Creates a generator to extract data from the queue. Skip the data if it is `None`. Yields: Tuples (inputs, targets) or (

Assigns a new value to the variable. This is essentially a shortcut for `assign(self, value)`. Args: value: A `Tensor`. The new value

Creates an `Iterator` for enumerating the elements of this dataset. Note: The returned iterator will be in an uninitialized state, and you mu

Enqueues zero or more elements to this queue. This operation slices each component tensor along the 0th dimension to make multiple queue elem

Creates a `Dataset` of a step-separated range of values. For example: ```python Dataset.range(5) == [0, 1, 2, 3, 4] Dataset.range(2,

Asserts that a Numpy ndarray and a TensorFlow tensor have the same shape. Args: np_array: A Numpy ndarray or Numpy scalar. tf_tensor:

Returns the truth value of (x == y) element-wise. *NOTE*: `Equal` supports broadcasting. More about broadcasting [here](http://docs.scipy.org/doc/num

return the control outputs of op.

Runs operations and evaluates tensors in `fetches`. This method runs one "step" of TensorFlow computation, by running the necessary graph fra

Returns a numpy array with the same contents as the Tensor. TODO(ashankar,agarwal): Perhaps this should NOT reference the underlying buffer b

Gets one element from this staging area. If the staging area is empty when this operation executes, it will block until there is an element t

The `TensorShape` of this variable. Returns: A `TensorShape`.

Updates the stats accumulator.

Stores `value` in the collection with the given `name`. Note that collections are not sets, so it is possible to add a value to a collection

Apply the layer on a input. This simply wraps `self.__call__`. Arguments: inputs: Input tensor(s). *args: additional positional

Add a node invoking a registered Op to a graph. Example usage: # input1 and input2 can be Tensors or anything ops.convert_to_tensor()

Returns a context manager that specifies an op to colocate with. Note: this function is not for public use, only for internal libraries. For

Returns a Thread wrapper that asserts 'target' completes successfully. This method should be used to create all threads in test cases, as oth

Asserts that the two given devices are the same. Args: device1: A string device name or TensorFlow `DeviceSpec` object. device2: A st

Low-level accessor for stuff like memcmp, handle with care. Returns pointer to the underlying storage of the array (similarly to std::vector::data()).

See evaluable.Evaluable.

Returns the shape of a tensor. This operation returns a 1-D integer tensor representing the shape of `input`. For example: ```python t = tf

Return selected values in the TensorArray as a packed `Tensor`. All of selected values must have been written and their shapes must all match

Evaluates the model given evaluation data input_fn. For each step, calls `input_fn`, which returns one batch of data. Evaluates until: -

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

Number of elements currently held by this TopN object. This will be no greater than 'limit' passed to the constructor.

Returns the dtype of a Keras tensor or variable, as a string. Arguments: x: Tensor or variable. Returns: String, dtype of `x`. Ex

Serializes the stats accumulator state.

Configures the learning process. Arguments: optimizer: str (name of optimizer) or optimizer object. See [optimizers](/optimiz

Construct a TensorArray for holding Tensors of type 'dtype' with 'N' elements. While the underlying storage is a std::vector and can hold more than M

Returns True if current thread is in GRAPH mode.

Lists registered items. Returns: A list of names of registered objects.

Start the handler's workers. Arguments: workers: number of worker threads max_queue_size: queue size (when full, work

Returns a new instance of `RunConfig` replacing specified properties. Only the properties in the following list are allowed to be replaced:

Test scope that runs tests on a Tensorflow/XLA device. Uses a compilation_scope() to mark operators to compile. Yields: A scope to app

Write a scalar summary. Args: name: A name for the generated node. Will also serve as the series name in TensorBoard. tensor:

Return the index of the source output that produces the data carried by this edge. The special value kControlSlot is used for control dependencies.

Trains a model given training data input_fn. Args: input_fn: Input function returning a tuple of: features - `Tensor` or dictiona