"failed to connect to all addresses"

[lepangdan]

##"failed to connect to all addresses"

hi, I have tried to run the example quickstart_pytorch, and encounter a bug shown as follows,

Traceback (most recent call last):
  File "client.py", line 106, in <module>
    fl.client.start_numpy_client(server_address="[::]:8081", client=FlowerClient())
  File "/opt/conda/envs/ml-federated-3.7.12/lib/python3.7/site-packages/flwr/client/app.py", line 115, in start_numpy_client
    grpc_max_message_length=grpc_max_message_length,
  File "/opt/conda/envs/ml-federated-3.7.12/lib/python3.7/site-packages/flwr/client/app.py", line 64, in start_client
    server_message = receive()
  File "/opt/conda/envs/ml-federated-3.7.12/lib/python3.7/site-packages/flwr/client/grpc_client/connection.py", line 60, in <lambda>
    receive: Callable[[], ServerMessage] = lambda: next(server_message_iterator)
  File "/opt/conda/envs/ml-federated-3.7.12/lib/python3.7/site-packages/grpc/_channel.py", line 426, in __next__
    return self._next()
  File "/opt/conda/envs/ml-federated-3.7.12/lib/python3.7/site-packages/grpc/_channel.py", line 809, in _next
    raise self
grpc._channel._MultiThreadedRendezvous: <_MultiThreadedRendezvous of RPC that terminated with:
        status = StatusCode.UNAVAILABLE
        details = "failed to connect to all addresses"
        debug_error_string = "{"created":"@1652340915.644527504","description":"Failed to pick subchannel","file":"src/core/ext/filters/client_channel/client_channel.cc","file_line":3128,"referenced_errors":[{"created":"@1652340915.644526921","description":"failed to connect to all addresses","file":"src/core/lib/transport/error_utils.cc","file_line":163,"grpc_status":14}]}"
>

please help

[ZHTushar23]

Having the same issue with Raspberry Pi 400. "failed to connect to all addresses".

[MKZuziak]

Hi lepangdan,

I had the same issue when I started to experiment with the Flower framework. As far as I've discovered, the issue may be arising due to the grpc insecure connection. May I ask about the environment in which you are trying to perform the test? Especially the OS.

What I may suggest and what has worked for me is installing WSL2 (if you are on Windows 10/11) and following the instructions posted in the [https://github.com/adap/flower/tree/main/examples/quickstart_tensorflow](relevant folder in the flower's repository), so:

• clone the repository;
• resolve dependencies through poetry;
• modify the code if needed.

Generally, the poetry-built environment on WSL2 should allow you to use Flower without running into Failed to pick subchannel error.

You may be also interested in checking ticket no. https://github.com/adap/flower/issues/537 and https://github.com/adap/flower/discussions/757

If you have more time on hand, you can also try to create a rework around that error (please refer to the GRPC core documentation ) - the issue, as I've said before, may be connected to the Windows 10/11 firewall.

[EliasBrohammer]

I had this issue too, but found a way to fix it.
My setup looks like this:

1. Docker image with ubuntu 20.04 with an exposed port (like 8080)
2. open three container of the image
3. in my server script i get the ip address via

   # server.py
   import socket
   ip_address = socket.gethostbyname((socket.gethostname()))
   server_address=ip_address + ':8080'
   
   # do some stuff
   
   fl.server.start_server(server_address=server_address, .... )

4. in my client script I set the ip address of the server

   # client.py
   ip_address = '0.0.0.0'  # here you should write the server ip-address
   server_address=ip_address + ':8080'
   
   # do some stuff
   
   fl.client.start_numpy_client(ip_address, client=MnistClient())

I'm using the sklearn example.
Hopefully this helps someone.