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Posted to commits@datalab.apache.org by my...@apache.org on 2021/07/05 09:04:54 UTC
[incubator-datalab] 01/01: [DATALAB-2372] - [AWS] DeepLearning
notebook for using existing cloud images for deeplearning updated
This is an automated email from the ASF dual-hosted git repository.
mykolabodnar pushed a commit to branch DATALAB-2372
in repository https://gitbox.apache.org/repos/asf/incubator-datalab.git
commit 8445020ac92ee51b01e95475d8fa38801c3efc32
Author: bodnarmykola <bo...@gmail.com>
AuthorDate: Mon Jul 5 12:04:15 2021 +0300
[DATALAB-2372] - [AWS] DeepLearning notebook for using existing cloud images for deeplearning updated
---
.../src/general/files/aws/deeplearning_description.json | 2 +-
.../src/general/scripts/aws/common_prepare_notebook.py | 4 ++--
2 files changed, 3 insertions(+), 3 deletions(-)
diff --git a/infrastructure-provisioning/src/general/files/aws/deeplearning_description.json b/infrastructure-provisioning/src/general/files/aws/deeplearning_description.json
index 891cc5e..06f671a 100644
--- a/infrastructure-provisioning/src/general/files/aws/deeplearning_description.json
+++ b/infrastructure-provisioning/src/general/files/aws/deeplearning_description.json
@@ -8,7 +8,7 @@
"exploratory_environment_versions" :
[
{
- "template_name": "Deep Learning AMI (Ubuntu 18.04) Version 42.1",
+ "template_name": "Deep Learning AMI Version 42.1",
"description": "MXNet-1.8.0 & 1.7.0, TensorFlow-2.4.1, 2.1.3 & 1.15.5, PyTorch-1.4.0 & 1.8.0, Neuron, & others. NVIDIA CUDA, cuDNN, NCCL, Intel MKL-DNN, Docker, NVIDIA-Docker & EFA support. Uses Anaconda virtual environments, configured to keep the different framework installations separate and easy to switch between frameworks as Jupyter kernels.",
"environment_type": "exploratory",
"version": "Deep Learning AMI (Ubuntu 18.04) Version 42.1",
diff --git a/infrastructure-provisioning/src/general/scripts/aws/common_prepare_notebook.py b/infrastructure-provisioning/src/general/scripts/aws/common_prepare_notebook.py
index 270ae56..ad7f59d 100644
--- a/infrastructure-provisioning/src/general/scripts/aws/common_prepare_notebook.py
+++ b/infrastructure-provisioning/src/general/scripts/aws/common_prepare_notebook.py
@@ -80,7 +80,7 @@ if __name__ == "__main__":
notebook_config['project_name'],
notebook_config['endpoint_name'],
notebook_config['exploratory_name'], args.uuid)
- notebook_config['primary_disk_size'] = (lambda x: '30' if x == 'deeplearning' else '16')(
+ notebook_config['primary_disk_size'] = (lambda x: '100' if x == 'deeplearning' else '16')(
os.environ['application'])
notebook_config['role_profile_name'] = '{}-{}-{}-nb-de-profile'.format(
notebook_config['service_base_name'], notebook_config['project_name'], notebook_config['endpoint_name'])
@@ -105,7 +105,7 @@ if __name__ == "__main__":
os.environ['conf_os_family'])])
image_id = datalab.meta_lib.get_ami_id_by_name(notebook_config['notebook_image_name'], 'available')
if os.environ['conf_deeplearning_cloud_ami'] == 'true' and os.environ['application'] == 'deeplearning' and image_id == '':
- image_id = datalab.meta_lib.get_ami_id(notebook_config['notebook_image_name'])
+ image_id = datalab.meta_lib.get_ami_id(os.environ['notebook_image_name'])
if image_id != '':
notebook_config['ami_id'] = image_id
print('Pre-configured image found. Using: {}'.format(notebook_config['ami_id']))
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