# -*- 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: ps-license@tuebingen.mpg.de from typing import Optional import torch from torch import Tensor, nn from pathlib import Path import os # import hydra class Rots2Joints(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) # path = hydra.utils.get_original_cwd() + '/' + rel_p if normalization: mean_path = Path(path) / "mean.pt" std_path = Path(path) / "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