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

tf.contrib.layers.avg_pool2d(*args, **kwargs) Adds a 2D average pooling op. It is assumed that

tf.contrib.learn.DNNClassifier.fit(x=None, y=None, input_fn=None, steps=None, batch_size=None, monitors=None, max_steps=None) See

tf.erfc(x, name=None) Computes the complementary error function of x element-wise. Args:

string tensorflow::TensorShapeUtils::ShapeListString(const gtl::ArraySlice< TensorShape > &shapes)

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.event_shape(name='event_shape') Shape of a single sample from a single

tf.contrib.util.ops_used_by_graph_def(graph_def) Collect the list of ops used by a graph. Does

tf.contrib.distributions.Mixture.sample_n(n, seed=None, name='sample_n') Generate n samples.

tf.contrib.bayesflow.stochastic_tensor.QuantizedDistributionTensor.input_dict

tf.contrib.bayesflow.stochastic_tensor.BaseStochasticTensor.dtype