iFddlZddlmZmZmZmZmZmZmZddl Z ddl m Z ddl m Z ddlmZddlmZmZmZerddlmZd ZeeZGd d eeZGd d eZddZy)N) TYPE_CHECKINGAnyDictListOptionalTupleUnion)validate_hf_hub_args)Self) ConfigMixin) BaseOutputPushToHubMixin get_logger BlockStatezguider_config.jsonc eZdZdZeZdZdZd)dedede fdZ dZ d Z d Z d ed ed ej ddfdZdeeeffdZdeffd Zdej.j0ddfdZdej.j0ddfdZdddedfdZdddeeeeeeefffdedfdZdeddefdZ defdZ!e"de fdZ#e"de fdZ$e"defdZ%e&deeeejNejNffded eddfd!Z(e&deeeeeeefffddded eddf d"Z)e&e* d*d#e+eee,jZfd$e+ede.fd%Z/d+d&eee,jZfd'e fd(Z0xZ1S), BaseGuidancezGBase class providing the skeleton for implementing guidance techniques.N__guidance_identifier__startstopenabledcvtjd||_||_d|_d|_d|_d|_d|_||_ d|cxkrdksntd|d||cxkrdksntd|d|d|jt|jts td y) NzGuiders are currently an experimental feature under active development. The API is subject to breaking changes in future releases.r?z4Expected `start` to be between 0.0 and 1.0, but got .zExpected `stop` to be between z and 1.0, but got z\`_input_predictions` must be a list of required prediction names for the guidance technique.)loggerwarning_start_stop_step_num_inference_steps _timestep_count_prepared _input_fields_enabled ValueError_input_predictions isinstancelist)selfrrrs h/home/obispo/Crisostomo_bridge/mision_env/lib/python3.12/site-packages/diffusers/guiders/guider_utils.py__init__zBaseGuidance.__init__+s Q    )-!+/ EI u"s"STYSZZ[\] ]$$=eWDVW[V\\]^_ _  " " **T=T=TVZ2[n 3\c P|jj|jfi|S)a Creates a copy of this guider instance, optionally with modified configuration parameters. Args: **kwargs: Configuration parameters to override in the new instance. If no kwargs are provided, returns an exact copy with the same configuration. Returns: A new guider instance with the same (or updated) configuration. Example: ```python # Create a CFG guider guider = ClassifierFreeGuidance(guidance_scale=3.5) # Create an exact copy same_guider = guider.new() # Create a copy with different start step, keeping other config the same new_guider = guider.new(guidance_scale=5) ``` ) __class__ from_configconfig)r+kwargss r,newzBaseGuidance.newCs$.*t~~))$++@@@r.cd|_y)NFr&r+s r,disablezBaseGuidance.disable\s  r.cd|_y)NTr6r7s r,enablezBaseGuidance.enable_s  r.stepnum_inference_stepstimestepreturnc<||_||_||_d|_y)Nr)r!r"r#r$)r+r;r<r=s r, set_statezBaseGuidance.set_statebs  $7!! r.c|j|j|j|j|j|j d}|S)an Returns the current state of the guidance technique as a dictionary. The state variables will be included in the __repr__ method. Returns: `Dict[str, Any]`: A dictionary containing the current state variables including: - step: Current inference step - num_inference_steps: Total number of inference steps - timestep: Current timestep tensor - count_prepared: Number of times prepare_models has been called - enabled: Whether the guidance is enabled - num_conditions: Number of conditions )r;r<r=count_preparedrnum_conditions)r!r"r#r$r&rC)r+states r, get_statezBaseGuidance.get_statehsBJJ#'#<#<"22}}"11   r.c xt |}|j}g}|jD]j\}}t |}d|vr?|j d}|ddzdj |ddDcgc]}d|z c}z}|jd|d|ldj |} |d| Scc}w) zq Returns a string representation of the guidance object including both config and current state.  rNz z z: z State: )super__repr__rEitemsstrsplitjoinappend) r+str_reprrD state_lineskvv_strv_linesline state_strr0s r,rJzBaseGuidance.__repr__~s 7#%  KKM 2DAqFEu}++d+ T)DIIQXYZY[Q\6]v}6],^^   A3b0 1 2IIk* :i[11 7^s1 B7 denoiserc.