tf.contrib.learn.RunConfig.__init__(master=None, task=None, num_ps_replicas=None, num_cores=0, log_device_placement=False, gpu_memory_fraction=1, cluster_spec=None,

virtual Status tensorflow::RandomAccessFile::Read(uint64 offset, size_t n, StringPiece *result, char *scratch) const =0 Reads

tf.contrib.training.SequenceQueueingStateSaver.barrier

tf.TensorArray.handle The reference to the TensorArray.

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.event_shape(name='event_shape') Shape of a single sample from a single

virtual Status tensorflow::Env::GetSymbolFromLibrary(void *handle, const char *symbol_name, void **symbol)=0

tf.contrib.learn.monitors.LoggingTrainable.every_n_post_step(step, session) Callback after a step is finished or end()

tf.contrib.bayesflow.stochastic_tensor.StudentTWithAbsDfSoftplusSigmaTensor.distribution

tf.contrib.learn.TensorFlowRNNClassifier.__init__(rnn_size, n_classes, cell_type='gru', num_layers=1, input_op_fn=null_input_op_fn, initial_state=None, bidirectional=False

tf.contrib.graph_editor.sgv_scope(scope, graph) Make a subgraph from a name scope. Args: