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Running on Zero
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f737f60 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Generic, Literal, TypeVar
from jaxtyping import Float
from torch import Tensor, nn
from ..types import Gaussians
DepthRenderingMode = Literal[
"depth",
"log",
"disparity",
"relative_disparity",
]
@dataclass
class DecoderOutput:
color: Float[Tensor, "batch view 3 height width"]
depth: Float[Tensor, "batch view height width"] | None
alpha: Float[Tensor, "batch view height width"] | None
lod_rendering: dict | None
T = TypeVar("T")
class Decoder(nn.Module, ABC, Generic[T]):
cfg: T
def __init__(self, cfg: T) -> None:
super().__init__()
self.cfg = cfg
@abstractmethod
def forward(
self,
gaussians: Gaussians,
extrinsics: Float[Tensor, "batch view 4 4"],
intrinsics: Float[Tensor, "batch view 3 3"],
near: Float[Tensor, "batch view"],
far: Float[Tensor, "batch view"],
image_shape: tuple[int, int],
depth_mode: DepthRenderingMode | None = None,
) -> DecoderOutput:
pass
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