[DATALAB-2466] - [GCP] Deeplearning creation fro custom image fixed
diff --git a/infrastructure-provisioning/src/general/scripts/gcp/common_prepare_notebook.py b/infrastructure-provisioning/src/general/scripts/gcp/common_prepare_notebook.py
index 17ac8e0..96d1a3b 100644
--- a/infrastructure-provisioning/src/general/scripts/gcp/common_prepare_notebook.py
+++ b/infrastructure-provisioning/src/general/scripts/gcp/common_prepare_notebook.py
@@ -120,13 +120,14 @@
else notebook_config['expected_primary_image_name'])(str(os.environ.get('notebook_image_name')))
print('Searching pre-configured images')
+ deeplearning_ami = 'false'
+
if os.environ['conf_deeplearning_cloud_ami'] == 'true' and os.environ['application'] == 'deeplearning':
notebook_config['primary_image_name'] = GCPMeta.get_deeplearning_image_by_family(os.environ['notebook_image_name'])
if notebook_config['primary_image_name']:
deeplearning_ami = 'true'
- else:
+ if deeplearning_ami != 'true':
notebook_config['primary_image_name'] = GCPMeta.get_image_by_name(notebook_config['notebook_primary_image_name'])
- deeplearning_ami = 'false'
if notebook_config['primary_image_name'] == '':
notebook_config['primary_image_name'] = os.environ['gcp_{}_image_name'.format(os.environ['conf_os_family'])]
else:
diff --git a/infrastructure-provisioning/src/general/scripts/gcp/dataengine_prepare.py b/infrastructure-provisioning/src/general/scripts/gcp/dataengine_prepare.py
index 2051b7c..2f08899 100644
--- a/infrastructure-provisioning/src/general/scripts/gcp/dataengine_prepare.py
+++ b/infrastructure-provisioning/src/general/scripts/gcp/dataengine_prepare.py
@@ -53,6 +53,11 @@
data_engine['endpoint_tag'] = data_engine['endpoint_name']
data_engine['region'] = os.environ['gcp_region']
data_engine['zone'] = os.environ['gcp_zone']
+ data_engine['gpu_accelerator_type'] = 'None'
+ data_engine['gpu_master_accelerator_type'] = 'None'
+ data_engine['gpu_master_accelerator_count'] = 'None'
+ data_engine['gpu_slave_accelerator_type'] = 'None'
+ data_engine['gpu_slave_accelerator_count'] = 'None'
edge_status = GCPMeta.get_instance_status('{0}-{1}-{2}-edge'.format(data_engine['service_base_name'],
data_engine['project_name'],
@@ -148,7 +153,6 @@
data = {"hostname": data_engine['cluster_name'], "error": ""}
json.dump(data, f)
- data_engine['gpu_accelerator_type'] = 'None'
if os.environ['application'] in ('tensor', 'tensor-rstudio', 'deeplearning'):
if os.environ['gpu_type'] != '':
notebook_config['gpu_accelerator_type'] = os.environ['gpu_type']
