingLayer.cpp b/tests/validation/CL/MaxUnpoolingLayer.cpp
index a0b20caeae..cf4fcdda70 100644
--- a/tests/validation/CL/MaxUnpoolingLayer.cpp
+++ b/tests/validation/CL/MaxUnpoolingLayer.cpp
@@ -57,7 +57,6 @@ FIXTURE_DATA_TEST_CASE(MaxUnpooling, CLMaxUnpoolingLayerFixture<float>, framewor
 
                                                                                                                   ))
 {
-    printf("validate\n");
     // Validate output
     validate(CLAccessor(_target), _reference);
 }
diff --git a/tests/validation/NEON/Convolution3D.cpp b/tests/validation/NEON/Convolution3D.cpp
index 1bfac900c0..4185488742 100644
--- a/tests/validation/NEON/Convolution3D.cpp
+++ b/tests/validation/NEON/Convolution3D.cpp
@@ -87,6 +87,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
                                                 TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid biases size
                                                 TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid biases dimensions
                                                 TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid output size
+                                                TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::U32, DataLayout::NDHWC), // Invalid data type
                                               }),
         framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F16),
                                                  TensorInfo(TensorShape(4U, 3U, 3U, 3U, 3U), 1U, DataType::F32),
@@ -95,6 +96,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
                                                  TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32),
                                                  TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32),
                                                  TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32),
+                                                 TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::U32),
                                               })),
         framework::dataset::make("BiasesInfo",{ TensorInfo(TensorShape(4U), 1U, DataType::F32),
                                                 TensorInfo(TensorShape(4U), 1U, DataType::F32),
@@ -103,6 +105,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
                                                 TensorInfo(TensorShape(3U), 1U, DataType::F32),
                                                 TensorInfo(TensorShape(4U, 2U), 1U, DataType::F32),
                                                 TensorInfo(TensorShape(4U), 1U, DataType::F32),
+                                                TensorInfo(TensorShape(4U), 1U, DataType::F32),
                                               })),
         framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32),
                                                 TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32),
@@ -111,8 +114,9 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
                                                 TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32),
                                                 TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32),
                                                 TensorInfo(TensorShape(26U, 11U, 4U), 1U, DataType::F32),
+                                                TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::U32),
                                               })),
-        framework::dataset::make("Expected", { false, false, false, false, false, false, false })),
+        framework::dataset::make("Expected", { false, false, false, false, false, false, false, false})),
         input_info, weights_info, biases_info, output_info, expected)
 {
         const Conv3dInfo  conv3d_info(Size3D(1, 1, 1), Padding3D(0, 0, 0), ActivationLayerInfo(), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false);