Hello,
I found that you used this code to init the pre-trained model params. But when I training the model with pre-trained model, it will re-init the ResNet params every epoch when calling model_fn. Is this an intentional behavior? Thanks a lot.
if is_training:
exclude = [base_architecture + '/logits', 'global_step']
variables_to_restore = tf.contrib.slim.get_variables_to_restore(exclude=exclude)
tf.train.init_from_checkpoint(pre_trained_model,
{v.name.split(':')[0]: v for v in variables_to_restore})
Hello, I found that you used this code to init the pre-trained model params. But when I training the model with pre-trained model, it will re-init the ResNet params every epoch when calling model_fn. Is this an intentional behavior? Thanks a lot.