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3
docs/apps/clearml_task.md
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@ -65,6 +65,7 @@ errors in identifying the correct default branch.
| `--docker_bash_setup_script` | Add a bash script to be executed inside the container before setting up the task's environment | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
| `--docker_args` | Add Docker arguments. Pass a single string in the following format: `--docker_args "<argument_string>"`. For example: `--docker_args "-v some_dir_1:other_dir_1 -v some_dir_2:other_dir_2"` | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
| `--folder` | Execute the code from a local folder. Notice, it assumes a git repository already exists. Current state of the repo (commit ID and uncommitted changes) is logged and replicated on the remote machine | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
| `--force-no-requirements` | If specified, skips all package and requirements installation, and neither packages nor a requirements file need to be provided. | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
| `--import-offline-session`| Specify the path to the offline session you want to import.| <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
| `--name` | Set a target name for the new task | <img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" /> |
| `--output-uri` | Set the task `output_uri`, upload destination for task models and artifacts | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
@ -73,7 +74,9 @@ errors in identifying the correct default branch.
| `--queue` | Select a task's execution queue. If not provided, a task is created but not launched | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
| `--repo` | URL of remote repository. Example: `--repo https://github.com/clearml/clearml.git` | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
| `--requirements` | Specify `requirements.txt` file to install when setting the session. By default, the` requirements.txt` from the repository will be used | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
| `--skip-python-env-install` | If specified, agent will use the existing Python environment without installing packages. Only applies when running in Docker mode or on Kubernetes. | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
| `--script` | Entry point script for the remote execution. When used with `--repo`, input the script's relative path inside the repository. For example: `--script source/train.py`. When used with `--folder`, it supports a direct path to a file inside the local repository itself, for example: `--script ~/project/source/train.py` | <img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" /> |
| `--skip-repo-detection` | If specified, skip repository detection when a repository is not specified. No repository will be set in remote execution | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
| `--skip-task-init` | If set, `Task.init()` call is not added to the entry point, and is assumed to be called within the script | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
| `--tags` | Add tags to the newly created task. For example: `--tags "base" "job"` | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
| `--task-type` | Set the task type. Optional values: training, testing, inference, data_processing, application, monitor, controller, optimizer, service, qc, custom | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |

4
docs/deploying_clearml/enterprise_deploy/agent_k8s.md
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@ -11,7 +11,7 @@ The ClearML Agent enables scheduling and executing distributed experiments on a
the ClearML UI (**Settings > Workspace > API Credentials > Create new credentials**). For more information, see [ClearML API Credentials](../../webapp/settings/webapp_settings_profile.md#clearml-api-credentials).
:::note
Make sure these credentials belong to an admin user or a service user with admin privileges.
Make sure these credentials belong to an admin user or a service account with admin privileges.
:::
- The worker environment must be able to access the ClearML Server over the same network.
@ -26,7 +26,7 @@ Add the ClearML Helm repository:
helm repo add clearml-enterprise https://raw.githubusercontent.com/clearml/clearml-enterprise-helm-charts/gh-pages --username <HELM_REPO_TOKEN> --password <HELM_REPO_TOKEN>
```
Update the repository locally:
Update the local repository:
```bash
helm repo update
```

4
docs/deploying_clearml/enterprise_deploy/extra_configs/apps.md
View File

@ -11,14 +11,14 @@ Applications are installed on top of the ClearML Server and are provided by the
## Requirements
- Python 3 installed on your local machine to run the provided installation scripts)
- Python 3 installed on your local machine to run the provided installation scripts
- A ClearML Enterprise Server is up and running with `clearmlApplications.enabled` set to `"true"` in the server's `overrides.yaml` file.
- Applications package provided by ClearML, including the following scripts:
- `convert_image_registry.py`
- `upload_apps.py`
- API credentials (`<ACCESS_KEY>` and `<SECRET_KEY>`) generated via
the ClearML UI (**Settings > Workspace > API Credentials > Create new credentials**). Make sure these credentials
belong to an admin user or a service user with admin privilegesFor more information, see [ClearML API Credentials](../../webapp/settings/webapp_settings_profile.md#clearml-api-credentials).
belong to an admin user or a service user with admin privilegesFor more information, see [ClearML API Credentials](../../../webapp/settings/webapp_settings_profile.md#clearml-api-credentials).
