/usr/bin/lstmtraining

Usage:
  /usr/bin/lstmtraining -v | --version | /usr/bin/lstmtraining [.tr files ...] [OPTION ...]

  --debug_level  Level of Trainer debugging  (type:int default:0)
  --load_images  Load images with tr files  (type:int default:0)
  --debug_interval  How often to display the alignment.  (type:int default:0)
  --net_mode  Controls network behavior.  (type:int default:192)
  --perfect_sample_delay  How many imperfect samples between perfect ones.  (type:int default:0)
  --max_image_MB  Max memory to use for images.  (type:int default:6000)
  --append_index  Index in continue_from Network at which to attach the new network defined by net_spec  (type:int default:-1)
  --max_iterations  If set, exit after this many iterations  (type:int default:0)
  --clusterconfig_min_samples_fraction  Min number of samples per proto as % of total  (type:double default:0.625)
  --clusterconfig_max_illegal  Max percentage of samples in a cluster which have more than 1 feature in that cluster  (type:double default:0.05)
  --clusterconfig_independence  Desired independence between dimensions  (type:double default:1)
  --clusterconfig_confidence  Desired confidence in prototypes created  (type:double default:1e-06)
  --target_error_rate  Final error rate in percent.  (type:double default:0.01)
  --weight_range  Range of initial random weights.  (type:double default:0.1)
  --learning_rate  Weight factor for new deltas.  (type:double default:0.001)
  --momentum  Decay factor for repeating deltas.  (type:double default:0.5)
  --adam_beta  Decay factor for repeating deltas.  (type:double default:0.999)
  --reset_learning_rate  Resets all stored learning rates to the value specified by --learning_rate.  (type:bool default:false)
  --debug_float  Raise error on certain float errors.  (type:bool default:false)
  --stop_training  Just convert the training model to a runtime model.  (type:bool default:false)
  --convert_to_int  Convert the recognition model to an integer model.  (type:bool default:false)
  --sequential_training  Use the training files sequentially instead of round-robin.  (type:bool default:false)
  --debug_network  Get info on distribution of weight values  (type:bool default:false)
  --randomly_rotate  Train OSD and randomly turn training samples upside-down  (type:bool default:false)
  --configfile  File to load more configs from  (type:string default:)
  --D  Directory to write output files to  (type:string default:)
  --F  File listing font properties  (type:string default:font_properties)
  --X  File listing font xheights  (type:string default:)
  --U  File to load unicharset from  (type:string default:unicharset)
  --O  File to write unicharset to  (type:string default:)
  --output_trainer  File to write trainer to  (type:string default:)
  --test_ch  UTF8 test character string  (type:string default:)
  --fonts_dir    (type:string default:)
  --fontconfig_tmpdir    (type:string default:)
  --net_spec  Network specification  (type:string default:)
  --continue_from  Existing model to extend  (type:string default:)
  --model_output  Basename for output models  (type:string default:lstmtrain)
  --train_listfile  File listing training files in lstmf training format.  (type:string default:)
  --eval_listfile  File listing eval files in lstmf training format.  (type:string default:)
  --traineddata  Combined Dawgs/Unicharset/Recoder for language model  (type:string default:)
  --old_traineddata  When changing the character set, this specifies the old character set that is to be replaced  (type:string default:)