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tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.mode()

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.mode(name='mode')

Mode.

Links:

https://www.tensorflow.org/versions/master/api_docs/python/contrib.distributions.html#MultivariateNormalDiagWithSoftplusStDev.mode

doc_TensorFlow

2016-10-14 12:58:52

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tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev class tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev MultivariateNormalDiag with diag_stddev = softplus(diag_stddev).

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.mean() tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.mean(name='mean') Mean.

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.pdf() tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.pdf(value, name='pdf') Probability density function. Args: value: float or double

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.sample() tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.sample(sample_shape=(), seed=None, name='sample') Generate samples of the specified

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