998b0e8f1c3ec165fc1ca7b6421c96b1c72ec297,tensorflow_transform/analyzers.py,Analyzer,__init__,#Analyzer#Any#Any#Any#Any#,116

Before Change

    with tf.name_scope(name) as scope:
      self._name = scope
      for dtype, shape, is_asset in output_dtype_shape_and_is_asset:
        output_tensor = tf.placeholder(dtype, shape)
        if is_asset and output_tensor.dtype != tf.string:
          raise ValueError(("Tensor {} cannot represent an asset, because it "
                            "is not a string.").format(output_tensor.name))
        self._output_infos.append(_AnalyzerOutputInfo(

After Change

    for index, tensor in enumerate(outputs):
      if not isinstance(tensor, tf.Tensor):
        raise ValueError(
            "In analyzer {}, the {}th output ({}) was not a Tensor".format(
                name, index, tensor))
    self._inputs = inputs
    self._outputs = outputs
    self._spec = spec

Instances