transforms.ColorJitter().get_params(...) does not support float inputs

[sagadre]

🐛 Bug

The docstring for transforms.ColorJitter().get_params(...) states that it accepts float and tuple inputs, just as ColorJitter's __init__(...), however, the current implementation supports tuple inputs only. Unlike the constructor it does not support float inputs.

To Reproduce

Steps to reproduce the behavior:

`from torchvision import transforms as T

t = T.ColorJitter()
t = t.get_params(0.4, 0.4, 0.4, 0.2)`

Expected behavior

the .get_params(...) should take float inputs.

• PyTorch / torchvision Version (e.g., 1.0 / 0.4.0): 1.4.0
• OS (e.g., Linux): Linux
• How you installed PyTorch / torchvision (conda, pip, source): pip
• Build command you used (if compiling from source): N/A
• Python version: 3.8
• CUDA/cuDNN version: 10.1
• GPU models and configuration: GeForce 2080ti
• Any other relevant information: N/A

cc @vfdev-5

[vfdev-5]

@sagadre thanks for reporting !

Yes, this is a bug for 0.4.0 version, but currently ColorJitter's behaviour in the master is such that ColorJitter.get_params() is not used inside __call__/forward and kept for backward compatibility: #2298 (comment). Getting back ColorJitter.get_params is low-priority issue and once it is done, due to torch jit limitation on Union usage, we can not make it work on simple floats and list of floats...

[sagadre]

@vfdev-5 I see. Thanks for the explanation!

My use case is that I want to apply the same transform (color jitter) to two images.

Here is a simple workaround for those interested:

from torchvision import transforms as T

cj = T.ColorJitter(0.4, 0.4, 0.4, 0.2)
t = cj.get_params(cj.brightness, cj.contrast, cj.saturation, cj.hue)

# t is now frozen (no randomness when called) and can be used to transform both images with the same transform.