* 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>
* [fx] metainfo class for auto parallel
* [fx] add unit test for linear metainfo
* [fx] fix bwd param for linear
* [fx] modify unit test
* [fx] modify unit test
* [fx] modify import
* [fx] modify import
* [fx] modify import
* [fx] move meta profiler to auto parallel
* [fx] add conv metainfo class
* [fx] restore profiler
* [fx] restore meta profiler
* [autoparallel] modify unit test
* [fx] modify unit test
* [autoparallel] add batchnorm metainfo class
* [autoparallel] fix batchnorm unit test function declaration
* [fx] restore profiler
* [fx] add relu metainfo class
* [fx] restore profiler
* [autoparallel] modify metainfo input
* [autoparallel] add pooling metainfo
* [autoparallel] add F.linear metainfo generator
* [fx] metainfo class for auto parallel
* [fx] add unit test for linear metainfo
* [fx] fix bwd param for linear
* [fx] modify unit test
* [fx] modify unit test
* [fx] modify import
* [fx] modify import
* [fx] modify import
* [fx] move meta profiler to auto parallel
* [fx] add conv metainfo class
* [fx] restore profiler
* [fx] restore meta profiler
* [autoparallel] modify unit test
* [fx] modify unit test
* [autoparallel] add batchnorm metainfo class
* [autoparallel] fix batchnorm unit test function declaration
* [fx] restore profiler
* [fx] add relu metainfo class
* [fx] restore profiler
* [autoparallel] modify metainfo input
* [autoparallel] add pooling metainfo
* [fx] metainfo class for auto parallel
* [fx] add unit test for linear metainfo
* [fx] fix bwd param for linear
* [fx] modify unit test
* [fx] modify unit test
* [fx] modify import
* [fx] modify import
* [fx] modify import
* [fx] move meta profiler to auto parallel
* [fx] add conv metainfo class
* [fx] restore profiler
* [fx] restore meta profiler
* [autoparallel] modify unit test
* [fx] modify unit test
* [autoparallel] add batchnorm metainfo class
* [autoparallel] fix batchnorm unit test function declaration
* [fx] restore profiler
* [fx] add relu metainfo class
* [fx] restore profiler
* [autoparallel] modify metainfo input
* [fx] metainfo class for auto parallel
* [fx] add unit test for linear metainfo
* [fx] fix bwd param for linear
* [fx] modify unit test
* [fx] modify unit test
* [fx] modify import
* [fx] modify import
* [fx] modify import
* [fx] move meta profiler to auto parallel
* [fx] add conv metainfo class
* [fx] restore profiler
* [fx] restore meta profiler
* [autoparallel] modify unit test
* [fx] modify unit test
* [autoparallel] add batchnorm metainfo class
* [autoparallel] fix batchnorm unit test function declaration
* [fx] restore profiler
* [fx] metainfo class for auto parallel
* [fx] add unit test for linear metainfo
* [fx] fix bwd param for linear
* [fx] modify unit test
* [fx] modify unit test
* [fx] modify import
* [fx] modify import
* [fx] modify import
* [fx] move meta profiler to auto parallel
* [fx] add conv metainfo class
* [fx] restore profiler
* [fx] restore meta profiler
* [autoparallel] modify unit test
* [fx] modify unit test
* [fx] metainfo class for auto parallel
* [fx] add unit test for linear metainfo
* [fx] fix bwd param for linear
* [fx] modify unit test
* [fx] modify unit test
* [fx] modify import
* [fx] modify import
* [fx] modify import
* [fx] move meta profiler to auto parallel
* [autoparallel] add getattr haandler
* polish code
* add extra processes for Parameters
* add unit test for param resharding cost
* add docstring and polish test
* [hotfix] fix zero's incompatibility with checkpoint in torch-1.12
* [zero] add cpu shard init
* [zero] add tiny example test
* [colo_tensor] fix bugs for torch-1.11
* fixes memory leak when paramter is in fp16 in ZeroDDP init.
* bans chunk releasement in CUDA. Only when a chunk is about to offload, it is allowed to release.
* adds a constant placement policy. With it, users can allocate a reserved caching memory space for parameters.
* [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
* [fx] add input activation offload to codegen
* [fx] modify unit test
* [fx] remove two skips in torch11
* [fx] use all_input_nodes instead of _input_nodes
* [fx] add some comment and docstrings.
* [fx] add dataflow analysis for an autograd graph.
* add intepretation for graph analysis.
* [fx] before doing save_tensor_hooks.
