GitLab

* fixes L1 test

* fix test_multigpu_encoder

* fixes for other multi-encoder tests

* jax.extend.ffi to jax.ffi

* initialization with float32

* add init_dtype as an optional arg to all modules

* update use_scan query from xla flags

* relax threshold for test_encoder fp8

* relax the tols

---------
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* add test_multiprocessing_encoder with processing spawning in bash

---------
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Skip encoder tests on V100

* Fix mulitprocessing jax.distributed.init

* Remove XLA xla_gpu_deterministic_ops which causes segfault

---------
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Create README.md

added all PyT examples
Signed-off-by: Santosh Bhavani <santosh.bhavani@live.com>

* Update README.md

- Added JAX, PaddlePaddle, and third-party examples
- Fixed DL framework links
- Removed issue request for new PRs
Signed-off-by: Santosh Bhavani <sbhavani@nvidia.com>

---------
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* Use jit instead of pjit

---------
Signed-off-by: Frederic Bastien <fbastien@nvidia.com>
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* Switch to nltk>3.8.1 and new data
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* fix nltk install
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

---------
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

[C/PyTorch] Fixed incorrect use of `torch.distributed.new_group()` when creating intra-node group in `initialize_ub()` (#1087)

* updated initialize_ub() to use new_subgroups_by_enumeration() to generate intra-node groups, added new unit tests for TE layers with comm overlap
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[PyTorch] Fixing hang in `initialize_ub()` for multi-node runs after PR901 removal of MPI-dependence (#986)

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

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* multi-node example working with UB_SKIPMC=1 but not with multicast
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* fixed multi-node hang in initialize_ub(), updated comm+GEMM overlap example to support multi-node mixed tensor/data parallelism, added README
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* fixed use case when Userbuffers is asked to allocate the TP overlap buffer with UB_SKIPMC=1
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* corrected example problem to set device by local ordinal instead of global process rank
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* double-free fix in userbuffers destructor
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* removed unnecessary and incorrect torch.cuda.set_device(...)
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* corrected inter-node ranks logic
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* generalized node ID logic in initialize_ub to handle arbitrary world rank layouts within node
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* added single-node comm+GEMM overlap unit tests
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* LayerNormMLP example confirmed working with 2 nodes on Eos
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* unit test cleanup
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* corrected DP group ranks logic in LNMLP comm+GEMM overlap example
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* corrected enums in unit test
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* fixed incorrect Ubuf object init signature
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* switched default backend for Userbuffer bootstrapping to Gloo with MPI and NCCL fallbacks, and initialize_ub option to manually select backend
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* fixed all comm+GEMM overlap unit tests
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* corrected all_gather use for Gloo backend
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* disabled scoped GIL release for comm+GEMM overlap algorithms
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* avoid dist.init_device_mesh in comm+GEMM overlap example to support older PyTorch versions
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* applied RS overlap FP8 fix from PR1004
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* fixed segfault in Userbuffers destructor
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* corrected comm+GEMM overlap unit test arguments
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* fixed unit test run command for when Userbuffers is compiled with MPI
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* rm tensor check if the workspace is empty
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* add trust_remote=true for load_dataset() in the mnist test
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---------
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* Apply formatting
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* Apply formatting
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

---------
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* added DL framework callbacks for bootstrapping userbuffers without MPI
Signed-off-by: Alp Dener <adener@nvidia.com>

* removed userbuffers availability check in TE modules since userbuffers is now always compiled
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* added comm+GEMM overlap example with LayerNormMLP
Signed-off-by: Alp Dener <adener@nvidia.com>

* lintin and review fixes
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* linting and review fixes
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* added header guards
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* removed transformer_engine/CMakeLists.txt and shifted all TE/common compile into transformer_engine/common/CmakeLists.txt
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* Reformat FP8 Meta

