Traceback (most recent call last):


 "gangpu.py", line 278, in <module>

gan = GANGPU('gan')


 "gangpu.py", line 96, in __init__

parallel_discriminator_model = multi_gpu_model(discriminator_model, gpus=2)


 "/n/home06/koshiba/.conda/envs/Keras7/lib/python3.6/site-packages/keras/utils/multi_gpu_utils.py", line 189, in multi_gpu_model

return Model(model.inputs, merged)


 "/n/home06/koshiba/.conda/envs/Keras7/lib/python3.6/site-packages/keras/legacy/interfaces.py", line 91, in wrapper

return func(*args, **kwargs)


 "/n/home06/koshiba/.conda/envs/Keras7/lib/python3.6/site-packages/keras/engine/topology.py", line 1829, in __init__

'Layer names: ', all_names)
RuntimeError: ('The name "Discriminator" is used 2 times in the model. All layer names should be unique. Layer names: ', ['input_3', 'input_4', 'lambda_3', 'lambda_4', 'lambda_5', 'lambda_6', 'model_3', 'Discriminator', 'Discriminator'])

Traceback (most recent call last):


 "train.py", line 190, in <module>

device=device, ext_len=args.ext_len)


 "/home/agemagician/Downloads/transformer-xl/pytorch/data_utils.py", line 239, in get_iterator

data_iter = LMOrderedIterator(self.train, *args, **kwargs)


 "/home/agemagician/Downloads/transformer-xl/pytorch/data_utils.py", line 29, in __init__

self.data = data.view(bsz, -1).t().contiguous().to(device)
RuntimeError: CUDA out of memory. Tried to allocate 40.00 GiB (GPU 0; 11.75 GiB total capacity; 0 bytes already allocated; 11.08 GiB free; 0 bytes cached)
