Remove activation checkpointing tag to get correct FQNs #124698
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/124698
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (3 Unrelated Failures)As of commit f7dc14e with merge base 7706cd7 ( FLAKY - The following jobs failed but were likely due to flakiness present on trunk:
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Apr 23, 2024
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@Skylion007 @fegin I'm not sure why two of the checks are failing and I can't seem to trigger re-runs. Could I get some assistance with this? |
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@snarayan21 The failures are unrelated and won't block merging. |
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@pytorchbot merge |
Merge failedReason: This PR needs a If not, please add the To add a label, you can comment to pytorchbot, for example For more information, see Details for Dev Infra teamRaised by workflow job |
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@pytorchbot label "topic: not user facing" |
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@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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Apr 24, 2024
Fixes pytorch#124546 When setting `use_orig_params = False` and using activation checkpointing, the FQN mapping as retrieved by the `_get_fqns` function is incorrect because the prefix that is added to the name of each activation checkpointed module, `_checkpoint_wrapped_module`, can still be present. I think this is an edge case with the `_get_fqns` function that was not addressed by this previous commit pytorch#118119. Without the change, the list of object names for an activation checkpointed module with FSDP (and `use_orig_params=False`) can be something like: ``` ['model', '_fsdp_wrapped_module', 'transformer', 'blocks', '0', '_fsdp_wrapped_module', '_checkpoint_wrapped_module', '_flat_param'] ``` Which will incorrectly return just one FQN, `{'model.transformer.blocks.0._flat_param'}`, when all the FQNs of the parameters of the transformer block should be returned. With the change, the list of object names will now have `_checkpoint_wrapped_module` removed: ``` ['model', '_fsdp_wrapped_module', 'transformer', 'blocks', '0', '_fsdp_wrapped_module', '_flat_param'] ``` And the FQNs are correctly retrieved and returned in `_get_fqns` when [this condition](https://github.com/pytorch/pytorch/blob/ea61c9cb299b6dfebc57dc9d8821c34321d568ab/torch/distributed/checkpoint/state_dict.py#L168) is satisfied. The correct FQNs are: ``` {'model.transformer.blocks.0.attn.Wqkv.bias', 'model.transformer.blocks.0.ffn.up_proj.bias', 'model.transformer.blocks.0.attn.out_proj.weight', 'model.transformer.blocks.0.norm_2.weight', 'model.transformer.blocks.0.ffn.down_proj.weight', 'model.transformer.blocks.0.attn.Wqkv.weight', 'model.transformer.blocks.0.norm_2.bias', 'model.transformer.blocks.0.ffn.up_proj.weight', 'model.transformer.blocks.0.ffn.down_proj.bias', 'model.transformer.blocks.0.norm_1.bias', 'model.transformer.blocks.0.norm_1.weight', 'model.transformer.blocks.0.attn.out_proj.bias'} ``` Pull Request resolved: pytorch#124698 Approved by: https://github.com/Skylion007
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carmocca
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Apr 29, 2024
Fixes pytorch#124546 When setting `use_orig_params = False` and using activation checkpointing, the FQN mapping as retrieved by the `_get_fqns` function is incorrect because the prefix that is added to the name of each activation checkpointed module, `_checkpoint_wrapped_module`, can still be present. I think this is an edge case with the `_get_fqns` function that was not addressed by this previous commit pytorch#118119. Without the change, the list of object names for an activation checkpointed module with FSDP (and `use_orig_params=False`) can be something like: ``` ['model', '_fsdp_wrapped_module', 'transformer', 'blocks', '0', '_fsdp_wrapped_module', '_checkpoint_wrapped_module', '_flat_param'] ``` Which will incorrectly return just one FQN, `{'model.transformer.blocks.0._flat_param'}`, when all the FQNs of the parameters of the transformer block should be returned. With the change, the list of object names will now have `_checkpoint_wrapped_module` removed: ``` ['model', '_fsdp_wrapped_module', 'transformer', 'blocks', '0', '_fsdp_wrapped_module', '_flat_param'] ``` And the FQNs are correctly retrieved and returned in `_get_fqns` when [this condition](https://github.com/pytorch/pytorch/blob/ea61c9cb299b6dfebc57dc9d8821c34321d568ab/torch/distributed/checkpoint/state_dict.py#L168) is satisfied. The correct FQNs are: ``` {'model.transformer.blocks.0.attn.Wqkv.bias', 'model.transformer.blocks.0.ffn.up_proj.bias', 'model.transformer.blocks.0.attn.out_proj.weight', 'model.transformer.blocks.0.norm_2.weight', 'model.transformer.blocks.0.ffn.down_proj.weight', 'model.transformer.blocks.0.attn.Wqkv.weight', 'model.transformer.blocks.0.norm_2.bias', 'model.transformer.blocks.0.ffn.up_proj.weight', 'model.transformer.blocks.0.ffn.down_proj.bias', 'model.transformer.blocks.0.norm_1.bias', 'model.transformer.blocks.0.norm_1.weight', 'model.transformer.blocks.0.attn.out_proj.bias'} ``` Pull Request resolved: pytorch#124698 Approved by: https://github.com/Skylion007
