CalvinBackup/iperov-DeepFaceLab
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

fix ModelBase.py

Browse Source
This commit is contained in:
iperov
2019-01-10 19:38:31 +04:00
parent f82bc7031e
commit bd2b575718
1 changed files with 4 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files
models/ModelBase.py
+4 -3
View File
@@ -64,18 +64,19 @@ class ModelBase(object):
force_best_gpu_idx = input_int("Which GPU idx to choose? ( skip: system choice ) : ", -1) force_best_gpu_idx = input_int("Which GPU idx to choose? ( skip: system choice ) : ", -1)
if self.epoch == 0 or ask_override: if self.epoch == 0 or ask_override:
self.options['write_preview_history'] = input_bool("Write preview history? (y/n ?:help skip:n) : ", False, help_message="Preview history will be writed to <ModelName>_history folder.") default_write_preview_history = False if self.epoch == 0 else self.options['batch_size']
self.options['write_preview_history'] = input_bool("Write preview history? (y/n ?:help skip:n/default) : ", default_write_preview_history, help_message="Preview history will be writed to <ModelName>_history folder.")
else: else:
self.options['write_preview_history'] = self.options.get('write_preview_history', False) self.options['write_preview_history'] = self.options.get('write_preview_history', False)
if self.epoch == 0 or ask_override: if self.epoch == 0 or ask_override:
self.options['target_epoch'] = max(0, input_int("Target epoch (skip:unlimited) : ", 0)) self.options['target_epoch'] = max(0, input_int("Target epoch (skip:unlimited/default) : ", 0))
else: else:
self.options['target_epoch'] = self.options.get('target_epoch', 0) self.options['target_epoch'] = self.options.get('target_epoch', 0)
if self.epoch == 0 or ask_override: if self.epoch == 0 or ask_override:
default_batch_size = 0 if self.epoch == 0 else self.options['batch_size'] default_batch_size = 0 if self.epoch == 0 else self.options['batch_size']
self.options['batch_size'] = max(0, input_int("Batch_size (?:help skip:default) : ", default_batch_size, help_message="Larger batch size is always better for NN's generalization, but it can cause Out of Memory error. Tune this value for your videocard manually.")) self.options['batch_size'] = max(0, input_int("Batch_size (?:help skip:0/default) : ", default_batch_size, help_message="Larger batch size is always better for NN's generalization, but it can cause Out of Memory error. Tune this value for your videocard manually."))
else: else:
self.options['batch_size'] = self.options.get('batch_size', 0) self.options['batch_size'] = self.options.get('batch_size', 0)