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[luci-interpreter] Relax StrideSlice rank limitations #14507

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Jan 2, 2025
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[luci-interpreter] Relax StrideSlice rank limitations #14507

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2 changes: 1 addition & 1 deletion compiler/luci-interpreter/src/kernels/StridedSlice.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -44,7 +44,7 @@ void StridedSlice::configure()
assert(begin()->element_type() == DataType::S32);
assert(end()->element_type() == DataType::S32);
assert(strides()->element_type() == DataType::S32);
assert(input()->shape().num_dims() <= 4);
assert(input()->shape().num_dims() <= 5);
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It is already supported in TF2.8 - https://github.com/tensorflow/tensorflow/blob/3f878cff5b698b82eea85db2b60d65a2e320850e/tensorflow/lite/kernels/internal/strided_slice_logic.h#L39
(introduced in tensorflow/tensorflow@bd9e81f)

if (params().ellipsis_mask != 0)
{
throw std::runtime_error("ellipsis_mask is not implemented yet.");
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44 changes: 44 additions & 0 deletions compiler/luci-interpreter/src/kernels/StridedSlice.test.cpp
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Expand Up @@ -18,6 +18,8 @@
#include "kernels/TestUtils.h"
#include "luci_interpreter/TestMemoryManager.h"

#include <numeric>

namespace luci_interpreter
{
namespace kernels
Expand Down Expand Up @@ -107,6 +109,48 @@ TEST(StridedSliceTest, Uint8)
EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(output_shape));
}

TEST(StridedSliceTest, 5DCase)
{
std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();

Shape input_shape{2, 3, 2, 2, 3};
std::vector<float> input_data(input_shape.num_elements());
std::iota(std::begin(input_data), std::end(input_data), 0);
Shape begin_shape{5};
std::vector<int32_t> begin_data{0, 0, 0, 0, 0};
Shape end_shape{5};
std::vector<int32_t> end_data{2, 3, 2, 2, 1};
Shape strides_shape{5};
std::vector<int32_t> strides_data{1, 1, 1, 1, 1};
Tensor input_tensor =
makeInputTensor<DataType::U8>(input_shape, 1.0f, 0, input_data, memory_manager.get());
Tensor begin_tensor =
makeInputTensor<DataType::S32>(begin_shape, begin_data, memory_manager.get());
Tensor end_tensor = makeInputTensor<DataType::S32>(end_shape, end_data, memory_manager.get());
Tensor strides_tensor =
makeInputTensor<DataType::S32>(strides_shape, strides_data, memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::U8, 1.0f, 0);

StridedSliceParams params{};
params.begin_mask = 0;
params.end_mask = 0;
params.ellipsis_mask = 0;
params.new_axis_mask = 0;
params.shrink_axis_mask = 0;

StridedSlice kernel(&input_tensor, &begin_tensor, &end_tensor, &strides_tensor, &output_tensor,
params);
kernel.configure();
memory_manager->allocate_memory(output_tensor);
kernel.execute();

std::vector<int32_t> output_shape{2, 3, 2, 2, 1};
std::vector<float> output_data{0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33,
36, 39, 42, 45, 48, 51, 54, 57, 60, 63, 66, 69};
EXPECT_THAT(dequantizeTensorData(output_tensor), FloatArrayNear(output_data));
EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(output_shape));
}

} // namespace
} // namespace kernels
} // namespace luci_interpreter