* Use self.[distribute_layers|get_stage_index] to exploit custom layer distribution
* Change static methods for t5 layer distribution to member functions
* Change static methods for whisper layer distribution to member functions
* Replace whisper policy usage with self one
* Fix test case to use non-static layer distribution methods
* fix: fix typo
---------
Co-authored-by: Wenhao Chen <cwher@outlook.com>
* fix: simplify merge_batch
* fix: use return_outputs=False to eliminate extra memory consumption
* feat: add return_outputs warning
* style: remove `return_outputs=False` as it is the default value
* A more general _communicate
* feat: finish tree_flatten version p2p
* fix: update p2p api calls
---------
Co-authored-by: Wenhao Chen <cwher@outlook.com>
* test: add more p2p tests
* fix: remove send_forward_recv_forward as p2p op list need to use the same group
* fix: make send and receive atomic
* feat: update P2PComm fn
* feat: add metadata cache in 1f1b
* feat: add metadata cache in interleaved pp
* feat: modify is_xx_stage fn
* revert: add _broadcast_object_list
* feat: add interleaved pp in llama policy
* feat: set NCCL_BUFFSIZE in HybridParallelPlugin
* [shardformer] implement policy for all GPT-J models and test
* [shardformer] support interleaved pipeline parallel for bert finetune
* [shardformer] shardformer support falcon (#4883)
* [shardformer]: fix interleaved pipeline for bert model (#5048)
* [hotfix]: disable seq parallel for gptj and falcon, and polish code (#5093)
* Add Mistral support for Shardformer (#5103)
* [shardformer] add tests to mistral (#5105)
---------
Co-authored-by: Pengtai Xu <henryxu880@gmail.com>
Co-authored-by: ppt0011 <143150326+ppt0011@users.noreply.github.com>
Co-authored-by: flybird11111 <1829166702@qq.com>
Co-authored-by: eric8607242 <e0928021388@gmail.com>
* [legacy] move communication to legacy (#4640)
* [legacy] refactor logger and clean up legacy codes (#4654)
* [legacy] make logger independent to gpc
* [legacy] make optim independent to registry
* [legacy] move test engine to legacy
* [legacy] move nn to legacy (#4656)
* [legacy] move nn to legacy
* [checkpointio] fix save hf config
* [test] remove useledd rpc pp test
* [legacy] fix nn init
* [example] skip tutorial hybriad parallel example
* [devops] test doc check
* [devops] test doc check
* refactor tests
* refactor bloom model
* finish policy tests
* refactor tests
* fix test pure pipeline
* remove test pipeline and cutdown launch process
* refactor tests
* refactor bloom model
* finish policy tests
* refactor tests
* fix test pure pipeline
* remove test pipeline and cutdown launch process
* opt forward and test
* pause
* finish opt model pipeline
* finish opt pipeline
* opt forward and test
* pause
* finish opt model pipeline
* finish opt pipeline
* fix opt
* set transformers version
* refactor the test pipeline
* bloom policy
* llama pipeline forward and tests
* fix the output and attention_mask
* fix name
* bind argument to policy
* Revert "bloom policy"
This reverts commit 8dee68a0a2.
This policy should be revert and copied to feature/bloom
* revert the bloom changes
* cancel unneeded inputs
* gpt
* finish llama
* causal lm and sequence classification
* revision
* add pure pipeline test
* finish some bert models
* finish all bert models
* finish bert tests
* fix bugs
* fix bugs
* fix test pipeline
* fix data gen for qa
* update the set pipeline forward
* shared params
* fix bugs
* add pipeline policy and bert forward to be done
* add bertmodel pipeline forward and make tests
* add Bert_Policy and test for policy
* update formatting
* update formatting
* update the code
* fix bugs
* fix name confilt
* add bloom model and policy ,revise the base class of policy
* revise
* revision
* add bert_for_pretraining
* add bert_for_pretraining forward and policy
* fix typos
* cancel warning
* change the imediate output to default dict
* change the default output of get_shared_params
* add pipeline policy and bert forward to be done
* add bertmodel pipeline forward and make tests
* add Bert_Policy and test for policy
* update formatting
* update formatting
* update the code
* fix bugs
* fix name confilt
* add bloom model and policy ,revise the base class of policy
* revise
* revision
* add bert_for_pretraining
* add pipeline policy and bert forward to be done
* add bertmodel pipeline forward and make tests
* add Bert_Policy and test for policy
* update formatting
* update formatting
* update the code
