[Reland] Add Dynamic Model Import and ModelSpec Definition #837
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`ghstack` didn't land pytorch#814 correctly. Open this PR to do so. The detail discussion please refer to pytorch#814 **What does this PR do?** 1. This PR introduces `ModelSpec` to describe a model and how to parallelize a model. * All the models should call `register_model_spec()`. * Users can also use `--experimental.custom_model_path` to dynamically import a model that is not implemented by TorchTitan. The module should also call `register_model_spec()`. 2. This PR also refactors `OptimizersContainer` and `LRSchedulersContainers` * Fixes an issue that optimizers will accept parameters that requires_grad is False. * Improve typing and docstring. * Improve the function and class reusability. * `OptimizersContainer` now inherits from `torch.optim.Optimizer` . 3. This PR also moves `parallelize_llama` and `pipelining_llama` to the `llama` folder. **Why do we need this PR?** This allows users to use TorchTitan with a new model without intrusively change TorchTitan code. **Next steps** 1. Dataloader is not included 2. Checkpoint customization is not included yet.
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ghstackdidn't land #814 correctly. Open this PR to do so. The detail discussion please refer to #814What does this PR do?
ModelSpecto describe a model and how to parallelize a model.register_model_spec().--experimental.custom_model_pathto dynamically import a model that is not implemented by TorchTitan. The module should also callregister_model_spec().OptimizersContainerandLRSchedulersContainersOptimizersContainernow inherits fromtorch.optim.Optimizer.parallelize_llamaandpipelining_llamato thellamafolder.Why do we need this PR?
This allows users to use TorchTitan with a new model without intrusively change TorchTitan code.
Next steps