COMPMID-2728: Add support for split sizes in CLSplit
Signed-off-by: Kurtis Charnock <kurtis.charnock@arm.com>
Change-Id: I69ea9e812478904c3e10379bb5943d534c45f942
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/214132
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2432
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
diff --git a/arm_compute/runtime/CL/functions/CLSplit.h b/arm_compute/runtime/CL/functions/CLSplit.h
index 7e22f52..87265a4 100644
--- a/arm_compute/runtime/CL/functions/CLSplit.h
+++ b/arm_compute/runtime/CL/functions/CLSplit.h
@@ -24,9 +24,11 @@
#ifndef ARM_COMPUTE_CLSPLIT_H
#define ARM_COMPUTE_CLSPLIT_H
+#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/CL/functions/CLSlice.h"
+#include "arm_compute/runtime/CPP/functions/CPPSplit.h"
#include "arm_compute/runtime/IFunction.h"
#include <memory>
@@ -34,43 +36,12 @@
namespace arm_compute
{
-// Forward declarations
-class ICLTensor;
-
/** Basic function to split a tensor along a given axis */
-class CLSplit : public IFunction
+class CLSplit : public CPPSplit<CLSlice, ICLTensor>
{
public:
- /** Default constructor */
- CLSplit();
- /** Initialise the kernel's input and outputs.
- *
- * @param[in] input The input tensor. Data types supported: All.
- * @param[out] outputs A vector containing the output tensors. Data types supported: Same as @p input.
- * The output tensors should match the input tensor dimensions for all shape dimensions apart
- * from the split dimension.
- * @param[in] axis Axis on which to split the input.
- */
- void configure(const ICLTensor *input, const std::vector<ICLTensor *> &outputs, unsigned int axis);
- /** Static function to check if given info will lead to a valid configuration of @ref CLSplit
- *
- * @param[in] input The input tensor info. Data types supported: All.
- * @param[in] outputs A vector containing the output tensors' info. Data types supported: Same as @p input.
- * The output tensors should match the input tensor dimensions for all shape dimensions apart
- * from the split dimension
- * @param[in] axis Axis on which to split the input.
- *
- * @return a status
- */
- static Status validate(const ITensorInfo *input, const std::vector<ITensorInfo *> &outputs, unsigned int axis);
-
// Inherited methods overridden:
void run() override;
-
-private:
- std::vector<ICLTensor *> _outputs_vector;
- std::vector<CLSlice> _slice_functions;
- unsigned int _num_outputs;
};
} // namespace arm_compute
#endif /* ARM_COMPUTE_CLSPLIT_H */
diff --git a/arm_compute/runtime/CPP/CPPFunctions.h b/arm_compute/runtime/CPP/CPPFunctions.h
index b78436c..c196381 100644
--- a/arm_compute/runtime/CPP/CPPFunctions.h
+++ b/arm_compute/runtime/CPP/CPPFunctions.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -30,6 +30,7 @@
#include "arm_compute/runtime/CPP/functions/CPPDetectionPostProcessLayer.h"
#include "arm_compute/runtime/CPP/functions/CPPNonMaximumSuppression.h"
#include "arm_compute/runtime/CPP/functions/CPPPermute.h"
+#include "arm_compute/runtime/CPP/functions/CPPSplit.h"
#include "arm_compute/runtime/CPP/functions/CPPTopKV.h"
#include "arm_compute/runtime/CPP/functions/CPPUpsample.h"
diff --git a/arm_compute/runtime/CPP/functions/CPPSplit.h b/arm_compute/runtime/CPP/functions/CPPSplit.h
new file mode 100644
index 0000000..6adcbc3
--- /dev/null
+++ b/arm_compute/runtime/CPP/functions/CPPSplit.h
@@ -0,0 +1,197 @@
+/*
+ * Copyright (c) 2020 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef ARM_COMPUTE_CPP_SPLIT_H
+#define ARM_COMPUTE_CPP_SPLIT_H
+
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+
+#include "support/ToolchainSupport.h"
+
+#include "arm_compute/runtime/IFunction.h"
+
+namespace arm_compute
+{
+/** Basic function to split a tensor along a given axis */
+template <typename SliceType, typename TensorInterfaceType = ITensor>
+class CPPSplit : public IFunction
+{
+public:
+ CPPSplit()
+ : _outputs_vector(), _slice_functions(), _num_outputs(0)
+ {
+ }
+ /** Static function to check if given info will lead to a valid configuration of @ref CPPSplit
+ *
+ * @param[in] input The input tensor info. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32.
