def std(x, axis=None, keepdims=False):
    """Compute the standard deviation along the specified axis.

    Args:
        x: Input tensor.
        axis: Axis along which to compute standard deviation.
            Default is to compute the standard deviation of the
            flattened tensor.
        keepdims: If this is set to `True`, the axes which are reduced are left
            in the result as dimensions with size one.

    Returns:
        Output tensor containing the standard deviation values.
    """
    if any_symbolic_tensors((x,)):
        return Std(axis=axis, keepdims=keepdims).symbolic_call(x)
    return backend.numpy.std(x, axis=axis, keepdims=keepdims)
Compute the standard deviation along the specified axis.

    Args:
        x: Input tensor.
        axis: Axis along which to compute standard deviation.
            Default is to compute the standard deviation of the
            flattened tensor.
        keepdims: If this is set to `True`, the axes which are reduced are left
            in the result as dimensions with size one.

    Returns:
        Output tensor containing the standard deviation values.
    
keras/src/ops/numpy.py