Ë •\;j'ãóX—ddlZddlZddlZddlmZmZddlmZgZ Gd„d«Z d d„Z y) éNé)Údefault_main_programÚin_dygraph_modeé)Úlazy_init_helpercó:—eZdZdZd„Zd d„Zd d„Zd d„Zd„Zd„Z y) Ú InitializeraBase class for parameter initializers Defines the common interface of parameter initializers. They add operations to the init program that are used to initialize parameter. Users should not use this class directly, but need to use one of its implementations. có—y©N©)Úselfs újG:\00. PROJECTS\API\Inventory\templateJSON\kerjaOCR\Lib\site-packages\paddle/nn/initializer/initializer.pyÚ__init__zInitializer.__init__#s€Ø óNcór—t«js|j||«S|j||«Sr )rÚstateÚforwardÚ _lazy_init©r ÚparamÚblocks rÚ__call__zInitializer.__call__&s0€ÜÓ!×'Ò'Ø—<‘<  uÓ-Ð -à‰˜u eÓ,Ð,rcó—t«‚)z;Add corresponding initialization operations to the network.)ÚNotImplementedErrorrs rrzInitializer.forward,s €ä!Ó#Ð#rcóÊ—t«sJ‚d„}|jtj|j««tj||j«|_|S)z+ Apply lazy initialization cóz—|jd|¬«}t«5|||«ddd«y#1swYyxYw)NT)r)Ú_to_static_varr)rrrÚnew_vars rÚinit_op_creatorz/Initializer._lazy_init..init_op_creator6s3€Ø×*Ñ*¨4°uÐ*Ó=ˆGä!Õ#Ù˜ Ô'÷$×#Ñ#úsž 1±:)rÚ set_init_funcÚ functoolsÚpartialrÚ_init_op_creator)r rrrs rrzInitializer._lazy_init0sW€ôÔ Ð Ð ò (ð ×ÑœI×-Ñ-¨d¯l©lÓ;Ô<Ü!*×!2Ñ!2Ø ˜TŸ\™\ó" ˆÔðˆ rcó:—|€t«j«}|Sr )rÚ global_block)r rs rÚ _check_blockzInitializer._check_blockDs€Ø ˆ=Ü(Ó*×7Ñ7Ó9ˆEàˆ rcó —|j}|rt|«dk(rdx}}||fSt|«dk(r |dx}}||fSt|«dk(r|d}|d}||fStj|dd«}|d|z}|d|z}||fS)aèCompute the fan_in and the fan_out for layers This method computes the fan_in and the fan_out for neural network layers, if not specified. It is not possible to perfectly estimate fan_in and fan_out. This method will estimate it correctly for matrix multiply and convolutions. Args: var: variable for which fan_in and fan_out have to be computed. Returns: tuple of two integers (fan_in, fan_out). rréN)ÚshapeÚlenÚnpÚprod)r Úvarr)Úfan_inÚfan_outÚreceptive_field_sizes rÚ _compute_fanszInitializer._compute_fansJsŀ𗠑 ˆÙœ˜E›  ašØ Ð ˆFWð ˜Ð Ð ô‹Z˜1Š_Ø$ Q™xÐ 'ˆFWð˜Ð Ð ô‹Z˜1Š_à˜1‘XˆFؘA‘hˆGð˜Ð Ð ô $&§7¡7¨5°°¨9Ó#5Рؘ1‘XÐ 4Ñ4ˆFؘA‘hÐ!5Ñ5ˆGà˜Ð Ð rr ) Ú__name__Ú __module__Ú __qualname__Ú__doc__rrrrr&r1r rrr r s%„ñò ó-ó $óò(ó !!rr có$—|€d}n(t|tttf«sJ‚t|«}dddddddddt j d«t j dd|dzzz «ddœ }||j «vr||Std|›d «‚) aª Get the recommended ``gain`` value of some nonlinearity function. ``gain`` value can be used in some ``paddle.nn.initializer`` api to adjust the initialization value. Args: nonlinearity(str): name of nonlinearity activation function. If it is a linear function, such as: `linear/conv1d/conv2d/conv3d/conv1d_transpose/conv2d_transpose/conv3d_transpose` , 1.0 will be returned. param(bool|int|float, optional): optional parameter for somme nonlinearity function. Now, it only applies to 'leaky_relu'. Default: None, it will be calculated as 0.01 in the formula. Returns: A float value, which is the recommended gain for this nonlinearity function. Examples: .. code-block:: python >>> import paddle >>> gain = paddle.nn.initializer.calculate_gain('tanh') >>> print(gain) 1.6666666666666667 >>> # 5.0 / 3 >>> gain = paddle.nn.initializer.calculate_gain('leaky_relu', param=1.0) >>> print(gain) 1.0 >>> # math.sqrt(2.0 / (1+param^2)) >>> initializer = paddle.nn.initializer.Orthogonal(gain) g{®Gáz„?rg«ªªªªªú?g@r(gè?) ÚsigmoidÚlinearÚconv1dÚconv2dÚconv3dÚconv1d_transposeÚconv2d_transposeÚconv3d_transposeÚtanhÚreluÚ leaky_reluÚseluznonlinearity function z is not suppported now.)Ú isinstanceÚboolÚintÚfloatÚmathÚsqrtÚkeysÚ ValueError)Ú nonlinearityrÚrecommended_gains rÚcalculate_gainrMns±€ð< €}؉ä˜%¤$¬¬UÐ!3Ô4Ð4Ð4Üe“ ˆàØØØØØØØØÜ— ‘ ˜#“Ü—i‘i  q¨5°!©8¡|Ñ 4Ó5Øñ ÐðÐ'×,Ñ,Ó.Ñ.Ø  Ñ-Ð-äØ$ \ NÐ2IÐ Jó ð rr ) r!rGÚnumpyr+Úbase.frameworkrrÚ lazy_initrÚ__all__r rMr rrÚrRs-ðóÛ ãçCÝ'à €÷Q!ñQ!ôh6 r