2VhW<ddlZddlZddlZddlZddlZddlZddlZddlZddlm Z ddlm Z ddl m Z ddl m Z dZejddZd Zd Zd Zd Zdd ZdZ ddZddZy)N)backend)tree) dtype_utils)io_utilsct|Dcgc]}|j}}ttd|DScc}w)Nc3FK|]}tj|ywN)mathprod).0ps M/home/dcms/DCMS/lib/python3.12/site-packages/keras/src/utils/summary_utils.py zcount_params..s0A499Q<0s!)shapeintsum)weightsvshapess r count_paramsrs4& '!agg 'F ' s000 11(s5ictj|}tj|}t j |}||zSr )r r rstandardize_dtyper dtype_size)rdtype weight_countsper_param_sizes r_compute_memory_sizers;IIe$M  % %e ,E ++E2N > ))c|Dcic]}t||c}j}d}|D]%}|t|j|jz }'|dz Scc}w)zCompute the memory footprint for weights based on their dtypes. Args: weights: An iterable contains the weights to compute weight size. Returns: The total memory size (in Bytes) of the weights. r)idvaluesrrr)rwunique_weightstotal_memory_sizes rweight_memory_sizer&!sg)001beQh0779N D1!''177CCD q  1sAcgd}d}|D]#}||z dkrdj||cS||z}%dj||dS)z.format_shapeXs949:q'*: :TYY{++c11;s0rc(|jSr )rr9rHs rz$format_layer_shape..es,qww/r output_shapec|Sr r7rJs rrKz$format_layer_shape..ns l1orr.'r7)_inbound_nodes_build_shapes_dictlenrangeoutput_tensorsr map_structurehasattrrLcompute_output_shapemap_shape_structureNotImplementedErrorstrreplace)layerioutputs output_shapesoutrHs @rformat_layer_shaperaTs   (@(@2 5   1$s5//01 A**1-<|dz }|Dcgc]}|dz c}dgz}|j!d|j!dt#|t%j&j(dz }|xs|}g}d}|D]9}t+||z|z }|dkr t-d|j!|||z };g}t/|D]>\}}t0j2j5|||||}|j!|@t1j2j6||dd}+fd(d)(,fd )d*)*fd *t9| |}| |d|dD]} *| D]}|j:| t=|dr+t?|j@}tC|j@}n*t?|jD}tC|jD}t?|jF} tC|jF}!|jHrc|jJrW|jJjLrAt?|jJjN}"tC|jJjN}#d}$nd}"d}#d}$|| z|"z}%||!z|#z}&|r3t0jPjSddd}'|'jUn t0jPjSd}'|'jWtYdt0jZj]|j^d |'jW||'jWtYd!ta|%d"zd#tc|&d$z|'jWtYd%ta|d"zd#tc|d$z|'jWtYd&ta| d"zd#tc|!d$z|$r8|'jWtYd'ta|"d"zd#tc|#d$z|rB|tj ur||'jed(y||'jeyycc}w)+aPrints a summary of a model. Args: model: Keras model instance. line_length: Total length of printed lines (e.g. set this to adapt the display to different terminal window sizes). positions: Relative or absolute positions of log elements in each line. If not provided, defaults to `[0.3, 0.6, 0.70, 1.]`. print_fn: Print function to use. It will be called on each line of the summary. You can set it to a custom function in order to capture the string summary. It defaults to `print` (prints to stdout). expand_nested: Whether to expand the nested models. If not provided, defaults to `False`. show_trainable: Whether to show if a layer is trainable. If not provided, defaults to `False`. layer_range: List or tuple containing two strings, the starting layer name and ending layer name (both inclusive), indicating the range of layers to be printed in the summary. The strings could also be regexes instead of an exact name. In this case, the starting layer will be the first layer that matches `layer_range[0]` and the ending layer will be the last element that matches `layer_range[1]`. By default (`None`) all layers in the model are included in the summary. r) Functional) SequentialTr.FX)g?g??) Layer (type) Output ShapeParam #)leftrjrightl)g333333?gQ?gGz?rf)rgrhriz Connected to)rjrjrkrj g?rf Trainablecenterz,Insufficient console width to print summary.)justifywidth)rr show_linesc (d}|jD]{}r|vr |jD]c}|j}|j}t |j }t |j }|r|dz }||jd|d|dz }e}|sd}|S)NrOrD[z][]-)rP input_tensors_keras_history operationr: node_index tensor_indexname) r\ connectionsnodekt keras_history inbound_layerr{r|relevant_nodess rget_connectionsz&print_summary..get_connectionss (( D$n"<((  " 1 1 - 7 7 -m.F.FG / 0J0JK 4'K$))*!JN rw)rar} __class____name__richmarkupescaper<rVr:rrappendrRr trainabler?) r\prefixrLr}cls_nameparamsfieldsrsequential_likeshow_trainables rget_layer_fieldsz'print_summary..get_layer_fields s;)%0  "??