When you specify the complete network spec as in

--net_spec '[1,36,0,1 Ct3,3,16 Mp3,3 Lfys48 Lfx96 Lrx96 Lfx256 O1c111]' \

It probably treats it as a training from scratch and ignores the
continue_from.

I haven't looked at how the training command is parsed. I just followed
Ray's examples for the different kinds of training.

example: from scratch

lstmtraining \
  --debug_interval -1 \
  --traineddata ~/tesstutorial/engtrain/eng/eng.traineddata \
  --net_spec '[1,36,0,1 Ct3,3,16 Mp3,3 Lfys48 Lfx96 Lrx96 Lfx192 O1c111]' \
  --model_output ~/tesstutorial/engoutput/base --learning_rate 20e-4 \
  --train_listfile ~/tesstutorial/engtrain/eng.training_files.txt \
  --eval_listfile ~/tesstutorial/engeval/eng.training_files.txt \
  --max_iterations 5000

example: finetune for impact

lstmtraining \
  --model_output ~/tesstutorial/impact_from_full/impact \
  --continue_from ~/tesstutorial/impact_from_full/eng.lstm \
  --traineddata ../tessdata_best/eng.traineddata \
  --train_listfile ~/tesstutorial/engeval/eng.training_files.txt \
  --max_iterations 400

example: finetune plusminus

lstmtraining \
  --model_output ./plus_from_deva/sanplustrain \
  --continue_from ./plus_from_deva/Devanagari.lstm \
  --old_traineddata ../tessdata_best/script/Devanagari.traineddata \
  --traineddata ./sanplustrain/san/san.traineddata \
  --train_listfile ./sanplustrain/san.training_files.txt \
  --debug_interval 0 \
  --max_image_MB 6000 \
  --max_iterations $num_iterations

example: replace top layer

lstmtraining \
  --model_output ./layer_from_deva/layer \
  --continue_from ./layer_from_deva/Devanagari.lstm \
  --append_index 5 --net_spec '[Lfx192 O1c1]' \
  --traineddata ./sanplustrain/san/san.traineddata \
  --train_listfile ./sanplustrain/san.training_files.txt \
  --eval_listfile ./sanpluseval/san.training_files.txt \
  --debug_interval 0 \
  --max_image_MB 6000 \
  --max_iterations $num_iterations

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