class tf.contrib.framework.VariableDeviceChooser Device chooser for variables. When using a parameter server it will assign them in a round-robin fashion. When not using a parameter server it allows GPU or CPU placement.

void tensorflow::Tensor::FillDescription(TensorDescription *description) const Fill in the TensorDescription proto with metadata about the tensor that is useful for monitoring and debugging.

tf.contrib.learn.monitors.ValidationMonitor.best_step Returns the step at which the best early stopping metric was found.

tf.contrib.bayesflow.stochastic_tensor.StudentTTensor.dtype

tf.contrib.distributions.Dirichlet.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32 Tensor. Args: name: name to give to the op Returns: event_shape: Tensor.

tf.contrib.graph_editor.matcher.__call__(op) Evaluate if the op matches or not.

tf.contrib.learn.TensorFlowRNNClassifier.bias_ Returns bias of the rnn layer.

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

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

tf.FixedLenFeature.default_value Alias for field number 2