tf.contrib.learn.TensorFlowEstimator.get_params(deep=True) Get parameters for this estimator. Args: deep: boolean, optional If True, will return the parameters for this estimator and contained subobjects that are estimators. Returns: params : mapping of string to any Parameter names mapped to their values.

tf.contrib.distributions.LaplaceWithSoftplusScale.pmf(value, name='pmf') Probability mass function. Args: value: float or double Tensor. name: The name to give this op. Returns: pmf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if is_continuous.

tf.nn.rnn_cell.LSTMCell.state_size

tf.contrib.bayesflow.stochastic_tensor.LaplaceTensor.graph

tf.contrib.distributions.QuantizedDistribution.pdf(value, name='pdf') Probability density function. Args: value: float or double Tensor. name: The name to give this op. Returns: prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if not is_continuous.

tf.contrib.distributions.GammaWithSoftplusAlphaBeta.pdf(value, name='pdf') Probability density function. Args: value: float or double Tensor. name: The name to give this op. Returns: prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if not is_continuous.

tf.sparse_segment_sqrt_n(data, indices, segment_ids, name=None) Computes the sum along sparse segments of a tensor divided by the sqrt of N. N is the size of the segment being reduced. Read the section on Segmentation for an explanation of segments. Args: data: A Tensor. Must be one of the following types: float32, float64. indices: A Tensor. Must be one of the following types: int32, int64. A 1-D tensor. Has same rank as segment_ids. segment_ids: A Tensor of type int32. A 1-D tensor. Value

tf.contrib.distributions.TransformedDistribution.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.distributions.WishartCholesky.parameters Dictionary of parameters used by this Distribution.

tf.contrib.distributions.Multinomial.mean(name='mean') Mean.