o  âg£ã@s<ddlZddlZddlmZddlmZGdd„deƒZdS)éN)ÚSamplerc@s*eZdZdZd dd„Zdd„Zdd„ZdS) ÚOrderedDistributedSamplera€Sampler that restricts data loading to a subset of the dataset. It is especially useful in conjunction with :class:`torch.nn.parallel.DistributedDataParallel`. In such case, each process can pass a DistributedSampler instance as a DataLoader sampler, and load a subset of the original dataset that is exclusive to it. .. note:: Dataset is assumed to be of constant size. Arguments: dataset: Dataset used for sampling. num_replicas (optional): Number of processes participating in distributed training. rank (optional): Rank of the current process within num_replicas. NcCs„|durt ¡s tdƒ‚t ¡}|dur t ¡stdƒ‚t ¡}||_||_||_tt   t |jƒd|j¡ƒ|_ |j |j|_ dS)Nz,Requires distributed package to be availablegð?)ÚdistÚ is_availableÚ RuntimeErrorÚget_world_sizeÚget_rankÚdatasetÚ num_replicasÚrankÚintÚmathÚceilÚlenÚ num_samplesÚ total_size)Úselfr r r ©rú6/home/terry/ogs_model/timm/data/distributed_sampler.pyÚ__init__s z"OrderedDistributedSampler.__init__cCslttt|jƒƒƒ}||d|jt|ƒ…7}t|ƒ|jksJ‚||j|j|j…}t|ƒ|jks2J‚t|ƒS©N) ÚlistÚrangerr rr r rÚiter)rÚindicesrrrÚ__iter__%s z"OrderedDistributedSampler.__iter__cCs|jSr)r)rrrrÚ__len__2sz!OrderedDistributedSampler.__len__)NN)Ú__name__Ú __module__Ú __qualname__Ú__doc__rrrrrrrrs   r)r ÚtorchÚtorch.utils.datarÚtorch.distributedÚ distributedrrrrrrÚs