class tf.errors.InvalidArgumentError Raised when an operation receives an invalid argument. This may occur, for example, if an operation is receives an input tensor that has an invalid value or shape. For example, the tf.matmul() op will raise this error if it receives an input that is not a matrix, and the tf.reshape() op will raise this error if the new shape does not match the number of elements in the input tensor.

tf.contrib.framework.add_model_variable(var) Adds a variable to the GraphKeys.MODEL_VARIABLES collection. Args: var: a variable.

tf.contrib.learn.monitors.SummaryWriterCache.get(logdir) Returns the SummaryWriter for the specified directory. Args: logdir: str, name of the directory. Returns: A SummaryWriter.

tf.contrib.learn.monitors.PrintTensor.epoch_end(epoch) End epoch. Args: epoch: int, the epoch number. Raises: ValueError: if we've not begun an epoch, or epoch number does not match.

tf.contrib.learn.monitors.NanLoss.every_n_step_end(step, outputs)

class tf.contrib.bayesflow.stochastic_tensor.Chi2WithAbsDfTensor Chi2WithAbsDfTensor is a StochasticTensor backed by the distribution Chi2WithAbsDf.

static bool tensorflow::TensorShapeUtils::IsMatrix(const TensorShape &shape)

tf.contrib.learn.monitors.EveryN.epoch_begin(epoch) Begin epoch. Args: epoch: int, the epoch number. Raises: ValueError: if we've already begun an epoch, or epoch < 0.

class tf.contrib.learn.monitors.EveryN Base class for monitors that execute callbacks every N steps. This class adds three new callbacks: - every_n_step_begin - every_n_step_end - every_n_post_step The callbacks are executed every n steps, or optionally every step for the first m steps, where m and n can both be user-specified. When extending this class, note that if you wish to use any of the BaseMonitor callbacks, you must call their respective super implementation: def step_begin(self, step

tf.contrib.learn.monitors.BaseMonitor.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.