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} | * remove 8x3b recipes
* remove 8x3b from test_nemo_run
* rm from __init__
---------
# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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"## Fix\n\nIn the `model_config.yaml` of the .nemo checkpoint downloaded from [Hugging Face](https://huggingface.co/nvidia/Minitron-4B-Base), the `tensor_model_parallel_size` is set to 4:\n\n```\ntensor_model_parallel_size: 4\n```\n\nIf you untar the `.nemo` checkpoint, change the value of `tensor_model_parallel_size` to 1 and then retar the .nemo checkpoint, it will allow the `merge_lora_weights/merge.py` script to work with a single GPU. \n\n### Steps\n1. Untar the nemo checkpoint\n```sh\ntar -xf minitron-4b-base.nemo\n```\n\n2. Move the original checkpoint to a safe location to avoid needing to redownload if something goes wrong and to get it out of the way for running tar later\n`mv minitron-4b-base.nemo ../`\n\n3. Modify `tensor_model_parallel_size` \n```sh\nvim model_config.yaml\n```\n\n```diff\nmcore_gpt: true\nmicro_batch_size: 4\nglobal_batch_size: 1152\n-- tensor_model_parallel_size: 4\n++ tensor_model_parallel_size: 1\npipeline_model_parallel_size: 1\nvirtual_pipeline_model_parallel_size: null\nencoder_seq_length: 4096\nmax_position_embeddings: 4096\nnum_layers: 32\nhidden_size: 3072\n...\n```\n\n4. Rebuild the nemo checkpoint (tar everything in this directory)\n```sh\ntar -cvf minitron-4b-base.nemo *\n```\n\n",
"This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 7 days.",
"This issue was closed because it has been inactive for 7 days since being marked as stale."
] | 2024-10-07T15:04:35 | 2024-11-17T02:05:18 | 2024-11-17T02:05:17 | NONE | {
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} | null | null | null | **Describe the bug**
When running `merge_lora_weights/merge.py` with TP and PP set to 1 on a fine-tuned minitron checkpoint, I run into the following error:
```sh
raise RuntimeError(f"world_size ({world_size}) is not divisible by {total_model_size}")
[rank0]: RuntimeError: world_size (1) is not divisible by 4
```
The world size should be 1 because the node I'm using only has a single A100 GPU, however, it is unclear why it's trying to split by 4.
Link to `parallel_state.py` where the error is raised: https://github.com/NVIDIA/Megatron-LM/blob/73e7b58e79df9da521ff31d74053579b7a060c7e/megatron/core/parallel_state.py#L531
**Full Traceback**
```python-traceback
(base) [ema8@node0414 syn_data_PEFT_exp]$ sh merge_lora_weights.sh
15:4: not a valid test operator:
15:4: not a valid test operator: 12.5
21:4: not a valid test operator: (
21:4: not a valid test operator: 550.54.15
rm: cannot remove '/usr/local/cuda/compat/lib': Read-only file system
[NeMo W 2024-10-07 10:34:46 nemo_logging:349] /opt/megatron-lm/megatron/core/tensor_parallel/layers.py:289: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.
def forward(ctx, input, weight, bias, allreduce_dgrad):
[NeMo W 2024-10-07 10:34:46 nemo_logging:349] /opt/megatron-lm/megatron/core/tensor_parallel/layers.py:300: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.
def backward(ctx, grad_output):
[NeMo W 2024-10-07 10:34:46 nemo_logging:349] /opt/megatron-lm/megatron/core/tensor_parallel/layers.py:392: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.
def forward(
[NeMo W 2024-10-07 10:34:46 nemo_logging:349] /opt/megatron-lm/megatron/core/tensor_parallel/layers.py:432: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.
def backward(ctx, grad_output):
[NeMo W 2024-10-07 10:34:47 nemo_logging:349] /opt/megatron-lm/megatron/core/dist_checkpointing/strategies/torch.py:17: DeprecationWarning: `torch.distributed._sharded_tensor` will be deprecated, use `torch.distributed._shard.sharded_tensor` instead
from torch.distributed._sharded_tensor import ShardedTensor as TorchShardedTensor
[NeMo W 2024-10-07 10:34:48 nemo_logging:349] /opt/megatron-lm/megatron/core/transformer/attention.py:29: DeprecationWarning: The 'megatron.core.transformer.custom_layers.transformer_engine'
module is deprecated and will be removed in 0.10.0. Please use
'megatron.core.extensions.transformer_engine' instead.
from megatron.core.transformer.custom_layers.transformer_engine import SplitAlongDim
[NeMo W 2024-10-07 10:34:49 nemo_logging:349] /opt/NeMo/nemo/collections/nlp/models/language_modeling/megatron_base_prompt_learning_model.py:181: DeprecationWarning: invalid escape sequence '\{'
"prompt_template_fields": re.findall("\{(.*?)\}", task.prompt_template),
[NeMo W 2024-10-07 10:34:49 nemo_logging:349] /opt/NeMo/nemo/collections/nlp/models/language_modeling/megatron_base_model.py:389: DeprecationWarning: invalid escape sequence '\.'
return re.fullmatch("[0-9][0-9]\.[0-9][0-9].*", nvidia_torch_version) # "YY.MM.*"
[NeMo W 2024-10-07 10:34:49 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/modelopt/torch/quantization/tensor_quant.py:168: FutureWarning: `torch.library.impl_abstract` was renamed to `torch.library.register_fake`. Please use that instead; we will remove `torch.library.impl_abstract` in a future version of PyTorch.
quantize_op_abstract = torch.library.impl_abstract("tensorrt::quantize_op")(
[NeMo W 2024-10-07 10:34:50 nemo_logging:349] /opt/NeMo/nemo/collections/nlp/modules/common/megatron/vocab_parallel_cross_entropy.py:88: DeprecationWarning: invalid escape sequence '\s'
"""
[NeMo W 2024-10-07 10:34:51 nemo_logging:349] /opt/NeMo/nemo/collections/asr/parts/utils/wfst_utils.py:1328: DeprecationWarning: invalid escape sequence '\d'
width, height = re.findall('\d+', line)
[NeMo W 2024-10-07 10:34:51 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/pyannote/core/notebook.py:134: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed in 3.11. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap()`` or ``pyplot.get_cmap()`` instead.
cm = get_cmap("Set1")
[NeMo W 2024-10-07 10:34:52 nemo_logging:349] /opt/NeMo/nemo/collections/asr/modules/rnnt.py:1550: DeprecationWarning: invalid escape sequence '\*'
"""
[NeMo W 2024-10-07 10:34:52 nemo_logging:349] /opt/NeMo/nemo/collections/common/data/lhotse/nemo_adapters.py:198: DeprecationWarning: invalid escape sequence '\d'
"""
[NeMo W 2024-10-07 10:34:52 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/nvidia/dali/_autograph/pyct/gast_util.py:79: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
if get_gast_version() < LooseVersion("0.5"):
[NeMo W 2024-10-07 10:34:52 nemo_logging:349] /home/ema8/.local/lib/python3.10/site-packages/setuptools/_distutils/version.py:337: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
other = LooseVersion(other)
[NeMo W 2024-10-07 10:34:53 nemo_logging:349] /opt/NeMo/nemo/collections/asr/parts/utils/vad_utils.py:1082: DeprecationWarning: invalid escape sequence '\s'
data = pd.read_csv(path2ground_truth_label, sep="\s+", delimiter=None, header=None)
[NeMo W 2024-10-07 10:34:53 nemo_logging:349] /opt/NeMo/nemo/collections/asr/parts/utils/asr_batching.py:39: DeprecationWarning: invalid escape sequence '\m'
"""
[NeMo W 2024-10-07 10:34:53 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/hydra/_internal/hydra.py:119: UserWarning: Future Hydra versions will no longer change working directory at job runtime by default.
See https://hydra.cc/docs/1.2/upgrades/1.1_to_1.2/changes_to_job_working_dir/ for more information.
ret = run_job(
[NeMo W 2024-10-07 10:34:53 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/lightning_fabric/connector.py:571: `precision=16` is supported for historical reasons but its usage is discouraged. Please set your precision to 16-mixed instead!
