David310/Detect_AI-generated_Image
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�}28t |29j� d�� � �d } | � � ��fdd�} |�| � | |j� | |j � |�� |t|j�!� �fS )a� Load a CLIP model30 31 Parameters32 ----------33 name : str34 A model name listed by `clip.available_models()`, or the path to a model checkpoint containing the state_dict35 36 device : Union[str, torch.device]37 The device to put the loaded model38 39 jit : bool40 Whether to load the optimized JIT model or more hackable non-JIT model (default).41 42 download_root: str43 path to download the model files; by default, it uses "~/.cache/clip"44 45 Returns46 -------47 model : torch.nn.Module48 The CLIP model49 50 preprocess : Callable[[PIL.Image], torch.Tensor]51 A torchvision transform that converts a PIL image into a tensor that the returned model can take as its input52 z
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|�D ]`\}}t73|�|kr�|r�|d|� }� |d< ntd | | � d74|� ���t�|�||dt75|��f< q�|S ) a� 76 Returns the tokenized representation of given input string(s)77 78 Parameters79 ----------80 texts : Union[str, List[str]]81 An input string or a list of input strings to tokenize82 83 context_length : int84 The context length to use; all CLIP models use 77 as the context length85 86 truncate: bool87 Whether to truncate the text in case its encoding is longer than the context length88 89 Returns90 -------91 A two-dimensional tensor containing the resulting tokens, shape = [number of input strings, context_length].92 We return LongTensor when torch version is <1.8.0, since older index_select requires indices to be long.93 z<|startoftext|>z
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