class_docstr: A class to remove ``script_mode`` from TensorFlow estimators (because it's the only mode).
docstr: Checks if the ``ast.Call`` node instantiates a TensorFlow estimator.
  
  TensorFlow estimator would use``script_mode`` set. This looks for the following formats:
  
  - ``TensorFlow``
  - ``sagemaker.tensorflow.TensorFlow``
  
  Args:
      node (ast.Call): a node that represents a function call. For more,
          see https://docs.python.org/3/library/ast.html#abstract-grammar.
  
  Returns:
      bool: If the ``ast.Call`` is instantiating a TensorFlow estimator with ``script_mode``.
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code: def node_should_be_modified(self, node):
      """Checks if the ``ast.Call`` node instantiates a TensorFlow estimator.
  
      TensorFlow estimator would use``script_mode`` set. This looks for the following formats:
  
      - ``TensorFlow``
      - ``sagemaker.tensorflow.TensorFlow``
  
      Args:
          node (ast.Call): a node that represents a function call. For more,
              see https://docs.python.org/3/library/ast.html#abstract-grammar.
  
      Returns:
          bool: If the ``ast.Call`` is instantiating a TensorFlow estimator with ``script_mode``.
      """
      is_tf_constructor = matching.matches_name_or_namespaces(
          node, "TensorFlow", TF_NAMESPACES
      )
      return is_tf_constructor and self._has_script_mode_param(node)
  
imports: from __future__ import absolute_import
  from sagemaker.cli.compatibility.v2.modifiers import matching
  from sagemaker.cli.compatibility.v2.modifiers.modifier import Modifier
label_desc: Use image node_id 1 for calling the TensorFlowScriptModeParameterRemover obj's underlying member method code with example usage: obj.node_should_be_modified(node) and returns: unknown