polygraphy.backend.tf.runner.TfRunner Class Reference

Inheritance diagram for polygraphy.backend.tf.runner.TfRunner:

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Public Member Functions
def	__init__ (self, sess, timeline_dir=None, name=None)
def	activate_impl (self)
def	get_input_metadata (self)
def	deactivate_impl (self)
def	infer_impl (self, feed_dict)
def	last_inference_time (self)
def	__enter__ (self)
def	__exit__ (self, exc_type, exc_value, traceback)
def	activate (self)
def	infer_impl (self)
def	infer (self, feed_dict)
def	deactivate (self)

Public Attributes
	timeline_dir
	num_inferences
	run_options
	run_metadata
	sess
	inference_time
	name
	is_active

Static Public Attributes
	RUNNER_COUNTS = defaultdict(int)

Private Attributes
	_sess

Detailed Description

Runs inference using a TensorFlow session.

Constructor & Destructor Documentation

__init__()

def polygraphy.backend.tf.runner.TfRunner.__init__	(		self,
			sess,
			timeline_dir = None,
			name = None
	)

Args:
    sess (Callable() -> Tuple[tf.Session, Sequence[str]]):
    A callable that can supply a tuple containing a
    TensorFlow session and output names.


    timeline_dir (str):
    Path to write a TensorFlow timeline.
    Note that profiling may affect execution time.
    name (str):
    The human-readable name prefix to use for this runner.
    A runner count and timestamp will be appended to this prefix.

Member Function Documentation

activate_impl()

def polygraphy.backend.tf.runner.TfRunner.activate_impl

(

self

)

Implementation for runner activation. Derived classes should override this function
rather than ``activate()``.

Reimplemented from polygraphy.backend.base.runner.BaseRunner.

get_input_metadata()

def polygraphy.backend.tf.runner.TfRunner.get_input_metadata

(

self

)

Returns information about the inputs of the model.
Shapes here may include dynamic dimensions, represented by ``None``.
Must be called only after activate() and before deactivate().

Returns:
    TensorMetadata: Input names, shapes, and data types.

Reimplemented from polygraphy.backend.base.runner.BaseRunner.

deactivate_impl()

def polygraphy.backend.tf.runner.TfRunner.deactivate_impl

(

self

)

Implementation for runner deactivation. Derived classes should override this function
rather than ``deactivate()``.

Reimplemented from polygraphy.backend.base.runner.BaseRunner.

infer_impl() [1/2]

def polygraphy.backend.tf.runner.TfRunner.infer_impl	(		self,
			feed_dict
	)

last_inference_time()

def polygraphy.backend.base.runner.BaseRunner.last_inference_time (   self )

inherited

Returns the total inference time required during the last call to ``infer()``.

Returns:
    float: The time in seconds, or None if runtime was not measured by the runner.

__enter__()

def polygraphy.backend.base.runner.BaseRunner.__enter__ (   self )

inherited

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__exit__()

def polygraphy.backend.base.runner.BaseRunner.__exit__ (   self,   exc_type,   exc_value,   traceback  )

inherited

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activate()

def polygraphy.backend.base.runner.BaseRunner.activate (   self )

inherited

Activate the runner for inference. This may involve allocating GPU buffers, for example.

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infer_impl() [2/2]

def polygraphy.backend.base.runner.BaseRunner.infer_impl (   self )

inherited

Implementation for runner inference. Derived classes should override this function
rather than ``infer()``

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infer()

def polygraphy.backend.base.runner.BaseRunner.infer (   self,   feed_dict  )

inherited

Runs inference using the provided feed_dict.

Args:
    feed_dict (OrderedDict[str, numpy.ndarray]): A mapping of input tensor names to corresponding input NumPy arrays.

Returns:
    OrderedDict[str, numpy.ndarray]:
    A mapping of output tensor names to their corresponding NumPy arrays.
    IMPORTANT: Runners may reuse these output buffers. Thus, if you need to save
    outputs from multiple inferences, you should make a copy with ``copy.copy(outputs)``.

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deactivate()

def polygraphy.backend.base.runner.BaseRunner.deactivate (   self )

inherited

Deactivate the runner.

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Member Data Documentation

_sess

polygraphy.backend.tf.runner.TfRunner._sess

private

timeline_dir

polygraphy.backend.tf.runner.TfRunner.timeline_dir

num_inferences

polygraphy.backend.tf.runner.TfRunner.num_inferences

run_options

polygraphy.backend.tf.runner.TfRunner.run_options

run_metadata

polygraphy.backend.tf.runner.TfRunner.run_metadata

sess

polygraphy.backend.tf.runner.TfRunner.sess

inference_time

polygraphy.backend.tf.runner.TfRunner.inference_time

RUNNER_COUNTS

polygraphy.backend.base.runner.BaseRunner.RUNNER_COUNTS = defaultdict(int)

staticinherited

name

polygraphy.backend.base.runner.BaseRunner.name

inherited

is_active

polygraphy.backend.base.runner.BaseRunner.is_active

inherited

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The documentation for this class was generated from the following file:

• backend/tf/runner.py