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* Load balanced offloading algorithm
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---------
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fix tp_size for GQA
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

This bug will cause bug [ERROR] failed (exitcode: -11) local_rank: 0 (pid: 1761020) of binary: ~/megatron/bin/python.

That is because we miss the rng_states that is required in attention recompute (for dropout), but no hint is provided.  

It is very very very difficult to trace and cost me two weeks.

```python
before the start of training step] datetime: 2024-07-22 18:26:45 
[2024-07-22 18:27:00,941] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: -11) local_rank: 0 (pid: 1761020) of binary: /home//miniconda3/envs/megatron/bin/python
Traceback (most recent call last):
  File "/home//miniconda3/envs/megatron/bin/torchrun", line 33, in <module>
    sys.exit(load_entry_point('torch==2.2.1+cu121', 'console_scripts', 'torchrun')())
  File "/home//miniconda3/envs/megatron/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
    return f(*args, **kwargs)
  File "/home//miniconda3/envs/megatron/lib/python3.10/site-packages/torch/distributed/run.py", line 812, in main
    run(args)
  File "/home//miniconda3/envs/megatron/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/home//miniconda3/envs/megatron/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home//miniconda3/envs/megatron/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 268, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
```
Signed-off-by: 李金梁 <975761915@qq.com>

* Specify python version
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* Add classifiers for python
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* Add aarch
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* Fixes
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* Fix paddle wheel
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* PaddlePaddle only builds for x86
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* Add optional fwk deps
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* Python3.8; catch install error
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* [wip] cudnn9 compile with paddle support
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* [wip] dont link cudnn
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* dlopen cudnn
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* fixes
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* fix
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* Fixes
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* fix
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* dynamically load nvrtc
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* Fix workflow paddle build
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* Fix paddle
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* Fix paddle
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* fix
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* fixes
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* CLeanup, remove residual code
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Fix linter warnings
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[PyTorch] Fixing hang in `initialize_ub()` for multi-node runs after PR901 removal of MPI-dependence (#986)

* Re-implementing PR901 (removing MPI-dependence in Userbuffers) with multi-node fixes

* passing data-parallel rank/size info from torch.distributed to userbuffers
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* multi-node example working with UB_SKIPMC=1 but not with multicast
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* fixed multi-node hang in initialize_ub(), updated comm+GEMM overlap example to support multi-node mixed tensor/data parallelism, added README
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* fixed use case when Userbuffers is asked to allocate the TP overlap buffer with UB_SKIPMC=1
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* corrected example problem to set device by local ordinal instead of global process rank
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* double-free fix in userbuffers destructor
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* removed unnecessary and incorrect torch.cuda.set_device(...)
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* corrected inter-node ranks logic
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* generalized node ID logic in initialize_ub to handle arbitrary world rank layouts within node
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* added single-node comm+GEMM overlap unit tests
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* LayerNormMLP example confirmed working with 2 nodes on Eos
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* unit test cleanup
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* corrected DP group ranks logic in LNMLP comm+GEMM overlap example
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* corrected enums in unit test
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* fixed incorrect Ubuf object init signature
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* switched default backend for Userbuffer bootstrapping to Gloo with MPI and NCCL fallbacks, and initialize_ub option to manually select backend
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* fixed all comm+GEMM overlap unit tests
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* corrected all_gather use for Gloo backend
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* changed userbuffers allgather callback to always use all_gather() instead of all_gather_into_tensor()
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* restored and verified old MPI-based bootstrapping via NVTE_UB_WITH_MPI=1 option at compile time
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* disabled scoped GIL release for comm+GEMM overlap algorithms
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* avoid dist.init_device_mesh in comm+GEMM overlap example to support older PyTorch versions
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* applied RS overlap FP8 fix from PR1004
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* fixed segfault in Userbuffers destructor
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* corrected comm+GEMM overlap unit test arguments
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* fixed unit test run command for when Userbuffers is compiled with MPI
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* Refactored torch.distributed collectives into pure C++ callbacks
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* removed unwanted memcpyDtoD/fixed weight parametrisation
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---------
Signed-off-by: Selvaraj Anandaraj <selvaraja@login-eos02.eos.clusters.nvidia.com>
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* Fixed convergence issues
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* Update transformer_engine/pytorch/module/layernorm_linear.py
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* Update transformer_engine/pytorch/module/layernorm_mlp.py
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* Update transformer_engine/pytorch/module/linear.py
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* Update sequential container constructor to handle modules in plain dicts
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* Avoid initializing Sequential with dicts
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---------
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* initialize output tensors to 0 for THD while waiting for cuDNN bug fix
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* move fill_() to F16 loop
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* fix fused_attn_bwd()
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* use nvtx3 instead
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* FP8 type switch macro now wraps only the FP8 kernel to avoid invalid type errors
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* DGRAD_RS UB overlap Bug fixes
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* Add option to pass kwargs to CUDA graph module
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* Debug unit tests
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* add cuDNN swa
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* Add linear op
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* Review suggestions from @sudhakarsingh27 and @ksivaman

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Build for python < 3.8
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* remove implicit padding and unpadding
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