ij2ddlZddlZddlZddlZddlZddlmZddlmZddlm Z ddlm Z ddl m Z ddl mZ ddZGd d Z dd Zd Zd Zej*dZej*dZdZy)N)backend)treeconvert_spec_to_tensor)get_input_signature)io_utils) tensorflowc lt|}||nd}|jdstd|tjdk(rt ||f||d|Stjdk7r tdt d ||d |}|j ||rtjd |d yy) aExport the model as a LiteRT artifact for inference. Args: model: The Keras model to export. filepath: The path to save the exported artifact. input_signature: Optional input signature specification. If `None`, it will be inferred. Note: With the PyTorch backend, dynamic input shapes are not supported. Any dynamic dimensions (represented as `None`) will be automatically replaced with `1` during export, which may cause runtime failures for other shapes. You must explicitly pass a fixed static `input_signature` matching your maximum runtime shape. **kwargs: Additional keyword arguments passed to the exporter. NT.tfliteDThe LiteRT export requires the filepath to end with '.tflite'. Got: torch)input_signatureverboser z[The LiteRT export API is currently only available with the TensorFlow and PyTorch backends.)modelrSaved artifact at ''.) strendswith ValueErrorrexport_litert_via_torchLiteRTExporterexportr print_msg)rfilepathrrkwargsactual_verboseexporters l/var/www/html/emotional.easysim.app/public_html/venv/lib/python3.12/site-packages/keras/src/export/litert.py export_litertr s,8}H ' 3WN   Y ' 'j *  G#&   ,"     L( 8  ' H  OOH0 "=>c,eZdZdZ ddZdZdZdZy)ra.Exporter for the LiteRT (TFLite) format. This class handles the conversion of Keras models for LiteRT runtime and generates a `.tflite` model file. For efficient inference on mobile and embedded devices, it creates a single callable signature based on the model's `call()` method. Nc .||_||_||_y)aInitialize the LiteRT exporter. Args: model: The Keras model to export input_signature: Input signature specification (e.g., TensorFlow TensorSpec or list of TensorSpec) **kwargs: Additional export parameters N)rrr)selfrrrs r__init__zLiteRTExporter.__init__Ps . r!c|jt|j|_t|jtt fs|jg|_|j dstd||j|j}t|d5}|j|ddd|S#1swY|SxYw)zExports the Keras model to a TFLite file. Args: filepath: Output path for the exported model Returns: Path to exported model Nr r wb) rrr isinstancelisttuplerr_convert_to_tfliteopenwrite)r$r tflite_modelfs rrzLiteRTExporter.exportbs    '$7tzz#BD $..u >$($8$8#9D   +##+*.  ..t/C/CD (D ! "Q GGL ! " "s B;;Ccddlm}tj5}|j }|j |j |jdtj|j jd||j|dtjjj|}tjj j"tjj j$g|j&_d|_|j-||j/cd d d S#1swYy xYw) aConverts the Keras model to TFLite format. Uses Keras ExportArchive as an intermediate SavedModel step. This aligns with TensorFlow's official Keras 3 TFLite conversion path: ExportArchive -> SavedModel -> from_saved_model. Args: input_signature: Input signature for the model to convert. Returns: A bytes object containing the serialized TFLite model. r)rserveF)training)r)rTN) keras.srcrtempfileTemporaryDirectory ExportArchivetrackr add_endpoint functoolspartial__call__ write_outtfliteTFLiteConverterfrom_saved_modelOpsSetTFLITE_BUILTINS SELECT_TF_OPS target_spec supported_ops&experimental_enable_resource_variables_apply_converter_kwargsconvert)r$r keras_exportsaved_model_dirarchive converters rr+z!LiteRTExporter._convert_to_tflites 5  ( ( * 'o"002G MM$** %  !!$**"5"5F / !    