* [fx] provide an accurate estimation of memory except for GPT-2.
* [fx] provide an accurate estimation of memory except for GPT-2.
* [fx] provide an accurate estimation of memory except for GPT-2.
* [fx] a very accurate version on GPT-2.
* [fx] refactor code.
* [fx] remove redundant inplace=True.
* [fx] refactor code.
* [fx] refactor code.
* [fx] refactor code.
* [fx] dive into backward memory.
* [fx] fix variable names in ckpt_solvers and unskip tests.
* [fx] commit my changes.
* [fx] restore skips.
* [fx] restore skips.
* [fx] chaange stage into phase.
* [fx] chaange stage into phase.
* [fx] chaange stage into phase.
* [fx] compute memory stat and flop count for MetaInfoProp.
* [fx] modify node attribute.
* [fx] modify ckpt_chen.
* [fx] fix compatibility.
* [fx] fix import error.
* [fx] skip test for MetaInfoProp.
* [fx] skip test for MetaInfoProp.
* [fx] skip test for MetaInfoProp.
* [fx] skip test for MetaInfoProp.
* [fx] skip if torch 1.11.0.
* [fx] recover MetaInfoProp support for PyTorch 1.11.
* [fx] provide a stable but not accurate enough version of profiler.
* [fx] provide a stable but not accurate enough version of profiler.
* [fx] fix compatibility in tests.
* [fx] fix compatibility in tests.
* [fx] fix compatibility in tests.
* [fx] fix compatibility in tests.
* [fx] fix compatibility in tests.
* [fx] fix compatibility in tests.
* [fx] fix compatibility in tests.
* [fx] fix compatibility in tests.
* [fx] fix compatibility in tests.
* [fx] fix compatibility in tests.
* [fx] fix import error.
* 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
* [fx] fix wrong variable name in solver rotor
* [fx] fix wrong variable name in solver rotor
* [fx] fix the discretize bug
* [fx] fix the first op in activation checkpoint codegen
* [fx] fix some bugs of ckpt solver
* [fx] modify test_ckpt_torchvision
* [fx] set sequence to __sequence__ attr of GraphModule
* [fx] docstring modification
* [fx] remove performance test
* 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
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* [fx] merge development into main (#1)
* [fx] activation checkpointing using Chen strategies.
* [fx] add test for ckpt_solver_chen
* [fx] add vanilla activation checkpoint search with test on resnet and densenet
* [fx] add a namespace code for solver_chen.
* [fx] fix the false interpretation of algorithm 3 in https://arxiv.org/abs/1604.06174.
* [fx] fix lowercase naming conventions.
* [fx] simplify test for ckpt.
* [fx] add rules to linearize computation graphs for searching. (#2)
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* [fx] merge development into main (#1)
* [fx] activation checkpointing using Chen strategies.
* [fx] add test for ckpt_solver_chen
* [fx] add vanilla activation checkpoint search with test on resnet and densenet
* [fx] add a namespace code for solver_chen.
* [fx] fix the false interpretation of algorithm 3 in https://arxiv.org/abs/1604.06174.
* [fx] fix lowercase naming conventions.
* [fx] simplify test for ckpt.
* [fx] fix test and algorithm bugs in activation checkpointing.
* [fx] polish ckpt_test.
* [fx] add rules to linearize computation graphs for searching.
* [fx] remove chen_sqrt for sake of simplicity
* [fx] remove chen_sqrt for sake of simplicity
* [fx] remove chen_sqrt for sake of simplicity
* [fx] remove chen_sqrt for sake of simplicity
* [fx] fix inconsistencies.
* [fx] fix MetaInfoProp.
* [fx] fix MetaInfoProp.
* [fx] consider MetaInfoProp for inplace operands.
* [fx] consider MetaInfoProp for inplace operands.
* [fx] consider MetaInfoProp for inplace operands.
* [fx] consider MetaInfoProp for inplace operands.
* [fx] consider MetaInfoProp for inplace operands.
* [fx] add profiler for fx nodes.
* [fx] add profiler for fx nodes.
* [fx] add profiler for fx nodes.
* [fx] add profiler for fx nodes.
* [fx] add profiler for fx nodes.
* [fx] add profiler for fx nodes.
* [fx] add profiler for fx nodes.
* [fx] fix error in tests.
* [fx] unfix bug.
* [fx] unfix bug.
