From 2ae5e9e386657c6ad2171bc4928143cd865c6ecf Mon Sep 17 00:00:00 2001
From: Tamino Huxohl <thuxohl@techfak.uni-bielefeld.de>
Date: Tue, 27 Sep 2022 10:04:49 +0200
Subject: [PATCH] restructuring to separate data processing from torch dataset
implementations
---
mu_map/data/preprocessing.py | 38 ------------------
mu_map/dataset/__init__.py | 0
.../{data/datasets.py => dataset/default.py} | 0
mu_map/{data => dataset}/mock.py | 2 +-
mu_map/dataset/normalization.py | 40 +++++++++++++++++++
.../patch_dataset.py => dataset/patches.py} | 2 +-
6 files changed, 42 insertions(+), 40 deletions(-)
delete mode 100644 mu_map/data/preprocessing.py
create mode 100644 mu_map/dataset/__init__.py
rename mu_map/{data/datasets.py => dataset/default.py} (100%)
rename mu_map/{data => dataset}/mock.py (98%)
create mode 100644 mu_map/dataset/normalization.py
rename mu_map/{data/patch_dataset.py => dataset/patches.py} (98%)
diff --git a/mu_map/data/preprocessing.py b/mu_map/data/preprocessing.py
deleted file mode 100644
index dc57c6f..0000000
--- a/mu_map/data/preprocessing.py
+++ /dev/null
@@ -1,38 +0,0 @@
-import torch
-
-
-def norm_max(tensor: torch.Tensor):
- return (tensor - tensor.min()) / (tensor.max() - tensor.min())
-
-
-class MaxNorm:
- def __call__(self, tensor: torch.Tensor):
- return norm_max(tensor)
-
-
-def norm_mean(tensor: torch.Tensor):
- return tensor / tensor.mean()
-
-
-class MeanNorm:
- def __call__(self, tensor: torch.Tensor):
- return norm_mean(tensor)
-
-
-def norm_gaussian(tensor: torch.Tensor):
- return (tensor - tensor.mean()) / tensor.std()
-
-
-class GaussianNorm:
- def __call__(self, tensor: torch.Tensor):
- return norm_gaussian(tensor)
-
-
-__all__ = [
- norm_max.__name__,
- norm_mean.__name__,
- norm_gaussian.__name__,
- MaxNorm.__name__,
- MeanNorm.__name__,
- GaussianNorm.__name__,
-]
diff --git a/mu_map/dataset/__init__.py b/mu_map/dataset/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/mu_map/data/datasets.py b/mu_map/dataset/default.py
similarity index 100%
rename from mu_map/data/datasets.py
rename to mu_map/dataset/default.py
diff --git a/mu_map/data/mock.py b/mu_map/dataset/mock.py
similarity index 98%
rename from mu_map/data/mock.py
rename to mu_map/dataset/mock.py
index 2bb2b9a..de564b0 100644
--- a/mu_map/data/mock.py
+++ b/mu_map/dataset/mock.py
@@ -1,4 +1,4 @@
-from mu_map.data.datasets import MuMapDataset
+from mu_map.dataset.default import MuMapDataset
class MuMapMockDataset(MuMapDataset):
diff --git a/mu_map/dataset/normalization.py b/mu_map/dataset/normalization.py
new file mode 100644
index 0000000..85ec9af
--- /dev/null
+++ b/mu_map/dataset/normalization.py
@@ -0,0 +1,40 @@
+from torch import Tensor
+
+from mu_map.dataset.transform import Transform
+
+
+def norm_max(tensor: Tensor) -> Tensor:
+ return (tensor - tensor.min()) / (tensor.max() - tensor.min())
+
+
+class MaxNormTransform(Transform):
+ def __call__(self, inputs: Tensor, outputs_expected: Tensor) -> Tuple[Tensor, Tensor]:
+ return norm_max(inputs), outputs_expected
+
+
+def norm_mean(tensor: Tensor):
+ return tensor / tensor.mean()
+
+
+class MeanNormTransform(Transform):
+ def __call__(self, inputs: Tensor, outputs_expected: Tensor) -> Tuple[Tensor, Tensor]:
+ return norm_mean(inputs), outputs_expected
+
+
+def norm_gaussian(tensor: Tensor):
+ return (tensor - tensor.mean()) / tensor.std()
+
+
+class GaussianNormTransform(Transform):
+ def __call__(self, inputs: Tensor, outputs_expected: Tensor) -> Tuple[Tensor, Tensor]:
+ return norm_gaussian(inputs), outputs_expected
+
+
+__all__ = [
+ norm_max.__name__,
+ norm_mean.__name__,
+ norm_gaussian.__name__,
+ MaxNormTransform.__name__,
+ MeanNormTransform.__name__,
+ GaussianNormTransform.__name__,
+]
diff --git a/mu_map/data/patch_dataset.py b/mu_map/dataset/patches.py
similarity index 98%
rename from mu_map/data/patch_dataset.py
rename to mu_map/dataset/patches.py
index 934ce82..df9f2c9 100644
--- a/mu_map/data/patch_dataset.py
+++ b/mu_map/dataset/patches.py
@@ -4,7 +4,7 @@ import random
import numpy as np
import torch
-from mu_map.data.datasets import MuMapDataset
+from mu_map.dataset.default import MuMapDataset
class MuMapPatchDataset(MuMapDataset):
--
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