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




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




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




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




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




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




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




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




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




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




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




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




