tf.contrib.distributions.Uniform.std()

tf.contrib.distributions.Uniform.std(name='std') Standard deviation.

tf.errors.DeadlineExceededError

class tf.errors.DeadlineExceededError Raised when a deadline expires before an operation could complete. This exception is not currently used.

tf.errors.AlreadyExistsError

class tf.errors.AlreadyExistsError Raised when an entity that we attempted to create already exists. For example, running an operation that saves a file (e.g. tf.train.Saver.save()) could potentially raise this exception if an explicit filename for an existing file was passed.

tf.contrib.distributions.DirichletMultinomial.log_pdf()

tf.contrib.distributions.DirichletMultinomial.log_pdf(value, name='log_pdf') Log probability density function. Args: value: float or double Tensor. name: The name to give this op. Returns: log_prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if not is_continuous.

tf.contrib.learn.LinearClassifier.get_estimator()

tf.contrib.learn.LinearClassifier.get_estimator()

tf.contrib.distributions.TransformedDistribution.is_continuous

tf.contrib.distributions.TransformedDistribution.is_continuous

tf.contrib.distributions.LaplaceWithSoftplusScale.scale

tf.contrib.distributions.LaplaceWithSoftplusScale.scale Distribution parameter for scale.

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalCholeskyTensor.mean()

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

tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.validate_args

tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.validate_args Python boolean indicated possibly expensive checks are enabled.

tf.SparseTensorValue

class tf.SparseTensorValue SparseTensorValue(indices, values, shape)