### Description

Hello, I am a new Airflow user. I am requesting a feature in which the airflow context (containing task instance, etc.) be available inside of functions decorated by `airflow.decorators.task.sensor`.

### Use case/motivation

I have noticed that when using the `airflow.decorators.task` decorator, one can access items from the context (such as the task instance) by using `**kwargs` or keyword arguments in the decorated function. But I have discovered that the same is not true for the `airflow.decorators.task.sensor` decorator. I'm not sure if this is a bug or intentional, but it would be very useful to be able to access the context normally from functions decorated by `task.sensor`.

I believe this may have been an oversight. The `DecoratedSensorOperator` class is a child class of `PythonSensor`:

https://github.com/apache/airflow/blob/1fbfd312d9d7e28e66f6ba5274421a96560fb7ba/airflow/decorators/sensor.py#L28

This `DecoratedSensorOperator` class overrides `poke`, but does not incorporate the passed in `Context` object before calling the decorated function:

https://github.com/apache/airflow/blob/1fbfd312d9d7e28e66f6ba5274421a96560fb7ba/airflow/decorators/sensor.py#L60-L61

This is in contrast to the `PythonSensor`, whose `poke` method merges the context with the existing `op_kwargs`:

https://github.com/apache/airflow/blob/1fbfd312d9d7e28e66f6ba5274421a96560fb7ba/airflow/sensors/python.py#L68-L77

This seems like an easy fix, and I'd be happy to submit a pull request. But I figured I'd start with a feature request since I'm new to the open source community.

### Related issues

_No response_

### Are you willing to submit a PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

#
#
from __future__ import annotations
from typing import Callable, Sequence
from airflow.decorators.base import TaskDecorator, get_unique_task_id, task_decorator_factory
from airflow.models.taskinstance import Context
from airflow.sensors.base import PokeReturnValue
from airflow.sensors.python import PythonSensor
class DecoratedSensorOperator(PythonSensor):
    """
    Wraps a Python callable and captures args/kwargs when called for execution.
    :param python_callable: A reference to an object that is callable
    :param task_id: task Id
    :param op_args: a list of positional arguments that will get unpacked when
        calling your callable (templated)
    :param op_kwargs: a dictionary of keyword arguments that will get unpacked
        in your function (templated)
    :param kwargs_to_upstream: For certain operators, we might need to upstream certain arguments
        that would otherwise be absorbed by the DecoratedOperator (for example python_callable for the
        PythonOperator). This gives a user the option to upstream kwargs as needed.
    """
    template_fields: Sequence[str] = ("op_args", "op_kwargs")
    template_fields_renderers: dict[str, str] = {"op_args": "py", "op_kwargs": "py"}
    
    
    shallow_copy_attrs: Sequence[str] = ("python_callable",)
    def __init__(