ou  =//@@I..,,3I ! ! /@DI <  ( ( 3$$&' ' ' 's D#EEcl|jjD]\}}|dk(ret|trU|jD]A\}}t |j |rt |j ||4td|dpt ||rt |||td|dy)zApply additional converter settings from kwargs. Args: converter: tf.lite.TFLiteConverter instance to configure Raises: ValueError: If any kwarg is not a valid converter attribute rDzUnknown target_spec attribute ''zUnknown converter attribute 'N)ritemsr(dicthasattrrDsetattrr)r$rLattrvaluespec_key spec_values rrGz&LiteRTExporter._apply_converter_kwargss ;;,,. JKD%}$E4)@,1KKM(Hjy44h? 5 5xL(=hZqI D) 4/ #@a!HII Jr!N)__name__ __module__ __qualname____doc__r%rr+rGrr!rrrGs#$B"'HJr!rc Jddlm}ddlm}|}t5 ddl}|dk7rE|j D]6} | jjjd| j_8 |d5| t|}tjd|} t| } |jt||} t!|du5 |j"|| fi| } | j)|dddddd|dk7rF|j D]6} | jjj|| j_8 ddd|durt+j,d |d |S#t $r t dwxYw#t$$r} t'd | | d} ~ wwxYw#1swYxYw#1swYxYw#|dk7rF|j D]6} | jjj|| j_8wwxYw#1swYxYw) z1Export Keras model to LiteRT via PyTorch backend.r) device_scope) get_deviceNzTo export to LiteRT with the PyTorch backend, you must install the `litert-torch` package. Install via: pip install litert-torchcpuct|dS)N)replace_none_numberr)xs rz)export_litert_via_torch..s4QANr!FzFailed to convert PyTorch model to LiteRT. Common causes: unsupported operations, dynamic shapes, or complex control flow. Original error: rr)keras.src.backend.torch.corer]r^_preserve_jax_x64_state litert_torch ImportError variablesrTdatatorr map_structurer*eval_prepare_litert_kwargs_silence_outputrH Exception RuntimeErrorrrr)rrrrrr]r^devicergv sample_inputslitert_torch_kwargs edge_modeles rrrs0:7 \F ! "5;   U?__ 6 ww||u5  6' ;e$" 0"*&9%&@O $ 2 2N#! !&m 4  &<L'#%W%56 0 !%9\%9%9!=&4G& %%h/ 0+" 0H;A#$77< Oo 8  L%!*/01c3 ! !! 0 0+" 0" 0H;A#$77<z)_prepare_litert_kwargs..s)  - -#2H szBUnsupported arguments for LiteRT export with the PyTorch backend: z, z. Supported arguments are: .)_get_litert_torch_kwarg_namesrO'_create_quant_config_from_optimizationssortedrjoin) rrgrukrs quant_cfgunsupported_argssupported_argsr~s @rrnrn s;LI '1 ' '%&  "'& ^;N%N; ? #\   2;  /  7?:K KL  "2345IIn-.a 1  r!ctj|jjDchc]}|dvr| c}Scc}w)N>module sample_args sample_kwargs)inspect signaturerH parameters)rgnames rrr)sD%%l&:&:;FF   A A   s <c#K ddl}|jj} d||jj d|yy#t$rd}d}Y4wxYw#||jj d|wwxYww)Nrjax_enable_x64)jaxconfigrrhupdate)r original_x64s rrfrf1s1 zz00 > ? JJ  . =    ? JJ  . = s=A:AA:A A: AA:AA:!A77A:c#K|sdytjtj5tjtj5dddddddy#1swYxYw#1swYyxYwwrW) contextlibredirect_stdoutioStringIOredirect_stderr)should_silences rroroBsh    # #BKKM 2  ' ' 6     s4/B(A;A/A;& B/A8 4A;;BBc.|sy ddlm}ddlm}ddlm} tjjj}ttjjdd}ttjjdd}||v}|xr||v} |xr||v} |s| s| r=|xr| xs| } | xs| } || | d } |}|j| || Sy#t $rt jdYywxYw#t tf$rYywxYw) z;Translate TFLite optimizations to litert_torch QuantConfig.Nr) PT2EQuantizer)!get_symmetric_quantization_config) QuantConfigzPWarning: litert_torch quantization modules not available. Skipping quantization.OPTIMIZE_FOR_SIZEOPTIMIZE_FOR_LATENCYF)is_per_channel is_dynamicis_qat)pt2e_quantizer)$litert_torch.quantize.pt2e_quantizerrr"litert_torch.quantize.quant_configrrhrrr=r>OptimizeDEFAULTgetattrAttributeError set_global)ryrgrrroptimize_default optimize_sizeoptimize_latency has_defaulthas_size has_latencyrrquant_config_obj quantizers rrrMs6  F  C77++33 0 02EtL " GG  4d  #m3K?-!?H"H'7='HKh+ B(*Ak%B $0<)!  "O -.)44 G  %    (s#CA.DC?>C?DD)NN)rr9rrr4r3rrkeras.src.export.export_utilsrrkeras.src.utilsrkeras.src.utils.module_utilsr r=r rrrnrcontextmanagerrfrorrr!rrs @=$9   5?pvJvJt48FR@  > >  .r!