Default: 0
  * **dilation** -- the spacing between kernel elements. Can be a
    single number or a tuple *(dD, dH, dW)*. Default: 1

  * **groups** -- split input into groups, \text{in\_channels}
    should be divisible by the number of groups. Default: 1

  * **padding_mode** -- the padding mode to use. Only "zeros" is
    supported for quantized convolution at the moment. Default:
    "zeros"

  * **scale** -- quantization scale for the output. Default: 1.0

  * **zero_point** -- quantization zero_point for the output.
    Default: 0

  * **dtype** -- quantization data type to use. Default:
    "torch.quint8"

Examples:
  >>> from torch.ao.nn.quantized import functional as qF
  >>> filters = torch.randn(8, 4, 3, 3, 3, dtype=torch.float)
  >>> inputs = torch.randn(1, 4, 5, 5, 5, dtype=torch.float)
  >>> bias = torch.randn(8, dtype=torch.float)
  >>>
  >>> scale, zero_point = 1.0, 0
  >>> dtype_inputs = torch.quint8