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2. Remove fp8_max and scale_inv.
3. Remove unused functions in fp8.py
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix unit-tests
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Remove ShardingType and MajorShardingType
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* Fix lint errors
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* Fixed unittests.
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* Rename few variables.
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* Add jit to update_amax_list
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* Fixed naming error in LayernormMLP
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* Fixed bugs in test_distributed_layernorm_mlp.py
Signed-off-by: Ming Huang <mingh@nvidia.com>

---------
Signed-off-by: Ming Huang <mingh@nvidia.com>

* New TE wrapper for PyTorch FullyShardedDataParallel to make TE modules distribute their activations after the forward pass and gather them before the backward pass
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* simplified TE module setup for FSDP comms
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* FSDP scatter/gather for tensors saved into autograd ctx now working for base TE modules
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* Fixed typo in attribute name
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* fixed bug in finding FSDP-wrapped TE modules
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* fixed typo in fp8 weight tensor name
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* fixed incorrect # of gradients
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* Added fp8 amax gradient hook tensor to the parameter reset
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* get rid of erroneous dummy tensor leftover from incorrect rebase
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* Linting fixes
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* fixing git snafu and removing debug statements
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* Allow multi-dims for dgamma and dbeta in LN descriptor.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix the jit error in examples/jax
Signed-off-by: Ming Huang <mingh@nvidia.com>

---------
Signed-off-by: Ming Huang <mingh@nvidia.com>

* fixed static argnums for jax.jit in single gpu encoder test, changed warning filtering for pytest
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* propagating the fix to the JAX mnist example
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* fixed missing space ibetween flags i QAA scripts
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* added TE warnings into the ignore list
Signed-off-by: Alp Dener <adener@nvidia.com>

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* Adding support of sequence parallelism
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding RoPE
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix wrong batch_logical_axes
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Rnaming FSDP outer env var
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* Poring RoPE to Praxis layers.
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* Porting GeLU + [FP8 Cast].
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* WAR to make XLA successfully match FP8 GEMM on FFN1 with GeLU.
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* Allowing arbitrary dimension of NVShape for the workspace allocation
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* Adding checkpoint_name to fused functions of mlp.py to get better perf with nn.scan.
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* Modify with review feedback.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix bugs
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix typo.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fixed for lint
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* Follow review feedback to modify code.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix typo.
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* Port SP to Praxis
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* Fix an issue when enabling both GQA and RoPE.
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* Update docs
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

---------
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

Signed-off-by: hugo-syn <hugo.vincent@synacktiv.com>

* Implemented deferred initialization via `device='meta'` option for te.Linear and added new PyTorch example to demonstrate its use with FullyShardedDataParallel execution.
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* correcting Float8Tensor initialization and fixing linting errors
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* removed duplicate code from upstream rebase, local tests passing
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* improved comments/documentation for FSDP example
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* converted reset_parameters() into a base module function
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* fixed Float8Tensor creation with deferred init, all tests passing locally
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* extended deferred initialization to all TE modules
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* fixed linting errors
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* removed unnecessary reference to the parent module of parameter, added clarifying comments in parameter reset
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---------
Signed-off-by: Alp Dener <adener@nvidia.com>

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* Migrating both FWD and BWD of all kinds of softmax from xmap to custom_partitioning.
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* Fix the wrong order of parameters to LN/RMSN bwd in ln_mlp_fp8.
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* WAR to LN/RMSN_fp8 before migrating to CP.
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* Fix the wrong order of parameters of bwd of LN/RMSN_fp8.
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* Following review feedback to modify
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* Force the hidden dim in Norm ops to no sharding and add warning msg.
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* add gelu and dgelu.
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* Reuse fwd_rule in VJP functions for attentions
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* Apply native FP8 Dtypes to fp8.py
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* Migrating cast_and_transpose from xmap to custom_partitioning
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* Migrating transpose from xmap to custom_partitioning
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* Apply XLA pattern match to perform FP8 GEMM.
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* migrate layernorm_fp8 to custom_partitioning.
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* Miner fix
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* Update README and Add deprecating warning to *ShardingType
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* Adding assertion for non-supported batch dims.
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Signed-off-by: Ming Huang <mingh@nvidia.com>

