def get_record_keeper():
# record_keeper is a useful package for logging data during training and testing
# You can use the trainers and testers without record_keeper.
# But if you'd like to install it, then do pip install record_keeper
# See more info about it here https://github.com/KevinMusgrave/record_keeper
try:
import os
import errno
import record_keeper as record_keeper_package
from torch.utils.tensorboard import SummaryWriter
def makedir_if_not_there(dir_name):
try:
os.makedirs(dir_name)
except OSError as e:
if e.errno != errno.EEXIST:
raise
pkl_folder = "example_logs"
tensorboard_folder = "example_tensorboard"
makedir_if_not_there(pkl_folder)
makedir_if_not_there(tensorboard_folder)
pickler_and_csver = record_keeper_package.PicklerAndCSVer(pkl_folder)
tensorboard_writer = SummaryWriter(log_dir=tensorboard_folder)
return record_keeper_package.RecordKeeper(
tensorboard_writer, pickler_and_csver,
["record_these", "learnable_param_names"])
except ModuleNotFoundError:
return None
def get_record_keeper(pkl_folder, tensorboard_folder):
try:
import record_keeper as record_keeper_package
from torch.utils.tensorboard import SummaryWriter
pickler_and_csver = record_keeper_package.PicklerAndCSVer(pkl_folder)
tensorboard_writer = SummaryWriter(log_dir=tensorboard_folder)
record_keeper = record_keeper_package.RecordKeeper(
tensorboard_writer, pickler_and_csver,
["record_these", "learnable_param_names"])
return record_keeper, pickler_and_csver, tensorboard_writer
except ModuleNotFoundError as e:
logging.warn(e)
return None, None, None
import errno
import record_keeper as record_keeper_package
from torch.utils.tensorboard import SummaryWriter
def makedir_if_not_there(dir_name):
try:
os.makedirs(dir_name)
except OSError as e:
if e.errno != errno.EEXIST:
raise
pkl_folder = "example_logs"
tensorboard_folder = "example_tensorboard"
makedir_if_not_there(pkl_folder)
makedir_if_not_there(tensorboard_folder)
pickler_and_csver = record_keeper_package.PicklerAndCSVer(pkl_folder)
tensorboard_writer = SummaryWriter(log_dir=tensorboard_folder)
record_keeper = record_keeper_package.RecordKeeper(
tensorboard_writer, pickler_and_csver,
["record_these", "learnable_param_names"])
except ModuleNotFoundError:
record_keeper = None
##############################
########## Training ##########
##############################
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
# Set trunk model and replace the softmax layer with an identity function