* 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
* 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
* Delete p2p_v2.py
* Delete _pipeline_schedule_v2.py
* Delete test_object_list_p2p_v2.py
* Delete test_boardcast_send_recv_v2.py
* Delete test_cifar_with_data_pipeline_tensor_v2.py
* [utils] Add use_reetrant=False into colossalai checkpoint
* [utils] add some annotation in utils.activaion_checkpoint
* [test] add reset_seed at the beginning of tests in test_actiavion_checkpointing.py
* [test] modify test_activation_checkpoint.py
* [test] modify test for reentrant=False
* [fx] Add use_reentrant=False of checkpoint into codegen
* [utils] Add use_reetrant=False into colossalai checkpoint
* [utils] add some annotation in utils.activaion_checkpoint
* [test] add reset_seed at the beginning of tests in test_actiavion_checkpointing.py
* [test] modify test_activation_checkpoint.py
* [test] modify test for reentrant=False
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* [fx] merge development into main (#1)
* [fx] activation checkpointing using Chen strategies.
* [fx] add test for ckpt_solver_chen
* [fx] add vanilla activation checkpoint search with test on resnet and densenet
* [fx] add a namespace code for solver_chen.
* [fx] fix the false interpretation of algorithm 3 in https://arxiv.org/abs/1604.06174.
* [fx] fix lowercase naming conventions.
* [fx] simplify test for ckpt.
* [fx] fix test and algorithm bugs in activation checkpointing.
* mend
[fx] fix test and algorithm bugs in activation checkpointing.
* mend
[fx] fix test and algorithm bugs in activation checkpointing.
* mend
[fx] fix test and algorithm bugs in activation checkpointing.
* mend
[fx] fix test and algorithm bugs in activation checkpointing.
* [fx] polish ckpt_test.
* [fx] polish ckpt_test.
* [fx] polish ckpt_test.
* [fx] Use colossalai.utils.checkpoint to replace torch.utils.checkpoint for offload activation and add offload annotation recognition in codegen
* [fx] Use colossalai.utils.checkpoint to replace torch.utils.checkpoint for offload activation and add offload annotation recognition in codegen
* Modification of test and add TODO in codegen
* [fx] Modification of colossal ckpt usage
* [fx] add gpc.destroy() to test_codegen
* support p2p communication with any type of object | pass test
* reconstruct pipeline schedule with p2p_v2.py(support communication with List[Any]) | pass test
* [communication] add p2p_v2.py to support communication with List[Any]
* Delete _pipeline_schedule_v2.py
* Delete test_cifar_with_data_pipeline_tensor_v2.py
* [engin/schedule] use p2p_v2 to recontruct pipeline_schedule
* [engin/schedule] use p2p_v2 to recontruct pipeline_schedule
* [engin/schedule] use p2p_v2 to recontruct pipeline_schedule
* [engin/schedule] use p2p_v2 to recontruct pipeline_schedule
* [engin/schedule] use p2p_v2 to recontruct pipeline_schedule
* Delete p2p_v2.py
* Delete test_boardcast_send_recv_v2.py
* Delete test_object_list_p2p_v2.py
* [engin/schedule] use p2p_v2 to recontruct pipeline_schedule
* [communication] remove print code
* [communication] remove print code
* [engin/schedule] shorten the running time of testing file to prevent cancelling in CI
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* [fx] activation checkpointing using Chen strategies.
* [fx] add test for ckpt_solver_chen
* mend
* [fx] add vanilla activation checkpoint search with test on resnet and densenet
* [fx] add vanilla activation checkpoint search with test on resnet and densenet
* [fx] add a namespace code for solver_chen.
* [fx] fix the false interpretation of algorithm 3 in https://arxiv.org/abs/1604.06174.
* [fx] fix lowercase naming conventions.
* [fx] activation checkpointing using Chen strategies.
* [fx] add test for ckpt_solver_chen
* [fx] add vanilla activation checkpoint search with test on resnet and densenet
* [fx] add vanilla activation checkpoint search with test on resnet and densenet
* [fx] add a namespace code for solver_chen.
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* [fx] modify the calculation of node_size in MetaInfoProp for activation checkpointing usages
* support p2p communication with any type of object | pass test
* reconstruct pipeline schedule with p2p_v2.py(support communication with List[Any]) | pass test
* [communication] add p2p_v2.py to support communication with List[Any]
* Delete _pipeline_schedule_v2.py
* Delete test_cifar_with_data_pipeline_tensor_v2.py
* [engin/schedule] use p2p_v2 to recontruct pipeline_schedule
* [communication] remove print code
* [communication] remove print code
Jiarui Fang