python flask 中的 cuda 错误 无法在分叉的子进程中重新初始化 CUDA。要将 CUDA 与多处理一起使用，您必须使用“spawn”start 方法

问：

我有一个问题。在 flask 中，当我将 comented 代码放入 dev 中时，我有一个错误。dev 之外的代码有效。我不知道为什么。

法典：

import random
import json
import torch
import spacy
import os
import torch.multiprocessing as mp
from .model import NeuralNet
from .nltk_utils import bag_of_words, tokenize

# from asistant_funt import extract_app_name

device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
with open('models/friday/intents.json', 'r') as f:
    intents = json.load(f)
FILE = 'models/friday/data.pth'
data = torch.load(FILE)
input_size = data["input_size"]
hidden_size = data["hidden_size"]
output_size = data["output_size"]
all_words = data["all_words"]
tags = data["tags"]
model_state = data["model_state"]
model = NeuralNet(input_size, hidden_size, output_size).to(device)
model.load_state_dict(model_state)
model.eval()
bot_name = 'friday'

# print("Let's chat type 'quit' to exit")
# while True:
#     respons = ''
#     sentence = input("You: ")
#     if sentence == "quit":
#         break
#     message = sentence
#     sentence = tokenize(sentence)
#     X = bag_of_words(sentence, all_words)
#     X = X.reshape(1, X.shape[0])
#     X = torch.from_numpy(X).to(device)
#
#     output = model(X)
#     _, prdicted = torch.max(output, dim=1)
#
#     tag = tags[prdicted.item()]
#     probs = torch.softmax(output, dim=1)
#     prob = probs[0][prdicted.item()]
#
#     if prob.item() > 0.85:
#         for intent in intents['intents']:
#             if tag == intent["tag"]:
#                 respons = random.choice(intent["responses"])
#                 print(f'{bot_name}: {respons}')
#     else:
#         print(f"{bot_name}: I don't understand...")

def Friday_chat(sentence):
    respons = ''
    message = sentence
    sentence = tokenize(sentence)
    X = bag_of_words(sentence, all_words)
    X = X.reshape(1, X.shape[0])
    X = torch.from_numpy(X).to(device)
    output = model(X)
    _, predicted = torch.max(output, dim=1)
    tag = tags[predicted.item()]
    probs = torch.softmax(output, dim=1)
    prob = probs[0][predicted.item()]
    if prob.item() > 0.85:
        for intent in intents['intents']:
            if tag == intent["tag"]:
                respons = random.choice(intent["responses"])
                return f'{bot_name}: {respons}'
    else:
        return f"{bot_name}: I don't understand..."

from flask import Flask, jsonify, request, Blueprint, send_from_directory
import os
import random
import string
import json
from models.friday.chat import Friday_chat


models_routes = Blueprint('models_routes', __name__)
@models_routes.route('/friday', methods=['POST'])

def friday():
    logout_data = request.get_json()
    if 'data' in logout_data:
        data = logout_data['data']
        response = Friday_chat(data)
        print(response)
        return jsonify({'field': response, 'valu': True})
    else:
        return jsonify({'error': 'Brak wymaganych danych'}), 400

错误：

[2023-11-15 20:29:57,913]应用中的错误：/星期五异常 [POST] 回溯（最近一次调用最后一次）：

  File "/home/ratt00/.local/lib/python3.10/site-packages/flask/app.py", line 1455, in wsgi_app
    response = self.full_dispatch_request()
  File "/home/ratt00/.local/lib/python3.10/site-packages/flask/app.py", line 869, in full_dispatch_request
    rv = self.handle_user_exception(e)
  File "/home/ratt00/.local/lib/python3.10/site-packages/flask/app.py", line 867, in full_dispatch_request
    rv = self.dispatch_request()
  File "/home/ratt00/.local/lib/python3.10/site-packages/flask/app.py", line 852, in dispatch_request
    return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args)
  File "/media/ratt00/Nowy/Antek/programowanie/python/echo/host/funtions/models_utils.py", line 17, in friday
    response = Friday_chat(data)
  File "/media/ratt00/Nowy/Antek/programowanie/python/echo/host/models/friday/chat.py", line 69, in Friday_chat
    X = torch.from_numpy(X).to(device)
  File "/home/ratt00/.local/lib/python3.10/site-packages/torch/cuda/__init__.py", line 284, in _lazy_init
    raise RuntimeError(
RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method

127.0.0.1 - - [15/Nov/2023 20:29:57] "POST /friday HTTP/1.1" 500 -

我尝试使用生成方法，但它不起作用，因为我有更多的错误。将 spawn 方法放在 def 中不起作用。

请帮忙!!