added recompute_scale_factor in interpolate

	modified:   python/paddle/nn/functional/common.py
	modified:   python/paddle/nn/layer/common.py
	new file:   test/legacy_test/test_interp_recompute_scale_factor.py

Author: Qin-sx

python/paddle/nn/functional/common.py

@@ -225,6 +225,7 @@ def interpolate(
     data_format: (
         DataLayout1DVariant | DataLayout2D | DataLayout3D | None
     ) = None,
+    recompute_scale_factor: bool | None = None,
     name: str | None = None,
 ) -> Tensor:
     """
@@ -493,6 +494,15 @@ def interpolate(
             "align_corners option can only be set with the interpolating modes: linear | bilinear | bicubic | trilinear"
         )
 
+    if (
+        recompute_scale_factor is not None
+        and recompute_scale_factor
+        and size is not None
+    ):
+        raise ValueError(
+            "recompute_scale_factor is not meaningful with an explicit size."
+        )
+
     if resample == 'AREA':
         if isinstance(size, (list, tuple, Variable, paddle.pir.Value)):
             if len(size) == 0:
@@ -645,7 +655,7 @@ def _is_list_or_tuple_(data):
                     attrs['out_h'] = out_shape[1]
                     attrs['out_w'] = out_shape[2]
 
-    else:
+    elif scale is not None and recompute_scale_factor is not True:
         if in_dynamic_mode() and isinstance(scale, Variable):
             if scale.shape == []:
                 scale = float(scale)
@@ -676,6 +686,51 @@ def _is_list_or_tuple_(data):
                 "Attr(scale)'s type should be float, int, list, tuple, or Tensor."
             )
 
+    elif recompute_scale_factor is not None and recompute_scale_factor:
+        assert (
+            scale is not None
+        ), "scale_factor must not be None when recompute_scale_factor=True"
+
+        if in_dynamic_mode() and isinstance(scale, Variable):
+            if scale.shape == []:
+                scale = float(scale)
+            else:
+                scale = list(scale.numpy())
+
+        dim = len(x.shape) - 2
+
+        if isinstance(scale, (float, int, numpy.ndarray)):
+            scale_list = [float(scale)] * dim
+        elif isinstance(scale, (list, tuple)):
+            if len(scale) != dim:
+                raise ValueError(
+                    f"scale_shape length should be {dim} for "
+                    f"input {len(x.shape)}-D tensor."
+                )
+            scale_list = list(map(float, scale))
+        else:
+            raise TypeError(
+                "Attr(scale)'s type should be float, int, list, tuple, or Tensor."
+            )
+
+        out_shape = []
+        for i in range(dim):
+            input_size = x.shape[i + 2]
+            output_size = int(numpy.floor(float(input_size) * scale_list[i]))
+            out_shape.append(output_size)
+
+        if len(x.shape) == 3:
+            attrs['out_w'] = out_shape[0]
+        elif len(x.shape) == 4:
+            attrs['out_h'] = out_shape[0]
+            attrs['out_w'] = out_shape[1]
+        elif len(x.shape) == 5:
+            attrs['out_d'] = out_shape[0]
+            attrs['out_h'] = out_shape[1]
+            attrs['out_w'] = out_shape[2]
+
+        scale = None
+
     if in_dynamic_or_pir_mode():
         attr_list = []
         for k, v in attrs.items():

python/paddle/nn/layer/common.py

@@ -431,6 +431,7 @@ class Upsample(Layer):
     align_corners: bool
     align_mode: int
     data_format: DataLayout1DVariant | DataLayout2D | DataLayout3D | None
+    recompute_scale_factor: bool | None
     name: str | None
 
     def __init__(
@@ -443,6 +444,7 @@ def __init__(
         data_format: (
             DataLayout1DVariant | DataLayout2D | DataLayout3D | None
         ) = None,
+        recompute_scale_factor: bool | None = None,
         name: str | None = None,
     ) -> None:
         super().__init__()
@@ -452,6 +454,7 @@ def __init__(
         self.align_corners = align_corners
         self.align_mode = align_mode
         self.data_format = data_format
+        self.recompute_scale_factor = recompute_scale_factor
         self.name = name
 
     def forward(self, x: Tensor) -> Tensor:
@@ -475,6 +478,7 @@ def forward(self, x: Tensor) -> Tensor:
             align_corners=self.align_corners,
             align_mode=self.align_mode,
             data_format=self.data_format,
+            recompute_scale_factor=self.recompute_scale_factor,
             name=self.name,
         )