diff --git a/brainpy/_src/dependency_check.py b/brainpy/_src/dependency_check.py
index ef73fa9f..997da4a8 100644
--- a/brainpy/_src/dependency_check.py
+++ b/brainpy/_src/dependency_check.py
@@ -29,8 +29,8 @@
 numba_install_info = ('We need numba. Please install numba by pip . \n'
                       '> pip install numba')
 cupy_install_info = ('We need cupy. Please install cupy by pip . \n'
-                      'For CUDA v11.2 ~ 11.8 > pip install cupy-cuda11x\n'
-                      'For CUDA v12.x        > pip install cupy-cuda12x\n')
+                     'For CUDA v11.2 ~ 11.8 > pip install cupy-cuda11x\n'
+                     'For CUDA v12.x        > pip install cupy-cuda12x\n')
 os.environ["TI_LOG_LEVEL"] = "error"
 
 
@@ -105,9 +105,11 @@ def import_cupy(error_if_not_found=True):
         return None
   return cupy
 
+
 def raise_cupy_not_found():
   raise ModuleNotFoundError(cupy_install_info)
 
+
 def is_brainpylib_gpu_installed():
   return False if brainpylib_gpu_ops is None else True
 
diff --git a/brainpy/_src/math/op_register/base.py b/brainpy/_src/math/op_register/base.py
index e13382cb..ca0624a4 100644
--- a/brainpy/_src/math/op_register/base.py
+++ b/brainpy/_src/math/op_register/base.py
@@ -127,7 +127,7 @@ def __init__(
     gpu_checked = False
     if gpu_kernel is None:
       gpu_checked = True
-    elif isinstance(gpu_kernel, str): # cupy
+    elif isinstance(gpu_kernel, str):  # cupy
       register_cupy_gpu_translation_rule(self.primitive, gpu_kernel)
       gpu_checked = True
     elif hasattr(gpu_kernel, '_is_wrapped_kernel') and gpu_kernel._is_wrapped_kernel:  # taichi
diff --git a/brainpy/_src/math/op_register/tests/test_cupy_based.py b/brainpy/_src/math/op_register/tests/test_cupy_based.py
index 8073c428..b7656c43 100644
--- a/brainpy/_src/math/op_register/tests/test_cupy_based.py
+++ b/brainpy/_src/math/op_register/tests/test_cupy_based.py
@@ -1,7 +1,7 @@
 import jax
 import jax.numpy as jnp
-
 import pytest
+
 import brainpy.math as bm
 from brainpy._src.dependency_check import import_cupy
 
@@ -43,7 +43,7 @@ def test_cupy_based():
 
   # n = jnp.asarray([N**2,], dtype=jnp.int32)
 
-  y = prim(x1, x2, N**2, grid=(N,), block=(N,), outs=[jax.ShapeDtypeStruct((N, N), dtype=jnp.float32)])[0]
+  y = prim(x1, x2, N ** 2, grid=(N,), block=(N,), outs=[jax.ShapeDtypeStruct((N, N), dtype=jnp.float32)])[0]
 
   print(y)
   assert jnp.allclose(y, x1 + x2)
@@ -57,5 +57,4 @@ def test_cupy_based():
   # ker_times((N,), (N,), (x1, x2, y, N**2)) # y = x1 * x2
   # assert cp.allclose(y, x1 * x2)
 
-
 # test_cupy_based()