| import torch |
| import torch.nn as nn |
| import torch.nn.functional as F |
|
|
| def get_encoder(encoding, input_dim=3, |
| multires=6, |
| degree=4, |
| num_levels=16, level_dim=2, base_resolution=16, log2_hashmap_size=19, desired_resolution=2048, align_corners=False, |
| **kwargs): |
|
|
| if encoding == 'None': |
| return lambda x, **kwargs: x, input_dim |
| |
| elif encoding == 'frequency': |
| from freqencoder import FreqEncoder |
| encoder = FreqEncoder(input_dim=input_dim, degree=multires) |
|
|
| elif encoding == 'sphere_harmonics': |
| from shencoder import SHEncoder |
| encoder = SHEncoder(input_dim=input_dim, degree=degree) |
|
|
| elif encoding == 'hashgrid': |
| from gridencoder import GridEncoder |
| encoder = GridEncoder(input_dim=input_dim, num_levels=num_levels, level_dim=level_dim, base_resolution=base_resolution, log2_hashmap_size=log2_hashmap_size, desired_resolution=desired_resolution, gridtype='hash', align_corners=align_corners) |
| |
| elif encoding == 'tiledgrid': |
| from gridencoder import GridEncoder |
| encoder = GridEncoder(input_dim=input_dim, num_levels=num_levels, level_dim=level_dim, base_resolution=base_resolution, log2_hashmap_size=log2_hashmap_size, desired_resolution=desired_resolution, gridtype='tiled', align_corners=align_corners) |
|
|
| else: |
| raise NotImplementedError('Unknown encoding mode, choose from [None, frequency, sphere_harmonics, hashgrid, tiledgrid]') |
|
|
| return encoder, encoder.output_dim |
