Add PADDLE_ENFORCE in nll loss cuda kernel (#26294)

* add nll loss API, update demo code of the comment

paddle/fluid/operators/nll_loss_op.cu

@@ -44,6 +44,8 @@ __global__ void GPUNLLLossForward1D_no_reduce(T* out_data, const T* x_data,
       out_data[i] = 0;
       continue;
     }
+    PADDLE_ENFORCE(cur_label >= 0 && cur_label < n_classes,
+                   "label should not be out of bounds.");
     const T cur_weight = weight_data ? weight_data[cur_label] : (T)1;
     out_data[i] = -x_data[i * n_classes + cur_label] * cur_weight;
   }
@@ -62,6 +64,8 @@ __global__ void GPUNLLLossForward1D_with_reduce(
   for (i = threadIdx.x; i < batch_size; i += NTHREADS) {
     const auto cur_label = label_data[i];
     if (cur_label != ignore_index) {
+      PADDLE_ENFORCE(cur_label >= 0 && cur_label < n_classes,
+                     "label should not be out of bounds.");
       const auto cur_weight = weight_data ? weight_data[cur_label] : (T)1;
       sharedInputs[threadIdx.x] -=
           x_data[i * n_classes + cur_label] * cur_weight;
@@ -198,6 +202,8 @@ __global__ void GPUNLLLossForward2D_no_reduce(
       out_data[index] = 0;
       continue;
     }
+    PADDLE_ENFORCE(cur_label >= 0 && cur_label < n_classes,
+                   "label should not be out of bounds.");
     const T cur_weight = weight_data ? weight_data[cur_label] : (T)1;
     out_data[index] =
         -x_data[b * sample_size + cur_label * map_size + h * in_dim3 + w] *
@@ -226,6 +232,8 @@ __global__ void GPUNLLLossForward2D_with_reduce(
        i < map_nelem; i += step) {
     const int64_t cur_label = label_data[toffset + i];
     if (cur_label != ignore_index) {
+      PADDLE_ENFORCE(cur_label >= 0 && cur_label < n_classes,
+                     "label should not be out of bounds.");
       const T cur_weight = weight_data ? weight_data[cur_label] : (T)1;
       input_sum -= x_data[ioffset + i + map_nelem * cur_label] * cur_weight;
       acc_weight += cur_weight;

python/paddle/fluid/tests/unittests/test_nll_loss.py

@@ -907,10 +907,8 @@ class TestNLLLossInvalidArgs(unittest.TestCase):
 
         def test_x_dim_imperative_lt_2():
             with fluid.dygraph.guard():
-                x_np = np.array(
-                    [0.88103855, 0.9908683, 0.6226845, 0.53331435,
-                     0.07999352]).astype(np.float32)
-                label_np = np.array([0, 2, 1, 1, 0]).astype(np.int64)
+                x_np = np.random.random(size=(5, )).astype(np.float64)
+                label_np = np.random.randint(0, 10, size=(5, )).astype(np.int64)
                 x = paddle.to_variable(x_np)
                 label = paddle.to_variable(label_np)
                 nll_loss = paddle.nn.loss.NLLLoss()
@@ -933,13 +931,8 @@ class TestNLLLossInvalidArgs(unittest.TestCase):
 
         def test_NLLLoss_reduction_imperative_not_sum_mean_none():
             with fluid.dygraph.guard():
-                x_np = np.array(
-                    [[0.88103855, 0.9908683, 0.6226845],
-                     [0.53331435, 0.07999352, 0.8549948],
-                     [0.25879037, 0.39530203, 0.698465],
-                     [0.73427284, 0.63575995, 0.18827209],
-                     [0.05689114, 0.0862954, 0.6325046]]).astype(np.float32)
-                label_np = np.array([0, 2, 1, 1, 0]).astype(np.int64)
+                x_np = np.random.random(size=(5, 3)).astype(np.float64)
+                label_np = np.random.randint(0, 3, size=(5, )).astype(np.int64)
                 x = paddle.to_variable(x_np)
                 label = paddle.to_variable(label_np)
                 nll_loss = paddle.nn.loss.NLLLoss(reduction='')
@@ -962,13 +955,8 @@ class TestNLLLossInvalidArgs(unittest.TestCase):
 
         def test_nll_loss_function_reduction_imperative_not_sum_mean_none():
             with fluid.dygraph.guard():
-                x_np = np.array(
-                    [[0.88103855, 0.9908683, 0.6226845],
-                     [0.53331435, 0.07999352, 0.8549948],
-                     [0.25879037, 0.39530203, 0.698465],
-                     [0.73427284, 0.63575995, 0.18827209],
-                     [0.05689114, 0.0862954, 0.6325046]]).astype(np.float32)
-                label_np = np.array([0, 2, 1, 1, 0]).astype(np.int64)
+                x_np = np.random.random(size=(5, 3)).astype(np.float64)
+                label_np = np.random.randint(0, 3, size=(5, )).astype(np.int64)
                 x = paddle.to_variable(x_np)
                 label = paddle.to_variable(label_np)
                 res = paddle.nn.functional.nll_loss(x, label, reduction='')

python/paddle/nn/functional/loss.py

@@ -41,6 +41,7 @@ from ...fluid.layers import edit_distance  #DEFINE_ALIAS
 from ...fluid.layers import huber_loss  #DEFINE_ALIAS
 from ...fluid.layers import sampled_softmax_with_cross_entropy  #DEFINE_ALIAS
 from ...fluid.layer_helper import LayerHelper
+from ...fluid.framework import in_dygraph_mode
 from ...fluid.framework import Variable
 
 __all__ = [