Function create_array

python/paddle/tensor/array.py:309–379

This OP creates an array. It is used as the input of :ref:`api_paddle_tensor_array_array_read` and :ref:`api_paddle_tensor_array_array_write`. Args: dtype (str): The data type of the elements in the array. Support data type: float32, float64, int32, int64 and bool. init

(
    dtype: _typing.DTypeLike,
    initialized_list: Sequence[paddle.Tensor] | None = None,
)

def create_array(
    dtype: _typing.DTypeLike,
    initialized_list: Sequence[paddle.Tensor] | None = None,
) -> paddle.Tensor | list[paddle.Tensor]:
    """
    This OP creates an array. It is used as the input of :ref:`api_paddle_tensor_array_array_read` and
    :ref:`api_paddle_tensor_array_array_write`.

    Args:
        dtype (str): The data type of the elements in the array. Support data type: float32, float64, int32, int64 and bool.
        initialized_list(list): Used to initialize as default value for created array.
                    All values in initialized list should be a Tensor.

    Returns:
        list|Tensor, An empty array. In dynamic mode, ``array`` is a Python list. But in static graph mode, array is a Tensor
        whose ``VarType`` is ``DENSE_TENSOR_ARRAY``.

    Examples:
        .. code-block:: pycon

            >>> import paddle

            >>> arr = paddle.tensor.create_array(dtype="float32")
            >>> x = paddle.full(shape=[1, 3], fill_value=5, dtype="float32")
            >>> i = paddle.zeros(shape=[1], dtype="int32")

            >>> arr = paddle.tensor.array_write(x, i, array=arr)

            >>> item = paddle.tensor.array_read(arr, i)
            >>> print(item.numpy())
            [[5. 5. 5.]]

    """
    array = []
    if initialized_list is not None:
        if not isinstance(initialized_list, (list, tuple)):
            raise TypeError(
                f"Require type(initialized_list) should be list/tuple, but received {type(initialized_list)}"
            )
        array = list(initialized_list)

    # NOTE: Only support plain list like [x, y,...], not support nested list in static graph mode.
    for val in array:
        if not isinstance(val, (Variable, paddle.pir.Value)):
            raise TypeError(
                f"All values in `initialized_list` should be Variable or pir.Value, but received {type(val)}."
            )

    if in_dynamic_mode():
        return array
    elif in_pir_mode():
        if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
            dtype = paddle.base.framework.convert_np_dtype_to_dtype_(dtype)
        out = paddle._pir_ops.create_array(dtype)
        for val in array:
            if dtype != paddle.base.libpaddle.DataType.UNDEFINED:
                val = paddle.cast(val, dtype)
            paddle._pir_ops.array_write_(out, val, array_length(out))