renwei2024/nemo-github-issues huggingface dataset:
Update Dockerfile.ci to offending MCore
State: closed | Pull request: yes
Labels: name: stale

name: Run CICD

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Update Dockerfile.ci to pre failure
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name: Run CICD

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asr + diarization config setting problem
State: closed | Pull request: no
Labels: name: bug

**Describe the bug**

I am following the tutorial of asr+diariation under examples/speaker_tasks/diarization.
I want to use diar_msdd_telephonic model so I have to add more parameters like this:

```
python  clustering_diarizer/offline_diar_with_asr_infer.py \
    diarizer.manifest_filepath='./manifest.json' \
    diarizer.out_dir='demo_asr_output' \
    diarizer.asr.model_path='stt_en_conformer_ctc_large' \
    diarizer.speaker_embeddings.parameters.save_embeddings=False \
    diarizer.asr.parameters.asr_based_vad=True \
    diarizer.speaker_embeddings.model_path='diar_msdd_telephonic' \
    parameters.window_length_in_sec=[1.5,1.0,0.5] \
    parameters.shift_length_in_sec=[0.75,0.5,0.25] \
    parameters.multiscale_weights=[0.33,0.33,0.33] 

```

But this setting will get error message caught, somthing like the follows:

>  raise ConfigCompositionException(
hydra.errors.ConfigCompositionException: Could not override 'parameters.window_length_in_sec'.
To append to your config use +parameters.window_length_in_sec=[1.5,1.0,0.5]

I do not know if I understood it correctly, so I used "+parameters.window_length_in_sec=[1.5,1.0,0.5] \ " instead.
The script can be executed successfully and proper results can be returned. But I am not sure if I have
set the config correctly. I did not find anywhere in the verbose logging message my config had taken effect.
Here  is logging output.

>    speaker_embeddings:
        model_path: diar_msdd_telephonic
        parameters:
          window_length_in_sec:
          - 3.0
          - 2.5
          - 2.0
          - 1.5
          - 1.0
          - 0.5
          shift_length_in_sec:
          - 1.5
          - 1.25
          - 1.0
          - 0.75
          - 0.5
          - 0.25
          multiscale_weights:
          - 1
          - 1
          - 1
          - 1
          - 1
          - 1
          save_embeddings: false




I know the reason, it should be 

>   #diarizer.speaker_embeddings.parameters.window_length_in_sec=[1.5,1.0,0.5] \
    #diarizer.speaker_embeddings.parameters.shift_length_in_sec=[0.75,0.5,0.25] \
    #diarizer.speaker_embeddings.parameters.multiscale_weights=[0.33,0.33,0.33]
chore(beep boop 🤖): Bump `MCORE_TAG=9a75c72...` (2024-11-25)
State: closed | Pull request: yes
Labels: name: Run CICD

🚀 PR to bump `NVIDIA/Megatron-LM` in `Dockerfile.ci` to `MCORE_TAG=9a75c72f7b41e1e74322827be466d56dec53ccce`.  

📝 Please remember the following to-do's before merge: 
- [ ] Verify the presubmit CI  

🙏 Please merge this PR only if the CI workflow completed successfully.
Huvu/t5 nemo2.0 nemoci 3b11b
State: closed | Pull request: yes
Labels: name: Run CICD

# What does this PR do ?

Update recipes for 3B and 11B T5 model, to use `run.Config`, so the objects can be serialized when running with nemo_run.

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chore(beep boop 🤖): Bump `MCORE_TAG=c10721e...` (2024-11-24)
State: closed | Pull request: yes
Labels: name: Run CICD

🚀 PR to bump `NVIDIA/Megatron-LM` in `Dockerfile.ci` to `MCORE_TAG=c10721e354144dda3123e02f4de050fa8cc2d6d2`.  

📝 Please remember the following to-do's before merge: 
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🙏 Please merge this PR only if the CI workflow completed successfully.
chore(beep boop 🤖): Bump `MCORE_TAG=a9d040c...` (2024-11-23)
State: closed | Pull request: yes
Labels: name: Run CICD

🚀 PR to bump `NVIDIA/Megatron-LM` in `Dockerfile.ci` to `MCORE_TAG=a9d040c355f7f2d3ead209931cd95d61167494fa`.  