---------
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>
Co-authored-by: Donglin Yang <dongliny@nvidia.com>

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Signed-off-by: Tim Moon <tmoon@nvidia.com>

---------
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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* [Paddle] Add TP, DP, PP, FSDP
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* Minor fix
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* Fix CI failure
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* Fix numel performance issue
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* Squashed commit of the following:

commit 79e2e5fd774e67dcdda9aae01a9f31a6479c5d70
Author: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>
Date:   Sun Aug 20 14:39:16 2023 +0000

    Add TP test
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

commit 1d40ad60540490f97ed82ba877cc6eda8902cbf6
Author: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>
Date:   Sun Aug 20 14:22:25 2023 +0000

    Fix tp_size when disabled
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

commit 6632f735a0c8251862355fc74622af59fae3a509
Author: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>
Date:   Sun Aug 20 05:52:18 2023 +0000

    Add TP for attention and transformer layer
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Add shape check
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Add FSDP check for stage 1,2,3
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Review changes
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Fix group_sharding test
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Support NVTE_FUSE_ATTN
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Fix CI errors
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

---------
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Cast Flax collections to FrozenDict as WAR to adapt Flax 0.7.1.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding min version of flax to requirements.txt in examples
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix praxis tests and rename compare_frozen_dict to compare_dict
Signed-off-by: Ming Huang <mingh@nvidia.com>

* [Paddle] Refactor FP8 state (#350)

Refactor fp8 state
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Store FP8 checkpointing data in CPU (#351)
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Make test_layer be able to run on both Flax >=0.7.1 and <=0.7.0
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Update Flax version
Signed-off-by: Tim Moon <tmoon@nvidia.com>

---------
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Tim Moon <tmoon@nvidia.com>
Co-authored-by: Tian Zheng <tizheng@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Co-authored-by: Tim Moon <tmoon@nvidia.com>

* Add FP8 support

- Add FP8 recipe
- Add FP8 path for nn layers
- Add MNIST FP8 example
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Update README
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Fix LayerNormMLP FP8 backward
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Fix FP8 training in float32 accumulation
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Fix FP8 checkpointing for non forward execution cases (same as #323)
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Refactors and improvements for better code stype, readability and organization
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Remove unnecassary pylint override
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

---------
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Add Linear layer (FP16)
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

- Add BF16 training example
- Add fp8_autocast (only supports non-fp8 for now)
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Remove FP8 stuff
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Simplify Linear layer forward
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Add LayerNorm layer (BF16)
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Add LayerNormLinear layer
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Store weights in BF16
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Add LayerNormMLP layer
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Add BF16 MNIST example
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Remove in-place cast for compatibility with Paddle AMP mechanism
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* README correction
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Add Paddle op as a backend option
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Fix code format
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Fix dtype change between iterations
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Minor fixes
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Move forward function out of base layer
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Use Paddle nvtx bindings
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

---------
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Fully remove attn_type and set self_attn_mask_type default to 'causal'
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Fix tests with new arguments
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Explicit self_attn_mask_type for examples
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Update transformer_engine/jax/flax/transformer.py
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: zlsh80826 <rewang@nvidia.com>

* Update transformer_engine/jax/flax/transformer.py
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: zlsh80826 <rewang@nvidia.com>

---------
Signed-off-by: Reese Wang <rewang@nvidia.com>
Signed-off-by: zlsh80826 <rewang@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fix example
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Review
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

