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diff --git a/‎paddle/fluid/operators/fake_quantize_op.cc
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-114Lines changed: 0 additions & 114 deletions b/‎paddle/fluid/operators/fake_quantize_op.cc
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diff --git a/‎paddle/fluid/operators/fake_quantize_op.cu
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diff --git a/‎paddle/fluid/operators/fake_quantize_op.cu.h
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-78Lines changed: 0 additions & 78 deletions b/‎paddle/fluid/operators/fake_quantize_op.cu.h
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diff --git a/‎paddle/fluid/operators/fake_quantize_op.h
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-58Lines changed: 0 additions & 58 deletions b/‎paddle/fluid/operators/fake_quantize_op.h
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diff --git a/‎paddle/phi/api/yaml/op_compat.yaml
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+8-2Lines changed: 8 additions & 2 deletions b/‎paddle/phi/api/yaml/op_compat.yaml
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diff --git a/‎paddle/phi/api/yaml/ops.yaml
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diff --git a/‎paddle/phi/infermeta/ternary.cc
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diff --git a/‎paddle/phi/infermeta/ternary.h
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+11Lines changed: 11 additions & 0 deletions b/‎paddle/phi/infermeta/ternary.h
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@@ -285,37 +285,6 @@ struct ChannelClipFakeQuantDequantFunctor<phi::CPUContext, T> {
   }
 };
 
-template struct ChannelClipFakeQuantDequantFunctor<phi::CPUContext, float>;
-template <typename T>
-struct FindRangeAbsMaxFunctor<phi::CPUContext, T> {
-  void operator()(const phi::CPUContext &ctx,
-                  const phi::DenseTensor &cur_scale,
-                  const phi::DenseTensor &last_scale,
-                  const phi::DenseTensor &iter,
-                  const int window_size,
-                  phi::DenseTensor *scales_arr,
-                  phi::DenseTensor *out_scale) {
-    T *scale_arr = scales_arr->mutable_data<T>(ctx.GetPlace());
-    int64_t it = iter.data<int64_t>()[0];
-    int idx = static_cast<int>(it % window_size);
-    T removed = scale_arr[idx];
-    T cur = cur_scale.data<T>()[0];
-    scale_arr[idx] = cur;
-
-    T max = last_scale.data<T>()[0];
-    if (max < cur) {
-      max = cur;
-    } else if (fabs(removed - max) < 1e-6) {
-      int size = static_cast<int>((it > window_size) ? window_size : it);
-      phi::funcs::FindAbsMaxFunctor<phi::CPUContext, T>()(
-          ctx, scale_arr, size, &max);
-    }
-    out_scale->mutable_data<T>(ctx.GetPlace())[0] = max;
-  }
-};
-
-template struct FindRangeAbsMaxFunctor<phi::CPUContext, float>;
-
 class FakeQuantOrWithDequantAbsMaxOp : public framework::OperatorWithKernel {
  public:
   FakeQuantOrWithDequantAbsMaxOp(const std::string &type,
@@ -539,77 +508,6 @@ In above three formulas, the range value of c is as follow:
 )DOC");
   }
 };
-
-class FakeQuantizeRangeAbsMaxOp : public framework::OperatorWithKernel {
- public:
-  FakeQuantizeRangeAbsMaxOp(const std::string &type,
-                            const framework::VariableNameMap &inputs,
-                            const framework::VariableNameMap &outputs,
-                            const framework::AttributeMap &attrs)
-      : OperatorWithKernel(type, inputs, outputs, attrs) {}
-
-  void InferShape(framework::InferShapeContext *ctx) const override {
-    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "FakeQuantizeRangeAbsMax");
-    OP_INOUT_CHECK(
-        ctx->HasOutput("Out"), "Output", "Out", "FakeQuantizeRangeAbsMax");
-    OP_INOUT_CHECK(ctx->HasOutput("OutScale"),
-                   "Output",
-                   "OutScale",
-                   "FakeQuantizeRangeAbsMax");
-    if (ctx->HasOutput("OutScales")) {
-      int window_size = ctx->Attrs().Get<int>("window_size");
-      ctx->SetOutputDim("OutScales", {window_size});
-    }
-    ctx->SetOutputDim("Out", ctx->GetInputDim("X"));
-    ctx->SetOutputDim("OutScale", {1});
-    ctx->ShareLoD("X", /*->*/ "Out");
-  }
-
- protected:
-  phi::KernelKey GetExpectedKernelType(
-      const framework::ExecutionContext &ctx) const override {
-    return phi::KernelKey(OperatorWithKernel::IndicateVarDataType(ctx, "X"),
-                          ctx.device_context().GetPlace());
-  }
-};
-
-class FakeQuantizeRangeAbsMaxOpMaker
-    : public framework::OpProtoAndCheckerMaker {
- public:
-  void Make() override {
-    AddInput("X", "(Tensor) Input is float data type.");
-    AddInput("InScale", "Last scale.");
-    AddInput("Iter", "Global step iteration.").AsDispensable();
-    AddOutput("Out", "(Tensor) Output of quantized low level tensor.");
-    AddOutput("OutScale", " Current scale");
-    AddOutput("OutScales", "(Tensor) scale buffer.").AsDispensable();
-    AddAttr<int>("window_size", "(int, default 10000) window range size.")
-        .SetDefault(10000);
-    AddAttr<int>("bit_length", "(int, default 8), quantization bit number.")
-        .SetDefault(8)
-        .AddCustomChecker([](const int &bit_length) {
-          PADDLE_ENFORCE_EQ(bit_length >= 1 && bit_length <= 16,
-                            true,
-                            phi::errors::InvalidArgument(
-                                "'bit_length' should be between 1 and 16, but "
-                                "the received is %d",
-                                bit_length));
-        });
-    AddAttr<bool>("is_test",
-                  "(bool, default false) Set to true for inference only, false "
-                  "for training. Some layers may run faster when this is true.")
-        .SetDefault(false);
-    AddComment(R"DOC(
-FakeQuantize operator is used in static quantization.
-
-$$scale = max(max(abs(x)), history_abs_max)$$
-$$range = 2^{bit_length - 1} - 1$$
-$$Out = round(X/scale * range)$$
-
-)DOC");
-  }
-};
-
 class FakeQuantOrWithDequantMovingAverageAbsMaxOp
     : public framework::OperatorWithKernel {
  public:
@@ -820,18 +718,6 @@ PD_REGISTER_STRUCT_KERNEL(fake_quantize_dequantize_abs_max,
                           ops::FakeQuantizeDequantizeAbsMaxKernel,
                           float) {}
 
