sapienzanlp / extend Goto Github PK

Hi! I just followed the steps for running the Docker image. The UI works in port 22001 but I can't reach the API in 22002. It says "Empty reply from server" when sending data and also with the /docs.
Any idea about how to solve it?
Thanks

Do you support disambiguation of Chinese entities

Using the same classy version mentioned in requirements.txt

Traceback (most recent call last):
File "spacy_extend.py", line 13, in
nlp.add_pipe("extend", after="ner", config=extend_config)
File "/home/vasista/miniconda3/envs/extendtest/lib/python3.8/site-packages/spacy/language.py", line 792, in add_pipe
pipe_component = self.create_pipe(
File "/home/vasista/miniconda3/envs/extendtest/lib/python3.8/site-packages/spacy/language.py", line 674, in create_pipe
resolved = registry.resolve(cfg, validate=validate)
File "/home/vasista/miniconda3/envs/extendtest/lib/python3.8/site-packages/thinc/config.py", line 746, in resolve
resolved, _ = cls._make(
File "/home/vasista/miniconda3/envs/extendtest/lib/python3.8/site-packages/thinc/config.py", line 795, in _make
filled, _, resolved = cls._fill(
File "/home/vasista/miniconda3/envs/extendtest/lib/python3.8/site-packages/thinc/config.py", line 867, in fill
getter_result = getter(*args, **kwargs)
File "/home/vasista/extend/extend/spacy_component.py", line 86, in init
self.model = load_checkpoint(checkpoint_path, device)
File "/home/vasista/extend/extend/spacy_component.py", line 22, in load_checkpoint
model = load_classy_module_from_checkpoint(checkpoint_path)
File "/home/vasista/miniconda3/envs/extendtest/lib/python3.8/site-packages/classy/utils/lightning.py", line 57, in load_classy_module_from_checkpoint
conf = load_training_conf_from_checkpoint(checkpoint_path)
File "/home/vasista/miniconda3/envs/extendtest/lib/python3.8/site-packages/classy/utils/lightning.py", line 23, in load_training_conf_from_checkpoint
conf = OmegaConf.load(f"{experiment_folder}/.hydra/{conf_file}")
File "/home/vasista/miniconda3/envs/extendtest/lib/python3.8/site-packages/omegaconf/omegaconf.py", line 183, in load
with io.open(os.path.abspath(file), "r", encoding="utf-8") as f:
FileNotFoundError: [Errno 2] No such file or directory: '/home/vasista/extend/.hydra/config.yaml'

Hi, I'm trying out your system and after installing everything the right way (some packages needed to be down/upgraded), I ran the spacy example on the longformer with le&titov's candidate sets.

The code is the following and the output warning message is below.

It says that dataset.base is empty. Might that be the problem?

Output: [('Japan', None), ('Syria', None), ('Friday', None)]

import spacy
from extend import spacy_component

nlp = spacy.load("en_core_web_sm")

extend_config = dict(
    checkpoint_path="../extend-longformer-large/2021-10-22/09-11-39/checkpoints/best.ckpt",
    mentions_inventory_path="../le-and-titov-2018-inventory.min-count-2.sqlite3",
    device=0,
    tokens_per_batch=4000,
)

nlp.add_pipe("extend", after="ner", config=extend_config)

input_sentence = "Japan began the defence of their title " \
                 "with a lucky 2-1 win against Syria " \
                 "in a championship match on Friday."

doc = nlp(input_sentence)

# [(Japan, Japan National Footbal Team), (Syria, Syria National Footbal Team)]
disambiguated_entities = [(ent.text, ent._.disambiguated_entity) for ent in doc.ents]






2022-05-05 13:39:07.458 WARNING classy.data.dataset.base: Token batch size 4000 < max length 4096. This might result in batches with only 1 sample that contain more token than the specified token batch size
2022-05-05 13:39:07.459 WARNING classy.data.dataset.base: Dataset empty

Hi, I have tried to train the model with the command you provided
classy train qa ./Datasets/aida -n my-model-name --profile aida-longformer-large-gam -pd extend

