tf.nn.rnn_cell.BasicRNNCell.output_size

tf.listdiff(x, y, out_idx=None, name=None) Computes the difference between two lists of numbers or strings. Given a list x and a list y, this operation returns a list out that represents all values that are in x but not in y. The returned list out is sorted in the same order that the numbers appear in x (duplicates are preserved). This operation also returns a list idx that represents the position of each out element in x. In other words: out[i] = x[idx[i]] for i in [0, 1, ..., len(out) - 1] F

class tf.nn.rnn_cell.GRUCell Gated Recurrent Unit cell (cf. http://arxiv.org/abs/1406.1078).

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)