## Installation

13
docs/deploying_clearml/enterprise_deploy/extra_configs/dynamic_edit_task_pod_template.md
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@ -18,8 +18,8 @@ Arguments passed to the function include:
* `queue` (string) - ID of the queue from which the task was pulled.
* `queue_name` (string) - Name of the queue from which the task was pulled.
* `template` (Python dictionary) - Base Pod template created from the agent's configuration and any queue-specific overrides.
* `task_data` (object) - Task data object (as returned by the `tasks.get_by_id` API call). For example, use `task_data.project` to get the task's project ID.
* `providers_info` (dictionary) - Provider info containing optional information collected for the user running this task
* `task_data` (object) - [Task object](../../../references/sdk/task.md) (as returned by the `tasks.get_by_id` API call). For example, use `task_data.project` to get the task's project ID.
* `providers_info` (dictionary) - [Identity provider](sso_login.md) info containing optional information collected for the user running this task
when the user logged into the system (requires additional server configuration).
* `task_config` (`clearml_agent.backend_config.Config` object) - Task configuration containing configuration vaults applicable
for the user running this task, and other configuration. Use `task_config.get("...")` to get specific configuration values.
@ -248,11 +248,8 @@ agentk8sglue:
- mountPath: "/tmp/task/"
name: task-pvc
```
:::
### Example: Required Role
The following is an example of `custom-agent-role` Role with permissions to handle `persistentvolumeclaims`:
* The following is an example of `custom-agent-role` Role with permissions to handle `persistentvolumeclaims`:
```yaml
apiVersion: rbac.authorization.k8s.io/v1
@ -271,4 +268,6 @@ rules:
- create
- patch
- delete
```
```
:::

2
docs/deploying_clearml/enterprise_deploy/extra_configs/gpu_operator.md
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@ -12,7 +12,7 @@ Add the NVIDIA GPU Operator Helm repository:
helm repo add nvidia https://nvidia.github.io/gpu-operator
```
Update the repository locally:
Update the local repository:
```bash
helm repo update
```

24
docs/deploying_clearml/enterprise_deploy/extra_configs/multi_node_training.md
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@ -2,10 +2,28 @@
title: Multi-Node Training
---
The ClearML Enterprise Agent supports horizontal multi-node training, allowing a single Task to run across multiple pods
The ClearML Enterprise Agent supports horizontal multi-node training, allowing a single ClearML Task to run across multiple pods
on different nodes.
Below is a configuration example using `clearml-agent-values.override.yaml`:
This is useful for distributed training where the training job needs to span multiple GPUs and potentially
multiple nodes.
To enable multi-node scheduling, set both `agentk8sglue.serviceAccountClusterAccess` and `agentk8sglue.multiNode` to `true`.
Multi-node behavior is controlled using the `multiNode` key in a queue configuration. This setting tells the
agent how to divide a Task's GPU requirements across multiple pods, with each pod running a part of the training job.
Below is a configuration example using `clearml-agent-values.override.yaml` to enable multi-node training.
In this example:
* The `multiNode: [4, 2]` setting means splits the Task into two workloads:
* One workload will need 4 GPUs
* The other workload will need 2 GPUs
* The GPU limit per pod is set to `nvidia.com/gpu: 2`, meaning each pod will be limited to 2 GPUs
With this setup:
* The first workload (which needs 4 GPUs) will be scheduled as 2 pods, each with 2 GPUs
* The second workload (which needs 2 GPUs) will be scheduled as 1 pod with 2 GPUs
```yaml
agentk8sglue:
@ -17,7 +35,7 @@ agentk8sglue:
queues:
multi-node-example:
queueSettings:
# Defines the distribution of GPUs Tasks across multiple nodes. The format [x, y, ...] specifies the distribution of Tasks as 'x' GPUs on a node and 'y' GPUs on another node. Multiple Pods will be spawned respectively based on the lowest-common-denominator defined.
