OFA-Visual_Grounding / data /file_dataset.py
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Duplicate from OFA-Sys/OFA-Visual_Grounding
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import os
import torch
import pickle
class FileDataset:
def __init__(self, file_path, selected_col_ids=None, dtypes=None, separator="\t", cached_index=False):
self.file_path = file_path
assert os.path.exists(self.file_path), "Error: The local datafile {} not exists!".format(self.file_path)
self.separator = separator
if selected_col_ids is None:
# default to all fields
self.selected_col_ids = list(
range(len(open(self.file_path).readline().rstrip("\n").split(self.separator))))
else:
self.selected_col_ids = [int(col_id) for col_id in selected_col_ids.split(",")]
if dtypes is None:
# default to str
self.dtypes = [str for col_id in self.selected_col_ids]
else:
self.dtypes = [eval(col_dtype) for col_dtype in dtypes.split(",")]
assert len(self.dtypes) == len(self.selected_col_ids)
self.data_cnt = 0
try:
self.slice_id = torch.distributed.get_rank()
self.slice_count = torch.distributed.get_world_size()
except Exception:
self.slice_id = 0
self.slice_count = 1
self.cached_index = cached_index
self._init_seek_index()
self._reader = self._get_reader()
print("file {} slice_id {} row count {} total row count {}".format(
self.file_path, self.slice_id, self.row_count, self.total_row_count)
)
def _init_seek_index(self):
if self.cached_index:
cache_path = "{}.index".format(self.file_path)
assert os.path.exists(cache_path), "cache file {} not exists!".format(cache_path)
self.total_row_count, self.lineid_to_offset = pickle.load(open(cache_path, "rb"))
print("local datafile {} slice_id {} use cached row_count and line_idx-to-offset mapping".format(
self.file_path, self.slice_id))
else:
# make an iteration over the file to get row_count and line_idx-to-offset mapping
fp = open(self.file_path, "r")
print("local datafile {} slice_id {} begin to initialize row_count and line_idx-to-offset mapping".format(
self.file_path, self.slice_id))
self.total_row_count = 0
offset = 0
self.lineid_to_offset = []
for line in fp:
self.lineid_to_offset.append(offset)
self.total_row_count += 1
offset += len(line.encode('utf-8'))
self._compute_start_pos_and_row_count()
print("local datafile {} slice_id {} finished initializing row_count and line_idx-to-offset mapping".format(
self.file_path, self.slice_id))
def _compute_start_pos_and_row_count(self):
self.row_count = self.total_row_count // self.slice_count
if self.slice_id < self.total_row_count - self.row_count * self.slice_count:
self.row_count += 1
self.start_pos = self.row_count * self.slice_id
else:
self.start_pos = self.row_count * self.slice_id + (self.total_row_count - self.row_count * self.slice_count)
def _get_reader(self):
fp = open(self.file_path, "r")
fp.seek(self.lineid_to_offset[self.start_pos])
return fp
def _seek(self, offset=0):
try:
print("slice_id {} seek offset {}".format(self.slice_id, self.start_pos + offset))
self._reader.seek(self.lineid_to_offset[self.start_pos + offset])
self.data_cnt = offset
except Exception:
print("slice_id {} seek offset {}".format(self.slice_id, offset))
self._reader.seek(self.lineid_to_offset[offset])
self.data_cnt = offset
def __del__(self):
self._reader.close()
def __len__(self):
return self.row_count
def get_total_row_count(self):
return self.total_row_count
def __getitem__(self, index):
if self.data_cnt == self.row_count:
print("reach the end of datafile, start a new reader")
self.data_cnt = 0
self._reader = self._get_reader()
column_l = self._reader.readline().rstrip("\n").split(self.separator)
self.data_cnt += 1
column_l = [dtype(column_l[col_id]) for col_id, dtype in zip(self.selected_col_ids, self.dtypes)]
return column_l