
    IЦi                     @    S SK JrJrJr  S SKr\ " S S\5      5       rg)    )AnyProtocolruntime_checkableNc                   R    \ rS rSrSrS\S\4S jrS rS\	R                  4S jrS	rg
)_Checkpointable   a  
Interface for checkpointable objects.
Implemented as a protocol, implicit subtyping is supported so subclasses do not need to inherit this explicitly.
This is to allow arbitrary objects/tensor subclasses to hook into DCP seamlessly through implementing the interface.
fqnobjectc                     [        S5      e)z9
Return a list of WriteItems based on object's contents.
z6_Checkpointable._create_write_items is not implementedNotImplementedError)selfr	   r
   s      `/var/www/html/ai-image-ml/venv/lib/python3.13/site-packages/torch/distributed/_checkpointable.py__create_write_items__&_Checkpointable.__create_write_items__   s     "D
 	
    c                     [        S5      e)zE
Return a list of `ChunkStorageMetadata` based on object's contents.
z5_Checkpointable._create_chunk_list is not implementedr   )r   s    r   __create_chunk_list__%_Checkpointable.__create_chunk_list__   s     "C
 	
r   returnc                     [        S5      e)z9
Return a 'torch.Tensor' shard based on 'MetadataIndex'.
z4_Checkpointable._get_tensor_shard is not implementedr   )r   indexs     r   __get_tensor_shard__$_Checkpointable.__get_tensor_shard__    s     "B
 	
r    N)__name__
__module____qualname____firstlineno____doc__strr   r   r   torchTensorr   __static_attributes__r   r   r   r   r      s/    
# 
s 


U\\ 
r   r   )typingr   r   r   r"   r   r   r   r   <module>r&      s+    4 3  
h 
 
r   