Traceback (most recent call last):


 "C:\Python38\lib\site-packages\TikTokApi\tiktok.py", line 48, in getData

return r.json()


 "C:\Python38\lib\site-packages\requests\models.py", line 898, in json

return complexjson.loads(self.text, **kwargs)


 "C:\Python38\lib\json\__init__.py", line 357, in loads

return _default_decoder.decode(s)


 "C:\Python38\lib\json\decoder.py", line 337, in decode

obj, end = self.raw_decode(s, idx=_w(s, 0).end())


 "C:\Python38\lib\json\decoder.py", line 355, in raw_decode

raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)

Traceback (most recent call last):


 "F:/expression/InterFaceGAN-master/edit.py", line 112, in <module>

main()


 "F:/expression/InterFaceGAN-master/edit.py", line 98, in main

outputs = model.easy_synthesize(interpolations_batch)


 "F:\expression\InterFaceGAN-master\models\base_generator.py", line 230, in easy_synthesize

outputs = self.synthesize(latent_codes, **kwargs)


 "F:\expression\InterFaceGAN-master\models\pggan_generator.py", line 117, in synthesize

images = self.model(zs)


 "E:\Users\Raytine\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 477, in __call__

result = self.forward(*input, **kwargs)


 "F:\expression\InterFaceGAN-master\models\pggan_generator_model.py", line 127, in forward

return super().forward(x)


 "E:\Users\Raytine\Anaconda3\lib\site-packages\torch\nn\modules\container.py", line 91, in forward

input = module(input)


 "E:\Users\Raytine\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 477, in __call__

result = self.forward(*input, **kwargs)


 "F:\expression\InterFaceGAN-master\models\pggan_generator_model.py", line 243, in forward

x = self.conv(x)


 "E:\Users\Raytine\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 477, in __call__

result = self.forward(*input, **kwargs)


 "E:\Users\Raytine\Anaconda3\lib\site-packages\torch\nn\modules\conv.py", line 301, in forward

self.padding, self.dilation, self.groups)
RuntimeError: Given groups=1, weight of size [16, 16, 3, 3], expected input[4, 512, 1, 1] to have 16 channels, but got 512 channels instead
