docstr: An image embedder is an input embedder that takes an image input from the state and produces a vector
  embedding by passing it through a neural network.
  
  :param params: parameters object containing input_clipping, input_rescaling, batchnorm, activation_function
      and dropout properties.
code: def __init__(self, params: InputEmbedderParameters):
      """
      An image embedder is an input embedder that takes an image input from the state and produces a vector
      embedding by passing it through a neural network.
  
      :param params: parameters object containing input_clipping, input_rescaling, batchnorm, activation_function
          and dropout properties.
      """
      super(ImageEmbedder, self).__init__(params)
      self.input_rescaling = params.input_rescaling["image"]
      self.input_offset = params.input_offset["image"]
  
file_path: coach/rl_coach/architectures/mxnet_components/embedders/image_embedder.py
imports: from typing import Union
  from types import ModuleType
  import mxnet
  from rl_coach.architectures.embedder_parameters import InputEmbedderParameters
  from rl_coach.architectures.mxnet_components.embedders.embedder import InputEmbedder
  from rl_coach.architectures.mxnet_components.layers import Conv2d
  from rl_coach.base_parameters import EmbedderScheme
label_desc: Use image node_id 1 to create a new ImageEmbedder object from inherited base classes: InputEmbedder with example: obj = ImageEmbedder(params)