class_docstr: Flattens the input. Does not affect the batch size.
  If inputs are shaped `(batch,)` without a channel dimension, then flattening
  adds an extra channel dimension and output shapes are `(batch, 1)`.
  Arguments:
      data_format: A string,
          one of `channels_last` (default) or `channels_first`.
          The ordering of the dimensions in the inputs.
          `channels_last` corresponds to inputs with shape
          `(batch, ..., channels)` while `channels_first` corresponds to
          inputs with shape `(batch, channels, ...)`.
          If you never set it, then it will be "channels_last".
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code: def build(self, input_shape):
      self.built = True
  
file_path: tf-encrypted/tf_encrypted/keras/layers/flatten.py
imports: import numpy
  from tensorflow.python.keras.utils import conv_utils
  import tf_encrypted
  from tf_encrypted.keras.engine import Layer
label_desc: Use image node_id 2 for calling the Flatten obj's underlying member method code with example usage: obj.build(input_shape) without return types