zjhddlmZddlZddlZddlmZmZmZddlZ ddl Z ddl m Z ddl mZmZmZmZmZmZddlmZer ddlmZddlmZddl mZGd d eZeeejd ZeZeZ ej!Z"eZ#eZeZ$d&dZ%d'dZ&dZ'de(fd(d%Z)e%e_*e&e_+e'e_,dS))) annotationsN) TYPE_CHECKINGAny TypedDict)core)AnalysisConfig PaddleDTypePaddleInferPredictorPaddleInferTensor PaddlePlaceconvert_to_mixed_precision_bind) get_logger)Unpack)TensorceZdZUded<dS) _WhiteListset[str] white_listN)__name__ __module__ __qualname____annotations__h/lsinfo/ai/hellotax_ai/data_center/backend/venv/lib/python3.11/site-packages/paddle/inference/wrapper.pyrr)srrz&%(asctime)s-%(levelname)s: %(message)s)fmtdatanpt.NDArray[Any] | list[str]returnNonect|tjsCt|trEt |dkr2t|dt r||dStd)zA Support input type check based on tensor.copy_from_cpu. rzHIn copy_from_cpu, we only support numpy ndarray and list[str] data type.N) isinstancenpndarraylistlenstr_copy_from_cpu_bind TypeErrorselfrs rtensor_copy_from_cpur,9sz$ ## 4 #&t99q==ZQ5M5M=   &&&&& V   rrcJt|tjr||dSt|tjr||dSt|tjjj rtdtd)zG Support input type check based on tensor.share_external_data. zThe interface 'share_external_data' can only be used in dynamic graph mode. Maybe you called 'paddle.enable_static()' and you are in static graph mode now. Please use 'copy_from_cpu' instead.z?In share_external_data, we only support Tensor and DenseTensor.N) r"r DenseTensor_share_external_data_bindpaddler'_share_external_data_paddle_tensor_bindbase frameworkVariabler)r*s rtensor_share_external_datar5Gs$())   &&t,,,,, D&- ( (   44T::::: D&+/8 9 9   2    M   rc6|||||dS)z9 Support tensor.share_external_data_by_ptr_name. N)%_share_external_data_by_ptr_name_bind)r+rshapedtypeplaces r&tensor_share_external_data_by_ptr_namer;[s$ ..tUE5IIIIIrT model_filer' params_filemixed_model_filemixed_params_filemixed_precision PrecisionTypebackend PlaceType keep_io_typesbool black_listrkwargsUnpack[_WhiteList]c |tjur-tjstdt j|} t|dkrt j|n| } t j | st j | | dt} t||||||||| dS)a Convert a fp32 model to mixed precision model. Args: model_file: fp32 model file, e.g. inference.pdmodel. params_file: fp32 params file, e.g. inference.pdiparams. mixed_model_file: The storage path of the converted mixed-precision model. mixed_params_file: The storage path of the converted mixed-precision params. mixed_precision: The precision, e.g. PrecisionType.Half. backend: The backend, e.g. PlaceType.GPU. keep_io_types: Whether the model input and output dtype remains unchanged. Default is True. black_list: Operators that do not convert precision. kwargs: Supported keys including 'white_list'. - white_list: Operators that do convert precision. zOYou should use PaddlePaddle compiled with GPU when backend set to PlaceType.GPUrrN)rCGPUris_compiled_with_cuda_loggererrorospathdirnamer&existsmakedirsgetsetr ) r<r=r>r?r@rBrDrFrGmixed_model_dirnamemixed_params_dirnamers rconvert_to_mixed_precisionrWbs6)-(B(D(D ]   '//*:;;  ! !Q & & )***  7>>. / /* ()))L#%%00J#     r)rrrr )rrrr )r<r'r=r'r>r'r?r'r@rArBrCrDrErFrrGrHrr )- __future__rloggingrNtypingrrrnumpyr#r0 paddle.baserpaddle.base.corerr r r r r paddle.base.log_helperr numpy.typingnpttyping_extensionsrrrrINFOrLDataTyperC PrecisionrAConfig Predictorr,r5r;rTrW copy_from_cpushare_external_datashare_external_data_by_ptr_namerrrrjs#""""" 0000000000 .-----((((((Y * gl H      (            (JJJ35566666r,7)O&&&r