Add more variant and pretrained_weight capability (#130) #154
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
Summary: Adding new variant: swin_s and swin_b with pretrained weight for omnivore. Test Plan: Create a test for each variant, also I change the test to use pytest instead of unittest. Usage: Here are example script to get the pretrained weight: ``` import torchmultimodal.models.omnivore as omnivore model = omnivore.omnivore_swin_s(pretrained=True) ``` Reviewed By: langong347 Differential Revision: D37834886 Pulled By: YosuaMichael fbshipit-source-id: 8a80d6c9d399eb22c87f43cca76bd2be73013774 [MUGEN]Spatialtemporal position embedding;tensor slicing utility [ghstack-poisoned]
facebook-github-bot
added
the
CLA Signed
This was referenced Jul 14, 2022
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Outdated suggestions cannot be applied.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.
Stack from ghstack (oldest at bottom):
Summary:
Adding new variant: swin_s and swin_b with pretrained weight for omnivore.
Test Plan:
Create a test for each variant, also I change the test to use pytest instead of unittest.
Usage:
Here are example script to get the pretrained weight:
Reviewed By: langong347
Differential Revision: D37834886
Pulled By: YosuaMichael
fbshipit-source-id: 8a80d6c9d399eb22c87f43cca76bd2be73013774
[MUGEN]Spatialtemporal position embedding;tensor slicing utility