[node0414.palmetto.clemson.edu:3567856] PMIX ERROR: ERROR in file gds_ds12_lock_pthread.c at line 168
Using 16bit Automatic Mixed Precision (AMP)
[NeMo W 2024-10-07 10:34:54 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/pytorch_lightning/plugins/precision/amp.py:53: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
HPU available: False, using: 0 HPUs
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: context_parallel_size in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: expert_model_parallel_size in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: moe_extended_tp in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: finalize_model_grads_func in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: deterministic_mode in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: use_te_rng_tracker in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_bulk_wgrad in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_bulk_dgrad in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_ag in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_rs in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_rs_dgrad in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_split_ag in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_atomic_ag in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_split_rs in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_atomic_rs in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cross_entropy_loss_fusion in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_disable_qkv in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_disable_fc1 in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: overlap_p2p_comm in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: batch_p2p_comm in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: defer_embedding_wgrad_compute in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: wgrad_deferral_limit in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: pipeline_model_parallel_split_rank in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cpu_offloading in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cpu_offloading_num_layers in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: _cpu_offloading_context in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cpu_offloading_activations in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cpu_offloading_weights in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: barrier_with_L1_time in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo I 2024-10-07 10:35:28 megatron_init:314] Rank 0 has data parallel group : [0]
[NeMo I 2024-10-07 10:35:28 megatron_init:320] Rank 0 has combined group of data parallel and context parallel : [0]
[NeMo I 2024-10-07 10:35:28 megatron_init:325] All data parallel group ranks with context parallel combined: [[0]]
[NeMo I 2024-10-07 10:35:28 megatron_init:328] Ranks 0 has data parallel rank: 0
[NeMo I 2024-10-07 10:35:28 megatron_init:336] Rank 0 has context parallel group: [0]
[NeMo I 2024-10-07 10:35:28 megatron_init:339] All context parallel group ranks: [[0]]
[NeMo I 2024-10-07 10:35:28 megatron_init:340] Ranks 0 has context parallel rank: 0
[NeMo I 2024-10-07 10:35:28 megatron_init:347] Rank 0 has model parallel group: [0]
[NeMo I 2024-10-07 10:35:28 megatron_init:348] All model parallel group ranks: [[0]]
[NeMo I 2024-10-07 10:35:28 megatron_init:357] Rank 0 has tensor model parallel group: [0]
[NeMo I 2024-10-07 10:35:28 megatron_init:361] All tensor model parallel group ranks: [[0]]
[NeMo I 2024-10-07 10:35:28 megatron_init:362] Rank 0 has tensor model parallel rank: 0
[NeMo I 2024-10-07 10:35:28 megatron_init:382] Rank 0 has pipeline model parallel group: [0]
[NeMo I 2024-10-07 10:35:28 megatron_init:394] Rank 0 has embedding group: [0]
[NeMo I 2024-10-07 10:35:28 megatron_init:400] All pipeline model parallel group ranks: [[0]]
[NeMo I 2024-10-07 10:35:28 megatron_init:401] Rank 0 has pipeline model parallel rank 0
[NeMo I 2024-10-07 10:35:28 megatron_init:402] All embedding group ranks: [[0]]
[NeMo I 2024-10-07 10:35:28 megatron_init:403] Rank 0 has embedding rank: 0
setting number of microbatches to constant 288
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: context_parallel_size in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: expert_model_parallel_size in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: moe_extended_tp in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: finalize_model_grads_func in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: deterministic_mode in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: use_te_rng_tracker in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_bulk_wgrad in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_bulk_dgrad in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_ag in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_rs in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_rs_dgrad in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_split_ag in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_atomic_ag in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_split_rs in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_atomic_rs in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cross_entropy_loss_fusion in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_disable_qkv in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_disable_fc1 in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: overlap_p2p_comm in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: batch_p2p_comm in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: defer_embedding_wgrad_compute in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: wgrad_deferral_limit in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: pipeline_model_parallel_split_rank in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cpu_offloading in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cpu_offloading_num_layers in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: _cpu_offloading_context in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cpu_offloading_activations in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cpu_offloading_weights in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: barrier_with_L1_time in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo I 2024-10-07 10:35:28 tokenizer_utils:196] Getting SentencePiece with model: /local_scratch/slurm.777326/tmpkg5ll76b/b1bc02bf987043f3884c39152f183238_nemotron_2_256k.model
[NeMo I 2024-10-07 10:35:28 megatron_base_model:604] Padded vocab_size: 256000, original vocab_size: 256000, dummy tokens: 0.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: context_parallel_size in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: expert_model_parallel_size in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: moe_extended_tp in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: finalize_model_grads_func in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: deterministic_mode in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: use_te_rng_tracker in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_bulk_wgrad in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_bulk_dgrad in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_ag in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_rs in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_rs_dgrad in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_split_ag in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_atomic_ag in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_split_rs in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_atomic_rs in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cross_entropy_loss_fusion in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_disable_qkv in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: tp_comm_overlap_disable_fc1 in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: overlap_p2p_comm in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: batch_p2p_comm in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: defer_embedding_wgrad_compute in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: wgrad_deferral_limit in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: pipeline_model_parallel_split_rank in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cpu_offloading in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cpu_offloading_num_layers in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: _cpu_offloading_context in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cpu_offloading_activations in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: cpu_offloading_weights in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:1189] The model: MegatronGPTModel() does not have field.name: barrier_with_L1_time in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: first_pipeline_num_layers in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: last_pipeline_num_layers in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: activation_func_fp8_input_store in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: num_moe_experts in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: window_size in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: qk_layernorm in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: test_mode in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: calculate_per_token_loss in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: multi_latent_attention in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: memory_efficient_layer_norm in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: fp8_wgrad in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: fp8_dot_product_attention in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: fp8_multi_head_attention in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_shared_expert_intermediate_size in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_shared_expert_overlap in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_router_load_balancing_type in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_router_topk in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_router_pre_softmax in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_grouped_gemm in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_aux_loss_coeff in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_z_loss_coeff in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_input_jitter_eps in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_token_dropping in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_token_dispatcher_type in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_per_layer_logging in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_expert_capacity_factor in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_pad_expert_input_to_capacity in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_token_drop_policy in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: moe_layer_recompute in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: clone_scatter_output_in_embedding in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: disable_parameter_transpose_cache in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: enable_cuda_graph in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: external_cuda_graph in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_base_model:577] The model: MegatronGPTModel() does not have field.name: config_logger_dir in its cfg. Add this key to cfg or config_mapping to make to make it configurable.
[NeMo W 2024-10-07 10:35:28 megatron_gpt_model:372] megatron_amp_O2 is enabled but transformer-engine is not.
