lv-sentiment-demo / metrics.py
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import numpy as np
import pandas as pd
import sys
file_path = sys.argv[1]
metric = {}
stastics = {}
with open(file_path) as input_file:
current_epoch=None
for line in input_file:
line= line.strip()
if line.find("Bert Model") >-1:
stastics["Bert Model"] =line
if line.find("Current date and time") >-1:
stastics["Current date and time"] =line
if line.find("Train file") >-1:
stastics["Train file"] =line
if line.find("Valid file") >-1:
stastics["Valid file"] =line
if line.find("Test file") >-1:
stastics["Test file"] =line
if line.find("Train size") >-1:
stastics["Train size"] =line
if line.find("Valid size") >-1:
stastics["Valid size"] =line
if line.find("Test size") >-1:
stastics["Test size"] =line
tokens = line.split()
for token in tokens:
if token.find("epoch")==0:
metric[token]=[]
current_epoch=token
continue
if token.find("train_loss")>-1:
metric[current_epoch].append(token)
if token.find("val_loss")>-1:
metric[current_epoch].append(token)
if token.find("test_loss")>-1:
metric[current_epoch].append(token)
if token.find("train_acc")>-1:
metric[current_epoch].append(token)
if token.find("val_acc")>-1:
metric[current_epoch].append(token)
if token.find("test_acc")>-1:
metric[current_epoch].append(token)
results =[]
for item in metric.items():
result=[]
result.append(item[0].replace('epoch=',""))
for fig in item[1]:
result.append(fig.split("=")[-1].replace(",",""))
results.append(result)
for item in stastics.items():
print(item[0],item[1].split()[-1])
#lets convert that to numpy array as np.array
num = np.array(results)
#now construct a beautiful table
df = pd.DataFrame(num, columns=["EPOCH","Trn loss","Val Acc" ,"Tst loss","Trn Acc","Val loss","Tst Acc"]) #
dash = 62
print("-"*dash)
print("| ".join(df.columns), "|")
for index,row in df.iterrows():
print("-"*dash)
print("|",row["EPOCH"]," |", row["Trn loss"]," |", row["Val loss"]," |",row["Tst loss"], " |", row["Trn Acc"]," |",row["Val Acc"]," |",row["Tst Acc"]," |")
print("-"*dash)
#