code: def parse_flatten_layer(
      keras_layer, input_names, input_shapes, data_reader
  ):
      assert keras_layer["class_name"] == "Flatten"
  
      layer = parse_default_keras_layer(keras_layer, input_names)
  
      layer["class_name"] = "Reshape"
      layer["target_shape"] = [
          input_shapes[0][0],
          np.prod(input_shapes[0][1:]),
      ]
      output_shape = layer["target_shape"]
  
      return layer, output_shape
  
file_path: hls4ml/hls4ml/converters/keras/reshape.py
imports: import numpy
  from hls4ml.converters.keras_to_hls import keras_handler, parse_default_keras_layer
  from hls4ml.converters.utils import parse_data_format
label_desc: Use image node_id 1 for calling a global function with example usage: parse_flatten_layer(keras_layer, input_names, input_shapes, data_reader) and returns: layer,  output_shape