Rename for PAN

Author: qubvel

segmentation_models_pytorch/decoders/pan/decoder.py

@@ -168,12 +168,12 @@ def __init__(
         self,
         in_channels: int,
         out_channels: int,
-        decoder_interpolation_mode: str = "bilinear",
+        interpolation_mode: str = "bilinear",
     ):
         super(GAUBlock, self).__init__()
 
-        self.interpolation_mode = decoder_interpolation_mode
-        self.align_corners = True if decoder_interpolation_mode == "bilinear" else None
+        self.interpolation_mode = interpolation_mode
+        self.align_corners = True if interpolation_mode == "bilinear" else None
 
         self.conv1 = nn.Sequential(
             nn.AdaptiveAvgPool2d(1),
@@ -214,7 +214,7 @@ def __init__(
         encoder_channels: Sequence[int],
         encoder_depth: Literal[3, 4, 5],
         decoder_channels: int,
-        decoder_interpolation_mode: str = "bilinear",
+        interpolation_mode: str = "bilinear",
     ):
         super().__init__()
 
@@ -235,19 +235,19 @@ def __init__(
             self.gau3 = GAUBlock(
                 in_channels=encoder_channels[2],
                 out_channels=decoder_channels,
-                decoder_interpolation_mode=decoder_interpolation_mode,
+                interpolation_mode=interpolation_mode,
             )
         if encoder_depth >= 4:
             self.gau2 = GAUBlock(
                 in_channels=encoder_channels[1],
                 out_channels=decoder_channels,
-                decoder_interpolation_mode=decoder_interpolation_mode,
+                interpolation_mode=interpolation_mode,
             )
         if encoder_depth >= 3:
             self.gau1 = GAUBlock(
                 in_channels=encoder_channels[0],
                 out_channels=decoder_channels,
-                decoder_interpolation_mode=decoder_interpolation_mode,
+                interpolation_mode=interpolation_mode,
             )
 
     def forward(self, features: List[torch.Tensor]) -> torch.Tensor:

segmentation_models_pytorch/decoders/pan/model.py

@@ -31,7 +31,7 @@ class PAN(SegmentationModel):
         encoder_output_stride: 16 or 32, if 16 use dilation in encoder last layer.
             Doesn't work with ***ception***, **vgg***, **densenet*`** backbones.Default is 16.
         decoder_channels: A number of convolution layer filters in decoder blocks
-        decoder_interpolation_mode: Interpolation mode used in decoder of the model. Available options are
+        decoder_interpolation: Interpolation mode used in decoder of the model. Available options are
             **"nearest"**, **"bilinear"**, **"bicubic"**, **"area"**, **"nearest-exact"**. Default is **"bilinear"**.
         in_channels: A number of input channels for the model, default is 3 (RGB images)
         classes: A number of classes for output mask (or you can think as a number of channels of output mask)
@@ -65,7 +65,7 @@ def __init__(
         encoder_weights: Optional[str] = "imagenet",
         encoder_output_stride: Literal[16, 32] = 16,
         decoder_channels: int = 32,
-        decoder_interpolation_mode: str = "bilinear",
+        decoder_interpolation: str = "bilinear",
         in_channels: int = 3,
         classes: int = 1,
         activation: Optional[Union[str, Callable]] = None,
@@ -82,6 +82,15 @@ def __init__(
                 )
             )
 
+        upscale_mode = kwargs.pop("upscale_mode", None)
+        if upscale_mode is not None:
+            warnings.warn(
+                "The usage of upscale_mode is deprecated. Please modify your code for decoder_interpolation",
+                DeprecationWarning,
+                stacklevel=2,
+            )
+            decoder_interpolation = upscale_mode
+
         self.encoder = get_encoder(
             encoder_name,
             in_channels=in_channels,
@@ -91,20 +100,11 @@ def __init__(
             **kwargs,
         )
 
-        upscale_mode = kwargs.pop("upscale_mode", None)
-        if upscale_mode is not None:
-            warnings.warn(
-                "The usage of upscale_mode is deprecated. Please modify your code for decoder_interpolation_mode",
-                DeprecationWarning,
-                stacklevel=2,
-            )
-            decoder_interpolation_mode = upscale_mode
-
         self.decoder = PANDecoder(
             encoder_channels=self.encoder.out_channels,
             encoder_depth=encoder_depth,
             decoder_channels=decoder_channels,
-            decoder_interpolation_mode=decoder_interpolation_mode,
+            interpolation_mode=decoder_interpolation,
         )
 
         self.segmentation_head = SegmentationHead(