33 lines
1.4 KiB
Python
33 lines
1.4 KiB
Python
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from keras.callbacks import Callback
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import numpy as np
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import os
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import csv
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class LossHistory(Callback):
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def __init__(self, job_folder, logger):
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super(LossHistory, self).__init__()
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self.save_path = job_folder
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self.logger = logger
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def on_train_begin(self, logs={}):
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self.logger.debug("Training started!")
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self.train_losses = []
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self.val_losses = []
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def on_epoch_end(self, epoch, logs={}):
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self.logger.debug("Training loss for epoch {} is {}".format(epoch+1, logs.get('loss')))
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self.logger.debug("Validation loss for epoch {} is {}".format(epoch+1, logs.get('val_loss')))
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self.train_losses.append(logs.get('loss'))
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self.val_losses.append(logs.get('val_loss'))
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with open(os.path.join(self.save_path, 'train_losses.csv'), 'a') as f:
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writer = csv.writer(f)
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writer.writerow([logs.get('loss')])
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with open(os.path.join(self.save_path, 'val_losses.csv'), 'a') as f:
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writer = csv.writer(f)
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writer.writerow([logs.get('val_loss')])
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def on_train_end(self, logs={}):
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self.logger.info('Saving training and validation loss history to file...')
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np.save(os.path.join(self.save_path, 'train_losses.npy'), np.array(self.train_losses))
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np.save(os.path.join(self.save_path, 'val_losses.npy'), np.array(self.val_losses))
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