+ * @param[in] outputs A vector containing the output tensors' info. Data types supported: Same as @p input.
+ * The output tensors should match the input tensor dimensions for all shape dimensions apart
+ * from the split dimension
+ * @param[in] axis Axis on which to split the input.
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input, const std::vector<ITensorInfo *> &outputs, unsigned int axis)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
+ ARM_COMPUTE_RETURN_ERROR_ON(axis >= input->num_dimensions());
+ ARM_COMPUTE_RETURN_ERROR_ON(outputs.size() < 2);
+
+ // Get output shape
+ TensorShape output_shape{};
+ unsigned int total_output_shape_size = 0;
+
+ // Sum the output sizes and fall back to evenly-sized splits if any are zero
+ const bool using_split_shapes = std::none_of(outputs.begin(), outputs.end(), [&total_output_shape_size](ITensorInfo * info)
+ {
+ unsigned int output_shape_size = info->tensor_shape().total_size();
+ total_output_shape_size += output_shape_size;
+ return output_shape_size == 0;
+ });
+
+ if(using_split_shapes)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape().total_size() != total_output_shape_size);
+ }
+ else
+ {
+ output_shape = arm_compute::misc::shape_calculator::compute_split_shape(input, axis, outputs.size());
+ ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() == 0);
+ }
+
+ // Validate output tensors
+ unsigned int axis_offset = 0;
+ for(const auto &output : outputs)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
+ if(using_split_shapes)
+ {
+ output_shape = output->tensor_shape();
+ ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() == 0);
+ }
+
+ const size_t axis_split_step = output_shape[axis];
+
+ // Start/End coordinates
+ Coordinates start_coords;
+ Coordinates end_coords;
+ for(unsigned int d = 0; d < output_shape.num_dimensions(); ++d)
+ {
+ end_coords.set(d, -1);
+ }
+
+ // Output auto inizialitation if not yet initialized
+ TensorInfo tmp_output_info = *output->clone();
+ auto_init_if_empty(tmp_output_info, input->clone()->set_is_resizable(true).set_tensor_shape(output_shape));
+
+ // Update coordinate on axis
+ start_coords.set(axis, axis_offset);
+ end_coords.set(axis, axis_offset + axis_split_step);
+
+ ARM_COMPUTE_RETURN_ON_ERROR(SliceType::validate(input, output, start_coords, end_coords));
+ axis_offset += axis_split_step;
+ }
+
+ return Status{};
+ }
+
+ /** Initialise the kernel's input and outputs.
+ *
+ * @param[in] input The input tensor. Data types supported: All
+ * @param[out] outputs A vector containing the output tensors. Data types supported: Same as @p input.
+ * The output tensors should match the input tensor dimensions for all shape dimensions apart
+ * from the split dimension.
+ * @param[in] axis Axis on which to split the input.
+ */
+ void configure(const TensorInterfaceType *input, const std::vector<TensorInterfaceType *> &outputs, unsigned int axis)
+ {
+ // Create Slice functions
+ _num_outputs = outputs.size();
+ _slice_functions.resize(_num_outputs);
+
+ // Extract output tensor info
+ std::vector<ITensorInfo *> outputs_info;
+ for(auto &output : outputs)
+ {
+ ARM_COMPUTE_ERROR_ON_NULLPTR(output);
+ outputs_info.emplace_back(output->info());
+ }
+
+ // If any of the outputs have a zero size, fall-back to using evenly-sized output splits
+ const bool outputs_have_sizes = std::none_of(outputs_info.begin(), outputs_info.end(), [](ITensorInfo * info)
+ {
+ return info->tensor_shape().total_size() == 0;
+ });
+
+ // Validate
+ ARM_COMPUTE_ERROR_THROW_ON(CPPSplit::validate(input->info(), outputs_info, axis));
+
+ unsigned int axis_offset = 0;
+ unsigned int i = 0;
+
+ for(const auto &output_info : outputs_info)
+ {
+ // Get output shape
+ TensorShape output_shape = (outputs_have_sizes ?
