Closed junweima closed 6 years ago
Hi, I solved it by passing a larger value or set None for NUM_TRAIN_STEPS and NUM_EVAL_STEPS. I didn't know train_steps is set to max_steps in function create_train_and_eval_specs in model_lib.py
train_spec = tf.estimator.TrainSpec( input_fn=train_input_fn, max_steps=train_steps)
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I'm training ssdlite model with mobileNetV2 on coco dataset, everything is default. The training was interrupted and killed and now I want to restore the model and resume training.
However, the current script does not support this feature. I tried to set fine_tune_checkpoint_type: "detection", the model is loaded but the script only runs evaluation without training. Is there a way to resume training?
I've seen this https://github.com/tensorflow/models/issues/4116 post but I'm not sure which part was modified and train.py seemed to be moved to legacy folder now.
Specifically, I just want to ask 1. Is there a feature for resuming training? If so, which flags should I set? 2. If there is no such feature, could you give some pointers on how to add this feature? I can make a PR if needed.
Thanks.