tf.contrib.rnn.GridLSTMCell.output_size

tf.contrib.rnn.GridLSTMCell.output_size

tensorflow::TensorShape::MaxDimensions()

static constexpr int tensorflow::TensorShape::MaxDimensions()

tf.contrib.distributions.GammaWithSoftplusAlphaBeta.entropy()

tf.contrib.distributions.GammaWithSoftplusAlphaBeta.entropy(name='entropy') Shanon entropy in nats. Additional documentation from Gamma: This is defined to be entropy = alpha - log(beta) + log(Gamma(alpha)) + (1-alpha)digamma(alpha) where digamma(alpha) is the digamma function.

tf.contrib.graph_editor.copy_op_handler()

tf.contrib.graph_editor.copy_op_handler(info, op, copy_shape=True) Copy a tf.Operation. Args: info: Transform._Info instance. op: the tf.Operation to be copied. copy_shape: also copy the shape of the tensor Returns: A copy of op.

tf.contrib.bayesflow.stochastic_tensor.StudentTTensor.name

tf.contrib.bayesflow.stochastic_tensor.StudentTTensor.name

tf.contrib.learn.monitors.CheckpointSaver.epoch_begin()

tf.contrib.learn.monitors.CheckpointSaver.epoch_begin(epoch) Begin epoch. Args: epoch: int, the epoch number. Raises: ValueError: if we've already begun an epoch, or epoch < 0.

tf.contrib.distributions.Beta.std()

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

tf.contrib.bayesflow.stochastic_tensor.MixtureTensor.name

tf.contrib.bayesflow.stochastic_tensor.MixtureTensor.name

tensorflow::Tensor::matrix()

TTypes<T>::Matrix tensorflow::Tensor::matrix()

tensorflow::TensorShapeDim::TensorShapeDim()

tensorflow::TensorShapeDim::TensorShapeDim(int64 s)