change int to init

keras_cv/backend/random.py

@@ -40,9 +40,9 @@ def next(self, ordered=True):
 def normal(shape, mean=0.0, stddev=1.0, dtype=None, seed=None):
     if isinstance(seed, SeedGenerator):
         seed = seed.next()
-        int_seed = seed[0] + seed[1]
+        init_seed = seed[0] + seed[1]
     else:
-        int_seed = seed
+        init_seed = seed
     if keras_3():
         return keras.random.normal(
             shape, mean=mean, stddev=stddev, dtype=dtype, seed=int_seed
@@ -58,9 +58,9 @@ def normal(shape, mean=0.0, stddev=1.0, dtype=None, seed=None):
 def uniform(shape, minval=0.0, maxval=1.0, dtype=None, seed=None):
     if isinstance(seed, SeedGenerator):
         seed = seed.next()
-        int_seed = seed[0] + seed[1]
+        init_seed = seed[0] + seed[1]
     else:
-        int_seed = seed
+        init_seed = seed
     if keras_3():
         return keras.random.uniform(
             shape, minval=minval, maxval=maxval, dtype=dtype, seed=int_seed
@@ -76,9 +76,9 @@ def uniform(shape, minval=0.0, maxval=1.0, dtype=None, seed=None):
 def shuffle(x, axis=0, seed=None):
     if isinstance(seed, SeedGenerator):
         seed = seed.next()
-        int_seed = seed[0] + seed[1]
+        init_seed = seed[0] + seed[1]
     else:
-        int_seed = seed
+        init_seed = seed
     if keras_3():
         return keras.random.shuffle(x=x, axis=axis, seed=int_seed)
     else:
@@ -90,9 +90,9 @@ def shuffle(x, axis=0, seed=None):
 def categorical(logits, num_samples, dtype="int32", seed=None):
     if isinstance(seed, SeedGenerator):
         seed = seed.next()
-        int_seed = seed[0] + seed[1]
+        init_seed = seed[0] + seed[1]
     else:
-        int_seed = seed
+        init_seed = seed
     if keras_3():
         return keras.random.categorical(
             logits=logits, num_samples=num_samples, dtype=dtype, seed=int_seed