+ output_info->tensor_shape() :
+ arm_compute::misc::shape_calculator::compute_split_shape(input->info(), axis, _num_outputs));
+
+ const size_t axis_split_step = output_shape[axis];
+
+ // Start/End coordinates
+ Coordinates start_coords;
+ Coordinates end_coords;
+
+ for(unsigned int d = 0; d < output_shape.num_dimensions(); ++d)
+ {
+ end_coords.set(d, -1);
+ }
+
+ // Update coordinate on axis
+ start_coords.set(axis, axis_offset);
+ end_coords.set(axis, axis_offset + axis_split_step);
+
+ // Configure slice function
+ _slice_functions[i].configure(input, outputs[i], start_coords, end_coords);
+
+ // Set valid region from shape
+ outputs[i]->info()->set_valid_region(ValidRegion(Coordinates(), output_shape));
+
+ // Update axis offset
+ axis_offset += axis_split_step;
+ ++i;
+ }
+ }
+
+protected:
+ std::vector<TensorInterfaceType *> _outputs_vector;
+ std::vector<SliceType> _slice_functions;
+ unsigned int _num_outputs;
+};
+
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_CPP_SPLIT_H */
diff --git a/src/runtime/CL/functions/CLSplit.cpp b/src/runtime/CL/functions/CLSplit.cpp
index 8d37d53..9fca52b 100644
--- a/src/runtime/CL/functions/CLSplit.cpp
+++ b/src/runtime/CL/functions/CLSplit.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -34,100 +34,6 @@
namespace arm_compute
{
-CLSplit::CLSplit()
- : _outputs_vector(), _slice_functions(), _num_outputs(0)
-{
-}
-
-void CLSplit::configure(const ICLTensor *input, const std::vector<ICLTensor *> &outputs, unsigned int axis)
-{
- // Create Slice functions
- _num_outputs = outputs.size();
- _slice_functions.resize(_num_outputs);
-
- // Get output shape
- const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_split_shape(input->info(), axis, _num_outputs);
-
- // Extract output tensor info
- std::vector<ITensorInfo *> outputs_info;
- for(auto &output : outputs)
- {
- ARM_COMPUTE_ERROR_ON_NULLPTR(output);
- outputs_info.emplace_back(output->info());
- }
-
- // Validate
- ARM_COMPUTE_ERROR_THROW_ON(CLSplit::validate(input->info(), outputs_info, axis));
-
- const size_t axis_split_step = output_shape[axis];
- unsigned int axis_offset = 0;
-
- // Start/End coordinates
- Coordinates start_coords;
- Coordinates end_coords;
- for(unsigned int d = 0; d < output_shape.num_dimensions(); ++d)
- {
- end_coords.set(d, -1);
- }
-
- for(unsigned int i = 0; i < _num_outputs; i++)
- {
- // Update coordinate on axis
- start_coords.set(axis, axis_offset);
- end_coords.set(axis, axis_offset + axis_split_step);
-
- // Configure slice function
- _slice_functions[i].configure(input, outputs[i], start_coords, end_coords);
-
- // Set valid region from shape
- outputs[i]->info()->set_valid_region(ValidRegion(Coordinates(), output_shape));
-
- // Update axis offset
- axis_offset += axis_split_step;
- }
-}
-
-Status CLSplit::validate(const ITensorInfo *input, const std::vector<ITensorInfo *> &outputs, unsigned int axis)
-{
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
- ARM_COMPUTE_RETURN_ERROR_ON(axis >= input->num_dimensions());
- ARM_COMPUTE_RETURN_ERROR_ON(outputs.size() < 2);
-
- // Get output shape
- const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_split_shape(input, axis, outputs.size());
- ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() == 0);
-
- const size_t axis_split_step = output_shape[axis];
- unsigned int axis_offset = 0;
-
- // Start/End coordinates
