[feat] Add classification fine-tuning utilities #8
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- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. [ghstack-poisoned]
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- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. ghstack-source-id: ae4206926a64ab7456885f6e47db2d7f9cc5e2e5 Pull Request resolved: #8
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- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. Differential Revision: [D35271487](https://our.internmc.facebook.com/intern/diff/D35271487) [ghstack-poisoned]
apsdehal
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Apr 1, 2022
- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. ghstack-source-id: 2c0b03cde9ca54f662c20c4f6d40b73cc1b306cb Pull Request resolved: #8
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@ankitade has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. Differential Revision: [D35271487](https://our.internmc.facebook.com/intern/diff/D35271487) [ghstack-poisoned]
ankitade
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that referenced
this pull request
Apr 1, 2022
- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. ghstack-source-id: bdf5a7e6fc0e824c50e2c5c0514d4de35e3d42e3 Pull Request resolved: #8
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@ankitade has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. Differential Revision: [D35271487](https://our.internmc.facebook.com/intern/diff/D35271487) [ghstack-poisoned]
apsdehal
added a commit
that referenced
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Apr 2, 2022
- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. ghstack-source-id: 7bb538829ae5e404c05b8a010a923b1f4804dd2b Pull Request resolved: #8
- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. Differential Revision: [D35271487](https://our.internmc.facebook.com/intern/diff/D35271487) [ghstack-poisoned]
ankitade
added a commit
that referenced
this pull request
Apr 4, 2022
- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. ghstack-source-id: d082767d1332b7dbb3a5c1178f84e40868dbd28d Pull Request resolved: #8
- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. [ghstack-poisoned]
ankitade
added a commit
that referenced
this pull request
Apr 4, 2022
- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. ghstack-source-id: 615e5cc7f28ece279979026213e39236544a1f32 Pull Request resolved: #8
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@ankitade has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. Differential Revision: [D35361821](https://our.internmc.facebook.com/intern/diff/D35361821) [ghstack-poisoned]
ankitade
added a commit
that referenced
this pull request
Apr 4, 2022
- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. ghstack-source-id: 72db90d45c85907592d5ab1ef85b8327337b9512 Pull Request resolved: #8
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@ankitade has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
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@ankitade has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. Differential Revision: [D35361821](https://our.internmc.facebook.com/intern/diff/D35361821) [ghstack-poisoned]
|
@ankitade has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. Differential Revision: [D35361821](https://our.internmc.facebook.com/intern/diff/D35361821) [ghstack-poisoned]
ankitade
added a commit
that referenced
this pull request
Apr 5, 2022
- The PR aims at ending starter classification utils to flava examples. As of now the PR adds following things: - Finetuning trainer - Classification FLAVA - TorchVisionDataModule for easy composability of datasets from torchvision - Some changes to MLP module for more generalization - Some improvements/bug fixes to original FLAVA code - Splits the datamodules to better service their individual concerns. TODOs: - Add support for rest of the datasets. This involves levaraging the existing datamodules that we created in this PR along with support for seamlessly plugging different dataset - Add command line overriding on top - Add support for retrieval, zero-shot and other downstream tasks in an easily accessible form - Expose more things from the model other than just the loss Test Plan: The code is not in 100% working stage. I have tested only the changes in my PR. I expect everything to be stable by the end of the stack. ghstack-source-id: 72db90d45c85907592d5ab1ef85b8327337b9512 Pull Request resolved: #8
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@ankitade has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
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@ankitade has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
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@ankitade has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
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@ankitade has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
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Stack from ghstack (oldest at bottom):
As of now the PR adds following things:
torchvision
TODOs:
existing datamodules that we created in this PR along with support for
seamlessly plugging different dataset
easily accessible form
Test Plan:
The code is not in 100% working stage. I have tested only the changes in
my PR. I expect everything to be stable by the end of the stack.
Differential Revision: D35361821