I am trying to understand this snippet of code that does language detection from the OpenAi whisper model. I am trying my best to understand this code, but I am struggling. I think they use a mask and use logistic regression to find the probability o

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from dataclasses import dataclass, field
from typing import Dict, List, Tuple, Iterable, Optional, Sequence, Union, TYPE_CHECKING

import numpy as np
import torch
import torch.nn.functional as F
from torch import Tensor
from torch.distributions import Categorical

from .audio import CHUNK_LENGTH
from .tokenizer import Tokenizer, get_tokenizer
from .utils import compression_ratio

if TYPE_CHECKING:
from .model import Whisper


@torch.no_grad()
def detect_language(model: "Whisper", mel: Tensor, tokenizer: Tokenizer = None) -> Tuple[Tensor, List[dict]]:
"""
Detect the spoken language in the audio, and return them as list …

code detection language languagetechnology logistic regression openai probability regression think whisper