o e*@sdZddlZddlZddlZddlmZddlmZddlmZddl m Z ddl m Z ddl mZgaGd d d Ze jd d Zd dZGdddeZGddde jedZedGdddeZGdddeZdS)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 selfrTD:\Projects\ConvertPro\env\Lib\site-packages\tensorflow/python/trackable/resource.py__init__%s zResourceTracker.__init__cC|jSr r r rrr resources(zResourceTracker.resourcescCs|j|dSr )r append)r resourcerrr add_resource,szResourceTracker.add_resourceN) __name__ __module__ __qualname____doc__ __slots__rpropertyrrrrrrr s  rccs,tt}t|zdVW|adS|aw)aA context to manage resource trackers. Use this in order to collect up all resources created within a block of code. 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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]) r6cs&tD]}||qtj|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. 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