|xjdz c_y)z Prepares the models for the guidance technique on a given batch of data. This method should be overridden in subclasses to implement specific model preparation logic. rHN)r$r+rXs r,prepare_modelszBaseGuidance.prepare_modelss !r.cy)a* Cleans up the models for the guidance technique after a given batch of data. This method should be overridden in subclasses to implement specific model cleanup logic. It is useful for removing any hooks or other stateful modifications made during `prepare_models`. NrZs r,cleanup_modelszBaseGuidance.cleanup_modelss r.datarctd)Nz?BaseGuidance::prepare_inputs must be implemented in subclasses.NotImplementedError)r+r_s r,prepare_inputszBaseGuidance.prepare_inputss!"cddr. input_fieldsctd)NzPBaseGuidance::prepare_inputs_from_block_state must be implemented in subclasses.ra)r+r_rds r,prepare_inputs_from_block_statez,BaseGuidance.prepare_inputs_from_block_states""tuur.c@td|Ds tdt||jk7r%td|jdt|d|Dcic]#}t ||j |j %}}|jdi|Scc}w)Nc34K|]}t|dyw) noise_predN)hasattr).0ds r, z(BaseGuidance.__call__..s:71l+:sz1Expected all data to have `noise_pred` attribute.z Expected z data items, but got z. Please check the input data.r])allr'lenrCgetattr_identifier_keyriforward)r+r_rlforward_inputss r,__call__zBaseGuidance.__call__s:T::PQ Q t9++ +D//00Ec$i[Pno SWWQ'!T%9%9:ALLHWWt||-n--Xs(Bctd)Nz8BaseGuidance::forward must be implemented in subclasses.ra)r+argsr3s r,rrzBaseGuidance.forwards!"\]]r.ctd)Nz?BaseGuidance::is_conditional must be implemented in subclasses.rar7s r,is_conditionalzBaseGuidance.is_conditional!"cddr.c|j S)N)rxr7s r,is_unconditionalzBaseGuidance.is_unconditionals&&&&r.ctd)Nz?BaseGuidance::num_conditions must be implemented in subclasses.rar7s r,rCzBaseGuidance.num_conditionsryr. tuple_index identifiercbddlm}i}|jD]V\}} t|tj r|||<n0t|t r ||||<ntdt|X|||j<|di|S#t$rtjd|dYwxYw) Prepares a batch of data for the guidance technique. This method is used in the `prepare_inputs` method of the `BaseGuidance` class. It prepares the batch based on the provided tuple index. Args: input_fields (`Dict[str, Union[str, Tuple[str, str]]]`): A dictionary where the keys are the names of the fields that will be used to store the data once it is prepared with `prepare_inputs`. The values can be either a string or a tuple of length 2, which is used to look up the required data provided for preparation. If a string is provided, it will be used as the conditional data (or unconditional if used with a guidance method that requires it). If a tuple of length 2 is provided, the first element must be the conditional data identifier and the second element must be the unconditional data identifier or None. data (`BlockState`): The input data to be prepared. tuple_index (`int`): The index to use when accessing input fields that are tuples. Returns: `BlockState`: The prepared batch of data. r rzInvalid value type: "`data` does not have attribute(s) , skipping.r]) "modular_pipelines.modular_pipelinerrKr)torchTensortupler'typerdebugrq)clsr_r}r~r data_batchkeyvalues r,_prepare_batchzBaseGuidance._prepare_batchs6 D **, VJC VeU\\2&+JsOu-&+K&8JsO$';DK=%IJJ V+5 3&&''J'' V A% TU VsAB  "B.