changes following review

docs/tutorial.rst

@@ -308,7 +308,7 @@ For the compute package we need to compress the *client* folder as .tar.gz file.
 
 .. code-block:: bash
 
-    tar -czvf package.tar.gz client
+    tar -czvf package.tgz client
 
 
 This file can then be uploaded to the FEDn network using the FEDn UI or the :py:mod:`fedn.network.api.client`.

examples/async-simulation/README.md

@@ -31,7 +31,7 @@ pip install -r requirements.txt
 
 Create the compute package and a seed model that you will be asked to upload in the next step.
 ```
-tar -cvzf package.tgz
+tar -czvf package.tgz client
 ```
 
 ```
@@ -50,4 +50,4 @@ See 'Experiments.pynb' or 'launch_client.py' to set the package and seed model.
 See 'Experiment.ipynb'. 
 
 ## Clean up
-You can clean up by running `docker-compose down`.
+You can clean up by running `docker-compose down -v`.

examples/async-simulation/launch_clients.py

@@ -2,7 +2,7 @@
 
 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
+are able to resolve the name "combiner" to 127.0.0.1
 
 One way to accomplish this is to edit your /etc/host,
 adding the line:

fedn/fedn/dashboard/templates/context.html

@@ -12,7 +12,7 @@ <h6 class="card-subtitle text-muted">{{ message }}</h6>
                 <label for="helper" class="col-sm-2 col-form-label">Helper:</label>
                 <div class="col-sm-10">
                     <select class="form-control" id="helper" name="helper" required>
-                        <option value='numpyheper'>numpyhelper</option>
+                        <option value='numpyhelper'>numpyhelper</option>
                     </select>
                 </div>
 

fedn/fedn/network/controller/control.py

@@ -338,7 +338,7 @@ def reduce(self, combiners):
                 data = self.model_repository.get_model(model_id)
                 meta['time_fetch_model'] += (time.time() - tic)
             except Exception as e:
-                logger.info("Failed to fetch model from model repository {}: {}".format(name, e))
+                logger.error("Failed to fetch model from model repository {}: {}".format(name, e))
                 data = None
 
             if data is not None: