docstr: Generalized Tensorflow placeholder. The main differences are:
  - possibly uses multiple placeholders internally and returns multiple values
  - can apply light postprocessing to the value feed to placeholder.
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code: def __init__(self, name="(unnamed)"):
      """Generalized Tensorflow placeholder. The main differences are:
      - possibly uses multiple placeholders internally and returns multiple values
      - can apply light postprocessing to the value feed to placeholder.
      """
      self.name = name
  
file_path: baselines/baselines/deepq/utils.py
imports: from baselines.common.input import observation_input
  from baselines.common.tf_util import adjust_shape
label_desc: Use image node_id 1 to create a new TfInput object from inherited base classes: object with example: obj = TfInput(name)