Function gaussian

python/paddle/tensor/random.py:628–746

Returns a Tensor filled with random values sampled from a Gaussian distribution, with ``shape`` and ``dtype``. Args: shape (tuple|list|Tensor): Shape of the Tensor to be created. The data type is ``int32`` or ``int64`` . If ``shape`` is a list or tuple, each element

(
    shape: ShapeLike,
    mean: complex = 0.0,
    std: float = 1.0,
    seed: int = 0,
    dtype: DTypeLike | None = None,
    name: str | None = None,
    *,
    out: paddle.Tensor | None = None,
    device: PlaceLike | None = None,
    requires_grad: bool = False,
)

def gaussian(
    shape: ShapeLike,
    mean: complex = 0.0,
    std: float = 1.0,
    seed: int = 0,
    dtype: DTypeLike | None = None,
    name: str | None = None,
    *,
    out: paddle.Tensor | None = None,
    device: PlaceLike | None = None,
    requires_grad: bool = False,
) -> Tensor:
    """
    Returns a Tensor filled with random values sampled from a Gaussian
    distribution, with ``shape`` and ``dtype``.

    Args:
        shape (tuple|list|Tensor): Shape of the Tensor to be created. The data type is ``int32`` or ``int64`` .
            If ``shape`` is a list or tuple, each element of it should be integer or 0-D Tensor with shape [].
            If ``shape`` is an Tensor, it should be an 1-D Tensor which represents a list.
        mean (float|int|complex, optional): Mean of the output tensor, default is 0.0.
        std (float|int, optional): Standard deviation of the output tensor, default
            is 1.0.
        seed (int, optional): Random seed of generator.
        dtype (str|np.dtype|paddle.dtype|None, optional): The data type of the output Tensor.
            Supported data types: bfloat16, float16, float32, float64, complex64, complex128.
            Default is None, use global default dtype (see ``get_default_dtype``
            for details).
        name (str|None, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
        out(Tensor, optional): The output tensor.
        device(PlaceLike|None, optional): The desired device of returned tensor.
            if None, uses the current device for the default tensor type (see paddle.device.set_device()).
            device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types. Default: None.
        requires_grad(bool, optional):  If autograd should record operations on the returned tensor. Default: False.

    Returns:
        Tensor, A Tensor filled with random values sampled from a Gaussian
            distribution, with ``shape`` and ``dtype``.
    """
    op_type_for_check = 'gaussian/standard_normal/randn/normal'
    supported_dtypes = [
        'float32',
        'float64',
        'float16',
        'uint16',
        'bfloat16',
        'complex64',
        'complex128',
    ]

    if dtype is None:
        dtype = paddle.framework.get_default_dtype()
        if dtype not in supported_dtypes:
            raise TypeError(
                f"{op_type_for_check} only supports {supported_dtypes}, but the default dtype is {dtype}"
            )
    if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
        dtype = convert_np_dtype_to_dtype_(dtype)