Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
* chlog update * Fix typo in script name (#15724) (cherry picked from commit d925077) * Torch inference mode for prediction (#15719) torch inference mode for prediction (cherry picked from commit 08d14ec) * [App] Update multi-node examples (#15700) Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com> Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com> (cherry picked from commit 8306797) * feature(docs/app/lit_tabs): add works (#15731) (cherry picked from commit 1a31d13) * [App] Fix VSCode IDE debugger (#15747) (cherry picked from commit 6714ca7) * Update tensorboard requirement from <2.11.0,>=2.9.1 to >=2.9.1,<2.12.0 in /requirements (#15746) Update tensorboard requirement in /requirements Updates the requirements on [tensorboard](https://github.com/tensorflow/tensorboard) to permit the latest version. - [Release notes](https://github.com/tensorflow/tensorboard/releases) - [Changelog](https://github.com/tensorflow/tensorboard/blob/master/RELEASE.md) - [Commits](tensorflow/tensorboard@2.9.1...2.11.0) --- updated-dependencies: - dependency-name: tensorboard dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com> Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> (cherry picked from commit 0b58b69) * Update beautifulsoup4 requirement from <=4.8.2 to <4.11.2 in /requirements (#15745) * Update beautifulsoup4 requirement in /requirements Updates the requirements on [beautifulsoup4](https://www.crummy.com/software/BeautifulSoup/bs4/) to permit the latest version. --- updated-dependencies: - dependency-name: beautifulsoup4 dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com> * Apply suggestions from code review Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com> (cherry picked from commit 1ffbe1b) * [App] Fix multi-node pytorch example CI (#15753) (cherry picked from commit bc797fd) * [App] Improve `LightningTrainerScript` start-up time (#15751) (cherry picked from commit c2c1974) * Enable Probot CheckGroup v5 (#15670) (cherry picked from commit 6c8ee01) * [App] Enable properties for the Lightning flow (#15750) (cherry picked from commit 5cfb176) * test for Enable setting property (#15755) Co-authored-by: thomas chaton <thomas@grid.ai> Co-authored-by: Ethan Harris <ethanwharris@gmail.com> (cherry picked from commit ba14038) * Move s3fs to cloud extras (#15729) Co-authored-by: Luca Antiga <luca@lightning.ai> (cherry picked from commit dd75906) * Revert new Hydra launch behavior (#15737) * revert new hydra cwd behavior * remove debug statements * changelog Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Jirka <jirka.borovec@seznam.cz> Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com> (cherry picked from commit 88b2e5a) * FCCV Docs (#15598) * add custom data iter docs * add custom data iter docs * Update docs/source-pytorch/data/custom_data_iterables.rst * remove ToDevice * nit * Update docs/source-pytorch/data/custom_data_iterables.rst Co-authored-by: Luca Antiga <luca.antiga@gmail.com> * clarification for @lantiga * typo * Update docs/source-pytorch/data/custom_data_iterables.rst * Update docs/source-pytorch/data/custom_data_iterables.rst * Update docs/source-pytorch/data/custom_data_iterables.rst Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com> Co-authored-by: Akihiro Nitta <nitta@akihironitta.com> Co-authored-by: Luca Antiga <luca.antiga@gmail.com> (cherry picked from commit 006fde9) * Switch from tensorboard to tensorboardx in logger (#15728) * Switch from tensorboard to tensorboardx in logger * Warn if log_graph is set to True but tensorboard is not installed * Fix warning message formatting * Apply suggestions from code review * simplify for TBX as required pkg * docs example * chlog * tbx 2.2 Co-authored-by: Luca Antiga <luca@lightning.ai> Co-authored-by: William Falcon <waf2107@columbia.edu> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com> Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com> Co-authored-by: Jirka <jirka.borovec@seznam.cz> (cherry picked from commit 9c2eb52) * resolve conflicts * Fix azure path excludes (#15756) Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com> (cherry picked from commit aef94ce) * Disable XSRF protection in StreamlitFrontend to support upload in localhost (#15684) * Enable CORS in StreamlitFrontend to support upload * Only disable XSRF when running