o oi"%@sddlmZddlZddlZddlZddlZddlmZmZddl Z ddl m Z ddl m Zddl mZmZddlmZgdZeeZGd d d eZdddZ ddddZdddZdS)) annotationsN)AnyOptional) kornia_config)numpy)onnxrequests)CachedDownloader) ONNXLoader add_metadataio_name_conversionc@sZeZdZdZeddd d Zedd ddZed!ddZed"ddZ ed"ddZ dS)#r z_Manages ONNX models, handling local caching, downloading from Hugging Face, and loading models.Turlstrdownloadboolkwargsrreturndict[str, Any]cKs|dr3|j|tj|df|dd|}t|}t|}|WdS1s.wY|s=td|dtd|d) adLoad JSON config from the specified URL. Args: url: The URL of the preprocessor config to load. download: If True, the config will be downloaded if it's not already in the local cache. kwargs: Additional download arguments. Returns: dict[str, Any]: The loaded preprocessor config. )zhttp:zhttps:z.jsonrsuffixNzFile `z)` not found. You may set `download=True`.z ` not found.) startswithdownload_to_cacheospathsplitopenjsonload RuntimeError)clsr rr file_pathf json_datar$E/home/ubuntu/.local/lib/python3.10/site-packages/kornia/onnx/utils.py load_config(s"    zONNXLoader.load_configF model_name with_dataonnx.ModelProtoc Ks|dr^|tdd}d|d}|ddp%tjtj|dd}| d|i|j ||ddf|dd |}|rYd|d }|j ||ddf|d d |t |S|d sh|d r|ddpptj}| d|i|j |tj|d f|dd |}|r|ddd }|j |tj|d ddd f|d d |t |Stj |rt |Std|d)aLoad an ONNX model from the local cache or downloads it from Hugging Face if necessary. Args: model_name: The name of the ONNX model or operator. For Hugging Face-hosted models, use the format 'hf://model_name'. Valid `model_name` can be found on https://huggingface.co/kornia/ONNX_models. Or a URL to the ONNX model. download: If True, the model will be downloaded from Hugging Face if it's not already in the local cache. cache_dir: The directory where the model should be cached. Defaults to None, which will use a default `{kornia_config.hub_onnx_dir}` directory. with_data: If True, the model will be loaded with its `.onnx_data` weights. **kwargs: Additional arguments to pass to the download method, if needed. Returns: onnx.ModelProto: The loaded ONNX model. zhf://Nz7https://huggingface.co/kornia/ONNX_models/resolve/main/z.onnx cache_dir/rrz .onnx_datazhttp://zhttps://rzFile z not found)rlengetrrjoinr hub_onnx_dirrupdaterrrexists ValueError) r r'rr(rr r*r!url_datar$r$r% load_modelFsf       zONNXLoader.load_modelfolderlist[dict[str, Any]]cCs:d|}tj|dd}|jdkr|Std|j)zFetch the contents of the Hugging Face repository using the Hugging Face API. Returns: A list of all files in the repository as dictionaries containing file details. z?https://huggingface.co/api/models/kornia/ONNX_models/tree/main/ )timeoutz%Failed to fetch repository contents: )rr/ status_coderr4)r7r responser$r$r%_fetch_repo_contentss  zONNXLoader._fetch_repo_contentsNonecC&|d}dd|D}t|dS)z[List all available ONNX operators in the 'operators' folder of the Hugging Face repository. operatorscSg|]}|dqSrr$.0filer$r$r% z-ONNXLoader.list_operators..Nr>pprintpp)r repo_contentsrAr$r$r%list_operators zONNXLoader.list_operatorscCr@)zUList all available ONNX models in the 'models' folder of the Hugging Face repository.modelscSrBrCr$rDr$r$r%rGrHz*ONNXLoader.list_models..NrI)r rLrOr$r$r% list_modelsrNzONNXLoader.list_modelsN)T)r rrrrrrr)TF)r'rrrr(rrr))r7rrr8)rr?) __name__ __module__ __qualname____doc__ classmethodr&r6 staticmethodr>rMrPr$r$r$r%r %s=   r onnx_modelr)io_name_mappingdict[str, str]rcCs&tt|jjD]}|jj|j}||vr|||jj|_qtt|jjD]}|jj|j}||vr=|||jj|_q'tt|jjD]&}tt|jj|jD]}|jj|j||vrk|||jj|j|<qSqFtt|jj|jD]}|jj|j||vr|||jj|j|<qx|S)zConvert the input and output names of an ONNX model to 'input' and 'output'. Args: onnx_model: The ONNX model to convert. io_name_mapping: A dictionary mapping the original input and output names to the new ones. )ranger.graphinputnameoutputnode)rWrXiin_nameout_namejr$r$r%r s* r additional_metadataOptional[list[tuple[str, str]]]cCsF|durg}ddtjfg|D]\}}|j}||_t||_q|S)aAdd metadata to an ONNX model. The metadata includes the source library (set to "kornia"), the version of kornia, and any additional metadata provided as a list of key-value pairs. Args: onnx_model: The ONNX model to add metadata to. additional_metadata: A list of tuples, where each tuple contains a key and a value for the additional metadata to add to the ONNX model. Returns: The ONNX model with the added metadata. N)sourcekorniaversion)rg __version__metadata_propsaddkeyrvalue)rWrdrlrmrjr$r$r%r s  r onnx_typerrc CsFtjtjtjtjtjtjtjtjd}||vrt d|d||S)N)z tensor(float)ztensor(float16)ztensor(double)z tensor(int32)z tensor(int64)z tensor(uint8)z tensor(int8)z tensor(bool)z ONNX type z not understood) npfloat32float16float64int32int64uint8int8bool_ TypeError)rn type_mappingr$r$r%onnx_type_to_numpys rz)rWr)rXrYrr))N)rWr)rdrerr))rnrrr) __future__rrloggingrrJtypingrrrg kornia.configrkornia.core.externalrrorrkornia.utils.downloadr __all__ getLoggerrQloggerr r r rzr$r$r$r%s&      %