andoorve
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May 1, 2024
Fixes pytorch#124546 When setting `use_orig_params = False` and using activation checkpointing, the FQN mapping as retrieved by the `_get_fqns` function is incorrect because the prefix that is added to the name of each activation checkpointed module, `_checkpoint_wrapped_module`, can still be present. I think this is an edge case with the `_get_fqns` function that was not addressed by this previous commit pytorch#118119. Without the change, the list of object names for an activation checkpointed module with FSDP (and `use_orig_params=False`) can be something like: ``` ['model', '_fsdp_wrapped_module', 'transformer', 'blocks', '0', '_fsdp_wrapped_module', '_checkpoint_wrapped_module', '_flat_param'] ``` Which will incorrectly return just one FQN, `{'model.transformer.blocks.0._flat_param'}`, when all the FQNs of the parameters of the transformer block should be returned. With the change, the list of object names will now have `_checkpoint_wrapped_module` removed: ``` ['model', '_fsdp_wrapped_module', 'transformer', 'blocks', '0', '_fsdp_wrapped_module', '_flat_param'] ``` And the FQNs are correctly retrieved and returned in `_get_fqns` when [this condition](https://github.com/pytorch/pytorch/blob/ea61c9cb299b6dfebc57dc9d8821c34321d568ab/torch/distributed/checkpoint/state_dict.py#L168) is satisfied. The correct FQNs are: ``` {'model.transformer.blocks.0.attn.Wqkv.bias', 'model.transformer.blocks.0.ffn.up_proj.bias', 'model.transformer.blocks.0.attn.out_proj.weight', 'model.transformer.blocks.0.norm_2.weight', 'model.transformer.blocks.0.ffn.down_proj.weight', 'model.transformer.blocks.0.attn.Wqkv.weight', 'model.transformer.blocks.0.norm_2.bias', 'model.transformer.blocks.0.ffn.up_proj.weight', 'model.transformer.blocks.0.ffn.down_proj.bias', 'model.transformer.blocks.0.norm_1.bias', 'model.transformer.blocks.0.norm_1.weight', 'model.transformer.blocks.0.attn.out_proj.bias'} ``` Pull Request resolved: pytorch#124698 Approved by: https://github.com/Skylion007
pytorch-bot bot
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May 3, 2024
Fixes #124546 When setting `use_orig_params = False` and using activation checkpointing, the FQN mapping as retrieved by the `_get_fqns` function is incorrect because the prefix that is added to the name of each activation checkpointed module, `_checkpoint_wrapped_module`, can still be present. I think this is an edge case with the `_get_fqns` function that was not addressed by this previous commit #118119. Without the change, the list of object names for an activation checkpointed module with FSDP (and `use_orig_params=False`) can be something like: ``` ['model', '_fsdp_wrapped_module', 'transformer', 'blocks', '0', '_fsdp_wrapped_module', '_checkpoint_wrapped_module', '_flat_param'] ``` Which will incorrectly return just one FQN, `{'model.transformer.blocks.0._flat_param'}`, when all the FQNs of the parameters of the transformer block should be returned. With the change, the list of object names will now have `_checkpoint_wrapped_module` removed: ``` ['model', '_fsdp_wrapped_module', 'transformer', 'blocks', '0', '_fsdp_wrapped_module', '_flat_param'] ``` And the FQNs are correctly retrieved and returned in `_get_fqns` when [this condition](https://github.com/pytorch/pytorch/blob/ea61c9cb299b6dfebc57dc9d8821c34321d568ab/torch/distributed/checkpoint/state_dict.py#L168) is satisfied. The correct FQNs are: ``` {'model.transformer.blocks.0.attn.Wqkv.bias', 'model.transformer.blocks.0.ffn.up_proj.bias', 'model.transformer.blocks.0.attn.out_proj.weight', 'model.transformer.blocks.0.norm_2.weight', 'model.transformer.blocks.0.ffn.down_proj.weight', 'model.transformer.blocks.0.attn.Wqkv.weight', 'model.transformer.blocks.0.norm_2.bias', 'model.transformer.blocks.0.ffn.up_proj.weight', 'model.transformer.blocks.0.ffn.down_proj.bias', 'model.transformer.blocks.0.norm_1.bias', 'model.transformer.blocks.0.norm_1.weight', 'model.transformer.blocks.0.attn.out_proj.bias'} ``` Pull Request resolved: #124698 Approved by: https://github.com/Skylion007
mvpatel2000
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May 17, 2024
