Slice

The slice operation extracts a portion of a tensor:

\( Y = X[start_0:end_0, start_1:end_1, ..., start_n:end_n] \)

Where \(X\) is the input tensor, \(Y\) is the output tensor, and \(start_i\) and \(end_i\) are the start and end indices for the \(i\)-th dimension.

The operation allows for flexible slicing across any number of dimensions, supporting Python-style slice syntax including start, stop, and step parameters.

C++ API

std::shared_ptr<Tensor_attributes>
Slice(std::shared_ptr<Tensor_attributes> input, Slice_attributes);

Slice attributes is a lightweight structure with setters:

Slice_attributes&
set_slices(std::vector<std::pair<int64_t, int64_t>> const value)

Slice_attributes&
set_name(std::string const&)

Slice_attributes&
set_compute_data_type(DataType_t value)

Python API:

• slice

  • input

    • The input tensor to be sliced

  • slices

    • A list of Python slice objects, one for each dimension

  • name

    • Optional name for the operation

  • compute_data_type

    • Optional compute data type for the operation

Example usage:

# Create an input tensor

input_tensor = graph.tensor(dims = [4, 8, 16])

# Perform slicing
sliced_tensor = graph.slice(input_tensor, 
                            slices=[slice(1, 3), slice(2, 6), slice(0, 16)],
                            name="my_slice",
                            compute_data_type=cudnn.float32)