📝 Please remember the following to-do's before merge: 
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🙏 Please merge this PR only if the CI workflow completed successfully.
add hindi tn/itn coverage
State: closed | Pull request: yes
Labels: name: NLP

name: Run CICD

# What does this PR do ?

Update wfst_text_normalization doc to reflect coverage of Hindi TN/ITN

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calculate metrics for nemo2 sftpeft notebook
State: closed | Pull request: yes

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Fix selective restore by explicitly verifying keys
State: closed | Pull request: yes
Labels: name: Run CICD

io.load_checkpoint always loads the entire state including `optimizer`. For selective restore, we need to explicitly select keys  to restore.

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Rewire tokenizer exception handling in model resume
State: closed | Pull request: yes
Labels: name: Run CICD

# What does this PR do ?

Rewrite the error handling strategy when model does not have tokenizer.
Previously the bare try-except block would mask out actual errors such as wrong model path.


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nemo/lightning/resume.py:266:4: C0116: Missing function or method docstring (missing-function-docstring)
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NeMo docker image 24.09 shows weird FileNotFoundError for shards FileNotFoundError: [Errno 2] No such file or directory: '/tmp/tmpxoyazmhf/model_weights/model.decoder.layers.self_attention.core_attention._extra_state/shard_0_32.pt'
State: closed | Pull request: no
Labels: name: bug

name: stale

Hello everyone and Nvidia folks,


We are trying to finetune llama3_1_8b_instruct. (70b as well after 8b)  

Docker pull Nvidia NeMo docker image 24.09 and run inside a container.

Using this notebook from Brev (now part of Nvidia) https://github.com/brevdev/notebooks/blob/main/llama31_law.ipynb

The error below happened when running the 1st cell at step 2 in the notebook for finetuning 

![Image](https://github.com/user-attachments/assets/14a4b19b-82f7-4d0d-a6d6-09b1c412cb35)

We are running this on our local machine with 4* A10 GPUs. 

Tried both 1 GPU and 4 GPUs but got the same FileNotFoundError for shard

FileNotFoundError: [Errno 2] No such file or directory: '/tmp/tmpxoyazmhf/model_weights/model.decoder.layers.self_attention.core_attention._extra_state/shard_0_32.pt'


Anyone knows why this happened and how to solve? 


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.

Did you solve this?
chore(beep boop 🤖): Bump `MCORE_TAG=ddd920f...` (2024-11-22)
State: closed | Pull request: yes
Labels: name: Run CICD

🚀 PR to bump `NVIDIA/Megatron-LM` in `Dockerfile.ci` to `MCORE_TAG=ddd920f9dd1b20f259314a969513372008d5ee2c`.  

📝 Please remember the following to-do's before merge: 
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🙏 Please merge this PR only if the CI workflow completed successfully.
Micro-optimizations with ~16% speedup Canary training on 1GPU
State: closed | Pull request: yes
Labels: name: ASR

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

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Fix deploy conflicts in llm.api
State: closed | Pull request: yes
Labels: name: Run CICD

In `llm.api.deploy`, the function is also named `deploy` and the import is also named `deploy` as `from nemo.collections.llm import deploy`. This PR fixes the imports to avoid the name conflicts.

Currently, python gives an attribute error when doing `deploy.` because of the naming conflict.

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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Fix Gemma2 Attention Args
State: closed | Pull request: yes
Labels: name: NLP

name: Run CICD

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Fix DDP unused param error when TE is enabled in NeMo Lite
State: closed | Pull request: yes
Labels: name: Run CICD

