Define Quantization within SparseGPTModifier

[Satrat]

• Updates the SparseGPT modifier to allow a quantization modifier to be defined under the SparseGPTModifier.quantization property within a recipe
• added a qat_active function to ModifiableModel, used to determine if quantization has already been applied
• boolean quantization is still supported, will log warnings for edge cases

Example

    SparseGPTModifier:
      sparsity: 0.5
      block_size: 128
      sequential_update: False
      quantize:
        QuantizationModifier:
          ignore: ["lm_head", "Embedding", "OPTLearnedPositionalEmbedding", "QuantizableBatchMatMul", "BMMLeftInput_QK", "BMMRightInput_QK", "BMMOutput_QK", "BMMLeftInput_PV", "BMMRightInput_PV", "BMMOutput_PV"]
          post_oneshot_calibration: True
          scheme_overrides:
            ReLU:
              input_activations: null
              output_activations: null
            LayerNorm:
              input_activations: null
              output_activations: null

Testing

Added unit tests for the different quantization conditions