2VhnddlmZddlmZddlmZddlmZddlmZ edGddejZ y ) )backend)layers) keras_export)_list_variables_used_by_fns) tensorflowzkeras.layers.TFSMLayercFeZdZdZ dfd ZdZddZfdZxZS) TFSMLayeragReload a Keras model/layer that was saved via SavedModel / ExportArchive. Arguments: filepath: `str` or `pathlib.Path` object. The path to the SavedModel. call_endpoint: Name of the endpoint to use as the `call()` method of the reloaded layer. If the SavedModel was created via `model.export()`, then the default endpoint name is `'serve'`. In other cases it may be named `'serving_default'`. Example: ```python model.export("path/to/artifact") reloaded_layer = TFSMLayer("path/to/artifact") outputs = reloaded_layer(inputs) ``` The reloaded object can be used like a regular Keras layer, and supports training/fine-tuning of its trainable weights. Note that the reloaded object retains none of the internal structure or custom methods of the original object -- it's a brand new layer created around the saved function. **Limitations:** * Only call endpoints with a single `inputs` tensor argument (which may optionally be a dict/tuple/list of tensors) are supported. For endpoints with multiple separate input tensor arguments, consider subclassing `TFSMLayer` and implementing a `call()` method with a custom signature. * If you need training-time behavior to differ from inference-time behavior (i.e. if you need the reloaded object to support a `training=True` argument in `__call__()`), make sure that the training-time call function is saved as a standalone endpoint in the artifact, and provide its name to the `TFSMLayer` via the `call_training_endpoint` argument. c htjdk7r tdt | |||tj j ||_||_||_ ||_ t|j|rt|j||_ ns||jjvr|jj||_ n,> $ND ! d00;; ;$($6$6$A$A-$PD ! 0$ **55::<=> @  "t))+AB18&&(>2.(4+=+=+H+HH151C1C1N1N*2.!$%;$<=( D..99>>@AB D(() ! NN499 :/8 T )A  % %a ( ) )A  % %a ( ) c tj||j|j|j|j j dd}|j|y)zTracks an existing weight./_) initializerr r shaper N)rVariabler r r/r replace_track_variable)r#weightvariables r)r!zTFSMLayer._add_existing_weightzsP##&&,,,,$$S#.   X&r*c j|r|jr|j|fi|S|j|fi|S)N)rrr)r#inputstrainingkwargss r)callzTFSMLayer.calls> **5t55fGGG$t$$V6v66r*ctt|}|j|j|jd}i||S)N)rrr)r get_configrrr)r# base_configconfigr(s r)r;zTFSMLayer.get_configsDg(*  !//&*&A&A   )+(((r*)serveNTNN)F) __name__ __module__ __qualname____doc__rr!r9r; __classcell__)r(s@r)r r s5$R# HT '7 ))r*r N) keras.srcrrkeras.src.api_exportrkeras.src.export.saved_modelrkeras.src.utils.module_utilsrrLayerr r*r)rJs<-D9&'K) K)(K)r*