from abc import ABCMeta
from abc import abstractmethod
from abc import abstractproperty
import sys
sys.path.append("/home/sverma/second.pytorch/second/core/")
sys.path.append("/home/sverma/second.pytorch/second/pytorch/core/")
from box_coders import GroundBox3dCoder, BevBoxCoder
# from second.pytorch.core import box_torch_ops
import box_torch_ops
import torch

class GroundBox3dCoderTorch(GroundBox3dCoder):
    def encode_torch(self, boxes, anchors):
        return box_torch_ops.second_box_encode(boxes, anchors, self.vec_encode, self.linear_dim)

    def decode_torch(self, boxes, anchors):
        return box_torch_ops.second_box_decode(boxes, anchors, self.vec_encode, self.linear_dim)



class BevBoxCoderTorch(BevBoxCoder):
    def encode_torch(self, boxes, anchors):
        anchors = anchors[..., [0, 1, 3, 4, 6]]
        boxes = boxes[..., [0, 1, 3, 4, 6]]
        return box_torch_ops.bev_box_encode(boxes, anchors, self.vec_encode, self.linear_dim)

    def decode_torch(self, encodings, anchors):
        anchors = anchors[..., [0, 1, 3, 4, 6]]
        ret = box_torch_ops.bev_box_decode(encodings, anchors, self.vec_encode, self.linear_dim)
        z_fixed = torch.full([*ret.shape[:-1], 1], self.z_fixed, dtype=ret.dtype, device=ret.device)
        h_fixed = torch.full([*ret.shape[:-1], 1], self.h_fixed, dtype=ret.dtype, device=ret.device)
        return torch.cat([ret[..., :2], z_fixed, ret[..., 2:4], h_fixed, ret[..., 4:]], dim=-1)


