From e2dde35917350b05cdb6e608ca48da4456682ebf Mon Sep 17 00:00:00 2001
From: Andre Anjos <andre.dos.anjos@gmail.com>
Date: Mon, 20 Apr 2020 19:14:30 +0200
Subject: [PATCH] [engine.trainer-s] Fix pytorch>=1.1 scheduler stepping;
Remove excessive logging
---
bob/ip/binseg/engine/evaluator.py | 1 -
bob/ip/binseg/engine/predictor.py | 3 ---
bob/ip/binseg/engine/ssltrainer.py | 7 +++++--
bob/ip/binseg/engine/trainer.py | 8 ++++++--
4 files changed, 11 insertions(+), 8 deletions(-)
diff --git a/bob/ip/binseg/engine/evaluator.py b/bob/ip/binseg/engine/evaluator.py
index 65f1dfc2..5b4f2a39 100644
--- a/bob/ip/binseg/engine/evaluator.py
+++ b/bob/ip/binseg/engine/evaluator.py
@@ -216,7 +216,6 @@ def run(data_loader, predictions_folder, output_folder, overlayed_folder=None,
"""
- logger.info("Start evaluation")
logger.info(f"Output folder: {output_folder}")
if not os.path.exists(output_folder):
diff --git a/bob/ip/binseg/engine/predictor.py b/bob/ip/binseg/engine/predictor.py
index a4cd2ce1..ca22cb3e 100644
--- a/bob/ip/binseg/engine/predictor.py
+++ b/bob/ip/binseg/engine/predictor.py
@@ -129,7 +129,6 @@ def run(model, data_loader, device, output_folder, overlayed_folder):
"""
- logger.info("Start prediction")
logger.info(f"Output folder: {output_folder}")
logger.info(f"Device: {device}")
@@ -176,8 +175,6 @@ def run(model, data_loader, device, output_folder, overlayed_folder):
if overlayed_folder is not None:
_save_overlayed_png(stem, img, prob, overlayed_folder)
- logger.info("End prediction")
-
# report operational summary
total_time = datetime.timedelta(seconds=int(time.time() - start_total_time))
logger.info(f"Total time: {total_time}")
diff --git a/bob/ip/binseg/engine/ssltrainer.py b/bob/ip/binseg/engine/ssltrainer.py
index 7bd4aba0..27c0089f 100644
--- a/bob/ip/binseg/engine/ssltrainer.py
+++ b/bob/ip/binseg/engine/ssltrainer.py
@@ -16,6 +16,8 @@ from bob.ip.binseg.utils.plot import loss_curve
import logging
logger = logging.getLogger(__name__)
+PYTORCH_GE_110 = (distutils.version.StrictVersion(torch.__version__) >= "1.1.0")
+
def sharpen(x, T):
temp = x ** (1 / T)
@@ -209,7 +211,6 @@ def run(
"""
- logger.info("Start SSL training")
start_epoch = arguments["epoch"]
max_epoch = arguments["max_epoch"]
@@ -251,7 +252,7 @@ def run(
start_training_time = time.time()
for epoch in range(start_epoch, max_epoch):
- scheduler.step()
+ if not PYTORCH_GE_110: scheduler.step()
losses = SmoothedValue(len(data_loader))
labelled_loss = SmoothedValue(len(data_loader))
unlabelled_loss = SmoothedValue(len(data_loader))
@@ -296,6 +297,8 @@ def run(
unlabelled_loss.update(ul)
logger.debug(f"batch loss: {loss.item()}")
+ if PYTORCH_GE_110: scheduler.step()
+
if checkpoint_period and (epoch % checkpoint_period == 0):
checkpointer.save(f"model_{epoch:03d}", **arguments)
diff --git a/bob/ip/binseg/engine/trainer.py b/bob/ip/binseg/engine/trainer.py
index 040e5651..dee2d628 100644
--- a/bob/ip/binseg/engine/trainer.py
+++ b/bob/ip/binseg/engine/trainer.py
@@ -5,6 +5,7 @@ import os
import csv
import time
import datetime
+import distutils.version
import torch
import pandas
@@ -16,6 +17,8 @@ from bob.ip.binseg.utils.plot import loss_curve
import logging
logger = logging.getLogger(__name__)
+PYTORCH_GE_110 = (distutils.version.StrictVersion(torch.__version__) >= "1.1.0")
+
def run(
model,
@@ -69,7 +72,6 @@ def run(
output path
"""
- logger.info("Start training")
start_epoch = arguments["epoch"]
max_epoch = arguments["max_epoch"]
@@ -108,7 +110,7 @@ def run(
start_training_time = time.time()
for epoch in range(start_epoch, max_epoch):
- scheduler.step()
+ if not PYTORCH_GE_110: scheduler.step()
losses = SmoothedValue(len(data_loader))
epoch = epoch + 1
arguments["epoch"] = epoch
@@ -139,6 +141,8 @@ def run(
losses.update(loss)
logger.debug(f"batch loss: {loss.item()}")
+ if PYTORCH_GE_110: scheduler.step()
+
if checkpoint_period and (epoch % checkpoint_period == 0):
checkpointer.save(f"model_{epoch:03d}", **arguments)
--
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