code: def ragged_ge(self, other):  # pylint: disable=g-doc-args
      """Elementwise `>=` comparison of two convertible-to-ragged-tensor values.
  
      Computes the elemewise `>=` comparison of two values that are convertible to
      ragged tenors, with [broadcasting]
      (http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html) support.
      Raises an exception if two values are not broadcast-compatible.
  
      For example:
  
      >>> rt1 = tf.ragged.constant([[1, 2], [3]])
      >>> rt1 >= rt1
      <tf.RaggedTensor [[True, True], [True]]>
  
      >>> rt2 = tf.ragged.constant([[2, 1], [3]])
      >>> rt1 >= rt2
      <tf.RaggedTensor [[False, True], [True]]>
  
      >>> rt3 = tf.ragged.constant([[1, 2], [3, 4]])
      >>> # rt1 and rt3 are not broadcast-compatible.
      >>> rt1 >= rt3
      Traceback (most recent call last):
      ...
      InvalidArgumentError: ...
  
      >>> # You can also compare a `tf.RaggedTensor` to a `tf.Tensor`.
      >>> rt4 = tf.ragged.constant([[1, 2],[3, 4]])
      >>> t1 = tf.constant([[2, 1], [4, 3]])
      >>> rt4 >= t1
      <tf.RaggedTensor [[False, True],
       [False, True]]>
      >>> t1 >= rt4
      <tf.RaggedTensor [[True, False],
       [True, False]]>
  
      >>> # Compares a `tf.RaggedTensor` to a `tf.Tensor` with broadcasting.
      >>> t2 = tf.constant([[2]])
      >>> rt4 >= t2
      <tf.RaggedTensor [[False, True],
       [True, True]]>
      >>> t2 >= rt4
      <tf.RaggedTensor [[True, True],
       [False, False]]>
  
      Args:
        other: The right-hand side of the `>=` operator.
  
      Returns:
        A `tf.RaggedTensor` of dtype `tf.bool` with the shape that `self` and
        `other` broadcast to.
  
      Raises:
        InvalidArgumentError: If `self` and `other` are not broadcast-compatible.
      """
      return math_ops.greater_equal(self, other)
  
file_path: tensorflow/tensorflow/python/ops/ragged/ragged_operators.py
imports: from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.ragged import ragged_getitem
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.util import tf_decorator
label_desc: Use image node_id 2 for calling a global function with example usage: ragged_ge(other) and returns: math_ops