Initializing distributed: GLOBAL_RANK: 0, MEMBER: 1/1
----------------------------------------------------------------------------------------------------
distributed_backend=nccl
All distributed processes registered. Starting with 1 processes
----------------------------------------------------------------------------------------------------
Error executing job with overrides: ['gpt_model_file=/scratch/ema8/Minitron-4B-Base/nemo/minitron-4b-base.nemo', 'lora_model_path=/scratch/ema8/PEFT/results/minitron-4b-base/peft_1000_minitron-4b-base/checkpoints/megatron_gpt_peft_lora_tuning.nemo', 'merged_model_path=/scratch/ema8/PEFT/results/minitron-4b-base/peft_1000_minitron-4b-base_merged.nemo', 'tensor_model_parallel_size=1', 'pipeline_model_parallel_size=1', 'trainer.num_nodes=1', 'trainer.devices=1', 'trainer.accelerator=gpu']
[rank0]: Traceback (most recent call last):
[rank0]: File "/opt/NeMo/scripts/nlp_language_modeling/merge_lora_weights/merge.py", line 307, in <module>
[rank0]: main() # noqa pylint: disable=no-value-for-parameter
[rank0]: File "/opt/NeMo/nemo/core/config/hydra_runner.py", line 129, in wrapper
[rank0]: _run_hydra(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/hydra/_internal/utils.py", line 394, in _run_hydra
[rank0]: _run_app(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/hydra/_internal/utils.py", line 457, in _run_app
[rank0]: run_and_report(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/hydra/_internal/utils.py", line 223, in run_and_report
[rank0]: raise ex
[rank0]: File "/usr/local/lib/python3.10/dist-packages/hydra/_internal/utils.py", line 220, in run_and_report
[rank0]: return func()
[rank0]: File "/usr/local/lib/python3.10/dist-packages/hydra/_internal/utils.py", line 458, in <lambda>
[rank0]: lambda: hydra.run(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/hydra/_internal/hydra.py", line 132, in run
[rank0]: _ = ret.return_value
[rank0]: File "/usr/local/lib/python3.10/dist-packages/hydra/core/utils.py", line 260, in return_value
[rank0]: raise self._return_value
[rank0]: File "/usr/local/lib/python3.10/dist-packages/hydra/core/utils.py", line 186, in run_job
[rank0]: ret.return_value = task_function(task_cfg)
[rank0]: File "/opt/NeMo/scripts/nlp_language_modeling/merge_lora_weights/merge.py", line 241, in main
[rank0]: model = MegatronGPTModel.restore_from(
[rank0]: File "/opt/NeMo/nemo/collections/nlp/models/nlp_model.py", line 478, in restore_from
[rank0]: return super().restore_from(
[rank0]: File "/opt/NeMo/nemo/core/classes/modelPT.py", line 468, in restore_from
[rank0]: instance = cls._save_restore_connector.restore_from(
[rank0]: File "/opt/NeMo/nemo/collections/nlp/parts/nlp_overrides.py", line 1322, in restore_from
[rank0]: trainer.strategy.setup_environment()
[rank0]: File "/usr/local/lib/python3.10/dist-packages/pytorch_lightning/strategies/ddp.py", line 154, in setup_environment
[rank0]: self.setup_distributed()
[rank0]: File "/opt/NeMo/nemo/collections/nlp/parts/nlp_overrides.py", line 251, in setup_distributed
[rank0]: init_model_parallel(
[rank0]: File "/opt/NeMo/nemo/collections/nlp/parts/nlp_overrides.py", line 155, in init_model_parallel
[rank0]: parallel_state.initialize_model_parallel(
[rank0]: File "/opt/megatron-lm/megatron/core/parallel_state.py", line 532, in initialize_model_parallel
[rank0]: raise RuntimeError(f"world_size ({world_size}) is not divisible by {total_model_size}")
[rank0]: RuntimeError: world_size (1) is not divisible by 4
```
**Steps/Code to reproduce bug**
Below is the shell script I'm running to merge the lora weights.
```sh
PATH_TO_MERGED_MODEL="/scratch/ema8/PEFT/results/minitron-4b-base/peft_1000_minitron-4b-base_merged.nemo"
MODEL="/scratch/ema8/Minitron-4B-Base/nemo/minitron-4b-base.nemo"
PATH_TO_TRAINED_MODEL="/scratch/ema8/PEFT/results/minitron-4b-base/peft_1000_minitron-4b-base/checkpoints/megatron_gpt_peft_lora_tuning.nemo"
export HYDRA_FULL_ERROR=1
srun singularity exec --nv /home/ema8/f24-nvidia/nemo_eval.sif python /opt/NeMo/scripts/nlp_language_modeling/merge_lora_weights/merge.py \
gpt_model_file=${MODEL} \
lora_model_path=${PATH_TO_TRAINED_MODEL} \
merged_model_path=${PATH_TO_MERGED_MODEL} \
tensor_model_parallel_size=1 \
pipeline_model_parallel_size=1 \
trainer.num_nodes=1 \
trainer.devices=1 \
trainer.accelerator=gpu \
```
Here is the script to fine-tune the model:
```sh
#!/bin/bash
# Script taken from: https://docs.nvidia.com/nemo-framework/user-guide/latest/playbooks/nemoframeworkpeft.html#nemo-framework-peft-playbook
# This is the nemo model we are finetuning
# Change this to match the model you want to finetune
MODEL="/scratch/ema8/Minitron-4B-Base/nemo/minitron-4b-base.nemo"
# These are the training datasets (in our case we only have one)
TRAIN_DS="[/home/ema8/f24-nvidia/syn_data_PEFT_exp/high_school_cs_dataset/train-1000.jsonl]"
# These are the validation datasets (in our case we only have one)
VALID_DS="[/home/ema8/f24-nvidia/syn_data_PEFT_exp/high_school_cs_dataset/val.jsonl]"
# These are the test datasets (in our case we only have one)
TEST_DS="[/home/ema8/f24-nvidia/syn_data_PEFT_exp/high_school_cs_dataset/test.jsonl]"
# These are the names of the test datasets
TEST_NAMES="[high_school_cs_dataset]"
# This is the PEFT scheme that we will be using. Set to "ptuning" for P-Tuning instead of LoRA
PEFT_SCHEME="lora"
# This is the concat sampling probability. This depends on the number of files being passed in the train set
# and the sampling probability for each file. In our case, we have one training file. Note sum of concat sampling
# probabilities should be 1.0. For example, with two entries in TRAIN_DS, CONCAT_SAMPLING_PROBS might be
# "[0.3,0.7]". For three entries, CONCAT_SAMPLING_PROBS might be "[0.3,0.1,0.6]"
# NOTE: Your entry must contain a value greater than 0.0 for each file
CONCAT_SAMPLING_PROBS="[1.0]"
# This is the tensor parallel size (splitting tensors among GPUs horizontally)
# See above matrix for proper value for the given model size
TP_SIZE=1
# This is the pipeline parallel size (splitting layers among GPUs vertically)
# See above matrix for proper value for the given model size
PP_SIZE=1
# The number of nodes to run this on
# See above matrix for proper value for the given model size
NODE_COUNT=1
# The number of total GPUs used
GPU_COUNT=1
# Where to store the finetuned model and training artifacts
OUTPUT_DIR="/scratch/ema8/PEFT/results/minitron-4b-base/peft_1000_200steps_minitron-4b-base"
# Run the PEFT command by appropriately setting the values for the parameters such as the number of steps,
# model checkpoint path, batch sizes etc. For a full reference of parameter
# settings refer to the config at https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/language_modeling/tuning/conf/megatron_gpt_finetuning_config.yaml
python /opt/NeMo/examples/nlp/language_modeling/tuning/megatron_gpt_finetuning.py \
trainer.log_every_n_steps=1 \
trainer.precision=bf16 \
trainer.devices=${GPU_COUNT} \
trainer.num_nodes=1 \
trainer.val_check_interval=5 \
trainer.max_steps=200 \
model.restore_from_path=${MODEL} \
model.peft.peft_scheme=${PEFT_SCHEME} \
model.peft.lora_tuning.target_modules=[attention_qkv] \
+model.tp_comm_overlap_disable_qkv=True \
model.micro_batch_size=1 \
model.global_batch_size=128 \
model.tensor_model_parallel_size=${TP_SIZE} \
model.pipeline_model_parallel_size=${PP_SIZE} \
model.megatron_amp_O2=True \
model.activations_checkpoint_granularity=selective \
model.activations_checkpoint_num_layers=null \
model.activations_checkpoint_method=uniform \
model.optim.name=fused_adam \
model.optim.lr=1e-4 \
model.answer_only_loss=True \
model.data.train_ds.file_names=${TRAIN_DS} \
model.data.validation_ds.file_names=${VALID_DS} \
model.data.test_ds.file_names=${TEST_DS} \
model.data.train_ds.concat_sampling_probabilities=${CONCAT_SAMPLING_PROBS} \
model.data.train_ds.max_seq_length=4096 \
model.data.validation_ds.max_seq_length=4096 \
model.data.train_ds.micro_batch_size=1 \
model.data.train_ds.global_batch_size=128 \
model.data.validation_ds.micro_batch_size=1 \
model.data.validation_ds.global_batch_size=128 \
model.data.train_ds.num_workers=0 \
model.data.validation_ds.num_workers=0 \
model.data.test_ds.num_workers=0 \
model.data.validation_ds.metric.name=loss \
model.data.test_ds.metric.name=loss \
exp_manager.create_wandb_logger=False \
exp_manager.checkpoint_callback_params.mode=min \
exp_manager.explicit_log_dir=${OUTPUT_DIR} \
exp_manager.resume_if_exists=True \
exp_manager.resume_ignore_no_checkpoint=True \
exp_manager.create_checkpoint_callback=True \
exp_manager.checkpoint_callback_params.monitor=validation_loss \
++exp_manager.checkpoint_callback_params.save_best_model=False \
exp_manager.checkpoint_callback_params.save_nemo_on_train_end=True \
model.save_nemo_on_validation_end=False
```
**Environment overview**
- Environment location: apptainer
- Method of NeMo install:
Built my NeMo container based on the dev tag, and then added the lm-evaluation-harness.
