tf.contrib.bayesflow.stochastic_tensor.BetaWithSoftplusABTensor.graph

tf.contrib.learn.TensorFlowRNNRegressor.fit(x, y, steps=None, monitors=None, logdir=None) Neural network model from provided

tf.contrib.bayesflow.stochastic_tensor.Chi2WithAbsDfTensor.entropy(name='entropy')

tf.image.adjust_saturation(image, saturation_factor, name=None) Adjust saturation of an RGB image. This

tf.contrib.distributions.WishartCholesky.survival_function(value, name='survival_function') Survival function.

class tf.contrib.rnn.GRUBlockCell Block GRU cell implementation. The implementation is based on:

tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.log_cdf(value, name='log_cdf') Log cumulative distribution function

tf.contrib.layers.separable_convolution2d(*args, **kwargs) Adds a depth-separable 2D convolution with optional batch_norm layer

tf.contrib.rnn.GridLSTMCell.__init__(num_units, use_peepholes=False, share_time_frequency_weights=False, cell_clip=None, initializer=None, num_unit_shards=1, forget_bias=1

tf.contrib.rnn.CoupledInputForgetGateLSTMCell.__init__(num_units, use_peepholes=False, initializer=None, num_proj=None, proj_clip=None, num_unit_shards=1, num_proj_shards=1