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import torch
import einops
import torchvision
import torch.nn as nn
from typing import List, Tuple
class MultiviewStack(nn.Module):
def __init__(
self,
encoders: List[nn.Module],
normalizations: List[Tuple[List, List]],
output_dim: int,
):
super().__init__()
self.encoders = nn.ModuleList(encoders)
self.normalizations = []
for mean, std in normalizations:
self.normalizations.append(
torchvision.transforms.Normalize(mean=mean, std=std)
)
def forward(self, x):
orig_shape = x.shape # NTVCHW or TVCHW
x = einops.rearrange(x, "... V C H W -> (...) V C H W")
outputs = []
for i, encoder in enumerate(self.encoders):
this_view = x[:, i]
this_view = self.normalizations[i](this_view)
outputs.append(encoder(this_view))
out = torch.stack(outputs, dim=-1)
out = out.reshape(*orig_shape[:-3], -1)
return out
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