* 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
Frank Lee