static graph autogen code support for full_like op

paddle/fluid/operators/generator/filters.py

@@ -94,6 +94,21 @@ class {to_pascal_case(op_name)}InferVarType : public framework::VarTypeInference
         ctx->GetInputDataType(framework::GradVarName("Out")));
   }}
 }};
+"""
+    elif op_name == "fill_any_like":
+        return f"""
+class {to_pascal_case(op_name)}InferVarType : public framework::VarTypeInference {{
+ public:
+  void operator()(framework::InferVarTypeContext *ctx) const override {{
+    auto var_data_type = static_cast<framework::proto::VarType::Type>(
+        PADDLE_GET_CONST(int, ctx->GetAttr("dtype")));
+    if (var_data_type < 0) {{
+      ctx->SetOutputDataType("Out", ctx->GetInputDataType("X"));
+    }} else {{
+      ctx->SetOutputDataType("Out", var_data_type);
+    }}
+  }}
+}};
 """
     else:
         return None

paddle/fluid/operators/generator/get_expected_kernel_func.cc

@@ -85,6 +85,18 @@ phi::KernelKey GetCheckFiniteAndUnscaleExpectedKernelType(
   return phi::KernelKey(dtype, ctx.GetPlace());
 }
 
+phi::KernelKey GetFullLikeExpectedKernelType(
+    const framework::ExecutionContext& ctx,
+    const framework::OperatorWithKernel* op_ptr) {
+  phi::KernelKey kt = op_ptr->OperatorWithKernel::GetExpectedKernelType(ctx);
+  const auto& data_type = ctx.Attr<int>("dtype");
+  if (data_type >= 0) {
+    kt.set_dtype(phi::TransToPhiDataType(
+        static_cast<framework::proto::VarType::Type>(data_type)));
+  }
+  return kt;
+}
+
 phi::KernelKey GetReduceExpectedKernelType(
     const framework::ExecutionContext& ctx,
     const framework::OperatorWithKernel* op_ptr) {

paddle/fluid/operators/generator/get_expected_kernel_func.h

@@ -28,6 +28,10 @@ phi::KernelKey GetCheckFiniteAndUnscaleExpectedKernelType(
     const framework::ExecutionContext& ctx,
     const framework::OperatorWithKernel* op_ptr);
 
+phi::KernelKey GetFullLikeExpectedKernelType(
+    const framework::ExecutionContext& ctx,
+    const framework::OperatorWithKernel* op_ptr);
+
 phi::KernelKey GetReduceGradExpectedKernelType(
     const framework::ExecutionContext& ctx,
     const framework::OperatorWithKernel* op_ptr);

paddle/phi/api/yaml/op_compat.yaml

@@ -1095,8 +1095,12 @@
     x : X
   outputs :
     out : Out
-  attrs :
-    {value: value, dtype: dtype}
+  scalar :
+    value :
+      data_type : float
+      support_tensor : true
+  get_expected_kernel_type :
+    full_like : GetFullLikeExpectedKernelType
 
 - op : fused_conv2d
   extra :

paddle/phi/api/yaml/static_ops.yaml

@@ -203,6 +203,16 @@
     param : [x, axis, keepdim, reduce_all]
   backward : frobenius_norm_grad
 
+- op : full_like
+  args : (Tensor x, Scalar value = 0.0, DataType dtype = DataType::UNDEFINED)
+  output: Tensor(out)
+  infer_meta :
+    func : FillAnyLikeInferMeta
+    param : [x]
+  kernel :
+    func : full_like
+    param : [x, value, dtype]
+
 - op : gaussian
   args : (IntArray shape = {}, float mean = .0f, float std = 1.0f, int seed = 0, DataType dtype = DataType::FLOAT32)
   output: Tensor(out)

paddle/phi/infermeta/unary.cc

@@ -1122,6 +1122,11 @@ void FillDiagonalInferMeta(
   out->set_dtype(x.dtype());
 }
 
+void FillAnyLikeInferMeta(const MetaTensor& x, MetaTensor* out) {
+  out->set_dims(x.dims());
+  out->share_lod(x);
+}
+
 void FFTC2CInferMeta(const MetaTensor& x,
                      const std::vector<int64_t>& axes,
                      const std::string& normalization,

paddle/phi/infermeta/unary.h

@@ -181,6 +181,8 @@ void ExpandInferMeta(const MetaTensor& x,
 void FillDiagonalInferMeta(
     const MetaTensor& x, float value, int offset, bool wrap, MetaTensor* out);
 
+void FillAnyLikeInferMeta(const MetaTensor& x, MetaTensor* out);
+
 void FFTC2CInferMeta(const MetaTensor& x,
                      const std::vector<int64_t>& axes,
                      const std::string& normalization,