I printed all tensor value in a checkpoint file.
I can understand "conv1/weights". But what is "conv1/weights/Adam" in checkpoint file?
It's an extra variable that was created because you are using an AdamOptimizer() to train your data. You can read about the algorithm in the original paper - https://arxiv.org/pdf/1412.6980v8.pdf
Related
Is it possible to restore a checkpoint if ckpt.index file is missing, and only ckpt.data, meta and .pb (the frozen model corresponding to this checkpoint) files are available?
Context: I want to load the model from the checkpoint and resume training.
No, you need to have ckpt.index file as well.
I have a tensorflow model that saves checkpoints, but I need to to load the weights and save the Kereas .h5 model. How can I do that?
I am assuming you need to convert your previous checkpoint into .h5
Given an already trained model, you want to load its weights and save as .h5. I am assuming you have it saved as a .model file. Lets say it was called first.model
In your script, you will want to use load_model, loading your checkpoint with
model = load_model('first.model')
then you will simply need to use
model.save('goal.h5')
to save as a .h5 file.
For future reference, you can avoid this conversion process by saving checkpoints as .h5:
When using the Checkpoints feature, you have the option to save as either a .model .h5, or .hdf5. The line might look something like this:
checkpoint = ModelCheckpoint("**FILE_NAME_HERE**.model",monitor='val_loss',verbose=1,mode='min',save_best_only=True,save_weights_only=False,period=1)
That is how you save your checkpoint as a .model, but to save it as a h5 as you are looking to do:
checkpoint = ModelCheckpoint("**FILE_NAME_HERE**.h5",monitor='val_loss',verbose=1,mode='min',save_best_only=True,save_weights_only=False,period=1)
Does export_inference_graph.py need an exact checkpoint number, or is there a way to run it so that it will use the highest numbered checkpoint in a directory?
It needs exact checkpoint number in the command to find the correct file.
I want to change a ckpt files's tensor's value by many other ckpt files's tensors, and use the modified ckpt files to restart TF training jobs.
Hope you some advices!
Thanks!
There are standalone utilities for reading checkpoint files (search for CheckpointReader or NewCheckpointReader) but not modifying them. The easiest approach is probably to load the checkpoint into your model, assign a new value to the variable you want to change, and save this new checkpoint.
I have implemented the sequence to sequence model in Tensorflow for about 100,000 steps without specifying the summarizing operations required for TensorBoard.
I have the checkpoint log files for every 1000 steps. Is there any way to visualize the data without having to retrain the entire model i.e. extract the summaries from the checkpoint files to feed to TensorBoard?
I tried running TensorBoard directly on the checkpoint files, which obviously said no scalar summaries found. I also tried inserting the summary operations in code but it requires me to completely retrain the model for the summaries to get created.