@@ -95,20 +95,15 @@ You can deploy agents on your varying compute resources as long as it has access
...
@@ -95,20 +95,15 @@ You can deploy agents on your varying compute resources as long as it has access
- export S3_SECRET_KEY=s3 secret key
- export S3_SECRET_KEY=s3 secret key
6. deploy agent and let it listen to a queue (for example: test). The following code also creates that queue and service mode makes sure that the agent can run multiple different jobs (needed for pipelines). See [here](https://clear.ml/docs/latest/docs/clearml_agent/#deployment) for more options. We also detach to let the agent run in the background.
6. deploy agent and let it listen to a queue (for example: test). The following code also creates that queue and service mode makes sure that the agent can run multiple different jobs (needed for pipelines). See [here](https://clear.ml/docs/latest/docs/clearml_agent/#deployment) for more options. We also detach to let the agent run in the background.
- clearml-agent daemon --queue test --create-queue --service-mode --detach
- clearml-agent daemon --queue test --create-queue --service-mode --detach
- For specific GPU units add --gpus flag (example: --gpus 0)
- To deploy the ClearML with a GPU allocated add the --gpus argument
- Install CUDA https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html
- install pytorch with cuda support https://pytorch.org/get-started/locally with Cuda support
- use cuda as device in script
7. [optional] We can also lock our terminal in Linux so nobody can read the environment variables.
7. [optional] We can also lock our terminal in Linux so nobody can read the environment variables.
- sudo screen
- sudo screen
- Press ctrl+a+x and input password
- Press ctrl+a+x and input password
- To reopen terminal, input password
- To reopen terminal, input password
To deploy the ClearML with a GPU allocated add the --gpus argument
- Install CUDA https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html
- install pytorch with cuda support https://pytorch.org/get-started/locally with Cuda support
- use cuda as device in script
- clearml-agent daemon --queue default --gpus 0
## Example task run
## Example task run
The task run can be used for running a single script. It runs locally by default, but if the **remote_queue** argument is input, the first epoch will run locally, but following epochs will run by the agent listening to the remote queue.
The task run can be used for running a single script. It runs locally by default, but if the **remote_queue** argument is input, the first epoch will run locally, but following epochs will run by the agent listening to the remote queue.
