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- from mmpose.models import KeypointMSELoss
- from mmpose.registry import MODELS
- # Register your loss to the `MODELS`.
- @MODELS.register_module()
- class ExampleLoss(KeypointMSELoss):
- """Implements an example loss.
- Implement the loss just like a normal pytorch module.
- """
- def __init__(self, **kwargs) -> None:
- print('Initializing ExampleLoss...')
- super().__init__(**kwargs)
- def forward(self, output, target, target_weights=None, mask=None):
- """Forward function of loss. The input arguments should match those
- given in `head.loss` function.
- Note:
- - batch_size: B
- - num_keypoints: K
- - heatmaps height: H
- - heatmaps weight: W
- Args:
- output (Tensor): The output heatmaps with shape [B, K, H, W]
- target (Tensor): The target heatmaps with shape [B, K, H, W]
- target_weights (Tensor, optional): The target weights of differet
- keypoints, with shape [B, K] (keypoint-wise) or
- [B, K, H, W] (pixel-wise).
- mask (Tensor, optional): The masks of valid heatmap pixels in
- shape [B, K, H, W] or [B, 1, H, W]. If ``None``, no mask will
- be applied. Defaults to ``None``
- Returns:
- Tensor: The calculated loss.
- """
- return super().forward(output, target, target_weights, mask)
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