[ML] Optimize inference step when there are no test docs #74315
Merged
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
In data frame analytics, when the analysis supports inference and `training_percent` is set to `100`, there is no need to load the model in memory only to realize there are no documents to run inference on. This commit optimizes the inference step in this scenario.
|
Pinging @elastic/ml-core (Team:ML) |
dimitris-athanasiou
changed the title
|
@droberts195 I had to change the implementation for this as the tests reminded me that it's not sufficient to check |
benwtrent
approved these changes
Jun 21, 2021
dimitris-athanasiou
deleted the
skip-inference-step-when-training-percent-is-100
branch
dimitris-athanasiou
added a commit
that referenced
this pull request
Jun 22, 2021
#74398) In data frame analytics, when the analysis supports inference, `training_percent` is set to `100`, and there are no test docs (i.e. docs missing a value for their dependent variable), there is no need to load the model in memory only to realize there are no documents to run inference on. This commit optimizes the inference step in this scenario. Backport of #74315
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Outdated suggestions cannot be applied.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.
In data frame analytics, when the analysis supports inference,
training_percentis set to100, and there are no test docs(i.e. docs missing a value for their dependent variable),
there is no need to load the model in memory only to realize
there are no documents to run inference on.
This commit optimizes the inference step in this scenario.