add enforce

paddle/fluid/operators/sampling_id_op.cc

@@ -33,6 +33,10 @@ class SamplingIdKernel : public framework::OpKernel<T> {
     const int batch_size = static_cast<int>(input->dims()[0]);
     const int width = static_cast<int>(input->dims()[1]);
 
+    PADDLE_ENFORCE_GE(batch_size, 0,
+                      "batch_size(dims[0]) must be nonnegative.");
+    PADDLE_ENFORCE_GE(width, 0, "width(dims[1]) must be nonnegative.");
+
     std::vector<T> ins_vector;
     framework::TensorToVector(*input, context.device_context(), &ins_vector);
 

paddle/fluid/operators/sampling_id_op.cu

@@ -46,6 +46,10 @@ class SamplingIdGPUKernel : public framework::OpKernel<T> {
     const int batch_size = static_cast<int>(input->dims()[0]);
     const int width = static_cast<int>(input->dims()[1]);
 
+    PADDLE_ENFORCE_GE(batch_size, 0,
+                      "batch_size(dims[0]) must be nonnegative.");
+    PADDLE_ENFORCE_GE(width, 0, "width(dims[1]) must be nonnegative.");
+
     std::vector<T> ins_vector;
     framework::TensorToVector(*input, context.device_context(), &ins_vector);
 
@@ -56,10 +60,11 @@ class SamplingIdGPUKernel : public framework::OpKernel<T> {
     }
     T min = static_cast<T>(context.Attr<float>("min"));
     T max = static_cast<T>(context.Attr<float>("max"));
+    UniformGenerator<T> gen = UniformGenerator<T>(min, max, seed);
 
     std::vector<T> ids(batch_size);
     for (size_t i = 0; i < batch_size; ++i) {
-      T r = UniformGenerator<T>(min, max, seed);
+      T r = gen(0);
       int idx = width - 1;
       for (int j = 0; j < width; ++j) {
         if ((r -= ins_vector[i * width + j]) < 0) {