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Fix T5 G2P Input and Output Types #9269

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What does this PR do ?

Fix T5 G2P Input and Output Types

Collection: tts

Changelog

  • Fix T5 G2P Input and Output Types

PR Type:

  • New Feature
  • Bugfix
  • Documentation

If you haven't finished some of the above items you can still open "Draft" PR.

* fix t5 g2p model

Signed-off-by: Jason <jasoli@nvidia.com>

* Apply isort and black reformatting

Signed-off-by: blisc <blisc@users.noreply.github.com>

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Signed-off-by: Jason <jasoli@nvidia.com>
Signed-off-by: blisc <blisc@users.noreply.github.com>
Co-authored-by: blisc <blisc@users.noreply.github.com>
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github-actions bot commented Jun 5, 2024

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.

@github-actions github-actions bot added the stale label Jun 5, 2024
@blisc blisc merged commit 3b758de into main Jun 6, 2024
133 checks passed
@blisc blisc deleted the cherry-pick-main-91003a09d38c687320037644625270d57ed5e27d branch June 6, 2024 13:01
marcromeyn pushed a commit that referenced this pull request Jun 7, 2024
* fix t5 g2p model

* Apply isort and black reformatting

---------

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Co-authored-by: Eric Harper <complex451@gmail.com>
Signed-off-by: Marc Romeyn <mromeijn@nvidia.com>
akoumpa added a commit that referenced this pull request Jun 10, 2024
…rategy (#9387)

* Integrating mcore's DistributedDataParallel into MegatronStrategy

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* Apply ddp-hooks from pytorch only when needed

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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 (#9083)

* 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 (#8953)

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

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* Changes to enable CUDA graph for LLM (#8955)

* Changes to enable CUDA graph for LLM (#8751)

* Use next instead of get_batch

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* Change to enable CG with weight caching

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* Cleanup

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* Revert "Revert "Copy jbaczek/mcore_parallel_state_api_change branch leaving out changes to nemo/export/quantize/quantizer.py""

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* Fix merge conflicts

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* Enhance Distributed Adam (#9051)

* Enhance Distributed Adam (#9037)

* Fix deprecated env.

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* Use user desired value for distributed adam.

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* Preserve memory format in parameter buffer of distributed adam.

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* Fix the contiguous_param_buffer bug about bprop overlap and redundant copy after all-gather.

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

* Fixed clustering diarizer to load MSDD to GPU by default if cuda on

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

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* ci: Fix sending alerts on failure

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* fix

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* fix

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* fix

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* increase timeout for `Speech_Checkpoints_tests`

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* improve readability

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* fix

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* all your comments are belong to us

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* Fix T5 G2P Input and Output Types (#9224) (#9269)

* fix t5 g2p model

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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
outputs from these operations, even if their inputs are fp16. See
here: https://pytorch.org/docs/stable/amp.html#cuda-ops-that-can-autocast-to-float32

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.

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

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* Huvu/rag pipeline citest (#9384)

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* Re-org export code (#9353)

* reorg the export code

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janekl pushed a commit that referenced this pull request Jun 12, 2024
* fix t5 g2p model



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

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* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* update module args

Signed-off-by: ericharper <complex451@gmail.com>

* add config to self

Signed-off-by: ericharper <complex451@gmail.com>

* build transformer config

Signed-off-by: ericharper <complex451@gmail.com>

* add model to provider func

Signed-off-by: ericharper <complex451@gmail.com>

* update forward and float16 wrapper

Signed-off-by: ericharper <complex451@gmail.com>

* instantiate model parallel config after init model parallel

Signed-off-by: ericharper <complex451@gmail.com>

* set virtual rank

Signed-off-by: ericharper <complex451@gmail.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Add GQA config to megatron gpt model (#7096)

* Add GQA config in gpt config file

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* Verify mcore is enabled when using GQA

Signed-off-by: jasonwan <jasonwan@nvidia.com>

---------

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* revert

Signed-off-by: ericharper <complex451@gmail.com>

* remove import

Signed-off-by: eharper <eharper@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* rollback model cast for p-tuning

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* update for dist adam

Signed-off-by: eharper <eharper@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* use get_gpt_module_list

Signed-off-by: eharper <eharper@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* update ckpt conversion script

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* ptl2.0 patch for llama config

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* add plugins to trainer in scripts

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* fix activation checkpointing mcore

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* fix variable names

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* overwrite normalization type for mcore/te

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* Update megatron_llama_sft.yaml

Signed-off-by: Jason Wang <jasonwan@nvidia.com>

* add PEFT adapter support for mcore gpt path (#7276)

* implementation for mcore adapter/mxins

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* small fix for lora and ptuning

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* support layerwise peft

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* support multiple target layers

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* support lora GQA

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* support amp O2

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* revert & more O2 fix

Signed-off-by: jasonwan <jasonwan@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* lora inject to attention

Signed-off-by: jasonwan <jasonwan@nvidia.com>

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