tf.ones(shape, dtype=tf.float32, name=None) Creates a tensor with all elements set to 1. This operation returns a tensor of type dtype with shape shape and all elements set to 1. For example: tf.ones([2, 3], int32) ==> [[1, 1, 1], [1, 1, 1]] Args: shape: Either a list of integers, or a 1-D Tensor of type int32. dtype: The type of an element in the resulting Tensor. name: A name for the operation (optional). Returns: A Tensor with all elements set to 1.

tf.contrib.framework.assert_scalar_int(tensor) Assert tensor is 0-D, of type tf.int32 or tf.int64. Args: tensor: Tensor to test. Returns: tensor, for chaining. Raises: ValueError: if tensor is not 0-D, of type tf.int32 or tf.int64.

tf.contrib.distributions.Multinomial.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.

class tf.contrib.bayesflow.stochastic_tensor.BernoulliWithSigmoidPTensor BernoulliWithSigmoidPTensor is a StochasticTensor backed by the distribution BernoulliWithSigmoidP.

tf.contrib.bayesflow.stochastic_tensor.ExponentialWithSoftplusLamTensor.entropy(name='entropy')

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagPlusVDVTTensor.loss(final_loss, name='Loss')

Status tensorflow::EnvWrapper::GetRegisteredFileSystemSchemes(std::vector< string > *schemes) override Returns the file system schemes registered for this Env .

tf.contrib.distributions.StudentT.get_batch_shape() Shape of a single sample from a single event index as a TensorShape. Same meaning as batch_shape. May be only partially defined. Returns: batch_shape: TensorShape, possibly unknown.

tf.contrib.bayesflow.stochastic_tensor.BaseStochasticTensor.input_dict

tf.contrib.distributions.DirichletMultinomial.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.