aconda3/envs/nova-cpu-bedge/lib/python3.5/site-packages/pyro_ppl-0.1.2-py3.5.egg/pyro/poutine/trace.py:17: UserWarning: Encountered NAN log_pdf at site 'z_89'
  warnings.warn("Encountered NAN log_pdf at site '{}'".format(name))
/data/sls/u/sameerk/anaconda3/envs/nova-cpu-bedge/lib/python3.5/site-packages/pyro_ppl-0.1.2-py3.5.egg/pyro/poutine/trace.py:17: UserWarning: Encountered NAN log_pdf at site 'z_90'
  warnings.warn("Encountered NAN log_pdf at site '{}'".format(name))
/data/sls/u/sameerk/anaconda3/envs/nova-cpu-bedge/lib/python3.5/site-packages/pyro_ppl-0.1.2-py3.5.egg/pyro/poutine/trace.py:17: UserWarning: Encountered NAN log_pdf at site 'z_97'
  warnings.warn("Encountered NAN log_pdf at site '{}'".format(name))
/data/sls/u/sameerk/anaconda3/envs/nova-cpu-bedge/lib/python3.5/site-packages/pyro_ppl-0.1.2-py3.5.egg/pyro/poutine/trace.py:17: UserWarning: Encountered NAN log_pdf at site 'z_99'
  warnings.warn("Encountered NAN log_pdf at site '{}'".format(name))
/data/sls/u/sameerk/anaconda3/envs/nova-cpu-bedge/lib/python3.5/site-packages/pyro_ppl-0.1.2-py3.5.egg/pyro/poutine/trace.py:17: UserWarning: Encountered NAN log_pdf at site 'z_91'
  warnings.warn("Encountered NAN log_pdf at site '{}'".format(name))
/data/sls/u/sameerk/anacond......

[training epoch 0001]  nan 				(dt = 8.369 sec)
[training epoch 0002]  nan 				(dt = 8.041 sec)
[training epoch 0003]  nan 				(dt = 8.240 sec)
[training epoch 0004]  nan 				(dt = 8.217 sec)
[training epoch 0005]  nan 				(dt = 8.588 sec)
[training epoch 0006]  nan 				(dt = 8.512 sec)
[training epoch 0007]  nan 				(dt = 8.644 sec)
[training epoch 0008]  nan 				(dt = 8.434 sec)
[training epoch 0009]  nan 				(dt = 9.041 sec)
[training epoch 0010]  nan 				(dt = 8.911 sec)

Namespace(annealing_epochs=1000, beta1=0.96, beta2=0.999, checkpoint_freq=0, clip_norm=20.0, cuda=False, iaf_dim=100, learning_rate=0.0004, load_model='', load_opt='', log='dmm.log', lr_decay=0.99996, mini_batch_size=20, minimum_annealing_factor=0.1, num_epochs=5000, num_iafs=0, rnn_dropout_rate=0.1, save_model='', save_opt='', weight_decay=0.6)
N_train_data: 229     avg. training seq. length: 60.29    N_mini_batches: 12
[training epoch 0000]  61.9873 				(dt = 9.196 sec)
[training epoch 0001]  51.8227 				(dt = 8.735 sec)
[training epoch 0002]  25.2403 				(dt = 9.289 sec)
[training epoch 0003]  16.1608 				(dt = 8.802 sec)
[training epoch 0004]  14.1899 				(dt = 9.282 sec)

Traceback (most recent call last):
  File "dmm.py", line 430, in <module>
    main(args)
  File "dmm.py", line 390, in main
    epoch_nll += process_minibatch(epoch, which_mini_batch, shuffled_indices)
  File "dmm.py", line 350, in process_minibatch
    mini_batch_seq_lengths, annealing_factor)
  File "/data/sls/u/sameerk/anaconda3/envs/nova-cpu-bedge/lib/python3.5/site-packages/pyro_ppl-0.1.2-py3.5.egg/pyro/infer/svi.py", line 97, in step
    loss = self.loss_and_grads(self.model, self.guide, *args, **kwargs)
  File "/data/sls/u/sameerk/anaconda3/envs/nova-cpu-bedge/lib/python3.5/site-packages/pyro_ppl-0.1.2-py3.5.egg/pyro/infer/trace_elbo.py", line 133, in loss_and_grads
    for weight, model_trace, guide_trace, log_r in self._get_traces(model, guide, *args, **kwargs):
  File "/data/sls/u/sameerk/anaconda3/envs/nova-cpu-bedge/lib/python3.5/site-packages/pyro_ppl-0.1.2-py3.5.egg/pyro/infer/trace_elbo.py", line 74, in _get_traces
    guide_trace = poutine.trace(guide).get_trace(*args, **kwargs)
  File "/data/sls/u/sameerk/anaconda3/envs/nova-cpu-bedge/lib/python3.5/site-packages/pyro_ppl-0.1.2-py3.5.egg/pyro/poutine/trace_poutine.py", line 250, in get_trace
    self(*args, **kwargs)
  File "/data/sls/u/sameerk/anaconda3/envs/nova-cpu-bedge/lib/python3.5/site-packages/pyro_ppl-0.1.2-py3.5.egg/pyro/poutine/trace_poutine.py", line 238, in __call__
    ret = super(TracePoutine, self).__call__(*args, **kwargs)
  File "/data/sls/u/sameerk/anaconda3/envs/nova-cpu-bedge/lib/python3.5/site-packages/pyro_ppl-0.1.2-py3.5.egg/pyro/poutine/poutine.py", line 147, in __call__
    return self.fn(*args, **kwargs)
  File "dmm.py", line 226, in guide
    rnn_output = poly.pad_and_reverse(rnn_output, mini_batch_seq_lengths)
  File "/data/sls/u/sameerk/repos/pyro/examples/dmm/polyphonic_data_loader.py", line 88, in pad_and_reverse
    reversed_output = reverse_sequences_torch(rnn_output, seq_lengths)
  File "/data/sls/u/sameerk/repos/pyro/examples/dmm/polyphonic_data_loader.py", line 78, in reverse_sequences_torch
    else Variable(torch.LongTensor(time_slice))
RuntimeError: tried to construct a tensor from a int sequence, but found an item of type numpy.int64 at index (0)