commit 69df64fc340215b8ce71d30105eb681811f5e0c3
author Freddie Liardet <frederick.liardet@arm.com> Tue Oct 26 14:06:47 2021 +0100
committer Freddie Liardet <frederick.liardet@arm.com> Wed Oct 27 12:24:45 2021 +0000
tree 1a42c57e905e7d6adceaa9720e2ea039fc79dc45
parent f727ef49e2109bdac105dd6575d2e336adf780a3

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>

tests/validation/NEON/Convolution3D.cpp

diff --git a/tests/validation/NEON/Convolution3D.cpp b/tests/validation/NEON/Convolution3D.cpp
index 1bfac90..4185488 100644
--- a/tests/validation/NEON/Convolution3D.cpp
+++ b/tests/validation/NEON/Convolution3D.cpp
@@ -87,6 +87,7 @@
                                                 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 @@
                                                  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 @@
                                                 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 @@
                                                 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);