tf.contrib.distributions.Poisson.param_shapes(cls, sample_shape, name='DistributionParamShapes') Shapes of parameters given the

tf.contrib.distributions.Poisson.pdf(value, name='pdf') Probability density function. Args:

tf.image.resize_nearest_neighbor(images, size, align_corners=None, name=None) Resize images to size

tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.__init__(df, mu, sigma, validate_args=False, allow_nan_stats=True, name='StudentTWithAbsDfSoftplusSigma')

tf.contrib.bayesflow.stochastic_tensor.WishartCholeskyTensor.value_type

tf.contrib.distributions.BaseDistribution.sample_n(n, seed=None, name='sample') Generate n samples.

tf.contrib.distributions.MultivariateNormalCholesky.event_shape(name='event_shape') Shape of a single sample from a single batch

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalFullTensor.loss(final_loss, name='Loss')

tf.contrib.distributions.Multinomial.param_static_shapes(cls, sample_shape) param_shapes with static (i.e. TensorShape) shapes

tf.contrib.distributions.MultivariateNormalFull.pmf(value, name='pmf') Probability mass function. Args: