tf.contrib.distributions.Poisson.dtype The DType of Tensors handled by this Distribution.

class tf.contrib.distributions.Exponential The Exponential distribution with rate parameter lam. The PDF of this distribution is: prob(x) = (lam * e^(-lam * x)), x > 0 Note that the Exponential distribution is a special case of the Gamma distribution, with Exponential(lam) = Gamma(1, lam).

tf.contrib.bayesflow.stochastic_tensor.MixtureTensor.clone(name=None, **dist_args)

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.variance(name='variance') Variance.

tf.contrib.distributions.Categorical.survival_function(value, name='survival_function') Survival function. Given random variable X, the survival function is defined: survival_function(x) = P[X > x] = 1 - P[X <= x] = 1 - cdf(x). Args: value: float or double Tensor. name: The name to give this op. Returns: Tensorof shapesample_shape(x) + self.batch_shapewith values of typeself.dtype`.

tf.contrib.bayesflow.stochastic_tensor.BernoulliWithSigmoidPTensor.clone(name=None, **dist_args)

tf.contrib.distributions.Chi2WithAbsDf.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.crf.crf_binary_score(tag_indices, sequence_lengths, transition_params) Computes the binary scores of tag sequences. Args: tag_indices: A [batch_size, max_seq_len] matrix of tag indices. sequence_lengths: A [batch_size] vector of true sequence lengths. transition_params: A [num_tags, num_tags] matrix of binary potentials. Returns: binary_scores: A [batch_size] vector of binary scores.

class tf.contrib.learn.TensorFlowRNNClassifier TensorFlow RNN Classifier model.

tf.IdentityReader.num_records_produced(name=None) Returns the number of records this reader has produced. This is the same as the number of Read executions that have succeeded. Args: name: A name for the operation (optional). Returns: An int64 Tensor.