tf.contrib.bayesflow.stochastic_tensor.TransformedDistributionTensor.dtype

tf.contrib.bayesflow.stochastic_tensor.BaseStochasticTensor.input_dict

tf.contrib.distributions.Chi2WithAbsDf.sample(sample_shape=(), seed=None, name='sample') Generate samples of the specified shape

tf.contrib.rnn.LayerNormBasicLSTMCell.__init__(num_units, forget_bias=1.0, input_size=None, activation=tanh, layer_norm=True, norm_gain=1.0, norm_shift=0.0, dropout_keep_prob=1

tf.contrib.layers.safe_embedding_lookup_sparse(embedding_weights, sparse_ids, sparse_weights=None, combiner=None, default_id=None, name=None, partition_strategy='div')

tf.contrib.learn.LinearClassifier.get_variable_names()

tf.contrib.distributions.Dirichlet.pmf(value, name='pmf') Probability mass function. Args:

tf.FixedLenFeature.__new__(_cls, shape, dtype, default_value=None) Create new instance of FixedLenFeature(shape, dtype, default_value)

tf.contrib.learn.Estimator.__init__(model_fn=None, model_dir=None, config=None, params=None, feature_engineering_fn=None) Constructs

tf.contrib.distributions.Mixture.pdf(value, name='pdf') Probability density function. Args: