Autograder [Sun Apr  5 23:05:36 2020]: Received job 11785-s20_hw4p1_4_agadhika@andrew.cmu.edu:444
Autograder [Sun Apr  5 23:05:54 2020]: Success: Autodriver returned normally
Autograder [Sun Apr  5 23:05:54 2020]: Here is the output from the autograder:
---
Autodriver: Job exited with status 0
mkdir -p handin
tar xf handin.tar -C handin
tar xf autograde.tar
AUTOLAB=1 python3 autograde/runner.py --module-path=./handin/
FYour mean NLL for predicting a single word: 5.127223014831543
.
=================================== FAILURES ===================================
_______________________________ test_generation ________________________________

    def test_generation():
        inp = np.load(fixture_path('generation.npy'))
        forward = 10
        n = inp.shape[0]
        t = inp.shape[1]
        pred = np.load(handin_path('generated_logits.npy'))
        assert pred.shape[0] == n
        assert pred.shape[1] == forward
    
        ninp = np.concatenate((inp, pred), axis=1)
        vocab = np.load(fixture_path('vocab.npy'))
        model = Model(vocab.shape[0], args=prediction_args)
        model.load_state_dict(load_from_numpy(read_chunks(fixture_path('model-00000099.tar.npy.{}'))))
        model.eval()
    
        state = model.zero_state(n)
        x = Variable(torch.from_numpy(ninp.T)).long()
>       logits, rnn_hs = model(x, state)

autograde/tests/test_generation.py:229: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/usr/local/lib64/python3.6/site-packages/torch/nn/modules/module.py:477: in __call__
    result = self.forward(*input, **kwargs)
autograde/tests/test_generation.py:183: in forward
    embedded = self.embedding(input)
/usr/local/lib64/python3.6/site-packages/torch/nn/modules/module.py:477: in __call__
    result = self.forward(*input, **kwargs)
autograde/tests/test_generation.py:153: in forward
    return self.embedding._backend.Embedding.apply(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <torch.nn.backends.thnn.THNNFunctionBackend object at 0x7fab98454a58>
name = 'Embedding'

    def __getattr__(self, name):
        fn = self.function_classes.get(name)
        if fn is None:
>           raise NotImplementedError
E           NotImplementedError

/usr/local/lib64/python3.6/site-packages/torch/nn/backends/backend.py:10: NotImplementedError
Run time:  2.693869113922119
{"scores": {"Generation": 0.0, "Prediction": 50.0}}