# Defines GPU needs per worker (e.g., 4 GPUs and 2 GPUs). Multiple Pods will be spawned respectively based on the lowest-common-denominator defined.
multiNode: [ 4, 2 ]
templateOverrides:
resources:

17
docs/deploying_clearml/enterprise_deploy/extra_configs/presign_service.md
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@ -1,9 +1,18 @@
---
title: ClearML Presign Service
title: ClearML S3 Presign Service
---
The ClearML Presign Service is a secure service that generates and redirects pre-signed storage URLs for authenticated
users, enabling direct access to cloud-hosted data (e.g., S3) without exposing credentials.
users, enabling direct access to S3 data without exposing credentials.
When configured, the ClearML WebApp automatically redirects requests for matching storage URLs (like `s3://...`) to the
Presign Service. The service:
* Authenticates the user with ClearML.
* Generates a temporary, secure (pre-signed) S3 URL.
* Redirects the user's browser to the URL for direct access.
This setup ensures secure access to S3-hosted data.
## Prerequisites
@ -12,7 +21,7 @@ users, enabling direct access to cloud-hosted data (e.g., S3) without exposing c
the ClearML UI (**Settings > Workspace > API Credentials > Create new credentials**). For more information, see [ClearML API Credentials](../../../webapp/settings/webapp_settings_profile.md#clearml-api-credentials).
:::note
Make sure these credentials belong to an admin user or a service user with admin privileges.
Make sure these credentials belong to an admin user or a service account with admin privileges.
:::
- The worker environment must be able to access the ClearML Server over the same network.
@ -27,7 +36,7 @@ Add the ClearML Helm repository:
helm repo add clearml-enterprise https://raw.githubusercontent.com/clearml/clearml-enterprise-helm-charts/gh-pages --username <HELM_REPO_TOKEN> --password <HELM_REPO_TOKEN>
```
Update the repository locally:
Update the local repository:
```bash
helm repo update
```

103
docs/deploying_clearml/enterprise_deploy/extra_configs/self_signed_certificates.md
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@ -1,13 +1,15 @@
---
title: ClearML Tenant with Self Signed Certificates
title: Kubernetes Deployment with Self-Signed Certificates
---
This guide covers how to configure the [AI Application Gateway](#ai-application-gateway) and [ClearML Agent](#clearml-agent)
This guide covers how to configure the [AI Application Gateway](../appgw.md) and [ClearML Agent](../agent_k8s.md)
to use self-signed or custom SSL certificates.
## AI Application Gateway
## Certificate Configuration
To configure certificates for the Application Gateway, update your `clearml-app-gateway-values.override.yaml` file:
To configure certificates, update the applicable overrides file:
* For AI Application Gateway: `clearml-app-gateway-values.override.yaml` file
* For ClearML Agent: `clearml-agent-values.override.yaml` file
```yaml
# -- Custom certificates
@ -72,83 +74,7 @@ customCertificates:
-----END CERTIFICATE-----
```
### Apply Changes
To apply the changes, run the update command:
```bash
helm upgrade -i <RELEASE_NAME> -n <WORKLOAD_NAMESPACE> clearml-enterprise/clearml-enterprise-app-gateway --version <CHART_VERSION> -f clearml-app-gateway-values.override.yaml
```
## ClearML Agent
For the ClearML Agent, configure certificates in the `clearml-agent-values.override.yaml` file:
```yaml
# -- Custom certificates
customCertificates:
# -- Override system crt certificate bundle. Mutual exclusive with extraCerts.
overrideCaCertificatesCrt:
# -- Extra certs usable in case of needs of adding more certificates to the standard bundle, Requires root permissions to run update-ca-certificates. Mutual exclusive with overrideCaCertificatesCrt.
extraCerts:
- alias: certificateName
pem: |
-----BEGIN CERTIFICATE-----
###
-----END CERTIFICATE-----
```
You have two configuration options:
- [**Replace**](#replace-entire-ca-certificatescrt-file-1) the entire `ca-certificates.crt` file
- [**Append**](#append-extra-certificates-to-the-existing-ca-certificatescrt-1) extra certificates to the existing `ca-certificates.crt`
### Replace Entire ca-certificates.crt File
To replace the whole ca-bundle, provide a concatenated list of all trusted CA certificates in `pem` format as
they are stored in a standard `ca-certificates.crt`.
