Add intermediate config for some api in yaml (#42824)

* add intermediate for some api

* fix bug

* fix fluid.layer

paddle/phi/infermeta/unary.cc

@@ -2163,8 +2163,8 @@ void SplitInferMeta(const MetaTensor& x,
 
 void SqueezeInferMeta(const MetaTensor& x,
                       const std::vector<int>& axes,
-                      MetaTensor* xshape,
-                      MetaTensor* out) {
+                      MetaTensor* out,
+                      MetaTensor* xshape) {
   const auto& x_dims = x.dims();
   // Check input tensor dims (<6) Eigen limit.
   PADDLE_ENFORCE_LE(x_dims.size(),
@@ -2964,8 +2964,8 @@ void UniqueRawInferMeta(const MetaTensor& x,
 
 void UnsqueezeInferMeta(const MetaTensor& x,
                         const IntArray& axes,
-                        MetaTensor* xshape,
                         MetaTensor* out,
+                        MetaTensor* xshape,
                         MetaConfig config) {
   const auto& x_dims = x.dims();
   // Validity Check: input tensor dims (<6).

paddle/phi/infermeta/unary.h

@@ -306,8 +306,8 @@ void SplitInferMeta(const MetaTensor& x_meta,
 
 void SqueezeInferMeta(const MetaTensor& x,
                       const std::vector<int>& axes,
-                      MetaTensor* xshape,
-                      MetaTensor* out);
+                      MetaTensor* out,
+                      MetaTensor* xshape);
 
 void StridedSliceRawInferMeta(const MetaTensor& x,
                               const std::vector<int>& axes,
@@ -425,8 +425,8 @@ void UniqueRawInferMeta(const MetaTensor& x,
 
 void UnsqueezeInferMeta(const MetaTensor& x,
                         const IntArray& axes,
-                        MetaTensor* xshape,
                         MetaTensor* out,
+                        MetaTensor* xshape,
                         MetaConfig config = MetaConfig());
 
 void UnStackInferMeta(const MetaTensor& x,

paddle/phi/kernels/impl/squeeze_kernel_impl.h

@@ -22,8 +22,8 @@ template <typename T, typename Context>
 void SqueezeKernel(const Context& dev_ctx,
                    const DenseTensor& x,
                    const std::vector<int>& axes,
-                   DenseTensor* xshape,
-                   DenseTensor* out) {
+                   DenseTensor* out,
+                   DenseTensor* xshape) {
   auto x_dims = x.dims();
   auto out_dims = funcs::GetOutputSqueezeShape(axes, x_dims, true);
 

paddle/phi/kernels/impl/unsqueeze_kernel_impl.h

@@ -22,8 +22,8 @@ template <typename T, typename Context>
 void UnsqueezeKernel(const Context& dev_ctx,
                      const DenseTensor& x,
                      const IntArray& axes,
-                     DenseTensor* xshape,
-                     DenseTensor* out) {
+                     DenseTensor* out,
+                     DenseTensor* xshape) {
   auto x_dims = x.dims();
   auto out_dims = out->dims();
   if (axes.FromTensor()) {

paddle/phi/kernels/squeeze_kernel.h

@@ -23,6 +23,6 @@ template <typename T, typename Context>
 void SqueezeKernel(const Context& dev_ctx,
                    const DenseTensor& x,
                    const std::vector<int>& axes,
-                   DenseTensor* xshape,
-                   DenseTensor* out);
+                   DenseTensor* out,
+                   DenseTensor* xshape);
 }  // namespace phi

paddle/phi/kernels/unsqueeze_kernel.h

@@ -24,6 +24,6 @@ template <typename T, typename Context>
 void UnsqueezeKernel(const Context& dev_ctx,
                      const DenseTensor& x,
                      const IntArray& axes,
-                     DenseTensor* xshape,
-                     DenseTensor* out);
+                     DenseTensor* out,
+                     DenseTensor* xshape);
 }  // namespace phi

paddle/phi/ops/compat/squeeze_sig.cc

@@ -18,7 +18,7 @@
 namespace phi {
 
 KernelSignature SqueezeOpArgumentMapping(const ArgumentMappingContext& ctx) {
-  return KernelSignature("squeeze", {"X"}, {"axes"}, {"XShape", "Out"});
+  return KernelSignature("squeeze", {"X"}, {"axes"}, {"Out", "XShape"});
 }
 
 KernelSignature SqueezeGradOpArgumentMapping(

paddle/phi/ops/compat/unsqueeze_sig.cc

@@ -21,14 +21,14 @@ KernelSignature UnsqueezeOpArgumentMapping(const ArgumentMappingContext& ctx) {
   if (ctx.InputSize("AxesTensorList") > 0) {
     VLOG(2) << "unsqueeze2 in AxesTensorList";
     return KernelSignature(
-        "unsqueeze", {"X"}, {"AxesTensorList"}, {"XShape", "Out"});
+        "unsqueeze", {"X"}, {"AxesTensorList"}, {"Out", "XShape"});
   } else if (ctx.InputSize("AxesTensor") > 0) {
     VLOG(2) << "unsqueeze2 in AxesTensor";
     return KernelSignature(
-        "unsqueeze", {"X"}, {"AxesTensor"}, {"XShape", "Out"});
+        "unsqueeze", {"X"}, {"AxesTensor"}, {"Out", "XShape"});
   } else {
     VLOG(2) << "unsqueeze2 in axes";
-    return KernelSignature("unsqueeze", {"X"}, {"axes"}, {"XShape", "Out"});
+    return KernelSignature("unsqueeze", {"X"}, {"axes"}, {"Out", "XShape"});
   }
 }
 

python/paddle/fluid/layers/nn.py

@@ -6533,7 +6533,7 @@ def squeeze(input, axes, name=None):
 
