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@ -180,10 +180,10 @@ NVIDIA_VISIBLE_DEVICES=0 trains-agent daemon --queue default &
NVIDIA_VISIBLE_DEVICES=1 trains-agent daemon --queue default &
```
Example: spin two agents, with two gpu's per agent:
Example: spin two agents, pulling from dedicated `dual_gpu` queue, two gpu's per agent
```bash
NVIDIA_VISIBLE_DEVICES=0,1 trains-agent daemon --queue default &
NVIDIA_VISIBLE_DEVICES=2,3 trains-agent daemon --queue default &
NVIDIA_VISIBLE_DEVICES=0,1 trains-agent daemon --queue dual_gpu &
NVIDIA_VISIBLE_DEVICES=2,3 trains-agent daemon --queue dual_gpu &
```
#### Starting the TRAINS Agent in docker mode
@ -198,16 +198,16 @@ For actual service mode, all the stdout will be stored automatically into a file
trains-agent daemon --queue default --docker
```
Example: spin two agents, one per gpu on the same machine:
Example: spin two agents, one per gpu on the same machine, with default nvidia/cuda docker:
```bash
NVIDIA_VISIBLE_DEVICES=0 trains-agent daemon --queue default --docker &
NVIDIA_VISIBLE_DEVICES=1 trains-agent daemon --queue default --docker &
NVIDIA_VISIBLE_DEVICES=0 trains-agent daemon --queue default --docker nvidia/cuda &
NVIDIA_VISIBLE_DEVICES=1 trains-agent daemon --queue default --docker nvidia/cuda &
```
Example: spin two agents, with two gpu's per agent:
Example: spin two agents, pulling from dedicated `dual_gpu` queue, two gpu's per agent, with default nvidia/cuda docker:
```bash
NVIDIA_VISIBLE_DEVICES=0,1 trains-agent daemon --queue default --docker &
NVIDIA_VISIBLE_DEVICES=2,3 trains-agent daemon --queue default --docker &
NVIDIA_VISIBLE_DEVICES=0,1 trains-agent daemon --queue dual_gpu --docker nvidia/cuda &
NVIDIA_VISIBLE_DEVICES=2,3 trains-agent daemon --queue dual_gpu --docker nvidia/cuda &
```
#### Starting the TRAINS Agent - Priority Queues
@ -220,7 +220,9 @@ trains-agent daemon --queue important_jobs default
```
The **TRAINS agent** will first try to pull jobs from the `important_jobs` queue, only then it will fetch a job from the `default` queue.
# How do I create an experiment on the TRAINS server? <a name="from-scratch"></a>
Adding queues, managing job order within a queue and moving jobs between queues, is available using the Web UI, see example on our [open server](https://demoapp.trains.allegro.ai/workers-and-queues/queues)
# How do I create an experiment on the TRAINS server? <a name="from-scratch"></a>
* Integrate [TRAINS](https://github.com/allegroai/trains) with your code
* Execute the code on your machine (Manually / PyCharm / Jupyter Notebook)
* As your code is running, **TRAINS** creates an experiment logging all the necessary execution information: