tests/datasets/ScatterDataset.h

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#ifndef ACL_TESTS_DATASETS_SCATTERDATASET_H
#define ACL_TESTS_DATASETS_SCATTERDATASET_H

#include "arm_compute/core/TensorShape.h"
#include "utils/TypePrinter.h"

namespace arm_compute
{
namespace test
{
namespace datasets
{

class ScatterDataset
{
public:
    using type = std::tuple<TensorShape, TensorShape, TensorShape, TensorShape>;

    struct iterator
    {
        iterator(std::vector<TensorShape>::const_iterator src_it,
                 std::vector<TensorShape>::const_iterator updates_it,
                 std::vector<TensorShape>::const_iterator indices_it,
                 std::vector<TensorShape>::const_iterator dst_it)
            : _src_it{ std::move(src_it) },
              _updates_it{ std::move(updates_it) },
              _indices_it{std::move(indices_it)},
              _dst_it{ std::move(dst_it) }
        {
        }

        std::string description() const
        {
            std::stringstream description;
            description << "A=" << *_src_it << ":";
            description << "B=" << *_updates_it << ":";
            description << "C=" << *_indices_it << ":";
            description << "Out=" << *_dst_it << ":";
            return description.str();
        }

        ScatterDataset::type operator*() const
        {
            return std::make_tuple(*_src_it, *_updates_it, *_indices_it, *_dst_it);
        }

        iterator &operator++()
        {
            ++_src_it;
            ++_updates_it;
            ++_indices_it;
            ++_dst_it;

            return *this;
        }

    private:
        std::vector<TensorShape>::const_iterator _src_it;
        std::vector<TensorShape>::const_iterator _updates_it;
        std::vector<TensorShape>::const_iterator _indices_it;
        std::vector<TensorShape>::const_iterator _dst_it;
    };

    iterator begin() const
    {
        return iterator(_src_shapes.begin(), _update_shapes.begin(), _indices_shapes.begin(), _dst_shapes.begin());
    }

    int size() const
    {
        return std::min(_src_shapes.size(), std::min(_indices_shapes.size(), std::min(_update_shapes.size(), _dst_shapes.size())));
    }

    void add_config(TensorShape a, TensorShape b, TensorShape c, TensorShape dst)
    {
        _src_shapes.emplace_back(std::move(a));
        _update_shapes.emplace_back(std::move(b));
        _indices_shapes.emplace_back(std::move(c));
        _dst_shapes.emplace_back(std::move(dst));
    }

protected:
    ScatterDataset()                 = default;
    ScatterDataset(ScatterDataset &&) = default;

private:
    std::vector<TensorShape> _src_shapes{};
    std::vector<TensorShape> _update_shapes{};
    std::vector<TensorShape> _indices_shapes{};
    std::vector<TensorShape> _dst_shapes{};
};


// 1D dataset for simple scatter tests.
class Small1DScatterDataset final : public ScatterDataset
{
public:
    Small1DScatterDataset()
    {
        add_config(TensorShape(6U), TensorShape(6U), TensorShape(1U, 6U), TensorShape(6U));
        add_config(TensorShape(10U), TensorShape(2U), TensorShape(1U, 2U), TensorShape(10U));
    }
};

// This dataset represents the (m+1)-D updates/dst case.
class SmallScatterMultiDimDataset final : public ScatterDataset
{
public:
    SmallScatterMultiDimDataset()
    {
        // NOTE: Config is src, updates, indices, output.
        //      - In this config, the dim replaced is the final number (largest tensor dimension)
        //      - Largest "updates" dim should match y-dim of indices.
        //      - src/updates/dst should all have same number of dims. Indices should be 2D.
        add_config(TensorShape(6U, 5U), TensorShape(6U, 2U), TensorShape(1U, 2U), TensorShape(6U, 5U));
        add_config(TensorShape(9U, 3U, 4U), TensorShape(9U, 3U, 2U), TensorShape(1U, 2U), TensorShape(9U, 3U, 4U));
        add_config(TensorShape(17U, 3U, 2U, 4U), TensorShape(17U, 3U, 2U, 7U), TensorShape(1U, 7U), TensorShape(17U, 3U, 2U, 4U));
    }
};

