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* reuse amax for current scaling
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* not fuse bias for output all reduction case + unit tests
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* norm to reduce dgamma along tpsp as well
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* clean up tests
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*Jax integration for clamped swiglu. This is the continuation of PR which added Clamped Swiglu(used in GPT OSS) support in TE along with Pytorch integration. This PR hooks up the clamped swiglu and dswiglu's nvte APIs to TE Jax.

fix rng_state shape
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* rm using_global_amax_of_x
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* init cgemm + unit tests

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* update misuse of TP warning
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* Rework shardy rules

* WAR for compound factor=1
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* Adding Amax Primitive and related args.
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* Enable local-amax for current-scaling and optionally run AR aross FSDP/TP/SP.
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* Adding doc for Amax Primitive.
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* Fix the function name conflict.
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* Modification as feedback suggested.
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* Fix the wrong amax-scope in the bwd.
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* Added more description for amax-scope
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* Fix the wrong attribute name.
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* Fix shardy_rule
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* Remove extra-collective bytes from ref_coll_count due to local amax.
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* remove import jax.extend.ffi
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* Applying the original precision as Norm outputs' and activation compuations.
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* Adding knob to control norm output precision.
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* Removing the knob and applying lower-precision norm with current-scaling only.
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* Fix the error when quantizer==None
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* add amax input to DBiasQuantizePrimitive and FFI
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* make sure amax is init with zero
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* Decouple recipe and scaling mode
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* FP8 AllGather in FP8 GroupedGEMM

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* added amax as an optional arg
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[JAX] Error checking for mesh resource and update GemmPrimitive to use global_mesh_resource().fsdp_resource (#2088)

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* fix fsdp
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* rm batch_dim, sequence_dim, sequence_parallel_output
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Revert "[JAX] Disable TE Norm Custom Calls (#1993)"

This reverts commit 6c970612

.

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Disable Norm custom calls
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[JAX] Fixing GemmPrimitive partitioning rules to handle tensor-parallelism correctly for sequence-parallel inputs (#1980)

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