-REGISTER_OPERATOR(
-    fake_quantize_range_abs_max,
-    ops::FakeQuantizeRangeAbsMaxOp,
-    ops::FakeQuantizeRangeAbsMaxOpMaker,
-    paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
-    paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>);
-PD_REGISTER_STRUCT_KERNEL(fake_quantize_range_abs_max,
-                          CPU,
-                          ALL_LAYOUT,
-                          ops::FakeQuantizeRangeAbsMaxKernel,
-                          float) {}
-
 REGISTER_OPERATOR(
     fake_quantize_dequantize_moving_average_abs_max,
     ops::FakeQuantOrWithDequantMovingAverageAbsMaxOp,
 
@@ -30,12 +30,6 @@ PD_REGISTER_STRUCT_KERNEL(fake_channel_wise_quantize_abs_max,
                           ops::FakeChannelWiseQuantizeAbsMaxKernel,
                           float,
                           float16) {}
-PD_REGISTER_STRUCT_KERNEL(fake_quantize_range_abs_max,
-                          GPU,
-                          ALL_LAYOUT,
-                          ops::FakeQuantizeRangeAbsMaxKernel,
-                          float,
-                          float16) {}
 PD_REGISTER_STRUCT_KERNEL(moving_average_abs_max_scale,
                           GPU,
                           ALL_LAYOUT,
 
@@ -418,84 +418,6 @@ struct ChannelClipAndFakeQuantFunctor<phi::GPUContext, T> {
 
 template struct ChannelClipAndFakeQuantFunctor<phi::GPUContext, float>;
 