- Coordinates start_coords;
- Coordinates end_coords;
- for(unsigned int d = 0; d < output_shape.num_dimensions(); ++d)
- {
- end_coords.set(d, -1);
- }
-
- // Validate output tensors
- for(const auto &output : outputs)
- {
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
-
- // Output auto inizialitation if not yet initialized
- TensorInfo tmp_output_info = *output->clone();
- auto_init_if_empty(tmp_output_info, input->clone()->set_is_resizable(true).set_tensor_shape(output_shape));
-
- // Update coordinate on axis
- start_coords.set(axis, axis_offset);
- end_coords.set(axis, axis_offset + axis_split_step);
-
- ARM_COMPUTE_RETURN_ON_ERROR(CLSlice::validate(input, output, start_coords, end_coords));
- axis_offset += axis_split_step;
- }
-
- return Status{};
-}
-
void CLSplit::run()
{
cl::CommandQueue q = CLScheduler::get().queue();
diff --git a/tests/datasets/SplitDataset.h b/tests/datasets/SplitDataset.h
index b38252a..3d4c289 100644
--- a/tests/datasets/SplitDataset.h
+++ b/tests/datasets/SplitDataset.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -128,6 +128,90 @@
add_config(TensorShape(128U, 64U, 32U, 4U), 3U, 4U);
}
};
+
+class SplitShapesDataset
+{
+public:
+ using type = std::tuple<TensorShape, unsigned int, std::vector<TensorShape>>;
+
+ struct iterator
+ {
+ iterator(std::vector<TensorShape>::const_iterator tensor_shapes_it,
+ std::vector<unsigned int>::const_iterator axis_values_it,
+ std::vector<std::vector<TensorShape>>::const_iterator split_shapes_values_it)
+ : _tensor_shapes_it{ std::move(tensor_shapes_it) },
+ _axis_values_it{ std::move(axis_values_it) },
+ _split_shapes_values_it{ std::move(split_shapes_values_it) }
+ {
+ }
+
+ std::string description() const
+ {
+ std::stringstream description;
+ description << "Shape=" << *_tensor_shapes_it << ":";
+ description << "Axis=" << *_axis_values_it << ":";
+ description << "Split shapes=" << *_split_shapes_values_it << ":";
+ return description.str();
+ }
+
+ SplitShapesDataset::type operator*() const
+ {
+ return std::make_tuple(*_tensor_shapes_it, *_axis_values_it, *_split_shapes_values_it);
+ }
+
+ iterator &operator++()
+ {
+ ++_tensor_shapes_it;
+ ++_axis_values_it;
+ ++_split_shapes_values_it;
+ return *this;
+ }
+
+ private:
+ std::vector<TensorShape>::const_iterator _tensor_shapes_it;
+ std::vector<unsigned int>::const_iterator _axis_values_it;
+ std::vector<std::vector<TensorShape>>::const_iterator _split_shapes_values_it;
+ };
+
+ iterator begin() const
+ {
+ return iterator(_tensor_shapes.begin(), _axis_values.begin(), _split_shapes_values.begin());
+ }
+
+ int size() const
+ {
+ return std::min(_tensor_shapes.size(), std::min(_axis_values.size(), _split_shapes_values.size()));
+ }
+
+ void add_config(TensorShape shape, unsigned int axis, std::vector<TensorShape> split_shapes)
+ {
+ _tensor_shapes.emplace_back(std::move(shape));
+ _axis_values.emplace_back(axis);
+ _split_shapes_values.emplace_back(split_shapes);
+ }
+
+protected:
+ SplitShapesDataset() = default;
+ SplitShapesDataset(SplitShapesDataset &&) = default;
+
+private:
+ std::vector<TensorShape> _tensor_shapes{};
+ std::vector<unsigned int> _axis_values{};
+ std::vector<std::vector<TensorShape>> _split_shapes_values{};
+};
+
+class SmallSplitShapesDataset final : public SplitShapesDataset
+{
+public:
+ SmallSplitShapesDataset()
+ {
+ add_config(TensorShape(27U, 3U, 16U, 2U), 2U, std::vector<TensorShape> { TensorShape(27U, 3U, 4U, 2U),
