[phi] Transfer fluid bicubic_interp_v2 to phi bicubic_interp (add yaml) (#45151)

* transfer bicubic_interp op to phi, change name from bicubic_interp_v2 to bicubic_interp

* test final_state_bicubic_interp api

* testcase match imperative case

paddle/phi/api/yaml/legacy_api.yaml

@@ -353,6 +353,17 @@
     func : bce_loss
   backward : bce_loss_grad
 
+- api : bicubic_interp
+  args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode)
+  output : Tensor(output)
+  infer_meta :
+    func : InterpolateInferMeta
+  optional: out_size, size_tensor, scale_tensor
+  kernel :
+    func : bicubic_interp
+    data_type : x
+  backward : bicubic_interp_grad
+
 - api : bilinear_tensor_product
   args : (Tensor x, Tensor y, Tensor weight, Tensor bias)
   output : Tensor

paddle/phi/api/yaml/legacy_backward.yaml

@@ -283,6 +283,18 @@
     func : bce_loss_grad
   inplace : (out_grad -> input_grad)
 
+- backward_api : bicubic_interp_grad
+  forward : bicubic_interp (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) -> Tensor(output)
+  args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, Tensor output_grad, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode)
+  output : Tensor(x_grad)
+  infer_meta :
+    func : UnchangedInferMeta
+    param: [x]
+  optional: out_size, size_tensor, scale_tensor
+  kernel :
+    func : bicubic_interp_grad
+    data_type : output_grad
+
 - backward_api : bilinear_tensor_product_grad
   forward : bilinear_tensor_product (Tensor x, Tensor y, Tensor weight, Tensor bias) -> Tensor(out)
   args : (Tensor x, Tensor y, Tensor weight, Tensor out_grad)

paddle/phi/core/compat/op_utils.h

@@ -75,7 +75,9 @@ const std::unordered_set<std::string> deprecated_op_names(
      "linear_interp",
      "linear_interp_grad",
      "nearest_interp",
-     "nearest_interp_grad"});
+     "nearest_interp_grad",
+     "bicubic_interp",
+     "bicubic_interp_grad"});
 
 class DefaultKernelSignatureMap {
  public:

paddle/phi/kernels/cpu/interpolate_grad_kernel.cc

@@ -1072,7 +1072,7 @@ PD_REGISTER_KERNEL(linear_interp_grad,
   kernel->InputAt(2).SetBackend(phi::Backend::ALL_BACKEND);
   kernel->InputAt(3).SetBackend(phi::Backend::ALL_BACKEND);
 }
-PD_REGISTER_KERNEL(bicubic_interp_v2_grad,
+PD_REGISTER_KERNEL(bicubic_interp_grad,
                    CPU,
                    ALL_LAYOUT,
                    phi::BicubicInterpGradKernel,

paddle/phi/kernels/cpu/interpolate_kernel.cc

@@ -1229,12 +1229,8 @@ PD_REGISTER_KERNEL(linear_interp,
   kernel->InputAt(2).SetBackend(phi::Backend::ALL_BACKEND);
   kernel->InputAt(3).SetBackend(phi::Backend::ALL_BACKEND);
 }
-PD_REGISTER_KERNEL(bicubic_interp_v2,
-                   CPU,
-                   ALL_LAYOUT,
-                   phi::BicubicInterpKernel,
-                   float,
-                   double) {
+PD_REGISTER_KERNEL(
+    bicubic_interp, CPU, ALL_LAYOUT, phi::BicubicInterpKernel, float, double) {
   kernel->InputAt(2).SetBackend(phi::Backend::ALL_BACKEND);
   kernel->InputAt(3).SetBackend(phi::Backend::ALL_BACKEND);
 }