*nemo_eval.def*
```def
Bootstrap: docker
From: nvcr.io/nvidia/nemo:dev
%post
git clone --depth 1 https://github.com/EleutherAI/lm-evaluation-harness
cd lm-evaluation-harness
pip install -e .
cd ..
```
The commands to build the container:
`apptainer build nemo_eval.sif nemo_eval.def`
**Additional context**
- Running on the [Palmetto Cluster](https://docs.rcd.clemson.edu/palmetto/])
- Using a node with a single A100 GPU
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"CI passed : https://github.com/NVIDIA/NeMo/actions/runs/11236355310"
] | 2024-10-07T13:30:08 | 2024-10-08T21:11:41 | 2024-10-08T21:11:39 | COLLABORATOR | {
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} | # What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | # What does this PR do ?
Changes:
1. use context manager when running reconfigure microbatch calculator to avoid side-effects across tests.
2. move test/lightning/io to test/lightning/_io to avoid name-collision with python's io lib.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | # What does this PR do ?
`signal.SIGKILL` is used but it's not supported in windows, it was introduced in #9352
**Collection**: Core
# Changelog
- Replace `signal.SIGKILL` with `signal.SIGTERM` as it is not supported in windows, I know windows is supposed to be used along with WSL, but most of the inference functionality does work without WSL, so if this PR doesn't break the functionality, there is no need to break what is left of windows compatibility
# Usage
`from nemo.collections.asr.models.msdd_models import NeuralDiarizer`
or
`from nemo.utils import exp_manager`
# GitHub Actions CI
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**PR Type**:
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If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
@ericharper @titu1994 @blisc @okuchaiev
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# Changelog
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# Usage
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```python
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# Before your PR is "Ready for review"
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If you haven't finished some of the above items you can still open "Draft" PR.
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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`IPython` is not included in the requirements but it is used in an non-optional manner
**Steps/Code to reproduce bug**
`from nemo.collections.asr.parts.utils.vad_utils import load_tensor_from_file`
On a new environment that comes without `IPython`
**Expected behavior**
`IPython` should be included in the requirements or imported inside the functions that need it (`plot` and `plot_sample_from_rttm`)
This was already discussed in https://github.com/NVIDIA/NeMo/pull/9890#discussion_r1704593976 | {
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"@akoumpa to help merge this in",
"CI passed: https://github.com/NVIDIA/NeMo/actions/runs/11446635583"
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} | # What does this PR do ?
Fixes param_groups in the checkpoint when we have a separate pipeline stage for lm_head. Without this we face error below when loading the distributed checkpoint before resuming training.
`ValueError: Cannot merge two lists with different lengths (2 and 1, encountered at level ('optimizer_states', 0, 'param_groups'))`
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
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```python
# Add a code snippet demonstrating how to use this
```
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# Before your PR is "Ready for review"
**Pre checks**:
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**PR Type**:
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- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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# Usage
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# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
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To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
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- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
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- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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- [ ] Bugfix
- [ ] Documentation
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Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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# Usage
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- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
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- [ ] Bugfix
- [ ] Documentation
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
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# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
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To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
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- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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"[π€]: Hi @yaoyu-33 π,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11732901102) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
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Add a one line overview of what this PR aims to accomplish.
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# Changelog
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} | # What does this PR do ?
tb overlap configs for llama3.1 405b, gpt 20b and 175b
**Collection**: [llm]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
trainer = run.Config(
nl.Trainer,
callbacks = [
run.Config(
MegatronCommOverlapCallback,
tp_comm_overlap=True,
tp_comm_overlap_cfg=userbuffers_fp8_h100_h12288_tp4_mbs1_seqlen2048,
)
]
```
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**PR Type**:
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- [ ] Bugfix
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If you haven't finished some of the above items you can still open "Draft" PR.
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} | * NeMoLogger arg rename dir -> log_dir
* Set NVTE_APPLY_QK_LAYER_SCALING=0
* call mbs reconfigure to avoid interference from other tests; rewrite os.environ :( to avoid interference from other tests
* Apply isort and black reformatting
---------
# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
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**PR Type**:
- [ ] New Feature
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- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | [π€]: Hi @HuiyingLi π,<br><br>we've cherry picked #10697 into `r2.0.0` for you! π<br><br>Please review and approve this cherry pick by your convenience\! | {
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} | ## Manifest format
```
{
βidβ: βsome_id_14323452β,
"conversations": [
{
"value": "Can you help summarize the following?",
"from": "User",
"type": "text",
},
{
"value": "123.wav",
"from": "User",
"type": "audio",
βdurationβ: 5.73,
},
{
"value": "I'm glad to assist you with your request. The information can be summarized as the following: β¦.",
"from": "Assistant",
"type": "text",
},
{
"value": "123_answer.wav",
"from": "Assistant",
"type": "audio",
βdurationβ: 7.11,
},
{
"value": "Can you further shorten it?",
"from": "User",
"type": "text",
},
β¦
}
```
## Input CFG format
```
- type: group
input_cfg:
- manifest_filepath: /media/data/datasets/LibriSpeech/dev_clean_10.conv.json
type: multimodal_conversation
audio_locator_tag: "<unused0>"
```
- Note: we need seprate ICFG for single turn and multi turn data mixing because we need to measure length / calibrate batch size differently.
## Example usage
- check here https://docs.google.com/document/d/15BppG_IyP7DWRh5Lw20bRVHdOXt1uvfhJZhIVmzh8AQ/edit#bookmark=id.5i9bljw374yo mainly needs to add the following flags
```
++model.data.validation_ds.force_finite=True \
++model.data.train_ds.prompt_format="gemma" \
++model.data.validation_ds.prompt_format="gemma" \
++model.data.validation_ds.drop_last=False \
++model.data.train_ds.drop_last=False \
++model.data.train_ds.input_cfg=manifests/train2.conv2.yaml \
++model.data.validation_ds.input_cfg=manifests/train2.conv2.yaml
```
## TODO
- Tar/sharding the audios
- BESTOW support https://github.com/zhehuaichen/NeMo/tree/speechllm-develop-prompt | {
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} | # What does this PR do ?
* Infers the list of VMs to check via the rest api. Another benefit: We can filter for runners that are online!
* Runs a check to decide if a reboot is necessary or not
* Transposes the execution order:
Prev. we worked in stages (first: shutdown of _all_ runners, second: re-install drivers) that all runners had to pass before the next stage could start. So all runners were delayed by the slowest runner, and so were just idle. Now, we do this on a one-by-one basis, so each runner will be maintained independently of other runners.
* Run this healthy check every 4hrs, b/c why not? It finishes super quickly (less than 5minutes) and is good for body and soul
π¨ This PR is in draft because of `environment: ko3n1g/ci/improve-vm-maintenance`. This was necessary to safely test this workflow. After an approval (just write a comment), I will change this to `environment: main` and merge it.
PS: This workflow requires sensitive secrets that we want to expose only to protected branches. So I added a branch protection rule for this branch (`ko3n1g/ci/improve-vm-maintenance`) such that I can safely test this feature.
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} | # What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | # What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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"The last step `CICD NeMo / Nemo_CICD_Test (pull_request)` fails due to a bug in the testing system. But I checked all test steps manually and haven't found any failure that would prevent from merging. So will override the branch protection rules and merge"
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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} | π PR to Bump `Dockerfile.ci`.
