make runtime avx act

paddle/fluid/operators/attention_lstm_op.cc

@@ -299,11 +299,21 @@ class AttentionLSTMKernel : public framework::OpKernel<T> {
     PADDLE_ENFORCE_EQ(c0->dims()[0], N, "C0 dims should be %d x %d.", N, D);
     fc_out->Resize({max_seq_len, 1});
 
-    math::VecActivations<T> act_functor;
     std::function<void(const int, const T *, T *)> act_gate, act_cell, act_cand;
-    act_gate = act_functor(ctx.Attr<std::string>("gate_activation"));
-    act_cell = act_functor(ctx.Attr<std::string>("cell_activation"));
-    act_cand = act_functor(ctx.Attr<std::string>("candidate_activation"));
+    auto& act_gate_str = ctx.Attr<std::string>("gate_activation");
+    auto& act_cell_str = ctx.Attr<std::string>("cell_activation");
+    auto& act_cand_str = ctx.Attr<std::string>("candidate_activation");
+    if (platform::jit::MayIUse(platform::jit::avx)) {
+      math::VecActivations<T, platform::jit::avx> act_functor;
+      act_gate = act_functor(act_gate_str);
+      act_cell = act_functor(act_cell_str);
+      act_cand = act_functor(act_cand_str);
+    } else {
+      math::VecActivations<T, platform::jit::isa_any> act_functor;
+      act_gate = act_functor(act_gate_str);
+      act_cell = act_functor(act_cell_str);
+      act_cand = act_functor(act_cand_str);
+    }
 
     const T* x_data = x->data<T>();
     const T* h0_data = h0 ? h0->data<T>() : NULL;