tf.contrib.learn.DNNClassifier.predict_proba(*args, **kwargs) Returns prediction probabilities for given features. (deprecated arguments) SOME ARGUMENTS ARE DEPRECATED. They will be removed after 2016-09-15. Instructions for updating: The default behavior of predict() is changing. The default value for as_iterable will change to True, and then the flag will be removed altogether. The behavior of this flag is described below. Args: x: features. input_fn: Input function. If set, x and y must

tf.contrib.distributions.LaplaceWithSoftplusScale.__init__(loc, scale, validate_args=False, allow_nan_stats=True, name='LaplaceWithSoftplusScale')

tf.contrib.learn.Estimator.get_params(deep=True) Get parameters for this estimator. Args: deep: boolean, optional If True, will return the parameters for this estimator and contained subobjects that are estimators. Returns: params : mapping of string to any Parameter names mapped to their values.

tf.contrib.learn.LinearRegressor.get_params(deep=True) Get parameters for this estimator. Args: deep: boolean, optional If True, will return the parameters for this estimator and contained subobjects that are estimators. Returns: params : mapping of string to any Parameter names mapped to their values.

tf.contrib.distributions.MultivariateNormalFull.mu

tf.contrib.graph_editor.filter_ops_from_regex(ops, regex) Get all the operations that match the given regex. Args: ops: an object convertible to a list of tf.Operation. regex: a regular expression matching the operation's name. For example, "^foo(/.*)?$" will match all the operations in the "foo" scope. Returns: A list of tf.Operation. Raises: TypeError: if ops cannot be converted to a list of tf.Operation.

class tf.contrib.rnn.AttentionCellWrapper Basic attention cell wrapper. Implementation based on https://arxiv.org/pdf/1601.06733.pdf.

tf.contrib.rnn.GRUBlockCell.zero_state(batch_size, dtype) Return zero-filled state tensor(s). Args: batch_size: int, float, or unit Tensor representing the batch size. dtype: the data type to use for the state. Returns: If state_size is an int or TensorShape, then the return value is a N-D tensor of shape [batch_size x state_size] filled with zeros. If state_size is a nested list or tuple, then the return value is a nested list or tuple (of the same structure) of 2-D tensors with the shape

tf.contrib.bayesflow.stochastic_tensor.LaplaceWithSoftplusScaleTensor.name

tf.contrib.learn.extract_pandas_matrix(data) Extracts numpy matrix from pandas DataFrame. Args: data: pandas.DataFrame containing the data to be extracted. Returns: A numpy ndarray of the DataFrame's values.