on localhost * Update test * Use utility fn to detect if localhost Co-authored-by: Luca Antiga <luca@lightning.ai> (cherry picked from commit ed3eef0) * Enable Probot CheckGroup v5.1 (#15763) (cherry picked from commit c55f80f) * Bump pytest from 7.1.3 to 7.2.0 in /requirements (#15677) Bumps [pytest](https://github.com/pytest-dev/pytest) from 7.1.3 to 7.2.0. - [Release notes](https://github.com/pytest-dev/pytest/releases) - [Changelog](https://github.com/pytest-dev/pytest/blob/main/CHANGELOG.rst) - [Commits](pytest-dev/pytest@7.1.3...7.2.0) --- updated-dependencies: - dependency-name: pytest dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> (cherry picked from commit cfb27bd) * Fix the `examples/app_dag` App (#14359) * Fix app dag example * Add test * Update doc * Update tests/tests_app_examples/test_app_dag.py Co-authored-by: Sherin Thomas <sherin@grid.ai> (cherry picked from commit 2b61c92) * mergify: drop ready for draft (#15766) (cherry picked from commit 1a07a9c) * lightning delete cluster CLI command help text update (#15760) * updated the lighting delete cluster CLI command help text output * updated changelog * typo fix * Apply suggestions from code review Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com> (cherry picked from commit 75b0573) * Deduplicate top level lighting CLI command groups (#15761) * unify remove and delete command groups & the add and delete command groups * added changelog * fix tests * Apply suggestions from code review Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com> (cherry picked from commit 7b2788e) * releasing 1.8.3 * CI: lite on GPU * Fix App Docs for lightning ssh-keys command (#15773) fixed ssh-keys docs (cherry picked from commit 317591d) Co-authored-by: thomas chaton <thomas@grid.ai> Co-authored-by: yiftachbeer <yiftach.beer@gmail.com> Co-authored-by: Sherin Thomas <sherin@lightning.ai> Co-authored-by: Ethan Harris <ethanwharris@gmail.com> Co-authored-by: Yurij Mikhalevich <yurij@grid.ai> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com> Co-authored-by: Luca Antiga <luca.antiga@gmail.com> Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com> Co-authored-by: Kaushik B <45285388+kaushikb11@users.noreply.github.com> Co-authored-by: Rick Izzo <rlizzo@users.noreply.github.com>
- Loading branch information
13 people
committed
Nov 23, 2022
1 parent
8bea72b
commit 7d6cfb1
Showing
60 changed files
with
440 additions
and
352 deletions.
There are no files selected for viewing
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,7 +1,8 @@ | ||
| .. lit_tabs:: | ||
| :titles: Hello world; Hello GPU world; PyTorch & ⚡⚡⚡ Trainer (1+ cloud GPUs); Train PyTorch (cloud GPU); Train PyTorch (32 cloud GPUs); Deploy a model on cloud GPUs; Run a model script; XGBoost; Streamlit demo | ||
| :code_files: /levels/basic/hello_components/hello_world.py; /levels/basic/hello_components/hello_world_gpu.py; /levels/basic/hello_components/pl_multinode.py; /levels/basic/hello_components/train_pytorch.py; /levels/basic/hello_components/pt_multinode.py; /levels/basic/hello_components/deploy_model.py; /levels/basic/hello_components/run_ptl_script.py; /levels/basic/hello_components/xgboost.py; /levels/basic/hello_components/streamlit_demo.py | ||
| :highlights: 7; 10, 11; 10-12, 17, 18; 4, 8, 12, 18-19, 26; 5, 10, 22, 28, 32, 42, 58-60; 3, 11-12, 25, 29; 7, 10; 15, 21; 9, 15, 24 | ||
| :highlights: 7; 10, 11; 9-11, 16, 17; 4, 8, 12, 18-19, 26; 5, 10, 22, 27, 31, 41, 57-59; 3, 11-12, 25, 29; 7, 10; 15, 21; 9, 15, 24 | ||
| :works: [{"name":"root.work","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"default","preemptible":false,"shmSize":0},"networkConfig":[{"name":"dzodf","port":61304}]}}];[{"name":"root.work","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"qnlgd","port":61516}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu","preemptible":false,"shmSize":0}}}];[{"name":"root.ws.0","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"ajfrc","port":61553}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu-fast-multi","preemptible":false,"shmSize":0}}},{"name":"root.ws.1","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"ttyqc","port":61554}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu-fast-multi","preemptible":false,"shmSize":0}}},{"name":"root.ws.2","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"svyej","port":61555