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Add comprehensive tests for tuners (merge into master) (#1681)
* Add comprehensive tests for tuners (#1570)
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,88 @@ | ||
| { | ||
| "choice_str": { | ||
| "_type": "choice", | ||
| "_value": ["cat", "dog", "elephant", "cow", "sheep", "panda"], | ||
| "fail": ["metis", "gp"] | ||
| }, | ||
| "choice_int": { | ||
| "_type": "choice", | ||
| "_value": [42, 43, -1] | ||
| }, | ||
| "choice_mixed": { | ||
| "_type": "choice", | ||
| "_value": [0.3, "cat", 1, null], | ||
| "fail": ["metis", "gp"] | ||
| }, | ||
| "choice_float": { | ||
| "_type": "choice", | ||
| "_value": [0.3, 1, 2.0] | ||
| }, | ||
| "choice_single": { | ||
| "_type": "choice", | ||
| "_value": [1] | ||
| }, | ||
| "randint_ok": { | ||
| "_type": "randint", | ||
| "_value": [-2, 3] | ||
| }, | ||
| "randint_single": { | ||
| "_type": "randint", | ||
| "_value": [10, 11] | ||
| }, | ||
| "randint_fail_equal": { | ||
| "_type": "randint", | ||
| "_value": [0, 0] | ||
| }, | ||
| "uniform_ok": { | ||
| "_type": "uniform", | ||
| "_value": [-1.0, 1.5] | ||
| }, | ||
| "uniform_equal": { | ||
| "_type": "uniform", | ||
| "_value": [99.9, 99.9] | ||
| }, | ||
| "quniform_ok": { | ||
| "_type": "quniform", | ||
| "_value": [0.0, 10.0, 2.5] | ||
| }, | ||
| "quniform_clip": { | ||
| "_type": "quniform", | ||
| "_value": [2.0, 10.0, 5.0] | ||
| }, | ||
| "quniform_clip_2": { | ||
| "_type": "quniform", | ||
| "_value": [-5.5, -0.5, 6] | ||
| }, | ||
| "loguniform_ok": { | ||
| "_type": "loguniform", | ||
| "_value": [0.001, 100] | ||
| }, | ||
| "loguniform_equal": { | ||
| "_type": "loguniform", | ||
| "_value": [1, 1] | ||
| }, | ||
| "qloguniform_ok": { | ||
| "_type": "qloguniform", | ||
| "_value": [0.001, 100, 1] | ||
| }, | ||
| "qloguniform_equal": { | ||
| "_type": "qloguniform", | ||
| "_value": [2, 2, 1] | ||
| }, | ||
| "normal_ok": { | ||
| "_type": "normal", | ||
| "_value": [-1.0, 5.0] | ||
| }, | ||
| "qnormal_ok": { | ||
| "_type": "qnormal", | ||
| "_value": [-1.5, 5.0, 0.1] | ||
| }, | ||
| "lognormal_ok": { | ||
| "_type": "lognormal", | ||
| "_value": [-1.0, 5.0] | ||
| }, | ||
| "qlognormal_ok": { | ||
| "_type": "qlognormal", | ||
| "_value": [-1.5, 5.0, 0.1] | ||
| } | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,125 @@ | ||
| # Copyright (c) Microsoft Corporation. All rights reserved. | ||
| # | ||
| # MIT License | ||
| # | ||
| # Permission is hereby granted, free of charge, to any person obtaining a copy of this software and | ||
| # associated documentation files (the "Software"), to deal in the Software without restriction, | ||
| # including without limitation the rights to use, copy, modify, merge, publish, distribute, | ||
| # sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is | ||
| # furnished to do so, subject to the following conditions: | ||
| # | ||
| # The above copyright notice and this permission notice shall be included in all copies or | ||
| # substantial portions of the Software. | ||
| # | ||
| # THE SOFTWARE IS PROVIDED *AS IS*, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT | ||
| # NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND | ||
| # NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, | ||
| # DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT | ||
| # OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. | ||
| # ================================================================================================== | ||
|
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| import json | ||
| from io import BytesIO | ||
| from unittest import TestCase, main | ||
|
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| import nni.protocol | ||
| from nni.msg_dispatcher import MsgDispatcher | ||
| from nni.protocol import CommandType, send, receive | ||
| from nni.tuner import Tuner | ||
| from nni.utils import extract_scalar_reward | ||
|
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| class NaiveTuner(Tuner): | ||
| def __init__(self): | ||
| self.param = 0 | ||
| self.trial_results = [] | ||
| self.search_space = None | ||
| self._accept_customized_trials() | ||
|
|
