With the help of this script Below is the shortest working code it gets all of the data in dataframe
then you can play further.
import traceback
import pandas as pd
from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
# Extraction function
def tflog2pandas(path):
runlog_data = pd.DataFrame({"metric": [], "value": [], "step": []})
try:
event_acc = EventAccumulator(path)
event_acc.Reload()
tags = event_acc.Tags()["scalars"]
for tag in tags:
event_list = event_acc.Scalars(tag)
values = list(map(lambda x: x.value, event_list))
step = list(map(lambda x: x.step, event_list))
r = {"metric": [tag] * len(step), "value": values, "step": step}
r = pd.DataFrame(r)
runlog_data = pd.concat([runlog_data, r])
# Dirty catch of DataLossError
except Exception:
print("Event file possibly corrupt: {}".format(path))
traceback.print_exc()
return runlog_data
path="Run1" #folderpath
df=tflog2pandas(path)
#df=df[(df.metric != 'params/lr')&(df.metric != 'params/mm')&(df.metric != 'train/loss')] #delete the mentioned rows
df.to_csv("output.csv")