我要评论tensorflow、keras、python 版本匹配一览表
兴冲冲装完软件，发现运行不了，查了下资料，发现是tensorflow、keras、python 版本匹配问题。
这里提供一个版本匹配清单，需要严格按此标准安装。
版本匹配清单
| framework | env name | description |
|---|---|---|
| tensorflow 2.2 | tensorflow-2.2 | tensorflow 2.2.0 + keras 2.3.1 on python 3.7. |
| tensorflow 2.1 | tensorflow-2.1 | tensorflow 2.1.0 + keras 2.3.1 on python 3.6. |
| tensorflow 2.0 | tensorflow-2.0 | tensorflow 2.0.0 + keras 2.3.1 on python 3.6. |
| tensorflow 1.15 | tensorflow-1.15 | tensorflow 1.15.0 + keras 2.3.1 on python 3.6. |
| tensorflow 1.14 | tensorflow-1.14 | tensorflow 1.14.0 + keras 2.2.5 on python 3.6. |
| tensorflow 1.13 | tensorflow-1.13 | tensorflow 1.13.0 + keras 2.2.4 on python 3.6. |
| tensorflow 1.12 | tensorflow-1.12 | tensorflow 1.12.0 + keras 2.2.4 on python 3.6. |
| tensorflow-1.12:py2 | tensorflow 1.12.0 + keras 2.2.4 on python 2. | |
| tensorflow 1.11 | tensorflow-1.11 | tensorflow 1.11.0 + keras 2.2.4 on python 3.6. |
| tensorflow-1.11:py2 | tensorflow 1.11.0 + keras 2.2.4 on python 2. | |
| tensorflow 1.10 | tensorflow-1.10 | tensorflow 1.10.0 + keras 2.2.0 on python 3.6. |
| tensorflow-1.10:py2 | tensorflow 1.10.0 + keras 2.2.0 on python 2. | |
| tensorflow 1.9 | tensorflow-1.9 | tensorflow 1.9.0 + keras 2.2.0 on python 3.6. |
| tensorflow-1.9:py2 | tensorflow 1.9.0 + keras 2.2.0 on python 2. | |
| tensorflow 1.8 | tensorflow-1.8 | tensorflow 1.8.0 + keras 2.1.6 on python 3.6. |
| tensorflow-1.8:py2 | tensorflow 1.8.0 + keras 2.1.6 on python 2. | |
| tensorflow 1.7 | tensorflow-1.7 | tensorflow 1.7.0 + keras 2.1.6 on python 3.6. |
| tensorflow-1.7:py2 | tensorflow 1.7.0 + keras 2.1.6 on python 2. | |
| tensorflow 1.5 | tensorflow-1.5 | tensorflow 1.5.0 + keras 2.1.6 on python 3.6. |
| tensorflow-1.5:py2 | tensorflow 1.5.0 + keras 2.0.8 on python 2. | |
| tensorflow 1.4 | tensorflow-1.4 | tensorflow 1.4.0 + keras 2.0.8 on python 3.6. |
| tensorflow-1.4:py2 | tensorflow 1.4.0 + keras 2.0.8 on python 2. | |
| tensorflow 1.3 | tensorflow-1.3 | tensorflow 1.3.0 + keras 2.0.6 on python 3.6. |
| tensorflow-1.3:py2 | tensorflow 1.3.0 + keras 2.0.6 on python 2. |
附上一段测试程序（鸢尾花分类简化版）
这一段代码不需要准备数据文件，可直接验证是否可以训练模型。
#ex7-2.py
#导入库包
import numpy as np
import keras
import matplotlib.pyplot as plt
from keras.models import sequential
from keras.layers import dense
#读入数据
train_x = np.array([[1.4, 0.2],
[1.7, 0.4],
[1.5, 0.4],
[2.3, 0.7],
[2.7, 1.1],
[2.6, 0.9],
[4.6, 1.3],
[3.5, 1.0],
[3.9, 1.2]])
train_y = np.array([[1, 0, 0],
[1, 0, 0],
[1, 0, 0],
[0, 1, 0],
[0, 1, 0],
[0, 1, 0],
[0, 0, 1],
[0, 0, 1],
[0, 0, 1]])
#搭建模型
model = sequential()
model.add(dense(units = 2, input_dim = 2))
#model.add(dense(units = 2, input_dim = 2, activation = 'sigmoid'))
model.add(dense(units = 3, activation = 'softmax'))
#编译模型
model.compile(optimizer = 'adam', loss = 'mse')
#训练模型
model.fit(x = train_x, y = train_y, epochs = 10000)
#保存模型
keras.models.save_model(model, 'iris2.model')
总结
以上为个人经验，希望能给大家一个参考，也希望大家多多支持代码网。
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