Fixes pytorch#124546 When setting `use_orig_params = False` and using activation checkpointing, the FQN mapping as retrieved by the `_get_fqns` function is incorrect because the prefix that is added to the name of each activation checkpointed module, `_checkpoint_wrapped_module`, can still be present. I think this is an edge case with the `_get_fqns` function that was not addressed by this previous commit pytorch#118119. Without the change, the list of object names for an activation checkpointed module with FSDP (and `use_orig_params=False`) can be something like: ``` ['model', '_fsdp_wrapped_module', 'transformer', 'blocks', '0', '_fsdp_wrapped_module', '_checkpoint_wrapped_module', '_flat_param'] ``` Which will incorrectly return just one FQN, `{'model.transformer.blocks.0._flat_param'}`, when all the FQNs of the parameters of the transformer block should be returned. With the change, the list of object names will now have `_checkpoint_wrapped_module` removed: ``` ['model', '_fsdp_wrapped_module', 'transformer', 'blocks', '0', '_fsdp_wrapped_module', '_flat_param'] ``` And the FQNs are correctly retrieved and returned in `_get_fqns` when [this condition](https://github.com/pytorch/pytorch/blob/ea61c9cb299b6dfebc57dc9d8821c34321d568ab/torch/distributed/checkpoint/state_dict.py#L168) is satisfied. The correct FQNs are: ``` {'model.transformer.blocks.0.attn.Wqkv.bias', 'model.transformer.blocks.0.ffn.up_proj.bias', 'model.transformer.blocks.0.attn.out_proj.weight', 'model.transformer.blocks.0.norm_2.weight', 'model.transformer.blocks.0.ffn.down_proj.weight', 'model.transformer.blocks.0.attn.Wqkv.weight', 'model.transformer.blocks.0.norm_2.bias', 'model.transformer.blocks.0.ffn.up_proj.weight', 'model.transformer.blocks.0.ffn.down_proj.bias', 'model.transformer.blocks.0.norm_1.bias', 'model.transformer.blocks.0.norm_1.weight', 'model.transformer.blocks.0.attn.out_proj.bias'} ``` Pull Request resolved: pytorch#124698 Approved by: https://github.com/Skylion007
This was referenced May 17, 2024
atalman
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May 24, 2024
…26559) Fixes #124546 When setting `use_orig_params = False` and using activation checkpointing, the FQN mapping as retrieved by the `_get_fqns` function is incorrect because the prefix that is added to the name of each activation checkpointed module, `_checkpoint_wrapped_module`, can still be present. I think this is an edge case with the `_get_fqns` function that was not addressed by this previous commit #118119. Without the change, the list of object names for an activation checkpointed module with FSDP (and `use_orig_params=False`) can be something like: ``` ['model', '_fsdp_wrapped_module', 'transformer', 'blocks', '0', '_fsdp_wrapped_module', '_checkpoint_wrapped_module', '_flat_param'] ``` Which will incorrectly return just one FQN, `{'model.transformer.blocks.0._flat_param'}`, when all the FQNs of the parameters of the transformer block should be returned. With the change, the list of object names will now have `_checkpoint_wrapped_module` removed: ``` ['model', '_fsdp_wrapped_module', 'transformer', 'blocks', '0', '_fsdp_wrapped_module', '_flat_param'] ``` And the FQNs are correctly retrieved and returned in `_get_fqns` when [this condition](https://github.com/pytorch/pytorch/blob/ea61c9cb299b6dfebc57dc9d8821c34321d568ab/torch/distributed/checkpoint/state_dict.py#L168) is satisfied. The correct FQNs are: ``` {'model.transformer.blocks.0.attn.Wqkv.bias', 'model.transformer.blocks.0.ffn.up_proj.bias', 'model.transformer.blocks.0.attn.out_proj.weight', 'model.transformer.blocks.0.norm_2.weight', 'model.transformer.blocks.0.ffn.down_proj.weight', 'model.transformer.blocks.0.attn.Wqkv.weight', 'model.transformer.blocks.0.norm_2.bias', 'model.transformer.blocks.0.ffn.up_proj.weight', 'model.transformer.blocks.0.ffn.down_proj.bias', 'model.transformer.blocks.0.norm_1.bias', 'model.transformer.blocks.0.norm_1.weight', 'model.transformer.blocks.0.attn.out_proj.bias'} ``` Pull Request resolved: #124698 Approved by: https://github.com/Skylion007 Co-authored-by: Saaketh <narayan.saaketh@gmail.com>
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Fixes #124546
When setting
use_orig_params = Falseand using activation checkpointing, the FQN mapping as retrieved by the_get_fqnsfunction is incorrect because the prefix that is added to the name of each activation checkpointed module,_checkpoint_wrapped_module, can still be present. I think this is an edge case with the_get_fqnsfunction that was not addressed by this previous commit #118119.Without the change, the list of object names for an activation checkpointed module with FSDP (and
use_orig_params=False) can be something like:Which will incorrectly return just one FQN,
{'model.transformer.blocks.0._flat_param'}, when all the FQNs of the parameters of the transformer block should be returned.With the change, the list of object names will now have
_checkpoint_wrapped_moduleremoved:And the FQNs are correctly retrieved and returned in
_get_fqnswhen this condition is satisfied. The correct FQNs are:cc @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @H-Huang @kwen2501 @awgu @penguinwu @fegin @XilunWu @wanchaol @fduwjj @wz337 @tianyu-l @wconstab @yf225 @chauhang @d4l3k @LucasLLC