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| def generate_parameters(self, parameter_id, **kwargs): | ||
| # report Tuner's internal states to generated parameters, | ||
| # so we don't need to pause the main loop | ||
| self.param += 2 | ||
| return { | ||
| 'param': self.param, | ||
| 'trial_results': self.trial_results, | ||
| 'search_space': self.search_space | ||
| } | ||
|
|
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| def receive_trial_result(self, parameter_id, parameters, value, **kwargs): | ||
| reward = extract_scalar_reward(value) | ||
| self.trial_results.append((parameter_id, parameters['param'], reward, kwargs.get("customized"))) | ||
|
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| def update_search_space(self, search_space): | ||
| self.search_space = search_space | ||
|
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|
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| _in_buf = BytesIO() | ||
| _out_buf = BytesIO() | ||
|
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|
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| def _reverse_io(): | ||
| _in_buf.seek(0) | ||
| _out_buf.seek(0) | ||
| nni.protocol._out_file = _in_buf | ||
| nni.protocol._in_file = _out_buf | ||
|
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| def _restore_io(): | ||
| _in_buf.seek(0) | ||
| _out_buf.seek(0) | ||
| nni.protocol._in_file = _in_buf | ||
| nni.protocol._out_file = _out_buf | ||
|
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| class MsgDispatcherTestCase(TestCase): | ||
| def test_msg_dispatcher(self): | ||
| _reverse_io() # now we are sending to Tuner's incoming stream | ||
| send(CommandType.RequestTrialJobs, '2') | ||
| send(CommandType.ReportMetricData, '{"parameter_id":0,"type":"PERIODICAL","value":10}') | ||
| send(CommandType.ReportMetricData, '{"parameter_id":1,"type":"FINAL","value":11}') | ||
| send(CommandType.UpdateSearchSpace, '{"name":"SS0"}') | ||
| send(CommandType.AddCustomizedTrialJob, '{"param":-1}') | ||
| send(CommandType.ReportMetricData, '{"parameter_id":2,"type":"FINAL","value":22}') | ||
| send(CommandType.RequestTrialJobs, '1') | ||
| send(CommandType.KillTrialJob, 'null') | ||
| _restore_io() | ||
|
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| tuner = NaiveTuner() | ||
| dispatcher = MsgDispatcher(tuner) | ||
| nni.msg_dispatcher_base._worker_fast_exit_on_terminate = False | ||
|
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| dispatcher.run() | ||
| e = dispatcher.worker_exceptions[0] | ||
| self.assertIs(type(e), AssertionError) | ||
| self.assertEqual(e.args[0], 'Unsupported command: CommandType.KillTrialJob') | ||
|
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| _reverse_io() # now we are receiving from Tuner's outgoing stream | ||
| self._assert_params(0, 2, [], None) | ||
| self._assert_params(1, 4, [], None) | ||
|
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| command, data = receive() # this one is customized | ||
| data = json.loads(data) | ||
| self.assertIs(command, CommandType.NewTrialJob) | ||
| self.assertEqual(data['parameter_id'], 2) | ||
| self.assertEqual(data['parameter_source'], 'customized') | ||
| self.assertEqual(data['parameters'], {'param': -1}) | ||
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| self._assert_params(3, 6, [[1, 4, 11, False], [2, -1, 22, True]], {'name': 'SS0'}) | ||
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| self.assertEqual(len(_out_buf.read()), 0) # no more commands | ||
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| def _assert_params(self, parameter_id, param, trial_results, search_space): | ||
| command, data = receive() | ||
| self.assertIs(command, CommandType.NewTrialJob) | ||
| data = json.loads(data) | ||
| self.assertEqual(data['parameter_id'], parameter_id) | ||
| self.assertEqual(data['parameter_source'], 'algorithm') | ||
| self.assertEqual(data['parameters']['param'], param) | ||
| self.assertEqual(data['parameters']['trial_results'], trial_results) | ||
| self.assertEqual(data['parameters']['search_space'], search_space) | ||
|
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| if __name__ == '__main__': | ||
| main() |
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