

dilation -- the spacing between kernel elements. Can be a
        single number or a tuple (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, dtype=torch.float)
  >>> inputs = torch.randn(1, 4, 5, 5, dtype=torch.float)
  >>> bias = torch.randn(8, dtype=torch.float)
  >>>
  >>> scale, zero_point = 1.0, 0
  >>> dtype_inputs = torch.quint8
