o i e+@svdZddlmmZddlmZddlmZ ddlm Z ddlm Z dZ dd Zd d Zd d ZddZddZdS)z%Utilities for keras functional model.N)backend) input_layer) keras_tensor)nodezFound 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||jjS)aCheck 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. ) node_moduleis_keras_tensor ValueError"_KERAS_TENSOR_TYPE_CHECK_ERROR_MSGformatris_inputtensorrP/var/www/myenv/lib/python3.10/site-packages/keras/src/engine/functional_utils.pyis_input_keras_tensors rc s*tj|}tj|}||D]}t|stt|qtdd|D}tg}g}t}|D]}| |j q4|r| d} t | |vrKq=| t | | | | jD]"} t | |vrj t | qZ| j } | jrwtd| | | qZ|s?|krfdd|D} td| |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|qSrid.0ktrrr Tsz4find_nodes_by_inputs_and_outputs..rzFound 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|vr|qSrrr end_ids_foundrrr~szHFound unvisited input tensors that are disconnected from the outputs: {})tfnestflattenrrrr r setappendrpopradd keras_inputsr ) inputsoutputsstart_keras_tensorsend_keras_tensorstend_idsnodes_to_visitnodes_in_graphnode_id_visitedrr inbound_nodeunvisited_inputsrrr find_nodes_by_inputs_and_outputs4sP           r,cCst||}g}g}i}tj|D]'}|jjr#||||t|<qt|}t j |d}||||t|<qtj ||}tj|D]} t| }| j |_ ||||t| <qFtj ||}|D]} t | j|} t | j|} t | j|} tj| j| | | dqe||fS)aClone 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 ) call_args call_kwargsr")r,rrrrr rr_clone_keras_tensorinput_layer_moduleInputpack_sequence_as_keras_historyclone_keras_tensorsoutput_tensorsr-r.rNodelayer)r!r"nodes_to_clone cloned_inputscloned_outputs kt_id_mappingkt_inputcpy cloned_input kt_outputr output_copycall_args_copycall_kwargs_copyrrrclone_graph_nodess<        rCcCszg}tj|D]-}t|r0t||vr|t|}nt|}|j|_||t|<||q||qtj ||S)aClone 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/r3rr2)argskeras_tensor_mappingresultobjr=rrrr4s     r4c Csxt.}|t|}t|WdWdS1s%wYWddS1s5wYdS)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)r_scratch_graph as_defaultrkeras_tensor_to_placeholderkeras_tensor_from_tensor)r scratch_graph placeholderrrrr/s  "r/)__doc__tensorflow.compat.v2compatv2r keras.srcrkeras.src.enginerr0rrrr rr,rCr4r/rrrrs    TK !