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no_preview for model
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parent
2429d28737
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b5c234dac3
2 changed files with 4 additions and 1 deletions
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@ -28,6 +28,7 @@ def trainerThread (s2c, c2s, e, args, device_args):
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save_interval_min = 15
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debug = args.get('debug', '')
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execute_programs = args.get('execute_programs', [])
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no_preview = args.get('no_preview', False)
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if not training_data_src_path.exists():
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io.log_err('Training data src directory does not exist.')
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@ -47,6 +48,7 @@ def trainerThread (s2c, c2s, e, args, device_args):
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pretraining_data_path=pretraining_data_path,
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is_training=True,
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debug=debug,
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no_preview=no_preview,
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device_args=device_args)
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is_reached_goal = model.is_reached_iter_goal()
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@ -23,7 +23,7 @@ You can implement your own model. Check examples.
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class ModelBase(object):
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def __init__(self, model_path, training_data_src_path=None, training_data_dst_path=None, pretraining_data_path=None, is_training=False, debug = False, device_args = None,
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def __init__(self, model_path, training_data_src_path=None, training_data_dst_path=None, pretraining_data_path=None, is_training=False, debug = False, no_preview=False, device_args = None,
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ask_enable_autobackup=True,
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ask_write_preview_history=True,
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ask_target_iter=True,
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@ -55,6 +55,7 @@ class ModelBase(object):
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self.pretraining_data_path = pretraining_data_path
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self.debug = debug
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self.no_preview = no_preview
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self.is_training_mode = is_training
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self.iter = 0
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