o di-+@sdZddlZddlmZmZddlmZmZmZm Z m Z m Z ddl m Z ddlmZmZmZddlmZdd lmZdd lmZdd lmZmZerPdd lmZeeZd Z GdddeZ!GdddeZ"dS)zBase exporters config.N)ABCabstractmethod) TYPE_CHECKINGAnyDictListOptionalUnion)is_torch_available)DEFAULT_DUMMY_SHAPESDummyInputGeneratorlogging)TORCH_MINIMUM_VERSION)TRANSFORMERS_MINIMUM_VERSION)add_dynamic_docstring)is_torch_versionis_transformers_version)PretrainedConfiga) Generates the dummy inputs necessary for tracing the model. If not explicitely specified, default input shapes are used. Args: framework (`str`, defaults to `"pt"`): The framework for which to create the dummy inputs. batch_size (`int`, defaults to {batch_size}): The batch size to use in the dummy inputs. sequence_length (`int`, defaults to {sequence_length}): The sequence length to use in the dummy inputs. num_choices (`int`, defaults to {num_choices}): The number of candidate answers provided for multiple choice task. image_width (`int`, defaults to {width}): The width to use in the dummy inputs for vision tasks. image_height (`int`, defaults to {height}): The height to use in the dummy inputs for vision tasks. num_channels (`int`, defaults to {num_channels}): The number of channels to use in the dummpy inputs for vision tasks. feature_size (`int`, defaults to {feature_size}): The number of features to use in the dummpy inputs for audio tasks in case it is not raw audio. This is for example the number of STFT bins or MEL bins. nb_max_frames (`int`, defaults to {nb_max_frames}): The number of frames to use in the dummpy inputs for audio tasks in case the input is not raw audio. audio_sequence_length (`int`, defaults to {audio_sequence_length}): The number of frames to use in the dummpy inputs for audio tasks in case the input is raw audio. Returns: `Dict[str, [tf.Tensor, torch.Tensor]]`: A dictionary mapping the input names to dummy tensors in the proper framework format. cseZdZfddZZS) ExportConfigc s tjdi|tddS)NztThe `ExportConfig` class is deprecated and will be removed in a future version. Please use `ExporterConfig` instead.)super__init_subclass__loggerwarning)clskwargs __class__rd/lsinfo/ai/hellotax_ai/llm_service/venv_embed/lib/python3.10/site-packages/optimum/exporters/base.pyrHszExportConfig.__init_subclass__)__name__ __module__ __qualname__r __classcell__rrrrrGsrc @seZdZUdZdZdZdZeee e effe d<e Z eZiddgddgd dgd dgd d gd dgddgddgddgddgddgddgddgddgddgdddgdddgdgdgdgdgdgdgdggdgd d! Z " #d=d$d%d&e d'e d(e fd)d*Zd+eefd,d-Zeed+e e e ee fffd.d/Zed+e e e ee fffd0d1Zed+ee e effd2d3Zed+efd4d5Zed+efd6d7Ze e!e"d8d>d:e d+e fd;d<Z#dS)?ExporterConfiga: Base class describing metadata on how to export the model. Class attributes: - NORMALIZED_CONFIG_CLASS (`Type`) -- A class derived from [`~optimum.utils.NormalizedConfig`] specifying how to normalize the model config. - DUMMY_INPUT_GENERATOR_CLASSES (`Tuple[Type]`) -- A tuple of classes derived from [`~optimum.utils.DummyInputGenerator`] specifying how to create dummy inputs. - ATOL_FOR_VALIDATION (`Union[float, Dict[str, float]]`) -- A float or a dictionary mapping task names to float, where the float values represent the absolute tolerance value to use during model conversion validation. - MIN_TORCH_VERSION (`packaging.version.Version`, defaults to [`~optimum.exporters.utils.TORCH_MINIMUM_VERSION`]) -- The minimum torch version supporting the export of the model. - MIN_TRANSFORMERS_VERSION (`packaging.version.Version`, defaults to [`~optimum.exporters.utils.TRANSFORMERS_MINIMUM_VERSION`] -- The minimum transformers version supporting the export of the model. Not always up-to-date or accurate. This is more for internal use. - PATCHING_SPECS (`Optional[List[PatchingSpec]]`, defaults to `None`) -- Specify which operators / modules should be patched before performing the export, and how. This is useful when some operator is not supported for instance. Args: config (`transformers.PretrainedConfig`): The model configuration. task (`str`, defaults to `"feature-extraction"`): The task the model should be exported for. int_dtype (`str`, defaults to `"int64"`): The data type of integer tensors, could be ["int64", "int32", "int8"], default to "int64". float_dtype (`str`, defaults to `"fp32"`): The data type of float tensors, could be ["fp32", "fp16", "bf16"], default to "fp32". Nrgh㈵>ATOL_FOR_VALIDATIONzaudio-classificationlogitszaudio-frame-classificationzautomatic-speech-recognitionz audio-xvectorzdepth-estimationpredicted_depthzdocument-question-answeringzfeature-extractionlast_hidden_statez fill-maskzimage-classificationzimage-segmentationz image-to-textzimage-to-imagereconstructionzmask-generationz masked-imzmultiple-choicezobject-detection pred_boxeszquestion-answering start_logits end_logitsprediction_outputs)logits_per_imagelogits_per_text text_embeds image_embeds)r&r*r0r1) zsemantic-segmentationztext2text-generationztext-classificationztext-generationztime-series-forecastingztoken-classificationzvisual-question-answeringzzero-shot-image-classificationzzero-shot-object-detectionint64fp32configrtask int_dtype float_dtypecCs*||_||_||j|_||_||_dS)N)r5_configNORMALIZED_CONFIG_CLASS_normalized_configr6r7)selfr4r5r6r7rrr__init__s  zExporterConfig.__init__returnc sfddjDS)a{ Instantiates the dummy input generators from `self.DUMMY_INPUT_GENERATOR_CLASSES`. Each dummy input generator is independent, so this method instantiates the first generator, and forces the other generators to use the same batch size, meaning they will all produce inputs of the same batch size. Override this method for custom behavior. cs"g|] }|jjfiqSr)r5r:).0cls_rr;rr s"zHExporterConfig._create_dummy_input_generator_classes..)DUMMY_INPUT_GENERATOR_CLASSES)r;rrr@r%_create_dummy_input_generator_classessz4ExporterConfig._create_dummy_input_generator_classescCst)z Dict containing the axis definition of the input tensors to provide to the model. Returns: `Dict[str, Dict[int, str]]`: A mapping of each input name to a mapping of axis position to the axes symbolic name. )NotImplementedErrorr;rrrinputss zExporterConfig.inputscCs|j|j}t|S)z Dict containing the axis definition of the output tensors to provide to the model. Returns: `Dict[str, Dict[int, str]]`: A mapping of each output name to a mapping of axis position to the axes symbolic name. )_TASK_TO_COMMON_OUTPUTSr5copydeepcopy)r;common_outputsrrroutputss  zExporterConfig.outputscCst|jdr ddiSdS)z Dictionary of keys to override in the model's config before exporting. Returns: `Optional[Dict[str, Any]]`: A dictionary specifying the configuration items to override. use_cacheFN)hasattrr8rErrrvalues_overrides zExporterConfig.values_overridecCstd|jjS)z Whether the installed version of Transformers allows the export. Returns: `bool`: Whether the install version of Transformers is compatible with the model. >=)rMIN_TRANSFORMERS_VERSION base_versionrErrr!is_transformers_support_availables z0ExporterConfig.is_transformers_support_availablecCstr td|jjSdS)z Whether the installed version of PyTorch allows the export. Returns: `bool`: Whether the installed version of PyTorch is compatible with the model. rOF)r rMIN_TORCH_VERSIONrQrErrris_torch_support_availablesz)ExporterConfig.is_torch_support_available)textdynamic_elementspt frameworkcKsr|jdi|}i}|jD])}d}|D]}||r+|j|||j|jd||<d}nq|s6td|dq |S)NF)rXr6r7Tz$Could not generate dummy input for "zK". Try adding a proper dummy input generator to the model exporters config.r)rCrFsupports_inputgenerater6r7 RuntimeError)r;rXrdummy_inputs_generators dummy_inputs input_nameinput_was_inserteddummy_input_genrrrgenerate_dummy_inputss$     z$ExporterConfig.generate_dummy_inputs)r2r3)rW)$r r!r"__doc__r9rBr%r floatrstr__annotations__GLOBAL_MIN_TORCH_VERSIONrSGLOBAL_MIN_TRANSFORMERS_VERSIONrPrGr<rr rCpropertyrintrFrKrrrNboolrRrTrGENERATE_DUMMY_DOCSTRINGr rarrrrr$Ps      !   "     r$)#rbrHabcrrtypingrrrrrr transformers.utilsr utilsr r rrrfrrg utils.docrutils.import_utilsrr transformersr get_loggerr rrkrr$rrrrs