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Duplicate from Whispering-GPT/whisper-youtube-2-hf_dataset
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from pathlib import Path
from typing import List, Dict, Optional
from loading.serialization import Serializer
class LoaderIterator:
"""Iterator that loads data from multiple files in batches."""
def __init__(self,
serializer: Serializer,
num_files_per_iteration: int,
load_paths: Optional[List[Path]] = None) -> None:
self.serializer = serializer
self.num_files_per_iteration = num_files_per_iteration
self._load_paths = load_paths
self._current_iteration = None
@property
def load_paths(self) -> Optional[List[Path]]:
return self._load_paths
@load_paths.setter
def load_paths(self, load_paths: List[Path]) -> None:
self._load_paths = load_paths
def __iter__(self):
self._current_iteration = 0
return self
def __next__(self) -> List[Dict]:
if self._did_load_all_batches():
raise StopIteration
data_batch = self._load_data_batch()
self._current_iteration += 1
return data_batch
def _did_load_all_batches(self) -> bool:
if self._current_iteration >= len(self._load_paths) / self.num_files_per_iteration:
return True
return False
def _load_data_batch(self) -> List[Dict]:
start_index = self._current_iteration * self.num_files_per_iteration
stop_index = start_index + self.num_files_per_iteration
return [self.serializer.load(load_path) for load_path in
self._load_paths[start_index:stop_index] if load_path.exists()]