+ TensorShape(27U, 3U, 4U, 2U),
+ TensorShape(27U, 3U, 8U, 2U)
+ });
+ }
+};
+
} // namespace datasets
} // namespace test
} // namespace arm_compute
diff --git a/tests/validation/CL/Split.cpp b/tests/validation/CL/Split.cpp
index e038b89..8f55b42 100644
--- a/tests/validation/CL/Split.cpp
+++ b/tests/validation/CL/Split.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -65,6 +65,29 @@
const Status status = CLSplit::validate(&input_info.clone()->set_is_resizable(false), outputs_info_ptr, axis);
ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS);
}
+
+DATA_TEST_CASE(ValidateSplitShapes, framework::DatasetMode::ALL, zip(zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 3U, 16U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(27U, 3U, 16U, 2U), 1, DataType::F32)
+ }),
+ framework::dataset::make("Axis", { 2, 2 })),
+ framework::dataset::make("Splits", { std::vector<TensorInfo>{TensorInfo(TensorShape(27U, 3U, 4U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(27U, 3U, 4U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(27U, 3U, 8U, 2U), 1, DataType::F32)},
+ std::vector<TensorInfo>{TensorInfo(TensorShape(27U, 3U, 3U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(27U, 3U, 13U, 2U), 1, DataType::F32)} })),
+ framework::dataset::make("Expected", { true, true })),
+ input_info, axis, splits, expected)
+{
+ std::vector<ITensorInfo*> outputs_info_ptr;
+
+ for(auto &split : splits)
+ {
+ outputs_info_ptr.emplace_back(const_cast<TensorInfo*>(&split));
+ }
+ const Status status = CLSplit::validate(&input_info.clone()->set_is_resizable(false), outputs_info_ptr, axis);
+ ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS);
+}
// clang-format on
// *INDENT-ON*
@@ -95,9 +118,45 @@
}
}
+DATA_TEST_CASE(ConfigurationSplitShapes,
+ framework::DatasetMode::ALL,
+ combine(datasets::SmallSplitShapesDataset(), framework::dataset::make("DataType", { DataType::F16, DataType::F32 })),
+ shape, axis, split_shapes, data_type)
+{
+ // Create tensors
+ CLTensor src = create_tensor<CLTensor>(shape, data_type);
+ std::vector<CLTensor> dsts;
+
+ for(const auto &split_shape : split_shapes)
+ {
+ CLTensor dst = create_tensor<CLTensor>(split_shape, data_type);
+ dsts.push_back(std::move(dst));
+ }
+
+ std::vector<ICLTensor *> dsts_ptrs;
+ for(auto &dst : dsts)
+ {
+ dsts_ptrs.emplace_back(&dst);
+ }
+
+ // Create and Configure function
+ CLSplit split;
+ split.configure(&src, dsts_ptrs, axis);
+
+ // Validate valid regions
+ for(auto &dst : dsts)
+ {
+ const ValidRegion valid_region = shape_to_valid_region(dst.info()->tensor_shape());
+ validate(dst.info()->valid_region(), valid_region);
+ }
+}
+
template <typename T>
using CLSplitFixture = SplitFixture<CLTensor, ICLTensor, CLAccessor, CLSplit, T>;
+template <typename T>
+using CLSplitShapesFixture = SplitShapesFixture<CLTensor, ICLTensor, CLAccessor, CLSplit, T>;
+
TEST_SUITE(Float)
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunSmall,
@@ -149,6 +208,18 @@
validate(CLAccessor(_target[i]), _reference[i]);
}
}
+
+FIXTURE_DATA_TEST_CASE(RunSmallSplitShapes,
+ CLSplitShapesFixture<float>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::SmallSplitShapesDataset(), framework::dataset::make("DataType", DataType::F32)))
+{
+ // Validate outputs
+ for(unsigned int i = 0; i < _target.size(); ++i)
+ {
