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visualize_log.py
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# Copyright 2020 RangerUFO
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re
import numpy as np
import matplotlib.pyplot as plt
def visualize(lines):
regex = re.compile("^\[Epoch ([0-9]+) Batch ([0-9]+)\] batch_loss (\S+).*")
batch_x = []
batch_loss = []
for line in lines:
m = regex.match(line)
if m:
batch_x.append((int(m.group(1)), int(m.group(2))))
batch_loss.append(float(m.group(3)))
batches = max(batch_x, key=lambda x: x[1])[1]
batch_x = [epoch + batch / batches for epoch, batch in batch_x]
regex = re.compile("^\[Epoch ([0-9]+)\] training_loss (\S+) validation_score (\S+).*")
epoch_x = []
training_loss = []
validation_score = []
for line in lines:
m = regex.match(line)
if m:
epoch_x.append(int(m.group(1)))
training_loss.append(float(m.group(2)))
validation_score.append(float(m.group(3)))
plt.subplot(2, 1, 1)
plt.plot(np.array(batch_x), np.array(batch_loss), label="batch loss")
plt.grid(True)
axl = plt.subplot(2, 1, 2)
axl.plot(np.array(epoch_x), np.array(training_loss))
axl.set_ylabel("training loss")
axr = axl.twinx()
axr.plot(np.array(epoch_x), np.array(validation_score), "r")
axr.set_ylabel("validation score")
plt.grid(True)
plt.show()
if __name__ == "__main__":
lines = []
while True:
try:
lines.append(input())
except EOFError:
break
visualize(lines)