class tf.errors.FailedPreconditionError Operation was rejected because the system is not in a state to execute it.

tf.contrib.learn.monitors.SummarySaver.every_n_step_begin(step)

tf.contrib.bayesflow.stochastic_tensor.ExponentialTensor.distribution

tf.test.compute_gradient(x, x_shape, y, y_shape, x_init_value=None, delta=0.001, init_targets=None) Computes and returns the theoretical

tf.contrib.bayesflow.stochastic_tensor.MeanValue.popped_above(unused_value_type)

tf.nn.rnn_cell.LSTMStateTuple.__new__(_cls, c, h) Create new instance of LSTMStateTuple(c, h)

tf.contrib.distributions.Exponential.param_static_shapes(cls, sample_shape) param_shapes with static (i.e. TensorShape) shapes

tf.contrib.distributions.Exponential.__init__(lam, validate_args=False, allow_nan_stats=True, name='Exponential') Construct Exponential

tf.contrib.distributions.ExponentialWithSoftplusLam.prob(value, name='prob') Probability density/mass function (depending on

tf.string_join(inputs, separator=None, name=None) Joins the strings in the given list of string tensors into one tensor;