Performs a sum reduction on `x` across pfor iterations. Note that this currently may not work inside a control flow construct. Args: x:

Returns a unique temporary directory for the test to use. If you call this method multiple times during in a test, it will return the same fo

Gets an existing variable with this name or create a new one.

A deterministic random uniform if seed is passed.

AddOperation adds the operation to the Graph managed by s. If there is a name prefix associated with s (such as if s was created by a call to SubScop

static */

Parse an expression. Args: expression: the expression to be parsed. Returns: The result of the evaluation. Raises: Va

Minimum value in a tensor. Arguments: x: A tensor or variable. axis: An integer, the axis to find minimum values. keepdims: A boo

Returns a TensorFlow Session for use in executing tests. Note that this will set this session and the graph as global defaults. Use the `use

Evaluates given model with provided evaluation data. Stop conditions - we evaluate on the given input data until one of the following: -

Return a pointer to the entry computation of the module.

If you know how many elements you will push at the time you create the TopN object, you can call reserve to preallocate the memory that TopN will need

Group tensors together. This creates a tuple of tensors with the same values as the `tensors` argument, except that the value of each tensor is o

All of Input's constructors are implicit. Input can be implicitly constructed from the following objects : Output: This is so that the output of an Op

Returns the type of the operation, i.e., the name of the computation performed by the operation.

Configures the model for training. Arguments: optimizer: String (name of optimizer) or optimizer instance. See `tf.keras.opti

Returns a list of values in the collection with the given `name`. This is different from `get_collection_ref()` which always returns the actu

Converts a float value into an unsigned eight-bit quantized value.

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

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

Returns the rank (number of dimensions) of the given shape. Shape must be an array.

Append an item to the Menu. Args: item: (MenuItem) the item to be appended.

Returns a TensorArray with the same content and properties. Returns: A new TensorArray object with flow that ensures the control dependenci

- Parameter(N) matches parameter number N. - Parameter() matches any parameter.

Split the values of a `Tensor` into the TensorArray. Args: value: (N+1)-D. Tensor of type `dtype`. The Tensor to split. lengths: 1-

Returns a context manager that specifies the default device to use. The `device_name_or_function` argument may either be a device name string

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

Trains the model for a fixed number of epochs (iterations on a dataset). Arguments: x: Input data. It could be: - A Numpy array

Wrapper around Session.run() that inserts tensor watch options. Args: fetches: Same as the `fetches` arg to regular `Session.run()`.

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

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

Alias of `Variable.shape`.

Warning: note that the pointer returned is not necessarily directly to device virtual address space, but is platform-dependent.

Returns a const iterator pointing to the past-the-end wrapped tensor input.