BVh?, dZddlZddlZddlZddlZddlmZddlmZ ddlm Z ddl m Z ddl mZddlmZdd lmZdd lmZd ZGd d ZGddej.dgdZdZy)zContains the `Node` class.N)ops)tensor) tensor_util)backend)base_layer_utils) json_utils)tf_utils)nest_CONSTANT_VALUEceZdZdZ ddZedZedZdZdZ dZ ed Z ed Z ed Z ed Zed ZedZy)Nodea A `Node` describes the connectivity between two layers. Each time a layer is connected to some new input, a node is added to `layer._inbound_nodes`. Each time the output of a layer is used by another layer, a node is added to `layer._outbound_nodes`. Args: layer: The Layer for the Layer.__call__ this node represents. call_args: The positional arguments the Layer was called with. call_kwargs: The keyword arguments the Layer was called with. outputs: The outputs of the Layer.__call__ Ncl|gn|}|in|}|gn|}||_| xr| |_tjd|}tjd|}tjd||_||_||_tj|j |j f|_|j xr<t|j dk(xr"tj|j d|_ tjsY|jD]J}t|t j"st%j&|ds6t%j(|Lg|_g|_t/|jD]_\}}t1|s|j*j3|t5t7|}|} |j,j3|| fa|jj8j3||j:D]6} | j<j} | | j>j3|8t|jj8dz } t/tj|D]\}} tA|| || _|j*Dcgc]}t5t7|c}|_!tj|jDcgc]}t5t7|c}|_"ycc}wcc}w) Nc|SNts S/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/keras/engine/node.pyzNode.__init__..EsQc|Srrrs rrzNode.__init__..Fsqrc|Srrrs rrzNode.__init__..GsrrT)ignore_call_contextlayer node_index tensor_index)#ris_inputr map_structureoutputs call_args call_kwargsflatten_flat_argumentslenr is_tf_type _single_positional_tensor_passedr#executing_eagerly_outside_functions isinstance tensor_libTensorrneeds_keras_historycreate_keras_history _keras_inputs_keras_inputs_ids_and_indices enumerateis_keras_tensorappendstrid_inbound_nodes keras_inputs_keras_history_outbound_nodes KerasHistoryflat_input_idsflat_output_ids)selfrr"r#r!objielekt_idkt_indexkt inbound_layerrrrs r__init__z Node.__init__3s  'YI#+"KObGDJ!M5+oDM""; :I$$[+>K%%k7;DLDN"D <<9I9I(JKD151A1A-A.Kc GG.K!,!7!7q8I!J )  2 2 4%%5# sJ-- .  0 0 /  / / 4 5 D)+D&D001E3   !!#&BsG  **115(2CD E JJ$$T*3''--m  "%%,,T23 TZZ../!3Jt||G45> 6**1>f> 04/A/AB!3r!u:BD04 T\\0JK1C1JKDCKs L,L1c|jS)zFTensors input to this node that can be traced back to a `keras.Input`.)r/r=s rr7zNode.keras_inputsss   rcg}|jD]O}|jj}|jj}|2|j |j |Q|S)zFReturns all the `Node`s whose output this node immediately depends on.)r7r8rrr3r6)r= node_depsrCrrs r parent_nodeszNode.parent_nodesxsgI;%%e$$//j  --j9: ; rc#K|jD]:}|j}|j}|j}|j}||||f<yw)zYields tuples representing the data inbound from other nodes. Yields: tuples like: (inbound_layer, node_index, tensor_index, tensor). N)r7r8rrr)r=rC keras_historyrrrs riterate_inboundzNode.iterate_inboundsX 0''m!!e ++j"//l :|R // 0sA A cb|jr(|jd\}}||jfifStj|j}|jD]\}}||j||<t j |j|jf|\}}||fS)z;Maps Keras Tensors to computed Tensors using `tensor_dict`.r) r(r0popcopyr%r pack_sequence_asr"r#)r= tensor_dictrA_flat_argumentsrBargskwargss r map_argumentszNode.map_argumentss ,,33A6heQ% $$& (" ,,yy!5!56n!??._serialize_keras_tensors $ %   ]]   ;,001= ~r?? Arzz "xxz Az(( )  #**,, hr)defaultzLayer z- was passed non-JSON-serializable arguments. zArguments had types: z6. They cannot be serialized out when saving the model.c<t|rl|j}|j}|jj|} j |d}|jj||j g}ntd|g}tj|S)Nr) r2r8rrr[r\rr r ListWrapper) rrarrbrcdatarfrVrdres rserialize_first_arg_tensorz2Node.serialize..serialize_first_arg_tensors     ]]   ;,001= ~rG  %>4#3#3LD&::::4HFD&S11!"5t<=I V F"   7 @F0 jj!9!9: (   8& AD NN4 JJ : :Vd  + +D 1D K= 0&&tV4k h0EF-.+&'*// 000s %D""AE=cR|jr |jgS|jdS)Nr)rr!r"rGs r input_tensorszNode.input_tensorss$ }}ll^ >>! rcL|jr |jgS|jSr)rr!rGs routput_tensorszNode.output_tensorss }}ll^ <<rctjtj|j}t |dk(r|j s|dS|S)Nrr)r r r int_shaperr&r)r= input_shapess rrzNode.input_shapessC%%g&7&79K9KLL <Admm !_ rc^tjtj|jSr)r r rrrrGs r output_shapeszNode.output_shapess!   g//1D1D EErc|jSr)rrGs routbound_layerzNode.outbound_layers ::rcj|jrgStjd|jd}|S)Nc.|jjSr)r8rrs rrz%Node.inbound_layers..s!2B2B2H2Hrr)rr r r")r=inbound_layerss rrzNode.inbound_layerss3 }} i''(H(,q(9;N r)NNN)__name__ __module__ __qualname____doc__rEpropertyr7rJrMrWr}rrrrrrrrrr r $s   >L@     0 =J          F F    rr ceZdZdZdZy)r:a}Tracks the Layer call that created a Tensor, for Keras Graph Networks. During construction of Keras Graph Networks, this metadata is added to each Tensor produced as the output of a Layer, starting with an `InputLayer`. This allows Keras to track how each Tensor was produced, and this information is later retraced by the `keras.engine.Network` class to reconstruct the Keras Graph Network. Attributes: layer: The Layer that produced the Tensor. node_index: The specific call to the Layer that produced this Tensor. Layers can be called multiple times in order to share weights. A new node is created every time a Layer is called. tensor_index: The output index for this Tensor. Always zero if the Layer that produced this Tensor only has one output. Nested structures of Tensors are deterministically assigned an index via `nest.flatten`. rN)rrrr __slots__rrrr:r:s&)rr:rct|dS)Nr8)rZ)r>s rr2r2!s & ''r)r collectionsrPrrnumpyr]tensorflow.python.frameworkrrr+rtensorflow.python.kerasrtensorflow.python.keras.enginer*tensorflow.python.keras.saving.saved_modelrtensorflow.python.keras.utilsr tensorflow.python.utilr r r namedtupler:r2rrrrse"! +<3+;A2'#aaHK>BD2(r