omegaconf.errors.ConfigAttributeError: Key 'checkpoint_activations' not in 'HubertConfig'
See original GitHub issue🐛 Bug
Hi,
When I tried to load a hubert model, I got this error:
Python 3.8.12 (default, Oct 12 2021, 13:49:34)
[GCC 7.5.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> import fairseq
>>> ckpt_path = "/path/to/fairseq/pretrained_models/hubert_xtralarge_ll60k_finetune_ls960_modified.pt"
>>> models, cfg, task = fairseq.checkpoint_utils.load_model_ensemble_and_task([ckpt_path])
2021-12-06 10:55:12 | INFO | fairseq.tasks.hubert_pretraining | current directory is /path/to/fairseq/scripts
2021-12-06 10:55:12 | INFO | fairseq.tasks.hubert_pretraining | HubertPretrainingTask Config {'_name': 'hubert_pretraining', 'data': '/checkpoint/abdo/old_checkpoint02/datasets/librispeech/960h/raw_repeated', 'fine_tuning': False, 'labels': ['ltr'], 'label_dir': None, 'label_rate': -1, 'sample_rate': 16000, 'normalize': True, 'enable_padding': False, 'max_keep_size': None, 'max_sample_size': 300000, 'min_sample_size': None, 'single_target': True, 'random_crop': False, 'pad_audio': False}
2021-12-06 10:55:12 | INFO | fairseq.tasks.hubert_pretraining | current directory is /path/to/fairseq/scripts
2021-12-06 10:55:12 | INFO | fairseq.tasks.hubert_pretraining | HubertPretrainingTask Config {'_name': 'hubert_pretraining', 'data': '/checkpoint/abdo/old_checkpoint02/datasets/librispeech/960h/raw_repeated', 'fine_tuning': False, 'labels': ['lyr9.km500'], 'label_dir': '/path/to/fairseq/scripts', 'label_rate': 50, 'sample_rate': 16000, 'normalize': True, 'enable_padding': False, 'max_keep_size': None, 'max_sample_size': 250000, 'min_sample_size': 32000, 'single_target': False, 'random_crop': True, 'pad_audio': False}
2021-12-06 10:55:12 | INFO | fairseq.models.hubert.hubert | HubertModel Config: {'_name': 'hubert', 'label_rate': 50, 'extractor_mode': layer_norm, 'encoder_layers': 48, 'encoder_embed_dim': 1280, 'encoder_ffn_embed_dim': 5120, 'encoder_attention_heads': 16, 'activation_fn': gelu, 'dropout': 0.0, 'attention_dropout': 0.0, 'activation_dropout': 0.1, 'encoder_layerdrop': 0.1, 'dropout_input': 0.0, 'dropout_features': 0.0, 'final_dim': 1024, 'untie_final_proj': True, 'layer_norm_first': True, 'conv_feature_layers': '[(512,10,5)] + [(512,3,2)] * 4 + [(512,2,2)] * 2', 'conv_bias': False, 'logit_temp': 0.1, 'target_glu': False, 'feature_grad_mult': 0.0, 'mask_length': 10, 'mask_prob': 0.5, 'mask_selection': static, 'mask_other': 0.0, 'no_mask_overlap': False, 'mask_min_space': 1, 'mask_channel_length': 64, 'mask_channel_prob': 0.25, 'mask_channel_selection': static, 'mask_channel_other': 0.0, 'no_mask_channel_overlap': False, 'mask_channel_min_space': 1, 'conv_pos': 128, 'conv_pos_groups': 16, 'latent_temp': [2.0, 0.5, 0.999995], 'skip_masked': False, 'skip_nomask': True}
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/path/to/fairseq/fairseq_latest/fairseq/checkpoint_utils.py", line 462, in load_model_ensemble_and_task
model = task.build_model(cfg.model)
File "/path/to/fairseq/fairseq_latest/fairseq/tasks/fairseq_task.py", line 335, in build_model
model = models.build_model(cfg, self)
File "/path/to/fairseq/fairseq_latest/fairseq/models/__init__.py", line 105, in build_model
return model.build_model(cfg, task)
