&Vf &4ddlZddlZddlmZddlmZddlmZddlm Z ddl m Z ddl m Z  ddl Z n #e$rdZ YnwxYwedd gdd Zed d gddZedddZedddZdS)N)logging) keras_export)legacy_h5_format) saving_lib) file_utils)io_utilszkeras.saving.save_modelzkeras.models.save_modelTc |dd}|dd}|rnt|ds"t|drtjd|nt d||r1t d t |t|drtjd  tj |}n#t$rd}YnwxYw|r|stj |}|sd St|drtj||d St|drt!j||||d St d |d )aSaves a model as a `.keras` file. Args: model: Keras model instance to be saved. filepath: `str` or `pathlib.Path` object. Path where to save the model. overwrite: Whether we should overwrite any existing model at the target location, or instead ask the user via an interactive prompt. Example: ```python model = keras.Sequential( [ keras.layers.Dense(5, input_shape=(3,)), keras.layers.Softmax(), ], ) model.save("model.keras") loaded_model = keras.saving.load_model("model.keras") x = keras.random.uniform((10, 3)) assert np.allclose(model.predict(x), loaded_model.predict(x)) ``` Note that `model.save()` is an alias for `keras.saving.save_model()`. The saved `.keras` file contains: - The model's configuration (architecture) - The model's weights - The model's optimizer's state (if any) Thus models can be reinstantiated in the exact same state. include_optimizerT save_formatF.h5.hdf5.keraszThe `save_format` argument is deprecated in Keras 3. We recommend removing this argument as it can be inferred from the file path. Received: save_format=zThe `save_format` argument is deprecated in Keras 3. Please remove this argument and pass a file path with either `.keras` or `.h5` extension.Received: save_format=z-The following argument(s) are not supported: aYou are saving your model as an HDF5 file via `model.save()` or `keras.saving.save_model(model)`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')` or `keras.saving.save_model(model, 'my_model.keras')`. NaInvalid filepath extension for saving. Please add either a `.keras` extension for the native Keras format (recommended) or a `.h5` extension. Use `model.export(filepath)` if you want to export a SavedModel for use with TFLite/TFServing/etc. Received: filepath=.)popstrendswithrwarning ValueErrorlistkeysospathexists TypeErrorrask_to_proceed_with_overwriter save_modelrsave_model_to_hdf5)modelfilepath overwritekwargsr r rproceeds X/var/www/html/software/conda/lib/python3.11/site-packages/keras/src/saving/saving_api.pyrrsRF #6==**]E22K x== ! !"2 3 3 s8}}7M7M 8 8   O7*577    7*577    %FKKMM"" % %    8}}.//  C   ))  i8BB  F 8}}h'' eX..... X   0 1 1  + 8Y(9      . #+  . . .   sD'' D65D6zkeras.saving.load_modelzkeras.models.load_modelct|dotj|}t j|rt j|s}|s{tj tj tj |}t j ||tj|r|}d}|rtj||||St|drtj|||St|drt#d|dt#d|d |d ) aLoads a model saved via `model.save()`. Args: filepath: `str` or `pathlib.Path` object, path to the saved model file. custom_objects: Optional dictionary mapping names (strings) to custom classes or functions to be considered during deserialization. compile: Boolean, whether to compile the model after loading. safe_mode: Boolean, whether to disallow unsafe `lambda` deserialization. When `safe_mode=False`, loading an object has the potential to trigger arbitrary code execution. This argument is only applicable to the Keras v3 model format. Defaults to `True`. Returns: A Keras model instance. If the original model was compiled, and the argument `compile=True` is set, then the returned model will be compiled. Otherwise, the model will be left uncompiled. Example: ```python model = keras.Sequential([ keras.layers.Dense(5, input_shape=(3,)), keras.layers.Softmax()]) model.save("model.keras") loaded_model = keras.saving.load_model("model.keras") x = np.random.random((10, 3)) assert np.allclose(model.predict(x), loaded_model.predict(x)) ``` Note that the model variables may have different name values (`var.name` property, e.g. `"dense_1/kernel:0"`) after being reloaded. It is recommended that you use layer attributes to access specific variables, e.g. `model.get_layer("dense_1").kernel`. rT)custom_objectscompile safe_moder )r&r'zFile not found: filepath=z<. Please ensure the file is an accessible `.keras` zip file.$File format not supported: filepath=a. Keras 3 only supports V3 `.keras` files and legacy H5 format files (`.h5` extension). Note that the legacy SavedModel format is not supported by `load_model()` in Keras 3. In order to reload a TensorFlow SavedModel as an inference-only layer in Keras 3, use `keras.layers.TFSMLayer(za, call_endpoint='serving_default')` (note that your `call_endpoint` might have a different name).)rrzipfile is_zipfileris_remote_pathisdirrrjoinr get_temp_dirbasenamecopy load_modelrload_model_from_hdf5r)r r&r'r( is_keras_zip local_paths r$r2r2tsJx==))(338J99L !(++  **  W\\  # % %rw'7'7'A'A  *---  j ) ) !HL $ )      8}}.// 4 ^W     X   ) )         ,8 , , , , ,   zkeras.saving.save_weightsc 2t|dstd| tj|}n#t $rd}YnwxYw|r|stj|}|sdStj ||fi|dS)N .weights.h5z;The filename must end in `.weights.h5`. Received: filepath=F) rrrrrrrrrrsave_weights_only)rr r!r"rr#s r$ save_weightsr:s x== ! !- 0 0  -"* - -   ))  i8BB  F ;;F;;;;;sA A%$A%zkeras.saving.load_weightsFc t|dr-|rtd|tj|||dSt|drD|dd}|rtd|tj||||dSt|ds"t|dr|d d }|rtd|t std t j|d 5}d |j vr d|vr|d}|rtj |||ntj ||ddddS#1swxYwYdStd|d)NrzInvalid keyword arguments: ) skip_mismatchr8objects_to_skip)r<r=r rby_nameFz2Loading a H5 file requires `h5py` to be installed.r layer_names model_weightsr)zY. Keras 3 only supports V3 `.keras` and `.weights.h5` files, or legacy V1/V2 `.h5` files.) rrrrload_weights_onlyrh5py ImportErrorFileattrsr$load_weights_from_hdf5_group_by_nameload_weights_from_hdf5_group)rr r<r"r=r>fs r$ load_weightsrJs 8}}h''&  EC6CCDD D$ 8=       X   . .   **%6==  EC6CCDD D$  '+       X   & & #h--*@*@*I*I **Y..  EC6CCDD D D Yx % % HAG++10D0Do& H Eum!=aGGG H H H H H H H H H H H H H H H H H H 28 2 2 2   sAF  F$'F$)T)NTT)F)rr*abslrkeras.src.api_exportrkeras.src.legacy.savingrkeras.src.savingrkeras.src.utilsrrrCrDrr2r:rJr6r$rQs ------444444''''''&&&&&&$$$$$$KKKK DDD(*CDEE^ ^ ^ FE^ B(*CDEEX X X FEX v)**<<<+*<")**' ' ' +*' ' ' s 3==