Cleaned up new example/test

examples/async-simulation/.gitignore

@@ -0,0 +1,6 @@
+data
+*.npz
+*.tgz
+*.tar.gz
+.async-simulation
+client.yaml

examples/async-simulation/README.md

@@ -11,51 +11,37 @@ This example is intended as a test for asynchronous clients.
 Clone FEDn and locate into this directory.
 ```sh
 git clone https://github.com/scaleoutsystems/fedn.git
-cd fedn/examples/mnist-pytorch
+cd fedn/examples/async-simulation
 ```
 
 ### Preparing the environment, the local data, the compute package and seed model
-Start by initializing a virtual enviroment with all of the required dependencies.
-```
-bin/init_venv.sh
-```
 
-Then, to get the data you can run the following script.
-```
-bin/get_data
-```
+Install FEDn and dependencies (we recommend using a virtual environment):
 
-The next command splits the data in 2 parts for the clients.
 ```
-bin/split_data
+pip install -e ../../fedn
+pip install -r requirements.txt
 ```
-> **Note**: run with `--n_splits=N` to split in *N* parts.
 
 Create the compute package and a seed model that you will be asked to upload in the next step.
 ```
-bin/build.sh
+tar -cvzf package.tgz
 ```
-> The files location will be `package/package.tgz` and `seed.npz`.
 
-### Deploy FEDn 
-Now we are ready to deploy FEDn with `docker-compose`.
 ```
-docker-compose -f ../../docker-compose.yaml up -d minio mongo mongo-express reducer combiner
+python client/entrypoint init_seed
 ```
 
-### Initialize the federated model 
-Now navigate to http://localhost:8090 to see the reducer UI. You will be asked to upload the compute package and the seed model that you created in the previous step. Make sure to choose the "PyTorch" helper.
+### Deploy FEDn and two clients
+docker-compose -f ../../docker-compose.yaml -f docker-compose.override.yaml up 
 
-### Attach clients 
-To attach clients to the network, use the docker-compose.override.yaml template to start 2 clients: 
+### Initialize the federated model 
+See 'Experiments.pynb' or 'launch_client.py' to set the package and seed model.
 
-```
-docker-compose -f ../../docker-compose.yaml -f docker-compose.override.yaml up client 
-```
 > **Note**: run with `--scale client=N` to start *N* clients.
 
 ### Run federated training 
-Finally, you can start the experiment from the "control" tab of the UI. 
+See 'Experiment.ipynb'. 
 
 ## Clean up
 You can clean up by running `docker-compose down`.

examples/async-simulation/init_fedn.py

@@ -1,8 +1,8 @@
 from fedn import APIClient
 
-DISCOVER_HOST = '54.208.105.152'
+DISCOVER_HOST = '127.0.0.1'
 DISCOVER_PORT = 8092
 
 client = APIClient(DISCOVER_HOST, DISCOVER_PORT)
-client.set_package('package.tar.gz', 'numpyarrayhelper')
+client.set_package('package.tgz', 'numpyhelper')
 client.set_initial_model('seed.npz')

examples/async-simulation/launch_clients.py

@@ -1,24 +1,41 @@
+"""This scripts starts N_CLIENTS using the SDK.
+
+If you are running with a local deploy of FEDn
+using docker compose, you need to make sure that clients
+are able to resolver the name "combiner" to 127.0.0.1
+
+One way to accomplish this is to edit your /etc/host,
+adding the line:
+
+combiner    127.0.0.1
+
+"""
+
+
 import copy
 import time
 
 from fedn.network.clients.client import Client
 
 DISCOVER_HOST = '127.0.0.1'
 DISCOVER_PORT = 8092
-N_CLIENTS = 1
+N_CLIENTS = 5
+CLIENTS_AVAILABLE_TIME = 120
 
 config = {'discover_host': DISCOVER_HOST, 'discover_port': DISCOVER_PORT, 'token': None, 'name': 'testclient',
           'client_id': 1, 'remote_compute_context': True, 'force_ssl': False, 'dry_run': False, 'secure': False,
           'preshared_cert': False, 'verify': False, 'preferred_combiner': False,
           'validator': True, 'trainer': True, 'init': None, 'logfile': 'test.log', 'heartbeat_interval': 2,
           'reconnect_after_missed_heartbeat': 30}
 
+# Start up N_CLIENTS clients
 clients = []
 for i in range(N_CLIENTS):
     config_i = copy.deepcopy(config)
     config['name'] = 'client{}'.format(i)
     clients.append(Client(config))
 
-time.sleep(120)
+# Disconnect clients after some time
+time.sleep(CLIENTS_AVAILABLE_TIME)
 for client in clients:
     client._detach()

examples/mnist-keras/bin/init_venv_macm1.sh

@@ -0,0 +1,10 @@
+#!/bin/bash
+set -e
+
+# Init venv
+python3 -m venv .mnist-keras
+
+# Pip deps
+.mnist-keras/bin/pip install --upgrade pip
+.mnist-keras/bin/pip install -e ../../fedn
+.mnist-keras/bin/pip install -r requirements-macos.txt

examples/mnist-keras/requirements-macos.txt

@@ -0,0 +1,4 @@
+tensorflow-macos
+tensorflow-metal 
+fire==0.3.1
+docker==5.0.2