fix the build issue

test=develop

paddle/fluid/operators/elementwise/elementwise_mul_mkldnn_op.cc

@@ -83,8 +83,12 @@ class ElementwiseMulMKLDNNKernel : public framework::OpKernel<T> {
     UpdateDataFormat(ctx, const_cast<Tensor*>(x), "x_data_format");
     UpdateDataFormat(ctx, const_cast<Tensor*>(y), "y_data_format");
 
+#ifdef PADDLE_WITH_XBYAK
     Xbyak::util::Cpu cpu;
     const bool is_avx512_enabled = cpu.has(Xbyak::util::Cpu::tAVX512F);
+#else
+    const bool is_avx512_enabled = platform::MayIUse(platform::avx512f);
+#endif  // PADDLE_WITH_XBYAK
     const bool are_dims_divisable = !(x_int_dims[1] % 16);
     const bool is_x_format_correct = x->format() == memory::format::nChw16c;
     const bool is_y_format_correct = y->format() == memory::format::nc;

paddle/fluid/operators/math/detail/lstm_cpu_kernel.h

@@ -17,6 +17,12 @@ limitations under the License. */
 #include "paddle/fluid/operators/math/detail/activation_functions.h"
 #include "paddle/fluid/operators/math/lstm_compute.h"
 
+#if defined(_WIN32)
+#if defined(__AVX2__) || defined(__AVX__)
+inline __m256 operator+=(__m256 a, __m256 b) { return _mm256_add_ps(a, b); }
+#endif
+#endif
+
 namespace paddle {
 namespace operators {
 namespace math {

paddle/fluid/operators/math/jit_kernel_blas.cc

@@ -212,8 +212,10 @@ class EltwiseMulnChw16cNCKernelImpl
 
  private:
   std::unique_ptr<gen::EltwiseMulnChw16cNC> jitcode_{nullptr};
+#endif
 };
 
+#ifdef PADDLE_WITH_XBYAK
 template <>
 bool EltwiseMulnChw16cNCKernelImpl<float>::useJIT(int d) {
   return true;