# What does this PR do ?

Fixed DDP issue with TE

<!-- pylint-output-strict-mode-false -->

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---

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```
************* Module hf
examples/llm/sft/hf.py:74:0: C0301: Line too long (162/119) (line-too-long)
examples/llm/sft/hf.py:26:0: C0115: Missing class docstring (missing-class-docstring)
examples/llm/sft/hf.py:39:0: C0116: Missing function or method docstring (missing-function-docstring)
examples/llm/sft/hf.py:23:0: W0611: Unused ModelCallback imported from nemo.lightning.pytorch.callbacks (unused-import)
************* Module nemo.collections.llm.gpt.model.hf_auto_model_for_causal_lm
nemo/collections/llm/gpt/model/hf_auto_model_for_causal_lm.py:26:0: C0116: Missing function or method docstring (missing-function-docstring)
nemo/collections/llm/gpt/model/hf_auto_model_for_causal_lm.py:34:0: C0115: Missing class docstring (missing-class-docstring)
nemo/collections/llm/gpt/model/hf_auto_model_for_causal_lm.py:58:4: C0116: Missing function or method docstring (missing-function-docstring)
nemo/collections/llm/gpt/model/hf_auto_model_for_causal_lm.py:69:4: C0116: Missing function or method docstring (missing-function-docstring)
nemo/collections/llm/gpt/model/hf_auto_model_for_causal_lm.py:72:4: C0116: Missing function or method docstring (missing-function-docstring)
nemo/collections/llm/gpt/model/hf_auto_model_for_causal_lm.py:89:4: C0116: Missing function or method docstring (missing-function-docstring)
nemo/collections/llm/gpt/model/hf_auto_model_for_causal_lm.py:101:4: C0116: Missing function or method docstring (missing-function-docstring)
nemo/collections/llm/gpt/model/hf_auto_model_for_causal_lm.py:115:4: C0116: Missing function or method docstring (missing-function-docstring)
nemo/collections/llm/gpt/model/hf_auto_model_for_causal_lm.py:126:4: C0116: Missing function or method docstring (missing-function-docstring)

-----------------------------------
Your code has been rated at 8.93/10
```

---

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Fix environment variables in torchrun executor
State: closed | Pull request: yes
Labels: name: Run CICD

# 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
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# Add a code snippet demonstrating how to use this 
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Doesn't have the shards in expected directory.
State: closed | Pull request: no
Labels: name: bug

name: stale

**Describe the bug**

I was trying to run the following lines:


```
%%bash

# Set paths to the model, train, validation and test sets.
MODEL="./llama-3_1-8b-instruct-nemo_v1.0/llama3_1_8b_instruct.nemo"

TRAIN_DS="[./curated-data/law-qa-train_preprocessed.jsonl]"
VALID_DS="[./curated-data/law-qa-val_preprocessed.jsonl]"
TEST_DS="[./curated-data/law-qa-test_preprocessed.jsonl]"
TEST_NAMES="[law]"

SCHEME="lora"
TP_SIZE=1
PP_SIZE=1

rm -rf results
OUTPUT_DIR="./results/Meta-llama3.1-8B-Instruct-titlegen"

torchrun --nproc_per_node=1 \
/opt/NeMo/examples/nlp/language_modeling/tuning/megatron_gpt_finetuning.py \
    exp_manager.exp_dir=${OUTPUT_DIR} \
    exp_manager.explicit_log_dir=${OUTPUT_DIR} \
    trainer.devices=1 \
    trainer.num_nodes=1 \
    trainer.precision=bf16-mixed \
    trainer.val_check_interval=0.2 \
    trainer.max_steps=50 \
    model.megatron_amp_O2=True \
    ++model.mcore_gpt=True \
    model.tensor_model_parallel_size=${TP_SIZE} \
    model.pipeline_model_parallel_size=${PP_SIZE} \
    model.micro_batch_size=1 \
    model.global_batch_size=64 \
    model.restore_from_path=${MODEL} \
    model.data.train_ds.file_names=${TRAIN_DS} \
    model.data.train_ds.concat_sampling_probabilities=[1.0] \
    model.data.validation_ds.file_names=${VALID_DS} \
    model.peft.peft_scheme=${SCHEME}
```

but keep getting the following error:

`'FileNotFoundError: [Errno 2] No such file or directory: '/tmp/tmpelprgyyt/model_weights/model.decoder.layers.self_attention.core_attention._extra_state/shard_0_32.pt''`

Just can't seem to have the weights file under the directory of `"/tmp/tmpelprgyyt/model_weights/model.decoder.layers.self_attention.core_attention._extra_state"`

**Expected behavior**

To successfully load the shards to the model.

**Environment overview (please complete the following information)**

 - Environment location: Primehub docker website interface(Jupyter lab)
 - Method of NeMo install: pull from nvcr.io/nvidia/nemo:24.09

**Environment details**

I'm using NeMo image 24.09 version on 4 A10 GPU cores.




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.
update SquadDataModule to use run.config
State: closed | Pull request: yes
Labels: name: Run CICD

# 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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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)
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- [ ] Bugfix
- [ ] Documentation

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## Who can review?

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<!-- pylint-output-strict-mode-false -->

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---

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```
************* Module nemo.collections.llm.t5.data.squad
nemo/collections/llm/t5/data/squad.py:33:0: C0301: Line too long (120/119) (line-too-long)
nemo/collections/llm/t5/data/squad.py:34:0: C0301: Line too long (123/119) (line-too-long)
nemo/collections/llm/t5/data/squad.py:38:0: C0301: Line too long (129/119) (line-too-long)
nemo/collections/llm/t5/data/squad.py:39:0: C0301: Line too long (120/119) (line-too-long)
nemo/collections/llm/t5/data/squad.py:103:0: C0301: Line too long (125/119) (line-too-long)
nemo/collections/llm/t5/data/squad.py:78:4: C0116: Missing function or method docstring (missing-function-docstring)
nemo/collections/llm/t5/data/squad.py:154:4: C0116: Missing function or method docstring (missing-function-docstring)

-----------------------------------
Your code has been rated at 9.29/10
```

