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Fix circular import for MM dataprep notebook #9292

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What does this PR do ?

  • Fix circular import of nemo.collections.multimodal.models.text_to_image.stable_diffusion.ldm.autoencoder.AutoencoderKL
  • Rename NeMo-Megatron-Launcher to NeMo-Framework-Launcher

Collection: [Note which collection this PR will affect]

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  • Add specific line by line info of high level changes in this PR.

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* update launcher name and fix mm circular import

Signed-off-by: Chen Cui <chcui@nvidia.com>

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@pablo-garay pablo-garay merged commit bbbe826 into main Jun 6, 2024
133 checks passed
@pablo-garay pablo-garay deleted the cherry-pick-main-c12030f77f679ddb00ddd24b35d4d89f3134e43a branch June 6, 2024 17:57
marcromeyn pushed a commit that referenced this pull request Jun 7, 2024
* update launcher name and fix mm circular import

* Apply isort and black reformatting

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akoumpa added a commit that referenced this pull request Jun 10, 2024
…rategy (#9387)

* Integrating mcore's DistributedDataParallel into MegatronStrategy

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* bugfix if using mcore distOpt with sft (#9356)

* bugfix if using mcore distOpt

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* fix typo infer_seq_lenght -> infer_seq_length (#9370)

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* Rachitg/ag (#9081)

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* Adding the original change made for label_models (#9377) (#9378)

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* Dgalvez/fix greedy batch strategy name r2.0.0rc0 (#9243) (#9253)

* Lazily warn about using greedy strategy instead of greedy_batch
strategy.

Previously, the warning would often run spuriously, since several
existing code paths simply call "change_decoding_strategy()" after
having first initialized a Module, rather than changing the config
before initializing the Module. This can be confusing.

The only problem I can see with this is that using logging inside a
forward() method might interfere with some compiler toolkits like
Torchscript or thunder.compile. Presumably it would be easy to add a
conditional statement to avoid this statement in a compiler context if
necessary.

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* Update README.rst (#9393)

Revised content per https://gitlab-master.nvidia.com/nemo-framework-tme/documentation/-/issues/25. Also removed reference to NIMs in LLMs and MMs Deployment and Optimization. It should be NVIDIA NeMo Microservices and not NIM. Removed  nemo:24.03.framework and nemo:24.01.speech in Docker Containers section and replaced with 24.05 . Please verify all changes.

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* a2a fix removed tp world size and group from init (#8944) (#8952)

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* Add config option for FP32 embedding grads (#8946)

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* Enhance Distributed Adam (#9037)

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* Preserve memory format in parameter buffer of distributed adam.

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* Force diarizer to use CUDA if cuda is available and if device=None. (#9380) (#9390)

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* ci: Properly catch failed tests by introduction of workflow templates (#9324)

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* Use model-cast-to-bfloat16 rather than AMP-to-bfloat16 for inference. (#9198)

* Fix the "cast ping pong" problem when we run AMP inference.

This has been tested only for Parakeet-CTC-1.1B right now. This
problem certainly exists elsewhere.

Automatic mixed precision and inference do not play well together.

First, automatic mixed precision was created back when neural networks
were much simpler. In particular, they did not have softmax and layer
norm as frequent operations. In the era of transformers, softmax and
layer norm are very common. AMP will uncoditionally output fp32
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This is no longer necessary, now that layer norm does accumulation in
fp32 in pytorch, even if the input is fp16:
https://github.com/pytorch/pytorch/issues/66707

Do infernece by casting model to bfloat16, not by using AMP.

Do feature preprocessing in float32 for accuracy. Warn if someone
tries to input a non-float32 tensor.

Always create the output in the type the rest of the model expects.

Sort manifests by duration.

Signed-off-by: Daniel Galvez <dgalvez@nvidia.com>

* Always cast softmax inputs to float32 when in training mode.

While we don't need this for accurate results in b/float16, this is a
safety precaution to make sure that training accuracy does not
regress.

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janekl pushed a commit that referenced this pull request Jun 12, 2024
* update launcher name and fix mm circular import



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janekl added a commit that referenced this pull request Jun 12, 2024
…rategy (#9387)

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JesusPaz pushed a commit to JesusPaz/NeMo that referenced this pull request Jun 18, 2024
* update launcher name and fix mm circular import



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rohitrango pushed a commit to rohitrango/NeMo that referenced this pull request Jun 25, 2024
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---------

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---------

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* lora inject to attention

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* support …
@ko3n1g ko3n1g mentioned this pull request Jul 18, 2024
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3 participants