class tf.contrib.learn.monitors.PrintTensor Prints given tensors every N steps. This is an EveryN monitor and has consistent semantic for every_n and first_n. The tensors will be printed to the log, with INFO severity.

tf.contrib.learn.TensorFlowRNNRegressor.weights_ Returns weights of the rnn layer.

tf.contrib.learn.monitors.GraphDump.post_step(step, session) Callback after the step is finished. Called after step_end and receives session to perform extra session.run calls. If failure occurred in the process, will be called as well. Args: step: int, global step of the model. session: Session object.

tf.contrib.graph_editor.SubGraphView.graph The underlying tf.Graph.

tf.contrib.distributions.Multinomial.is_continuous

tf.contrib.framework.get_model_variables(scope=None, suffix=None) Gets the list of model variables, filtered by scope and/or suffix. Args: scope: an optional scope for filtering the variables to return. suffix: an optional suffix for filtering the variables to return. Returns: a list of variables in collection with scope and suffix.

tf.contrib.distributions.Laplace.std(name='std') Standard deviation.

tf.contrib.learn.LinearRegressor.linear_weights_ Returns weights per feature of the linear part.

tf.contrib.distributions.QuantizedDistribution.sample(sample_shape=(), seed=None, name='sample') Generate samples of the specified shape. Note that a call to sample() without arguments will generate a single sample. Args: sample_shape: 0D or 1D int32 Tensor. Shape of the generated samples. seed: Python integer seed for RNG name: name to give to the op. Returns: samples: a Tensor with prepended dimensions sample_shape.

tf.contrib.graph_editor.select_ops_and_ts(*args, **kwargs) Helper to select operations and tensors. Args: *args: list of 1) regular expressions (compiled or not) or 2) (array of) tf.Operation 3) (array of) tf.Tensor. Regular expressions matching tensors must start with the comment "(?#ts)", for instance: "(?#ts)^foo/.*". **kwargs: 'graph': tf.Graph in which to perform the regex query.This is required when using regex. 'positive_filter': an elem if selected only if positive_filter(elem) is Tr