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configuration_dpt.py

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+"""TIPSv2 DPT head configuration."""
+
+from transformers import PretrainedConfig
+
+
+class TIPSv2DPTConfig(PretrainedConfig):
+    """Configuration for TIPSv2 DPT dense prediction heads."""
+
+    model_type = "tipsv2_dpt"
+
+    def __init__(
+        self,
+        backbone_repo="google/tipsv2-l14",
+        embed_dim=1024,
+        channels=256,
+        post_process_channels=(128, 256, 512, 1024),
+        block_indices=(5, 11, 17, 23),
+        readout_type="project",
+        num_depth_bins=256,
+        min_depth=1e-3,
+        max_depth=10.0,
+        num_seg_classes=150,
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.backbone_repo = backbone_repo
+        self.embed_dim = embed_dim
+        self.channels = channels
+        self.post_process_channels = list(post_process_channels)
+        self.block_indices = list(block_indices)
+        self.readout_type = readout_type
+        self.num_depth_bins = num_depth_bins
+        self.min_depth = min_depth
+        self.max_depth = max_depth
+        self.num_seg_classes = num_seg_classes