RUN/multi/MultiTalk_s2/test-20240707_000302.log

[2024-07-07 00:03:03,357 INFO test_multi_pred.py line 63 3703560]=>INaffine: False
StepLR: False
adaptive_lr: False
arch: stage2
autoencoder: stage1_vocaset
base_lr: 0.0001
batch_size: 1
batch_size_val: 1
data_root: sample_dataset
dataset: multi
device: cuda
dist_backend: nccl
dist_url: tcp://127.0.0.1:6701
epochs: 100
eval_freq: 5
evaluate: True
face_quan_num: 16
factor: 0.3
feature_dim: 1024
gamma: 0.5
gt_save_folder: demo/gt
hidden_size: 1024
in_dim: 15069
intermediate_size: 1536
log_dir: None
loss: MSE
manual_seed: 131
measure_lve: False
model_path: checkpoints/stage2.pth.tar
momentum: 0.9
motion_weight: 1.0
multiprocessing_distributed: True
n_embed: 256
n_head: 4
neg: 0.2
num_attention_heads: 8
num_hidden_layers: 6
num_layers: 6
patience: 3
period: 25
poly_lr: False
power: 0.9
print_freq: 10
quant_factor: 0
rank: 0
read_audio: True
reg_weight: 1.0
resume: None
save: True
save_folder: demo/output
save_freq: 1
save_path: None
start_epoch: 0
step_size: 100
style_emb_method: nnemb
sync_bn: False
teacher_forcing: True
template_file: templates.pkl
test_batch_size: 1
test_gpu: [0]
test_subjects: Arabic English French German Greek Italian Portuguese Russian Spanish Korean Mandarin Japanese
test_workers: 0
threshold: 0.0001
train_gpu: [0]
train_subjects: Arabic English French German Greek Italian Portuguese Russian Spanish Korean Mandarin Japanese
use_sgd: False
val_subjects: Arabic English French German Greek Italian Portuguese Russian Spanish Korean Mandarin Japanese
vertice_dim: 15069
vertices_path: npy
visualize_mesh: True
vqvae_pretrained_path: checkpoints/stage1.pth.tar
warmup_steps: 1
wav2vec2model_path: facebook/wav2vec2-large-xlsr-53
wav_path: wav
weight: None
weight_decay: 0.002
window_size: 1
workers: 10
world_size: 1
zquant_dim: 64
[2024-07-07 00:03:03,357 INFO test_multi_pred.py line 64 3703560]=>=> creating model ...

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Some weights of the model checkpoint at facebook/wav2vec2-large-xlsr-53 were not used when initializing Wav2Vec2Model: ['quantizer.weight_proj.bias', 'project_hid.bias', 'project_q.bias', 'quantizer.weight_proj.weight', 'project_q.weight', 'quantizer.codevectors', 'project_hid.weight']
- This IS expected if you are initializing Wav2Vec2Model from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing Wav2Vec2Model from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
[2024-07-07 00:04:21,701 INFO test_multi_pred.py line 69 3703560]=>=> loading checkpoint 'checkpoints/stage2.pth.tar'
[2024-07-07 00:04:22,268 INFO test_multi_pred.py line 72 3703560]=>=> loaded checkpoint 'checkpoints/stage2.pth.tar'
Loading data...

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Traceback (most recent call last):
  File "main/test_multi_pred.py", line 144, in <module>
    main()
  File "main/test_multi_pred.py", line 78, in main
    dataset = get_dataloaders(cfg, test_config=True)
  File "/home/rnd/Documents/Ameer/Dream/MultiTalk/dataset/data_loader_multi.py", line 142, in get_dataloaders
    train_data, valid_data, test_data, subjects_dict = read_data(args, test_config)
  File "/home/rnd/Documents/Ameer/Dream/MultiTalk/dataset/data_loader_multi.py", line 66, in read_data
    processor = Wav2Vec2Processor.from_pretrained(args.wav2vec2model_path)
  File "/home/rnd/miniconda3/envs/multitalk/lib/python3.8/site-packages/transformers/models/wav2vec2/processing_wav2vec2.py", line 105, in from_pretrained
    tokenizer = Wav2Vec2CTCTokenizer.from_pretrained(pretrained_model_name_or_path, **kwargs)
  File "/home/rnd/miniconda3/envs/multitalk/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 1708, in from_pretrained
    raise EnvironmentError(msg)
OSError: Can't load tokenizer for 'facebook/wav2vec2-large-xlsr-53'. Make sure that:

- 'facebook/wav2vec2-large-xlsr-53' is a correct model identifier listed on 'https://huggingface.co/models'

- or 'facebook/wav2vec2-large-xlsr-53' is the correct path to a directory containing relevant tokenizer files