fix: random_op.py pylint error

mindspore/ops/composite/random_ops.py

@@ -136,10 +136,10 @@ def multinomial(inputs, num_sample=None, replacement=True, seed=0):
             n_dist = shape(inputs)[-2]
         a = Tensor(0.0, mstype.float32)
         b = Tensor(1.0, mstype.float32)
-        uniform = P.UniformReal(seed=seed)((n_dist * num_sample,), a, b)
+        random_uniform = P.UniformReal(seed=seed)((n_dist * num_sample,), a, b)
         if n_dist != 1:
-            uniform = reshape(uniform, (n_dist, num_sample))
-        vals = P.RealDiv()(P.Log()(uniform), inputs + 1e-6)
+            random_uniform = reshape(random_uniform, (n_dist, num_sample))
+        vals = P.RealDiv()(P.Log()(random_uniform), inputs + 1e-6)
         _, indices = P.TopK()(vals, num_sample)
         return indices
     return P.Multinomial(seed=seed)(inputs, num_sample)
@@ -211,8 +211,8 @@ def gamma(shape, alpha, beta, seed=0):
     const_utils.check_tensors_dtype_same(beta_dtype, mstype.float32, "gamma")
     seed1 = get_seed()
     seed2 = seed
-    gamma = P.Gamma(seed1, seed2)
-    value = gamma(shape, alpha, beta)
+    random_gamma = P.Gamma(seed1, seed2)
+    value = random_gamma(shape, alpha, beta)
     return value
 
 def poisson(shape, mean, seed=0):
@@ -238,6 +238,6 @@ def poisson(shape, mean, seed=0):
     const_utils.check_tensors_dtype_same(mean_dtype, mstype.float32, "poisson")
     seed1 = get_seed()
     seed2 = seed
-    poisson = P.Poisson(seed1, seed2)
-    value = poisson(shape, mean)
+    random_poisson = P.Poisson(seed1, seed2)
+    value = random_poisson(shape, mean)
     return value