-template <typename T>
-__global__ void FindRangeAbsMaxAndFillArray(const T *cur_scale,
-                                            const T *last_scale,
-                                            const int64_t *iter,
-                                            const int window_size,
-                                            T *scale_arr,
-                                            T *out_scale,
-                                            int *need_find_max,
-                                            int *out_size) {
-  int it = iter[0];
-  int idx = it % window_size;
-  T removed = scale_arr[idx];
-  T cur = cur_scale[0];
-  scale_arr[idx] = cur;
-  T max = last_scale[0];
-  out_scale[0] = max < cur ? cur : max;
-  if (fabs(static_cast<typename QuantizeDataType<T>::type>(removed - max)) <
-      1e-6) {
-    need_find_max[0] = 1;
-    out_size[0] = it > window_size ? window_size : it;
-  } else {
-    need_find_max[0] = 0;
-  }
-}
-
-template <typename T>
-struct FindRangeAbsMaxFunctor<phi::GPUContext, T> {
-  void operator()(const phi::GPUContext &ctx,
-                  const phi::DenseTensor &cur_scale,
-                  const phi::DenseTensor &last_scale,
-                  const phi::DenseTensor &iter,
-                  const int window_size,
-                  phi::DenseTensor *scales_arr,
-                  phi::DenseTensor *out_scale) {
-    const auto gpu_place = ctx.GetPlace();
-
-    T *scale_arr = scales_arr->mutable_data<T>(gpu_place);
-    T *out_scale_data = out_scale->mutable_data<T>(gpu_place);
-
-    phi::DenseTensor need_find_max, out_size;
-    int *find_max = need_find_max.mutable_data<int>({1}, gpu_place);
-    int *out_size_data = out_size.mutable_data<int>({1}, gpu_place);
-
-    FindRangeAbsMaxAndFillArray<T>
-        <<<1, 1, 0, ctx.stream()>>>(cur_scale.data<T>(),
-                                    last_scale.data<T>(),
-                                    iter.data<int64_t>(),
-                                    window_size,
-                                    scale_arr,
-                                    out_scale_data,
-                                    find_max,
-                                    out_size_data);
-
-    int g_find_max;
-    memory::Copy(platform::CPUPlace(),
-                 &g_find_max,
-                 gpu_place,
-                 find_max,
-                 sizeof(int),
-                 ctx.stream());
-    ctx.Wait();
-    if (g_find_max) {
-      int len;
-      memory::Copy(platform::CPUPlace(),
-                   &len,
-                   gpu_place,
-                   out_size_data,
-                   sizeof(int),
-                   ctx.stream());
-      ctx.Wait();
-      phi::funcs::FindAbsMaxFunctor<phi::GPUContext, T>()(
-          ctx, scale_arr, len, out_scale_data);
-    }
-  }
-};
-
-template struct FindRangeAbsMaxFunctor<phi::GPUContext, float>;
-
 // ChannelClipAndQuantDequantKernel for quant_axis is 0
 template <typename T>
 __global__ void ChannelClipAndQuantDequantKernelQuantAxis0(const T *in,
 
@@ -37,17 +37,6 @@ struct ClipAndFakeQuantDequantFunctor {
                   phi::DenseTensor *out);
 };
 
-template <typename DeviceContext, typename T>
-struct FindRangeAbsMaxFunctor {
-  void operator()(const DeviceContext &ctx,
-                  const phi::DenseTensor &cur_scale,
-                  const phi::DenseTensor &last_scale,
-                  const phi::DenseTensor &iter,
-                  const int window_size,
-                  phi::DenseTensor *scales_arr,
-                  phi::DenseTensor *out_scale);
-};
-
 template <typename DeviceContext, typename T>
 struct FindChannelAbsMaxFunctor {
   void operator()(const DeviceContext &ctx,
@@ -176,53 +165,6 @@ class FakeChannelWiseQuantizeDequantizeAbsMaxKernel
   }
 };
 
