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A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

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![image](https://github.com/pytorch/examples/assets/81737228/940d626c-5101-41ae-a36f-496319c03b0a) ![image](https://github.com/pytorch/examples/assets/81737228/7ea00869-7dd0-48ac-b0ef-1b25d57cbccc) ![image](https://github.com/pytorch/examples/assets/81737228/d3d5b76c-2e5e-4fcb-91c3-aa692938de0c)

https://github.com/pytorch/examples/blob/c67bbaba018d438447036c114133c6ad6c4f78b1/distributed/minGPT-ddp/mingpt/trainer.py#L103 according to [this link](https://pytorch.org/docs/stable/amp.html#torch.cuda.amp.GradScaler.unscale_) , we should add unscale before it when we need to [modify or inspect gradients](https://pytorch.org/docs/stable/notes/amp_examples.html#working-with-unscaled-gradients)

I tried the regression example in cpp using C++ 20 instead of 14. (https://github.com/pytorch/examples/tree/main/cpp/regression ) I just changed set(CMAKE_CXX_STANDARD 14) to set(CMAKE_CXX_STANDARD 20) in CMakeLists.txt The following errors occur: /Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX14.1.sdk/usr/include/c++/v1/vector:549:52:...

Fixed #247 by adjusted the learning rate and cleaned the code

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## Description I added pointers on debugging multinode training in AWS. ## Type of change - [x] Documentation update

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Dear developers It is so great that you've provided a examples/imagenet/main.py script which looks amazing. I'm looking how to setup a _Multi-processing Distributed Data Parallel Training_, for instance 8 GPUs...

This will be useful when we do multi-process distributed training.

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distributed

added sequence labeling example

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nlp

This is a simple update to super_resolution so that: It implements standard "freeze_support" so multithreading works on both Windows and Linux Removes Python-Lint warnings by passing references to variables Adds...

help wanted
vision
windows

The update step for REINFORCE appears to be wrong. Instead of multiplying log probs and rewards at each step, we should sum up all the rewards to go, and the...

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reinforcement learning