Move validation logic from `_run_trial` to `study.tell` #3144

himkt · 2021-12-03T13:32:07Z

This PR makes the behavior of optuna tell consistent with study.optimize when an objective value is nan or a list containing nan. Inside study.optimize, the case observing nan as an objective values is considered as a special case that Optuna doesn't raise an exception and make trial.state failed and show a log message. For Optuna CLI, I think it would be natural to behave as in study.optimize.

optuna/optuna/study/_optimize.py

Lines 224 to 230 in cf33d05

    
           values, values_conversion_failure_message = _check_and_convert_to_values( 
        
               len(study.directions), value_or_values, trial.number 
        
           ) 
        
           if values_conversion_failure_message is not None: 
        
               state = TrialState.FAIL 
        
           else: 
        
               state = TrialState.COMPLETE

optuna/optuna/study/_optimize.py

Lines 256 to 257 in cf33d05

    
           elif values_conversion_failure_message is not None: 
        
               _logger.warning(values_conversion_failure_message)

Motivation

Make optuna tell consistent with study.optimize
- One may think optuna tell should only be consistent with study.tell . Any feedback is highly appreciated
  - If so, we should guide users to run optuna tell ... --state fail when they observe nan
When nan is passed to optuna tell, Optuna makes a trial state FAILED

Description of the changes

abf53a6 Add test case
84413f7 Invoke _check_and_convert_to_values in _Tell.take_action

Behavior

> optuna create-study --storage sqlite:///example.db --study-name test
[I 2021-12-03 22:09:54,814] A new study created in RDB with name: test
test

> optuna ask --storage sqlite:///sample.db --study-name test
/home/himkt/work/github.com/himkt/optuna/optuna/cli.py:736: ExperimentalWarning: 'ask' is an experimental CLI command. The interface can change in the future.
  warnings.warn(
[I 2021-12-03 22:10:01,697] A new study created in RDB with name: test
[I 2021-12-03 22:10:01,715] Asked trial 0 with parameters {}.
{"number": 0, "params": {}}

> optuna tell --study-name test --storage sqlite:///sample.db --trial-number 0 --values nan
/home/himkt/work/github.com/himkt/optuna/optuna/cli.py:852: ExperimentalWarning: 'tell' is an experimental CLI command. The interface can change in the future.
  warnings.warn(
[I 2021-12-03 22:10:09,387] Told trial 0 with values None and state TrialState.FAIL.
[W 2021-12-03 22:10:09,387] Trial 0 failed, because the objective function returned nan.

>>> import optuna
op>>> study = optuna.load_study(storage="sqlite:///sample.db", study_name="test")
>>> study.get_trials()
[FrozenTrial(number=0, values=None, datetime_start=datetime.datetime(2021, 12, 3, 22, 10, 1, 708719), datetime_complete=datetime.datetime(2021, 12, 3, 22, 10, 9, 371719), params={}, distributions={}, user_attrs={}, system_attrs={}, intermediate_values={}, trial_id=1, state=TrialState.FAIL, value=None)]
>>>

codecov-commenter · 2021-12-03T14:01:58Z

Codecov Report

Merging #3144 (921b9be) into master (6fd45a6) will increase coverage by 0.03%.
The diff coverage is 95.31%.

@@            Coverage Diff             @@
##           master    #3144      +/-   ##
==========================================
+ Coverage   91.83%   91.86%   +0.03%     
==========================================
  Files         156      157       +1     
  Lines       12292    12316      +24     
==========================================
+ Hits        11288    11314      +26     
+ Misses       1004     1002       -2

Impacted Files	Coverage Δ
optuna/cli.py	`20.47% <0.00%> (-0.10%)`	⬇️
optuna/multi_objective/trial.py	`91.03% <ø> (-0.19%)`	⬇️
optuna/study/_tell.py	`97.93% <97.93%> (ø)`
optuna/multi_objective/study.py	`97.58% <100.00%> (+0.03%)`	⬆️
optuna/study/_optimize.py	`98.63% <100.00%> (+0.32%)`	⬆️
optuna/study/study.py	`96.15% <100.00%> (+0.13%)`	⬆️
optuna/samplers/nsgaii/_sampler.py	`95.33% <0.00%> (-0.85%)`	⬇️
optuna/storages/__init__.py	`100.00% <0.00%> (ø)`
optuna/visualization/_utils.py	`98.46% <0.00%> (ø)`
optuna/visualization/_contour.py	`98.11% <0.00%> (ø)`
... and 2 more

