    The attributes that will be lazily initialized are `weight` and `bias`.

    Check the :class:`torch.nn.modules.lazy.LazyModuleMixin` for further documentation
    on lazy modules and their limitations.

    Args:
        out_channels (int): Number of channels produced by the convolution
        kernel_size (int or tuple): Size of the convolving kernel
        stride (int or tuple, optional): Stride of the convolution. Default: 1
        padding (int or tuple, optional): Zero-padding added to both sides of
            the input. Default: 0
        padding_mode (str, optional): ``'zeros'``, ``'reflect'``,
            ``'replicate'`` or ``'circular'``. Default: ``'zeros'``
        dilation (int or tuple, optional): Spacing between kernel
            elements. Default: 1
        groups (int, optional): Number of blocked connections from input
            channels to output channels. Default: 1
        bias (bool, optional): If ``True``, adds a learnable bias to the
            output. Default: ``True``

    .. seealso:: :class:`torch.nn.Conv2d` and :class:`torch.nn.modules.lazy.LazyModuleMixin`
    r