Function logspace

python/paddle/tensor/creation.py:556–748

r""" Return fixed number of logarithmically-evenly spaced values within the interval \ :math:`[base^{start}, base^{stop}]`. Notes: This API does not compute the gradient. Args: start(int|float|Tensor): The input :attr:`start` is exponent of first entry in \

(
    start: float | paddle.Tensor,
    stop: float | paddle.Tensor,
    num: int | paddle.Tensor,
    base: float | paddle.Tensor = 10.0,
    dtype: DTypeLike | None = None,
    name: str | None = None,
)

def logspace(
    start: float | paddle.Tensor,
    stop: float | paddle.Tensor,
    num: int | paddle.Tensor,
    base: float | paddle.Tensor = 10.0,
    dtype: DTypeLike | None = None,
    name: str | None = None,
) -> paddle.Tensor:
    r"""
    Return fixed number of logarithmically-evenly spaced values within the interval \
    :math:`[base^{start}, base^{stop}]`.

    Notes:
        This API does not compute the gradient.

    Args:
        start(int|float|Tensor): The input :attr:`start` is exponent of first entry in \
            the sequence. It is a scalar, or a 0-D Tensor of shape [] with input data \
            type int32, int64, float32 or float64.
        stop(int|float|Tensor): The input :attr:`stop` is exponent of last entry in the \
            sequence. It is a scalar, or a 0-D Tensor of shape [] with input data \
            type int32, int64, float32 or float64.
        num(int|Tensor): The input :attr:`num` is given number of items in the sequence. \
            It is an int scalar, or a 0-D Tensor of shape [] with data type int32.
        base(int|float|Tensor): The input :attr:`base` is base of the logarithm function. \
            It is a scalar, or a 0-D Tensor of shape [] with input data type int32, int64, \
            float32 or float64.
        dtype(str|paddle.dtype|np.dtype, optional): The data type of output tensor, it could be \
            int32, int64, float32 or float64. Default: if None, the data type is float32. \
        name(str|None, optional): For details, please refer to :ref:`api_guide_Name`. Generally, no setting is required. Default: None.

    Returns:
        Tensor: The output data type will be float32, float64. The 1-D tensor with \
        fixed number of logarithmically-evenly spaced values, the data shape of this \
        tensor is :math:`[num]`. If the :attr:`num` is set 1, the output tensor \
        just has the value with exponential of :attr:`start` with base :attr:`base`.

    Examples:
        .. code-block:: pycon

            >>> import paddle
            >>> data = paddle.logspace(0, 10, 5, 2, 'float32')
            >>> print(data.numpy())
            [1.0000000e+00 5.6568542e+00 3.2000000e+01 1.8101933e+02 1.0240000e+03]
            >>> data = paddle.logspace(0, 10, 1, 2, 'float32')
            >>> print(data.numpy())
            [1.]
    """
    if dtype is None:
        dtype = paddle.get_default_dtype()
    tensor_num = num
    tensor_start = start
    tensor_stop = stop
    tensor_base = base
    if not isinstance(num, (Variable, paddle.pir.Value)):
        check_type(num, 'num', (int), 'logspace')
    if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
        dtype = convert_np_dtype_to_dtype_(dtype)