code: def Flatten(n_axes_to_keep=1):
      """Returns a layer that combines one or more trailing axes of a tensor.
  
      Flattening keeps all the values of the input tensor, but reshapes it by
      collapsing one or more trailing axes into a single axis. For example, a
      `Flatten(n_axes_to_keep=2)` layer would map a tensor with shape
      `(2, 3, 5, 7, 11)` to the same values with shape `(2, 3, 385)`.
  
      Args:
        n_axes_to_keep: Number of leading axes to leave unchanged when reshaping;
            collapse only the axes after these.
      """
      layer_name = f"Flatten_keep{n_axes_to_keep}"
  
      def f(x):  # pylint: disable=invalid-name
          in_rank = len(x.shape)
          if in_rank <= n_axes_to_keep:
              raise ValueError(
                  f"Input rank ({in_rank}) must exceed the number of "
                  f"axes to keep ({n_axes_to_keep}) after flattening."
              )
          shape = x.shape
          if isinstance(shape, tf.TensorShape):
              shape = tuple(shape.as_list())
          return jnp.reshape(x, (shape[:n_axes_to_keep] + (-1,)))
  
      return Fn(layer_name, f)
  
imports: from absl import logging
  import numpy
  import tensorflow
  from trax import fastmath
  from trax.fastmath import numpy
  from trax.layers import base
  from trax.layers import initializers
  from trax.layers.assert_shape import assert_shape
  from trax.layers.base import Fn
label_desc: Use image node_id 2 for calling a global function with example usage: Flatten(n_axes_to_keep) and returns: Fn, jnp