tf.contrib.distributions.Categorical.dtype

tf.contrib.distributions.Categorical.dtype The DType of Tensors handled by this Distribution

2016-10-14 12:48:08
tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.param_shapes()

tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.param_shapes(cls, sample_shape, name='DistributionParamShapes') Shapes

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tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.mean()

tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.mean(name='mean') Mean. Additional documentation

2016-10-14 13:02:33
tf.contrib.distributions.BernoulliWithSigmoidP.is_reparameterized

tf.contrib.distributions.BernoulliWithSigmoidP.is_reparameterized

2016-10-14 12:45:42
tf.contrib.distributions.MultivariateNormalCholesky.dtype

tf.contrib.distributions.MultivariateNormalCholesky.dtype The DType of Tensors handled by this

2016-10-14 12:57:19
tf.contrib.distributions.Chi2.get_batch_shape()

tf.contrib.distributions.Chi2.get_batch_shape() Shape of a single sample from a single event index as a TensorShape

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tf.contrib.distributions.Bernoulli.sample()

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

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tf.contrib.distributions.MultivariateNormalCholesky.mean()

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

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tf.contrib.distributions.ExponentialWithSoftplusLam.mode()

tf.contrib.distributions.ExponentialWithSoftplusLam.mode(name='mode') Mode. Additional documentation

2016-10-14 12:52:49
tf.contrib.distributions.MultivariateNormalFull.validate_args

tf.contrib.distributions.MultivariateNormalFull.validate_args Python boolean indicated possibly expensive checks are enabled.

2016-10-14 12:59:36