Tutorials : Pretraining VGG from Scrtach #2971
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saving and loading a general checkpoint.py \n intial -> initial
toctree : Image and Video Pretraining Vgg from scratch
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/tutorials/2971
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| In this tutorial, we will embark on an exciting journey to build and | |||
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Please follow this template . Your tutorials should have: Title, a short abstract, Author, Overview, Steps, and Conclusion. Please maintain a third-person narrative throughout the document. Avoid using first-person pronouns like "I" and instead use "we". Use active voice where possible.
Follow Pytorch Tutorial convetion Modify I -> We
Add More things to try , Conclusion , Further Reading
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Hi @svekars, could you please help to take a look of this PR? |
pyspell fixed
add packagge install code
add packagge install code
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Hi @svekars, could you please help to take a look of this PR again? |
remove tqdm
pyspell check,add albumentations installation code
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Hi @svekars , could you please help to take a look of this PR again? |
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Thanks for the PR!
@svekars are you okay with handling review for the polish needed for this tutorial? (e.g. grammar / punctuation / spacing). I added several comments regarding this but it's incomplete and I shifted to focusing on the ML component of the tutorial.
Made a pass but haven't spent a ton of time verifying the code logic yet. I can take another look once some of these issues are addressed.
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| ###################################################################### | ||
| # Worth point of this tutorial |
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| # Worth point of this tutorial | |
| # Purpose of this tutorial |
| train a VGG network from scratch using Python and popular deep learning | ||
| libraries such as PyTorch. We will dive into the details of the VGG |
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| train a VGG network from scratch using Python and popular deep learning | |
| libraries such as PyTorch. We will dive into the details of the VGG | |
| train a VGG network from scratch using PyTorch. We will dive into the details of the VGG |
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A better intro would be:
VGG (Visual Geometry Group) is a convolutional neural network architecture that is particularly
efficient in image classification tasks. In this tutorial, we will guide you through building
and training a VGG network from scratch using Python and PyTorch. We will dive into the details of the VGG
architecture, understanding its components and the rationale behind its
design.
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| ###################################################################### | ||
| # | If your GPU memory is 24GB ,The maximum batch size is 128. But, if you |
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| # | If your GPU memory is 24GB ,The maximum batch size is 128. But, if you | |
| # | If your GPU memory is 24GB, the maximum batch size is 128. But if you |
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| ###################################################################### | ||
| # | If your GPU memory is 24GB ,The maximum batch size is 128. But, if you | ||
| # use Colab , We recommend using 32 . |
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| # use Colab , We recommend using 32 . | |
| # use Colab, we recommend using 32GB. |
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| ###################################################################### | ||
| # We use ``CIFAR100`` Dataset in this tutorial. In VGG paper , the authors |
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| # We use ``CIFAR100`` Dataset in this tutorial. In VGG paper , the authors | |
| # We use the ``CIFAR100`` dataset in this tutorial. In VGG paper, the authors |
| # When training VGG , the authors first train model A , then initialized | ||
| # the weights of other models with the weights of model A. Waiting for | ||
| # Model A to be trained takes a long time . The authors mention how to | ||
| # train with ``xavier`` initialization rather than initializing with the |
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capitalization nit: xavier -> Xavier throughout
| # When training VGG , the authors first train model A , then initialized | ||
| # the weights of other models with the weights of model A. Waiting for |
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| # When training VGG , the authors first train model A , then initialized | |
| # the weights of other models with the weights of model A. Waiting for | |
| # When training VGG, the authors first train model A, then continue training from | |
| # the resultant weights for other variants. Waiting for |
| # ------------------- | ||
| # | ||
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| class Cusotm_ImageNet(ImageNet) : |
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| class Cusotm_ImageNet(ImageNet) : | |
| class Custom_ImageNet(ImageNet) : |
| ###################################################################### | ||
| # Conclusion | ||
| # ---------- | ||
| # We have seen how ``pretraining`` VGG from scratch . This Tutorial will be helpful to reproduce another Foundation Model . |
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this needs to be expanded a bit, and I'm not sure what is meant by the Foundation Model comment
| # - Trying On ImageNet | ||
| # - Try All version of Model | ||
| # - Try All evaluation method in VGG paper |
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| # - Trying On ImageNet | |
| # - Try All version of Model | |
| # - Try All evaluation method in VGG paper | |
| # - Apply model to ImageNet | |
| # - Try all model variants | |
| # - Try additional evaluation methods |
@jbschlosser yes, I will do the editorial pass as long as we align on the overall technical content. |
Lint and Technical Details and flexible code style
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@svekars Sorry for being late. I've been busy with lab work. I've made some revisions based on the feedback I received. Could you check again? |
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There is a build error related to the code. |
Editorial and formatting fixes
Co-authored-by: Joel Schlosser <[email protected]>
| * Complete the `Learn the Basics tutorials <https://pytorch.org/tutorials/beginner/basics/intro.html>`__ | ||
| * Familiarity with basic machine learning concepts and terms | ||
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| If you are running this in Google Colab, install albumentations |
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| If you are running this in Google Colab, install albumentations | |
| If you are running this in Google Colab, install albumentations by running the following command: | |
| .. code-block:: py | |
| !pip install albumentations |
train loader fail
train loader fail
feedback accepted Re PullRequest because of network issue
Co-authored-by: Joel Schlosser <[email protected]>
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@svekars Are there any other things I need to fix? |
Fixes #ISSUE_NUMBER
Description
I make a new tutorial training VGG from scratch . There are no tutorials traning Vgg from scratch.
Checklist
cc @subramen @albanD