Accessing a pretrained model's weights (names and values) in TensorFlow

Question

Quantitative analysis of Neural Networks needs load all variables first in TensorFlow. So I import the SSDLite MobileNet v2 model's checkpoint and restore weights. But I can not get its weights or variables by using some functions, such as get_all_coolection_keys, get_collection. The code snippet as follows:

import tensorflow as tf
import numpy as np
model_dir = 'ssdlite_mobilenet_v2_coco_2018_05_09'
checkpoint = tf.train.get_checkpoint_state(model_dir)
input_checkpoint = checkpoint.model_checkpoint_path # ssdlite_mobilenet_v2_coco_2018_05_09/model.ckpt
sess =  tf.Session()
tf.reset_default_graph()
saver = tf.train.import_meta_graph(input_checkpoint + '.meta')
graph = tf.get_default_graph()
saver.restore(sess, input_checkpoint)
# INFO:tensorflow:Restoring parameters from ssdlite_mobilenet_v2_coco_2018_05_09/model.ckpt   
graph_collections_keys = graph.get_all_collection_keys()
print(graph_collections_keys) # []
hyperparameters = tf.get_collection('hyperparameters')
print(len(hyperparameters)) # 0
model_variables = tf.get_collection(tf.GraphKeys.MODEL_VARIABLES)
print(len(model_variables)) # 0

So, how to access a pretrained model's weights (names and values) in TensorFlow?

Answer 1

pal, you can't restore variable name, weights is as far as you go. Also in tensorflow or in your code in general , the only option you got for restoring is saver . It also depends what kind of data you wanna restore if it's .npy file then np.load will do.