tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagWithSoftplusStDevTensor.graph

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagWithSoftplusStDevTensor.graph

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagWithSoftplusStDevTensor.entropy()

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagWithSoftplusStDevTensor.entropy(name='entropy')

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagWithSoftplusStDevTensor.dtype

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagWithSoftplusStDevTensor.dtype

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagWithSoftplusStDevTensor.distribution

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagWithSoftplusStDevTensor.distribution

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagWithSoftplusStDevTensor.clone()

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

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagWithSoftplusStDevTensor

class tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagWithSoftplusStDevTensor MultivariateNormalDiagWithSoftplusStDevTensor is a StochasticTensor backed by the distribution MultivariateNormalDiagWithSoftplusStDev.

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagTensor.__init__()

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

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagTensor.value_type

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagTensor.value_type

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagTensor.value()

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagTensor.value(name='value')

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagTensor.name

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagTensor.name