Masked autoencoder pre-training for virtual staining models #67
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new black version has different rules
edyoshikun
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Apr 2, 2024
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@ziw-liu Looks like this is now the de facto branch for both training recipes: end-to-end training and pre-training + fine-tuning. Can you confirm if that is the case? Please merge in Combined and concatenated data loaders are also valuable for infection phenotyping work. cc: @Soorya19Pradeep |
This is the case. However note that I didn't do comprehensive backwards compatibility testing so it could break previously trained models. |
👍🏼 Since we are tracking the key hyper-parameters with configs, we can retrain models we need. |
edyoshikun
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Jun 12, 2024
* refactor data loading into its own module * update type annotations * move the logging module out * move old logging into utils * rename tests to match module name * bump torch * draft fcmae encoder * add stem to the encoder * wip: masked stem layernorm * wip: patchify masked features for linear * use mlp from timm * hack: POC training script for FCMAE * fix mask for fitting * remove training script * default architecture * fine-tuning options * fix cli for finetuning * draft combined data module * fix import * manual validation loss reduction * update linting new black version has different rules * update development guide * update type hints * bump iohub * draft ctmc v1 dataset * update tests * move test_data * remove path conversion * configurable normalizations (#68) * inital commit adding the normalization. * adding dataset_statistics to each fov to facilitate the configurable augmentations * fix indentation * ruff * test preprocessing * remove redundant field * cleanup --------- Co-authored-by: Ziwen Liu <[email protected]> * fix ctmc dataloading * add example ctmc v1 loading script * changing the normalization and augmentations default from None to empty list. * invert intensity transform * concatenated data module * subsample videos * livecell dataset * all sample fields are optional * fix multi-dataloader validation * lint * fixing preprocessing for varying array shapes (i.e aics dataset) * update loading scripts * fix CombineMode * compose normalizations for predict and test stages * black * fix normalization in example config * fix collate when multi-sample transform is not used * ddp caching fixes * fix caching when using combined loader * move log values to GPU before syncing Lightning-AI/pytorch-lightning#18803 * removing normalize_source from configs. * typing fixes * fix test data path * fix test dataset * add docstring for ConcatDataModule * format --------- Co-authored-by: Eduardo Hirata-Miyasaki <[email protected]>
edyoshikun
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Jun 12, 2024
* refactor data loading into its own module * update type annotations * move the logging module out * move old logging into utils * rename tests to match module name * bump torch * draft fcmae encoder * add stem to the encoder * wip: masked stem layernorm * wip: patchify masked features for linear * use mlp from timm * hack: POC training script for FCMAE * fix mask for fitting * remove training script * default architecture * fine-tuning options * fix cli for finetuning * draft combined data module * fix import * manual validation loss reduction * update linting new black version has different rules * update development guide * update type hints * bump iohub * draft ctmc v1 dataset * update tests * move test_data * remove path conversion * configurable normalizations (#68) * inital commit adding the normalization. * adding dataset_statistics to each fov to facilitate the configurable augmentations * fix indentation * ruff * test preprocessing * remove redundant field * cleanup --------- Co-authored-by: Ziwen Liu <[email protected]> * fix ctmc dataloading * add example ctmc v1 loading script * changing the normalization and augmentations default from None to empty list. * invert intensity transform * concatenated data module * subsample videos * livecell dataset * all sample fields are optional * fix multi-dataloader validation * lint * fixing preprocessing for varying array shapes (i.e aics dataset) * update loading scripts * fix CombineMode * compose normalizations for predict and test stages * black * fix normalization in example config * fix collate when multi-sample transform is not used * ddp caching fixes * fix caching when using combined loader * move log values to GPU before syncing Lightning-AI/pytorch-lightning#18803 * removing normalize_source from configs. * typing fixes * fix test data path * fix test dataset * add docstring for ConcatDataModule * format --------- Co-authored-by: Eduardo Hirata-Miyasaki <[email protected]>
edyoshikun
added a commit
that referenced
this pull request
Jun 12, 2024
* refactor data loading into its own module * update type annotations * move the logging module out * move old logging into utils * rename tests to match module name * bump torch * draft fcmae encoder * add stem to the encoder * wip: masked stem layernorm * wip: patchify masked features for linear * use mlp from timm * hack: POC training script for FCMAE * fix mask for fitting * remove training script * default architecture * fine-tuning options * fix cli for finetuning * draft combined data module * fix import * manual validation loss reduction * update linting new black version has different rules * update development guide * update type hints * bump iohub * draft ctmc v1 dataset * update tests * move test_data * remove path conversion * configurable normalizations (#68) * inital commit adding the normalization. * adding dataset_statistics to each fov to facilitate the configurable augmentations * fix indentation * ruff * test preprocessing * remove redundant field * cleanup --------- Co-authored-by: Ziwen Liu <[email protected]> * fix ctmc dataloading * add example ctmc v1 loading script * changing the normalization and augmentations default from None to empty list. * invert intensity transform * concatenated data module * subsample videos * livecell dataset * all sample fields are optional * fix multi-dataloader validation * lint * fixing preprocessing for varying array shapes (i.e aics dataset) * update loading scripts * fix CombineMode * compose normalizations for predict and test stages * black * fix normalization in example config * fix collate when multi-sample transform is not used * ddp caching fixes * fix caching when using combined loader * move log values to GPU before syncing Lightning-AI/pytorch-lightning#18803 * removing normalize_source from configs. * typing fixes * fix test data path * fix test dataset * add docstring for ConcatDataModule * format --------- Co-authored-by: Eduardo Hirata-Miyasaki <[email protected]>
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