---------
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Enable fused attention dropout
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Cast the uint32 key/counter to int64
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Update dropout support in fused attention docs
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Revise devPtrCuSeqlen* to align the naming
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Support different Jax PRNG impls
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Revert CastAsync since it is not used
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Implement is_training for 16-bit fused attn
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add fused attn with dropout sanity unit tests
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Enhance the comments readability and rng_state checker
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Change the attention dropout shape to align other frameworks
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Make encoder tests deterministic
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Change the default seed for the jax encoder tests
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Maintain offset in TE
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Enhance the resource safety
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Revert rng_state type to allow only i64
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Handle the corner case for elts_per_threads calculation
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Populate rng state by kernels
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Rename rng_state as seed in cpp_extensions
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Update the attention dropout comment
Signed-off-by: Reese Wang <rewang@nvidia.com>

---------
Signed-off-by: Reese Wang <rewang@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Adding JAX/Praxis modules and dependencies.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding UTs to JAX/Praxis modules.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Remove praxis as a dependency due to not strictly needed
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Repalce is_fp8_supported to is_fp8_available
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Make Praxis as an optional dependency.

1. Removed 'from . import praxis' in __init__.py.
    1.1 Noted, keep 'from . import flax' for deprecated warning.
2. Changed te.flax to te_flax in examples and README.rst.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding a workaround to FP8 training on Praxis.
Signed-off-by: Ming Huang <mingh@nvidia.com>

---------
Signed-off-by: Ming Huang <mingh@nvidia.com>

bugfix for softmax lowering
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* add mp example
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* update doc-string
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* better FP8 checker
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* update readme
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* replace te.* with te.flax* to remove deprecated warning
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* remove nouse os.environ
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* remove nouse
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix typo
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update examples/jax/encoder/README.md
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update examples/jax/encoder/README.md
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update examples/jax/encoder/README.md
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update examples/jax/encoder/README.md
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update examples/jax/encoder/test_multiprocessing_encoder.py
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* remove cuda-python
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* adjust readme
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update examples/jax/encoder/README.md
Signed-off-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix cpp lint

fix issue of "Could not find a newline character at the end of the file."
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix AssertionError: 1 GPU per process
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* replace tfds with datasets

The Flax application crash if it use TensorFlow Dataset (tfds) in NVIDIA JAX container.
The tfds is very useful for downloading well-knwon dataset (e.g., MNIST, GLUE) and commonly used by TF/JAX community.
However, it seems like that it is NOT compatible with NVIDIA TensorFlow in NVIDIA JAX container and somehow affects JAX.
It triggers random errors at JAX initialization depending on different versions, and make CI unstable.
Thus, this commit replaces tfds with "huggingface datasets" to download needed datasets.
See "nvbugs 4039266" for more details.
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix input sharding

Unlike SPMD mode, in multiprocessing mode, the input tensor must be sharded manually.
Using DP=4, TP=2 as an example, the device mesh looks like:

mesh.device_ids = [[0, 1],
                   [2, 3],
                   [4, 5],
                   [6, 7]]

Assume that the process ID is mapped to GPU ID.
The process 0 and process 1 are grouped for model parallelism,
process 2 and process 3 are grouped together too, and so on.

The process 0 and process 1 need to share the same micro-batch in the training step,
process 0 and process 2, 4, and 6 have different micro-batch.

Thus, `shard_array_wrapper` partitions inputs to 4 parts (and setup
needed arguments for jax.make_array_from_single_device_arrays).
The process 0 and process 1 take the first quarter,
process 2 and process 3 take the second quarter, and so on.
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor UT for multiprocess example

Use Python `multiprocessing` to test the multiprocessing example,
if the system has multiple GPU. 1 GPU per process.

