daphna
August 1, 2021, 2:46pm
#1
Hello, I want to train Unet with TLT.
There are some configuration options that do not work for me.
I would appreciate your help
use_pooling - does not work at all
regularizer : the default value is L2 but the training worked for us just with L1
augmentation_config - the error is:
Message type “DatasetConfig” has no field named “augmentation_config”
besides, is it possible to train with multiple image sizes? Or multiple types of images?
• Hardware GeForce RTX 2080
• Network Type: Unet
• TLT Version: tlt-streamanalytics:v3.0-dp-py3
Thanks, Daphna
Please update your tlt version to tlt-streamanalytics:v3.0-py3
See TLT Quick Start Guide — Transfer Learning Toolkit 3.0 documentation
The nvidia-tlt
package is hosted in the nvidia-pyindex
, which has to be installed as a pre-requisite to install nvidia-tlt
.
If you had installed an older version of nvidia-tlt
launcher, you may upgrade to the latest version by running the following command.
pip3 install --upgrade nvidia-tlt
Please refer to UNET — Transfer Learning Toolkit 3.0 documentation
or you can download jupyter notebook and find the sample spec of Unet.
TLT Quick Start Guide — Transfer Learning Toolkit 3.0 documentation
wget --content-disposition https://api.ngc.nvidia.com/v2/resources/nvidia/tlt_cv_samples/versions/v1.1.0/zip -O tlt_cv_samples_v1.1.0.zip
unzip -u tlt_cv_samples_v1.1.0.zip -d ./tlt_cv_samples_v1.1.0 && rm -rf tlt_cv_samples_v1.1.0.zip && cd ./tlt_cv_samples_v1.1.0
daphna
August 11, 2021, 1:28pm
#5
Hello again,
We are now facing a new problem. Maybe related.
When working with the .tlt version you proposed (tlt-streamanalytics: v3.0-py3), we cannot see the examples folder. If we are working with the previous version, the examples folder exists.
About a month ago, working with the previous version, we used TLT for UNet training. It was possible to prune the model, and now we can not find that option. In addition, the deployment was to an .etlt file and now the export is to an engine file. Can you help us understand and resolve the difficulties we have presented?
Otherwise, where can we find a solution?
Thanks,
Daphna
Morganh
August 12, 2021, 12:56am
#6
Please download jupyter notebook and find the sample spec of Unet.
TLT Quick Start Guide — Transfer Learning Toolkit 3.0 documentation
wget --content-disposition https://api.ngc.nvidia.com/v2/resources/nvidia/tlt_cv_samples/versions/v1.1.0/zip -O tlt_cv_samples_v1.1.0.zip
unzip -u tlt_cv_samples_v1.1.0.zip -d ./tlt_cv_samples_v1.1.0 && rm -rf tlt_cv_samples_v1.1.0.zip && cd ./tlt_cv_samples_v1.1.0
Please refer to UNET — Transfer Learning Toolkit 3.0 documentation
daphna
August 12, 2021, 11:39am
#7
OK … Is it possible to train UNet which is not isbi?
This option was available in the previous version of tlt-streamanalytics…
Thanks for the help, we read the TLT documentation but could not find a solution to the questions we asked you. Can you refer us to a specific section that can help us?
Thank you again,
Daphna
Yes, Unet can train other dataset.
More, for your previous questions
Unet pruning, please see UNET — Transfer Learning Toolkit 3.0 documentation
for exporting to an engine, please see UNET — Transfer Learning Toolkit 3.0 documentation
Morganh
August 17, 2021, 1:08am
#10
As mention above, see TLT Quick Start Guide — Transfer Learning Toolkit 3.0 documentation , could you please download jupyter notebook and then trigger notebook and find the Unet .
wget --content-disposition https://api.ngc.nvidia.com/v2/resources/nvidia/tlt_cv_samples/versions/v1.1.0/zip -O tlt_cv_samples_v1.1.0.zip
unzip -u tlt_cv_samples_v1.1.0.zip -d ./tlt_cv_samples_v1.1.0 && rm -rf tlt_cv_samples_v1.1.0.zip && cd ./tlt_cv_samples_v1.1.0
pip3 install jupyter
jupyter notebook --ip 0.0.0.0 --allow-root --port 8888
Please refer to its step.