Update WOQ AutoRoundConfig parameter

examples/huggingface/pytorch/text-generation/quantization/run_generation_cpu_woq.py

@@ -154,7 +154,7 @@
     help="minmax learning rate, if None,it will beset to be the same with lr",
 )
 parser.add_argument(
-    "--enable_quanted_input",
+    "--disable_quanted_input",
     action="store_true",
     help="whether to use the output of quantized block to tune the next block",
 )
@@ -286,7 +286,7 @@
             calib_len=args.calib_len,
             lr=args.lr,
             minmax_lr=args.minmax_lr,
-            enable_quanted_input=args.enable_quanted_input,
+            disable_quanted_input=args.disable_quanted_input,
             use_ipex=args.use_ipex,
         )
     else:

intel_extension_for_transformers/transformers/llm/quantization/utils.py

@@ -527,7 +527,7 @@ def default_calib_func(model):
                     "seqlen": config.calib_len,
                     "iters": config.iters,
                     "scale_dtype": config.scale_dtype,
-                    "enable_quanted_input": config.enable_quanted_input,
+                    "enable_quanted_input": not config.disable_quanted_input,
                     "lr": config.lr,
                     "minmax_lr": config.minmax_lr,
                 }

intel_extension_for_transformers/transformers/utils/config.py

@@ -1056,7 +1056,7 @@ def __init__(
         sym: bool = False,
         lr: float = None,
         minmax_lr: float = None,
-        enable_quanted_input: bool = True,
+        disable_quanted_input: bool = False,
         nsamples: int = 512,
         iters: int = 200,
         use_ggml: bool = False,
@@ -1083,7 +1083,7 @@ def __init__(
         self.group_size = group_size
         self.lr = lr
         self.minmax_lr = minmax_lr
-        self.enable_quanted_input = enable_quanted_input
+        self.disable_quanted_input = disable_quanted_input
         self.iters = iters
         self.llm_int8_skip_modules = (
             llm_int8_skip_modules if llm_int8_skip_modules else []