From 60d7070fdd41c15853c09bc1c697082039cba29e Mon Sep 17 00:00:00 2001
From: Anjith George <ageorge@idiap.ch>
Date: Wed, 3 Jun 2020 20:46:25 +0200
Subject: [PATCH] WIP: logging with summary writer
---
bob/learn/pytorch/trainers/GenericTrainer.py | 13 +++++++------
1 file changed, 7 insertions(+), 6 deletions(-)
diff --git a/bob/learn/pytorch/trainers/GenericTrainer.py b/bob/learn/pytorch/trainers/GenericTrainer.py
index 89cadfe..639339e 100644
--- a/bob/learn/pytorch/trainers/GenericTrainer.py
+++ b/bob/learn/pytorch/trainers/GenericTrainer.py
@@ -10,6 +10,7 @@ import torch.nn as nn
from torch.autograd import Variable
from .tflog import Logger
+from torch.utils.tensorboard import SummaryWriter
import bob.core
logger = bob.core.log.setup("bob.learn.pytorch")
@@ -67,7 +68,7 @@ class GenericTrainer(object):
bob.core.log.set_verbosity_level(logger, verbosity_level)
- self.tf_logger = Logger(tf_logdir)
+ self.tf_logger = SummaryWriter(log_dir=tf_logdir)
# Setting the gradients to true for the layers which needs to be adapted
@@ -252,17 +253,17 @@ class GenericTrainer(object):
# scalar logs
for tag, value in info.items():
- self.tf_logger.scalar_summary(tag, value, epoch+1)
+ self.tf_logger.add_scalar(tag=tag, scalar_value=value, global_step=epoch+1)
# Log values and gradients of the parameters (histogram summary)
for tag, value in self.network.named_parameters():
tag = tag.replace('.', '/')
try:
- self.tf_logger.histo_summary(
- tag, value.data.cpu().numpy(), epoch+1)
- self.tf_logger.histo_summary(
- tag+'/grad', value.grad.data.cpu().numpy(), epoch+1)
+ self.tf_logger.add_histogram(
+ tag=tag, values=value.data.cpu().numpy(), global_step=epoch+1)
+ self.tf_logger.add_histogram(
+ tag=tag+'/grad', values=value.grad.data.cpu().numpy(), global_step=epoch+1)
except:
pass
--
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