tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.__init__(df, mu, sigma, validate_args=False, allow_nan_stats=True, name='StudentTWithAbsDfSoftplusSigma')

tf.contrib.distributions.ExponentialWithSoftplusLam.is_reparameterized

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.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.

tensorflow::error::Code tensorflow::Status::State::code

tf.contrib.bayesflow.stochastic_tensor.Chi2Tensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

class tf.contrib.learn.monitors.StepCounter Steps per second monitor.

tf.contrib.bayesflow.stochastic_tensor.DirichletTensor.clone(name=None, **dist_args)

tf.contrib.bayesflow.stochastic_tensor.StudentTTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

tf.contrib.bayesflow.stochastic_tensor.QuantizedDistributionTensor.input_dict

tf.contrib.distributions.StudentT.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.