📣 Codecov can now indicate which changes are the most critical in Pull Requests. Learn more

himkt · 2021-12-07T15:09:09Z

@g-votte and @hvy suggested to move the validation logic inside Study.tell. I read the code of tell and I'm not sure whether we should do or not. In the current logic of Study.tell, state is immutable and I feel this design is clean. But if we won't change this design, Study.tell and CLI optuna tell would be different or we would force users to handle nan values on their own.

optuna/optuna/study/study.py

Lines 577 to 659 in 45caa72

    
           if not isinstance(trial, (trial_module.Trial, int)): 
        
               raise TypeError("Trial must be a trial object or trial number.") 
        
           if state == TrialState.COMPLETE: 
        
               if values is None: 
        
                   raise ValueError( 
        
                       "No values were told. Values are required when state is TrialState.COMPLETE." 
        
                   ) 
        
           elif state in (TrialState.PRUNED, TrialState.FAIL): 
        
               if values is not None: 
        
                   raise ValueError( 
        
                       "Values were told. Values cannot be specified when state is " 
        
                       "TrialState.PRUNED or TrialState.FAIL." 
        
                   ) 
        
           else: 
        
               raise ValueError(f"Cannot tell with state {state}.") 
        
           if isinstance(trial, trial_module.Trial): 
        
               trial_number = trial.number 
        
               trial_id = trial._trial_id 
        
           elif isinstance(trial, int): 
        
               trial_number = trial 
        
               try: 
        
                   trial_id = self._storage.get_trial_id_from_study_id_trial_number( 
        
                       self._study_id, trial_number 
        
                   ) 
        
               except NotImplementedError as e: 
        
                   warnings.warn( 
        
                       "Study.tell may be slow because the trial was represented by its number but " 
        
                       f"the storage {self._storage.__class__.__name__} does not implement the " 
        
                       "method required to map numbers back. Please provide the trial object " 
        
                       "to avoid performance degradation." 
        
                   ) 
        
                   trials = self.get_trials(deepcopy=False) 
        
                   if len(trials) <= trial_number: 
        
                       raise ValueError( 
        
                           f"Cannot tell for trial with number {trial_number} since it has not been " 
        
                           "created." 
        
                       ) from e 
        
                   trial_id = trials[trial_number]._trial_id 
        
               except KeyError as e: 
        
                   raise ValueError( 
        
                       f"Cannot tell for trial with number {trial_number} since it has not been " 
        
                       "created." 
        
                   ) from e 
        
           else: 
        
               assert False, "Should not reach." 
        
           frozen_trial = self._storage.get_trial(trial_id) 
        
           if state == TrialState.PRUNED: 
        
               # Register the last intermediate value if present as the value of the trial. 
        
               # TODO(hvy): Whether a pruned trials should have an actual value can be discussed. 
        
               assert values is None 
        
               last_step = frozen_trial.last_step 
        
               if last_step is not None: 
        
                   values = [frozen_trial.intermediate_values[last_step]] 
        
           if values is not None: 
        
               values, values_conversion_failure_message = _check_and_convert_to_values( 
        
                   len(self.directions), values, trial_number 
        
               ) 
        
               # When called from `Study.optimize` and `state` is pruned, the given `values` contains 
        
               # the intermediate value with the largest step so far. In this case, the value is 
        
               # allowed to be NaN and errors should not be raised. 
        
               if state != TrialState.PRUNED and values_conversion_failure_message is not None: 
        
                   raise ValueError(values_conversion_failure_message) 
        
           try: 
        
               # Sampler defined trial post-processing. 
        
               study = pruners._filter_study(self, frozen_trial) 
        
               self.sampler.after_trial(study, frozen_trial, state, values) 
        
           except Exception: 
        
               raise 
        
           finally: 
        
               if values is not None: 
        
                   self._storage.set_trial_values(trial_id, values) 
        
               self._storage.set_trial_state(trial_id, state)

hvy · 2021-12-08T02:21:39Z

Thanks a lot @himkt for quickly addressing the issue with an RFC.

