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# Copyright (c) 2023-2024, Zexin He | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# https://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
import torch | |
import torch.nn as nn | |
class CameraEmbedder(nn.Module): | |
""" | |
Embed camera features to a high-dimensional vector. | |
Reference: | |
DiT: https://github.com/facebookresearch/DiT/blob/main/models.py#L27 | |
""" | |
def __init__(self, raw_dim: int, embed_dim: int): | |
super().__init__() | |
self.mlp = nn.Sequential( | |
nn.Linear(raw_dim, embed_dim), | |
nn.SiLU(), | |
nn.Linear(embed_dim, embed_dim), | |
) | |
def forward(self, x): | |
return self.mlp(x) | |