BVhD*<dZddlZddlZddlZddlmZddlmZddlmZddlm Z ddl m Z ddl m Z dd lmZgaGd d Ze j$d Zd ZGddeZGdde j.eZedGddeZGddeZy)z7Definitions for resource-type trackable object classes.N)context) def_function)ops)tensor)base) tf_contextlib) tf_exportc2eZdZdZdgZdZedZdZy)ResourceTrackerz*An object that tracks a list of resources. _resourcescg|_yNr selfs T/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/trackable/resource.py__init__zResourceTracker.__init__&s DOc|jSrrrs r resourceszResourceTracker.resources)s ??rc:|jj|yr)r append)rresources r add_resourcezResourceTracker.add_resource-sOO8$rN) __name__ __module__ __qualname____doc__ __slots__rpropertyrrrrr r !s*2n)  %rr c#pKtt}tj| d|ay#|awxYww)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. N)list_RESOURCE_TRACKER_STACKr)resource_trackerolds rresource_tracker_scoper'1s6* $%#  !12" !cs%6/636cfd}|S)z"To avoid capturing loop variables.cg|i|Srr!)argskwargscaptured_gettercaptured_previouss rgetterz_make_getter..getterQs , >t >v >>rr!)r,r-r.s`` r _make_getterr/Ns? -rceZdZdZdZy)_ResourceMetaclassz!Metaclass for CapturableResource.cfdfd}tjj}|jD]}t ||}||i|S)Nc`|Jjg|i|}|j|i||Sr)__new__r) next_creatorakwobjclss rdefault_resource_creatorz=_ResourceMetaclass.__call__..default_resource_creator\sA  !! ! CKK &a &2 &ccllA jrcdg|i|Srr!)r6r7r:s rz-_ResourceMetaclass.__call__..bs'?'Oq'OB'Or)rget_default_graph_resource_creator_stack_resource_typer/)r9r*r+previous_getterresource_creator_stackr.r:s` @r__call__z_ResourceMetaclass.__call__Zs` PO 224LL(););)=>>$V_=o> D +F ++rN)rrrrrBr!rrr1r1Ws ) ,rr1ceZdZdZddZedZedZejdZdZ edZ e jdZ d Z d Z ed Zd Zej"j$ffd ZdZxZS)CapturableResourceazHolds a Tensor which a tf.function can capture. `CapturableResource`s are discovered by traversing the graph of object attributes, e.g. during `tf.saved_model.save`. They are excluded from the scope-based tracking of `TrackableResource`; generally things that require initialization should inherit from `TrackableResource` instead of `CapturableResource` directly. cd|_||_tjrtj|_yt j j|_y)adInitialize the `CapturableResource`. 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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N) _resource_handle_value_resource_devicerexecuting_eagerly eager_moderr= as_default_self_destruction_context)rdevices rrzCapturableResource.__init__tsJ#'D"D%779 "  " " $ / / "rc|jSr)r)r9s rr?z!CapturableResource._resource_types <<rc8t|dtjS)NrK)getattr contextlibsuppressrs r_destruction_contextz'CapturableResource._destruction_contexts 44&& ((rc||_yr)rK)rdestruction_contexts rrRz'CapturableResource._destruction_contexts %8D"rctd)z*A function that creates a resource handle.z3TrackableResource._create_resource not implemented.)NotImplementedErrorrs r_create_resourcez#CapturableResource._create_resources - ..rc|jSr)rFrs r_resource_handlez#CapturableResource._resource_handles  & &&rct|tjtjfrt j ||_||_yr) isinstancerTensorr EagerTensorweakrefref_parent_trackablerF)rvalues rrYz#CapturableResource._resource_handles2%&--9: ' D 1e"'Drcy)z3A function that initializes the resource. Optional.Nr!rs r _initializezCapturableResource._initializercy)z0A function that destroys the resource. Optional.Nr!rs r_destroy_resourcez$CapturableResource._destroy_resourcerdrc|jItj|j5|j |_ddd|jS|jS#1swY|jSxYw)z:Returns the resource handle associated with this Resource.N)rYrrLrGrWrs rresource_handlez"CapturableResource.resource_handlesf $ ::d++ ,8 $ 5 5 78   4  8   s A""A6c tj|}tj|j5|j }ddd|_|||<|||j <|j gS#1swY1xYw)zFor implementing `Trackable`.N)copyrrLrGrWrYrh)r object_map tensor_map unused_kwargsnew_obj new_resources r_export_to_saved_model_graphz/CapturableResource._export_to_saved_model_graphswiioG D)) *0--/l0+GJt'3Jt##$  !! 00s A66A?c t|fi|}|dk(rrtjgdfd}tjgdfd}tjgdfd}|j |||d|S)N savedmodelF)input_signature autographc(j}|Sr)rW)rrs r_creatorz8CapturableResource._trackable_children.._creators((*rc&jyN)rcrsr _initializerz._initializers rc&jyrx)rfrsr _destroyerz:CapturableResource._trackable_children.._destroyers  r)rWrcrf)super_trackable_childrenrfunctionupdate)r save_typer+childrenrvrzr| __class__s` rr~z&CapturableResource._trackable_childrensw*9??HL R5ABR5ABR5ABoo&%) Orc |j5|jdddy#1swYyxYw#t$rYywxYwr)rRrf Exceptionrs r__del__zCapturableResource.__del__sM   $ $ &!  !!!    s#8,8588 AA)rrrrr classmethodr?r rRsetterrWrYrcrfrhrprSaveType CHECKPOINTr~r __classcell__rs@rrDrDjs 1 ( ( 99.  ' '((    ! ! "+/--*B*B2 rrD) metaclassz*saved_model.experimental.TrackableResourcec$eZdZdZdfd ZxZS)TrackableResourceaiHolds a Tensor which a tf.function can capture. A TrackableResource is most useful for stateful Tensors that require initialization, such as `tf.lookup.StaticHashTable`. `TrackableResource`s are discovered by traversing the graph of object attributes, e.g. during `tf.saved_model.save`. A TrackableResource has three methods to override: * `_create_resource` should create the resource tensor handle. * `_initialize` should initialize the resource held at `self.resource_handle`. * `_destroy_resource` is called upon a `TrackableResource`'s destruction and should decrement the resource's ref count. For most resources, this should be done with a call to `tf.raw_ops.DestroyResourceOp`. 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]) c^tD]}|j|t| |y)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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