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[FSDP][Replicate] tests replicate runs forward/backward for root and non-root module #162654
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…non-root module [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/162654
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 2568bdd with merge base 0819de4 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
…r root and non-root module" **Summary:** Verifies that Replicate correctly handles the scenario where forward and backward passes are run through both the root module and a non-root module. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_non_root_forward_backward cc H-Huang awgu wanchaol fegin fduwjj wz337 wconstab d4l3k pragupta ezyang msaroufim dcci [ghstack-poisoned]
…r root and non-root module" **Summary:** Verifies that Replicate correctly handles the scenario where forward and backward passes are run through both the root module and a non-root module. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_non_root_forward_backward cc H-Huang awgu wanchaol fegin fduwjj wz337 wconstab d4l3k pragupta ezyang msaroufim dcci [ghstack-poisoned]
…r root and non-root module" **Summary:** Verifies that Replicate correctly handles the scenario where forward and backward passes are run through both the root module and a non-root module. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_non_root_forward_backward cc H-Huang awgu wanchaol fegin fduwjj wz337 wconstab d4l3k pragupta ezyang msaroufim dcci [ghstack-poisoned]
@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 |
…iple times in a forward pass (#162656) **Summary:** Verifies that Replicate works correctly when a module is used multiple times in a single forward pass. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_multi_forward_module Pull Request resolved: #162656 Approved by: https://github.com/mori360 ghstack dependencies: #162631, #162636, #162650, #162654
**Summary:** Prefetching tests validate that distributed training systems can correctly overlap communication and computation by pre-loading parameters or data before they're needed. This test ensures the prefetching mechanism doesn't break training correctness while potentially improving performance by reducing idle time where computation waits for communication to complete. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_explicit_prefetching Pull Request resolved: #162658 Approved by: https://github.com/mori360 ghstack dependencies: #162631, #162636, #162650, #162654, #162656
…tes (#162785) **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. Verify replicate correctly handles post-optimizer events. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_post_optim_event Pull Request resolved: #162785 Approved by: https://github.com/mori360 ghstack dependencies: #162631, #162636, #162650, #162654, #162656, #162658
…non-root module (pytorch#162654) **Summary:** Verifies that Replicate correctly handles the scenario where forward and backward passes are run through both the root module and a non-root module. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_non_root_forward_backward Pull Request resolved: pytorch#162654 Approved by: https://github.com/mori360 ghstack dependencies: pytorch#162631, pytorch#162636, pytorch#162650
…iple times in a forward pass (pytorch#162656) **Summary:** Verifies that Replicate works correctly when a module is used multiple times in a single forward pass. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_multi_forward_module Pull Request resolved: pytorch#162656 Approved by: https://github.com/mori360 ghstack dependencies: pytorch#162631, pytorch#162636, pytorch#162650, pytorch#162654
**Summary:** Prefetching tests validate that distributed training systems can correctly overlap communication and computation by pre-loading parameters or data before they're needed. This test ensures the prefetching mechanism doesn't break training correctness while potentially improving performance by reducing idle time where computation waits for communication to complete. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_explicit_prefetching Pull Request resolved: pytorch#162658 Approved by: https://github.com/mori360 ghstack dependencies: pytorch#162631, pytorch#162636, pytorch#162650, pytorch#162654, pytorch#162656
…tes (pytorch#162785) **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. Verify replicate correctly handles post-optimizer events. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_post_optim_event Pull Request resolved: pytorch#162785 Approved by: https://github.com/mori360 ghstack dependencies: pytorch#162631, pytorch#162636, pytorch#162650, pytorch#162654, pytorch#162656, pytorch#162658
…non-root module (pytorch#162654) **Summary:** Verifies that Replicate correctly handles the scenario where forward and backward passes are run through both the root module and a non-root module. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_non_root_forward_backward Pull Request resolved: pytorch#162654 Approved by: https://github.com/mori360 ghstack dependencies: pytorch#162631, pytorch#162636, pytorch#162650
…iple times in a forward pass (pytorch#162656) **Summary:** Verifies that Replicate works correctly when a module is used multiple times in a single forward pass. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_multi_forward_module Pull Request resolved: pytorch#162656 Approved by: https://github.com/mori360 ghstack dependencies: pytorch#162631, pytorch#162636, pytorch#162650, pytorch#162654
**Summary:** Prefetching tests validate that distributed training systems can correctly overlap communication and computation by pre-loading parameters or data before they're needed. This test ensures the prefetching mechanism doesn't break training correctness while potentially improving performance by reducing idle time where computation waits for communication to complete. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_explicit_prefetching Pull Request resolved: pytorch#162658 Approved by: https://github.com/mori360 ghstack dependencies: pytorch#162631, pytorch#162636, pytorch#162650, pytorch#162654, pytorch#162656
…tes (pytorch#162785) **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. Verify replicate correctly handles post-optimizer events. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_post_optim_event Pull Request resolved: pytorch#162785 Approved by: https://github.com/mori360 ghstack dependencies: pytorch#162631, pytorch#162636, pytorch#162650, pytorch#162654, pytorch#162656, pytorch#162658
…non-root module (pytorch#162654) **Summary:** Verifies that Replicate correctly handles the scenario where forward and backward passes are run through both the root module and a non-root module. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_non_root_forward_backward Pull Request resolved: pytorch#162654 Approved by: https://github.com/mori360 ghstack dependencies: pytorch#162631, pytorch#162636, pytorch#162650
…iple times in a forward pass (pytorch#162656) **Summary:** Verifies that Replicate works correctly when a module is used multiple times in a single forward pass. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_multi_forward_module Pull Request resolved: pytorch#162656 Approved by: https://github.com/mori360 ghstack dependencies: pytorch#162631, pytorch#162636, pytorch#162650, pytorch#162654
**Summary:** Prefetching tests validate that distributed training systems can correctly overlap communication and computation by pre-loading parameters or data before they're needed. This test ensures the prefetching mechanism doesn't break training correctness while potentially improving performance by reducing idle time where computation waits for communication to complete. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_explicit_prefetching Pull Request resolved: pytorch#162658 Approved by: https://github.com/mori360 ghstack dependencies: pytorch#162631, pytorch#162636, pytorch#162650, pytorch#162654, pytorch#162656
…tes (pytorch#162785) **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. Verify replicate correctly handles post-optimizer events. **Test Cases** 1. pytest test/distributed/_composable/test_replicate_training.py -k test_post_optim_event Pull Request resolved: pytorch#162785 Approved by: https://github.com/mori360 ghstack dependencies: pytorch#162631, pytorch#162636, pytorch#162650, pytorch#162654, pytorch#162656, pytorch#162658
Summary: Verifies that Replicate correctly handles the scenario where forward and backward passes are run through both the root module and a non-root module.
Test Cases
Stack from ghstack (oldest at bottom):
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @pragupta @ezyang @msaroufim @dcci