+ validate(CLAccessor(_target[i]), _reference[i]);
+ }
+}
TEST_SUITE_END() // FP32
TEST_SUITE_END() // Float
diff --git a/tests/validation/fixtures/SplitFixture.h b/tests/validation/fixtures/SplitFixture.h
index 0750177..d2336ab 100644
--- a/tests/validation/fixtures/SplitFixture.h
+++ b/tests/validation/fixtures/SplitFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -145,6 +145,115 @@
std::vector<TensorType> _target{};
std::vector<SimpleTensor<T>> _reference{};
};
+
+template <typename TensorType, typename ITensorType, typename AccessorType, typename FunctionType, typename T>
+class SplitShapesFixture : public framework::Fixture
+{
+public:
+ template <typename...>
+ void setup(TensorShape shape, unsigned int axis, std::vector<TensorShape> split_shapes, DataType data_type)
+ {
+ _target = compute_target(shape, axis, split_shapes, data_type);
+ _reference = compute_reference(shape, axis, split_shapes, data_type);
+ }
+
+protected:
+ template <typename U>
+ void fill(U &&tensor, int i)
+ {
+ library->fill_tensor_uniform(tensor, i);
+ }
+
+ std::vector<TensorType> compute_target(TensorShape shape, unsigned int axis, std::vector<TensorShape> split_shapes, DataType data_type)
+ {
+ // Create tensors
+ TensorType src = create_tensor<TensorType>(shape, data_type);
+ std::vector<TensorType> dsts{};
+ std::vector<ITensorType *> dsts_ptr;
+
+ for(const auto &split_shape : split_shapes)
+ {
+ TensorType dst = create_tensor<TensorType>(split_shape, data_type);
+ dsts.push_back(std::move(dst));
+ }
+
+ for(auto &dst : dsts)
+ {
+ dsts_ptr.emplace_back(&dst);
+ }
+
+ // Create and configure function
+ FunctionType split;
+ split.configure(&src, dsts_ptr, axis);
+
+ ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(std::all_of(dsts.cbegin(), dsts.cend(), [](const TensorType & t)
+ {
+ return t.info()->is_resizable();
+ }),
+ framework::LogLevel::ERRORS);
+
+ // Allocate tensors
+ src.allocator()->allocate();
+ for(unsigned int i = 0; i < dsts.size(); ++i)
+ {
+ dsts[i].allocator()->allocate();
+ }
+
+ ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(std::all_of(dsts.cbegin(), dsts.cend(), [](const TensorType & t)
+ {
+ return !t.info()->is_resizable();
+ }),
+ framework::LogLevel::ERRORS);
+
+ // Fill tensors
+ fill(AccessorType(src), 0);
+
+ // Compute function
+ split.run();
+
+ return dsts;
+ }
+
+ std::vector<SimpleTensor<T>> compute_reference(TensorShape shape, unsigned int axis, std::vector<TensorShape> split_shapes, DataType data_type)
+ {
+ // Create reference
+ SimpleTensor<T> src{ shape, data_type };
+ std::vector<SimpleTensor<T>> dsts;
+
+ // Fill reference
+ fill(src, 0);
+
+ unsigned int axis_offset{ 0 };
+ for(const auto &split_shape : split_shapes)
+ {
+ // Calculate splice for each split
+ const size_t axis_split_step = split_shape[axis];
+
+ // Start/End coordinates
+ Coordinates start_coords;
+ Coordinates end_coords;
+ for(unsigned int d = 0; d < shape.num_dimensions(); ++d)
+ {
+ end_coords.set(d, -1);
+ }
+
+ // Update coordinate on axis
+ start_coords.set(axis, axis_offset);
+ end_coords.set(axis, axis_offset + axis_split_step);
+
+ dsts.emplace_back(std::move(reference::slice(src, start_coords, end_coords)));
+
+ axis_offset += axis_split_step;
+ }
+
+ return dsts;
+ }
+
+ std::vector<TensorType> _target{};
+ std::vector<SimpleTensor<T>> _reference{};
+};
} // namespace validation
} // namespace test
} // namespace arm_compute