Mindspore框架循环神经网络RNN模型实现情感分类|（一）IMDB影评数据集准备

Mindspore框架循环神经网络RNN模型实现情感分类

Mindspore框架循环神经网络RNN模型实现情感分类|（一）IMDB影评数据集准备
Mindspore框架循环神经网络RNN模型实现情感分类|（二）预训练词向量
Mindspore框架循环神经网络RNN模型实现情感分类|（三）RNN模型构建
Mindspore框架循环神经网络RNN模型实现情感分类|（四）损失函数与优化器
Mindspore框架循环神经网络RNN模型实现情感分类|（五）模型训练
Mindspore框架循环神经网络RNN模型实现情感分类|（六）模型加载和推理（情感分类模型资源下载）
Mindspore框架循环神经网络RNN模型实现情感分类|（七）模型导出ONNX与应用部署

tips:安装依赖库

pip install -i https://pypi.mirrors.ustc.edu.cn/simple mindspore==2.2.14
pip install tqdm requests

一、IMDB影评数据集

影评-标签

Review	Label
“Quitting” may be as much about exiting a pre-ordained identity as about drug withdrawal. As a rural guy coming to Beijing, class and success must have struck this young artist face on as an appeal to separate from his roots and far surpass his peasant parents’ acting success. Troubles arise, however, when the new man is too new, when it demands too big a departure from family, history, nature, and personal identity. The ensuing splits, and confusion between the imaginary and the real and the dissonance between the ordinary and the heroic are the stuff of a gut check on the one hand or a complete escape from self on the other.	Negative
This movie is amazing because the fact that the real people portray themselves and their real life experience and do such a good job it’s like they’re almost living the past over again. Jia Hongsheng plays himself an actor who quit everything except music and drugs struggling with depression and searching for the meaning of life while being angry at everyone especially the people who care for him most.	Positive

情感分类是自然语言处理中的经典任务，是典型的分类问题。本项目使用MindSpore框架实现一个基于RNN网络的情感分类模型，实现如下的效果：

输入: This film is terrible
正确标签: Negative
预测标签: Negative

输入: This film is great
正确标签: Positive
预测标签: Positive

1.1 数据下载

首先设计数据下载模块，实现可视化下载流程，并保存至指定路径。
数据下载模块使用requests库进行http请求，并通过tqdm库对下载百分比进行可视化。此外针对下载安全性，使用IO的方式下载临时文件，而后保存至指定的路径并返回。

import os
import shutil
import requests
import tempfile
from tqdm import tqdm
from typing import IO
from pathlib import Path

# 指定保存路径为 `home_path/.mindspore_examples`
cache_dir = Path.home() / '.mindspore_examples'

def http_get(url: str, temp_file: IO):
    """使用requests库下载数据，并使用tqdm库进行流程可视化"""
    req = requests.get(url, stream=True)
    content_length = req.headers.get('Content-Length')
    total = int(content_length) if content_length is not None else None
    progress = tqdm(unit='B', total=total)
    for chunk in req.iter_content(chunk_size=1024):
        if chunk:
            progress.update(len(chunk))
            temp_file.write(chunk)
    progress.close()

def download(file_name: str