From 528d7de6fdc42185d98d147c9e10d3f56daf8090 Mon Sep 17 00:00:00 2001
From: "Wang, Chang" <chang1.wang@intel.com>
Date: Wed, 20 Mar 2024 08:54:17 +0800
Subject: [PATCH] Fix gptq desc_act and static_group (#1395)

---
 .../llm/quantization/nn/modules.py            | 41 ++++++++++---------
 .../transformers/modeling/modeling_auto.py    |  2 +-
 2 files changed, 22 insertions(+), 21 deletions(-)

diff --git a/intel_extension_for_transformers/transformers/llm/quantization/nn/modules.py b/intel_extension_for_transformers/transformers/llm/quantization/nn/modules.py
index 7b81f87d5d9..0d85a3b9f86 100644
--- a/intel_extension_for_transformers/transformers/llm/quantization/nn/modules.py
+++ b/intel_extension_for_transformers/transformers/llm/quantization/nn/modules.py
@@ -169,22 +169,27 @@ def set_weights_bias(
         q_config,
         bias=None,
     ):
-        if q_config.quant_method.value == "gptq" and (
-            q_config.desc_act and not q_config.static_groups
-        ):
-            int_weight2 = int_weight.clone()
-            group_size = q_config.group_size
-            group_dict = {}
-            for i in range(len(g_idx)):
-                group_idx = g_idx[i].item()
-                if group_idx not in group_dict:
-                    target_idx = group_idx * group_size
-                    group_dict[group_idx] = 0
+
+        if q_config.quant_method.value == "gptq":
+            if q_config.desc_act:
+                if not q_config.static_groups:
+                    int_weight2 = int_weight.clone()
+                    group_size = q_config.group_size
+                    group_dict = {}
+                    for i in range(len(g_idx)):
+                        group_idx = g_idx[i].item()
+                        if group_idx not in group_dict:
+                            target_idx = group_idx * group_size
+                            group_dict[group_idx] = 0
+                        else:
+                            group_dict[group_idx] = group_dict[group_idx] + 1
+                            target_idx = group_idx * group_size + group_dict[group_idx]
+                        int_weight2[target_idx] = int_weight[i]
+                    int_weight = int_weight2
                 else:
-                    group_dict[group_idx] = group_dict[group_idx] + 1
-                    target_idx = group_idx * group_size + group_dict[group_idx]
-                int_weight2[target_idx] = int_weight[i]
-            int_weight = int_weight2
+                    g_idx = torch.empty(0, dtype=torch.int32)
+            else:
+                g_idx = torch.empty(0, dtype=torch.int32)
 
         if q_config.bits == 4:
             int_weight = (int_weight - 8) * 16
@@ -194,11 +199,7 @@ def set_weights_bias(
         if q_config.sym:
             gptq_zeros = torch.empty(0, dtype=torch.int8)
 
-        if (
-            q_config.quant_method.value != "gptq"
-            or q_config.static_groups
-            or (not q_config.desc_act)
-        ):
+        if q_config.quant_method.value != "gptq":
             g_idx = torch.empty(0, dtype=torch.int32)
 
         packw = torch.ops.bestlaop.woq_packq(
diff --git a/intel_extension_for_transformers/transformers/modeling/modeling_auto.py b/intel_extension_for_transformers/transformers/modeling/modeling_auto.py
index f50d7e8e4ef..ec7d66c35f7 100644
--- a/intel_extension_for_transformers/transformers/modeling/modeling_auto.py
+++ b/intel_extension_for_transformers/transformers/modeling/modeling_auto.py
@@ -67,7 +67,6 @@
     convert_to_quantized_model,
     replace_linear,
 )
-from ..llm.quantization.nn.modules import QuantizedLinearQBits
 from neural_compressor.adaptor.torch_utils.model_wrapper import WeightOnlyLinear
 from transformers.configuration_utils import PretrainedConfig
 from transformers import AutoConfig
@@ -83,6 +82,7 @@ def recover_export_model(model, current_key_name=None):
 
     Return optimum format model.
     """
+    from ..llm.quantization.nn.modules import QuantizedLinearQBits
     for name, module in model.named_children():
         if current_key_name is None:
             current_key_name = []