Fix error log for yaml check (#48126)

* fix error log for yaml check

* remove grad_op of increment

paddle/fluid/operators/generator/CMakeLists.txt

@@ -77,16 +77,21 @@ execute_process(
     ./parsed_ops/ops.parsed.yaml ./parsed_ops/legacy_ops.parsed.yaml
     --backward_yaml_paths ./parsed_ops/backward_ops.parsed.yaml
     ./parsed_ops/legacy_backward_ops.parsed.yaml
+  RESULT_VARIABLE _result)
+if(${_result})
+  message(FATAL_ERROR "ops validation failed, exiting.")
+endif()
+
+execute_process(
+  WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}/paddle/fluid/operators/generator
   COMMAND
     ${PYTHON_EXECUTABLE} cross_validate.py --forward_yaml_paths
     ./parsed_ops/sparse_ops.parsed.yaml --backward_yaml_paths
     ./parsed_ops/sparse_backward.parsed.yaml
-  RESULT_VARIABLE _results)
-foreach(_result in ${_results})
-  if(${_result})
-    message(FATAL_ERROR "ops validation failed, exiting.")
-  endif()
-endforeach()
+  RESULT_VARIABLE _result)
+if(${_result})
+  message(FATAL_ERROR "sparse ops validation failed, exiting.")
+endif()
 
 # code generation for op, op makers, and argument mapping functions
 message(

paddle/phi/api/yaml/legacy_backward.yaml

@@ -326,7 +326,7 @@
     func : conv3d_transpose_grad
 
 - backward_op : crop_grad
-  forward : crop_tensor (Tensor x, IntArray shape, IntArray offsets) -> Tensor(out)
+  forward : crop (Tensor x, IntArray shape, IntArray offsets) -> Tensor(out)
   args : (Tensor x, Tensor out_grad, IntArray offsets)
   output : Tensor(x_grad)
   infer_meta :
@@ -674,12 +674,6 @@
   output : Tensor(x_grad)
   invoke : imag_grad_impl(out_grad, x_grad)
 
-- backward_op : increment_grad
-  forward : increment (Tensor x, float value) -> Tensor(out)
-  args : (Tensor out, float value)
-  output : Tensor(x_grad)
-  invoke : increment (out, -value)
-
 - backward_op : index_add_grad
   forward : index_add(Tensor x, Tensor index,  Tensor add_value, int axis) -> Tensor(out)
   args : (Tensor index, Tensor add_value, Tensor out_grad, int axis)
@@ -1338,15 +1332,6 @@
   backward : reshape_double_grad
   inplace : (out_grad -> x_grad)
 
-- backward_op : reverse_array_grad
-  forward : reverse_array (Tensor[] x, IntArray axis) -> Tensor[](out)
-  args : (Tensor[] out_grad, IntArray axis)
-  output : Tensor[](x_grad){out_grad.size()}
-  infer_meta :
-    func : ReverseArrayInferMeta
-  kernel :
-    func : reverse
-
 - backward_op : reverse_grad
   forward : reverse (Tensor x, IntArray axis) -> Tensor(out)
   args : (Tensor out_grad, IntArray axis)