Rename full infer_meta (#38332)

* rename full infer_meta

* fix merge problem

paddle/pten/include/creation.h

@@ -30,7 +30,7 @@ DenseTensor FullLike(
     DataType dtype = DataType::UNDEFINED,
     Backend backend = Backend::UNDEFINED,  // Is backend needed here?
     DataLayout layout = DataLayout::UNDEFINED) {
-  auto out_meta = FullLikeInferMeta(x.meta(), dtype, layout);
+  auto out_meta = CreateLikeInferMeta(x.meta(), dtype, layout);
   pten::DenseTensor dense_out(
       pten::make_intrusive<paddle::experimental::SharedStorage>(
           dev_ctx.GetPlace()),

paddle/pten/infermeta/nary.cc

@@ -17,16 +17,16 @@ limitations under the License. */
 
 namespace pten {
 
-DenseTensorMeta FullInferMeta(const std::vector<int64_t>& shape,
-                              DataType dtype,
-                              DataLayout layout) {
+DenseTensorMeta CreateInferMeta(const std::vector<int64_t>& shape,
+                                DataType dtype,
+                                DataLayout layout) {
   const auto& out_dims = paddle::framework::make_ddim(shape);
   return {dtype, out_dims, layout};
 }
 
-DenseTensorMeta FullInferMeta(const ScalarArray& shape,
-                              DataType dtype,
-                              DataLayout layout) {
+DenseTensorMeta CreateInferMeta(const ScalarArray& shape,
+                                DataType dtype,
+                                DataLayout layout) {
   const auto& out_dims = paddle::framework::make_ddim(shape.GetData());
   return {dtype, out_dims, layout};
 }

paddle/pten/infermeta/nary.h

@@ -27,12 +27,12 @@ namespace pten {
 //  Because functions in this file
 //  not only can infer shape, but alse need infer lod or other useful data.
 
-DenseTensorMeta FullInferMeta(const std::vector<int64_t>& shape,
-                              DataType dtype,
-                              DataLayout layout);
+DenseTensorMeta CreateInferMeta(const std::vector<int64_t>& shape,
+                                DataType dtype,
+                                DataLayout layout);
 
-DenseTensorMeta FullInferMeta(const ScalarArray& shape,
-                              DataType dtype,
-                              DataLayout layout);
+DenseTensorMeta CreateInferMeta(const ScalarArray& shape,
+                                DataType dtype,
+                                DataLayout layout);
 
 }  // namespace pten

paddle/pten/infermeta/unary.cc

@@ -81,9 +81,9 @@ DenseTensorMeta CastInferMeta(const DenseTensorMeta& x_meta,
   return out_meta;
 }
 
-DenseTensorMeta FullLikeInferMeta(const DenseTensorMeta& x_meta,
-                                  DataType dtype,
-                                  DataLayout layout) {
+DenseTensorMeta CreateLikeInferMeta(const DenseTensorMeta& x_meta,
+                                    DataType dtype,
+                                    DataLayout layout) {
   return {dtype == DataType::UNDEFINED ? x_meta.dtype : dtype,
           x_meta.dims,
           layout == DataLayout::UNDEFINED ? x_meta.layout : layout};

paddle/pten/infermeta/unary.h

@@ -44,9 +44,9 @@ DenseTensorMeta FlattenInferMeta(const DenseTensorMeta& x_meta,
 DenseTensorMeta CastInferMeta(const DenseTensorMeta& x_meta,
                               const DataType out_dtype);
 
-DenseTensorMeta FullLikeInferMeta(const DenseTensorMeta& x_meta,
-                                  DataType dtype,
-                                  DataLayout layout);
+DenseTensorMeta CreateLikeInferMeta(const DenseTensorMeta& x_meta,
+                                    DataType dtype,
+                                    DataLayout layout);
 
 DenseTensorMeta InferMetaFromVecValue(const DenseTensorMeta& x_meta,
                                       const std::vector<int64_t>& shape);

python/paddle/utils/code_gen/api.yaml

@@ -48,7 +48,7 @@
   args : (const ScalarArray& shape, const Scalar& value, DataType dtype=DataType::FLOAT32, Backend place=Backend::CPU, DataLayout layout=DataLayout::NCHW)
   output: Tensor
   infer_meta : 
-    func : FullInferMeta
+    func : CreateInferMeta
     param : [shape, dtype, layout]
   kernel : 
     func : full
@@ -61,7 +61,7 @@
   args : (const Tensor& x, const Scalar& value, DataType dtype = DataType::UNDEFINED, Backend place = Backend::UNDEFINED, DataLayout layout = DataLayout::UNDEFINED)
   output: Tensor
   infer_meta : 
-    func : FullLikeInferMeta
+    func : CreateLikeInferMeta
     param : [x, dtype, layout]
   kernel : 
     func : full_like
@@ -146,15 +146,6 @@
   output : Tensor
   invoke : full_like(x, 0, dtype, place, layout)
 
-# - api : full_like
-#   args : (const Tensor& x, const Scalar& value, DataType dtype, Backend place)->Tensor
-#   output: {Tensor : dtype}
-#   kernel : fill_any_like
-#   T : [dtype, x]
-#   backend : [place, x]
-#   layout : []
-#   InferMeta : UnchangedInferMeta(x)
-
 - api : conj
   args : (const Tensor& x)
   output : Tensor