how to transform a posting file to a pytorch tensor
Is there a python package that transforms a postings file to a pytorch tensor?
By a posting file I mean a csv file with the following format:
&quot;docID&quot; ,&quot;wordID&quot; ,&quot;count&quot;
I also have a dictionary.txt which associates each wordID to a word.
At the end, my text data consists of postings file and a dictionary and I want to use it with a deep learning model that I have implemented with Pytorch.

No, you have to do it youself. You can simply convert each elemnt into a pytorch tensor or use the pytorch dataset api like this.
import csv
import torch
from torch.utils.data import Dataset
from typing import List, NamedTuple

CsvRowItem = NamedTuple(&quot;CsvRowItem&quot;, [
    (&quot;docId&quot;, int),
    (&quot;wordId&quot;, int),
    (&quot;count&quot;, int)
])

data: List[CsvRowItem] = []
with open(&quot;data.csv&quot;, mode='r') as file:
    reader = csv.reader(file)
    next(reader) # Skip the header
    for row in reader:
        data.append(
            CsvRowItem(docId=int(row[0]),
                       wordId=int(row[1]),
                       count=int(row[2]))
        )



class YourDataset(Dataset):

    def __init__(self, data: List[CsvRowItem]):
        self.data = data
    
    def __len__(self):
        return len(self.data)
    
    def __getitem__(self, index: int) -&gt; torch.IntTensor:
        item = self.data[index]
        return torch.IntTensor([item.docId, item.wordId, item.count])


dataset = YourDataset(data=data)
print(f&quot;Length of data: {len(dataset):,}&quot;)
print(dataset[0])

