PLOTTING TENSORFLOW EPOCH LOSSES

plot_tf_loss.py

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### PLOTTING TENSORFLOW EPOCH LOSSES ###
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"""
NOTE: this script assumes the epoch output of a tensorflow run has been saved in a .TXT file called 'val.txt' in the working directory.

The copied text should be formatted to look like the following...

---------------------------------------------------------------------------------------------------

200/200 [==============================] - 9s 46ms/step - loss: 0.3036 - val_loss: 0.2138
Epoch 2/20
200/200 [==============================] - 4s 22ms/step - loss: 0.2013 - val_loss: 0.2014
Epoch 3/20

---------------------------------------------------------------------------------------------------


In particular, this script assumes the losses are printed after the word 'loss' or 'val_loss' followed by a colon and space, and that the losses are printed to four decimal places.

"""

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

row_num = 0

loss_line = []
val_loss_line = []

txt = open('val.txt','r')

for line in txt:
	if line.find('loss')!=-1:
		loss_pos = line.find('loss')
		loss = float(line[loss_pos+6:loss_pos+12])
		loss_line.append(loss)

		val_loss_pos = line.find('val_loss')
		val_loss = float(line[val_loss_pos+10:val_loss_pos+16])
		val_loss_line.append(val_loss)


epoch = (list(range(1,len(loss_line)+1)))

dict = {'Epoch':epoch,'Loss':loss_line,'Val_Loss':val_loss_line}

df = pd.DataFrame(dict)
df = df.set_index('Epoch')

#print(df)

plt.plot(df)
plt.legend(['Loss','Val_loss'])
plt.xticks(np.arange(0, len(epoch)+1, 1))
plt.ylabel('Loss')
plt.xlabel('Epoch')
plt.title('Loss Over Epoch')
plt.show()