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# context
# `prefect_ray.context`
Contexts to manage Ray clusters and tasks.
## Functions
### `remote_options`
```python theme={null}
remote_options(**new_remote_options: Dict[str, Any]) -> Generator[None, Dict[str, Any], None]
```
Context manager to add keyword arguments to Ray `@remote` calls
for task runs. If contexts are nested, new options are merged with options
in the outer context. If a key is present in both, the new option will be used.
**Examples:**
Use 4 CPUs and 2 GPUs for the `process` task:
```python theme={null}
from prefect import flow, task
from prefect_ray.task_runners import RayTaskRunner
from prefect_ray.context import remote_options
@task
def process(x):
return x + 1
@flow(task_runner=RayTaskRunner())
def my_flow():
# equivalent to setting @ray.remote(num_cpus=4, num_gpus=2)
with remote_options(num_cpus=4, num_gpus=2):
process.submit(42)
```
## Classes
### `RemoteOptionsContext`
The context for Ray remote\_options management.
**Attributes:**
* `current_remote_options`: A set of current remote\_options in the context.
**Methods:**
#### `get`
```python theme={null}
get(cls) -> 'RemoteOptionsContext'
```
Return an empty `RemoteOptionsContext`
instead of `None` if no context exists.
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