* [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>
* [npu] setup device utils (#5047)
* [npu] add npu device support
* [npu] support low level zero
* [test] update npu zero plugin test
* [hotfix] fix import
* [test] recover tests
* [npu] gemini support npu (#5052)
* [npu] refactor device utils
* [gemini] support npu
* [example] llama2+gemini support npu
* [kernel] add arm cpu adam kernel (#5065)
* [kernel] add arm cpu adam
* [optim] update adam optimizer
* [kernel] arm cpu adam remove bf16 support
* Use p2p
* Cannot bidirectonal send p2p
* Refactor tensor creation and serialization in P2P
communication
* Fix llama forward args in flash attention
* Add flop estimate from megatron
* Support loading weight not in weight_map when strict=False in hybrid_parallel
* Use send_forward_recv_backward, etc in 1f1b
* Use dataclass for metdata
Remove torch.cuda.synchronize() as suggested
* Add comment about the torch.cuda.synchronize for potential error
* Typo
* Update hybrid_parallel_checkpoint_io.py
* Update p2p.py
* Update one_f_one_b.py
* Update p2p.py
---------
Co-authored-by: flybird11111 <1829166702@qq.com>
* [pipeline inference] pipeline inference (#4492)
* add pp stage manager as circle stage
* fix a bug when create process group
* add ppinfer basic framework
* add micro batch manager and support kvcache-pp gpt2 fwd
* add generate schedule
* use mb size to control mb number
* support generate with kv cache
* add output, remove unused code
* add test
* reuse shardformer to build model
* refactor some code and use the same attribute name of hf
* fix review and add test for generation
* remove unused file
* fix CI
* add cache clear
* fix code error
* fix typo
* [Pipeline inference] Modify to tieweight (#4599)
* add pp stage manager as circle stage
* fix a bug when create process group
* add ppinfer basic framework
* add micro batch manager and support kvcache-pp gpt2 fwd
* add generate schedule
* use mb size to control mb number
* support generate with kv cache
* add output, remove unused code
* add test
* reuse shardformer to build model
* refactor some code and use the same attribute name of hf
* fix review and add test for generation
* remove unused file
* modify the way of saving newtokens
* modify to tieweight
* modify test
* remove unused file
* solve review
* add docstring
* [Pipeline inference] support llama pipeline inference (#4647)
* support llama pipeline inference
* remove tie weight operation
* [pipeline inference] Fix the blocking of communication when ppsize is 2 (#4708)
* add benchmark verbose
* fix export tokens
* fix benchmark verbose
* add P2POp style to do p2p communication
* modify schedule as p2p type when ppsize is 2
* remove unused code and add docstring
* [Pipeline inference] Refactor code, add docsting, fix bug (#4790)
* add benchmark script
* update argparse
* fix fp16 load
* refactor code style
* add docstring
* polish code
* fix test bug
* [Pipeline inference] Add pipeline inference docs (#4817)
* add readme doc
* add a ico
* Add performance
* update table of contents
* refactor code (#4873)
* [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
* 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
* fixed version
* fixed version
* pure 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 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>
* use Topo class to rewrite DAG
* polish code
* polish code
* polish code
* add comment
* add else to unended if
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/fix-bug] num_microbatches support any integrate | stable chimera | launch tool for rpc pp framework
* [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/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
Wenhao Chen