-B.cJddlm}i}|jD]J\}} t|trt ||||<n$t|t rt |||||<n L|||j<|di|S#t$rtjd|dYwxYw)rr rrrr]) rrrKr)rLrprAttributeErrorrrrq) rrdr_r}r~rrrrs r,_prepare_batch_from_block_statez,BaseGuidance._prepare_batch_from_block_states8 D &,,. VJC VeS)&-dE&:JsOu-&-dE+4F&GJsO V+5 3&&''J''" V A% TU VsAA=="B"!B"pretrained_model_name_or_path subfolderc b|jd||ddd|\}}}|j|fd|i|S)a& Instantiate a guider from a pre-defined JSON configuration file in a local directory or Hub repository. Parameters: pretrained_model_name_or_path (`str` or `os.PathLike`, *optional*): Can be either: - A string, the *model id* (for example `google/ddpm-celebahq-256`) of a pretrained model hosted on the Hub. - A path to a *directory* (for example `./my_model_directory`) containing the guider configuration saved with [`~BaseGuidance.save_pretrained`]. subfolder (`str`, *optional*): The subfolder location of a model file within a larger model repository on the Hub or locally. return_unused_kwargs (`bool`, *optional*, defaults to `False`): Whether kwargs that are not consumed by the Python class should be returned or not. cache_dir (`Union[str, os.PathLike]`, *optional*): Path to a directory where a downloaded pretrained model configuration is cached if the standard cache is not 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. proxies (`Dict[str, str]`, *optional*): A dictionary of proxy servers to use by protocol or endpoint, for example, `{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}`. The proxies are used on each request. output_loading_info(`bool`, *optional*, defaults to `False`): Whether or not to also return a dictionary containing missing keys, unexpected keys and error messages. local_files_only(`bool`, *optional*, defaults to `False`): Whether to only load local model weights and configuration files or not. If set to `True`, the model won't be downloaded from the Hub. token (`str` or *bool*, *optional*): The token to use as HTTP bearer authorization for remote files. If `True`, the token generated from `diffusers-cli login` (stored in `~/.huggingface`) is used. revision (`str`, *optional*, defaults to `"main"`): The specific model version to use. It can be a branch name, a tag name, a commit id, or any identifier allowed by Git. > [!TIP] > To use private or [gated models](https://huggingface.co/docs/hub/models-gated#gated-models), log-in with `hf > auth login`. You can also activate the special > ["offline-mode"](https://huggingface.co/diffusers/installation.html#offline-mode) to use this method in a > firewalled environment. T)rrreturn_unused_kwargsreturn_commit_hashrr]) load_configr1)rrrrr3r2 commit_hashs r,from_pretrainedzBaseGuidance.from_pretrainedsVh'6coo' *G!%# '  ' # sv[,2#22"uxx"4" uxx 4 e<eD4Fev v04S%U3PS8_@T:U5U0Vv l v .T,/.C.^#^eee'$''eee((3ellELL899:(((( ((  ((((T*(3c5c?&: ;;<*(*( *(  *(  *(*(XLP#'" 9\'/c2;;6F0G'H9\C=9\  9\9\v[eC4D.E[TX[r.rcteZdZUejed<eejed<eejed<y) GuiderOutputpred pred_cond pred_uncondN)rrrrr__annotations__rr]r.r,rrns* ,, %%%,,''r.rc|jttd|jd}|jttd|jd}|||z z}||zd|z |zz}|S)a Rescales `noise_cfg` tensor based on `guidance_rescale` to improve image quality and fix overexposure. Based on Section 3.4 from [Common Diffusion Noise Schedules and Sample Steps are Flawed](https://huggingface.co/papers/2305.08891). Args: noise_cfg (`torch.Tensor`): The predicted noise tensor for the guided diffusion process. noise_pred_text (`torch.Tensor`): The predicted noise tensor for the text-guided diffusion process. guidance_rescale (`float`, *optional*, defaults to 0.0): A rescale factor applied to the noise predictions. Returns: noise_cfg (`torch.Tensor`): The rescaled noise prediction tensor. rHT)dimkeepdim)stdr*rangendim) noise_cfgnoise_pred_textguidance_rescalestd_textstd_cfgnoise_pred_rescaleds r,rescale_noise_cfgrts ""tE!_5I5I,J'KUY"ZHmmU1inn%= >mMG#x''9: #66!>N:NR[9[[I r.)r)rtypingrrrrrrr rhuggingface_hub.utilsr typing_extensionsr configuration_utilsr utilsrrrrrrrrrrrr]r.r,rse III 6"-::?* H G[;G[T (:( r.