π Please remember the following to-do's before merge:
- [ ] Verify the presubmit CI
π Please merge this PR only if the CI workflow completed successfully. | {
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"isn't this changed needed for 8x3b as well?\r\n"
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
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- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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"This PR is dependent on implementation of media in Mcore. Will need to add the changes to NeMo first or stay as a draft until the Mcore change is merged.",
"@zpx01 can you take a look at the flow matching?",
"[π€]: Hi @Victor49152 π,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11390808610) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"[π€]: Hi @Victor49152 π,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11445018290) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
] | 2024-10-04T00:16:35 | 2024-10-22T00:24:03 | 2024-10-22T00:24:03 | COLLABORATOR | {
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} | # What does this PR do ?
Add flux inference pipeline
**Collection**:
diffusion
# Changelog
/nemo/collections/diffusion
# GitHub Actions CI
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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
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**PR Type**:
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https://api.github.com/repos/NVIDIA/NeMo/issues/10750 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/10750/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/10750/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/10750/events | https://github.com/NVIDIA/NeMo/pull/10750 | 2,565,044,750 | PR_kwDOC_bI7s59jc6X | 10,750 | [Draft] Fix optimizer state_dict compatibility between Apex's fused_adam and distributed_fused_adam | {
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"This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days.",
"This PR was closed because it has been inactive for 7 days since being marked as stale."
] | 2024-10-03T21:38:32 | 2024-10-25T01:59:17 | 2024-10-25T01:59:16 | COLLABORATOR | {
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} | # Description
The use case I am supporting is the ability to take model checkpoints trained with fused_adam optimizer and then resume training with Apex's distributed_fused_adam while maintaining optimizer state.
There is mismatch in the optimizer state_dict where MoE-specific keys, which are ShardedTensorFactory objects and not ShardedTensor's, are not caught in the rename_fp32_params function, causing the moe keys to fall under the missing and unexpected keys when loading the optimizer state_dict.
Additionally, when resuming training from a model using fused_adam, state_dict['param_groups'] does not contain any keys aside from params. The param_groups need to be pulled from state_dict['optimizer'].
I override load_state_dict in NeMo's MegatronDistributedFusedAdam and manipulate the optimizer's state_dict if we see state_dict['param_groups'] only contains params key.
This behavior can be reproduced by training any MoE model with fused_adam and then attempt to resume training with distributed_fused_adam.
Additionally,
# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
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# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
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If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
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"https://wandb.ai/joc/llava_next_energon/runs/70551i0j?nw=nwuserykarnati - fine tuning convergence run on LLaVA dataset"
] | 2024-10-03T20:32:53 | 2024-11-04T18:58:06 | 2024-11-04T18:58:06 | COLLABORATOR | {
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} | # What does this PR do ?
Support training of LLaVa NeXt model.
**Collection**: [Note which collection this PR will affect]
Multimodal
# Changelog
- Added necessary task encoders for energon data module to support training LLaVA NeXT with NeVA Model
# Usage
The only change is to use the energon based data module as shown below with existing NeVA model
```python
from nemo.collections.multimodal.data.energon.config import MultiModalSampleConfig
from nemo.collections.vlm import LlavaNextTaskEncoder
from nemo.collections.multimodal.data.energon import SimpleMultiModalDataModule
from transformers import AutoProcessor
processor = AutoProcessor.from_pretrained("llava-hf/llava-v1.6-mistral-7b-hf")
data_path = args.data_path
image_processor = processor.image_processor
tokenizer = processor.tokenizer
multimodal_sample_config = MultiModalSampleConfig()
task_encoder = LlavaNextTaskEncoder(
tokenizer=tokenizer, image_processor=image_processor, multimodal_sample_config=multimodal_sample_config
)
data = SimpleMultiModalDataModule(
path=data_path,
tokenizer=tokenizer,
image_processor=image_processor,
num_workers=8,
micro_batch_size=mbs,
global_batch_size=gbs,
multimodal_sample_config=multimodal_sample_config,
task_encoder=task_encoder,
)
```
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} | # What does this PR do ?
1. Copies the argument guard for param AG overlap with optim.step from Megatron LM.
2. Add FP8 support to MoE sequential group gemm
**Collection**: [Note which collection this PR will affect]
# Changelog
- AUse param AG overlap with optim.step only when using (1) param AG overlap and (2) virtual pipelining
- Param AG overlap can be used only when grad RS overlap is used
- Fp8 interface is passed accordingly to GPT specs
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```python
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Add a one line overview of what this PR aims to accomplish.
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# Changelog
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# Usage
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```python
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# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
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**PR Type**:
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- [ ] Bugfix
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If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | [π€]: Hi @BoxiangW π,<br><br>we've cherry picked #10703 into `r2.0.0` for you! π<br><br>Please review and approve this cherry pick by your convenience\! | {
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] | 2024-10-03T17:55:24 | 2024-11-11T01:58:43 | 2024-11-11T01:58:43 | NONE | {
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} | null | null | null | I am launching a continuous pretraining job from a 70B model checkpoint. The checkpoint is saved as .nemo file. I use
```
megatronGPTModel.restore_from(restore_path="/path/to/my/70B/.nemo", override_config_path, trainer)
```
to restore the checkpoint. It hangs while unpacking the .nemo file.
The container I am using is `nvcr.io/nvidia/nemo:24.05.llama3.1` | {
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"@meatybobby Do you think this PR should also be merged to 24.09 release? If yes, we need to add the r2.0.0 label.",
"[π€]: Hi @meatybobby π,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/$REPOSITORY/actions/runs/$RUN_ID) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
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} | # What does this PR do ?
Fix load nemo issue in Multimodal TRTLLM
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | # What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | # Fix tests for TestEncDecMultiTaskModel
**PR Type**:
- [ ] New Feature
- [ V] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
@pzelasko
# Additional Information
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
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# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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] | 2024-10-03T11:15:41 | 2024-11-11T01:58:45 | 2024-11-11T01:58:44 | NONE | {
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If using NeMo for supervised fune-tuning, how do I implement penalizing the distance between starting and current weights? This was shown to be effective in https://arxiv.org/abs/1706.03610 | {
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
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* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
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# Before your PR is "Ready for review"
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- [ ] Bugfix
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If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
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# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
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# GitHub Actions CI
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**PR Type**:
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- [ ] Bugfix
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If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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# Usage
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# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
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**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
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- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
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- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | # What does this PR do ?
Fix error raising logic in model import
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
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# Before your PR is "Ready for review"
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```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
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- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
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- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
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- [ ] Bugfix
- [ ] Documentation
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | * Call reload_model_params only if there's no optimizer state
* add nemo-ux resume test
* Apply isort and black reformatting
---------
# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
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# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
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To re-run CI remove and add the label again.
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} | * Adding nemo-run to requirements
* Updating nemo-run entrypoint inside setup.py
* Remove nemo-run from requirements until we have a pypi package
* Update entrypoint naming
* Setting up cli recipe for llama3-8b
* Move AutoTokenizer import inline for starcoder
* Move AutoTokenizer import inline for starcoder2
* Use target for factories inside llama3_8b
* Update other recipes
* Fix some bugs in the recipes
* Adding some examples
* Adding repl example
* Starting to add a notebook example as well
* Fix wrong imports
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Apply isort and black reformatting
* Fix wrong imports
* Apply isort and black reformatting
* Fix typo + add script with default executor
* Apply isort and black reformatting
* Add nemo-run to Dockerfile.ci
* Adding copyright to recipes
* Apply isort and black reformatting
* Adding guides to recipes dir
* Adding hatchling to Dockerfile.ci
* Move install to different line
* fix install
* Move llama3_pretraining to scripts for now
* Remove img folder & use images from release instead
* Apply isort and black reformatting
* Updating default of num_nodes in all recipes
* Apply isort and black reformatting
* Adding tests for all recipes
* ddAing docstrings
* Apply isort and black reformatting
* Fix failing tests inside test_mixtral_8x7b_64k
* Rename fabric to _fabric to avoid name collision with package fabric
* add rename comment
---------
# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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"Close this and move to https://github.com/NVIDIA/NeMo/pull/10748\r\nto avoid CI issues"
] | 2024-10-02T21:23:46 | 2024-10-08T03:59:47 | 2024-10-03T20:53:58 | CONTRIBUTOR | {
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} | # What does this PR do ?
