Implement get_next_trials #3107
Open
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
facebook-github-bot
added
the
CLA Signed
|
This pull request was exported from Phabricator. Differential Revision: D66367189 |
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #3107 +/- ##
==========================================
+ Coverage 95.43% 95.79% +0.35%
==========================================
Files 503 508 +5
Lines 50348 50776 +428
==========================================
+ Hits 48051 48641 +590
+ Misses 2297 2135 -162 ☔ View full report in Codecov by Sentry. |
mpolson64
added a commit
to mpolson64/Ax
that referenced
this pull request
Nov 26, 2024
Summary: As titled. Get next trials takes in a maximum number of trials to generate and optionally a dict of parameter values to be fixed and generates up to that number of trials (as parallelism is available). If Experiment is not set or Experiment is set but Optimization is not set raise an Exception. If GenerationStrategy is not set then choose one automatically. Once generated trials are attached to the experiment and immediately marked RUNNING Differential Revision: D66367189
mpolson64
force-pushed
the
export-D66367189
branch
from
8cc7f9c
to
20d5b45
Compare
mpolson64
added a commit
to mpolson64/Ax
that referenced
this pull request
Nov 26, 2024
Summary: As titled. Get next trials takes in a maximum number of trials to generate and optionally a dict of parameter values to be fixed and generates up to that number of trials (as parallelism is available). If Experiment is not set or Experiment is set but Optimization is not set raise an Exception. If GenerationStrategy is not set then choose one automatically. Once generated trials are attached to the experiment and immediately marked RUNNING Differential Revision: D66367189
mpolson64
added a commit
to mpolson64/Ax
that referenced
this pull request
Nov 26, 2024
Summary: As titled. Get next trials takes in a maximum number of trials to generate and optionally a dict of parameter values to be fixed and generates up to that number of trials (as parallelism is available). If Experiment is not set or Experiment is set but Optimization is not set raise an Exception. If GenerationStrategy is not set then choose one automatically. Once generated trials are attached to the experiment and immediately marked RUNNING Differential Revision: D66367189
|
This pull request was exported from Phabricator. Differential Revision: D66367189 |
Summary: Implements new Client methods `configure_experiment`, `configure_optimization`, and `configure_generation_strategy`. Creates new module api.utils.instantiation that holds functions for converting from Configs to core Ax objects. These functions do not do validation, which will live on the configs themselves and be implemented in a separate diff. Note that this diff also does not implement saving to DB, although this will happen after each of these three methods are called if a config is provided **Id especially like comment on our use of SymPy** here to parse through objective and constraint strings -- what we've wound up with is much less verbose and I suspect much less error prone than what exists now in InstantiationBase while also providing a more natural user experience (ex. not getting tripped up by spacing, automatically handling inequality simplification like `(x1 + x2) / 2 + 0.5 >= 0` --> `-0.5 * x1 - 0.5 * x2 <= 1`, etc.) without any manual string parsing on our end at all. Im curious what people think of this strategy overall. SymPy usage occurs in `_parse_objective`, `_parse_parameter_constraint`, and `_parse_outcome_constraint`. Specific RFCs: * We made the decision earlier to combine the concepts of "outcome constraint" and objective thresholds into a single concept to make things clearer for our users -- do we still stand by this decision? Seeing it in practice I think it will help our users a ton but I want to confirm this before we get too far into implementation * We discussed previously that if we were using strings to represent objectives we wanted users to be able to specify optimization direction via coefficients (ex objective="loss" vs objective="-loss") **but we did not decide which direction a positive coefficient would indicate**. In this diff Ive implemented things such that a positive coefficient indicates minimization but Im happy to change -- I dont think one is better than the other we just need to be consistent. * To express relative outcome constraints, rather than use "%" like we do in AxClient, we ask the user multiply their bound by the term "baseline" (ex. "qps >= 0.95 * baseline" will constrain such that the QPS is at least 95% of the baseline arm's qps). To be honest we do this to make things play nice with SymPy but I also find it clearer, though Im curious what you all think Differential Revision: D65826204
Summary: These methods are not strictly speaking "part of the API" but may be useful for developers and trusted partners. Each is fairly self explanatory. Differential Revision: D66304352
Summary: configure_runner and configure_metric allow users to attach custom Runners and Metrics to their experiment. configure_runner is fairly straightforward and just sets experiment.runner configure_metric is more complicated: given a list of IMetrics it iterates through and tries to find a metric with the same name somewhere on the experiment. In order it checks the Objective (single, MOO, or secularized), outcome constraints, then tracking metrics. If no metric with a matching name is found then the provided metric is added as a tracking metric. Reviewed By: lena-kashtelyan Differential Revision: D66305614
Summary: As titled. Get next trials takes in a maximum number of trials to generate and optionally a dict of parameter values to be fixed and generates up to that number of trials (as parallelism is available). If Experiment is not set or Experiment is set but Optimization is not set raise an Exception. If GenerationStrategy is not set then choose one automatically. Once generated trials are attached to the experiment and immediately marked RUNNING Differential Revision: D66367189
mpolson64
force-pushed
the
export-D66367189
branch
from
20d5b45
to
c2a2486
Compare
|
This pull request was exported from Phabricator. Differential Revision: D66367189 |
mpolson64
added a commit
to mpolson64/Ax
that referenced
this pull request
Nov 26, 2024
Summary: As titled. Get next trials takes in a maximum number of trials to generate and optionally a dict of parameter values to be fixed and generates up to that number of trials (as parallelism is available). If Experiment is not set or Experiment is set but Optimization is not set raise an Exception. If GenerationStrategy is not set then choose one automatically. Once generated trials are attached to the experiment and immediately marked RUNNING Differential Revision: D66367189
mpolson64
added a commit
to mpolson64/Ax
that referenced
this pull request
Nov 26, 2024
Summary: As titled. Get next trials takes in a maximum number of trials to generate and optionally a dict of parameter values to be fixed and generates up to that number of trials (as parallelism is available). If Experiment is not set or Experiment is set but Optimization is not set raise an Exception. If GenerationStrategy is not set then choose one automatically. Once generated trials are attached to the experiment and immediately marked RUNNING Differential Revision: D66367189
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Summary:
As titled. Get next trials takes in a maximum number of trials to generate and optionally a dict of parameter values to be fixed and generates up to that number of trials (as parallelism is available).
If Experiment is not set or Experiment is set but Optimization is not set raise an Exception. If GenerationStrategy is not set then choose one automatically.
Once generated trials are attached to the experiment and immediately marked RUNNING
Differential Revision: D66367189