Traceback (most recent call last):



 "<ipython-input-8-c4ba89694fd5>", line 10, in <module>

pipeline.fit(X)



 "C:\...\sklearn\pipeline.py", line 250, in fit

self._final_estimator.fit(Xt, y, **fit_params)



 "C:\...\tslearn\clustering.py", line 531, in fit

self._fit_one_init(X_, x_squared_norms, rs)



 "C:\...\tslearn\clustering.py", line 460, in _fit_one_init

self._assign(X)



 "C:\...\tslearn\clustering.py", line 480, in _assign

dists = cdist_soft_dtw(X, self.cluster_centers_, gamma=self.gamma_sdtw)

AttributeError: 'TimeSeriesKMeans' object has no attribute 'gamma_sdtw'

Traceback (most recent call last):


 "train.py", line 451, in <module>

train()
# train normally


 "train.py", line 332, in train

dataloader=testloader)


 "/yolov3/test.py", line 77, in test

_ = model(torch.zeros((1, 3, img_size, img_size), device=device)) if device.type != 'cpu' else None
# run once


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 550, in __call__

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


 "/yolov3/models.py", line 236, in forward

return self.forward_once(x)


 "/yolov3/models.py", line 288, in forward_once

yolo_out.append(module(x, out))


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 550, in __call__

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


 "/yolov3/models.py", line 210, in forward

io[..., :2] = torch.sigmoid(io[..., :2]) + self.grid # xy


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 594, in __getattr__

type(self).__name__, name))
AttributeError: 'YOLOLayer' object has no attribute 'grid'