Just to clarify, do you mean that making state mutable (by defaulting to None), would make the behavior unnecessarily complicated, from a user-perspective, or from a code complexity point of view?
I was imagining moving https://github.com/optuna/optuna/blob/release-v3.0.0-a0/optuna/study/_optimize.py#L223-L230 to Study.tell and having all the validation done there. Study.optimize would merely add logging on top of that. Would you like me to prototype on that or have you already tried perhaps?

My understanding is that the validation logic (currently only done in Study.optimize) isn't trivial and is costly for the ask-and-tell users to implement, especially via the CLI. I personally find it acceptable trying to move more logic to Study.tell, even though it'd make the API/behavior more involved positioning it as a rather high-level API (but I also understand that having the specified state always written is simpler to use in some cases. Maybe we'd even go as far as introducing an additional "strict" option to control this behavior (edit: actually passing state with an actual state may act "strictly"), or exposing a different API publicly for value validation.). Perhaps starting with the CLI is a fine first approach, but I would argue that the interfaces are better designed kept consistent between the CLI and Study.tell at least for this topic.

himkt · 2021-12-13T15:12:16Z

Sorry for the inactive @hvy.

Just to clarify, do you mean that making state mutable (by defaulting to None), would make the behavior unnecessarily complicated, from a user-perspective, or from a code complexity point of view?

I said it by the point of code complexity. I was not sure how to tell a conversion failure to study._optimize.
But later I noticed we don't have to do so: it's enough to simply do logging in tell.

And I also found _check_and_convert_to_values is also called inside study.tell.
So, I simply tried to update it (many tests will fail. I'll check them) in c143c3a.

optuna/optuna/study/study.py

Lines 639 to 647 in 10d1111

    
           if values is not None: 
        
               values, values_conversion_failure_message = _check_and_convert_to_values( 
        
                   len(self.directions), values, trial_number 
        
               ) 
        
               # When called from `Study.optimize` and `state` is pruned, the given `values` contains 
        
               # the intermediate value with the largest step so far. In this case, the value is 
        
               # allowed to be NaN and errors should not be raised. 
        
               if state != TrialState.PRUNED and values_conversion_failure_message is not None: 
        
                   raise ValueError(values_conversion_failure_message)

hvy · 2021-12-21T03:40:46Z

📝 Just had a discussion with @himkt outside this PR. This work is ready for review.
📝 Make sure that Study.tell's behavior is consistent with Study.optimize's return value handling from the objective function (best-effort, i.e. putting aside the catch parameter in Study.optimize which adds a layer of behavior control above the abstraction of Study.tell).

HideakiImamura

Thanks for an important PR to resolve #3132. Also, I think this PR partially resolve #3205. I agree with the idea to make sure that Study.tell's behavior is consistent with Study.optimize's return value handling.

I have a minor comment. Could you take a look?

optuna/study/study.py

HideakiImamura · 2021-12-24T07:05:13Z

I confirmed that this PR makes the behavior of Study.optimize and Study.tell consistent as follows.

code: This is the same as nan-tell.py provided in #3205.

import optuna
import numpy as np


# In-memory storage
study = optuna.create_study()
trial = study.ask()
try:
    study.tell(trial, float(np.nan))
except Exception as e:
    print(e)
finally:
    print(f"In-memory : Trial state is {study.trials[-1].state}")

# RDB storage (SQLite)
study = optuna.create_study(storage='sqlite:///../sqlite.db')
trial = study.ask()
try:
    study.tell(trial, float(np.nan))
except Exception as e:
    print(e)
finally:
    print(f"SQLite    : Trial state is {study.trials[-1].state}")

# RDB storage (MySQL)
study = optuna.create_study(storage="mysql+pymysql://root:test@localhost/mysql")
trial = study.ask()
try:
    study.tell(trial, float(np.nan))
except Exception as e:
    print(e)
finally:
    print(f"MySQL     : Trial state is {study.trials[-1].state}")

