tf.contrib.graph_editor.get_consuming_ops(ts) Return all the consuming ops of the tensors in ts. Args: ts: a list of tf.Tensor Returns: A list of all the consuming tf.Operation of the tensors in ts. Raises: TypeError: if ts cannot be converted to a list of tf.Tensor.

tf.contrib.distributions.Gamma.get_batch_shape() Shape of a single sample from a single event index as a TensorShape. Same meaning as batch_shape. May be only partially defined. Returns: batch_shape: TensorShape, possibly unknown.

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagPlusVDVTTensor.mean(name='mean')

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

tf.contrib.learn.DNNRegressor.dnn_weights_ Returns weights of deep neural network part.

tf.contrib.distributions.Chi2.prob(value, name='prob') Probability density/mass function (depending on is_continuous). Args: value: float or double Tensor. name: The name to give this op. Returns: prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.

class tf.errors.NotFoundError Raised when a requested entity (e.g., a file or directory) was not found. For example, running the tf.WholeFileReader.read() operation could raise NotFoundError if it receives the name of a file that does not exist.

tf.contrib.learn.monitors.SummaryWriterCache.clear() Clear cached summary writers. Currently only used for unit tests.

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

tf.contrib.distributions.TransformedDistribution.sample(sample_shape=(), seed=None, name='sample') Generate samples of the specified shape. Note that a call to sample() without arguments will generate a single sample. Args: sample_shape: 0D or 1D int32 Tensor. Shape of the generated samples. seed: Python integer seed for RNG name: name to give to the op. Returns: samples: a Tensor with prepended dimensions sample_shape.