Copies the argument guard for param AG overlap with optim.step from Megatron LM.
# Changelog
- Use param AG overlap with optim.step only when using (1) param AG overlap and (2) virtual pipelining
- Param AG overlap can be used only when grad RS overlap is used
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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"@gvenkatakris Thanks for this great feature! I note that the current impl only support TP. Will PP be supported in the roadmap? "
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This fixes major slowdowns when running diarization parallel on multiple gpus
Discussion: https://github.com/NVIDIA/NeMo/issues/7101
# What does this PR do ?
Stores embedding extraction on device.
# Changelog
- Add specific line by line info of high level changes in this PR.
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```python
# Add a code snippet demonstrating how to use this
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Add a one line overview of what this PR aims to accomplish.
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This fixes major slowdowns when running diarization parallel on multiple gpus
Discussion: https://github.com/NVIDIA/NeMo/issues/7101
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
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"I find it:\nI have to delete this folder:\nnemo_experiments/megatron_gpt/checkpoints",
"This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 7 days.",
"This issue was closed because it has been inactive for 7 days since being marked as stale.",
"what is the folder nemo_experiments/megatron_gpt/checkpoints? And why delete it can work?"
] | 2024-10-02T17:40:32 | 2024-11-12T07:12:17 | 2024-11-10T02:00:52 | NONE | {
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} | null | null | null | **Describe the bug**
I followed the instructions in:
https://docs.nvidia.com/nemo-framework/user-guide/latest/nemotoolkit/nlp/nemo_megatron/gpt/gpt_training.html
the i replace 1024 with 512
```
python src/examples/nlp/language_modeling/megatron_gpt_pretraining.py \
--config-path=conf \
--config-name=megatron_gpt_config \
trainer.devices=1 \
trainer.num_nodes=1 \
trainer.max_epochs=null \
trainer.max_steps=30000 \
trainer.val_check_interval=300 \
trainer.log_every_n_steps=50 \
trainer.limit_val_batches=50 \
trainer.limit_test_batches=50 \
trainer.accumulate_grad_batches=1 \
trainer.precision=16 \
model.micro_batch_size=6 \
model.global_batch_size=192 \
model.tensor_model_parallel_size=1 \
model.pipeline_model_parallel_size=1 \
model.max_position_embeddings=512 \
model.encoder_seq_length=512 \
model.hidden_size=768 \
model.ffn_hidden_size=3072 \
model.num_layers=12 \
model.num_attention_heads=12 \
model.init_method_std=0.021 \
model.hidden_dropout=0.1 \
model.layernorm_epsilon=1e-5 \
model.tokenizer.vocab_file=data/tokenizer/gpt2-vocab.json \
model.tokenizer.merge_file=data/tokenizer/gpt2-merges.txt \
model.data.data_prefix=[1.0,data/tokenized_data/hfbpe_gpt_training_data_text_document] \
model.data.num_workers=2 \
model.data.seq_length=512 \
model.data.splits_string=\'980,10,10\' \
model.megatron_amp_O2=False \
model.optim.name=fused_adam \
model.optim.lr=6e-4 \
model.optim.betas=[0.9,0.95] \
model.optim.weight_decay=0.1 \
model.optim.sched.name=CosineAnnealing \
model.optim.sched.warmup_steps=750 \
model.optim.sched.constant_steps=80000 \
model.optim.sched.min_lr=6e-5 \
exp_manager.resume_if_exists=True \
exp_manager.resume_ignore_no_checkpoint=True \
exp_manager.create_checkpoint_callback=True \
exp_manager.checkpoint_callback_params.monitor=val_loss \
exp_manager.checkpoint_callback_params.save_top_k=3 \
exp_manager.checkpoint_callback_params.mode=min \
exp_manager.checkpoint_callback_params.always_save_nemo=False
```
It get this error:
```
Error executing job with overrides: ['trainer.devices=1', 'trainer.num_nodes=1', 'trainer.max_epochs=null', 'trainer.max_steps=30000', 'trainer.val_check_interval=300', 'trainer.log_every_n_steps=50', 'trainer.limit_val_batches=50', 'trainer.limit_test_batches=50', 'trainer.accumulate_grad_batches=1', 'trainer.precision=16', 'model.micro_batch_size=6', 'model.global_batch_size=192', 'model.tensor_model_parallel_size=1', 'model.pipeline_model_parallel_size=1', 'model.max_position_embeddings=512', 'model.encoder_seq_length=512', 'model.fp8_amax_history_len=512', 'model.hidden_size=768', 'model.ffn_hidden_size=3072', 'model.num_layers=12', 'model.num_attention_heads=12', 'model.init_method_std=0.021', 'model.hidden_dropout=0.1', 'model.layernorm_epsilon=1e-5', 'model.tokenizer.vocab_file=data/tokenizer/gpt2-vocab.json', 'model.tokenizer.merge_file=data/tokenizer/gpt2-merges.txt', 'model.data.data_prefix=[1.0,data/tokenized_data/hfbpe_gpt_training_data_text_document]', 'model.data.num_workers=2', 'model.data.seq_length=512', "model.data.splits_string='980,10,10'", 'model.megatron_amp_O2=False', 'model.optim.name=fused_adam', 'model.optim.lr=6e-4', 'model.optim.betas=[0.9,0.95]', 'model.optim.weight_decay=0.1', 'model.optim.sched.name=CosineAnnealing', 'model.optim.sched.warmup_steps=750', 'model.optim.sched.constant_steps=80000', 'model.optim.sched.min_lr=6e-5', 'exp_manager.resume_if_exists=True', 'exp_manager.resume_ignore_no_checkpoint=True', 'exp_manager.create_checkpoint_callback=True', 'exp_manager.checkpoint_callback_params.monitor=val_loss', 'exp_manager.checkpoint_callback_params.save_top_k=3', 'exp_manager.checkpoint_callback_params.mode=min', 'exp_manager.checkpoint_callback_params.always_save_nemo=False']
Traceback (most recent call last):
File "/app/src/examples/nlp/language_modeling/megatron_gpt_pretraining.py", line 42, in main
trainer.fit(model)
File "/usr/local/lib/python3.10/dist-packages/pytorch_lightning/trainer/trainer.py", line 543, in fit
call._call_and_handle_interrupt(
File "/usr/local/lib/python3.10/dist-packages/pytorch_lightning/trainer/call.py", line 43, in _call_and_handle_interrupt
return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 105, in launch
return function(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/pytorch_lightning/trainer/trainer.py", line 579, in _fit_impl
self._run(model, ckpt_path=ckpt_path)
File "/usr/local/lib/python3.10/dist-packages/pytorch_lightning/trainer/trainer.py", line 973, in _run
self._checkpoint_connector._restore_modules_and_callbacks(ckpt_path)
File "/usr/local/lib/python3.10/dist-packages/pytorch_lightning/trainer/connectors/checkpoint_connector.py", line 397, in _restore_modules_and_callbacks
self.resume_start(checkpoint_path)
File "/usr/local/lib/python3.10/dist-packages/pytorch_lightning/trainer/connectors/checkpoint_connector.py", line 79, in resume_start
loaded_checkpoint = self.trainer.strategy.load_checkpoint(checkpoint_path)
File "/opt/NeMo/nemo/collections/nlp/parts/nlp_overrides.py", line 441, in load_checkpoint
return self.checkpoint_io.load_checkpoint(checkpoint_path, sharded_state_dict=checkpoint)
File "/opt/NeMo/nemo/utils/callbacks/dist_ckpt_io.py", line 78, in load_checkpoint
return dist_checkpointing.load(
File "/opt/megatron-lm/megatron/core/dist_checkpointing/serialization.py", line 135, in load
loaded_state_dict = sharded_strategy.load(sharded_state_dict, checkpoint_dir)
File "/opt/megatron-lm/megatron/core/dist_checkpointing/strategies/tensorstore.py", line 43, in load
dict_list_map_inplace(load_fn, sharded_state_dict)
File "/opt/megatron-lm/megatron/core/dist_checkpointing/dict_utils.py", line 180, in dict_list_map_inplace
x[k] = dict_list_map_inplace(f, v)
File "/opt/megatron-lm/megatron/core/dist_checkpointing/dict_utils.py", line 180, in dict_list_map_inplace
x[k] = dict_list_map_inplace(f, v)
File "/opt/megatron-lm/megatron/core/dist_checkpointing/dict_utils.py", line 184, in dict_list_map_inplace
return f(x)
File "/opt/megatron-lm/megatron/core/dist_checkpointing/strategies/tensorstore.py", line 80, in _load_from_array
x = _load_regular_chunk(sharded_tensor, checkpoint_dir)
File "/opt/megatron-lm/megatron/core/dist_checkpointing/strategies/tensorstore.py", line 107, in _load_regular_chunk
raise CheckpointingException(_msg)
megatron.core.dist_checkpointing.core.CheckpointingException: Global shape mismatch for loaded ((1024, 768)) and expected ((512, 768)) tensor for key model.embedding.position_embeddings.weight
```
**Environment details**
A100
nemo docker:
nvcr.io/nvidia/nemo:24.05.01
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Adds support for nemo 2.0 ckpt in export
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"[π€]: Hi @marcromeyn π,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11494978487) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
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**Collection**: [Note which collection this PR will affect]
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* You can potentially add a usage example below
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# Add a code snippet demonstrating how to use this
```
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If you haven't finished some of the above items you can still open "Draft" PR.
