tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalCholeskyTensor.name

tf.FixedLenFeature.shape Alias for field number 0

tf.contrib.distributions.BernoulliWithSigmoidP.param_shapes(cls, sample_shape, name='DistributionParamShapes') Shapes of parameters given the desired shape of a call to sample(). Subclasses should override static method _param_shapes. Args: sample_shape: Tensor or python list/tuple. Desired shape of a call to sample(). name: name to prepend ops with. Returns: dict of parameter name to Tensor shapes.

tf.contrib.distributions.MultivariateNormalCholesky.cdf(value, name='cdf') Cumulative distribution function. Given random variable X, the cumulative distribution function cdf is: cdf(x) := P[X <= x] Args: value: float or double Tensor. name: The name to give this op. Returns: cdf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.

tf.contrib.bayesflow.stochastic_tensor.MeanValue.__init__(stop_gradient=False)

tf.contrib.rnn.LayerNormBasicLSTMCell.output_size

tf.contrib.learn.TensorFlowRNNRegressor.model_dir

tf.contrib.rnn.AttentionCellWrapper.__call__(inputs, state, scope=None) Long short-term memory cell with attention (LSTMA).

tf.SparseTensorValue.shape Alias for field number 2

tf.contrib.distributions.Poisson.entropy(name='entropy') Shanon entropy in nats.