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tf.contrib.learn.TensorFlowRNNRegressor

class tf.contrib.learn.TensorFlowRNNRegressor

TensorFlow RNN Regressor model.

Links:

https://www.tensorflow.org/versions/master/api_docs/python/contrib.learn.html#TensorFlowRNNRegressor

doc_TensorFlow

2016-10-14 13:07:03

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

tf.contrib.learn.TensorFlowRNNRegressor.config tf.contrib.learn.TensorFlowRNNRegressor.config

tf.contrib.learn.TensorFlowRNNRegressor.weights_ tf.contrib.learn.TensorFlowRNNRegressor.weights_ Returns weights of the rnn layer.

tf.contrib.learn.TensorFlowRNNRegressor.fit() tf.contrib.learn.TensorFlowRNNRegressor.fit(x, y, steps=None, monitors=None, logdir=None) Neural network model from provided model_fn and training d

tf.contrib.learn.TensorFlowRNNRegressor.save() tf.contrib.learn.TensorFlowRNNRegressor.save(path) Saves checkpoints and graph to given path. Args: path: Folder to save model to.