diff --git a/python/tvm/topi/hexagon/qnn/__init__.py b/python/tvm/topi/hexagon/qnn/__init__.py
index aa7f7f0d16a3..b7de7c822227 100644
--- a/python/tvm/topi/hexagon/qnn/__init__.py
+++ b/python/tvm/topi/hexagon/qnn/__init__.py
@@ -18,4 +18,4 @@
 """ Computes and schedules for Hexagon quantized ops """
 
 from .avg_pool2d import qnn_avg_pool2d_compute, qnn_avg_pool2d_schedule
-from .qadd_qsub_qmul import *
\ No newline at end of file
+from .qadd_qsub_qmul import *
diff --git a/python/tvm/topi/hexagon/qnn/qadd_qsub_qmul.py b/python/tvm/topi/hexagon/qnn/qadd_qsub_qmul.py
index fbba1ad2d75b..271ee8f9ad07 100755
--- a/python/tvm/topi/hexagon/qnn/qadd_qsub_qmul.py
+++ b/python/tvm/topi/hexagon/qnn/qadd_qsub_qmul.py
@@ -25,7 +25,6 @@
 from tvm import te
 from tvm import tir
 from ..utils import get_layout_transform_fn, get_fixed_point_value
-import tvm
 
 
 def broadcast_axis(tensor_A, tensor_B):
@@ -51,7 +50,7 @@ def saturate(x: te.Tensor, dtype: str):
     return te.max(te.min_value(dtype), te.min(x, te.max_value(dtype)))
 
 
-def get_int_scale(scale_A, scale_B, scale_M, zero_point_A, zero_point_B, zero_point_M, op, dtype):
+def get_int_scale(scale_A, scale_B, scale_M, zero_point_A, zero_point_B, zero_point_M, op):
     """Get fixed-point number"""
     C_recip = 1 / scale_M
 
@@ -104,7 +103,7 @@ def qadd_broadcast_compute(
     n_b, h_b, w_b, c_b = B_broadcast
 
     scale_a, scale_b, rsh, corr = get_int_scale(
-        scale_A, scale_B, scale_M, zero_point_A, zero_point_B, zero_point_M, "qadd", "int16"
+        scale_A, scale_B, scale_M, zero_point_A, zero_point_B, zero_point_M, "qadd"
     )
 
     return te.compute(
@@ -141,7 +140,7 @@ def qsubtract_broadcast_compute(
     n_b, h_b, w_b, c_b = B_broadcast
 
     scale_a, scale_b, rsh, corr = get_int_scale(
-        scale_A, scale_B, scale_M, zero_point_A, zero_point_B, zero_point_M, "qsub", "int16"
+        scale_A, scale_B, scale_M, zero_point_A, zero_point_B, zero_point_M, "qsub"
     )
 
     return te.compute(
@@ -178,7 +177,7 @@ def qmultiply_broadcast_compute(
     n_b, h_b, w_b, c_b = B_broadcast
 
     scale_int, rsh, corr = get_int_scale(
-        scale_A, scale_B, scale_M, zero_point_A, zero_point_B, zero_point_M, "qmul", "int16"
+        scale_A, scale_B, scale_M, zero_point_A, zero_point_B, zero_point_M, "qmul"
     )
 
     return te.compute(
@@ -205,7 +204,6 @@ def tir_schedule_quant(
     output_layout: str,
     tensor_A_layout: str,
     tensor_B_layout: str,
-    op_name: str,
 ):
     """Schedule for output layout nhwc-8h8w32c-2d"""
     func = te.create_prim_func([tensor_A, tensor_B, out_M])
@@ -234,4 +232,4 @@ def tir_schedule_quant(
 
     s.reorder(n, h_o, w_o, c_o, h_i, wio, wii, c_i)
 
-    return s
\ No newline at end of file
+    return s
diff --git a/tests/python/contrib/test_hexagon/topi/test_add_subtract_multiply.py b/tests/python/contrib/test_hexagon/topi/test_add_subtract_multiply.py
index 482b07fd3552..78e6e918ce3c 100755
--- a/tests/python/contrib/test_hexagon/topi/test_add_subtract_multiply.py
+++ b/tests/python/contrib/test_hexagon/topi/test_add_subtract_multiply.py
@@ -55,7 +55,7 @@ def input_np_B(input_shape_B, dtype):
 def quantize_input_np_A(input_np_A, dtype):
     if dtype == "uint8" or dtype == "int8":
         global zero_point_A_val, scale_A_val
-        input_np_A_quantized, scale_A_val, zero_point_A_val= quantize_np(input_np_A, dtype)
+        input_np_A_quantized, scale_A_val, zero_point_A_val = quantize_np(input_np_A, dtype)
         return input_np_A_quantized
 
 
@@ -318,7 +318,7 @@ def test_transform(
             elif op_name == "multiply":
                 M = qn.qmultiply_broadcast_compute(*args)
             tir_schedule = qn.tir_schedule_quant(
-                M, A, B, output_layout, input_A_layout, input_B_layout, op_name
+                M, A, B, output_layout, input_A_layout, input_B_layout
             )
 
         sch = tir_schedule.mod
@@ -390,4 +390,4 @@ def test_transform(
 
 
 if __name__ == "__main__":
-    tvm.testing.main()
\ No newline at end of file
+    tvm.testing.main()