rbegin/rend for iterating over all nodes in reverse.

Set the string values of an attribute of the operation being built. @param name attribute name @param value attribute values @return the OperationBui

Get all the valid tests configs to run. Returns: all the valid test configs as tuples of data_format and use_gpu.

Returns the value of `key` if it exists, else `default`.

Test-only.

Returns whether any errors have occurred while entraining work for this stream.

Atomically set the value. Args: value: integer value.

Returns a hashable reference object to this Tensor. Warning: Experimental API that could be changed or removed. The primary usecase for this

Construct a `DeviceSpec` from a string. Args: spec: a string of the form /job:<name>/replica:<id>/task:<id>/device:CPU:<id> or

Make device, colocation and dependencies stacks thread-local. Device, colocation and dependencies stacks are not thread-local be default. If

How many elements are in the array with this shape.

NewSession creates a new execution session with the associated graph. options may be nil to use the default options.

Creates a constant tensor. The resulting tensor is populated with values of type `dtype`, as specified by arguments `value` and (optionally) `sha

Returns the inputs handle shapes and types, for the resource tensor output at index <idx>. Returns NULL if the shape and types were not available.

A wrapper around CommandHandlerRegistry.register_command_handler(). In addition to calling the wrapped register_command_handler() method, this

Return a unique operation name for `name`. Note: You rarely need to call `unique_name()` directly. Most of the time you just need to create

static */

Returns a `tf.train.ClusterDef` protocol buffer based on this cluster.

r"""Converts two real numbers to a complex number. Given a tensor `real` representing the real part of a complex number, and a tensor `imag` repr

Applies the given transform(s) to the image(s). Args: images: A tensor of shape (num_images, num_rows, num_columns, num_channels) (NHWC)

Returns the InferenceContext for 'node', if present.

Wrapper for the square function to reduce verbosity.

Returns the value of the attr of this op with the given `name`. Args: name: The name of the attr to fetch. Returns: The value of

Returns the number of parameters for this computation.

Returns a `tf.Operation` to write a dataset to a file. Args: dataset: a `tf.data.Dataset` whose elements are to be written to a file R

Returns a Cholesky factor as a `LinearOperator`. Given `A` representing this `LinearOperator`, if `A` is positive definite self-adjoint, retu

Functional interface for the densely-connected layer. This layer implements the operation: `outputs = activation(inputs * kernel + bias)` where

Instantiates a `Loss` from its config (output of `get_config()`). Args: config: Output of `get_config()`. Returns: A `Loss`

Invoke make to build tflite C++ sources. Build dependencies: apt-get install swig libjpeg-dev zlib1g-dev python3-dev python3-nump

Set up argument parser, and parse CLI args.