-template <typename T, typename DeviceContext>
-class FakeQuantizeRangeAbsMaxKernel : public framework::OpKernel<T> {
- public:
-  void Compute(const framework::ExecutionContext &context) const override {
-    auto *in = context.Input<phi::DenseTensor>("X");
-    auto *in_scale = context.Input<phi::DenseTensor>("InScale");
-
-    auto *out = context.Output<phi::DenseTensor>("Out");
-    out->mutable_data<T>(context.GetPlace());
-
-    bool is_test = context.Attr<bool>("is_test");
-    int bit_length = context.Attr<int>("bit_length");
-    int round_type = context.Attr<int>("round_type");
-    int bin_cnt = std::pow(2, bit_length - 1) - 1;
-    auto &dev_ctx = context.template device_context<DeviceContext>();
-
-    // testing
-    if (is_test) {
-      phi::funcs::ClipAndFakeQuantFunctor<DeviceContext, T>()(
-          dev_ctx, *in, *in_scale, bin_cnt, round_type, out);
-      return;
-    }
-
-    // training
-    auto *out_scale = context.Output<phi::DenseTensor>("OutScale");
-    auto *out_scales = context.Output<phi::DenseTensor>("OutScales");
-    auto *iter = context.Input<phi::DenseTensor>("Iter");
-
-    int window_size = context.Attr<int>("window_size");
-    out_scale->mutable_data<T>(context.GetPlace());
-
-    phi::DenseTensor cur_scale;
-    T *cur_scale_data = cur_scale.mutable_data<T>({1}, context.GetPlace());
-    phi::funcs::FindAbsMaxFunctor<DeviceContext, T>()(
-        dev_ctx, in->data<T>(), in->numel(), cur_scale_data);
-    FindRangeAbsMaxFunctor<DeviceContext, T>()(dev_ctx,
-                                               cur_scale,
-                                               *in_scale,
-                                               *iter,
-                                               window_size,
-                                               out_scales,
-                                               out_scale);
-    phi::funcs::ClipAndFakeQuantFunctor<DeviceContext, T>()(
-        dev_ctx, *in, *out_scale, bin_cnt, round_type, out);
-  }
-};
-
 template <typename T, typename DeviceContext>
 class FakeMovingAverageAbsMaxKernelBase : public framework::OpKernel<T> {
  public:
 
@@ -1126,8 +1126,14 @@
     out_accum : OutAccum
 
 - op : fake_quantize_range_abs_max
-  extra :
-    attrs : [int round_type = 1]
+  inputs :
+    x : X
+    in_scale : InScale
+    iter : Iter
+  outputs :
+    out : Out
+    out_scale : OutScale
+    out_scales : OutScales
 
 - op : fc
   inputs :
 
@@ -1005,6 +1005,16 @@
     data_type : x
   optional : in_accum, in_state, out_state, out_accum
 
+- op : fake_quantize_range_abs_max
+  args : (Tensor x, Tensor in_scale, Tensor iter, int window_size = 10000,  int bit_length = 8, bool is_test = false, int round_type = 1)
+  output : Tensor(out), Tensor(out_scale), Tensor(out_scales)
+  infer_meta :
+    func : FakeQuantizeRangeAbsMaxInferMeta
+  kernel :
+    func : fake_quantize_range_abs_max
+    data_type : x
+  optional : iter, out_scales
+
 - op : fft_c2c
   args : (Tensor x, int64_t[] axes, str normalization, bool forward)
   output : Tensor
 
@@ -372,6 +372,31 @@ void DpsgdInferMeta(const MetaTensor& param,
           grad.dims()));
   param_out->set_dims(param_dims);
 }
+
+void FakeQuantizeRangeAbsMaxInferMeta(const MetaTensor& x,
+                                      const MetaTensor& in_scale,
+                                      const MetaTensor& iter,
+                                      int window_size,
+                                      int bit_length,
+                                      bool is_test,
+                                      int round_type,
+                                      MetaTensor* out,
+                                      MetaTensor* out_scale,
+                                      MetaTensor* out_scales) {
+  PADDLE_ENFORCE_EQ(bit_length >= 1 && bit_length <= 16,
+                    true,
+                    phi::errors::InvalidArgument(
+                        "'bit_length' should be between 1 and 16, but "
+                        "the received is %d",
+                        bit_length));
+  if (out_scales) {
+    out_scales->set_dims({window_size});
+  }
+  out->set_dims(x.dims());
+  out_scale->set_dims({1});
+  out->share_lod(x);
+}
+
 void FlashAttnInferMeta(const MetaTensor& q,
                         const MetaTensor& k,
                         const MetaTensor& v,
 
@@ -96,6 +96,17 @@ void DpsgdInferMeta(const MetaTensor& param,
                     int size,
                     MetaTensor* param_out);
 
+void FakeQuantizeRangeAbsMaxInferMeta(const MetaTensor& x,
+                                      const MetaTensor& in_scale,
+                                      const MetaTensor& iter,
+                                      int window_size,
+                                      int bit_length,
+                                      bool is_test,
+                                      int round_type,
+                                      MetaTensor* out,
+                                      MetaTensor* out_scale,
+                                      MetaTensor* out_scales);
+
 void FlashAttnInferMeta(const MetaTensor& q,
                         const MetaTensor& k,
                         const MetaTensor& v,