Fix CompressedTensorsWNA16MoE with grouped scales

[mgoin]

Eval on main:

vllm (pretrained=nm-testing/Qwen1.5-MoE-A2.7B-Chat-quantized.w4a16,dtype=float16,trust_remote_code=True), gen_kwargs: (None), limit: None, num_fewshot: 5, batch_size: auto
|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value|   |Stderr|
|-----|------:|----------------|-----:|-----------|---|----:|---|-----:|
|gsm8k|      3|flexible-extract|     5|exact_match|↑  |    0|±  |     0|
|     |       |strict-match    |     5|exact_match|↑  |    0|±  |     0|

Eval on this PR:

vllm (pretrained=nm-testing/Qwen1.5-MoE-A2.7B-Chat-quantized.w4a16,dtype=float16,trust_remote_code=True), gen_kwargs: (None), limit: None, num_fewshot: 5, batch_size: auto
|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|     5|exact_match|↑  |0.4556|±  |0.0137|
|     |       |strict-match    |     5|exact_match|↑  |0.2964|±  |0.0126|

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[mgoin]

cc @dsikka @ElizaWszola

[dsikka]

Have we verified the other MoE models with this change?
At least to make sure generations are coherent.

[mgoin]

I ran Mixtral and that worked well

vllm (pretrained=nm-testing/Mixtral-8x7B-Instruct-v0.1-W4A16-quantized,trust_remote_code=True), gen_kwargs: (None), limit: None, num_fewshot: 5, batch_size: auto
|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|     5|exact_match|↑  |0.6141|±  |0.0134|
|     |       |strict-match    |     5|exact_match|↑  |0.6111|±  |0.0134|