2VhtddlZddlZddlmZddlmZddlmZddlm Z ddlm Z ddlm Z ddlm Z dd lm Z dd lmZdd lmZdd lmZdd lmZddlmZddlmZddlmZddlmZddlmZddlmZddlmZddlmZddlmZddlmZee e e e e eeeeeeeeeeehZ e Dcic]}|jB|c}Z"e"jGe Dcic]}e|jB|c}e"jGe ee e eee deddZ$edddZ%eddZ&ycc}wcc}w) N)backend)ops) keras_export)STFT)Constant)Identity)Ones)Zeros) Initializer) GlorotNormal) GlorotUniform)HeNormal) HeUniform) LecunNormal) LecunUniform) Orthogonal) RandomNormal) RandomUniform)TruncatedNormal)VarianceScaling)serialization_lib) to_snake_case)IdentityInitializernormaloneSTFTInitializerOrthogonalInitializeruniformzerozkeras.initializers.serializec,tj|S)z7Returns the initializer configuration as a Python dict.)rserialize_keras_object) initializers O/home/dcms/DCMS/lib/python3.12/site-packages/keras/src/initializers/__init__.py serializer$Bs  3 3K @@zkeras.initializers.deserializec:tj|t|S)z9Returns a Keras initializer object via its configuration.)module_objectscustom_objects)rdeserialize_keras_objectALL_OBJECTS_DICT)configr(s r# deserializer,Hs   5 5'% r%zkeras.initializers.getcyttr t}ntttrtid}t|}nJt j s*tt jt jfr dfd }|}n}t|rtj|r|}|Std)aRetrieves a Keras initializer object via an identifier. The `identifier` may be the string name of a initializers function or class (case-sensitively). >>> identifier = 'Ones' >>> keras.initializers.get(identifier) <...keras.initializers.initializers.Ones...> You can also specify `config` of the initializer to this function by passing dict containing `class_name` and `config` as an identifier. Also note that the `class_name` must map to a `Initializer` class. >>> cfg = {'class_name': 'Ones', 'config': {}} >>> keras.initializers.get(cfg) <...keras.initializers.initializers.Ones...> In the case that the `identifier` is a class, this method will return a new instance of the class by its constructor. You may also pass a callable function with a signature that includes `shape` and `dtype=None` as an identifier. >>> fn = lambda shape, dtype=None: ops.ones(shape, dtype) >>> keras.initializers.get(fn) at ...> Alternatively, you can pass a backend tensor or numpy array as the `identifier` to define the initializer values directly. Note that when calling the initializer, the specified `shape` argument must be the same as the shape of the tensor. >>> tensor = ops.ones(shape=(5, 5)) >>> keras.initializers.get(tensor) .initialize_fn at ...> Args: identifier: A string, dict, callable function, or tensor specifying the initializer. If a string, it should be the name of an initializer. If a dict, it should contain the configuration of an initializer. Callable functions or predefined tensors are also accepted. Returns: Initializer instance base on the input identifier. N) class_namer+ctj|}tj|tjjk7rt djd|t j |S)NzExpected `shape` to be z2 for direct tensor as initializer. Received shape=)rstandardize_dtypestandardize_shapeshape ValueErrorrcast)r2dtype identifiers r# initialize_fnzget..initialize_fns}--e4E((/73L3L  4!-j.>.>-?@==BGE88J. .r%z,Could not interpret initializer identifier: N) isinstancedictr,strr is_tensornpgenericndarraycallableinspectisclassr3)r6objr+r7s` r#getrDRs`*d#*% J $ #J2>&! z "jRZZ,' /} ??3 %C ::, G  r%r8)'rAnumpyr= keras.srcrrkeras.src.api_exportr,keras.src.initializers.constant_initializersrrrr r "keras.src.initializers.initializerr *keras.src.initializers.random_initializersr r rrrrrrrrrkeras.src.savingrkeras.src.utils.namingr ALL_OBJECTS__name__r*updater$r,rD)clss0r#rQsT-=AA=>:CD?@BCACDFF.0     # (2==#CLL#%=1<=#]3<< #%='!+  ,-A.A ./0&'P (P G>=s $D0 D5