tf.contrib.bayesflow.stochastic_tensor.CategoricalTensor.loss(final_loss, name='Loss')

tf.contrib.bayesflow.stochastic_tensor.StudentTWithAbsDfSoftplusSigmaTensor.entropy(name='entropy')

tf.contrib.learn.monitors.CaptureVariable.set_estimator(estimator) A setter called automatically by the target estimator. If the estimator is locked, this method does nothing. Args: estimator: the estimator that this monitor monitors. Raises: ValueError: if the estimator is None.

tf.contrib.framework.is_tensor(x) Check for tensor types. Check whether an object is a tensor. Equivalent to isinstance(x, [tf.Tensor, tf.SparseTensor, tf.Variable]). Args: x: An python object to check. Returns: True if x is a tensor, False if not.

tf.contrib.distributions.Categorical.get_event_shape() Shape of a single sample from a single batch as a TensorShape. Same meaning as event_shape. May be only partially defined. Returns: event_shape: TensorShape, possibly unknown.

tf.nn.rnn_cell.BasicLSTMCell.state_size

tf.contrib.bayesflow.stochastic_tensor.BernoulliWithSigmoidPTensor.mean(name='mean')

tf.FixedLenFeature.default_value Alias for field number 2

tf.contrib.bayesflow.stochastic_tensor.DirichletMultinomialTensor.mean(name='mean')

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, attn_length=None, attn_size=None, attn_vec_size=None, n_classes=0, batch_size=32, steps=50, optimizer='Adagrad', learning_rate=0.1, clip_gradients=5.0, continue_training=False, config=None, verbose=1) Initializes a TensorFlowRNNRegressor instance. Args: rnn_size: The size for rnn cell, e.g. size of your word embe