code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size,
      stride=1,
      padding=0,
      dilation=1,
      groups=1,
      bias=True,
  ):
      self.kernel_size = (
          (kernel_size, kernel_size)
          if isinstance(kernel_size, int)
          else tuple(kernel_size)
      )
      self.stride, self.padding, self.dilation, self.groups = (
          stride,
          padding,
          dilation,
          groups,
      )
      self.weight = self.initialize_weight(
          out_channels, in_channels, groups
      )
      bound = 1 / math.sqrt(
          cast(int, prod(self.weight.shape[1:]))
      )  # weight shape is always ints but mypy cannot tell
      self.bias = (
          Tensor.uniform(out_channels, low=-bound, high=bound)
          if bias
          else None
      )
  
imports: import math
  from typing import Optional, Union, Tuple, cast
  from tinygrad.tensor import Tensor
  from tinygrad.helpers import prod
  from tinygrad.nn import optim, state
label_desc: Use image node_id 1 to create a new Conv2d object  with example: obj = Conv2d(in_channels, out_channels, kernel_size, stride, padding, dilation, groups, bias)