diff --git a/paddle/fluid/framework/ir/auto_mixed_precision_pass.cc b/paddle/fluid/framework/ir/auto_mixed_precision_pass.cc
index 061e2432eed1a3597a9e567e439f978b37dbf01b..fa570394d80f3bda8e3ceb4c4f1a71ec764851a0 100644
--- a/paddle/fluid/framework/ir/auto_mixed_precision_pass.cc
+++ b/paddle/fluid/framework/ir/auto_mixed_precision_pass.cc
@@ -620,6 +620,15 @@ bool AutoMixedPrecisionPass::InputVarsNotConvert(
       if (std::find(vecs.begin(), vecs.end(), var_name) != vecs.end()) {
         return true;
       }
+    } else if (GetOpOriginalType(op_desc->Type()) == "instance_norm") {
+      auto vecs = op_desc->Input("Bias");
+      if (std::find(vecs.begin(), vecs.end(), var_name) != vecs.end()) {
+        return true;
+      }
+      vecs = op_desc->Input("Scale");
+      if (std::find(vecs.begin(), vecs.end(), var_name) != vecs.end()) {
+        return true;
+      }
     }
   }
 
diff --git a/paddle/fluid/framework/ir/inplace_op_var_pass.cc b/paddle/fluid/framework/ir/inplace_op_var_pass.cc
index 0ccac637be36c741f5b5729b71794635cf0e83ac..5bbe980daaba7ef7d525b83e60d10c91fcea0829 100644
--- a/paddle/fluid/framework/ir/inplace_op_var_pass.cc
+++ b/paddle/fluid/framework/ir/inplace_op_var_pass.cc
@@ -36,6 +36,12 @@ bool InplaceOpVarPass::IsValidInplaceOp(
     if (var_node->Name() != x_name) continue;
     if (var_node->Var()->Persistable() || var_node->outputs.size() != 1)
       return false;
+    // The op type in front of in_var_node should not be feed.
+    for (auto* pre_op : var_node->inputs) {
+      if (pre_op->Op()->Type() == "feed") {
+        return false;
+      }
+    }
   }
 
   // in/out_var_node should be not used in multi graphs.
diff --git a/paddle/phi/backends/xpu/xpu2_op_list.cc b/paddle/phi/backends/xpu/xpu2_op_list.cc
index 419bba4da7417acf7c80fae7ec3fab09aed783b7..ceab85cf551d6bfe597480e7a92e65a557b04b9a 100644
--- a/paddle/phi/backends/xpu/xpu2_op_list.cc
+++ b/paddle/phi/backends/xpu/xpu2_op_list.cc
@@ -416,7 +416,8 @@ XPUOpMap& get_kl2_ops() {
        XPUKernelSet({phi::DataType::FLOAT32,
                      phi::DataType::INT32,
                      phi::DataType::INT64})},
-      {"instance_norm", XPUKernelSet({phi::DataType::FLOAT32})},
+      {"instance_norm",
+       XPUKernelSet({phi::DataType::FLOAT32, phi::DataType::FLOAT16})},
       {"instance_norm_grad", XPUKernelSet({phi::DataType::FLOAT32})},
       {"iou_similarity", XPUKernelSet({phi::DataType::FLOAT32})},
       {"label_smooth", XPUKernelSet({phi::DataType::FLOAT32})},
diff --git a/paddle/phi/kernels/assign_kernel.cc b/paddle/phi/kernels/assign_kernel.cc
index 09046ef45565e3d1744805e13838be89a5be59eb..9aba3bcb78faf1639add0cd8bc301ce5a602862e 100644
--- a/paddle/phi/kernels/assign_kernel.cc
+++ b/paddle/phi/kernels/assign_kernel.cc
@@ -186,6 +186,5 @@ PD_REGISTER_KERNEL(assign_value,
                    int,
                    float,
                    double,
-                   int64_t,
-                   phi::dtype::float16) {}
+                   int64_t) {}
 #endif
diff --git a/paddle/phi/kernels/xpu/instance_norm_kernel.cc b/paddle/phi/kernels/xpu/instance_norm_kernel.cc
index 293397f66ee37def5f5953e3faccc39b9f0dc9b8..1631d0ccbeed8de53272cfd319a34c001d3ac934 100644
--- a/paddle/phi/kernels/xpu/instance_norm_kernel.cc
+++ b/paddle/phi/kernels/xpu/instance_norm_kernel.cc
@@ -15,6 +15,7 @@
 #include "paddle/phi/kernels/instance_norm_kernel.h"
 #include "paddle/phi/backends/xpu/enforce_xpu.h"
 #include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/math_function.h"
 
 namespace phi {
 
@@ -37,9 +38,31 @@ void InstanceNormKernel(const Context& dev_ctx,
   dev_ctx.template Alloc<T>(y);
   dev_ctx.template Alloc<float>(saved_mean);
   dev_ctx.template Alloc<float>(saved_var);
-
+  // scale
   const auto scale_ptr = scale.get_ptr();
-  const auto bias_ptr = bias.get_ptr();
+  const float* scale_data_fp32 = nullptr;
+  DenseTensor scale_data;
+  if (scale_ptr == nullptr) {
+    scale_data.Resize({c});
+    dev_ctx.template Alloc<float>(&scale_data);
+    phi::funcs::set_constant(dev_ctx, &scale_data, static_cast<float>(1));
+    scale_data_fp32 = scale_data.data<float>();
+  } else {
+    // no need to cast
+    scale_data_fp32 = scale_ptr->data<float>();
+  }
+  // bias
+  const float* bias_data_fp32 = nullptr;
+  const auto* bias_ptr = bias.get_ptr();
+  DenseTensor bias_data;
+  if (bias_ptr == nullptr) {
+    bias_data.Resize({c});
+    dev_ctx.template Alloc<float>(&bias_data);
+    phi::funcs::set_constant(dev_ctx, &bias_data, static_cast<float>(0));
+    bias_data_fp32 = bias_data.data<float>();
+  } else {
+    bias_data_fp32 = bias_ptr->data<float>();
+  }
 
   int r = xpu::instance_norm(dev_ctx.x_context(),
                              reinterpret_cast<const XPUType*>(x.data<T>()),
@@ -49,8 +72,8 @@ void InstanceNormKernel(const Context& dev_ctx,
                              h,
                              w,
                              epsilon,
-                             scale_ptr->data<float>(),
-                             bias_ptr->data<float>(),
+                             scale_data_fp32,
+                             bias_data_fp32,
                              saved_mean->data<float>(),
                              saved_var->data<float>(),
                              true);
@@ -60,5 +83,9 @@ void InstanceNormKernel(const Context& dev_ctx,
 
 }  // namespace phi
 
-PD_REGISTER_KERNEL(
-    instance_norm, XPU, ALL_LAYOUT, phi::InstanceNormKernel, float) {}
+PD_REGISTER_KERNEL(instance_norm,
+                   XPU,
+                   ALL_LAYOUT,
+                   phi::InstanceNormKernel,
+                   float,
+                   phi::dtype::float16) {}