tf.contrib.distributions.MultivariateNormalCholesky.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'

int64 tensorflow::Tensor::NumElements() const Convenience accessor for the tensor shape.

tf.contrib.learn.DNNRegressor.dnn_bias_ Returns bias of deep neural network part.

tf.contrib.distributions.WishartCholesky.mean(name='mean') Mean.

tf.assert_rank(x, rank, data=None, summarize=None, message=None, name=None) Assert x has rank equal to rank. Example of adding a dependency to an operation: with tf.control_dependencies([tf.assert_rank(x, 2)]): output = tf.reduce_sum(x) Example of adding dependency to the tensor being checked: x = tf.with_dependencies([tf.assert_rank(x, 2)], x) Args: x: Numeric Tensor. rank: Scalar integer Tensor. data: The tensors to print out if the condition is False. Defaults to error message and fi

tf.contrib.distributions.Distribution.name Name prepended to all ops created by this Distribution.

tf.contrib.learn.monitors.StepCounter.set_estimator(estimator)

tf.contrib.rnn.GridLSTMCell.state_size

tf.contrib.learn.monitors.RunHookAdapterForMonitors.before_run(run_context)

tf.contrib.distributions.BetaWithSoftplusAB.__init__(a, b, validate_args=False, allow_nan_stats=True, name='BetaWithSoftplusAB')