tensor flow 之學習 (1)


  1.  上python 官網 down 3.5.x 版本 installer
  2. 係vs code 裝返 python 既 extension
  3. configure vs code setting 

{
"name": "Python",
"type": "python",
"request": "launch",
"stopOnEntry": true,
"pythonPath": "{YOURPATHFOR}/python.exe",
"program": "${file}",
"cwd": "{YOURPATHFOR}",
"env": {},
"envFile": "${workspaceRoot}/.env",
"debugOptions": [
"WaitOnAbnormalExit",
"WaitOnNormalExit",
"RedirectOutput"
]
},
  1. 跟住 To install TensorFlow, start a terminal. Then issue the appropriate pip3 install command in that terminal. To install the CPU-only version of TensorFlow, enter the following command:
  2. 

    

    

    
C:\> pip3 install --upgrade tensorflow
    To install the GPU version of TensorFlow, enter the following command:
    

    

    

    
C:\> pip3 install --upgrade tensorflow-gpu
  3. open a file hello.py

  4. import tensorflow as tf

    print('hello')
    hello = tf.constant('Hello, TensorFlow!')
    sess = tf.Session()
    print(sess.run(hello))
  5. then runt the code .
  6. result
  7. hello
    b'Hello, TensorFlow!'
  8. done.

留言

張貼留言

這個網誌中的熱門文章

tensorflow 學習之(2＿

tf.train API 解 equation, y = W*x +b ,  The completed trainable linear regression model is shown here: import numpy as np import tensorflow as tf # Model parameters W = tf . Variable ([. 3 ], dtype = tf . float32 ) b = tf . Variable ([-. 3 ], dtype = tf . float32 ) # Model input and output x = tf . placeholder ( tf . float32 ) linear_model = W * x + b y = tf . placeholder ( tf . float32 ) # loss loss = tf . reduce_sum ( tf . square ( linear_model - y )) # sum of the squares # optimizer optimizer = tf . train . GradientDescentOptimizer ( 0.01 ) train = optimizer . minimize ( loss ) # training data x_train = [ 1 , 2 , 3 , 4 ] y_train = [ 0 ,- 1 ,- 2 ,- 3 ] # training loop init = tf . global_variables_initializer () sess = tf . Session () sess . run ( init ) # reset values to wrong for i in range ( 1000 ):   sess . run ( train , { x : x_train , y : y_train }) # evaluate training accuracy curr_W , curr_b , curr_loss...
閱讀完整內容