tf.contrib.distributions.Bernoulli.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.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagPlusVDVTTensor.dtype

tf.contrib.learn.extract_dask_labels(labels) Extract data from dask.Series for labels.

tf.contrib.distributions.Uniform.is_reparameterized

tf.FixedLenSequenceFeature.shape Alias for field number 0

tf.exp(x, name=None) Computes exponential of x element-wise. \(y = e^x\). Args: x: A Tensor. Must be one of the following types: half, float32, float64, complex64, complex128. name: A name for the operation (optional). Returns: A Tensor. Has the same type as x.

bool tensorflow::PartialTensorShape::AsTensorShape(TensorShape *tensor_shape) const

tf.contrib.distributions.MultivariateNormalDiag.mode(name='mode') Mode.

class tf.contrib.learn.ModeKeys Standard names for model modes. The following standard keys are defined: TRAIN: training mode. EVAL: evaluation mode. INFER: inference mode.

tf.contrib.distributions.QuantizedDistribution.parameters Dictionary of parameters used by this Distribution.