```yaml
# -- Custom certificates
customCertificates:
# -- Override system crt certificate bundle. Mutual exclusive with extraCerts.
overrideCaCertificatesCrt: |
-----BEGIN CERTIFICATE-----
### CERT 1
-----END CERTIFICATE-----
-----BEGIN CERTIFICATE-----
### CERT 2
-----END CERTIFICATE-----
-----BEGIN CERTIFICATE-----
### CERT 3
-----END CERTIFICATE-----
...
```
### Append Extra Certificates to the Existing ca-certificates.crt
You can add certificates to the existing CA bundle. Each certificate must have a unique `alias`.
```yaml
# -- Custom certificates
customCertificates:
# -- Extra certs usable in case of needs of adding more certificates to the standard bundle, Requires root permissions to run update-ca-certificates. Mutual exclusive with overrideCaCertificatesCrt.
extraCerts:
- alias: certificate-name-1
pem: |
-----BEGIN CERTIFICATE-----
###
-----END CERTIFICATE-----
- alias: certificate-name-2
pem: |
-----BEGIN CERTIFICATE-----
###
-----END CERTIFICATE-----
```
### Add Certificates to Task Pods
### ClearML Agent: Add Certificates to Task Pods
If your workloads need access to these certificates (e.g., for HTTPS requests), configure the agent to inject them into pods:
@ -194,8 +120,15 @@ Their names are usually prefixed with the Helm release name, so adjust according
### Apply Changes
Apply the changes by running the update command:
To apply the changes, run the update command:
* For AI Application Gateway:
``` bash
helm upgrade -i -n <WORKER_NAMESPACE> clearml-agent clearml-enterprise/clearml-enterprise-agent --create-namespace -f clearml-agent-values.override.yaml
```
```bash
helm upgrade -i <RELEASE_NAME> -n <WORKLOAD_NAMESPACE> clearml-enterprise/clearml-enterprise-app-gateway --version <CHART_VERSION> -f clearml-app-gateway-values.override.yaml
```
* For ClearML Agent:
```bash
helm upgrade -i -n <WORKER_NAMESPACE> clearml-agent clearml-enterprise/clearml-enterprise-agent --create-namespace -f clearml-agent-values.override.yaml
```

11
docs/deploying_clearml/enterprise_deploy/extra_configs/sso_login.md
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@ -6,13 +6,8 @@ ClearML Enterprise Server supports various Single Sign-On (SSO) identity provide
SSO configuration is managed via environment variables in your `clearml-values.override.yaml` file and is applied to the
`apiserver` component.
The following are configuration examples for commonly used providers. Other supported systems include:
* Auth0
* Keycloak
* Okta
* Azure AD
* Google
* AWS Cognito
The following are configuration examples for commonly used identity providers. See [full list of supported identity providers](../../../webapp/settings/webapp_settings_id_providers.md).
## Auth0
@ -52,7 +47,7 @@ apiserver:
value: "true"
```
## Group Membership Mapping in Keycloak
### Group Membership Mapping in Keycloak
To map Keycloak groups into the ClearML user's SSO token:

22
docs/deploying_clearml/enterprise_deploy/fractional_gpus/cdmo.md
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@ -1,8 +1,14 @@
---
title: ClearML Dynamic MIG Operator (CDMO)
title: Managing GPU Fractions with ClearML Dynamic MIG Operator (CDMO)
---
The ClearML Dynamic MIG Operator (CDMO) enables dynamic MIG (Multi-Instance GPU) configurations.
This guide covers using GPU fractions in Kubernetes clusters using NVIDIA MIGs and
ClearML's Dynamic MIG Operator (CDMO). CDMO enables dynamic MIG (Multi-Instance GPU) configurations.
