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

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

* Fixing few issues with multi-process launching.
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* Custom call tests passing
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* Fix test_layer.py
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* Lint
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* Fix comments
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* Support using amax on HighPrecision tensor if it exists instead of recomputing for current scaling
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* Fix shardy issue with amax being shape 1,1,1 instead of shape (1,)
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* Add higher-precision VJP tests to test_distributed_layernorm_mlp
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* Cast non-quantized kernels to input dtype in VJPs
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* Rename HighPrecisionTensor to NoScaleTensor
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* Use NoScaleTensor in pure JAX impls where it was missing
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* Fix tests
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* Fix failing tests for dropout=0.1 and bias for fused attn for blackwell
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Add check for sm100
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* Code clean up
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* Decouple recipe and scaling mode
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* Rename UsageType to TensorSource
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* FP8 AllGather in FP8 GroupedGEMM

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* Slightly refactor
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* Move quantizaer store/reset into FP8 only.
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* Adding all layout support for Blackwell+
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* Fixed the wrong stream used by d2d in groupedGEMM FFI.
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---------
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* clean up sharding
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* added tpsp_resource
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* add mesh_resource into fp8_autocast in test_helper.py
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