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
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- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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`convert_mistral_7b_nemo_to_hf.py` does not support tied embeddings. In other words,
- `share_embeddings_and_output_weights: true` in `model_config.yaml` in a .nemo checkpoint should be converted to `tie_word_embeddings": true` in `config.json` in an HF checkpoint.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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# Changelog
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# Before your PR is "Ready for review"
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If you haven't finished some of the above items you can still open "Draft" PR.
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# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
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```python
# Add a code snippet demonstrating how to use this
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# Before your PR is "Ready for review"
**Pre checks**:
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- [ ] Did you write any new necessary tests?
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
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```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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"this needs the 'r2.0.0' tag right?\r\n",
"@maanug-nv I have it on https://github.com/NVIDIA/NeMo/pull/10526",
"[π€]: Hi @akoumpa π,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/$REPOSITORY/actions/runs/$RUN_ID) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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"hey @BoxiangW, this PR broke the test [L0_Unit_Tests_GPU_LLM](https://github.com/NVIDIA/NeMo/actions/runs/11149877529/job/30989881442). Can you help us fixing it?"
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Removed finetuning recipes due to no use cases
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
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- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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"@pablo-garay I saw the failure test OPTIONAL_L0_Unit_Tests_CPU_ASR / main but it seem not related to my change. Not sure if these are expected?",
"Close this and move to https://github.com/NVIDIA/NeMo/pull/10748\r\nto avoid CI issues"
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**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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} | 1. tokenize_with_prompt (from Piotr)
2. keep the previous behavior of truncating input_ids when the length is larger than max_seq_length
3. add gemma support
4. make the prompt template compatible with our data which has `context`, `question`, or `default_context` in the manifest
5. support distributed fused adam on lora
6. fix lora ckpt loading and storing issue in naming
verified speechllm-develop can train with `/lustre/fs8/portfolios/llmservice/users/zhehuaic/works/mod_speech_llm/scripts/oci_canary_gpt_gemma_prompt_lorac_lhmerge6_p2h_d5.sh`
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"lgtm"
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} | # What does this PR do ?
add diffusion energon dataloader
# Changelog
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* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
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"This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days.",
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] | 2024-10-01T19:30:32 | 2024-10-30T01:59:23 | 2024-10-30T01:59:22 | MEMBER | {
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} | # What does this PR do ?
Allow logging memory profile via the interval constructor arg.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
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To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | # What does this PR do ?
Fixing two things in **r2.0.0** release testing, to be cherry-picked to the release branch: - repro below for an oldish Nemo checkpoint from FP8 SFT:
```
python /opt/NeMo/tests/export/nemo_export.py \
--checkpoint_dir /opt/checkpoints/LLAMA2-7B-base/LLAMA2-7B-fp8-sft.nemo \
--model_type llama \
--min_tps 1 \
--max_output_len 24 \
--test_deployment False \
--in_framework True \
--model_name llama
```
Issues are:
1. Loading old checkpoints - solved with https://github.com/NVIDIA/NeMo/commit/86408ccbabc4920a5c8e2a5d76cfc5d3afaf7bf4
```
[rank0]: File "/opt/megatron-lm/megatron/core/dist_checkpointing/dict_utils.py", line 191, in dict_list_map_inplace
[rank0]: x[k] = dict_list_map_inplace(f, v)
[rank0]: File "/opt/megatron-lm/megatron/core/dist_checkpointing/dict_utils.py", line 191, in dict_list_map_inplace
[rank0]: x[k] = dict_list_map_inplace(f, v)
[rank0]: File "/opt/megatron-lm/megatron/core/dist_checkpointing/dict_utils.py", line 195, in dict_list_map_inplace
[rank0]: return f(x)
[rank0]: File "/opt/megatron-lm/megatron/core/dist_checkpointing/strategies/common.py", line 118, in load_sharded_object
[rank0]: raise CheckpointingException(err_msg) from e
[rank0]: megatron.core.dist_checkpointing.core.CheckpointingException: Object shard /tmp/tmpuuv6zoo9/model_weights/model.decoder.layers.self_attention.core_attention._extra_state/shard_0_32.pt not found
```
2. In-framework inference issues for FP8 - solved with https://github.com/NVIDIA/NeMo/commit/56d6e6f4c21bd1ce6328d756c34256791718f5dd (need to disable)
```
[rank0]: mixed_qkv, _ = self.linear_qkv(hidden_states)
[rank0]: File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1552, in _wrapped_call_impl
[rank0]: return self._call_impl(*args, **kwargs)
[rank0]: File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1561, in _call_impl
[rank0]: return forward_call(*args, **kwargs)
[rank0]: File "/opt/megatron-lm/megatron/core/extensions/transformer_engine.py", line 336, in forward
[rank0]: out = super().forward(x, is_first_microbatch=_is_first_microbatch)
[rank0]: File "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py", line 574, in _fn
[rank0]: return fn(*args, **kwargs)
[rank0]: File "/usr/local/lib/python3.10/dist-packages/transformer_engine/pytorch/module/layernorm_linear.py", line 1216, in forward
[rank0]: out = fwd_fn(*args)
[rank0]: File "/usr/local/lib/python3.10/dist-packages/transformer_engine/pytorch/module/layernorm_linear.py", line 101, in forward
[rank0]: assert_dim_for_fp8_exec(inputmat)
[rank0]: File "/usr/local/lib/python3.10/dist-packages/transformer_engine/pytorch/utils.py", line 237, in assert_dim_for_fp8_exec
[rank0]: and tensor.size(1) % 16 == 0
[rank0]: AssertionError: FP8 execution requires 2D input matrices with height divisible by 8 and width divisible by 16, but got tensor with dims=[12, 4096]
```
**Collection**: NLP
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
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To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
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**PR Type**:
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- [x] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
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- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
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To re-run CI remove and add the label again.
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# Before your PR is "Ready for review"
**Pre checks**:
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- [ ] Did you write any new necessary tests?
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
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"This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days.",
"This PR was closed because it has been inactive for 7 days since being marked as stale.",
"[π€]: Hi @sanandaraj5597 π,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/12659627818) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
] | 2024-10-01T05:51:42 | 2025-01-15T23:25:44 | 2025-01-15T02:22:22 | COLLABORATOR | {
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} | # What does this PR do ?
This PR adds an interface argument to support the MCore Partial DistOpt feature. The argument `num_distributed_optimizer_instances` determines the the level of sharding that can be done on the MCore DistOpt across the DP domain.
