**What happened**:

With the new Backport providers, when calling `DataflowCreatePythonJobOperator` with an empty `py_rerquirments` Dataflow commands always launch inside a virtualenv.

**What you expected to happen**:

The Dataflow command should run locally.


airflow/providers/google/cloud/operators/dataflow.py
self.hook = DataflowHook(
            gcp_conn_id=self.gcp_conn_id,
            delegate_to=self.delegate_to,
            poll_sleep=self.poll_sleep
        )
        def set_current_job_id(job_id):
            self.job_id = job_id
        options = self.dataflow_default_options
        options.update(self.options)
        job = self.hook.start_template_dataflow(
            job_name=self.job_name,
            variables=options,
            parameters=self.parameters,
            dataflow_template=self.template,
            on_new_job_id_callback=set_current_job_id,
            project_id=self.project_id,
            location=self.location
        )
        return job
    def on_kill(self) -> None:
        self.log.info("On kill.")
        if self.job_id:
            self.hook.cancel_job(job_id=self.job_id, project_id=self.project_id)
class DataflowCreatePythonJobOperator(BaseOperator):
    """
    Launching Cloud Dataflow jobs written in python. Note that both
    dataflow_default_options and options will be merged to specify pipeline
    execution parameter, and dataflow_default_options is expected to save