TODO(b/80418076): Move to legacy ops file, update invocations.

Writes file_content to the file. Appends to the end of the file.

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

Combines consecutive elements of this dataset into batches. The components of the resulting element will have an additional outer dimension,

Repeats this dataset `count` times. NOTE: If this dataset is a function of global state (e.g. a random number generator), then different repe

Creates a generator to extract data from the queue. Skip the data if it is `None`. Yields: The next element in the queue, i.e. a tup

Asserts that message is same as parsed expected_message_ascii. Creates another prototype of message, reads the ascii message into it and then

Returns an iterator pointing to the given ShapeIndex. REQUIRES: index must exist in the ShapeTree.

Generates output predictions for the input samples. Computation is done in batches. Arguments: x: Input samples. It could be:

Returns the <a href="https://www.tensorflow.org/resources/dims_types.html#shape">shape</a> of the Tensor, i.e., the sizes of each dimension. @return

In a session, computes and returns the value of this variable. This is not a graph construction method, it does not add ops to the graph. Th

Maps `map_func` across the elements of this dataset. This transformation applies `map_func` to each element of this dataset, and returns a ne

Custom implementation of session() for XLA tests. We override the standard Tensorflow session() since it is too specific to CPU and GPU tests

Creates a `Dataset` whose elements are slices of the given tensors. Note that if `tensors` contains a NumPy array, and eager execution is not

Creates a `Dataset` by concatenating the given dataset with this dataset. ```python a = Dataset.range(1, 4) # ==> [ 1, 2, 3 ] b = Datase

Returns a Tiled sharding attribute. This causes an op to be partially computed on multiple cores in the XLA device. Args: tile_ass

Returns the size of the dimension at the given index.

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

Returns a context manager selecting this Strategy as current. Inside a `with strategy.scope():` code block, this thread will use a variable c

Returns a symbolic handle to one of the tensors produced by this operation. <p>Warning: Does not check that the type of the tensor matches T. It is r

We still have that one convenience accessor to avoid the awkward double bracket issue: shape.dims()[i].

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

Modifies the pattern to match only if the instruction has the given name.

Adds a layer instance on top of the layer stack. Arguments: layer: layer instance. Raises: TypeError: If `layer` is not a la

Slice a RichTextLines object. The object itself is not changed. A sliced instance is returned. Args: begin: (int) Beginning line index

Returns the next record (key, value) pair produced by a reader. Will dequeue a work unit from queue if necessary (e.g. when the Reader needs

Returns `Tensor`'s shape partitioned into `sample`, `batch`, `event`. Args: x: `Tensor`. name: Python `str`. The name to give this op

Computes the gradient using operations recorded in context of this tape. Args: target: a list or nested structure of Tensors or Variables t

Outputs random values from a uniform distribution. The generated values follow a uniform distribution in the range `[minval, maxval)`. The lo

The function to predict.