---

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Sequence packing with ChatDataset
State: closed | Pull request: no
Labels: name: stale

Hello, may I know how to use gpt_sft_chat_dataset with sequence packing? I couldnt find documentation related to it. I only found to convert from input-output format. 

Sequence packing steps can found [here](https://docs.nvidia.com/nemo-framework/user-guide/24.07/llms/starcoder2/dataprep.html?highlight=packed#step-4-prepare-packed-dataset)

To make it work for chat dataset, you probably need to add the chat format option, like this:
```
python /workspace/sequence_packing/tokenize_dataset.py \
  model.data.train_ds.file_names=[/path/to/training.jsonl] \
  model.data.train_ds.max_seq_length=4096 \
  +model.data.chat=True \
  +model.data.chat_prompt_tokens.system_turn_start='<extra_id_0>' \
      +model.data.chat_prompt_tokens.turn_start='<extra_id_1>' \
      +model.data.chat_prompt_tokens.label_start='<extra_id_2>' \
      +model.data.chat_prompt_tokens.end_of_turn="\x0A" \
      +model.data.chat_prompt_tokens.end_of_name="\x0A" \
  model.restore_from_path=/path/to/starcoder2.nemo \ # any starcoder2 .nemo models works here
  +output_path=/path/to/my_dataset.npy
```

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.
Fix linear layer replacement
State: closed | Pull request: yes
Labels: name: Run CICD

# What does this PR do ?

Fixes the bug with TE linear layer replacement

<!-- pylint-output-strict-mode-true -->

beep boop 🤖: 🚨 The following files must be fixed before merge!

---

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------------------------------------
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chore(beep boop 🤖): Bump `MCORE_TAG=81fee9b...` (2024-11-21)
State: closed | Pull request: yes
Labels: name: Run CICD

🚀 PR to bump `NVIDIA/Megatron-LM` in `Dockerfile.ci` to `MCORE_TAG=81fee9b0047fb3ac6001b5e71e4df89fc01b2a1c`.  

📝 Please remember the following to-do's before merge: 
- [ ] Verify the presubmit CI  

🙏 Please merge this PR only if the CI workflow completed successfully.
fix typo
State: closed | Pull request: yes
Labels: name: Run CICD

# 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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**Pre checks**:
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- [ ] Did you write any new necessary tests?
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## Who can review?

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<!-- pylint-output-strict-mode-false -->

beep boop 🤖: 🙏 The following files have warnings. In case you are familiar with these, please try helping us to improve the code base.

---

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```
************* Module nemo.collections.llm.recipes.mamba2_hybrid_8b
nemo/collections/llm/recipes/mamba2_hybrid_8b.py:258:0: C0301: Line too long (120/119) (line-too-long)
nemo/collections/llm/recipes/mamba2_hybrid_8b.py:38:0: C0116: Missing function or method docstring (missing-function-docstring)

-----------------------------------
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```

---

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Add torchrun local executor to recipes
State: closed | Pull request: yes
Labels: name: Run CICD

# 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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<!-- pylint-output-strict-mode-true -->

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NeMo-UX: MegatronAutoModel
State: open | Pull request: yes
Labels: name: CI

name: Run CICD

# What does this PR do ?

```
model = MegatronAutoModel("meta-llama/Llama-3.1-8B")
print(model)
> LlamaModel()
```

**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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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.
Add sample generate to PTQ for NeMo 2.0
State: closed | Pull request: yes
Labels: name: Run CICD

name: skip-docs

# What does this PR do ?

Adds optional sample generate to PTQ and validation of the exported checkpoint

**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
# Add a code snippet demonstrating how to use this 
```

# GitHub Actions CI

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# Before your PR is "Ready for review"
**Pre checks**:
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