code: def __init__(self, c0, c1):
      self.upsample_conv = [
          nn.ConvTranspose2d(c0, c1, kernel_size=(2, 2, 2), stride=2)
      ]
      self.conv1 = [
          nn.Conv2d(
              2 * c1,
              c1,
              kernel_size=(3, 3, 3),
              padding=(1, 1, 1, 1, 1, 1),
              bias=False,
          ),
          nn.InstanceNorm(c1),
          Tensor.relu,
      ]
      self.conv2 = [
          nn.Conv2d(
              c1,
              c1,
              kernel_size=(3, 3, 3),
              padding=(1, 1, 1, 1, 1, 1),
              bias=False,
          ),
          nn.InstanceNorm(c1),
          Tensor.relu,
      ]
  
file_path: tinygrad/extra/models/unet3d.py
imports: from pathlib import Path
  import torch
  from tinygrad import nn
  from tinygrad.tensor import Tensor
  from tinygrad.helpers import fetch, get_child
label_desc: Use image node_id 1 to create a new UpsampleBlock object  with example: obj = UpsampleBlock(c0, c1)