RuntimeError: 1D tensors expected, got 2D, 2D tensors

pytorch version: pytorch 1.2.0

I am trying to run the code from Practical PyTorch: Translation with a Sequence to Sequence Network and Attention from: https://github.com/spro/practical-pytorch/blob/master/seq2seq-translation/seq2seq-translation.ipynb. I ran it "out of the box" without any modifications, yet I get the following error:

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-55-588688507d61> in <module>
     23 
     24 for i in range(3):
---> 25     decoder_output, decoder_context, decoder_hidden, decoder_attn = decoder_test(word_inputs[i], decoder_context, decoder_hidden, encoder_outputs)
     26     print(decoder_output.size(), decoder_hidden.size(), decoder_attn.size())
     27     decoder_attns[0, i] = decoder_attn.squeeze(0).cpu().data

~/miniconda3/envs/pytorch/lib/python3.7/site-packages/torch/nn/modules/module.py in __call__(self, *input, **kwargs)
    545             result = self._slow_forward(*input, **kwargs)
    546         else:
--> 547             result = self.forward(*input, **kwargs)
    548         for hook in self._forward_hooks.values():
    549             hook_result = hook(self, input, result)

<ipython-input-54-ed0e3fee0079> in forward(self, word_input, last_context, last_hidden, encoder_outputs)
     30 
     31         # Calculate attention from current RNN state and all encoder outputs; apply to encoder outputs
---> 32         attn_weights = self.attn(rnn_output.squeeze(0), encoder_outputs)
     33         context = attn_weights.bmm(encoder_outputs.transpose(0, 1)) # B x 1 x N
     34 

~/miniconda3/envs/pytorch/lib/python3.7/site-packages/torch/nn/modules/module.py in __call__(self, *input, **kwargs)
    545             result = self._slow_forward(*input, **kwargs)
    546         else:
--> 547             result = self.forward(*input, **kwargs)
    548         for hook in self._forward_hooks.values():
    549             hook_result = hook(self, input, result)

<ipython-input-34-b18c85dc1210> in forward(self, hidden, encoder_outputs)
     22         # Calculate energies for each encoder output
     23         for i in range(seq_len):
---> 24             attn_energies[i] = self.score(hidden, encoder_outputs[i])
     25 
     26         # Normalize energies to weights in range 0 to 1, resize to 1 x 1 x seq_len

<ipython-input-34-b18c85dc1210> in score(self, hidden, encoder_output)
     35         elif self.method == 'general':
     36             energy = self.attn(encoder_output)
---> 37             energy = hidden.dot(energy)
     38             return energy
     39 

RuntimeError: 1D tensors expected, got 2D, 2D tensors at /tmp/pip-req-build-58y_cjjl/aten/src/THC/generic/THCTensorMathBlas.cu:14

The error appears when running the code-block section titled "Testing the models" , from the link above.

spro / practical-pytorch

RuntimeError: 1D tensors expected, got 2D, 2D tensors #140