int64 tensorflow::TensorShape::dim_size(int d) const Returns the number of elements in dimension d. REQUIRES: 0 <= d < dims()

class tf.nn.rnn_cell.BasicRNNCell The most basic RNN cell.

tf.contrib.framework.add_arg_scope(func) Decorates a function with args so it can be used within an arg_scope. Args: func: function to decorate. Returns: A tuple with the decorated function func_with_args().

tf.contrib.learn.monitors.StepCounter.begin(max_steps=None) Called at the beginning of training. When called, the default graph is the one we are executing. Args: max_steps: int, the maximum global step this training will run until. Raises: ValueError: if we've already begun a run.

tf.contrib.rnn.CoupledInputForgetGateLSTMCell.state_size

tf.matrix_set_diag(input, diagonal, name=None) Returns a batched matrix tensor with new batched diagonal values. Given input and diagonal, this operation returns a tensor with the same shape and values as input, except for the diagonals of the innermost matrices. These will be overwritten by the values in diagonal. The batched matrices must be square. The output is computed as follows: Assume input has k+1 dimensions [I, J, K, ..., N, N] and diagonal has k dimensions [I, J, K, ..., N]. Then th

tf.contrib.losses.get_total_loss(add_regularization_losses=True, name='total_loss') Returns a tensor whose value represents the total loss. Notice that the function adds the given losses to the regularization losses. Args: add_regularization_losses: A boolean indicating whether or not to use the regularization losses in the sum. name: The name of the returned tensor. Returns: A Tensor whose value represents the total loss. Raises: ValueError: if losses is not iterable.

tf.contrib.distributions.Mixture.log_pmf(value, name='log_pmf') Log probability mass function. Args: value: float or double Tensor. name: The name to give this op. Returns: log_pmf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if is_continuous.

tf.contrib.graph_editor.ControlOutputs.get(op) return the control outputs of op.

tf.SparseTensor.dtype The DType of elements in this tensor.