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author | Georgios Pinitas <georgios.pinitas@arm.com> | 2019-02-22 11:08:32 +0000 |
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committer | Georgios Pinitas <georgios.pinitas@arm.com> | 2019-02-22 14:49:12 +0000 |
commit | 8f5802f1ee432445ed37344060ffa23916f7f29f (patch) | |
tree | ae119ed1c1817b74d14699265d7bcd7ad1a74bab /tests/validation | |
parent | 804aafbce2750049e658af8b01afde731413287f (diff) | |
download | ComputeLibrary-8f5802f1ee432445ed37344060ffa23916f7f29f.tar.gz |
COMPMID-1710: Add FP16 support checks.
Change-Id: I6291847935996859ab245160714f9fbefb03b5be
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-on: https://review.mlplatform.org/761
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Diffstat (limited to 'tests/validation')
-rw-r--r-- | tests/validation/NEON/ArgMinMax.cpp | 2 | ||||
-rw-r--r-- | tests/validation/NEON/Gather.cpp | 9 |
2 files changed, 4 insertions, 7 deletions
diff --git a/tests/validation/NEON/ArgMinMax.cpp b/tests/validation/NEON/ArgMinMax.cpp index bf7dbfe6b7..d3f70e6424 100644 --- a/tests/validation/NEON/ArgMinMax.cpp +++ b/tests/validation/NEON/ArgMinMax.cpp @@ -69,7 +69,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, - combine(datasets::SmallShapes(), framework::dataset::make("DataType", { DataType::F16, DataType::F32 })), + combine(datasets::SmallShapes(), framework::dataset::make("DataType", { DataType::F32 })), shape, data_type) { // Create tensors diff --git a/tests/validation/NEON/Gather.cpp b/tests/validation/NEON/Gather.cpp index 2e6a3d4ed2..6c7faa0032 100644 --- a/tests/validation/NEON/Gather.cpp +++ b/tests/validation/NEON/Gather.cpp @@ -48,8 +48,7 @@ TEST_SUITE(Gather) // *INDENT-OFF* // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( - framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 27U), 1, DataType::F16), - TensorInfo(TensorShape(27U, 27U), 1, DataType::F32), + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 27U), 1, DataType::F32), TensorInfo(TensorShape(27U, 27U), 1, DataType::F32), TensorInfo(TensorShape(27U, 27U), 1, DataType::F32), // Invalid Indices data type TensorInfo(TensorShape(27U, 27U), 1, DataType::F32), // Invalid Indices dimensionality @@ -61,7 +60,6 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( framework::dataset::make("IndicesInfo", { TensorInfo(TensorShape(10U), 1, DataType::U32), TensorInfo(TensorShape(10U), 1, DataType::U32), - TensorInfo(TensorShape(10U), 1, DataType::U32), TensorInfo(TensorShape(10U), 1, DataType::U8), TensorInfo(TensorShape(10U, 10U), 1, DataType::U32), TensorInfo(TensorShape(10U), 1, DataType::U32), @@ -70,7 +68,6 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( TensorInfo(TensorShape(10U), 1, DataType::U32), })), framework::dataset::make("OutputInfo", { - TensorInfo(TensorShape(10U, 27U), 1, DataType::F16), TensorInfo(TensorShape(27U, 10U), 1, DataType::F32), TensorInfo(TensorShape(10U, 27U), 1, DataType::F32), TensorInfo(TensorShape(10U, 27U), 1, DataType::F32), @@ -91,7 +88,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( 2, -3, })), - framework::dataset::make("Expected", { true, true, true, false, false, false, false, false, false })), + framework::dataset::make("Expected", { true, true, false, false, false, false, false, false })), input_info, indices_info, output_info, axis, expected) { const Status status = NEGather::validate(&input_info.clone()->set_is_resizable(true), &indices_info.clone()->set_is_resizable(true), &output_info.clone()->set_is_resizable(true), axis); @@ -102,7 +99,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, - combine(arm_compute::test::datasets::SmallGatherDataset(), framework::dataset::make("DataType", { DataType::F16, DataType::F32 })), + combine(arm_compute::test::datasets::SmallGatherDataset(), framework::dataset::make("DataType", { DataType::F32 })), input_shape, indices_shape, axis, data_type) { const uint32_t actual_axis = wrap_around(axis, static_cast<int>(input_shape.num_dimensions())); |