class_docstr: A block containing multiple subsequent vgg style convolution stacks
  followed by flattening and a dense layer block.
  
  For details on the convolution part see :class:`~maze.perception.blocks.feed_forward.vgg_conv.VGGConvolutionBlock`.
  For details on flattening see :class:`~maze.perception.blocks.general.flatten.FlattenBlock`.
  For details on dense layers see :class:`~maze.perception.blocks.feed_forward.dense.DenseBlock`.
  
  :param in_keys: One key identifying the input tensors.
  :param out_keys: One key identifying the output tensors.
  :param in_shapes: List of input shapes.
  :param hidden_channels: List containing the number of hidden channels for hidden layers.
  :param hidden_units: List containing the number of hidden units for hidden layers.
  :param non_lin: The non-linearity to apply after each layer.
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code: def __repr__(self):
      txt = f"{VGGConvolutionDenseBlock.__name__}:"
      txt += f"\n\n{str(self.conv_block)}"
      txt += f"\n\n{str(self.flatten_block)}"
      txt += f"\n\n{str(self.dense_block)}"
      return txt
  
file_path: maze/maze/perception/blocks/joint_blocks/vgg_conv_dense.py
imports: from typing import Union, List, Sequence, Dict
  import torch
  from torch import nn
  from maze.core.annotations import override
  from maze.perception.blocks.base import PerceptionBlock
  from maze.perception.blocks.feed_forward.dense import DenseBlock
  from maze.perception.blocks.feed_forward.vgg_conv import VGGConvolutionBlock
  from maze.perception.blocks.general.flatten import FlattenBlock
label_desc: Use image node_id 3 for calling the VGGConvolutionDenseBlock obj's underlying member method code with example usage: obj.__repr__() and returns: txt