fix convert_quantized model bug (#158)

Signed-off-by: Yu, Zhentao <zhentao.yu@intel.com>

Author: zhentaoyu

neural_speed/convert/convert_quantized_llama.py

@@ -71,7 +71,7 @@ def convert_to_q4_bestla_tensor(src_name, dst_name, model, fout, q_config, n_hea
         int_weight = (int_weight - 8) * 16
         gptq_scales = gptq_scales / 16
         gptq_zeros = (gptq_zeros - 8) * 16
-        weight_dtype == "int4"
+        weight_dtype = "int4"
 
     dst = np.zeros((int_weight.shape[0], int_weight.shape[1] * 4), dtype=np.int8)
     int_weight = np.ascontiguousarray(int_weight.numpy())

neural_speed/convert/convert_quantized_mistral.py

@@ -74,7 +74,7 @@ def convert_to_q4_bestla_tensor(src_name, dst_name, model, fout, q_config, n_hea
         int_weight = (int_weight - 8) * 16
         gptq_scales = gptq_scales / 16
         gptq_zeros = (gptq_zeros - 8) * 16
-        weight_dtype == "int4"
+        weight_dtype = "int4"
 
     dst = np.zeros((int_weight.shape[0], int_weight.shape[1] * 4), dtype=np.int8)
     int_weight = np.ascontiguousarray(int_weight.numpy())

neural_speed/convert/convert_quantized_mixtral.py

@@ -80,7 +80,7 @@ def convert_to_q4_bestla_tensor(src_name, dst_name, model, fout, q_config, n_hea
         int_weight = (int_weight - 8) * 16
         gptq_scales = gptq_scales / 16
         gptq_zeros = (gptq_zeros - 8) * 16
-        weight_dtype == "int4"
+        weight_dtype = "int4"
 
     dst = np.zeros((int_weight.shape[0], int_weight.shape[1] * 4), dtype=np.int8)
     int_weight = np.ascontiguousarray(int_weight.numpy())