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Signed-off-by: mgoin <michael@neuralmagic.com>

Signed-off-by: wangshuai09 <391746016@qq.com>

Signed-off-by: youkaichao <youkaichao@gmail.com>

Signed-off-by: wangshuai09 <391746016@qq.com>

Signed-off-by: charlifu <charlifu@amd.com>

Co-authored-by: Dipika <dipikasikka1@gmail.com>
Co-authored-by: Dipika Sikka <ds3822@columbia.edu>

Co-authored-by: Tyler Michael Smith <tyler@neuralmagic.com>

Co-authored-by: Dipika <dipikasikka1@gmail.com>

Co-authored-by: Robert Shaw <rshaw@neuralmagic>
Co-authored-by: Michael Goin <michael@neuralmagic.com>

[Kernel] Support MoE Fp8 Checkpoints for Mixtral (Static Weights with Dynamic/Static Activations) (#4527)

Follow on to #4332 to enable FP8 checkpoint loading for Mixtral and supersedes #4436.

This PR enables the following checkpoint loading features for Mixtral:

Supports loading fp8 checkpoints for Mixtral, such as this "nm-testing/Mixtral-8x7B-Instruct-v0.1-FP8" test model
Supports static or dynamic activation quantization with static weight quantization (all per tensor)
Supports different scales for each expert weight
Supports Fp8 in QKV layer
Notes:

The Expert Gate/Router always runs at half / full precision for now.
If there are different weight scales between QKV layer (for separate QKV weights), they are re-quantized using layer.weight_scale.max() so we can have a single gemm for performance.