tf.nn.rnn_cell.GRUCell.__call__()

tf.nn.rnn_cell.GRUCell.__call__(inputs, state, scope=None) Gated recurrent unit (GRU) with nunits cells.

tf.contrib.distributions.StudentT.pdf()

tf.contrib.distributions.StudentT.pdf(value, name='pdf') Probability density function. Args: value: float or double Tensor. name: The name to give this op. Returns: prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if not is_continuous.

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.log_prob()

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.log_prob(value, name='log_prob') Log probability density/mass function (depending on is_continuous). Additional documentation from _MultivariateNormalOperatorPD: x is a batch vector with compatible shape if x is a Tensor whose shape can be broadcast up to either: self.batch_shape + self.event_shape or [M1,...,Mm] + self.batch_shape + self.event_shape Args: value: float or double Tensor. name: The name to give this op. Retur

tf.contrib.distributions.QuantizedDistribution.entropy()

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

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.std()

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

tf.contrib.distributions.MultivariateNormalFull.get_event_shape()

tf.contrib.distributions.MultivariateNormalFull.get_event_shape() Shape of a single sample from a single batch as a TensorShape. Same meaning as event_shape. May be only partially defined. Returns: event_shape: TensorShape, possibly unknown.

tf.contrib.distributions.Dirichlet.param_shapes()

tf.contrib.distributions.Dirichlet.param_shapes(cls, sample_shape, name='DistributionParamShapes') Shapes of parameters given the desired shape of a call to sample(). Subclasses should override static method _param_shapes. Args: sample_shape: Tensor or python list/tuple. Desired shape of a call to sample(). name: name to prepend ops with. Returns: dict of parameter name to Tensor shapes.

tf.contrib.distributions.Laplace.get_event_shape()

tf.contrib.distributions.Laplace.get_event_shape() Shape of a single sample from a single batch as a TensorShape. Same meaning as event_shape. May be only partially defined. Returns: event_shape: TensorShape, possibly unknown.

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.event_shape()

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32 Tensor. Args: name: name to give to the op Returns: event_shape: Tensor.

tf.contrib.distributions.Gamma.get_event_shape()

tf.contrib.distributions.Gamma.get_event_shape() Shape of a single sample from a single batch as a TensorShape. Same meaning as event_shape. May be only partially defined. Returns: event_shape: TensorShape, possibly unknown.