tf.decode_base64(input, name=None) Decode web-safe base64-encoded strings. Input may or may not have padding at the end. See EncodeBase64 for padding. Web-safe means that input must use - and _ instead of + and /. Args: input: A Tensor of type string. Base64 strings to decode. name: A name for the operation (optional). Returns: A Tensor of type string. Decoded strings.

Status tensorflow::Env::GetFileSize(const string &fname, uint64 *file_size) Stores the size of fname in *file_size.

tf.contrib.bayesflow.stochastic_tensor.Chi2WithAbsDfTensor.value(name='value')

tf.self_adjoint_eigvals(tensor, name=None) Computes the eigenvalues of one or more self-adjoint matrices. Args: tensor: Tensor of shape [..., N, N]. name: string, optional name of the operation. Returns: e: Eigenvalues. Shape is [..., N]. The vector e[..., :] contains the N eigenvalues of tensor[..., :, :].

tf.contrib.distributions.Dirichlet.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.learn.monitors.CaptureVariable.step_begin(step) Overrides BaseMonitor.step_begin. When overriding this method, you must call the super implementation. Args: step: int, the current value of the global step. Returns: A list, the result of every_n_step_begin, if that was called this step, or an empty list otherwise. Raises: ValueError: if called more than once during a step.

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

tf.contrib.learn.monitors.CheckpointSaver.step_begin(step)

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

tf.contrib.learn.LinearRegressor.linear_bias_ Returns bias of the linear part.