o Gi " @sddlmZddlZddlZddlmZddlZddlm Z ddl m Z ddl m Z mZmZmZer7ddlZeeZejejejejejejejejejejej ej!d Z"Gd d d Z#dS) ) annotationsN)Path)hf_hub_download)validate_hf_hub_args)ONNX_EXTERNAL_WEIGHTS_NAMEONNX_WEIGHTS_NAMEis_onnx_availablelogging) z tensor(bool)z tensor(int8)z tensor(uint8)z tensor(int16)ztensor(uint16)z tensor(int32)ztensor(uint32)z tensor(int64)ztensor(uint64)ztensor(float16)z tensor(float)ztensor(double)c@seZdZd#ddZddZed$d%dd Zd#d&d dZd'ddZe e       d(d)ddZ e e  d*d+d!d"Z dS),OnnxRuntimeModelNcKs0td||_|dd|_|dt|_dS)NzL`diffusers.OnnxRuntimeModel` is experimental and might change in the future.model_save_dirlatest_model_name)loggerinfomodelgetr rr )selfrkwargsrR/home/ubuntu/.local/lib/python3.10/site-packages/diffusers/pipelines/onnx_utils.py__init__5s zOnnxRuntimeModel.__init__cKs dd|D}|jd|S)NcSsi|] \}}|t|qSr)nparray).0kvrrr <sz-OnnxRuntimeModel.__call__..)itemsrrun)rrinputsrrr__call__;szOnnxRuntimeModel.__call__path str | PathcCsH|dur tdd}|durg}nt|ts|g}tj||g||dS)au Loads an ONNX Inference session with an ExecutionProvider. Default provider is `CPUExecutionProvider` Arguments: path (`str` or `Path`): Directory from which to load provider(`str`, *optional*): Onnxruntime execution provider to use for loading the model, defaults to `CPUExecutionProvider` Nz=No onnxruntime provider specified, using CPUExecutionProviderCPUExecutionProvider) providers sess_optionsprovider_options)rr isinstancelistortInferenceSession)r!providerr%r&rrr load_model?s   zOnnxRuntimeModel.load_modelsave_directory file_name str | NonecKs|dur|nt}|j|j}t||}zt||Wn tjy(Ynw|jt}| rOt|t}z t||WdStjyNYdSwdS)a? Save a model and its configuration file to a directory, so that it can be re-loaded using the [`~optimum.onnxruntime.modeling_ort.ORTModel.from_pretrained`] class method. It will always save the latest_model_name. Arguments: save_directory (`str` or `Path`): Directory where to save the model file. file_name(`str`, *optional*): Overwrites the default model file name from `"model.onnx"` to `file_name`. This allows you to save the model with a different name. N) rr joinpathr rshutilcopyfile SameFileErrorrexists)rr-r.rmodel_file_namesrc_pathdst_pathrrr_save_pretrainedWs"  z!OnnxRuntimeModel._save_pretrainedstr | os.PathLikecKsFtj|rtd|ddStj|dd|j|fi|dS)a$ Save a model to a directory, so that it can be re-loaded using the [`~OnnxModel.from_pretrained`] class method.: Arguments: save_directory (`str` or `os.PathLike`): Directory to which to save. Will be created if it doesn't exist. zProvided path (z#) should be a directory, not a fileNT)exist_ok)osr!isfilererrormakedirsr8)rr-rrrrsave_pretrainedvs z OnnxRuntimeModel.save_pretrainedFmodel_idtokenbool | str | None | Nonerevisionstr | None | Noneforce_downloadbool cache_dirr+r%'ort.SessionOptions' | Nonec Ks|dur|nt} tj|r&tjt|| ||| dd} t|| d<n$t || ||||d} t| j | d<t| j | d<tj| ||| dd} |dd| i| S) a; Load a model from a directory or the HF Hub. Arguments: model_id (`str` or `Path`): Directory from which to load token (`str` or `bool`): Is needed to load models from a private or gated repository revision (`str`): Revision is the specific model version to use. It can be a branch name, a tag name, or a commit id cache_dir (`str | Path`, *optional*): Path to a directory in which a downloaded pretrained model configuration should be cached if the standard cache should not be used. force_download (`bool`, *optional*, defaults to `False`): Whether or not to force the (re-)download of the model weights and configuration files, overriding the cached versions if they exist. file_name(`str`): Overwrites the default model file name from `"model.onnx"` to `file_name`. This allows you to load different model files from the same repository or directory. provider(`str`): The ONNX runtime provider, e.g. `CPUExecutionProvider` or `CUDAExecutionProvider`. kwargs (`Dict`, *optional*): kwargs will be passed to the model during initialization Nr&)r+r%r&r )repo_idfilenamerArCrGrEr rr) rr;r!isdirr r,ras_posixpoprparentname) clsr@rArCrErGr.r+r%rr5rmodel_cache_pathrrr_from_pretraineds4&  z!OnnxRuntimeModel._from_pretrainedTcKsDd}tt|ddkr|d\}}|jd|||||d|S)N@r)r@rCrGrErAr)lenstrsplitrR)rPr@rErArG model_kwargsrCrrrfrom_pretraineds z OnnxRuntimeModel.from_pretrained)N)NNN)r!r")r-r"r.r/)r-r9)NNFNNNN)r@r"rArBrCrDrErFrGr/r.r/r+r/r%rH)TNN)r@r"rErFrAr/rGr/) __name__ __module__ __qualname__rr staticmethodr,r8r? classmethodrrRrXrrrrr 4s.   Cr )$ __future__rr;r1pathlibrnumpyrhuggingface_hubrhuggingface_hub.utilsrutilsrrr r onnxruntimer) get_loggerrYrbool_int8uint8int16uint16int32uint32int64uint64float16float32float64ORT_TO_NP_TYPEr rrrrs2