# RDB storage (PostgreSQL)
study = optuna.create_study(storage="postgresql+psycopg2://postgres:test@localhost:15432/postgres")
trial = study.ask()
try:
    study.tell(trial, float(np.nan))
except Exception as e:
    print(e)
finally:
    print(f"PostgreSQL: Trial state is {study.trials[-1].state}")

output:

(venv) mamu@HideakinoMacBook-puro 3205-3206 % python nan-tell.py
[I 2021-12-24 16:02:58,636] A new study created in memory with name: no-name-91d1fb55-6f9c-4c51-861a-42892b705424
[W 2021-12-24 16:02:58,637] Trial 0 failed, because the objective function returned nan.
In-memory : Trial state is TrialState.FAIL
[I 2021-12-24 16:02:58,709] A new study created in RDB with name: no-name-ccbae3aa-b661-4e01-913e-d2d489e4cb90
[W 2021-12-24 16:02:58,754] Trial 0 failed, because the objective function returned nan.
SQLite    : Trial state is TrialState.FAIL
[I 2021-12-24 16:02:58,907] A new study created in RDB with name: no-name-92237945-fb07-46b8-92cd-b0349805fb78
[W 2021-12-24 16:02:59,011] Trial 0 failed, because the objective function returned nan.
MySQL     : Trial state is TrialState.FAIL
[I 2021-12-24 16:02:59,322] A new study created in RDB with name: no-name-ffaba79b-3556-42da-b23a-29962316e788
[W 2021-12-24 16:02:59,439] Trial 0 failed, because the objective function returned nan.
PostgreSQL: Trial state is TrialState.FAIL
`

hvy

Looks good, the code becomes simpler with this change in my opinion. Left some comments still if you could take a look. 🙏

optuna/study/_optimize.py

hvy · 2022-01-04T07:14:50Z

optuna/study/_optimize.py

+        frozen_trial.state == TrialState.FAIL
+        and func_err is not None
+        and not isinstance(func_err, catch)
+    ):
        raise func_err
    return trial


You can simplify the internal logic even further (at _optimize_sequential, the caller of _run_trial) now with the return value of Study.tell.

Suggested change

return trial

return frozen_trial

Please note that the suggested change here is just a part of my suggestion in the comment.

Thank you for the suggestion! It really makes sense to me.
aae3a54 aaf638d ad4e8b5 (ad4e8b5 6f413c6 for multi objective) updates the logic using FrozenTrial.

Thanks a lot, you can simplify it even further. There is a line in _optimize_sequential that obtains a frozen trial from the previously returned Trial. Now that we return a frozen trial, we can skip this line.

frozen_trial = copy.deepcopy(study._storage.get_trial(trial._trial_id))

optuna/study/_optimize.py

optuna/study/study.py

hvy · 2022-01-04T07:33:17Z

optuna/study/study.py

+        if state is None and values is None:
+            self._storage.set_trial_state(trial_id, TrialState.FAIL)
+            _logger.warning("You must specify either state or values.")
+            return self._storage.get_trial(trial_id)


Should this always be executed without taking into account skip_if_finished ? Wondering if something like the following can replace.

Suggested change

if state is None and values is None:

self._storage.set_trial_state(trial_id, TrialState.FAIL)

_logger.warning("You must specify either state or values.")

return self._storage.get_trial(trial_id)

if state is None and values is None:

state = TrialState.FAIL

The logging message might be lacking information for the user, I think adding some context would help. (Besides from the comment above)

You suggestion is applied in adecbc4. I'll update message as well.

I updated the doc in 6fa50b4. I'm not sure if it improves a usability so please give me a feedback. 🙏

Thanks. Sorry for my vague comment but I meant that we could omit the warning altogether, if we get rid of the early return statement (which you did).

optuna/study/study.py

himkt · 2022-01-09T11:02:06Z

Thank you so much @hvy for the careful review. I revised my PR based on your comments/suggestions!

hvy · 2022-01-11T00:38:58Z

Thanks a lot, I'll go through the changes today!

