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License: MIT License
Distributed Task Execution Framework with Genetic Algorithm for Neural Network Architecture Search
License: MIT License
We need an installation script or documentation of the steps to install e.g. the distributed evolver.
All Python modules must be installed via:
pip install generic/...
Developers may want to use --editable
within the above command.
Sometimes individual frontend does not load when navigating through genealogy
Exceptions that occur in DiTEF Workers should be handed through back to the Task Producers in a standardized way to be handled there centrally.
What it says
The genetic algorithm UI currently doesn't show any error messages when requests to the server fail.
I propose some kind popup message when a user interaction causes a failing request and a status message box (maybe below the update interval setting) at the top when the last periodic refresh request failed.
Cannot click on "Remove" when UI updates in population list
Allow to set --population-tasks
via algorithm's configuration over the web frontend.
While leaving the task-worker
running for a long time, I got this error message (unknown cause):
Traceback (most recent call last):
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/urllib3/connectionpool.py", line 445, in _make_request
six.raise_from(e, None)
File "<string>", line 3, in raise_from
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/urllib3/connectionpool.py", line 440, in _make_request
httplib_response = conn.getresponse()
File "/usr/lib/python3.8/http/client.py", line 1347, in getresponse
response.begin()
File "/usr/lib/python3.8/http/client.py", line 307, in begin
version, status, reason = self._read_status()
File "/usr/lib/python3.8/http/client.py", line 268, in _read_status
line = str(self.fp.readline(_MAXLINE + 1), "iso-8859-1")
File "/usr/lib/python3.8/socket.py", line 669, in readinto
return self._sock.recv_into(b)
socket.timeout: timed out
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/requests/adapters.py", line 439, in send
resp = conn.urlopen(
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/urllib3/connectionpool.py", line 755, in urlopen
retries = retries.increment(
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/urllib3/util/retry.py", line 531, in increment
raise six.reraise(type(error), error, _stacktrace)
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/urllib3/packages/six.py", line 735, in reraise
raise value
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/urllib3/connectionpool.py", line 699, in urlopen
httplib_response = self._make_request(
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/urllib3/connectionpool.py", line 447, in _make_request
self._raise_timeout(err=e, url=url, timeout_value=read_timeout)
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/urllib3/connectionpool.py", line 336, in _raise_timeout
raise ReadTimeoutError(
urllib3.exceptions.ReadTimeoutError: HTTPConnectionPool(host='localhost', port=8080): Read timed out. (read timeout=1)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "nao/tools/machine-learning/venv/bin/task-worker", line 8, in <module>
sys.exit(main())
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/click/core.py", line 829, in __call__
return self.main(*args, **kwargs)
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/click/core.py", line 782, in main
rv = self.invoke(ctx)
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/click/core.py", line 1066, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/click/core.py", line 610, in invoke
return callback(*args, **kwargs)
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/task_worker/__init__.py", line 141, in main
result_response = requests.post(
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/requests/api.py", line 119, in post
return request('post', url, data=data, json=json, **kwargs)
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/requests/api.py", line 61, in request
return session.request(method=method, url=url, **kwargs)
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/requests/sessions.py", line 542, in request
resp = self.send(prep, **send_kwargs)
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/requests/sessions.py", line 655, in send
r = adapter.send(request, **kwargs)
File "nao/tools/machine-learning/venv/lib/python3.8/site-packages/requests/adapters.py", line 529, in send
raise ReadTimeout(e, request=request)
requests.exceptions.ReadTimeout: HTTPConnectionPool(host='localhost', port=8080): Read timed out. (read timeout=1)
The task router should currently not be hosted publicly because of 1. the unencrypted HTTP server, 2. missing authentication, 3. missing hardening
Possible solutions for encryption and authentication: SSH, mutual TLS, Let's Encrypt, own PKI
We want to have a UI for the router internals (queue status, evaluator status, etc.). One idea is to expose an API which e.g. the genetic algorithm can consume to show its own specialized UI.
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