ϑiSSKJr SSKrSSKrSSKJrJrJr SSKr SSK r SSK J r SSK JrJrJrJrJrJr SSKJr \(aSSKJr SSKJr SSK Jr "S S \5r\"\\R:S S 9r\r\r \RBr"\r#\r\r$SS jr%SSjr&Sr'S\("54SSjjr)\%\l*\&\l+\'\l,g)) annotationsN) TYPE_CHECKINGAny TypedDict)core)AnalysisConfig PaddleDTypePaddleInferPredictorPaddleInferTensor PaddlePlaceconvert_to_mixed_precision_bind) get_logger)Unpack)Tensorc \rSrSr%S\S'Srg) _WhiteList)set[str] white_listN)__name__ __module__ __qualname____firstlineno____annotations____static_attributes__rX/var/www/html/banglarbhumi/venv/lib/python3.13/site-packages/paddle/inference/wrapper.pyrr)srrz&%(asctime)s-%(levelname)s: %(message)s)fmtc[U[R5(d<[U[5(a9[ U5S:a*[US[ 5(aUR U5 g[S5e)z9 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 TypeErrorselfdatas rtensor_copy_from_cpur,9sZ$ ##43t9q=ZQ5M5M   & V  rcX[U[R5(aURU5 g[U[R 5(aUR U5 g[U[RRR5(a [S5e[S5e)z? 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&++//88 9 9 2   M  rc(URXX45 g)z1 Support tensor.share_external_data_by_ptr_name. N)%_share_external_data_by_ptr_name_bind)r*r+shapedtypeplaces r&tensor_share_external_data_by_ptr_namer;[s ..tEIrTc U[RLa/[R"5(d[R S5 [ RRU5n [U5S:wa[ RRU5OU n [ RRU 5(d[ R"U 5 URS[55n [UUUUUUUUU 5 g)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) PlaceTypeGPUris_compiled_with_cuda_loggererrorospathdirnamer%existsmakedirsgetsetr ) model_file params_filemixed_model_filemixed_params_filemixed_precisionbackend keep_io_types black_listkwargsmixed_model_dirnamemixed_params_dirnamers rconvert_to_mixed_precisionrTbs6)--(B(B(D(D ] ''//*:;  !Q & )*  77>>. / / ()L#%0J# r)r+znpt.NDArray[Any] | list[str]returnNone)r+rrUrV)rIr&rJr&rKr&rLr&rM PrecisionTyperNr=rOboolrPrrQzUnpack[_WhiteList]rUrV)- __future__rloggingrBtypingrrrnumpyr"r0 paddle.baserpaddle.base.corerr r r r r paddle.base.log_helperr numpy.typingnpttyping_extensionsrrrrINFOr@DataTyper= PrecisionrWConfig Predictorr,r5r;rHrT copy_from_cpushare_external_datashare_external_data_by_ptr_namerrrrks# 00 .(Y  gll H    ((      (J56666 6 # 6  666!6 6r,7)O&r