* fix bugs
* fix name confilt
* add pipeline policy and bert forward to be done
* add bertmodel pipeline forward and make tests
* add Bert_Policy and test for policy
* update formatting
* update formatting
* update the code
* fix bugs
* fix name confilt
* add DAG test case
* fix datarace by adjusting theposition of lock
* polish code
* fix pytest for middleware
* remove test
Co-authored-by: Ziyue Jiang <ziyue.jiang@gmail.com>
* add DAG to split_module
* add comment
* add test case for DAG
* remove print
* add DAG middleware in scheduler
* add test case for scheduler
* remove break
* recover old lifecycle
Co-authored-by: Ziyue Jiang <ziyue.jiang@gmail.com>
* [pipeline/tuning] improve dispatch performance both time and space cost
* [pipeline/converge] add interface for testing convergence
* [NFC] polish colossalai/utils/multi_tensor_apply/multi_tensor_apply.py code style
* Update PipelineBase.py
* [pipeline/chimera] reconstruct PipelineBase and Worker to support more feasible custom schedule | finish Chimera
* [pipeline/chimera] test chimera | fix bug of initializing
* [pipeline/pytree] add pytree to process args and kwargs | provide to process args and kwargs after forward
* [pipeline/tuning] improve dispatch performance both time and space cost
* [pipeline/converge] add interface for testing convergence
* [NFC] polish colossalai/utils/multi_tensor_apply/multi_tensor_apply.py code style
* Update PipelineBase.py
* [pipeline/chimera] reconstruct PipelineBase and Worker to support more feasible custom schedule | finish Chimera
* [pipeline/chimera] test chimera | fix bug of initializing
* [pipeline/tuning] improve dispatch performance both time and space cost
* [pipeline/converge] add interface for testing convergence
* [NFC] polish colossalai/utils/multi_tensor_apply/multi_tensor_apply.py code style
* Update PipelineBase.py
* [pipeline/chimera] reconstruct PipelineBase and Worker to support more feasible custom schedule | finish Chimera
* support p2p communication with any type of object | pass test
* reconstruct pipeline schedule with p2p_v2.py(support communication with List[Any]) | pass test
* [engin/schedule] use p2p_v2 to recontruct pipeline_schedule
* [pipeline/rpc] implement a demo for PP with cuda rpc framework
* [pipeline/rpc] support interleaving | fix checkpoint bug | change logic when dispatch data in work_list to ensure steady 1F1B
* [pipeline/rpc] implement distributed optimizer | test with assert_close
* [pipeline/rpc] implement distributed optimizer | test with assert_close
* [pipeline/rpc] update outstanding mechanism | optimize dispatching strategy
* [pipeline/rpc] update outstanding mechanism | optimize dispatching strategy
* [pipeline/rpc] update outstanding mechanism | optimize dispatching strategy
* [pipeline/pipleline_process_group] finish PipelineProcessGroup to manage local abd global rank in TP,DP and PP
* [pipeline/pipleline_process_group] remove comment
* [pipeline/pipleline_process_group] remove comment
* [pipeline/pipleline_process_group] skip process group test
* [pipeline/pipleline_process_group] remove test named function
* support p2p communication with any type of object | pass test
* reconstruct pipeline schedule with p2p_v2.py(support communication with List[Any]) | pass test
* [engin/schedule] use p2p_v2 to recontruct pipeline_schedule
* [pipeline/rpc] implement a demo for PP with cuda rpc framework
* [pipeline/rpc] support interleaving | fix checkpoint bug | change logic when dispatch data in work_list to ensure steady 1F1B
* [pipeline/rpc] implement distributed optimizer | test with assert_close
* [pipeline/rpc] implement distributed optimizer | test with assert_close
* [pipeline/rpc] update outstanding mechanism | optimize dispatching strategy
* [pipeline/rpc] update outstanding mechanism | optimize dispatching strategy
* [pipeline/rpc] update outstanding mechanism | optimize dispatching strategy
* support p2p communication with any type of object | pass test
* reconstruct pipeline schedule with p2p_v2.py(support communication with List[Any]) | pass test
* [engin/schedule] use p2p_v2 to recontruct pipeline_schedule
* [pipeline/rpc] implement a demo for PP with cuda rpc framework
* [pipeline/rpc] support interleaving | fix checkpoint bug | change logic when dispatch data in work_list to ensure steady 1F1B
* [pipeline/rpc] implement distributed optimizer | test with assert_close
* [pipeline/rpc] implement distributed optimizer | test with assert_close
Wenhao Chen