o ={c +ã@svdZddlmmZddlmZddlmZ ddlm Z ddlm Z dZ dd „Zd d „Zd d „Zdd„Zdd„ZdS)z%Utilities for keras functional model.éN)Úbackend)Ú input_layer)Ú keras_tensor)Únodez´Found unexpected instance while processing input tensors for keras functional model. Expecting KerasTensor which is from tf.keras.Input() or output from keras layer call(). Got: {}cCs t |¡s tt |¡ƒ‚|jjS)aàCheck if tensor is directly generated from `tf.keras.Input`. This check is useful when constructing the functional model, since we will need to clone Nodes and KerasTensors if the model is building from non input tensor. Args: tensor: A `KerasTensor` as inputs to the functional model. Returns: bool. Whether the tensor is directly generated from `tf.keras.Input`. Raises: ValueError: if the tensor is not a KerasTensor instance. )Ú node_moduleÚis_keras_tensorÚ ValueErrorÚ"_KERAS_TENSOR_TYPE_CHECK_ERROR_MSGÚformatrÚis_input©Ztensor©r ú=lib/python3.10/site-packages/keras/engine/functional_utils.pyÚis_input_keras_tensors rc s*tj |¡}tj |¡}||D]}t |¡stt |¡ƒ‚qtdd„|Dƒƒ}tƒ‰g}g}tƒ}|D]}|  |j ¡q4|r|  d¡} t | ƒ|vrKq=|  t | ƒ¡|  | ¡| jD]"} t | ƒ|vrjˆ  t | ƒ¡qZ| j } | jrwtd | ¡ƒ‚|  | ¡qZ|s?|ˆkr“‡fdd„|Dƒ} td | ¡ƒ‚|S)a6Fetch all Nodes in the graph defined by "inputs" and "outputs". This method is used to find and then clone Nodes when creating a new sub-model from an existing functional model. Args: inputs: A nested structure of KerasTensor to use as model inputs. outputs: A nested structure of KerasTensor to use as model outputs. Returns: A list of Nodes that are connected to the inputs and outputs. Raises: ValueError: when inputs and outputs are disconnected or in case of unexpected objects in the inputs/outputs. cSsg|]}t|ƒ‘qSr ©Úid©Ú.0Úktr r rÚ Tsz4find_nodes_by_inputs_and_outputs..rz¢Found input tensor cannot be reached given provided output tensors. Please make sure the tensor {} is included in the model inputs when building functional model.csg|] }t|ƒˆvr|‘qSr rr©Z end_ids_foundr rr~szHFound unvisited input tensors that are disconnected from the outputs: {})ÚtfÚnestÚflattenrrrr r ÚsetÚappendrÚpoprÚaddZ keras_inputsr ) ÚinputsÚoutputsZstart_keras_tensorsZend_keras_tensorsÚtZend_idsZnodes_to_visitZnodes_in_graphZnode_id_visitedrrZ inbound_nodeZunvisited_inputsr rrÚ find_nodes_by_inputs_and_outputs4sP    ÿ     ü ç ÿþr!cCst||ƒ}g}g}i}tj |¡D]'}|jjr#| |¡||t|ƒ<qt|ƒ}t j |d}| |¡||t|ƒ<qtj  ||¡}tj |¡D]} t| ƒ}| j |_ | |¡||t| ƒ<qFtj  ||¡}|D]} t | j|ƒ} t | j|ƒ} t | j|ƒ} tj| j| | | dqe||fS)a¬Clone the `Node` between the inputs and output tensors. This function is used to create a new functional model from any intermediate keras tensors. The clone of the nodes mimic the behavior of reconstructing the functional graph network by re-executing all the __call__ methods. The cloned nodes will be appended to the layers. Note that a new tf.keras.Inputs will be created for any items in the `inputs` Args: inputs: A nested structure of keras_tensors. outputs: A nested structure of keras_tensors. Returns: A pair of inputs and outputs, with cloned keras_tensors. They can be used to create a new functional model. r )Ú call_argsÚ call_kwargsr)r!rrrrr rrÚ_clone_keras_tensorÚinput_layer_moduleZInputÚpack_sequence_asÚ_keras_historyÚclone_keras_tensorsZoutput_tensorsr"r#rZNodeZlayer)rrZnodes_to_cloneZ cloned_inputsZcloned_outputsZ kt_id_mappingZkt_inputÚcpyZ cloned_inputZ kt_outputrZ output_copyZcall_args_copyZcall_kwargs_copyr r rÚclone_graph_nodesˆs<        ür*cCszg}tj |¡D]-}t |¡r0t|ƒ|vr|t|ƒ}nt|ƒ}|j|_||t|ƒ<| |¡q| |¡qtj  ||¡S)aëClone the keras tensors from the inputs. For any KerasTensor instance in the `args`, a new copy of KerasTensor will be created if it has not been cloned yet (by checking the `keras_tensor_mapping`). For any other types, the instance will be unchanged. This function is useful for cloning the Nodes since KerasTensor can't be reused across the models. Args: args: A nested structure of objects, which could contain KerasTensor. keras_tensor_mapping: A dict contains the ID of original KerasTensor, and the cloned KerasTensor instance. The dict will be updated with newly copied KerasTensor instances within this method. Returns: Same structure as inputs, with KerasTensor cloned. ) rrrrrrr$r'rr&)ÚargsZkeras_tensor_mappingÚresultÚobjr)r r rr(Ós     r(c Csxt ¡.}| ¡t |¡}t |¡WdƒWdƒS1s%wYWdƒdS1s5wYdS)a(Create an identical keras_tensor based on the input. We use keras_tensor_to_placeholder and keras_tensor_from_tensor to make sure inferred shape are not lost during the copy. Args: kt: the input KerasTensor. Returns: An identical copy of the input KerasTensor. N)rZ_scratch_graphZ as_defaultrZkeras_tensor_to_placeholderZkeras_tensor_from_tensor)rZ scratch_graphZ placeholderr r rr$ôs  þÿ"ÿr$)Ú__doc__Ztensorflow.compat.v2ÚcompatZv2rZkerasrZ keras.enginerr%rrrr rr!r*r(r$r r r rÚs    ÿTK !