Load model tensorflow

from tensorflow import keras
model = keras.models.load_model('path/to/location')

Load saved model tensorflow

new_model = tf.keras.models.load_model('my_model.h5')

Source: tensorflow.org

Use model from checkpoint tensorflow

 
with tf.Session() as sess:
  new_saver = tf.train.import_meta_graph('my_test_model-1000.meta')
  new_saver.restore(sess, tf.train.latest_checkpoint('./'))

Source: cv-tricks.com

Use model from checkpoint tensorflow

 
with tf.Session() as sess:    
    saver = tf.train.import_meta_graph('my-model-1000.meta')
    saver.restore(sess,tf.train.latest_checkpoint('./'))
    print(sess.run('w1:0'))
##Model has been restored. Above statement will print the saved value of w1.

Source: cv-tricks.com

Similar codes

24 votes111 views2 answers
How to check the type of a variable in python
Python
0 vote132 views1 answer
Standardscaler
Python
0 vote107 views1 answer
Numpy element sum privous
Python
21 votes129 views6 answers
Select columns from dataframe pandas
Python
6 votes79 views1 answer
All tkinter events
Python
3 votes120 views1 answer
What is a class
Python
1 vote115 views1 answer
Numpy divide array by scalar
Python
0 vote110 views1 answer
Exec inside def is not working in python
Python
3 votes116 views1 answer
Take array of string in python
Python
4 votes108 views2 answers
Delete rows in dataframe pandas
Python