o ?߱i+# @sddlmZddlZddlZz ddlmZmZWney.Z z e dWYdZ [ ndZ [ wwddl m Z ddl mZdZ dded eefd d Zd d ZGdddZedkrd edZe ddSdS))OptionalN)extract_vision_infoprocess_vision_infoz,sz(flatten_content_list.. ) isinstancelistjoinappend)messagesZ new_messagesmessage text_listr r r flatten_content_list(s rc@s:eZdZdddZ ddd Zd d Zd d ZddZdS)r Qwen/Qwen2.5-VL-3B-InstructNcCs||_|dvrtd|dd|vrd|_nd|_d|d}d d lm}||}t||_t d t |jd rF|jj |jj |_nd|_t |jd rZ|jj |jj|_nd|_t |jdrq|jj j|_|jj j|_dS|jj|_|jj|_dS)N)zQwen/Qwen2.5-VL-7B-InstructrzQwen/Qwen2-VL-2B-InstructzQwen/Qwen2.5-VL-32B-InstructzQwen/Qwen2.5-VL-72B-InstructzQwen/Qwen2.5-0.5BzError loading processor z,, please check if the tokenizer is availableVLFTz8s3://bucket/cosmos_reasoning1/pretrained/Qwen_tokenizer//r)get_checkpoint_pathz.Successfully loaded processor from local cache image_token video_token tokenizer)name ValueErroris_vision_tokenizer3cosmos_predict2._src.imaginaire.utils.checkpoint_dbr rfrom_pretrained processorrinfohasattrr#convert_tokens_to_idsr!image_token_idr"video_token_id eos_token_ideos_id pad_token_idpad_id)selfr$r s3_urir r r r __init__4s,         zProcessor.__init__FptTcCs|sJd|jdrk|jst|}|jj|d||d}t|dd\}}} t|} g} | D] } d| vr;| | dq.|jrL|j|g||d|| d } n |j|gd|d } || d <| d d | d <| dd | d<| St d|j)Nztokenize must be True Qwen/Qwen2F)tokenizeadd_generation_prompt add_vision_idT)Zreturn_video_kwargsvideofps)rimagesvideospaddingreturn_tensorsr<)rr?r@r input_idsrattention_maskz:apply_chat_template is not implemented for tokenizer_type ) r$ startswithr&rr)apply_chat_templaterrrr%)r3rr9r@r8r:rZ image_inputsZ video_inputs_Z vision_infosZfps_list vision_infoinputsr r r rD]sH   zProcessor.apply_chat_templatecsttjr'jdkr'tfddtjdD}|jjks%J|Sttjr3nt }|jdks?Jj drd}d}d }d }d}j j|} j j|} j j|} t || kd} t || kd} t j|td }t| t| ksJt| | D]\}}||d| krd |||||<qntd j |j|jksJttjrt|S|S)a Add a mask to the assistant tokens. This is used to mask out tokens that are not generated by the assistant (e.g., system prompts, user prompts, chat templates), such that in the loss computation, only the tokens generated by the assistant are used. If there are multiple turns in the conversation, the mask will mask all the assistant tokens in each turn. Args: tokens (Union[List[int], torch.Tensor]): The tokens to add the mask to. Returns: Union[List[bool], torch.Tensor]: The mask. True for tokens generated by the assistant (i.e. should apply loss on), False for tokens not generated by the assistant. csg|] }|qSr )add_assistant_tokens_mask)rir3tokensr r rsz7Processor.add_assistant_tokens_mask..rr7z <|im_start|>z <|im_end|>Z assistant)dtypeTz@add_assistant_tokens_mask is not implemented for tokenizer_type )rtorchTensorndimstackrangeshapecpunumpynparrayr$rCr)r#r,where zeros_likeboollenzipr% from_numpytolist)r3rLmaskZ np_tokensZ BOS_TOKENZ EOS_TOKENROLEZ START_OFFSETZ END_OFFSET bos_token_idr/Zrole_id start_indices end_indicesmasksstartendr rKr rIs: $"   z#Processor.add_assistant_tokens_maskcO|jj|i|Sr )r)encoder3argskwargsr r r rjzProcessor.encodecOrir )r)decoderkr r r rornzProcessor.decode)rN)Fr6TF)__name__ __module__ __qualname__r5rDrIrjror r r r r 2s * 66 r __main__rdoner )typingrrWrXrPZ qwen_vl_utilsrr ImportErroreprintZ(transformers.models.auto.processing_autor%cosmos_predict2._src.imaginaire.utilsrZ_LOCK_TIMEOUT_SECONDSstrrrr rpr)r r r r s4