Traceback (most recent call last):



 "<ipython-input-1-88b9df752e72>", line 1, in <module>

runfile('/home/user/Desktop/dl-dev python/gp_examples/test.py', wdir='/home/user/Desktop/dl-dev python/gp_examples')



 "/home/user/anaconda3/envs/dkl/lib/python3.6/site-packages/spyder_kernels/customize/spydercustomize.py", line 827, in runfile

execfile(filename, namespace)



 "/home/user/anaconda3/envs/dkl/lib/python3.6/site-packages/spyder_kernels/customize/spydercustomize.py", line 110, in execfile

exec(compile(f.read(), filename, 'exec'), namespace)



 "/home/user/Desktop/dl-dev python/gp_examples/test.py", line 136, in <module>

preds = model(test_x)



 "/home/user/anaconda3/envs/dkl/lib/python3.6/site-packages/gpytorch/models/exact_gp.py", line 294, in __call__

likelihood=self.likelihood,



 "/home/user/anaconda3/envs/dkl/lib/python3.6/site-packages/gpytorch/models/exact_prediction_strategies.py", line 36, in prediction_strategy

return cls(train_inputs, train_prior_dist, train_labels, likelihood)



 "/home/user/anaconda3/envs/dkl/lib/python3.6/site-packages/gpytorch/kernels/grid_interpolation_kernel.py", line 205, in prediction_strategy

return InterpolatedPredictionStrategy(train_inputs, train_prior_dist, train_labels, likelihood)



 "/home/user/anaconda3/envs/dkl/lib/python3.6/site-packages/gpytorch/models/exact_prediction_strategies.py", line 380, in __init__

super().__init__(train_inputs, train_prior_dist, train_labels, likelihood)



 "/home/user/anaconda3/envs/dkl/lib/python3.6/site-packages/gpytorch/models/exact_prediction_strategies.py", line 50, in __init__

mvn = self.likelihood(train_prior_dist, train_inputs)



 "/home/user/anaconda3/envs/dkl/lib/python3.6/site-packages/gpytorch/likelihoods/likelihood.py", line 313, in __call__

return self.marginal(input, *args, **kwargs)



 "/home/user/anaconda3/envs/dkl/lib/python3.6/site-packages/gpytorch/likelihoods/gaussian_likelihood.py", line 76, in marginal

full_covar = covar + noise_covar



 "/home/user/anaconda3/envs/dkl/lib/python3.6/site-packages/gpytorch/lazy/lazy_tensor.py", line 1626, in __add__

return AddedDiagLazyTensor(self, other)



 "/home/user/anaconda3/envs/dkl/lib/python3.6/site-packages/gpytorch/lazy/added_diag_lazy_tensor.py", line 27, in __init__

broadcasting._mul_broadcast_shape(lazy_tensors[0].shape, lazy_tensors[1].shape)



 "/home/user/anaconda3/envs/dkl/lib/python3.6/site-packages/gpytorch/utils/broadcasting.py", line 20, in _mul_broadcast_shape

raise RuntimeError("Shapes are not broadcastable for mul operation")

RuntimeError: Shapes are not broadcastable for mul operatio

Traceback (most recent call last):


 "/home/shuxiaobo/anaconda3/bin/fairseq-train", line 11, in <module>

load_entry_point('fairseq', 'console_scripts', 'fairseq-train')()


 "/data/fairseq/fairseq_cli/train.py", line 322, in cli_main

main(args)


 "/data/fairseq/fairseq_cli/train.py", line 81, in main

train(args, trainer, task, epoch_itr)


 "/data/fairseq/fairseq_cli/train.py", line 122, in train

log_output = trainer.train_step(samples)


 "/data/fairseq/fairseq/trainer.py", line 324, in train_step

raise e


 "/data/fairseq/fairseq/trainer.py", line 294, in train_step

ignore_grad


 "/data/fairseq/fairseq/tasks/fairseq_task.py", line 231, in train_step

loss, sample_size, logging_output = criterion(model, sample)


 "/home/shuxiaobo/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in __call__

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


 "/data/fairseq/fairseq/criterions/sentence_ranking.py", line 49, in forward

classification_head_name='sentence_classification_head',


 "/home/shuxiaobo/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in __call__

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


 "/data/fairseq/fairseq/models/roberta/model.py", line 99, in forward

x, extra = self.decoder(src_tokens, features_only, return_all_hiddens, **kwargs)


 "/home/shuxiaobo/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in __call__

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


 "/data/fairseq/fairseq/models/roberta/model.py", line 284, in forward

x, extra = self.extract_features(src_tokens, return_all_hiddens)


 "/data/fairseq/fairseq/models/roberta/model.py", line 291, in extract_features

src_tokens, last_state_only=not return_all_hiddens,


 "/home/shuxiaobo/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in __call__

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


 "/data/fairseq/fairseq/modules/transformer_sentence_encoder.py", line 182, in forward

x = self.embed_tokens(tokens)


 "/home/shuxiaobo/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in __call__

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


 "/home/shuxiaobo/anaconda3/lib/python3.7/site-packages/torch/nn/modules/sparse.py", line 114, in forward

self.norm_type, self.scale_grad_by_freq, self.sparse)


 "/home/shuxiaobo/anaconda3/lib/python3.7/site-packages/torch/nn/functional.py", line 1467, in embedding

return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
RuntimeError: _th_index_select not supported on CPUType for Half
