[RFC][WIP][CP] Enable FlexAttention CP for llama3 #1857
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… llama3" This PR uses the latest CP APIs to enable FlexAttention + CP for llama3. This PR removes the usage of context_paralle() context manager and use `_context_parallel_shard()` to shard the input data. Pull-Request: #1857 [ghstack-poisoned]
XilunWu
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Oct 16, 2025
This PR uses the latest CP APIs to enable FlexAttention + CP for llama3. This PR removes the usage of context_paralle() context manager and use `_context_parallel_shard()` to shard the input data. Pull-Request: #1857 [ghstack-poisoned]
fegin
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Oct 28, 2025
Stack from [ghstack](https://github.com/ezyang/ghstack/tree/0.12.0) (oldest at bottom): * #1857 * __->__ #1939 TorchTitan doesn't need compiled_autograd, which is meant to support compiled DDP, but TorchTitan will adopt fully_shard-based replicate. Let's remove it.
fegin
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Oct 30, 2025
| yield input_dict, labels | ||
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| def forward_backward_step( | ||
| def post_dataloader_step( |
fegin
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Nov 4, 2025
We are adding more actions to convert the raw inputs and label. 1. The new CP can do the input/label/BlockMask sharding this in this method. 2. The experimental full dtensor model can simply override this method without changing too many Trainer code. This method is extracted from #1857 Makeing this a standalone PR allows us to continue the two projects above without one blocks another. ghstack-source-id: d1882a7 Pull-Request: #1985
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Stack from ghstack (oldest at bottom):
This PR uses the latest CP APIs to enable FlexAttention + CP for llama3. This PR removes the usage of context_paralle() context manager and use
_context_parallel_shard()to shard the input data.