The setting need to be set as `training.model.optim. num_distributed_optimizer_instances =2` in the configuration YAML file. | {
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] | 2024-10-01T05:23:12 | 2024-10-11T06:27:31 | 2024-10-11T06:27:30 | MEMBER | {
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} | # What does this PR do ?
Run Mini-Mixtral (3M) pretraining with Mcore & NeMo and compare bitexactness of checkpoints.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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π Please remember the following to-do's before merge:
- [ ] Verify the presubmit CI
π Please merge this PR only if the CI workflow completed successfully. | {
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"Seems like we don't have the ability to save '.nemo' in 2.0 right?",
"Yes, this was an NVbug about NeMo 1.0. We are not going to save .nemo in 2.0 right now",
"One last request, can we add a test in `test_exp_manager.py` to ensure this configuration will fail?",
"@maanug-nv Can you help approve this again? It just passed all tests."
] | 2024-09-30T23:51:31 | 2024-10-22T07:49:59 | 2024-10-22T07:49:59 | COLLABORATOR | {
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"merged_at": "2024-10-22T07:49:58"
} | # What does this PR do ?
`always_save_nemo` option is not supported yet to work with model parallel. Added assertions to avoid future confusions.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
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* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
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"This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days.",
"Finalizing reviews and comments this week\r\n",
"This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days.",
"This PR was closed because it has been inactive for 7 days since being marked as stale.",
"Reopening this one"
] | 2024-09-30T23:40:37 | 2024-12-06T18:30:19 | 2024-11-29T02:03:52 | NONE | {
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} | # What does this PR do ?
Tutorial for DAPT with NeMo Framework
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
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* You can potentially add a usage example below
```python
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To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [Y ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
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**PR Type**:
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- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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"Please fix [DCO](https://github.com/NVIDIA/NeMo/pull/10688/checks?check_run_id=31972432771) also.",
"Could you let me know when it will be completed? Iβve been really looking forward to this feature. It works in pretrain, but itβs really strange that it doesnβt work in SFT.",
"<!-- pylint-output-strict-mode-false -->\n\nbeep boop π€: π The following files have warnings. In case you are familiar with these, please try helping us to improve the code base.\n\n---\n\nYour code was analyzed with PyLint. The following annotations have been identified:\n\n```\n************* Module nemo.collections.nlp.data.language_modeling.megatron.gpt_sft_dataset\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:70:0: C0301: Line too long (353/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:72:0: C0301: Line too long (173/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:73:0: C0301: Line too long (156/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:79:0: C0301: Line too long (157/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:82:0: C0301: Line too long (147/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:83:0: C0301: Line too long (178/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:84:0: C0301: Line too long (138/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:85:0: C0301: Line too long (121/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:87:0: C0301: Line too long (144/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:90:0: C0301: Line too long (247/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:165:0: C0301: Line too long (125/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:174:0: C0301: Line too long (121/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:244:0: C0301: Line too long (137/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:247:0: C0301: Line too long (133/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:272:0: C0301: Line too long (146/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:277:0: C0301: Line too long (153/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:278:0: C0301: Line too long (155/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:300:0: C0301: Line too long (127/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:389:0: C0301: Line too long (120/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:655:0: C0301: Line too long (120/119) (line-too-long)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:36:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/nlp/data/language_modeling/megatron/gpt_sft_dataset.py:526:0: C0115: Missing class docstring (missing-class-docstring)\n************* Module 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(line-too-long)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1337:0: C0301: Line too long (122/119) (line-too-long)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1378:0: C0301: Line too long (122/119) (line-too-long)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1435:0: C0301: Line too long (140/119) (line-too-long)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1616:0: C0301: Line too long (132/119) (line-too-long)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1617:0: C0301: Line too long (136/119) (line-too-long)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1619:0: C0301: Line too long (159/119) (line-too-long)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1790:0: C0301: Line too long (128/119) (line-too-long)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1810:0: C0301: Line too long (140/119) (line-too-long)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1818:0: C0301: Line too long (155/119) (line-too-long)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1839:0: C0301: Line too long (141/119) (line-too-long)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1909:0: C0301: Line too long (125/119) (line-too-long)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1936:0: C0301: Line too long (134/119) (line-too-long)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:140:0: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:153:0: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:179:0: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:198:0: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:245:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:283:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:287:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:299:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:307:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:469:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:472:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:701:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:705:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:787:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1104:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1177:12: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1226:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1255:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1448:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1583:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1591:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1600:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:1884:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:2037:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:2044:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:2050:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:20:0: W0611: Unused fields imported from dataclasses (unused-import)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:28:0: W0611: Unused _DataFetcherWrapper imported from lightning.pytorch.loops.fetchers (unused-import)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:30:0: W0611: Unused OmegaConf imported from omegaconf (unused-import)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:72:0: W0611: Unused activation_to_func imported from nemo.collections.nlp.parts.utils_funcs (unused-import)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:81:4: W0611: Unused megatron.core imported as core (unused-import)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:82:4: W0611: Unused tensor_parallel imported from megatron.core (unused-import)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:101:4: W0611: Unused init_method_normal imported from megatron.core.utils (unused-import)\nnemo/collections/nlp/models/language_modeling/megatron_gpt_model.py:101:4: W0611: Unused scaled_init_method_normal imported from megatron.core.utils (unused-import)\n************* Module nemo.utils.sequence_packing_utils\nnemo/utils/sequence_packing_utils.py:53:0: C0301: Line too long (125/119) (line-too-long)\nnemo/utils/sequence_packing_utils.py:112:0: C0301: Line too long (127/119) (line-too-long)\nnemo/utils/sequence_packing_utils.py:121:0: C0301: Line too long (122/119) (line-too-long)\nnemo/utils/sequence_packing_utils.py:122:0: C0301: Line too long (139/119) (line-too-long)\n************* Module scripts.nlp_language_modeling.prepare_packed_ft_dataset\nscripts/nlp_language_modeling/prepare_packed_ft_dataset.py:206:0: C0301: Line too long (157/119) (line-too-long)\nscripts/nlp_language_modeling/prepare_packed_ft_dataset.py:169:0: C0115: Missing class docstring (missing-class-docstring)\nscripts/nlp_language_modeling/prepare_packed_ft_dataset.py:175:4: C0116: Missing function or method docstring (missing-function-docstring)\nscripts/nlp_language_modeling/prepare_packed_ft_dataset.py:188:0: C0116: Missing function or method docstring (missing-function-docstring)\n\n-----------------------------------\nYour code has been rated at 9.46/10\n```\n\n---\n\nThank you for improving NeMo's documentation!"
] | 2024-09-30T23:39:01 | 2024-11-28T00:03:05 | 2024-11-28T00:03:05 | CONTRIBUTOR | {
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} | # What does this PR do ?
This PR adds CP support for THD format and is compatible with cu_seqlen_padded in the latest CUDNN fused attention.
Steps to run SFT + CP + THD format:
1. Prepare packed dataset in THD format: run `scripts/nlp_language_modeling/prepare_packed_ft_dataset.py` to pack the dataset into THD format in desired sequence length. For example:
```
python <NeMo_top_dir>/scripts/nlp_language_modeling/prepare_packed_ft_dataset.py \
model.data.train_ds.file_names=[<dataset_top_dir>/squad/1_squad_train.jsonl] \
model.data.train_ds.max_seq_length=4096 \
+model.context_parallel_size=2 \
+tokenizer_path=<tokenizer_path> \
+output_dir=<output_dir> +pack_sizes=[4096] \
```
2. Run SFT on the packed dataset in THD format with the same CP size specified in the last step
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
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} | * Require setuptools>=70 and update deprecated api
* Apply isort and black reformatting
---------
# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | [π€]: Hi @Victor49152 π,<br><br>we've cherry picked #10662 into `r2.0.0` for you! π<br><br>Please review and approve this cherry pick by your convenience\! | {
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} | [π€]: Hi @akoumpa π,<br><br>we've cherry picked #10596 into `r2.0.0` for you! π<br><br>Please review and approve this cherry pick by your convenience\! | {
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