From 291180a01880a55520186d470ca5a8a2a94a2cf5 Mon Sep 17 00:00:00 2001
From: Tamino Huxohl <thuxohl@techfak.uni-bielefeld.de>
Date: Wed, 21 Dec 2022 14:26:51 +0100
Subject: [PATCH] remove outdated scale transform and refactor to support
variable number of tensors
---
mu_map/dataset/transform.py | 39 +++++++++----------------------------
1 file changed, 9 insertions(+), 30 deletions(-)
diff --git a/mu_map/dataset/transform.py b/mu_map/dataset/transform.py
index 9e34995..e2fad43 100644
--- a/mu_map/dataset/transform.py
+++ b/mu_map/dataset/transform.py
@@ -12,11 +12,11 @@ class Transform:
used for normalization and data augmentation.
"""
- def __call__(self, inputs: Tensor, targets: Tensor) -> Tuple[Tensor, Tensor]:
+ def __call__(self, *tensors: Tensor) -> Tuple[Tensor, ...]:
"""
Apply the transformer to a pair of inputs and expected outputs in a dataset.
"""
- return inputs, targets
+ return tensors
class SequenceTransform(Transform):
@@ -27,33 +27,12 @@ class SequenceTransform(Transform):
def __init__(self, transforms: List[Transform]):
self.transforms = transforms
- def __call__(self, inputs: Tensor, targets: Tensor) -> Tuple[Tensor, Tensor]:
+ def __call__(self, *tensors: Tensor) -> Tuple[Tensor, ...]:
for transforms in self.transforms:
- inputs, targets = transforms(inputs, targets)
- return inputs, targets
+ tensors = transforms(*tensors)
+ return tensors
-class ScaleTransform(Transform):
- """
- A transformer that scales the inputs and outputs by pre-defined factors.
- """
-
- def __init__(self, scale_inputs: float = 1.0, scale_outputs: float = 1.0):
- """
- Initialize a scale transformer.
-
- :param scale_inputs: the scale multiplied to the inputs
- :param scale_outputs: the scale multiplied to the outputs
- """
- self.scale_inputs = scale_inputs
- self.scale_outputs = scale_outputs
-
- def __call__(self, inputs: Tensor, targets: Tensor) -> Tuple[Tensor, Tensor]:
- """
- Scale the inputs and the outputs by the factors defined in the constructor.
- """
- return inputs * self.scale_inputs, targets * self.scale_outputs
-
class PaddingTransform(Transform):
"""
@@ -68,12 +47,12 @@ class PaddingTransform(Transform):
self.dim = dim
self.size = size
- def __call__(self, inputs: Tensor, targets: Tensor) -> Tuple[Tensor, Tensor]:
+ def __call__(self, *tensors: Tensor) -> Tuple[Tensor, ...]:
"""
Pad inputs and targets so that dimension self.dim has at
least a size of self.size.
"""
- return self.pad(inputs), self.pad(targets)
+ return tuple(map(lambda tensor: self.pad(tensor), tensors))
def pad(self, inputs: Tensor):
"""
@@ -104,12 +83,12 @@ class CroppingTransform(Transform):
self.dim = dim
self.size = size
- def __call__(self, inputs: Tensor, targets: Tensor) -> Tuple[Tensor, Tensor]:
+ def __call__(self, *tensors: Tensor) -> Tuple[Tensor, ...]:
"""
Crop inputs and targets so that dimension self.dim has at
most a size of self.size.
"""
- return self.crop(inputs), self.crop(targets)
+ return tuple(map(lambda tensor: self.crop(tensor), tensors))
def crop(self, inputs: Tensor):
"""
--
GitLab