This guide covers:
* Installing CDMO
* Enabling MIG mode on your cluster
* Managing GPU partitioning dynamically
## Installation
@ -78,7 +84,7 @@ The ClearML Dynamic MIG Operator (CDMO) enables dynamic MIG (Multi-Instance GPU
* For convenience, this command can be run from within the `nvidia-device-plugin-daemonset` pod running on the related node.
:::
1. Label all MIG-enabled GPU node `<NODE_NAME>` from the previous step:
1. Label all MIG-enabled GPU nodes `<NODE_NAME>` from the previous step:
```bash
kubectl label nodes <NODE_NAME> "cdmo.clear.ml/gpu-partitioning=mig"
@ -106,7 +112,7 @@ To disable MIG mode and restore standard full-GPU access:
nvidia-smi -mig 0
```
4. Edit the `gpu-operator.override.yaml` file to restore full-GPU access, and upgrade the `gpu-operator`:
4. Edit the `gpu-operator.override.yaml` file to restore full-GPU access:
```yaml
toolkit:
@ -129,4 +135,10 @@ To disable MIG mode and restore standard full-GPU access:
value: all
- name: NVIDIA_DRIVER_CAPABILITIES
value: all
```
```
5. Upgrade the `gpu-operator`:
```bash
helm upgrade -n gpu-operator gpu-operator nvidia/gpu-operator -f gpu-operator.override.yaml
```

6
docs/deploying_clearml/enterprise_deploy/fractional_gpus/cfgi.md
View File

@ -16,7 +16,7 @@ helm repo update
### Requirements
* Install the NVIDIA `gpu-operator` using Helm
* Install the NVIDIA `gpu-operator` using Helm. For instructions, see [Basic Deployment](../extra_configs/gpu_operator.md).
* Set the number of GPU slices to 8
* Add and update the Nvidia Helm repo:
@ -59,7 +59,7 @@ helm repo update
devicePlugin:
repository: docker.io/clearml
image: k8s-device-plugin
version: v0.17.1-gpu-card-selection
version: "v0.17.2-gpu-card-selection"
imagePullPolicy: Always
imagePullSecrets:
- "clearml-dockerhub-access"
@ -191,7 +191,7 @@ Valid values for `"<GPU_FRACTION_VALUE>"` include:
### ClearML Agent Configuration
To run ClearML jobs with fractional GPU allocation, configure your queues in accordingly in your `clearml-agent-values.override.yaml` file.
To run ClearML jobs with fractional GPU allocation, configure your queues in your `clearml-agent-values.override.yaml` file.
Each queue should include a `templateOverride` that sets the `clearml-injector/fraction` label, which determines the
fraction of a GPU to allocate (e.g., "0.500" for half a GPU).

2
docs/deploying_clearml/enterprise_deploy/k8s.md
View File

@ -50,7 +50,7 @@ Add the ClearML Helm repository:
helm repo add clearml-enterprise https://raw.githubusercontent.com/clearml/clearml-enterprise-helm-charts/gh-pages --username <HELM_REPO_TOKEN> --password <HELM_REPO_TOKEN>
```
Update the repository locally:
Update the local repository:
``` bash
helm repo update
```

4
docs/release_notes/clearml_server/enterprise/ver_3_25.md
View File

@ -29,7 +29,7 @@ title: Version 3.25
* Display per-GPU metrics in "CPU and GPU Usage" and "Video Memory" graphs when multiple GPUs are available
* Add "GPU Count" column to the Resource Groups table in the Orchestration Dashboard
* Add global search bar to all UI pages
* Enable setting service users as admins
* Enable setting service accounts as admins
* Add filter to UI Model Endpoints table
* Add UI scalar viewing configuration on a per-project basis ([ClearML GitHub issue #1377](https://github.com/clearml/clearml/issues/1377))
* Add clicking project name in breadcrumbs of full-screen task opens the task in detail’s view ([ClearML GitHub issue #1376](https://github.com/clearml/clearml/issues/1376))
@ -42,7 +42,7 @@ title: Version 3.25
* Fix EMA smoothing in UI scalars is incorrect in first data point ([ClearML Web GitHub issue #101](https://github.com/clearml/clearml-web/issues/101))