}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu-fast-multi","preemptible":false,"shmSize":0}}},{"name":"root.ws.3","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"parme","port":61556}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu-fast-multi","preemptible":false,"shmSize":0}}}];[{"name":"root.work","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"cutdu","port":61584}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu","preemptible":false,"shmSize":0}}}];[{"name":"root.ws.0","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"whhby","port":61613}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu-fast-multi","preemptible":false,"shmSize":0}}},{"name":"root.ws.1","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"yhjtf","port":61614}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu-fast-multi","preemptible":false,"shmSize":0}}},{"name":"root.ws.2","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"rqwkt","port":61615}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu-fast-multi","preemptible":false,"shmSize":0}}},{"name":"root.ws.3","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"pjdsj","port":61616}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu-fast-multi","preemptible":false,"shmSize":0}}},{"name":"root.ws.4","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"efdor","port":61617}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu-fast-multi","preemptible":false,"shmSize":0}}},{"name":"root.ws.5","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"pxmso","port":61618}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu-fast-multi","preemptible":false,"shmSize":0}}},{"name":"root.ws.6","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"feevy","port":61619}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu-fast-multi","preemptible":false,"shmSize":0}}},{"name":"root.ws.7","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"tbmse","port":61620}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu-fast-multi","preemptible":false,"shmSize":0}}}];[{"name":"root.work","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"umqqg","port":7777}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"gpu","preemptible":false,"shmSize":0}}}];[];[{"name":"root.work","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"tggba","port":61729}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"default","preemptible":false,"shmSize":0}}}];[{"name":"root.work","spec":{"buildSpec":{"commands":[],"pythonDependencies":{"packageManager":"PACKAGE_MANAGER_PIP","packages":""}},"drives":[],"networkConfig":[{"name":"hpyaz","port":61763}],"userRequestedComputeConfig":{"count":1,"diskSize":0,"name":"default","preemptible":false,"shmSize":0}}}] | ||
| :enable_run: true | ||
| :tab_rows: 3 | ||
| :height: 620px |
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
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
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
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
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,122 @@ | ||
| .. _dataiters: | ||
|
|
||
| ################################## | ||
| Injecting 3rd Party Data Iterables | ||
| ################################## | ||
|
|
||
| When training a model on a specific task, data loading and preprocessing might become a bottleneck. | ||
| Lightning does not enforce a specific data loading approach nor does it try to control it. | ||
| The only assumption Lightning makes is that the data is returned as an iterable of batches. | ||
|
|
||
| For PyTorch-based programs, these iterables are typically instances of :class:`~torch.utils.data.DataLoader`. | ||
|
|
||
| However, Lightning also supports other data types such as plain list of batches, generators or other custom iterables. | ||
|
|
||
| .. code-block:: python | ||
| # random list of batches | ||
| data = [(torch.rand(32, 3, 32, 32), torch.randint(0, 10, (32,))) for _ in range(100)] | ||
| model = LitClassifier() | ||
| trainer = Trainer() | ||
| trainer.fit(model, data) | ||
| Examples for custom iterables include `NVIDIA DALI <https://github.com/NVIDIA/DALI>`__ or `FFCV <https://github.com/libffcv/ffcv>`__ for computer vision. | ||
| Both libraries offer support for custom data loading and preprocessing (also hardware accelerated) and can be used with Lightning. | ||
