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# -*- coding: utf-8 -*- | |
# Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (MPG) is | |
# holder of all proprietary rights on this computer program. | |
# You can only use this computer program if you have closed | |
# a license agreement with MPG or you get the right to use the computer | |
# program from someone who is authorized to grant you that right. | |
# Any use of the computer program without a valid license is prohibited and | |
# liable to prosecution. | |
# | |
# Copyright©2020 Max-Planck-Gesellschaft zur Förderung | |
# der Wissenschaften e.V. (MPG). acting on behalf of its Max Planck Institute | |
# for Intelligent Systems. All rights reserved. | |
# | |
# Contact: [email protected] | |
from typing import Optional | |
import torch | |
from torch import Tensor, nn | |
from pathlib import Path | |
import os | |
class Joints2Jfeats(nn.Module): | |
def __init__(self, | |
path: Optional[str] = None, | |
normalization: bool = False, | |
eps: float = 1e-12, | |
**kwargs) -> None: | |
if normalization and path is None: | |
raise TypeError( | |
"You should provide a path if normalization is on.") | |
super().__init__() | |
self.normalization = normalization | |
self.eps = eps | |
# workaround for cluster local/sync | |
if path is not None: | |
# rel_p = path.split('/') | |
# rel_p = rel_p[rel_p.index('deps'):] | |
# rel_p = '/'.join(rel_p) | |
pass | |
if normalization: | |
mean_path = Path(path) / "jfeats_mean.pt" | |
std_path = Path(path) / "jfeats_std.pt" | |
self.register_buffer('mean', torch.load(mean_path)) | |
self.register_buffer('std', torch.load(std_path)) | |
def normalize(self, features: Tensor) -> Tensor: | |
if self.normalization: | |
features = (features - self.mean) / (self.std + self.eps) | |
return features | |
def unnormalize(self, features: Tensor) -> Tensor: | |
if self.normalization: | |
features = features * self.std + self.mean | |
return features | |