DeepHash
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Will there be a problem to load pretrained imagenet model?
It seems that in all your models such as dch.py, dhn.py, you first load model and pretrained model weights and then run global initializer,
self.img_last_layer, self.deep_param_img, self.train_layers, self.train_last_layer = self.load_model()
self.global_step = tf.Variable(0, trainable=False)
self.train_op = self.apply_loss_function(self.global_step)
self.sess.run(tf.global_variables_initializer())
return
We know that sess.run(tf.global_variables_initializer())
will initialize all trainable variables, so the model weights you load before are randomly initialized again if I understand correctly, right?
Looking forward to your reply!!!