fix unit test

paddle/operators/layer_norm_op.cc

@@ -233,13 +233,13 @@ class LayerNormGradKernel<platform::CPUDeviceContext, T>
     if (d_x) {
       d_x->mutable_data<T>(ctx.GetPlace());
       auto d_x_map = EigenMatrixMapRowMajor<T>(d_x->data<T>(), left, right);
-      auto triple_product = [](T ele) { return ele * ele * ele; };
-      auto neg_inv_std = [](T ele) { return T(-1.0) * std::sqrt(1 / ele); };
+      auto triple_product = [](T ele) { return ele * ele; };
+      auto neg_inv_std = [](T ele) { return -std::sqrt(1 / ele); };
       auto inv_std_scale_func = [scale_data](T ele) {
         return std::sqrt(1 / ele) * scale_data;
       };
       auto neg_inv_std_scale_func = [scale_data](T ele) {
-        return T(-1.0) * std::sqrt(1 / ele) * scale_data;
+        return -std::sqrt(1 / ele) * scale_data;
       };
       // dy_dx
       auto dx_end = var_map.unaryExpr(inv_std_scale_func)
@@ -260,10 +260,13 @@ class LayerNormGradKernel<platform::CPUDeviceContext, T>
       auto dvar_end = var_map.unaryExpr(neg_inv_std)
                           .unaryExpr(triple_product)
                           .cwiseProduct(dvar_end_0);
-      auto dx_var = (1.0f / right) *
+      auto dx_var = (T(1.0) / right) *
                     (x_map - mean_map.replicate(1, right))
                         .cwiseProduct(dvar_end.replicate(1, right));
 
+      // d_x = (1. / N) * scale * inv_var * (N * d_y - np.sum(d_y, axis=0)
+      //   - (X - mean) * inv_var * inv_var * np.sum(d_y * (X - mean), axis=0))
+
       d_x_map = dx_end + dx_mean + dx_var;
     }
   }