train_lstm.py 文件源码

def __init__(self, num_units, num_features, dtype=tf.float32):
    """Initialize/configure the model object.
    Note that we do not start graph building here. Rather, this object is a
    configurable factory for TensorFlow graphs which are run by an Estimator.
    Args:
      num_units: The number of units in the model's LSTMCell.
      num_features: The dimensionality of the time series (features per
        timestep).
      dtype: The floating point data type to use.
    """
    super(_LSTMModel, self).__init__(
        # Pre-register the metrics we'll be outputting (just a mean here).
        train_output_names=["mean"],
        predict_output_names=["mean"],
        num_features=num_features,
        dtype=dtype)
    self._num_units = num_units
    # Filled in by initialize_graph()
    self._lstm_cell = None
    self._lstm_cell_run = None
    self._predict_from_lstm_output = None