conv2d
class torch.ao.nn.quantized.functional.conv2d(input, weight, bias, stride=1, padding=0, dilation=1, groups=1, padding_mode='zeros', scale=1.0, zero_point=0, dtype=torch.quint8)
Applies a 2D convolution over a quantized 2D input composed of
   several input planes.
See "Conv2d" for details and output shape.
Parameters:
      * input -- quantized input tensor of shape (\text{minibatch}
        , \text{in_channels} , iH , iW)
  * **weight** -- quantized filters of shape (\text{out\_channels}
    , \frac{\text{in\_channels}}{\text{groups}} , kH , kW)

  * **bias** -- **non-quantized** bias tensor of shape
    (\text{out\_channels}). The tensor type must be *torch.float*.

  * **stride** -- the stride of the convolving kernel. Can be a
    single number or a tuple *(sH, sW)*. Default: 1

  * **padding** -- implicit paddings on both sides of the input.
    Can be a single number or a tuple *(padH, padW)*. Default: 0
