tf.contrib.distributions.MultivariateNormalCholesky.cdf(value, name='cdf') Cumulative distribution function. Given random variable X, the cumulative distribution function cdf is: cdf(x) := P[X <= x] Args: value: float or double Tensor. name: The name to give this op. Returns: cdf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.

tf.contrib.bayesflow.stochastic_tensor.MeanValue.__init__(stop_gradient=False)

tf.contrib.rnn.LayerNormBasicLSTMCell.output_size

tf.contrib.learn.TensorFlowRNNRegressor.model_dir

tf.contrib.rnn.AttentionCellWrapper.__call__(inputs, state, scope=None) Long short-term memory cell with attention (LSTMA).

tf.SparseTensorValue.shape Alias for field number 2

tf.contrib.distributions.Poisson.entropy(name='entropy') Shanon entropy in nats.

tf.contrib.distributions.MultivariateNormalFull.cdf(value, name='cdf') Cumulative distribution function. Given random variable X, the cumulative distribution function cdf is: cdf(x) := P[X <= x] Args: value: float or double Tensor. name: The name to give this op. Returns: cdf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.

tf.contrib.graph_editor.transform_op_in_place(info, op, detach_outputs=False) Transform a op in-place - experimental! Transform an operation in place. It reconnects the inputs if they have been modified. if detach_outputs is True, the outputs of op are also detached. Args: info: Transform._Info instance. op: the op to transform in place. detach_outputs: if True, the outputs of op are detached, ready for the user to add more operation. Returns: The transformed op.

tf.contrib.graph_editor.bypass(sgv) Bypass the given subgraph by connecting its inputs to its outputs. Args: sgv: the subgraph view to be bypassed. This argument is converted to a subgraph using the same rules than the function subgraph.make_view. Note that sgv is modified in place. Returns: A tuple (sgv, detached_inputs) where: sgv is a new subgraph view of the bypassed subgraph; detached_inputs is a list of the created input placeholders. Raises: StandardError: if sgv cannot be converted