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$ python jukebox/sample.py --model=5b_lyrics --name=sample_5b --levels=3 --sample_length_in_seconds=20 --total_sample_length_in_seconds=180 --sr=44100 --n_samples=6 --hop_fraction=0.5,0.5,0.125 | |
Using cuda True | |
{'name': 'sample_5b', 'levels': 3, 'sample_length_in_seconds': 20, 'total_sample_length_in_seconds': 180, 'sr': 44100, 'n_samples': 6, 'hop_fraction': (0.5, 0.5, 0.125)} | |
Setting sample length to 881920 (i.e. 19.998185941043083 seconds) to be multiple of 128 | |
Downloading from gce | |
Restored from /home/ubuntu/.cache/jukebox-assets/models/5b/vqvae.pth.tar | |
0: Loading vqvae in eval mode | |
Using apex FusedLayerNorm | |
Conditioning on 1 above level(s) | |
Checkpointing convs | |
Checkpointing convs | |
Loading artist IDs from /home/ubuntu/jukebox/jukebox/data/ids/v2_artist_ids.txt | |
Loading artist IDs from /home/ubuntu/jukebox/jukebox/data/ids/v2_genre_ids.txt | |
Level:0, Cond downsample:4, Raw to tokens:8, Sample length:65536 | |
Downloading from gce | |
Restored from /home/ubuntu/.cache/jukebox-assets/models/5b/prior_level_0.pth.tar | |
0: Loading prior in eval mode | |
Conditioning on 1 above level(s) | |
Checkpointing convs | |
Checkpointing convs | |
Loading artist IDs from /home/ubuntu/jukebox/jukebox/data/ids/v2_artist_ids.txt | |
Loading artist IDs from /home/ubuntu/jukebox/jukebox/data/ids/v2_genre_ids.txt | |
Level:1, Cond downsample:4, Raw to tokens:32, Sample length:262144 | |
Downloading from gce | |
Restored from /home/ubuntu/.cache/jukebox-assets/models/5b/prior_level_1.pth.tar | |
0: Loading prior in eval mode | |
Loading artist IDs from /home/ubuntu/jukebox/jukebox/data/ids/v2_artist_ids.txt | |
Loading artist IDs from /home/ubuntu/jukebox/jukebox/data/ids/v2_genre_ids.txt | |
Level:2, Cond downsample:None, Raw to tokens:128, Sample length:1048576 | |
0: Converting to fp16 params | |
Downloading from gce | |
Restored from /home/ubuntu/.cache/jukebox-assets/models/5b_lyrics/prior_level_2.pth.tar | |
0: Loading prior in eval mode | |
Sampling level 2 | |
Sampling 6890 tokens for [0,6890]. Conditioning on 0 tokens | |
Ancestral sampling 3 samples with temp=0.99, top_k=0, top_p=0.0 | |
Traceback (most recent call last): | |
File "jukebox/sample.py", line 237, in <module> | |
fire.Fire(run) | |
File "/home/ubuntu/anaconda3/envs/jukebox/lib/python3.7/site-packages/fire/core.py", line 127, in Fire | |
component_trace = _Fire(component, args, context, name) | |
File "/home/ubuntu/anaconda3/envs/jukebox/lib/python3.7/site-packages/fire/core.py", line 366, in _Fire | |
component, remaining_args) | |
File "/home/ubuntu/anaconda3/envs/jukebox/lib/python3.7/site-packages/fire/core.py", line 542, in _CallCallable | |
result = fn(*varargs, **kwargs) | |
File "jukebox/sample.py", line 234, in run | |
save_samples(model, device, hps, sample_hps) | |
File "jukebox/sample.py", line 215, in save_samples | |
ancestral_sample(labels, sampling_kwargs, priors, hps) | |
File "jukebox/sample.py", line 123, in ancestral_sample | |
zs = _sample(zs, labels, sampling_kwargs, priors, sample_levels, hps) | |
File "jukebox/sample.py", line 101, in _sample | |
zs = sample_level(zs, labels[level], sampling_kwargs[level], level, prior, total_length, hop_length, hps) | |
File "jukebox/sample.py", line 86, in sample_level | |
zs = sample_partial_window(zs, labels, sampling_kwargs, level, prior, total_length, hps) | |
File "jukebox/sample.py", line 27, in sample_partial_window | |
return sample_single_window(zs, labels, sampling_kwargs, level, prior, start, hps) | |
File "jukebox/sample.py", line 68, in sample_single_window | |
z_samples_i = prior.sample(n_samples=z_i.shape[0], z=z_i, z_conds=z_conds_i, y=y_i, **sampling_kwargs) | |
File "/home/ubuntu/jukebox/jukebox/prior/prior.py", line 252, in sample | |
x_cond, y_cond, prime = self.get_cond(z_conds, y) | |
File "/home/ubuntu/jukebox/jukebox/prior/prior.py", line 232, in get_cond | |
y_cond, y_pos = self.y_emb(y) if self.y_cond else (None, None) | |
File "/home/ubuntu/anaconda3/envs/jukebox/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in __call__ | |
result = self.forward(*input, **kwargs) | |
File "/home/ubuntu/jukebox/jukebox/prior/conditioners.py", line 150, in forward | |
pos_emb = self.total_length_emb(total_length) + self.absolute_pos_emb(start, end) + self.relative_pos_emb(start/total_length, end/total_length) | |
File "/home/ubuntu/anaconda3/envs/jukebox/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in __call__ | |
result = self.forward(*input, **kwargs) | |
File "/home/ubuntu/jukebox/jukebox/prior/conditioners.py", line 111, in forward | |
return self.emb(bins) | |
File "/home/ubuntu/anaconda3/envs/jukebox/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in __call__ | |
result = self.forward(*input, **kwargs) | |
File "/home/ubuntu/anaconda3/envs/jukebox/lib/python3.7/site-packages/torch/nn/modules/sparse.py", line 117, in forward | |
self.norm_type, self.scale_grad_by_freq, self.sparse) | |
File "/home/ubuntu/anaconda3/envs/jukebox/lib/python3.7/site-packages/torch/nn/functional.py", line 1506, in embedding | |
return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse) | |
RuntimeError: CUDA out of memory. Tried to allocate 450.00 MiB (GPU 0; 11.17 GiB total capacity; 10.69 GiB already allocated; 31.31 MiB free; 172.81 MiB cached) |
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