mirror of https://github.com/hpcaitech/ColossalAI
75 lines
2.8 KiB
Python
75 lines
2.8 KiB
Python
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import math
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from abc import abstractmethod
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import torch
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from torch.utils.data import Dataset, ConcatDataset, ChainDataset, IterableDataset
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import os
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import numpy as np
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import cv2
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class Txt2ImgIterableBaseDataset(IterableDataset):
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'''
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Define an interface to make the IterableDatasets for text2img data chainable
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'''
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def __init__(self, file_path: str, rank, world_size):
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super().__init__()
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self.file_path = file_path
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self.folder_list = []
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self.file_list = []
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self.txt_list = []
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self.info = self._get_file_info(file_path)
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self.start = self.info['start']
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self.end = self.info['end']
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self.rank = rank
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self.world_size = world_size
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# self.per_worker = int(math.floor((self.end - self.start) / float(self.world_size)))
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# self.iter_start = self.start + self.rank * self.per_worker
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# self.iter_end = min(self.iter_start + self.per_worker, self.end)
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# self.num_records = self.iter_end - self.iter_start
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# self.valid_ids = [i for i in range(self.iter_end)]
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self.num_records = self.end - self.start
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self.valid_ids = [i for i in range(self.end)]
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print(f'{self.__class__.__name__} dataset contains {self.__len__()} examples.')
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def __len__(self):
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# return self.iter_end - self.iter_start
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return self.end - self.start
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def __iter__(self):
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sample_iterator = self._sample_generator(self.start, self.end)
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# sample_iterator = self._sample_generator(self.iter_start, self.iter_end)
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return sample_iterator
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def _sample_generator(self, start, end):
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for idx in range(start, end):
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file_name = self.file_list[idx]
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txt_name = self.txt_list[idx]
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f_ = open(txt_name, 'r')
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txt_ = f_.read()
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f_.close()
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image = cv2.imdecode(np.fromfile(file_name, dtype=np.uint8), 1)
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image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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image = torch.from_numpy(image) / 255
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yield {"caption": txt_, "image":image}
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def _get_file_info(self, file_path):
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info = \
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{
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"start": 1,
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"end": 0,
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}
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self.folder_list = [file_path + i for i in os.listdir(file_path) if '.' not in i]
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for folder in self.folder_list:
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files = [folder + '/' + i for i in os.listdir(folder) if 'jpg' in i]
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txts = [k.replace('jpg', 'txt') for k in files]
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self.file_list.extend(files)
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self.txt_list.extend(txts)
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info['end'] = len(self.file_list)
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# with open(file_path, 'r') as fin:
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# for _ in enumerate(fin):
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# info['end'] += 1
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# self.txt_list = [k.replace('jpg', 'txt') for k in self.file_list]
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return info
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