Because `jax.distributed.initialize` must be called before any other JAX or Flax API,
GPU info cannot be queried by calling jax.local_devices() in TestEncoder.
Thus, `unittest_query_gpu()` forks another process to query number of GPUs and
FP8 capability.
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* remove nouse arg `--num-gpu`

JAX doesn't have an API to setup number of GPU used in SPMD mode.
The only way is to use `CUDA_VISIBLE_DEVICES` for now.
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix typo
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix ut
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* simplify the mask setting
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* increase batch-size for multigpu example

The batch-size 64 is too small to be partitioned for 8xH100.
If batch-size is 64, the GEMM shape is 256x8192x8 per GPU.
The 8 is too small for FP8 GEMM kernel, and
cuBLASLt will throw "Failed to query heuristics".
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix downloading mnist error

To download MNIST via `huggingface datasets`, it requires Pillow.
Otherwise, it throws `An error occurred while generating the
dataset`
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

---------
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Signed-off-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>

* Adjust Module Structure.

1. Collect Flax related modules to a sub-folder, flax.
2. Add a function to unify scale_init for zero-centered-gamma LN.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Make changes be compatible to previous versions.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adapt jax/examples to the new module structure.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Update jax/docs and Add deprecated warning.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Update README
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding deprecated_wrapper
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding deprecated warning to flax modules which imported via transformer_engine.jax
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix CI errors and update docs.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Removing unnecessary deprecated warning in docs.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Implementing __iter__ to DeprecatedEnum.
Signed-off-by: Ming Huang <mingh@nvidia.com>

---------
Signed-off-by: Ming Huang <mingh@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* refactor JAX examples
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix doc-string
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* add dp example
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix params_axes_pspec
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Add model parallel example and refactor
Update readme
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* align code and readme
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* update verification
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* add mask
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* num_gpu is configurable
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* update readme
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* update readme
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* solvepylint issue
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* ignore markdown and txt file from license check
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update README.md
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* add flax into requirements.txt
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

---------
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Add tensorflow build

Improve build instructions

Fix pybind enum usage

Fix Python_EXECUTABLE cmake var

Move scale_inv calculations to FW
Signed-off-by: Trevor Morris <tmorris@nvidia.com>
Signed-off-by: kaixih <kaixih@nvidia.com>

* Apply clang-format
Signed-off-by: Trevor Morris <tmorris@nvidia.com>
Signed-off-by: kaixih <kaixih@nvidia.com>

* Format python files
Signed-off-by: Trevor Morris <tmorris@nvidia.com>
Signed-off-by: kaixih <kaixih@nvidia.com>

* Add TF build CI
Signed-off-by: Trevor Morris <tmorris@nvidia.com>
Signed-off-by: kaixih <kaixih@nvidia.com>

* Lint checks
Signed-off-by: kaixih <kaixih@nvidia.com>

* Another round of lint checks
Signed-off-by: kaixih <kaixih@nvidia.com>

* Fix TF image tag
Signed-off-by: Trevor Morris <tmorris@nvidia.com>
Signed-off-by: kaixih <kaixih@nvidia.com>

* Use the existing recipe file
Signed-off-by: kaixih <kaixih@nvidia.com>

* Add license claim blocks
Signed-off-by: kaixih <kaixih@nvidia.com>

* Fix a bug about bias dtype conversion
Signed-off-by: kaixih <kaixih@nvidia.com>

* Add mnist example and cleanup old examples
Signed-off-by: kaixih <kaixih@nvidia.com>

* Autopep8 the tests
Signed-off-by: kaixih <kaixih@nvidia.com>

* Autopep8 the examples
Signed-off-by: kaixih <kaixih@nvidia.com>

* Add example in Readme
Signed-off-by: kaixih <kaixih@nvidia.com>

* Add unit tests and linting for TensorFlow
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Add causal mask for non-fused case
Signed-off-by: kaixih <kaixih@nvidia.com>