* Improve UI scalar smoothing algorithms (ClearML Web GitHub issues [#101](https://github.com/clearml/clearml-web/issues/101), [#102](https://github.com/clearml/clearml-web/issues/102), [#103](https://github.com/clearml/clearml-web/issues/103))
* Fix UI Users & Groups table's "Groups" column data remains condensed after column is expanded
* Fix setting service users as admins causes apiserver to crash
* Fix setting service accounts as admins causes apiserver to crash
* Fix UI "New Dataview" modal's version selection sometimes does not display draft versions
* Fix GCS and Azure credential input popups not displaying in UI task debug samples
* Fix UI pipeline "Preview" tab sometimes displays "Failed to get plot charts" error

33
docs/release_notes/sdk/open_source/ver_2_0.md Normal file
View File

@ -0,0 +1,33 @@
---
title: Version 2.0
---
### ClearML 2.0.0
**New Features**
* Clean up exception handling in `cleanup_service.py` ([ClearML GitHub issue #1386](https://github.com/clearml/clearml/pull/1386))
* Add support for `clearml-task` command line options `--force-no-requirements`,` --skip-repo-detection`, and `--skip-python-env-install`
* Allow calling the same pipeline step multiple times with inputs that originate from tasks/controller
* Add` Task.upload_artifact()` argument` sort_keys` to allow disabling sorting yaml/json keys when uploading artifacts
* Add Python annotations to all methods
* Update `pyjwt` constraint version
**Bug Fixes**
* Fix local file uploads without scheme ([ClearML GitHub issue #1313](https://github.com/clearml/clearml/pull/1313))
* Fix argument order mismatch in `PipelineController` ([ClearML GitHub PR #1406](https://github.com/clearml/clearml/pull/1406))
* Fix `_logger` property might be `None` in Session ([ClearML GitHub PR #1412](https://github.com/clearml/clearml/pull/1412))
* Fix unhandled `None` value in project IDs when listing all datasets ([ClearML GitHub PR #1413](https://github.com/clearml/clearml/pull/1413))
* Fix typo in config exception string ([ClearML GitHub PR #1418](https://github.com/clearml/clearml/pull/1418))
* Fix experiments are created twice during HPO ([ClearML GitHub issue #644](https://github.com/clearml/clearml/issues/644))
* Fix `clearml-task-run` HPO breaks up ([ClearML GitHub issue #1151](https://github.com/clearml/clearml/issues/1151))
* Fix oversized event reports cause subsequent events to be lost ([ClearML GitHub issue #1316](https://github.com/clearml/clearml/issues/1316))
* Fix downloading datasets with multiple parents might not work ([ClearML GitHub issue #1398](https://github.com/clearml/clearml/issues/1398))
* Fix GPU reporting fails to detect GPU when the `NVIDIA_VISIBLE_DEVICES` env var contains a directory reference
* Fix verify configuration option for S3 storage (boto3) is not used when testing buckets
* Fix `PipelineDecorator.component()` ignores `*args` and crashes with `**kwargs`
* Fix Pipelines run via `clearml-task` do not appear in the UI
* Fix task log URL print for API v2.31 should show `"/tasks/{}/output/log"`
* Fix tqdm upload/download reporting, remove warning
* Fix pipeline from CLI with no args fails
* Fix pillow constraint for `Python<=3.7`
* Fix requests constraint for `Python<3.8`

4
sidebars.js
View File

@ -328,10 +328,10 @@ module.exports = {
{
'Open Source':
[
'release_notes/sdk/open_source/ver_1_18',
'release_notes/sdk/open_source/ver_2_0',
{
'Older Versions': [
'release_notes/sdk/open_source/ver_1_17',
'release_notes/sdk/open_source/ver_1_18', 'release_notes/sdk/open_source/ver_1_17',
'release_notes/sdk/open_source/ver_1_16', 'release_notes/sdk/open_source/ver_1_15',
'release_notes/sdk/open_source/ver_1_14', 'release_notes/sdk/open_source/ver_1_13',
'release_notes/sdk/open_source/ver_1_12', 'release_notes/sdk/open_source/ver_1_11',