fix the bug of layer_norm when batch_size=1 (#35480)

The bug is that access to mean and var is incorrect, and the array will be out of bounds: the shape of mean and var is [batch_size], and the range of thread idx is 0~feature_size, so mean[idx] and var[idx] is incorrect.

When batch_size=1, the correct access is mean[0] and var[0], and a unit test with batch_size=1 is added.

paddle/fluid/operators/layer_norm_kernel.cu.h

@@ -705,7 +705,7 @@ __global__ void LayerNormBackwardWhenBatchSizeIsOne(
   int64_t idx = threadIdx.x + blockIdx.x * blockDim.x;
   if (idx < feature_size) {
     auto var_val =
-        static_cast<U>(real_sqrt(static_cast<float>(var[idx]) + epsilon));
+        static_cast<U>(real_sqrt(static_cast<float>(var[0]) + epsilon));
     if (d_x != nullptr) {
       if (d_scale == nullptr) {
         d_x[idx] = static_cast<T>(static_cast<U>(d_y[idx]) / var_val);
@@ -717,7 +717,7 @@ __global__ void LayerNormBackwardWhenBatchSizeIsOne(
 
     if (d_scale != nullptr) {
       d_scale[idx] = static_cast<U>(d_y[idx]) *
-                     (static_cast<U>(x[idx]) - mean[idx]) / var_val;
+                     (static_cast<U>(x[idx]) - mean[0]) / var_val;
     }
 
     if (d_bias != nullptr) d_bias[idx] = static_cast<U>(d_y[idx]);

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

@@ -233,6 +233,7 @@ class TestLayerNormOp(unittest.TestCase):
             test_with_place(place, shape, begin_norm_axis)
 
     def test_check_forward_backward_with_scale_and_bias(self):
+        self.check_forward_backward(shape=[1, 3, 4, 5], begin_norm_axis=1)
         self.check_forward_backward(shape=[2, 3, 4, 5], begin_norm_axis=1)
         self.check_forward_backward(
             shape=[2, 3, 4, 5],