a 0Sic7*@sdZddlZddlZddlZddlZddlmZddlmZddlm Z ddl m Z ddl m Z ddlmZgaGd d d eZe jd d Zd dZGdddeZGdddeee jZedGdddeZGdddeZdS)z7Definitions for resource-type trackable object classes.N)context) def_function)ops)base) tf_contextlib) tf_exportc@s2eZdZdZdgZddZeddZddZd S) ResourceTrackerz*An object that tracks a list of resources. _resourcescCs g|_dSNr selfr`/var/www/html/django/DPS/env/lib/python3.9/site-packages/tensorflow/python/trackable/resource.py__init__'szResourceTracker.__init__cCs|jSr r r rrr resources*szResourceTracker.resourcescCs|j|dSr )r append)r resourcerrr add_resource.szResourceTracker.add_resourceN) __name__ __module__ __qualname____doc__ __slots__rpropertyrrrrrrr"s  rccs,tt}t|zdVW|an|a0dS)aA context to manage resource trackers. Use this in order to collect up all resources created within a block of code. Example usage: ```python resource_tracker = ResourceTracker() with resource_tracker_scope(resource_tracker): resource = TrackableResource() assert resource_tracker.resources == [resource] Args: resource_tracker: The passed in ResourceTracker object Yields: A scope in which the resource_tracker is active. 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Example usage: >>> class DemoResource(tf.saved_model.experimental.TrackableResource): ... def __init__(self): ... super().__init__() ... self._initialize() ... def _create_resource(self): ... return tf.raw_ops.VarHandleOp(dtype=tf.float32, shape=[2]) ... def _initialize(self): ... tf.raw_ops.AssignVariableOp( ... resource=self.resource_handle, value=tf.ones([2])) ... def _destroy_resource(self): ... tf.raw_ops.DestroyResourceOp(resource=self.resource_handle) >>> class DemoModule(tf.Module): ... def __init__(self): ... self.resource = DemoResource() ... def increment(self, tensor): ... return tensor + tf.raw_ops.ReadVariableOp( ... resource=self.resource.resource_handle, dtype=tf.float32) >>> demo = DemoModule() >>> demo.increment([5, 1]) r9cs*tD]}||qtt|j|ddS)acInitialize the `TrackableResource`. Args: device: A string indicating a required placement for this resource, e.g. "CPU" if this resource must be created on a CPU device. A blank device allows the user to place resource creation, so generally this should be blank unless the resource only makes sense on one device. rAN)rrrarnr)r rArrgrrrs  zTrackableResource.__init__)r9)rrrrrrmrrrgrrns'rncs6eZdZdZd fdd ZeddZddZZS) RestoredResourcezRestored SavedResource.r9cstt|j|ddS)Nro)rarprr@rgrrr&szRestoredResource.__init__cKs*||jjd}|d}|dur&||_|S)NrorG)rrAgetrG)r. object_proto dependencies unused_kwargsr,resource_creatorrrr_deserialize_from_proto)s  z(RestoredResource._deserialize_from_protocCs4t|||t|tjr0t|tjs0|||dSr )setattrrIr TrackablerFunction_track_trackable)r namerOrrr_add_trackable_child1s    z%RestoredResource._add_trackable_child)r9) rrrrrrkrvr|rmrrrgrrp#s  rp)rrCrSrLsixtensorflow.python.eagerrrtensorflow.python.frameworkrtensorflow.python.trackablertensorflow.python.utilr tensorflow.python.util.tf_exportrrobjectrcontextmanagerrr&typer'with_metaclassrxr8rnrprrrrs,        8