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

tf.image.convert_image_dtype(image, dtype, saturate=False, name=None) Convert image to dtype, scaling

tf.cholesky(input, name=None) Computes the Cholesky decomposition of one or more square matrices. The

tf.FixedLenSequenceFeature.__repr__() Return a nicely formatted representation string

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

tf.contrib.distributions.Distribution.cdf(value, name='cdf') Cumulative distribution function. Given

tf.contrib.distributions.Gamma.prob(value, name='prob') Probability density/mass function (depending on is_continuous)

tf.contrib.distributions.WishartCholesky.log_pdf(value, name='log_pdf') Log probability density function.

tf.contrib.distributions.Poisson.cdf(value, name='cdf') Cumulative distribution function. Given

tf.contrib.distributions.Dirichlet.__init__(alpha, validate_args=False, allow_nan_stats=True, name='Dirichlet') Initialize a batch