tf.contrib.learn.LinearClassifier.evaluate(x=None, y=None, input_fn=None, feed_fn=None, batch_size=None, steps=None, metrics=None, name=None)

tf.contrib.learn.LinearRegressor.config

tf.contrib.learn.TensorFlowRNNRegressor.__init__(rnn_size, cell_type='gru', num_layers=1, input_op_fn=null_input_op_fn, initial_state=None, bidirectional=False, sequence_length=None

tf.contrib.learn.DNNRegressor.linear_bias_ Returns bias of the linear part.

tf.contrib.learn.DNNRegressor.partial_fit(x=None, y=None, input_fn=None, steps=1, batch_size=None, monitors=None) Incremental

tf.contrib.learn.run_n(output_dict, feed_dict=None, restore_checkpoint_path=None, n=1) Run output_dict tensors n

tf.contrib.learn.evaluate(graph, output_dir, checkpoint_path, eval_dict, update_op=None, global_step_tensor=None, supervisor_master='', log_every_steps=10, feed_fn=None

tf.contrib.learn.read_batch_examples(file_pattern, batch_size, reader, randomize_input=True, num_epochs=None, queue_capacity=10000, num_threads=1, read_batch_size=1

tf.contrib.learn.Estimator.export(*args, **kwargs) Exports inference graph into given dir. (deprecated arguments)

tf.contrib.learn.DNNRegressor.export(*args, **kwargs) Exports inference graph into given dir. (deprecated arguments)