Traceback (most recent call last):


 "examples/seq2seq/run_summarization.py", line 595, in <module>

main()


 "examples/seq2seq/run_summarization.py", line 533, in main

train_result = trainer.train(resume_from_checkpoint=checkpoint)


 "/opt/anaconda3/envs/tensorflow2/lib/python3.6/site-packages/transformers/trainer.py", line 1082, in train

tr_loss += self.training_step(model, inputs)


 "/opt/anaconda3/envs/tensorflow2/lib/python3.6/site-packages/transformers/trainer.py", line 1472, in training_step

loss = self.compute_loss(model, inputs)


 "/opt/anaconda3/envs/tensorflow2/lib/python3.6/site-packages/transformers/trainer.py", line 1511, in compute_loss

loss = self.label_smoother(outputs, labels)


 "/opt/anaconda3/envs/tensorflow2/lib/python3.6/site-packages/transformers/trainer_pt_utils.py", line 439, in __call__

smoothed_loss.masked_fill_(padding_mask, 0.0)
RuntimeError: The expanded size of the tensor (128) must match the existing size (64) at non-singleton dimension 1.
Target sizes: [4, 128, 1].
Tensor sizes: [4, 64, 1]

Traceback (most recent call last):


 "train.py", line 266, in <module>

var=opt.var,


 "train.py", line 95, in train

load_weights(model, def_weight_file)


 "E:\ObjectDetectionCode\Pytorch-yolov3-new\PyTorch-yolov3-master2\yolov3-tiny-master\models.py", line 384, in load_weights

conv_b = torch.from_numpy(weights[ptr:ptr + num_b]).view_as(conv_layer.bias)
RuntimeError: shape '[30]' is invalid for input of size 0
