class_docstr: Represents the output of a generic prediction head.
  
  A generic prediction need not be either a classification or a regression.
  
  Named outputs must be provided as a dict from string to `Tensor`,
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docstr: Constructor for PredictOutput.
  
  Args:
    outputs: A `Tensor` or a dict of string to `Tensor` representing the
      predictions.
  
  Raises:
    ValueError: if the outputs is not dict, or any of its keys are not
        strings, or any of its values are not `Tensor`s.
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code: def __init__(self, outputs):
      """Constructor for PredictOutput.
  
      Args:
        outputs: A `Tensor` or a dict of string to `Tensor` representing the
          predictions.
  
      Raises:
        ValueError: if the outputs is not dict, or any of its keys are not
            strings, or any of its values are not `Tensor`s.
      """
  
      self._outputs = self._wrap_and_check_outputs(
          outputs,
          self._SINGLE_OUTPUT_DEFAULT_NAME,
          error_label="Prediction",
      )
  
imports: import abc
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.keras.saving.utils_v1 import signature_def_utils
  from tensorflow.python.saved_model import signature_def_utils
label_desc: Use image node_id 1 to create a new PredictOutput object from inherited base classes: ExportOutput with example: obj = PredictOutput(outputs)