2VhCXddlmZddlmZd dZd dZdZd dZd dZ d Z d d Z y))backend) tensorflowNct|tjr|}nwt|tjjr |j }nFt |dr9t |dr-tj|j|j|}ny|s|S|j}|j|jdk(r|S|j}d|d<tj|}||_ |S)z?Returns a `TensorSpec` given a single `Tensor` or `TensorSpec`.shapedtype)rrnameNr) isinstancetfTypeSpec __internal__CompositeTensor _type_spechasattr TensorSpecrrrankas_list TensorShape_shape)t dynamic_batchrspecr shape_lists H/home/dcms/DCMS/lib/python3.12/site-packages/keras/src/utils/tf_utils.pyget_tensor_specrs!R[[! Ar66 7|| G G!4}}177!''E  JJE zzUZZ1_ JJqM NN: &EDK Kctt|tjtjtjfsWt j dk(r*t j |rt j|}tj||}|%|j|k7rtj||}|S)z/s YY   #  FWWVU #F ||Ax XXf%a( "E* __v}},F Mrc Xtjj|||||d|}|jjdk(r'|j tj |f|S|jjd}|j tj ||f|S)z+Apply binary or count encoding to an input.r-)r.r/r0rr1r2r3r)r mathr8rr set_shaperr)r%r9r2rr:r;r=s rdense_bincountrBEs WW   #F||A12 M\\))+A. U(;<= Mrct|tjr tjj ||Stj||S)z0Expand dims on sparse, ragged, or dense tensors.)r r rr7 expand_dims)r%r1s rrDrDXs8&"//*yy$$VT22 >>&$ ''rc "|dk(r)tjtj||S|j}|jjdk(r t |d}|dk(r|jddk7r t |d}|jjdkDr)t d|d|d |jjd |d v}|rt|||||} nt|||||} tj| |} |d k7r| S|t d|d||r_tj|| jd d df} tj| j| | jz| jStj| |S)zeEncodes categorical inputs according to output_mode. Faster method that relies on bincount. intrr-one_hotr3zZWhen output_mode is not `'int'`, maximum supported output rank is 2. Received output_mode z and input shape z$, which would result in output rank .) multi_hotrGtf_idfNzTWhen output mode is `'tf_idf'`, idf_weights must be provided. Received: output_mode=z and idf_weights=)r identityr$rrrD ValueErrorr>rBgatherr4rr5r6multiply) r% output_moder9rr7r: idf_weightsoriginal_shaper2 bincounts value_weightss rtf_encode_categorical_inputsrU_se{{27765122\\N ||AVR(i << q  ,F ||1 **56G1171B1B0C1 F   #;;M # E=% # E=%  5)Ih %%0M1B;- Q   +y/@/@B/GH     I,, ,  ! !  {{9k22r)FN)N)float32FNN) keras.srcrkeras.src.utils.module_utilsrr rr&r+r>rBrDrUrrrZs<94 8,&(  >3r