File "/path/to/fairseq/fairseq_latest/fairseq/models/hubert/hubert_asr.py", line 146, in build_model
w2v_encoder = HubertEncoder(cfg, task.target_dictionary)
File "/path/to/fairseq/fairseq_latest/fairseq/models/hubert/hubert_asr.py", line 272, in __init__
model = task.build_model(w2v_args.model)
File "/path/to/fairseq/fairseq_latest/fairseq/tasks/fairseq_task.py", line 335, in build_model
model = models.build_model(cfg, self)
File "/path/to/fairseq/fairseq_latest/fairseq/models/__init__.py", line 105, in build_model
return model.build_model(cfg, task)
File "/path/to/fairseq/fairseq_latest/fairseq/models/hubert/hubert.py", line 302, in build_model
model = HubertModel(cfg, task.cfg, task.dictionaries)
File "/path/to/fairseq/fairseq_latest/fairseq/models/hubert/hubert.py", line 265, in __init__
self.encoder = TransformerEncoder(cfg)
File "/path/to/fairseq/fairseq_latest/fairseq/models/wav2vec/wav2vec2.py", line 858, in __init__
if args.checkpoint_activations:
File "/path/to/miniconda3/envs/fairseq/lib/python3.8/site-packages/omegaconf/dictconfig.py", line 305, in __getattr__
self._format_and_raise(key=key, value=None, cause=e)
File "/path/to/miniconda3/envs/fairseq/lib/python3.8/site-packages/omegaconf/base.py", line 95, in _format_and_raise
format_and_raise(
File "/path/to/miniconda3/envs/fairseq/lib/python3.8/site-packages/omegaconf/_utils.py", line 629, in format_and_raise
_raise(ex, cause)
File "/path/to/miniconda3/envs/fairseq/lib/python3.8/site-packages/omegaconf/_utils.py", line 610, in _raise
raise ex # set end OC_CAUSE=1 for full backtrace
File "/path/to/miniconda3/envs/fairseq/lib/python3.8/site-packages/omegaconf/dictconfig.py", line 303, in __getattr__
return self._get_impl(key=key, default_value=DEFAULT_VALUE_MARKER)
File "/path/to/miniconda3/envs/fairseq/lib/python3.8/site-packages/omegaconf/dictconfig.py", line 361, in _get_impl
node = self._get_node(key=key)
File "/path/to/miniconda3/envs/fairseq/lib/python3.8/site-packages/omegaconf/dictconfig.py", line 383, in _get_node
self._validate_get(key)
File "/path/to/miniconda3/envs/fairseq/lib/python3.8/site-packages/omegaconf/dictconfig.py", line 135, in _validate_get
self._format_and_raise(
File "/path/to/miniconda3/envs/fairseq/lib/python3.8/site-packages/omegaconf/base.py", line 95, in _format_and_raise
format_and_raise(
File "/path/to/miniconda3/envs/fairseq/lib/python3.8/site-packages/omegaconf/_utils.py", line 694, in format_and_raise
_raise(ex, cause)
File "/path/to/miniconda3/envs/fairseq/lib/python3.8/site-packages/omegaconf/_utils.py", line 610, in _raise
raise ex # set end OC_CAUSE=1 for full backtrace
omegaconf.errors.ConfigAttributeError: Key 'checkpoint_activations' not in 'HubertConfig'
full_key: w2v_args.checkpoint_activations
reference_type=Optional[HubertConfig]
object_type=HubertConfig
To Reproduce
I am following here.
Environment
- fairseq Version (e.g., 1.0 or main): ‘1.0.0a0+0dfd6b6’
- PyTorch Version ‘1.10.0+cu102’
- OS (e.g., Linux): Ubuntu
- How you installed fairseq (
pip
, source): pip install --editable ./ - Python version: 3.8.12
- CUDA/cuDNN version: CUDA Version: 11.1
- GPU models and configuration: Tesla P100
Issue Analytics
- State:
- Created 2 years ago
- Comments:6
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Actually just adding 3 lines to here, line206.
that fixed the problem, thanks a lot @EmreOzkose !