Removes symbols in a module that are not referenced by a docstring. Args: module_name: the name of the module (usually `__name__`). allowed

Returns an id that is unique to this module across all modules created over the lifetime of this process.

UpdateErr is used to notify Scope of any graph construction errors while creating the operation op.

Returns word's id in the vocabulary. If category is new, creates a new id for it. Args: category: string or integer to lookup in vocab

Parse the following regex manually name(\[index\])?(\.field)?

The number of GPUs available to execute operations.

If map has an entry for k, return the corresponding value, else return def.

Flat size calculation, checking that dimensions match with one or more other arrays.

Asserts that two float arrays are near each other. Checks that for all elements of farray1 and farray2 |f1 - f2| < err. Asserts a test failu

Creates a Tensor from a Java object. <p>A {@code Tensor} is a multi-dimensional array of elements of a limited set of types. Not all Java objects can

Returns a list of values in the collection with the given `name`. If the collection exists, this returns the list itself, which can be modifi

Writes a `SavedModel` protocol buffer to disk. The function writes the SavedModel protocol buffer to the export directory in serialized forma

Wait for threads to terminate. This call blocks until a set of threads have terminated. The set of thread is the union of the threads passed

Returns the number of inputs to the operator.

Return a copy of itself. Note that this class is a "view", copying it only create another view and does not copy the underlying part of the t

Handles a command by dispatching it to a registered command handler. Args: prefix: Command prefix, as a str, e.g., "print". argv: Com

Starts this server. Raises: tf.errors.OpError: Or one of its subclasses if an error occurs while starting the TensorFlow server.

Deprecated, do NOT use! Alias for `add_weight`.

Creates a new single-process cluster running on the local host. This method is a convenience wrapper for creating a `tf.distribute.Server` wi

Variance. Variance is defined as, ```none Var = E[(X - E[X])**2] ``` where `X` is the random variable associated with this dist

Default constructor creates an empty example.

Decoder using LSTM. Args: x: tensor of size [num_children, num_groups, embedding_size]. last_c: tensor of size [num_children, hidden_

Releases the cleanup function instead of running it. Hint: use c.release()() to run early.

Request that the threads stop. After this is called, calls to `should_stop()` will return `True`. Note: If an exception is being passed in,

Apply gradients to a replica variable.

In graph mode returns the result Tensor while in eager the callable.