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rslearn.models.resize_features

resize_features

The ResizeFeatures module.

ResizeFeatures

Bases: IntermediateComponent

Resize input features to new sizes.

Source code in rslearn/models/resize_features.py 
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class ResizeFeatures(IntermediateComponent):
    """Resize input features to new sizes."""

    def __init__(
        self,
        out_sizes: list[tuple[int, int]],
        mode: str = "bilinear",
    ):
        """Initialize a ResizeFeatures.

        Args:
            out_sizes: the output sizes of the feature maps. There must be one entry
                for each input feature map.
            mode: mode to pass to torch.nn.Upsample, e.g. "bilinear" (default) or
                "nearest".
        """
        super().__init__()
        layers = []
        for size in out_sizes:
            layers.append(
                torch.nn.Upsample(
                    size=size,
                    mode=mode,
                )
            )
        self.layers = torch.nn.ModuleList(layers)

    def forward(self, intermediates: Any, context: ModelContext) -> FeatureMaps:
        """Resize the input feature maps to new sizes.

        Args:
            intermediates: the outputs from the previous component, which must be a FeatureMaps.
            context: the model context.

        Returns:
            resized feature maps
        """
        if not isinstance(intermediates, FeatureMaps):
            raise ValueError("input to ResizeFeatures must be a FeatureMaps")

        feat_maps = intermediates.feature_maps
        resized_feat_maps = [
            self.layers[idx](feat_map) for idx, feat_map in enumerate(feat_maps)
        ]
        return FeatureMaps(resized_feat_maps)

forward 

forward(intermediates: Any, context: ModelContext) -> FeatureMaps

Resize the input feature maps to new sizes.

Parameters:

Name Type Description Default
intermediates Any

the outputs from the previous component, which must be a FeatureMaps.

 required
context ModelContext

the model context.

 required

Returns:

Type Description
FeatureMaps

resized feature maps
Source code in rslearn/models/resize_features.py 
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def forward(self, intermediates: Any, context: ModelContext) -> FeatureMaps:
    """Resize the input feature maps to new sizes.

    Args:
        intermediates: the outputs from the previous component, which must be a FeatureMaps.
        context: the model context.

    Returns:
        resized feature maps
    """
    if not isinstance(intermediates, FeatureMaps):
        raise ValueError("input to ResizeFeatures must be a FeatureMaps")

    feat_maps = intermediates.feature_maps
    resized_feat_maps = [
        self.layers[idx](feat_map) for idx, feat_map in enumerate(feat_maps)
    ]
    return FeatureMaps(resized_feat_maps)