一、TensorFlow实现一个加法运算

day01_deeplearning.py

import tensorflow as tfdef tensorflow_demo():"""TensorFlow的基本结构"""# TensorFlow实现加减法运算a_t = tf.constant(2)b_t = tf.constant(3)c_t = a_t + b_tprint("TensorFlow加法运算结果：\n", c_t)print(c_t.numpy())# 2.0版本不需要开启会话，已经没有会话模块了return Noneif __name__ == "__main__":# 代码1：TensorFlow的基本结构tensorflow_demo()

python3 day01_deeplearning.py2024-02-16 01:04:36.715081: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2024-02-16 01:04:36.715126: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2024-02-16 01:04:38.803888: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2024-02-16 01:04:38.803994: W tensorflow/stream_executor/cuda/cuda_driver.cc:269] failed call to cuInit: UNKNOWN ERROR (303)
2024-02-16 01:04:38.804045: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (server001): /proc/driver/nvidia/version does not exist
2024-02-16 01:04:38.804692: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
TensorFlow加法运算结果：tf.Tensor(5, shape=(), dtype=int32)
5

二、TensorFlow结构分析

1、TensorFlow程序通常被组织成一个构建图阶段和一个执行图阶段
在构建阶段，数据与操作的执行步骤被描述成一个图
在执行阶段，使用会话执行构建好的图中的操作

TensorFlow1.x构建和执行是分成两个步骤，TensorFlow2.x升级到了即时执行模式，所以就不需要会话了
参考资料：
https://www.jianshu.com/p/006d1292402b
https://blog.csdn.net/weixin_40920183/article/details/106718315

注：Session函数在2.x版本中有保留的tf.compat.v1.Session

2、图
这是TensorFlow将计算表示为指令之间的依赖关系的一种表示法
图定义了数据和操作的步骤

3、会话
TensorFlow1.x中跨一个或多个本地或远程设备运行数据流图的机制

4、张量（Tensor）
TensorFlow中的基本数据对象

5、节点
提供图当中执行的操作

三、不打印警告信息
添加：

import os
os.environ['TF_CPP_MIN_LOG_LEVEL']='2'

注意：要写在import tensorflow as tf的前面