pass all constants to _fused_variance_kernel2 as device scalars

* avoids an issue with an internal numpy.can_cast call in CuPy's kernel fusion code when using NumPy 2.0

python/cucim/src/cucim/skimage/segmentation/_chan_vese.py

@@ -7,6 +7,8 @@
 from .._shared.utils import _supported_float_type
 from .._vendored import pad
 
+_one = cp.asarray(1.0, dtype=cp.float32)
+
 
 @cp.fuse()
 def _fused_variance_kernel1(eta, x_start, x_mid, x_end, y_start, y_mid, y_end):
@@ -53,7 +55,7 @@ def _fused_hphi_hinv(phi):
 
 @cp.fuse()
 def _fused_variance_kernel2(
-    image, c1, c2, lam1, lam2, phi, K, dt, mu, delta_phi, Csum
+    image, c1, c2, lam1, lam2, phi, K, dt, mu, delta_phi, Csum, one
 ):
     difference_term = image - c1
     difference_term *= difference_term
@@ -65,7 +67,7 @@ def _fused_variance_kernel2(
     difference_term += term2
 
     new_phi = phi + (dt * delta_phi) * (mu * K + difference_term)
-    out = new_phi / (1 + mu * dt * delta_phi * Csum)
+    out = new_phi / (one + mu * dt * delta_phi * Csum)
     return out
 
 
@@ -105,7 +107,7 @@ def _cv_calculate_variation(image, phi, mu, lambda1, lambda2, dt):
     c1, c2 = _cv_calculate_averages(image, Hphi, Hinv)
     delta_phi = _cv_delta(phi)
     out = _fused_variance_kernel2(
-        image, c1, c2, lambda1, lambda2, phi, K, dt, mu, delta_phi, Csum
+        image, c1, c2, lambda1, lambda2, phi, K, dt, mu, delta_phi, Csum, _one
     )
     return out
 
@@ -430,6 +432,9 @@ def chan_vese(
     phivar = tol + 1
 
     dt = cp.asarray(dt, dtype=float_dtype)
+    mu = cp.asarray(mu, dtype=float_dtype)
+    lambda1 = cp.asarray(lambda1, dtype=float_dtype)
+    lambda2 = cp.asarray(lambda2, dtype=float_dtype)
     while phivar > tol and i < max_num_iter:
         # Save old level set values
         oldphi = phi