"remove unused test net modified"

paddle/operators/gaussian_random_op.cc

@@ -22,8 +22,8 @@ template <typename T>
 class GaussianRandomKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext& context) const override {
-    T mean = static_cast<T>(context.op_.GetAttr<T>("mean"));
-    T std = static_cast<T>(context.op_.GetAttr<T>("std"));
+    float mean = context.op_.GetAttr<float>("mean");
+    float std = context.op_.GetAttr<float>("std");
     auto* tensor = context.Output<framework::Tensor>(0);
     T* data = tensor->mutable_data<T>(context.GetPlace());
 
@@ -35,7 +35,8 @@ class GaussianRandomKernel : public framework::OpKernel {
     }
     std::mt19937 g(seed);
     std::normal_distribution<T> distribution(mean, std);
-    for (int i = 0; i < framework::product(tensor->dims()); ++i) {
+    ssize_t size = framework::product(tensor->dims());
+    for (int i = 0; i < size; ++i) {
       data[i] = distribution(g);
     }
   }

paddle/operators/gaussian_random_op.cu

@@ -26,8 +26,8 @@ template <typename T>
 class GaussianRandomKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext& context) const override {
-    T mean = static_cast<T>(context.op_.GetAttr<T>("mean"));
-    T std = static_cast<T>(context.op_.GetAttr<T>("std"));
+    float mean = context.op_.GetAttr<float>("mean");
+    float std = context.op_.GetAttr<float>("std");
     auto* tensor = context.Output<framework::Tensor>(0);
     T* data = tensor->mutable_data<T>(context.GetPlace());
 
@@ -40,7 +40,6 @@ class GaussianRandomKernel : public framework::OpKernel {
         &g, CURAND_RNG_PSEUDO_DEFAULT));
     PADDLE_ENFORCE(
         platform::dynload::curandSetPseudoRandomGeneratorSeed(g, seed));
-    // auto g = const_cast<platform::GPUDeviceContext*>(ctx)->RandGenerator();
     curandGenerateNormal(g, data, framework::product(tensor->dims()), mean,
                          std);
   }

python/paddle/v2/framework/tests/test_gaussian_random_op.py

@@ -14,13 +14,15 @@ class GaussianRandomTest(unittest.TestCase):
     def test_gaussian_random(self, place):
         scope = core.Scope()
         scope.new_var("Out").get_tensor()
+
         op = Operator(
             "gaussian_random",
             Out="Out",
             dims=[1000, 784],
             mean=.0,
             std=1.,
-            seed=0)
+            seed=10)
+
         op.infer_shape(scope)
         context = core.DeviceContext.create(place)
         op.run(scope, context)