HideakiImamura

A minor comment

optuna/study/_optimize.py

himkt · 2022-04-01T05:54:57Z

I talked with @HideakiImamura and decided to stop moving existing tests to test_study.py. There is need to discuss where to put tests for methods in Study (e.g. Study.optimize, Study.tell, ...) and it should be discussed in the another place (this PR is already huge). It is done in 474cae8 and bc2b690.

HideakiImamura

Thanks for the update. I have several comments around tests. PTAL.

tests/study_tests/test_optimize.py

HideakiImamura · 2022-04-01T09:11:54Z

tests/study_tests/test_study.py

@@ -912,6 +913,66 @@ def objective(trial: Trial) -> float:
    assert states == []


+@pytest.mark.parametrize("storage_mode", STORAGE_MODES)
+def test_run_trial(storage_mode: str) -> None:


It looks like this test should be placed in test_optimize.py since this does not call Study.optimize but _run_trial.

Totally right, sorry for my careless. 🙇 8d62268

HideakiImamura · 2022-04-01T09:12:05Z

tests/study_tests/test_study.py

+
+
+@pytest.mark.parametrize("storage_mode", STORAGE_MODES)
+def test_run_trial_automatically_fail(storage_mode: str) -> None:


HideakiImamura · 2022-04-01T09:32:21Z

tests/study_tests/test_study.py

+
+
+@pytest.mark.parametrize("storage_mode", STORAGE_MODES)
+def test_run_trial_pruned(storage_mode: str) -> None:


Co-authored-by: Hideaki Imamura <38826298+HideakiImamura@users.noreply.github.com>

After my approval, the codes ware changed. I will re-review.

…e invalid

himkt · 2022-04-04T10:47:48Z

https://github.com/optuna/optuna/runs/5813743672?check_suite_focus=true#step:8:128
Tests passed in my local environment but CI isn't happy...

himkt · 2022-04-04T11:55:33Z

3bd7bd3 solves. @hvy @HideakiImamura PTAL. 🙏

hvy · 2022-04-05T00:31:42Z

tests/study_tests/test_optimize.py


-        # Test trial with invalid objective value: None
-        def func_none(_: Trial) -> float:
+    logging.enable_propagation()


Line is repeated, a small careless.

Suggested change

logging.enable_propagation()

tests/study_tests/test_optimize.py

hvy · 2022-04-05T00:51:21Z

I ran the local test script and it looked good too. 👍

HideakiImamura

I checked all of the test cases. Thanks for the long running work. LGTM!

hvy

LGTM!

Thank you very much for the effort. 🙇
While code complexity is still somewhat high, it turned out a lot better than expected.
Tests look great in my opinion and should make future refactoring a lot easier.

There are some nits such as commenting about the in-memory system attribute for warning propagation, and maybe a request to check in unit tests that when Study.tell fails with e.g. ValueError, that a trial is not modified. These are not significant, or not something introduced by this PR.

hvy · 2022-04-06T15:43:14Z

optuna/study/_tell.py

+
+    if value is not None and math.isnan(value):
+        value = None
+        failure_message = f"The objective function returned {original_value}."


Slightly misleading message for a user of Study.tell, but I think it's acceptable.

himkt · 2022-04-07T04:46:17Z

Thank you so much for informative reviews @hvy. ❤️ + Thank you for the patience!
I created the followup #3454 to apply your comments. 🩹

himkt mentioned this pull request Dec 3, 2021

nan handling of optuna tell. #3132

Closed

himkt force-pushed the cli-tell-nan branch 2 times, most recently from 829b30b to c143c3a Compare December 13, 2021 15:08

hvy self-assigned this Dec 15, 2021

himkt force-pushed the cli-tell-nan branch 3 times, most recently from 02955ec to 582dc5b Compare December 19, 2021 13:28

himkt changed the title ~~[RFC] Adding validation for nan in optuna tell~~ [RFC] Move validation logic from _run_trial to study.tell Dec 20, 2021

himkt force-pushed the cli-tell-nan branch from 50630a3 to 478bf92 Compare December 20, 2021 06:20

