Uh oh!
There was an error while loading. Please reload this page.
refac(example):simple learn-saturated-mixing-ratio - #248
Merged
Conversation
This commit adds a trainable_network_t constructor that accepts the components derived types components directly rather than exposing the use of its neural_network_t parent as an intermediary. This eliminates the need for the neural_network_t type in the learn-saturated-mixing-ratio example and thereby makes that example's use of Fiats entities a subset of the entities used by the similar but much more complicated demonstration application train-cloud-microphysics. This change makes the example a useful proxy for the demonstration application when introducing new users to the demonstration application in the ISS conference paper.
This file contains hidden or 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
Sign up for freeto join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
This commit adds a
trainable_network_tconstructor that accepts the components derived types components directly rather than exposing the use of itsneural_network_tparent as an intermediary. This eliminates the need for theneural_network_ttype in thelearn-saturated-mixing-ratio exampleand thereby makes that example's use of Fiats entities a subset of the entities used by the similar but much more complicated demonstration applicationtrain-cloud-microphysics. This change makes the example a useful proxy for the demonstration application when introducing new users to the demonstration application in the ISS conference paper.