-
Notifications
You must be signed in to change notification settings - Fork 27.3k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Improve vision models #17731
Improve vision models #17731
Conversation
The documentation is not available anymore as the PR was closed or merged. |
dcd728c
to
33b720a
Compare
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Nice cleanup! Thanks for working on it!
src/transformers/models/data2vec/modeling_tf_data2vec_vision.py
Outdated
Show resolved
Hide resolved
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Nice! Thanks for making all these changes 🧹🧹🧹
Just some small comments about tests, but otherwise LGTM :)
* Improve vision models * Add a lot of improvements * Remove to_2tuple from swin tests * Fix TF Swin * Fix more tests * Fix copies * Improve more models * Fix ViTMAE test * Add channel check for TF models * Add proper channel check for TF models * Apply suggestion from code review * Apply suggestions from code review * Add channel check for Flax models, apply suggestion * Fix bug * Add tests for greyscale images * Add test for interpolation of pos encodigns Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
* Improve vision models * Add a lot of improvements * Remove to_2tuple from swin tests * Fix TF Swin * Fix more tests * Fix copies * Improve more models * Fix ViTMAE test * Add channel check for TF models * Add proper channel check for TF models * Apply suggestion from code review * Apply suggestions from code review * Add channel check for Flax models, apply suggestion * Fix bug * Add tests for greyscale images * Add test for interpolation of pos encodigns Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
* Initial TF DeiT implementation * Fix copies naming issues * Fix up + docs * Properly same main layer * Name layers properly * Initial TF DeiT implementation * Fix copies naming issues * Fix up + docs * Properly same main layer * Name layers properly * Fixup * Fix import * Fix import * Fix import * Fix weight loading for tests whilst not on hub * Add doc tests and remove to_2tuple * Add back to_2tuple Removing to_2tuple results in many downstream changes needed because of the copies checks * Incorporate updates in Improve vision models #17731 PR * Don't hard code num_channels * Copy PyTorch DeiT embeddings and remove pytorch operations with mask * Fix patch embeddings & tidy up * Update PixelShuffle to move logic into class layer * Update doc strings - remove PT references * Use NHWC format in internal layers * Fix up * Use linear activation layer * Remove unused import * Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Move dataclass to top of file * Remove from_pt now weights on hub * Fixup Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Amy Roberts <amyeroberts@users.noreply.github.com>
* Initial TF DeiT implementation * Fix copies naming issues * Fix up + docs * Properly same main layer * Name layers properly * Initial TF DeiT implementation * Fix copies naming issues * Fix up + docs * Properly same main layer * Name layers properly * Fixup * Fix import * Fix import * Fix import * Fix weight loading for tests whilst not on hub * Add doc tests and remove to_2tuple * Add back to_2tuple Removing to_2tuple results in many downstream changes needed because of the copies checks * Incorporate updates in Improve vision models huggingface#17731 PR * Don't hard code num_channels * Copy PyTorch DeiT embeddings and remove pytorch operations with mask * Fix patch embeddings & tidy up * Update PixelShuffle to move logic into class layer * Update doc strings - remove PT references * Use NHWC format in internal layers * Fix up * Use linear activation layer * Remove unused import * Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Move dataclass to top of file * Remove from_pt now weights on hub * Fixup Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Amy Roberts <amyeroberts@users.noreply.github.com>
What does this PR do?
This PR improves the vision models by:
to_2tuple
config.num_channels
config.num_channels
forxxxForMaskedImageModeling
models (fixes SimMIM output num_channels should not be hardcoded #17727)config.num_channels
in Flax models (ViT, BEiT)To do: