tf.contrib.learn.LinearRegressor.bias_

class tf.contrib.graph_editor.matcher Graph match class.

tf.contrib.distributions.Uniform.sample(sample_shape=(), seed=None, name='sample') Generate samples of the specified shape. Note that a call to sample() without arguments will generate a single sample. Args: sample_shape: 0D or 1D int32 Tensor. Shape of the generated samples. seed: Python integer seed for RNG name: name to give to the op. Returns: samples: a Tensor with prepended dimensions sample_shape.

tf.contrib.training.SequenceQueueingStateSaver.batch_size

tf.contrib.distributions.MultivariateNormalCholesky.is_continuous

tf.nn.rnn_cell.OutputProjectionWrapper.state_size

bool tensorflow::PartialTensorShape::IsValid(const TensorShapeProto &proto) Returns true iff proto is a valid partial tensor shape.

class tf.contrib.bayesflow.stochastic_tensor.DirichletMultinomialTensor DirichletMultinomialTensor is a StochasticTensor backed by the distribution DirichletMultinomial.

tf.contrib.learn.monitors.GraphDump.begin(max_steps=None)

class tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagTensor MultivariateNormalDiagTensor is a StochasticTensor backed by the distribution MultivariateNormalDiag.