From e4695064e57783d72a64b44325d0a59963d8258a Mon Sep 17 00:00:00 2001
From: Andre Anjos <andre.dos.anjos@gmail.com>
Date: Thu, 2 Apr 2020 20:46:14 +0200
Subject: [PATCH] [engine] Set logger on module level
---
bob/ip/binseg/engine/inferencer.py | 6 ++++--
bob/ip/binseg/engine/predicter.py | 5 +++--
bob/ip/binseg/engine/ssltrainer.py | 5 +++--
bob/ip/binseg/engine/trainer.py | 15 ++++++++-------
4 files changed, 18 insertions(+), 13 deletions(-)
diff --git a/bob/ip/binseg/engine/inferencer.py b/bob/ip/binseg/engine/inferencer.py
index f09b39b0..4eae75ce 100644
--- a/bob/ip/binseg/engine/inferencer.py
+++ b/bob/ip/binseg/engine/inferencer.py
@@ -2,7 +2,6 @@
# -*- coding: utf-8 -*-
import os
-import logging
import time
import datetime
import numpy as np
@@ -17,6 +16,9 @@ from bob.ip.binseg.utils.metric import base_metrics
from bob.ip.binseg.utils.plot import precision_recall_f1iso_confintval
from bob.ip.binseg.utils.summary import summary
+import logging
+logger = logging.getLogger(__name__)
+
def batch_metrics(predictions, ground_truths, names, output_folder, logger):
"""
@@ -165,7 +167,7 @@ def do_inference(model, data_loader, device, output_folder=None):
device to use ``'cpu'`` or ``'cuda'``
output_folder : str
"""
- logger = logging.getLogger("bob.ip.binseg.engine.inference")
+
logger.info("Start evaluation")
logger.info("Output folder: {}, Device: {}".format(output_folder, device))
results_subfolder = os.path.join(output_folder, "results")
diff --git a/bob/ip/binseg/engine/predicter.py b/bob/ip/binseg/engine/predicter.py
index 764af86d..3aabffcc 100644
--- a/bob/ip/binseg/engine/predicter.py
+++ b/bob/ip/binseg/engine/predicter.py
@@ -2,7 +2,6 @@
# -*- coding: utf-8 -*-
import os
-import logging
import time
import datetime
import numpy as np
@@ -12,6 +11,9 @@ from tqdm import tqdm
from bob.ip.binseg.engine.inferencer import save_probability_images
from bob.ip.binseg.engine.inferencer import save_hdf
+import logging
+logger = logging.getLogger(__name__)
+
def do_predict(model, data_loader, device, output_folder=None):
@@ -27,7 +29,6 @@ def do_predict(model, data_loader, device, output_folder=None):
device to use ``'cpu'`` or ``'cuda'``
output_folder : str
"""
- logger = logging.getLogger("bob.ip.binseg.engine.inference")
logger.info("Start evaluation")
logger.info("Output folder: {}, Device: {}".format(output_folder, device))
results_subfolder = os.path.join(output_folder, "results")
diff --git a/bob/ip/binseg/engine/ssltrainer.py b/bob/ip/binseg/engine/ssltrainer.py
index 46083544..02ad551c 100644
--- a/bob/ip/binseg/engine/ssltrainer.py
+++ b/bob/ip/binseg/engine/ssltrainer.py
@@ -2,7 +2,6 @@
# -*- coding: utf-8 -*-
import os
-import logging
import time
import datetime
import torch
@@ -13,6 +12,9 @@ import numpy as np
from bob.ip.binseg.utils.metric import SmoothedValue
from bob.ip.binseg.utils.plot import loss_curve
+import logging
+logger = logging.getLogger(__name__)
+
def sharpen(x, T):
temp = x ** (1 / T)
@@ -204,7 +206,6 @@ def do_ssltrain(
rampup epochs
"""
- logger = logging.getLogger("bob.ip.binseg.engine.trainer")
logger.info("Start training")
start_epoch = arguments["epoch"]
max_epoch = arguments["max_epoch"]
diff --git a/bob/ip/binseg/engine/trainer.py b/bob/ip/binseg/engine/trainer.py
index 2b35528e..a5eb759c 100644
--- a/bob/ip/binseg/engine/trainer.py
+++ b/bob/ip/binseg/engine/trainer.py
@@ -2,7 +2,6 @@
# -*- coding: utf-8 -*-
import os
-import logging
import time
import datetime
import torch
@@ -12,6 +11,9 @@ from tqdm import tqdm
from bob.ip.binseg.utils.metric import SmoothedValue
from bob.ip.binseg.utils.plot import loss_curve
+import logging
+logger = logging.getLogger(__name__)
+
def do_train(
model,
@@ -25,12 +27,12 @@ def do_train(
arguments,
output_folder,
):
- """
+ """
Train model and save to disk.
-
+
Parameters
----------
- model : :py:class:`torch.nn.Module`
+ model : :py:class:`torch.nn.Module`
Network (e.g. DRIU, HED, UNet)
data_loader : :py:class:`torch.utils.data.DataLoader`
optimizer : :py:mod:`torch.optim`
@@ -42,14 +44,13 @@ def do_train(
checkpointer
checkpoint_period : int
save a checkpoint every n epochs
- device : str
+ device : str
device to use ``'cpu'`` or ``'cuda'``
arguments : dict
start end end epochs
- output_folder : str
+ output_folder : str
output path
"""
- logger = logging.getLogger("bob.ip.binseg.engine.trainer")
logger.info("Start training")
start_epoch = arguments["epoch"]
max_epoch = arguments["max_epoch"]
--
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