[FSDP][Replicate] tests replicate parity for shared parameters #162836
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This was referenced Sep 12, 2025
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/162836
Note: Links to docs will display an error until the docs builds have been completed. ❗ 1 Active SEVsThere are 1 currently active SEVs. If your PR is affected, please view them below: ✅ No FailuresAs of commit 8e2c2d3 with merge base 77b9aac ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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This was referenced Sep 12, 2025
…ters" cc H-Huang awgu wanchaol fegin fduwjj wz337 wconstab d4l3k pragupta ezyang msaroufim dcci [ghstack-poisoned]
…ters" cc H-Huang awgu wanchaol fegin fduwjj wz337 wconstab d4l3k pragupta ezyang msaroufim dcci [ghstack-poisoned]
This was referenced Sep 12, 2025
…ters" cc H-Huang awgu wanchaol fegin fduwjj wz337 wconstab d4l3k pragupta ezyang msaroufim dcci [ghstack-poisoned]
…ters" cc H-Huang awgu wanchaol fegin fduwjj wz337 wconstab d4l3k pragupta ezyang msaroufim dcci [ghstack-poisoned]
mori360
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Sep 25, 2025
…ters" cc H-Huang awgu wanchaol fegin fduwjj wz337 wconstab d4l3k pragupta ezyang msaroufim dcci [ghstack-poisoned]
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Sep 29, 2025
Pull Request resolved: #162836 Approved by: https://github.com/mori360 ghstack dependencies: #162830
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…obatching (#162839) **Summary:** In order to ensure that replicate acts as intended (a specialized version of hsdp) we need to make sure that it can pass the same tests that fully_shard can for training. The first test verifies Replicate works with gradient accumulation properly. The second verifies that replicate works correctly with a One-Forward-One-Backward (1F1B) pipeline parallelism schedule **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_gradient_accumulation 2. pytest test/distributed/_composable/test_replicate_training.py -k test_1f1b_microbatching Pull Request resolved: #162839 Approved by: https://github.com/mori360 ghstack dependencies: #162830, #162836
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**Summary: tests replicate works when users use custom forward methods** **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_register_fsdp_forward_method Pull Request resolved: #162851 Approved by: https://github.com/mori360 ghstack dependencies: #162830, #162836, #162839
pytorchmergebot
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…sion (#162855) **Summary:** Ensures that replicate functionality works the same as fully shard's when mixed precision is used **Test Cases** 1. pytest test/distributed/_composable/test_replicate_mixed_precision.py -k TestReplicateMixedPrecisionTraining Pull Request resolved: #162855 Approved by: https://github.com/mori360 ghstack dependencies: #162830, #162836, #162839, #162851, #162853
pytorchmergebot
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…s in mixed precision (#162861) **Summary:** Ensures that replicate can handle the same type casting behavior and edge cases that fully shard can when mixed precision is used **Test Cases** 1. pytest test/distributed/_composable/test_replicate_mixed_precision.py -k test_float16_on_one_submodule 2. pytest test/distributed/_composable/test_replicate_mixed_precision.py -k test_submodules_with_external_inputs 3. pytest test/distributed/_composable/test_replicate_mixed_precision.py -k test_norm_modules_bf16 4. pytest test/distributed/_composable/test_replicate_mixed_precision.py -k test_norm_modules_fp16 5. pytest test/distributed/_composable/test_replicate_mixed_precision.py -k test_clamp_reduce_dtype 6. pytest test/distributed/_composable/test_replicate_mixed_precision.py -k test_dataclass_input Pull Request resolved: #162861 Approved by: https://github.com/mori360 ghstack dependencies: #162830, #162836, #162839, #162851, #162853, #162855
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cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @pragupta @ezyang @msaroufim @dcci