paddle/phi/kernels/gpu/interpolate_grad_kernel.cu

@@ -1605,7 +1605,7 @@ PD_REGISTER_KERNEL(linear_interp_grad,
   kernel->InputAt(2).SetBackend(phi::Backend::ALL_BACKEND);
   kernel->InputAt(3).SetBackend(phi::Backend::ALL_BACKEND);
 }
-PD_REGISTER_KERNEL(bicubic_interp_v2_grad,
+PD_REGISTER_KERNEL(bicubic_interp_grad,
                    GPU,
                    ALL_LAYOUT,
                    phi::BicubicInterpGradKernel,

paddle/phi/kernels/gpu/interpolate_kernel.cu

@@ -1481,7 +1481,7 @@ PD_REGISTER_KERNEL(linear_interp,
   kernel->InputAt(2).SetBackend(phi::Backend::ALL_BACKEND);
   kernel->InputAt(3).SetBackend(phi::Backend::ALL_BACKEND);
 }
-PD_REGISTER_KERNEL(bicubic_interp_v2,
+PD_REGISTER_KERNEL(bicubic_interp,
                    GPU,
                    ALL_LAYOUT,
                    phi::BicubicInterpKernel,

paddle/phi/ops/compat/interpolate_sig.cc

@@ -77,7 +77,7 @@ KernelSignature LinearInterpOpArgumentMapping(
 
 KernelSignature BicubicInterpOpArgumentMapping(
     const ArgumentMappingContext& ctx) {
-  return KernelSignature("bicubic_interp_v2",
+  return KernelSignature("bicubic_interp",
                          {"X", "OutSize", "SizeTensor", "Scale"},
                          {"data_layout",
                           "out_d",
@@ -151,7 +151,7 @@ KernelSignature LinearInterpGradOpArgumentMapping(
 
 KernelSignature BicubicInterpGradOpArgumentMapping(
     const ArgumentMappingContext& ctx) {
-  return KernelSignature("bicubic_interp_v2_grad",
+  return KernelSignature("bicubic_interp_grad",
                          {"X", "OutSize", "SizeTensor", "Scale", "Out@GRAD"},
                          {"data_layout",
                           "out_d",
@@ -168,9 +168,11 @@ KernelSignature BicubicInterpGradOpArgumentMapping(
 
 PD_REGISTER_BASE_KERNEL_NAME(linear_interp_v2, linear_interp);
 PD_REGISTER_BASE_KERNEL_NAME(nearest_interp_v2, nearest_interp);
+PD_REGISTER_BASE_KERNEL_NAME(bicubic_interp_v2, bicubic_interp);
 
 PD_REGISTER_BASE_KERNEL_NAME(linear_interp_v2_grad, linear_interp_grad);
 PD_REGISTER_BASE_KERNEL_NAME(nearest_interp_v2_grad, nearest_interp_grad);
+PD_REGISTER_BASE_KERNEL_NAME(bicubic_interp_v2_grad, bicubic_interp_grad);
 
 PD_REGISTER_ARG_MAPPING_FN(bilinear_interp_v2,
                            phi::BilinearInterpOpArgumentMapping);

python/paddle/nn/functional/common.py

@@ -619,7 +619,17 @@ def interpolate(x,
             else:
                 out = _C_ops.nearest_interp_v2(x, *dy_attr)
         elif resample_type == "bicubic":
-            out = _C_ops.bicubic_interp_v2(x, *dy_attr)
+            if in_dygraph_mode():
+                out = _C_ops.final_state_bicubic_interp(
+                    x, inputs['OutSize'] if 'OutSize' in inputs else None,
+                    inputs['SizeTensor'] if 'SizeTensor' in inputs else None,
+                    inputs['Scale'] if 'Scale' in inputs else None,
+                    attrs['data_layout'], attrs['out_d'], attrs['out_h'],
+                    attrs['out_w'], attrs['scale'] if 'scale' in attrs else [],
+                    attrs['interp_method'], attrs['align_corners'],
+                    attrs['align_mode'])
+            else:
+                out = _C_ops.bicubic_interp_v2(x, *dy_attr)
         return out
     out = helper.create_variable_for_type_inference(dtype)
     helper.append_op(type='{}_interp_v2'.format(resample_type),