Enable specifying alpha for PTQ INT8 SmoothQuant method

[janekl]

What does this PR do ?

Allow users to specifying alpha for INT8 SmoothQuant method. For example, setting it to 0.8 improves Llama3 (8b, 70b) MMLU accuracy results compared to default alpha=1.0.

| MODEL      |   ALPHA |   MMLU |
|------------|---------|--------|
| LLAMA3-70B |    0    |  0.004 |
| LLAMA3-70B |    0.25 |  0.116 |
| LLAMA3-70B |    0.5  |  0.516 |
| LLAMA3-70B |    0.7  |  0.765 |
| LLAMA3-70B |    0.75 |  0.77  |
| LLAMA3-70B |    0.8  |  0.772 |
| LLAMA3-70B |    0.85 |  0.766 |
| LLAMA3-70B |    0.9  |  0.75  |
| LLAMA3-70B |    1    |  0.728 |
| LLAMA3-8B  |    0    |  0.062 |
| LLAMA3-8B  |    0.25 |  0.227 |
| LLAMA3-8B  |    0.5  |  0.379 |
| LLAMA3-8B  |    0.7  |  0.617 |
| LLAMA3-8B  |    0.75 |  0.624 |
| LLAMA3-8B  |    0.8  |  0.625 |
| LLAMA3-8B  |    0.85 |  0.62  |
| LLAMA3-8B  |    0.9  |  0.619 |
| LLAMA3-8B  |    0.95 |  0.612 |
| LLAMA3-8B  |    1    |  0.594 |

Collection: NLP

Changelog

• Add specific line by line info of high level changes in this PR.

Usage

• You can potentially add a usage example below

python megatron_quantization.py \
    ...   
    quantization.algorithm=int8_sq \
    quantization.alpha=0.5 \
    ....

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Additional Information

• Related to # (issue)

[oyilmaz-nvidia]

LGTM.