// This dataset represents the (m+1)-D updates tensor, (m+n)-d output tensor cases
class SmallScatterMultiIndicesDataset final : public ScatterDataset
{
public:
    SmallScatterMultiIndicesDataset()
    {
        // NOTE: Config is src, updates, indices, output.
        // NOTE: indices.shape.x = src.num_dimensions - updates.num_dimensions + 1

        // index length is 2
        add_config(TensorShape(6U, 5U, 2U), TensorShape(6U, 4U), TensorShape(2U, 4U), TensorShape(6U, 5U, 2U));
        add_config(TensorShape(17U, 3U, 3U, 2U), TensorShape(17U, 3U, 2U), TensorShape(2U, 2U), TensorShape(17U, 3U, 3U, 2U));
        add_config(TensorShape(11U, 3U, 3U, 2U, 4U), TensorShape(11U, 3U, 3U, 4U), TensorShape(2U, 4U), TensorShape(11U, 3U, 3U, 2U, 4U));
        add_config(TensorShape(5U, 4U, 3U, 3U, 2U, 4U), TensorShape(5U, 4U, 3U, 3U, 5U), TensorShape(2U, 5U), TensorShape(5U, 4U, 3U, 3U, 2U, 4U));

        // index length is 3
        add_config(TensorShape(4U, 3U, 2U, 2U), TensorShape(4U, 2U), TensorShape(3U, 2U), TensorShape(4U, 3U, 2U, 2U));
        add_config(TensorShape(17U, 4U, 3U, 2U, 2U), TensorShape(17U, 4U, 4U), TensorShape(3U, 4U), TensorShape(17U, 4U, 3U, 2U, 2U));
        add_config(TensorShape(10U, 4U, 5U, 3U, 2U, 2U), TensorShape(10U, 4U, 5U, 3U), TensorShape(3U, 3U), TensorShape(10U, 4U, 5U, 3U, 2U, 2U));

        // index length is 4
        add_config(TensorShape(35U, 4U, 3U, 2U, 2U), TensorShape(35U, 4U), TensorShape(4U, 4U), TensorShape(35U, 4U, 3U, 2U, 2U));
        add_config(TensorShape(10U, 4U, 5U, 3U, 2U, 2U), TensorShape(10U, 4U, 3U), TensorShape(4U, 3U), TensorShape(10U, 4U, 5U, 3U, 2U, 2U));

        // index length is 5
        add_config(TensorShape(10U, 4U, 5U, 3U, 2U, 2U), TensorShape(10U, 3U), TensorShape(5U, 3U), TensorShape(10U, 4U, 5U, 3U, 2U, 2U));
    }
};

// This dataset represents the (m+k)-D updates tensor, (k+1)-d indices tensor and (m+n)-d output tensor cases
class SmallScatterBatchedDataset final : public ScatterDataset
{
public:
    SmallScatterBatchedDataset()
    {
        // NOTE: Config is src, updates, indices, output.
        // NOTE: Updates/Indices tensors are now batched.
        // NOTE: indices.shape.x = (updates_batched) ? (src.num_dimensions - updates.num_dimensions) + 2 : (src.num_dimensions - updates.num_dimensions) + 1
        add_config(TensorShape(6U, 5U), TensorShape(6U, 2U, 2U), TensorShape(1U, 2U, 2U), TensorShape(6U, 5U));
        add_config(TensorShape(6U, 5U, 2U), TensorShape(6U, 2U, 2U), TensorShape(2U, 2U, 2U), TensorShape(6U, 5U, 2U));
        add_config(TensorShape(6U, 5U, 2U, 2U), TensorShape(3U, 2U), TensorShape(4U, 3U, 2U), TensorShape(6U, 5U, 2U, 2U));
        add_config(TensorShape(5U, 5U, 4U, 2U, 2U), TensorShape(6U, 2U), TensorShape(5U, 6U, 2U), TensorShape(5U, 5U, 4U, 2U, 2U));
    }
};
} // namespace datasets
} // namespace test
} // namespace arm_compute
#endif // ACL_TESTS_DATASETS_SCATTERDATASET_H