57 lines
2.0 KiB
Python
57 lines
2.0 KiB
Python
# -*- coding: utf-8 -*-
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# Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (MPG) is
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# holder of all proprietary rights on this computer program.
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# You can only use this computer program if you have closed
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# a license agreement with MPG or you get the right to use the computer
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# program from someone who is authorized to grant you that right.
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# Any use of the computer program without a valid license is prohibited and
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# liable to prosecution.
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#
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# Copyright©2020 Max-Planck-Gesellschaft zur Förderung
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# der Wissenschaften e.V. (MPG). acting on behalf of its Max Planck Institute
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# for Intelligent Systems. All rights reserved.
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#
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# Contact: ps-license@tuebingen.mpg.de
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from typing import Optional
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import torch
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from torch import Tensor, nn
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from pathlib import Path
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import os
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# import hydra
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class Rots2Joints(nn.Module):
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def __init__(self, path: Optional[str] = None,
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normalization: bool = False,
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eps: float = 1e-12,
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**kwargs) -> None:
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if normalization and path is None:
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raise TypeError("You should provide a path if normalization is on.")
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super().__init__()
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self.normalization = normalization
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self.eps = eps
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# workaround for cluster local/sync
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if path is not None:
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rel_p = path.split('/')
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rel_p = rel_p[rel_p.index('deps'):]
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rel_p = '/'.join(rel_p)
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# path = hydra.utils.get_original_cwd() + '/' + rel_p
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if normalization:
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mean_path = Path(path) / "mean.pt"
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std_path = Path(path) / "std.pt"
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self.register_buffer('mean', torch.load(mean_path))
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self.register_buffer('std', torch.load(std_path))
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def normalize(self, features: Tensor) -> Tensor:
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if self.normalization:
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features = (features - self.mean)/(self.std + self.eps)
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return features
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def unnormalize(self, features: Tensor) -> Tensor:
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if self.normalization:
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features = features * self.std + self.mean
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return features
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