|
|
||
|
|
||
| For example, taking the example from FFCV's readme, we can use it with Lightning by just removing the hardcoded ``ToDevice(0)`` | ||
| as Lightning takes care of GPU placement. In case you want to use some data transformations on GPUs, change the | ||
| ``ToDevice(0)`` to ``ToDevice(self.trainer.local_rank)`` to correctly map to the desired GPU in your pipeline. | ||
|
|
||
| .. code-block:: python | ||
| from ffcv.loader import Loader, OrderOption | ||
| from ffcv.transforms import ToTensor, ToDevice, ToTorchImage, Cutout | ||
| from ffcv.fields.decoders import IntDecoder, RandomResizedCropRGBImageDecoder | ||
| class CustomClassifier(LitClassifier): | ||
| def train_dataloader(self): | ||
| # Random resized crop | ||
| decoder = RandomResizedCropRGBImageDecoder((224, 224)) | ||
| # Data decoding and augmentation | ||
| image_pipeline = [decoder, Cutout(), ToTensor(), ToTorchImage()] | ||
| label_pipeline = [IntDecoder(), ToTensor()] | ||
| # Pipeline for each data field | ||
| pipelines = {"image": image_pipeline, "label": label_pipeline} | ||
| # Replaces PyTorch data loader (`torch.utils.data.Dataloader`) | ||
| loader = Loader( | ||
| write_path, batch_size=bs, num_workers=num_workers, order=OrderOption.RANDOM, pipelines=pipelines | ||
| ) | ||
| return loader | ||
| When moving data to a specific device, you can always refer to ``self.trainer.local_rank`` to get the accelerator | ||
| used by the current process. | ||
|
|
||
| By just changing ``device_id=0`` to ``device_id=self.trainer.local_rank`` we can also leverage DALI's GPU decoding: | ||
|
|
||
| .. code-block:: python | ||
| from nvidia.dali.pipeline import pipeline_def | ||
| import nvidia.dali.types as types | ||
| import nvidia.dali.fn as fn | ||
| from nvidia.dali.plugin.pytorch import DALIGenericIterator | ||
| import os | ||
| class CustomLitClassifier(LitClassifier): | ||
| def train_dataloader(self): | ||
| # To run with different data, see documentation of nvidia.dali.fn.readers.file | ||
| # points to https://github.com/NVIDIA/DALI_extra | ||
| data_root_dir = os.environ["DALI_EXTRA_PATH"] | ||
| images_dir = os.path.join(data_root_dir, "db", "single", "jpeg") | ||
| @pipeline_def(num_threads=4, device_id=self.trainer.local_rank) | ||
| def get_dali_pipeline(): | ||
| images, labels = fn.readers.file(file_root=images_dir, random_shuffle=True, name="Reader") | ||
| # decode data on the GPU | ||
| images = fn.decoders.image_random_crop(images, device="mixed", output_type=types.RGB) | ||
| # the rest of processing happens on the GPU as well | ||
| images = fn.resize(images, resize_x=256, resize_y=256) | ||
| images = fn.crop_mirror_normalize( | ||
| images, | ||
| crop_h=224, | ||
| crop_w=224, | ||
| mean=[0.485 * 255, 0.456 * 255, 0.406 * 255], | ||
| std=[0.229 * 255, 0.224 * 255, 0.225 * 255], | ||
| mirror=fn.random.coin_flip(), | ||
| ) | ||
| return images, labels | ||
| train_data = DALIGenericIterator( | ||
| [get_dali_pipeline(batch_size=16)], | ||
| ["data", "label"], | ||
| reader_name="Reader", | ||
| ) | ||
| return train_data | ||
| Limitations | ||
| ------------ | ||
| Lightning works with all kinds of custom data iterables as shown above. There are, however, a few features that cannot | ||
| be supported this way. These restrictions come from the fact that for their support, | ||
| Lightning needs to know a lot on the internals of these iterables. | ||
|
|
||
| - In a distributed multi-GPU setting (ddp), | ||
| Lightning automatically replaces the DataLoader's sampler with its distributed counterpart. | ||
| This makes sure that each GPU sees a different part of the dataset. | ||
| As sampling can be implemented in arbitrary ways with custom iterables, | ||
| there is no way for Lightning to know, how to replace the sampler. | ||
|
|
||
| - When training fails for some reason, Lightning is able to extract all of the relevant data from the model, | ||
| optimizers, trainer and dataloader to resume it at the exact same batch it crashed. | ||
| This feature is called fault-tolerance and is limited to PyTorch DataLoaders. | ||
| Lighning needs to know a lot about sampling, fast forwarding and random number handling to enable fault tolerance, | ||
| meaning that it cannot be supported for arbitrary iterables. |
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
Oops, something went wrong.