code: def decoder_block(
      in_chan: int, out_chan: int, stride: int, **kwargs: Any
  ) -> Sequential:
      """Creates a LinkNet decoder block"""
      return Sequential(
          [
              *conv_sequence(
                  in_chan // 4, "relu", True, kernel_size=1, **kwargs
              ),
              layers.Conv2DTranspose(
                  filters=in_chan // 4,
                  kernel_size=3,
                  strides=stride,
                  padding="same",
                  use_bias=False,
                  kernel_initializer="he_normal",
              ),
              layers.BatchNormalization(),
              layers.Activation("relu"),
              *conv_sequence(out_chan, "relu", True, kernel_size=1),
          ]
      )
  
imports: from copy import deepcopy
  from typing import Any, Dict, List, Optional, Tuple
  import numpy
  import tensorflow
  from tensorflow import keras
  from tensorflow.keras import Model, Sequential, layers
  from doctr.file_utils import CLASS_NAME
  from doctr.models.classification import resnet18, resnet34, resnet50
  from doctr.models.utils import IntermediateLayerGetter, _bf16_to_float32, conv_sequence, load_pretrained_params
  from doctr.utils.repr import NestedObject
  from .base import LinkNetPostProcessor, _LinkNet
label_desc: Use image node_id 1 for calling a global function with example usage: decoder_block(in_chan, out_chan, stride) and returns: Sequential