BVhJdZddlZddlmZddlmZddlmZddlmZddlm Z ddl m Z ejad Zeej#tj$d Zd d Zd Zy)z2Keras initializer serialization / deserialization.N)tf2)initializers_v1)initializers_v2) generic_utils) tf_inspect)init_opsc4 ttdsit_dt_tjr&tjt j k(ryit_t j t_t jtjd<t jtjd<t jtjd<t jtjd<t jtjd<t jtjd<t jtjd <t jtjd <t jtjd <t j tjd <t j"tjd <t j$tjd<t j&tjd<t j(tjd<t j*tjd<t jtjd<t jtjd<t jtjd<t jtjd<t jtjd<t jtjd<t j ri}t j,t/j0|t gfd|j3D]>\}}|tj|<|tjt/j4|<@n5t6jt6jt6jt6jt6jt6j t6j(t6j*t8jt8jt8jt8jt8j"t8j$t8j&d}|j3D]>\}}|tj|<|tjt/j4|<@tjdtjd<tjdtjd<tjdtjd <tjd!tjd"<y)#z>Populates dict ALL_OBJECTS with every built-in initializer. ALL_OBJECTSN ConstantV2GlorotNormalV2GlorotUniformV2 HeNormalV2 HeUniformV2 IdentityV2 LecunNormalV2LecunUniformV2OnesV2 OrthogonalV2RandomNormalV2RandomUniformV2TruncatedNormalV2VarianceScalingV2ZerosV2glorot_normalV2glorot_uniformV2 he_normalV2 he_uniformV2lecun_normalV2lecun_uniformV2cJtj|xr t|SN)inspectisclass issubclass)xbase_clss ]/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/keras/initializers/__init__.pyz1populate_deserializable_objects..RsW__Q/KJq(4K) obj_filter)Constant GlorotNormal GlorotUniformIdentityOnes OrthogonalVarianceScalingZerosHeNormal HeUniform LecunNormal LecunUniform RandomNormal RandomUniformTruncatedNormal random_normalnormalrandom_uniformuniformonesonezeroszero)hasattrLOCALr GENERATED_WITH_V2renabledrr+r,r-r3r4r.r5r6r/r0r7r8r9r1r2 Initializerr!populate_dict_with_module_objectsitems to_snake_caserr)v2_objskeyvaluev1_objsr&s @r'populate_deserializable_objectsrN s  &E"E 522ckkmC %KKM%%4$<$<%L!(7(D(D%$%)8)F)F%%&$3$<$<%L!%4%>%>%M"$3$<$<%L!'6'B'B%O$(7(D(D%$% / 4 4%H&5&@&@%N#(7(D(D%$%)8)F)F%%&+:+J+J%'(+:+J+J%'(!0!6!6%I*9)E)E%%&*9*G*G%&'%4%=%=%M"&5&?&?%N#(7(C(C%$%)8)E)E%%&[[]G**H33 KMmmoB U$e>> identifier = 'Ones' >>> tf.keras.initializers.deserialize(identifier) <...keras.initializers.initializers_v2.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': {}} >>> tf.keras.initializers.deserialize(cfg) <...keras.initializers.initializers_v2.Ones...> In the case that the `identifier` is a class, this method will return a new instance of the class by its constructor. Args: identifier: String or dict that contains the initializer name or configurations. Returns: Initializer instance base on the input identifier. Raises: ValueError: If the input identifier is not a supported type or in a bad format. Nz,Could not interpret initializer identifier: ) isinstancedictrYstrcallabler"r# ValueError) identifiers r'getras~B  D! z ""*c"ZJ z "" z"rlsc9!@@7?*  S9r ! ""# ;+.&r)