`NormalWithSoftplusSigmaTensor` is a `StochasticTensor` backed by the distribution `NormalWithSoftplusSigma`.
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#### `tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)` {#NormalWithSoftplusSigmaTensor.__init__}




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#### `tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.clone(name=None, **dist_args)` {#NormalWithSoftplusSigmaTensor.clone}




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#### `tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.distribution` {#NormalWithSoftplusSigmaTensor.distribution}




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#### `tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.dtype` {#NormalWithSoftplusSigmaTensor.dtype}




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#### `tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.entropy(name='entropy')` {#NormalWithSoftplusSigmaTensor.entropy}




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#### `tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.graph` {#NormalWithSoftplusSigmaTensor.graph}




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#### `tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.input_dict` {#NormalWithSoftplusSigmaTensor.input_dict}




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#### `tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.loss(final_loss, name='Loss')` {#NormalWithSoftplusSigmaTensor.loss}




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#### `tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.mean(name='mean')` {#NormalWithSoftplusSigmaTensor.mean}




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#### `tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.name` {#NormalWithSoftplusSigmaTensor.name}




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#### `tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.value(name='value')` {#NormalWithSoftplusSigmaTensor.value}




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#### `tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.value_type` {#NormalWithSoftplusSigmaTensor.value_type}




