[mschweig]

Building the SAM 3 image model with build_sam3_image_model(device="cpu") and running inference on CPU-only machines previously failed because PositionEmbeddingSine and TransformerDecoder hardcoded device="cuda" when precomputing their coordinate and positional encoding caches during initialization, and SequenceGeometryEncoder._encode_boxes unconditionally called .pin_memory() even when input tensors were on CPU.

This change selects "cuda" if torch.cuda.is_available() else "cpu" when precomputing the positional and coordinate caches, ensures cached tensors are moved to the input tensor's device during the forward pass (preventing device mismatches when device="cpu" is used on a CUDA-capable host), and only calls .pin_memory() in _encode_boxes when the box tensor is on CUDA.

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