++{{!!$' "%dkk&8&8&BCDAFFug&%a(F%a(<7F%););)=a(@BF f- MM/%0 1 ui(S-?!-C c, #3a0  in- rc|r d|zdzdz}nd}||}|g}r^t|drR|jrF|j}|dz }tt|D]}|j  ||| |S) Nz u└ rO)rlayersr.) nested_level)rVrrSrRextend) r\rrrrows nested_layersr] expand_nestedr print_layers rrz"print_summary..print_layer)s \)E1C7FF!%7x WUH5%,,!LLM A L3}-.   a 0|L  r_collected_trainable_weightsN) highlightforce_terminal color_system)rzModel: ""z Total params: rrrEz Trainable params: z Non-trainable params: z Optimizer params: ) line_break)rO)r)3keras.src.modelsrcrdris_interactive_logging_enabled print_msg isinstancer _operations_nodes_by_depthr"rRrflattenrxrPrminshutilget_terminal_sizecolumnsr ValueError enumeratertableColumnTable#get_layer_index_bound_by_layer_nameadd_rowrVrrr&trainable_weightsnon_trainable_weightscompiled optimizerr variablesconsoleConsole begin_captureprintr?rrr}r:r4 end_capture)-model line_length positionsprint_fnrr layer_rangercrdrnodes_by_depthnodesrr\flagrdefault_line_lengthheader alignmentr column_widthscurrentposrrrr]r}columnrrowtrainable_counttrainable_memory_sizenon_trainable_countnon_trainable_memory_sizeoptimizer_weight_countoptimizer_memory_sizeoptimizer_built total_countr%rrrrrrs- `` @@@@@r print_summaryrysH,+ HCCE%%%$ z *""..557 AA A! DLL11C1C$D E I #( QJE   !00(Du}.3O!#'D ('  2!2 <- !7!7 L5 &&--/ A a N r!'01!QX1SE9  k""V557??!C4!4KMGC+%&0 19KL LU#5 GV$4"" aL"#  v  JJ  g[T JE(8&6fkJK AQ8 u% C EMM3   u45&u'I'IJ 2  . .! 'u'>'>? 253J3J K&u'B'BC 253N3N O ~~%//eoo.C.C!-eoo.G.G!H 25??3L3L M!" !!$77:PPK # $  ,,&&E'  ,,&&&7 MM)ht{{'9'9%**'E&FaHIJ MM% MM#$ k!_ . / #$567q 9 :  MM'( oa0 2 3 #$9:;1 = >  MM+, 1!4 6 7 #$=>?q A B  + ,"8!;= >'(=>?qA B  x)) ) W((*u = W((* + O2s Wc|\t|dk7rtd|dt|t|dtrt|dtstd|dt|gSt |Dcgc]*\}}t j |d|jr|,}}}t |Dcgc]*\}}t j |d|jr|,}}}|r|std|t|t|kDrt|t|dzgSt|t|dzgScc}}wcc}}w)a*Get the layer indexes from the model based on layer names. The layer indexes can be used to slice the model into sub models for display. Args: model: `Model` instance. layer_names: a list or tuple of 2 strings, the starting layer name and ending layer name (both inclusive) for the result. All layers will be included when `None` is provided. Returns: The index value of layer based on its unique name (layer_names). Output will be [first_layer_index, last_layer_index + 1]. zIlayer_range must be a list or tuple of length 2. Received: layer_range = z of length rr.z7layer_range should contain string type only. Received: zHPassed layer_names do not match the layer names in the model. Received: ) rRrrrZrrematchr}rmax)rridxr\ lower_index upper_indexs rrrs  { q !!, [[9I8JL +a.#.j NC7 (M+  3v;$F+ C 88KNEJJ / K$F+ C 88KNEJJ / K k $  '   ;#k**K #k"2Q"677  c+.2 33' s :/E:/E r )NNNFFN) functoolsr rrr rich.console rich.markup rich.table keras.srcrrkeras.src.utilsrrr lru_cacherr&r4r:r<r?rarrr7rrrs '$2 S** ! =$ "N L,^34r