&Vf<ddlZddlmZddlmZddlmZddlmZddl m Z edGdd e Z d Z d Z d Zd ZdS)N)tree) keras_export) KerasTensor)backend) Operationzkeras.FunctionceZdZdZd fd ZedZedZedZdZ dZ d d Z d Z xZ S) FunctionaClass that encapsulates a computation graph of Keras operations. You can use a `Function` to capture the computation graph linking some input tensors to some output tensors, and reapply the same computation on new inputs. A `Function` is similar to a Functional Model, with the difference that it is stateless (it does not track state variables) and does not implement the `Layer` API. Example: ```python input_1 = keras.KerasTensor(shape=(None, 2, 3)) input_2 = keras.KerasTensor(shape=(None, 2, 3)) x = input_1 + input_2 output = keras.ops.sigmoid(x) fn = keras.Function(inputs=[input_1, input_2], outputs=output) input_1_val = np.random.random((4, 2, 3)) input_2_val = np.random.random((4, 2, 3)) output_val = fn([input_1_val, input_2_val]) ``` Args: inputs: `KerasTensor` instance or nested structured of `KerasTensor` instances. outputs: `KerasTensor` instance or nested structured of `KerasTensor` instances. They should be computable given only the values of `inputs`. name: String. The name of the function. Nct|tdkrt|dd}d|_t jd||_t jd||_t j ||_ t j ||_ |j std|d ||j std |d |tdkr||_t|j |j \}}}}||_||_||_||_dS) Nname tensorflow_self_setattr_trackingTFc|SNxs S/var/www/html/software/conda/lib/python3.11/site-packages/keras/src/ops/function.pyz#Function.__init__..9s1c|Srrrs rrz#Function.__init__..:sArz4`inputs` argument cannot be empty. Received: inputs=z outputs=z5`outputs` argument cannot be empty. Received: inputs=)super__init__rgetattrrr map_structure_inputs_struct_outputs_structflatten_inputs_outputs ValueError map_graph_nodes_nodes_by_depth _operations_operations_by_depth) selfinputsoutputsr rnodesnodes_by_depth operationsoperations_by_depth __class__s rrzFunction.__init__-s} d### 99 $ $ &-.&& "+0D '"0fEE#1++wGG|F++  W-- | % %%"%%  } % %%"%%  99 $ $*@D 'CL L$-D D @ ,? -%$7!!!rc |jddSr)r%r's rr,zFunction.operationsUs""rc|jSr)rr0s rr(zFunction.inputsYs |rc|jSr)r r0s rr)zFunction.outputs]s }rc||d}ttj||jD]\}}|j|jkrd}n|rtjd|jS||dS)NTFc8t|j|jS)N)shapedtype)rr5r6rs rrz.Function.compute_output_spec..ls+AG17CCCrc|jSr)compute_output_specops rrz.Function.compute_output_spec..ts B,Br operation_fn) _assert_input_compatibilityziprrrr5rr_run_through_graph)r'r(shortcutrx_refs rr8zFunction.compute_output_specas ((000DL00$,??  HAuw%+%% &  %CC$ && !B!B'   rc\||||dS)z'Computes output tensors for new inputs.c|Srrr9s rrzFunction.call..zsrrr;)r=r?)r'r(s rcallz Function.callws1 ((000&&vMM&JJJrc,tj|}it|j|D]\}}|t |<|j}t |}|d|D]}||} | D]} | j r| j rtfd| j Dr2| j \} } || j } | || g| Ri| }n| | i| }t| jtj|D]\}}|t |<g}|jD]*}|t |+tj|j|S)zExecute the graph. At each node we compute outputs via `operation_fn(node.operation)(*args, **kwargs)`. Treversec3:K|]}t|vVdSr)id).0r tensor_dicts r z.Function._run_through_graph..s.LLAr!uuK/LLLLLLr)rrr>r(rIr$listkeyssort operationis_inputany input_tensors argumentsfill_inr)appendpack_sequence_asr)r'r(r<call_fnryr+ depth_keysdepthr*nodeargskwargsr:r)output_tensorsrKs @rr?zFunction._run_through_graph|s f%%  V,, # #DAq!"K1  -.--//00 %%% + +E"5)E + +~LLLL9KLLLLL#~55kBB f!\$.11&%gb:4:::6::GG b$1&11G  dl7.C.CDD++DAq)*K1&&+ +$ 6 6A  ! !+bee"4 5 5 5 5$T%9>JJJrc d tj||jdn(#t$rtd|jd|wxYwt tj||jD]\}}t|jt|jkr4t|j j d|j d|jd|jdt |j|jD]C\}}|<|:||kr4t|j j d|j d|jd|jdDdS) NF) check_typeszOFunction was called with an invalid input structure. Expected input structure: z Received input structure: z, was passed incompatible inputs. For input 'z', expected shape z+, but received instead a tensor with shape .) rassert_same_structurerr!r>rrlenr5r.__name__r )r'r(rrAdimref_dims rr=z$Function._assert_input_compatibilitys   &+        6-1-@66-366   DL00$,??  HAu17||s5;//// ~.>>7>&+k>>457>>> !$AGU[ 9 9   W&3?g~~(#~6FF?DzFF.3kFF<=7FFF   s %Ar)re __module__ __qualname____doc__rpropertyr,r(r)r8rDr?r= __classcell__)r.s@rr r sB&8&8&8&8&8&8P##X#XX   ,KKK )K)K)K)KVrr c`tt|dzt|zS)Nz_ib-)strrI)r: node_indexs r make_node_keyrps$ r"vv;; #j// 11rc t||\}d|D}i}i}t|D]}||d}||jd}t ||}|||j<|||<|jD].} || d}t |dz||| </|D]R} | jd} | rA| |vr=d|| <d| <d|| jd<| t| dStj t} |D] \}}| ||!tj t} |D] \}}| ||!t| }|dg}|D]8}| |}|fd||9t| }|dt'}|D]}| |g}|D]}| |D]}t)j|jD]?}||vr|j}t/d |d |d |||j@t)j|jD]}| |d |D}|D]D}||dkr)t/d |d||dE|| || fS)a Validates a graph's topology and gather its operations and nodes. Args: inputs: List of input tensors. outputs: List of outputs tensors. Returns: A tuple `(nodes, nodes_by_depth, operations, operations_by_depth)`. - nodes: set of Node instances - nodes_by_depth: dict mapping ints (depth) to lists of node instances. - operations: list of Operation instances. - operations_by_depth: dict mapping ints (depth) to lists of Operation instances. crh|]4}t|j|jj|5Sr)rprP_inbound_nodesindex)rJr\s r zmap_graph..sG  dndn&C&I&I$&O&OPPrrTrFc|Srr)roperation_indicess rrzmap_graph..s 0A!0Dr)keyz2Graph disconnected: cannot find parent for tensor z at operation 'zB'. The following previous operations were accessed without issue: cg|] }|j Srr )rJrPs r zmap_graph..8s<<fg3N3N00-M L233DD''a00+..t~qAA E>**,1$.)" T ) D DH)--h::N%(N%C%CL " " DAA!03  A6GGG12 o .13 o .>?L7: ;   mOQ?? @ @ @!,T22N#))++++ eu$$T****&1$77-335555 5E")))4444)..0011JOODO!!!J00259 !!&D&D&D&D!EEE.////n))++,,JOODO!!!  ""q!!!!%'"**"5) * *D\$"455 F F... $I$K"#KK4=KK+IKK /55inEEEE\$,// * *"&&q)))) * *"=<<<