Add search parameters

Author: shaahji

olive/passes/onnx/model_builder.py

@@ -25,6 +25,7 @@
 from olive.passes import Pass
 from olive.passes.olive_pass import PassConfigParam
 from olive.passes.pass_config import BasePassConfig
+from olive.search.search_parameter import Boolean, Categorical
 
 logger = logging.getLogger(__name__)
 
@@ -83,11 +84,16 @@ def _default_config(cls, accelerator_spec: AcceleratorSpec) -> dict[str, PassCon
             "int4_block_size": PassConfigParam(
                 type_=ModelBuilder.BlockSize,
                 required=False,
+                search_defaults=Categorical([
+                    ModelBuilder.BlockSize.B32,
+                    ModelBuilder.BlockSize.B64,
+                    ModelBuilder.BlockSize.B128]),
                 description="Specify the block_size for int4 quantization. Acceptable values: 16/32/64/128/256.",
             ),
             "int4_is_symmetric": PassConfigParam(
                 type_=bool,
                 required=False,
+                search_defaults=Boolean(),
                 description="Specify whether symmetric or asymmetric INT4 quantization needs to be used.",
             ),
             "int4_op_types_to_quantize": PassConfigParam(
@@ -106,6 +112,12 @@ def _default_config(cls, accelerator_spec: AcceleratorSpec) -> dict[str, PassCon
             "int4_algo_config": PassConfigParam(
                 type_=str,
                 required=False,
+                search_defaults=Categorical([
+                    "default",
+                    "rtn",
+                    "k_quant_mixed",
+                    "k_quant_last",
+                ]),
                 description="Specify the INT4 quantization algorithm to use in GenAI Model Builder",
             ),
             "use_qdq": PassConfigParam(

olive/passes/pytorch/selective_mixed_precision.py

@@ -20,6 +20,7 @@
 from olive.passes import Pass
 from olive.passes.pass_config import BasePassConfig, PassConfigParam
 from olive.passes.pytorch.train_utils import get_calibration_dataset, kl_div_loss, load_hf_base_model
+from olive.search.search_parameter import Boolean, Categorical
 
 if TYPE_CHECKING:
     from olive.hardware.accelerator import AcceleratorSpec
@@ -65,7 +66,11 @@ def _default_config(cls, accelerator_spec: AcceleratorSpec) -> dict[str, PassCon
         return {
             "algorithm": PassConfigParam(
                 type_=SelectiveMixedPrecision.Algorithm,
-                required=True,
+                required=False,
+                search_defaults=Categorical([
+                    SelectiveMixedPrecision.Algorithm.K_QUANT_DOWN,
+                    SelectiveMixedPrecision.Algorithm.K_QUANT_MIXED,
+                    SelectiveMixedPrecision.Algorithm.K_QUANT_LAST]),
                 description="The algorithm to use for mixed precision.",
             ),
             "bits": PassConfigParam(