HideakiImamura self-assigned this Dec 23, 2021

HideakiImamura mentioned this pull request Dec 24, 2021

nan handling in Optuna #3205

Closed

3 tasks

HideakiImamura added bug Issue/PR about behavior that is broken. Not for typos/examples/CI/test but for Optuna itself. optuna.study Related to the `optuna.study` submodule. This is automatically labeled by github-actions. v3 Issue/PR for Optuna version 3. labels Dec 24, 2021

HideakiImamura reviewed Dec 24, 2021

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hvy requested changes Jan 4, 2022

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himkt force-pushed the cli-tell-nan branch 2 times, most recently from cb6e986 to 03d80ea Compare January 9, 2022 03:00

himkt marked this pull request as draft January 9, 2022 03:49

himkt force-pushed the cli-tell-nan branch from 0ee6c44 to 9ef0d75 Compare January 9, 2022 09:37

himkt marked this pull request as ready for review January 9, 2022 11:01

HideakiImamura reviewed Jan 11, 2022

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himkt force-pushed the cli-tell-nan branch from d934a95 to bc2b690 Compare April 1, 2022 05:53

HideakiImamura reviewed Apr 1, 2022

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himkt and others added 3 commits April 1, 2022 20:50

Move tests using _run_trial to test_optimize.py

8d62268

Update tests/study_tests/test_optimize.py

a423a0c

Co-authored-by: Hideaki Imamura <38826298+HideakiImamura@users.noreply.github.com>

Cleanup imports

72f50fc

himkt added 7 commits April 4, 2022 15:13

Revert tests order

c5f8a67

Add test for tell with state={fail,pruned} and value is not None

95fab95

Add test for _run_trial with valid values

2ca6eb3

Add test for _run_trial with unacceptable exception

a7342ae

Add test for tell in multi-objective with part of or all of values ar…

227d626

…e invalid

Check logging output in _run_trial

0aab004

Run isort

d4b7a08

Reconstruct logger in each test

3bd7bd3

hvy reviewed Apr 5, 2022

View reviewed changes

himkt added 2 commits April 5, 2022 11:36

Use pytest.fixture

5c199a7

Cleanup tests

921b9be

himkt requested a review from HideakiImamura April 5, 2022 10:43

HideakiImamura approved these changes Apr 6, 2022

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hvy approved these changes Apr 6, 2022

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hvy merged commit 217dd5e into optuna:master Apr 6, 2022

hvy added this to the v3.0.0-b0 milestone Apr 6, 2022

himkt mentioned this pull request Apr 7, 2022

Update warning message and add a test when a trial fails with exception #3454

Merged

himkt deleted the cli-tell-nan branch April 7, 2022 04:46

HideakiImamura removed the enhancement Change that does not break compatibility and not affect public interfaces, but improves performance. label Apr 8, 2022

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Move validation logic from `_run_trial` to `study.tell` #3144

Move validation logic from `_run_trial` to `study.tell` #3144

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	values, values_conversion_failure_message = _check_and_convert_to_values(
	len(study.directions), value_or_values, trial.number
	)
	if values_conversion_failure_message is not None:
	state = TrialState.FAIL
	else:
	state = TrialState.COMPLETE

	elif values_conversion_failure_message is not None:
	_logger.warning(values_conversion_failure_message)



		@pytest.mark.parametrize("storage_mode", STORAGE_MODES)
		def test_run_trial_automatically_fail(storage_mode: str) -> None:



		@pytest.mark.parametrize("storage_mode", STORAGE_MODES)
		def test_run_trial_pruned(storage_mode: str) -> None:

Move validation logic from _run_trial to study.tell #3144

Move validation logic from _run_trial to study.tell #3144

Conversation

himkt commented Dec 3, 2021 • edited

Motivation

Description of the changes

Behavior

codecov-commenter commented Dec 3, 2021 • edited

Codecov Report

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himkt commented Jan 9, 2022

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himkt commented Apr 7, 2022

Move validation logic from `_run_trial` to `study.tell` #3144

Move validation logic from `_run_trial` to `study.tell` #3144

himkt commented Dec 3, 2021 •

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