     """
     if in_dygraph_mode():
-        return _C_ops.final_state_squeeze(input, axes)[1]
+        return _C_ops.final_state_squeeze(input, axes)
     if _in_legacy_dygraph():
         out, _ = _C_ops.squeeze2(input, 'axes', axes)
         return out
@@ -6598,7 +6598,7 @@ def unsqueeze(input, axes, name=None):
         if _in_legacy_dygraph():
             out, _ = _C_ops.unsqueeze2(input, 'axes', axes)
             return out
-        return _C_ops.final_state_unsqueeze(input, axes)[1]
+        return _C_ops.final_state_unsqueeze(input, axes)
 
     check_type(axes, 'axis/axes', (int, list, tuple, Variable), 'unsqueeze')
     check_variable_and_dtype(input, 'input', [

python/paddle/tensor/manipulation.py

@@ -1427,8 +1427,7 @@ def flatten(x, start_axis=0, stop_axis=-1, name=None):
         raise ValueError("The stop_axis should be larger than stat_axis")
 
     if in_dygraph_mode():
-        dy_out, _ = _C_ops.final_state_flatten(x, start_axis, stop_axis)
-        return dy_out
+        return _C_ops.final_state_flatten(x, start_axis, stop_axis)
 
     if _in_legacy_dygraph():
         dy_out, _ = _C_ops.flatten_contiguous_range(x, 'start_axis', start_axis,
@@ -1936,7 +1935,7 @@ def squeeze(x, axis=None, name=None):
     input = x
     axes = axis
     if in_dygraph_mode():
-        return _C_ops.final_state_squeeze(input, axes)[1]
+        return _C_ops.final_state_squeeze(input, axes)
     if _in_legacy_dygraph():
         out, _ = _C_ops.squeeze2(input, 'axes', axes)
         return out
@@ -2271,7 +2270,7 @@ def unsqueeze(x, axis, name=None):
         if _in_legacy_dygraph():
             out, _ = _C_ops.unsqueeze2(input, 'axes', axes)
             return out
-        return _C_ops.final_state_unsqueeze(input, axes)[1]
+        return _C_ops.final_state_unsqueeze(input, axes)
 
     check_type(axes, 'axis/axes', (int, list, tuple, Variable), 'unsqueeze')
     check_variable_and_dtype(input, 'input', [

python/paddle/utils/code_gen/api.yaml

@@ -714,7 +714,7 @@
     backend : x
   inplace : (x -> out)
   view : (x -> out)
-  # intermediate : xshape
+  intermediate : xshape
   backward : flatten_grad
 
 # flip
@@ -1984,12 +1984,13 @@
 
 - api : squeeze
   args : (Tensor x, int[] axes)
-  output : Tensor(xshape), Tensor(out)
+  output : Tensor(out), Tensor(xshape)
   infer_meta :
     func : SqueezeInferMeta
   kernel :
     func : squeeze
   view: (x -> out)
+  intermediate : xshape
   backward : squeeze_grad
 
 - api : stack
@@ -2213,12 +2214,13 @@
 
 - api : unsqueeze
   args : (Tensor x, IntArray axis)
-  output : Tensor(xshape), Tensor(out)
+  output : Tensor(out), Tensor(xshape)
   infer_meta :
     func : UnsqueezeInferMeta
   kernel :
     func : unsqueeze
   view: (x -> out)
+  intermediate : xshape
   backward : unsqueeze_grad
 
 # viterbi_decode

python/paddle/utils/code_gen/backward.yaml

@@ -1750,7 +1750,7 @@
     func : square_grad
 
 - backward_api : squeeze_grad
-  forward : squeeze(Tensor x, int[] axes) -> Tensor(xshape), Tensor(out)
+  forward : squeeze(Tensor x, int[] axes) -> Tensor(out), Tensor(xshape)
   args : (Tensor xshape, Tensor out_grad, int[] axes)
   output : Tensor(x_grad)
   infer_meta :
@@ -2021,7 +2021,7 @@
   no_need_buffer : x
 
 - backward_api : unsqueeze_grad
-  forward : unsqueeze(Tensor x, IntArray axes) -> Tensor(xshape), Tensor(out)
+  forward : unsqueeze(Tensor x, IntArray axes) -> Tensor(out), Tensor(xshape)
   args : (Tensor xshape, Tensor out_grad)
   output : Tensor(x_grad)
   infer_meta :