from tensorflow.config.experimental import list_physical_devices, set_memory_growth
physical_devices = list_physical_devices('GPU')
set_memory_growth(physical_devices[0], True)

import os
import time
import numpy as np
import matplotlib.pyplot as plt
import cv2
import tqdm  # 进度条工具

from tensorflow.config.experimental import list_physical_devices, set_memory_growth
physical_devices = list_physical_devices('GPU')

physical_devices

set_memory_growth(physical_devices[0], True)

from sklearn.datasets import load_iris

x = load_iris()['data']
y = load_iris()['target']
print(x.shape)
print(y.shape)

from tensorflow.keras import activations

# activations.sigmoid()
# activations.relu()
# activations.softmax()

import tensorflow as tf
import numpy as np

# 查看tensorflow2的版本，注意双下划线
tf.__version__

# 查看电脑GPU是否可用   cuda  cudnn
tf.test.is_gpu_available()

import requests

url = 'https://www.bilibili.com/video/BV1bU4y1775K'

response = requests.get(url)

import requests

url = 'http://hzbmmc.com:8080/jeecg-boot/api/v1/webbaseinfo/announcement/brief?mentTypehzbWebbaseinfoAnnounce=1&queryPage=1&querySize=5'

response = requests.get(url)

import requests

url = 'https://top.baidu.com/board?tab=movie'

response = requests.get(url)

import requests

# 设置请求的网址
url = "http://hzbmmc.com/"

# 发送get请求
response = requests.get(url)

# 查看响应的状态码
response.status_code