Add Cropping to CLBatchToSpace
- Deprecate dynamic block shape interface
- Iterate over output window instead of input window for simpler implementation and better performance.
- Add cropping support and cropping tests
Resolves [COMPMID-5865]
Signed-off-by: Omar Al Khatib <omar.alkhatib@arm.com>
Change-Id: Ic67d44a6a39299ecdafc507f12e3dc5d517dfb62
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9385
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/CL/BatchToSpaceLayer.cpp b/tests/validation/CL/BatchToSpaceLayer.cpp
index e90ac92..ca12b76 100644
--- a/tests/validation/CL/BatchToSpaceLayer.cpp
+++ b/tests/validation/CL/BatchToSpaceLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2020 Arm Limited.
+ * Copyright (c) 2018-2021, 2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -50,56 +50,38 @@
// *INDENT-OFF*
// clang-format off
-DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
- framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32),
- TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // blockx != blocky && blockx > blocky
- TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // blockx != blocky && blocky > blockx
- TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), // Mismatching data types
- TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), // Wrong data type block shape
- TensorInfo(TensorShape(32U, 13U, 2U, 2U, 4U), 1, DataType::F32), // Wrong tensor shape
- }),
- framework::dataset::make("BlockShapeInfo",{ TensorInfo(TensorShape(2U, 2U), 1, DataType::S32),
- TensorInfo(TensorShape(2U, 4U), 1, DataType::S32),
- TensorInfo(TensorShape(4U, 2U), 1, DataType::S32),
- TensorInfo(TensorShape(2U, 2U), 1, DataType::S32),
- TensorInfo(TensorShape(2U, 2U), 1, DataType::F16),
- TensorInfo(TensorShape(2U, 2U), 1, DataType::S32),
- })),
- framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32),
- TensorInfo(TensorShape(64U, 16U, 2U, 1U), 1, DataType::F32),
- TensorInfo(TensorShape(32U, 32U, 2U, 1U), 1, DataType::F32),
-
- TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F16),
- TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32),
- TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32),
- })),
- framework::dataset::make("Expected", { true, true,true, false, false, false})),
- input_info, block_shape_info, output_info, expected)
-{
- bool has_error = bool(CLBatchToSpaceLayer::validate(&input_info.clone()->set_is_resizable(false), &block_shape_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false)));
- ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS);
-}
-DATA_TEST_CASE(ValidateStatic, framework::DatasetMode::ALL, zip(zip(zip(zip(
+DATA_TEST_CASE(ValidateStatic, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
framework::dataset::make("InputInfo", { TensorInfo(TensorShape(16U, 8U, 2U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // blockx != blocky && blockx > blocky
- TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // blockx != blocky && blocky > blockx
- TensorInfo(TensorShape(16U, 8U, 2U, 4U), 1, DataType::F32), // Mismatching data types
- TensorInfo(TensorShape(16U, 8U, 2U, 4U), 1, DataType::F32), // Negative block shapes
- TensorInfo(TensorShape(32U, 16U, 2U, 4U, 4U), 1, DataType::F32), // Wrong tensor shape
+ TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // Supported: blockx != blocky && blockx > blocky
+ TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // Supported: blockx != blocky && blocky > blockx
+ TensorInfo(TensorShape(16U, 8U, 2U, 4U), 1, DataType::F32), // Invalid: Mismatching data types
+ TensorInfo(TensorShape(16U, 8U, 2U, 4U), 1, DataType::F32), // Invalid: Negative block shapes
+ TensorInfo(TensorShape(32U, 16U, 2U, 4U, 4U), 1, DataType::F32),// Unsupported tensor rank
+ TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // Invalid output tensor shape (invalid batch dimension)
+ TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // Invalid output tensor shape (invalid spatial dimension)
+ TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // Supported: correct tensor shape with cropping
+ TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // Invalid tensor shape with cropping
}),
- framework::dataset::make("BlockShapeX", { 2, 4, 2, 2, 2, 2 })),
- framework::dataset::make("BlockShapeY", { 2, 2, 4, 2, -2, 2 })),
+ framework::dataset::make("BlockShapeX", { 2, 4, 2, 2, 2, 2, 2, 2, 2, 2 })),
+ framework::dataset::make("BlockShapeY", { 2, 2, 4, 2, -2, 2, 2, 2, 2, 2 })),
+ framework::dataset::make("CropInfo", {
+ CropInfo{}, CropInfo{}, CropInfo{}, CropInfo{}, CropInfo{}, CropInfo{}, CropInfo{}, CropInfo{}, CropInfo{3, 2, 1, 3}, CropInfo{3, 2, 1, 3}
+ })),
framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 16U, 2U, 1U), 1, DataType::F32),
- TensorInfo(TensorShape(64U, 16U, 2U, 1U), 1, DataType::F32),
- TensorInfo(TensorShape(32U, 32U, 2U, 1U), 1, DataType::F32),
+ TensorInfo(TensorShape(64U, 16U, 2U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 32U, 2U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 16U, 2U, 1U), 1, DataType::F16),
TensorInfo(TensorShape(32U, 16U, 2U, 1U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 8U, 2U, 1U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 16U, 2U, 1U), 1, DataType::F32),
+ TensorInfo(TensorShape(33U, 32U, 2U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(27, 12U, 2U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 16U, 2U, 4U), 1, DataType::F32),
})),
- framework::dataset::make("Expected", { true, true,true, false, false, false})),
- input_info, block_shape_x, block_shape_y, output_info, expected)
+ framework::dataset::make("Expected", { true, true, true, false, false, false, false, false, true, false})),
+ input_info, block_shape_x, block_shape_y, crop_info, output_info, expected)
{
- bool has_error = bool(CLBatchToSpaceLayer::validate(&input_info.clone()->set_is_resizable(false), block_shape_x, block_shape_y, &output_info.clone()->set_is_resizable(false)));
+ bool has_error = bool(CLBatchToSpaceLayer::validate(&input_info.clone()->set_is_resizable(false), block_shape_x, block_shape_y, &output_info.clone()->set_is_resizable(false), crop_info));
ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS);
}
// clang-format on
@@ -114,6 +96,16 @@
// Validate output
validate(CLAccessor(_target), _reference);
}
+
+FIXTURE_DATA_TEST_CASE(RunSmallWithCropping, CLBatchToSpaceLayerFixture<float>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(datasets::SmallBatchToSpaceLayerWithCroppingDataset(), framework::dataset::make("DataType",
+ DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference);
+}
+
FIXTURE_DATA_TEST_CASE(RunLarge, CLBatchToSpaceLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeBatchToSpaceLayerDataset(), framework::dataset::make("DataType",
DataType::F32)),
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
@@ -131,6 +123,16 @@
// Validate output
validate(CLAccessor(_target), _reference);
}
+
+FIXTURE_DATA_TEST_CASE(RunSmallWithCropping, CLBatchToSpaceLayerFixture<half>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(datasets::SmallBatchToSpaceLayerWithCroppingDataset(), framework::dataset::make("DataType",
+ DataType::F16)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference);
+}
+
FIXTURE_DATA_TEST_CASE(RunLarge, CLBatchToSpaceLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeBatchToSpaceLayerDataset(), framework::dataset::make("DataType",
DataType::F16)),
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))