diff --git a/src/operators/kernel/fpga/V1/tanh_kernel.cpp b/src/operators/kernel/fpga/V1/tanh_kernel.cpp
index 46dd3a0f6f8819f6485243a445725554943ab2bf..216cb726e3fe93e9ebfaf328a9ab4ca0725b6bb1 100644
--- a/src/operators/kernel/fpga/V1/tanh_kernel.cpp
+++ b/src/operators/kernel/fpga/V1/tanh_kernel.cpp
@@ -15,17 +15,61 @@ limitations under the License. */
 #ifdef TANH_OP
 
 #include "operators/kernel/tanh_kernel.h"
-
+#include <math.h>
 namespace paddle_mobile {
 namespace operators {
 
 template <>
 bool TanhKernel<FPGA, float>::Init(TanhParam<FPGA> *param) {
+  auto input = const_cast<Tensor *>(param->InputX());
+  auto input_ptr = input->data<float>();
+  auto float_input = new Tensor;
+  float_input->mutable_data<float>(
+      {1, input->dims()[1], input->dims()[2], input->dims()[3]});
+  fpga::format_fp32_ofm(float_input);
+
+  fpga::BypassArgs args = {fpga::DATA_TYPE_FP16};
+  args.input_layout_type = fpga::LAYOUT_HWC;
+  args.output_layout_type = fpga::LAYOUT_CHW;
+  args.input_data_type = fpga::DATA_TYPE_FP16;
+  args.output_data_type = fpga::DATA_TYPE_FP32;
+  args.image.address = input_ptr;
+  args.image.height = (uint32_t)input->dims()[2];
+  args.image.width = (uint32_t)input->dims()[3];
+  args.image.channels = (uint32_t)input->dims()[1];
+  args.output.address = float_input->data<float>();
+  args.output.scale_address = float_input->scale;
+  param->SetFloatInput(float_input);
+  param->SetFpgaArgs(args);
   return true;
 }
 
+#define EXP_MAX_INPUT 40.0
+template <typename T>
+T Tanh(const T a) {
+  T tmp = -2.0 * a;
+  tmp = (tmp > EXP_MAX_INPUT) ? EXP_MAX_INPUT : tmp;
+  return (2.0 / (1.0 + exp(tmp))) - 1.0;
+}
+template <typename T>
+void tanhFuntor(Tensor *input, Tensor *output) {
+  auto *input_ptr = input->data<T>();
+  auto *output_ptr = output->mutable_data<T>();
+  for (int i = 0; i < input->numel(); i++) {
+    *(output_ptr + i) = Tanh<T>(*(input_ptr + i));
+  }
+}
 template <>
-void TanhKernel<FPGA, float>::Compute(const TanhParam<FPGA> &param) {}
+void TanhKernel<FPGA, float>::Compute(const TanhParam<FPGA> &param) {
+  Tensor *in_x = param.FloatInput();
+  Tensor *out = param.Out();
+
+  fpga::PerformBypass(param.FpgaArgs());
+  fpga::fpga_invalidate((void *)in_x->data<float>(),
+                        in_x->numel() * sizeof(float));
+  tanhFuntor<float>(in_x, out);
+  fpga::fpga_flush(out->data<float>(), out->memory_size());
+}
 
 }  // namespace operators
 }  // namespace paddle_mobile
diff --git a/src/operators/op_param.h b/src/operators/op_param.h
index fe5cce379d199be5d3931308513823c7279c21ff..24af798a84c89ba6434178d5c4392a03c0ba5d87 100644
--- a/src/operators/op_param.h
+++ b/src/operators/op_param.h
@@ -1554,6 +1554,20 @@ class TanhParam : public OpParam {
  private:
   RType *input_x_;
   RType *out_;
+#ifdef PADDLE_MOBILE_FPGA
+
+ private:
+  std::shared_ptr<RType> float_input_x_;
+  fpga::BypassArgs fpga_bypass_args;
+
+ public:
+  RType *FloatInput() const {
+    return float_input_x_ == nullptr ? input_x_ : float_input_x_.get();
+  }
+  void SetFloatInput(Tensor *input) { float_input_x_.reset(input); }
+  const fpga::BypassArgs &FpgaArgs() const { return fpga_bypass_args; }
+  void SetFpgaArgs(const fpga::BypassArgs &args) { fpga_bypass_args = args; }
+#endif
 };
 #endif