tf.contrib.learn.TensorFlowRNNRegressor.predict(x, axis=1, batch_size=None) Predict class or regression for x. For a classification model, the predicted class for each sample in x is returned. For a regression model, the predicted value based on x is returned. Args: x: array-like matrix, [n_samples, n_features...] or iterator. axis: Which axis to argmax for classification. By default axis 1 (next after batch) is used. Use 2 for sequence predictions. batch_size: If test set is too big, use b

tf.errors.OutOfRangeError.__init__(node_def, op, message) Creates an OutOfRangeError.

tf.contrib.learn.LinearClassifier.get_variable_value(name)

tf.contrib.distributions.MultivariateNormalFull.dtype The DType of Tensors handled by this Distribution.

tf.contrib.distributions.TransformedDistribution.dtype The DType of Tensors handled by this Distribution.

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.log_sigma_det(name='log_sigma_det') Log of determinant of covariance matrix.

tf.contrib.learn.DNNRegressor.export(*args, **kwargs) Exports inference graph into given dir. (deprecated arguments) SOME ARGUMENTS ARE DEPRECATED. They will be removed after 2016-09-23. Instructions for updating: The signature of the input_fn accepted by export is changing to be consistent with what's used by tf.Learn Estimator's train/evaluate. input_fn (and in most cases, input_feature_key) will become required args, and use_deprecated_input_fn will default to False and be removed altogethe

tf.contrib.distributions.Exponential.get_batch_shape() Shape of a single sample from a single event index as a TensorShape. Same meaning as batch_shape. May be only partially defined. Returns: batch_shape: TensorShape, possibly unknown.

tf.FixedLenFeature.__getnewargs__() Return self as a plain tuple. Used by copy and pickle.

tf.contrib.distributions.Categorical.is_continuous