tf.contrib.distributions.NormalWithSoftplusSigma.param_shapes()

tf.contrib.distributions.NormalWithSoftplusSigma.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.NormalWithSoftplusSigma.pdf()

tf.contrib.distributions.NormalWithSoftplusSigma.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.NormalWithSoftplusSigma.pmf()

tf.contrib.distributions.NormalWithSoftplusSigma.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.distributions.NormalWithSoftplusSigma.param_static_shapes()

tf.contrib.distributions.NormalWithSoftplusSigma.param_static_shapes(cls, sample_shape) param_shapes with static (i.e. TensorShape) shapes. Args: sample_shape: TensorShape or python list/tuple. Desired shape of a call to sample(). Returns: dict of parameter name to TensorShape. Raises: ValueError: if sample_shape is a TensorShape and is not fully defined.

tf.contrib.distributions.NormalWithSoftplusSigma.parameters

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

tf.contrib.distributions.NormalWithSoftplusSigma.name

tf.contrib.distributions.NormalWithSoftplusSigma.name Name prepended to all ops created by this Distribution.

tf.contrib.distributions.NormalWithSoftplusSigma.mode()

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

tf.contrib.distributions.NormalWithSoftplusSigma.mu

tf.contrib.distributions.NormalWithSoftplusSigma.mu Distribution parameter for the mean.

tf.contrib.distributions.NormalWithSoftplusSigma.mean()

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

tf.contrib.distributions.NormalWithSoftplusSigma.log_prob()

tf.contrib.distributions.NormalWithSoftplusSigma.log_prob(value, name='log_prob') Log probability density/mass function (depending on is_continuous). Args: value: float or double Tensor. name: The name to give this op. Returns: log_prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.