tf.contrib.distributions.Mixture.pmf(value, name='pmf') Probability mass function. Args: value: float or double Tensor. name: The name to give this op. Returns: pmf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if is_continuous.

tf.contrib.learn.monitors.ExportMonitor.signature_fn

tf.contrib.learn.RunConfig.job_name

tf.contrib.distributions.DirichletMultinomial.allow_nan_stats Python boolean describing behavior when a stat is undefined. Stats return +/- infinity when it makes sense. E.g., the variance of a Cauchy distribution is infinity. However, sometimes the statistic is undefined, e.g., if a distribution's pdf does not achieve a maximum within the support of the distribution, the mode is undefined. If the mean is undefined, then by definition the variance is undefined. E.g. the mean for Student's T fo

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalCholeskyTensor.entropy(name='entropy')

tf.contrib.bayesflow.stochastic_tensor.UniformTensor.dtype

tf.contrib.layers.batch_norm(*args, **kwargs) Adds a Batch Normalization layer from http://arxiv.org/abs/1502.03167. "Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift" Sergey Ioffe, Christian Szegedy Can be used as a normalizer function for conv2d and fully_connected. Note: When is_training is True the moving_mean and moving_variance need to be updated, by default the update_ops are placed in tf.GraphKeys.UPDATE_OPS so they need to be added as a depe

tf.contrib.bayesflow.stochastic_tensor.BetaTensor.clone(name=None, **dist_args)

tf.contrib.distributions.Dirichlet.entropy(name='entropy') Shanon entropy in nats.

Status tensorflow::Env::RegisterFileSystem(const string &scheme, FileSystemRegistry::Factory factory)