[bug] trainer got unexpected keyword argument 'truncated_bptt_steps'
mglowacki100 opened this issue · 4 comments
mglowacki100 commented
🐛 Bug
To Reproduce
- Environment: google colab. I've also get the same error on ubuntu 18.
- !pip install lightning-transformers and restart as requested by google colab
- !pl-transformers-train task=nlp/summarization dataset=nlp/summarization/cnn_dailymail backbone.pretrained_model_name_or_path=t5-base
- I've got error:
TypeError: Error instantiating 'pytorch_lightning.trainer.trainer.Trainer' : __init__() got an unexpected keyword argument 'truncated_bptt_steps'
also there is a warning from hydra. - I suspect that there is some mismatch in libraries versions (e.g. lightning and hydra need to be downgraded or lightning-transformer updated).
Full traceback:
/usr/local/lib/python3.7/dist-packages/hydra/_internal/defaults_list.py:251: UserWarning: In 'config': Defaults list is missing `_self_`. See https://hydra.cc/docs/upgrades/1.0_to_1.1/default_composition_order for more information
warnings.warn(msg, UserWarning)
dataset:
_target_: lightning_transformers.task.nlp.summarization.CNNDailyMailSummarizationDataModule
cfg:
batch_size: ${training.batch_size}
num_workers: ${training.num_workers}
dataset_name: cnn_dailymail
dataset_config_name: 3.0.0
train_file: null
validation_file: null
test_file: null
train_val_split: null
max_samples: null
cache_dir: null
padding: max_length
truncation: only_first
preprocessing_num_workers: 1
load_from_cache_file: true
max_length: 128
limit_train_samples: null
limit_val_samples: null
limit_test_samples: null
max_source_length: 1024
max_target_length: 128
task:
_recursive_: false
_target_: lightning_transformers.task.nlp.summarization.SummarizationTransformer
optimizer: ${optimizer}
scheduler: ${scheduler}
backbone: ${backbone}
downstream_model_type: transformers.AutoModelForSeq2SeqLM
cfg:
use_stemmer: true
rouge_newline_sep: true
val_target_max_length: 142
num_beams: null
compute_generate_metrics: true
tokenizer:
_target_: transformers.AutoTokenizer.from_pretrained
pretrained_model_name_or_path: ${backbone.pretrained_model_name_or_path}
use_fast: true
backbone:
pretrained_model_name_or_path: t5-base
optimizer:
_target_: torch.optim.AdamW
lr: ${training.lr}
weight_decay: 0.001
scheduler:
_target_: transformers.get_linear_schedule_with_warmup
num_training_steps: -1
num_warmup_steps: 0.1
training:
run_test_after_fit: true
lr: 5.0e-05
output_dir: .
batch_size: 16
num_workers: 16
trainer:
_target_: pytorch_lightning.Trainer
logger: true
checkpoint_callback: true
callbacks: null
default_root_dir: null
gradient_clip_val: 0.0
process_position: 0
num_nodes: 1
num_processes: 1
gpus: null
auto_select_gpus: false
tpu_cores: null
log_gpu_memory: null
progress_bar_refresh_rate: 1
overfit_batches: 0.0
track_grad_norm: -1
check_val_every_n_epoch: 1
fast_dev_run: false
accumulate_grad_batches: 1
max_epochs: 1
min_epochs: 1
max_steps: null
min_steps: null
limit_train_batches: 1.0
limit_val_batches: 1.0
limit_test_batches: 1.0
val_check_interval: 1.0
flush_logs_every_n_steps: 100
log_every_n_steps: 50
accelerator: null
sync_batchnorm: false
precision: 32
weights_summary: top
weights_save_path: null
num_sanity_val_steps: 2
truncated_bptt_steps: null
resume_from_checkpoint: null
profiler: null
benchmark: false
deterministic: false
reload_dataloaders_every_epoch: false
auto_lr_find: false
replace_sampler_ddp: true
terminate_on_nan: false
auto_scale_batch_size: false
prepare_data_per_node: true
plugins: null
amp_backend: native
amp_level: O2
move_metrics_to_cpu: false
experiment_name: ${now:%Y-%m-%d}_${now:%H-%M-%S}
log: false
ignore_warnings: true
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Dataset cnn_dailymail downloaded and prepared to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/3cb851bf7cf5826e45d49db2863f627cba583cbc32342df7349dfe6c38060234. Subsequent calls will reuse this data.
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Error executing job with overrides: ['task=nlp/summarization', 'dataset=nlp/summarization/cnn_dailymail', 'backbone.pretrained_model_name_or_path=t5-base']
Traceback (most recent call last):
File "/usr/local/lib/python3.7/dist-packages/hydra/_internal/instantiate/_instantiate2.py", line 62, in _call_target
return _target_(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/connectors/env_vars_connector.py", line 38, in insert_env_defaults
return fn(self, **kwargs)
TypeError: __init__() got an unexpected keyword argument 'truncated_bptt_steps'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.7/dist-packages/lightning_transformers/cli/train.py", line 84, in hydra_entry
main(cfg)
File "/usr/local/lib/python3.7/dist-packages/lightning_transformers/cli/train.py", line 78, in main
logger=logger,
File "/usr/local/lib/python3.7/dist-packages/lightning_transformers/cli/train.py", line 58, in run
logger=logger,
File "/usr/local/lib/python3.7/dist-packages/lightning_transformers/core/instantiator.py", line 111, in trainer
return self.instantiate(cfg, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/lightning_transformers/core/instantiator.py", line 114, in instantiate
return hydra.utils.instantiate(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/hydra/_internal/instantiate/_instantiate2.py", line 180, in instantiate
return instantiate_node(config, *args, recursive=_recursive_, convert=_convert_)
File "/usr/local/lib/python3.7/dist-packages/hydra/_internal/instantiate/_instantiate2.py", line 249, in instantiate_node
return _call_target(_target_, *args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/hydra/_internal/instantiate/_instantiate2.py", line 66, in _call_target
).with_traceback(sys.exc_info()[2])
File "/usr/local/lib/python3.7/dist-packages/hydra/_internal/instantiate/_instantiate2.py", line 62, in _call_target
return _target_(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/connectors/env_vars_connector.py", line 38, in insert_env_defaults
return fn(self, **kwargs)
TypeError: Error instantiating 'pytorch_lightning.trainer.trainer.Trainer' : __init__() got an unexpected keyword argument 'truncated_bptt_steps'
Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
Google colab install traceback:
Collecting lightning-transformers
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Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from lightning-transformers) (1.19.5)
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Requirement already satisfied: torch>=1.6 in /usr/local/lib/python3.7/dist-packages (from lightning-transformers) (1.10.0+cu111)
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Requirement already satisfied: importlib-resources in /usr/local/lib/python3.7/dist-packages (from hydra-core>=1.1.0.dev4->lightning-transformers) (5.4.0)
Collecting PyYAML>=5.1.0
Downloading PyYAML-6.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (596 kB)
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WARNING: The following packages were previously imported in this runtime:
[pydevd_plugins]
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mglowacki100 commented
Downgrading pytorch-ligthning seems to fix an issue:
!pip install pytorch-lightning==1.4
or installing directly from git (this one is preffered):
!pip install git+https://github.com/PytorchLightning/lightning-transformers.git@master --upgrade
For version 1.4, I've got error in multi-gpu setting.
Borda commented
It shall be fixed now on master... 🐰
ChristopherMarais commented
For me downgrading pytorch-lightning also worked just to add to this conversation.
swcrazyfan commented
This is still a problem when I run inside Colab. When I downgrade, it works. Will this be fixed?