* Fix the mismatched TF vs TE masks
Signed-off-by: kaixih <kaixih@nvidia.com>

* Addressing CI tests
Signed-off-by: kaixih <kaixih@nvidia.com>

* Run lint test
Signed-off-by: kaixih <kaixih@nvidia.com>

* Add missing import
Signed-off-by: kaixih <kaixih@nvidia.com>

* Skip fp8 tests for pre-Hopper GPUs
Signed-off-by: kaixih <kaixih@nvidia.com>

* Remove non-pytest tests
Signed-off-by: kaixih <kaixih@nvidia.com>

* Fix license
Signed-off-by: Tim Moon <tmoon@nvidia.com>

---------
Signed-off-by: Trevor Morris <tmorris@nvidia.com>
Signed-off-by: kaixih <kaixih@nvidia.com>
Signed-off-by: Tim Moon <tmoon@nvidia.com>
Co-authored-by: kaixih <kaixih@nvidia.com>
Co-authored-by: Tim Moon <tmoon@nvidia.com>

* add transformer module , unittests and examples
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update tests/jax/test_sharding.py
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>

* Update transformer_engine/jax/transformer.py
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>

* remove pylint: disable=line-too-long
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* remove pylint: disable=too-many-func-args
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Fix the wrong broadcasting dim to dropout masks when enable transpose_bs.
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Enable 2xACC for WGRAD and DGRAD by default
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* rename LayerNormMlpBlock as LayerNormMLP
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor to avoid line-too-long
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* rename amax_history_size to amax_history_len
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* align dropout mask to TE/PyTorch as default
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* enlarge atol for decoder unittests

Two decoder unittests can pass in old JAX container(e.g., 23.02)
but can't in latest container (devel).

1. The actual(-0.020264) and desired(-0.020386) are very close.
2. The TE kernels are not changed, the diff should come from
   new codegen behavior of XLA.

Thus, it is a common floating-point accumulated error.
Enlarge atol to avoid unittest failures.
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Adding Amax History Support

1. hide amax update in custom_vjp
2. replace amax indexing with roll(using circular buffer)
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* move kernel_init to __post_init__
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor encoder examples
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update transformer_engine/jax/fp8.py
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>

* Update transformer_engine/jax/fp8.py
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>

* remove envvar regarding 2xACC
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* remove unused import
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

---------
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Co-authored-by: Ming-Xu Huang <mingh@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Initial commit for fp8 calibration.
Signed-off-by: Sharan Chetlur <schetlur@dlcluster.nvidia.com>

* Fixes to make unit tests pass
Signed-off-by: Sharan Chetlur <schetlur@dlcluster.nvidia.com>

* Added test and finished implementation
Signed-off-by: Sharan Chetlur <schetlur@nvidia.com>

* Cleaning up handling of save_for_backward in Linear
Signed-off-by: Sharan Chetlur <schetlur@nvidia.com>

* Removing commented lines
Signed-off-by: Sharan Chetlur <schetlur@nvidia.com>

* Minor fix to mnist test.
Signed-off-by: Sharan Chetlur <schetlur@nvidia.com>

* Pylint cleanup
Signed-off-by: Sharan Chetlur <schetlur@nvidia.com>

* Moving stats computation to the forward pass instead of pre_forward, and extending to all other layers
Signed-off-by: Sharan Chetlur <schetlur@nvidia.com>

* Pylint cleanup
Signed-off-by: Sharan Chetlur <schetlur@nvidia.com>

* Pylint cleanup.
Signed-off-by: Sharan Chetlur <schetlur@nvidia.com>

* Fixing unit test failures.
Signed-off-by: Sharan Chetlur <schetlur@nvidia.com>

* Misc changes
Signed-off-by: Sharan Chetlur <schetlur@nvidia.com>

* Fixing bad indentation from master merge and moving some code into the needs_stats conditional
Signed-off-by: Sharan Chetlur <schetlur@nvidia.com>
Signed-off-by: Sharan Chetlur <schetlur@dlcluster.nvidia.com>
Signed-off-by: Sharan Chetlur <schetlur@nvidia.com>
Signed-off-by: schetlur-nv <116769508+schetlur-nv@users.noreply.github.com>
Co-authored-by: Sharan Chetlur <schetlur@dlcluster.nvidia.com>