tf.contrib.bayesflow.stochastic_tensor.Chi2Tensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

Status tensorflow::EnvWrapper::LoadLibrary(const char *library_filename, void **handle) override

tf.contrib.distributions.WishartCholesky.survival_function(value, name='survival_function') Survival function. Given random variable X, the survival function is defined: survival_function(x) = P[X > x] = 1 - P[X <= x] = 1 - cdf(x). Args: value: float or double Tensor. name: The name to give this op. Returns: Tensorof shapesample_shape(x) + self.batch_shapewith values of typeself.dtype`.

tf.contrib.bayesflow.stochastic_tensor.InverseGammaWithSoftplusAlphaBetaTensor.input_dict

tf.contrib.distributions.ExponentialWithSoftplusLam.lam

tf.SparseTensor.op The Operation that produces values as an output.

tf.contrib.distributions.LaplaceWithSoftplusScale.is_reparameterized

tf.python_io.TFRecordWriter.__exit__(unused_type, unused_value, unused_traceback) Exit a with block, closing the file.

tf.contrib.learn.TensorFlowEstimator.__repr__()

Status tensorflow::PartialTensorShape::MergeWith(const PartialTensorShape &shape, PartialTensorShape *result) const Merges all the dimensions from shape. Returns InvalidArgument error if either shape has a different rank or if any of the dimensions are incompatible.