About the args in FedML parrot examples.

from the step3 in docs https://doc.fedml.ai/simulation/examples/sp_fedavg_mnist_lr_example.html, I am told to execute the following command to run the example code: python torch_fedavg_mnist_lr_one_line_example.py --cf fedml_config.yaml However, when I tried to modify the args in this YAML file (eg. set the using_gpu to true), I found that in the runtime the training is still based on the CPU. So I checked the code in fedml/lib/python3.7/site-packages/fedml/arguments.py, line 63, and I found a snippet of code as follows: `

    path_current_file = path.abspath(path.dirname(__file__))
    if training_type == "simulation" and comm_backend == "single_process":
        config_file = path.join(path_current_file, "config/simulation_sp/fedml_config.yaml")
        cmd_args.yaml_config_file = config_file
    elif training_type == "simulation" and comm_backend == "MPI":
        config_file = path.join(
            path_current_file, "config/simulaton_mpi/fedml_config.yaml"
        )
        cmd_args.yaml_config_file = config_file
    elif training_type == "cross_silo":
        pass
    elif training_type == "cross_device":
        pass
    else:
        pass

` It seems during the simulation, it does not matter how you set the YAML file, the default one would be loaded.

[chaoyanghe]

@JLU-Neal @mlpotter I’ve optimized the source code and solved your issues. Please pip install fedml==0.7.27

[chaoyanghe]

@JLU-Neal OK. The issue is super outdated and we iterated a lot in the past few months. Please switch to our new version later if you still need to use FedML.