I have also prepared the training data with the right name and extension, but the command gives me this error
Traceback (most recent call last): File "/opt/miniconda3/envs/extend/bin/classy", line 8, in <module> sys.exit(main()) File "/opt/miniconda3/envs/extend/lib/python3.9/site-packages/classy/scripts/cli/__init__.py", line 141, in main import_module_and_submodules(to_import) File "/opt/miniconda3/envs/extend/lib/python3.9/site-packages/classy/scripts/cli/utils.py", line 201, in import_module_and_submodules import_module_and_submodules(subpackage, exclude=exclude) File "/opt/miniconda3/envs/extend/lib/python3.9/site-packages/classy/scripts/cli/utils.py", line 201, in import_module_and_submodules import_module_and_submodules(subpackage, exclude=exclude) File "/opt/miniconda3/envs/extend/lib/python3.9/site-packages/classy/scripts/cli/utils.py", line 190, in import_module_and_submodules module = importlib.import_module(package_name) File "/opt/miniconda3/envs/extend/lib/python3.9/importlib/__init__.py", line 127, in import_module return _bootstrap._gcd_import(name[level:], package, level) File "<frozen importlib._bootstrap>", line 1030, in _gcd_import File "<frozen importlib._bootstrap>", line 1007, in _find_and_load File "<frozen importlib._bootstrap>", line 986, in _find_and_load_unlocked File "<frozen importlib._bootstrap>", line 680, in _load_unlocked File "<frozen importlib._bootstrap_external>", line 850, in exec_module File "<frozen importlib._bootstrap>", line 228, in _call_with_frames_removed File "/home/agazzi/extend/extend/demo/serve.py", line 2, in <module> import spacy File "/opt/miniconda3/envs/extend/lib/python3.9/site-packages/spacy/__init__.py", line 14, in <module> from . import pipeline # noqa: F401 File "/opt/miniconda3/envs/extend/lib/python3.9/site-packages/spacy/pipeline/__init__.py", line 1, in <module> from .attributeruler import AttributeRuler File "/opt/miniconda3/envs/extend/lib/python3.9/site-packages/spacy/pipeline/attributeruler.py", line 6, in <module> from .pipe import Pipe File "spacy/pipeline/pipe.pyx", line 8, in init spacy.pipeline.pipe File "/opt/miniconda3/envs/extend/lib/python3.9/site-packages/spacy/training/__init__.py", line 11, in <module> from .callbacks import create_copy_from_base_model # noqa: F401 File "/opt/miniconda3/envs/extend/lib/python3.9/site-packages/spacy/training/callbacks.py", line 3, in <module> from ..language import Language File "/opt/miniconda3/envs/extend/lib/python3.9/site-packages/spacy/language.py", line 25, in <module> from .training.initialize import init_vocab, init_tok2vec File "/opt/miniconda3/envs/extend/lib/python3.9/site-packages/spacy/training/initialize.py", line 14, in <module> from .pretrain import get_tok2vec_ref File "/opt/miniconda3/envs/extend/lib/python3.9/site-packages/spacy/training/pretrain.py", line 16, in <module> from ..schemas import ConfigSchemaPretrain File "/opt/miniconda3/envs/extend/lib/python3.9/site-packages/spacy/schemas.py", line 216, in <module> class TokenPattern(BaseModel): File "pydantic/main.py", line 299, in pydantic.main.ModelMetaclass.__new__ File "pydantic/fields.py", line 411, in pydantic.fields.ModelField.infer File "pydantic/fields.py", line 342, in pydantic.fields.ModelField.__init__ File "pydantic/fields.py", line 451, in pydantic.fields.ModelField.prepare File "pydantic/fields.py", line 545, in pydantic.fields.ModelField._type_analysis File "pydantic/fields.py", line 550, in pydantic.fields.ModelField._type_analysis File "/opt/miniconda3/envs/extend/lib/python3.9/typing.py", line 852, in __subclasscheck__ return issubclass(cls, self.__origin__) TypeError: issubclass() arg 1 must be a class

Hi,

I tried to run a REST service with the docker image that you make available. However, I do not receive any result when I try to disambiguate even simple sentences.

Example:

resp = requests.post(url="http://127.0.0.1:22002/", data='[{"text":"Bob Dylan is a famous singer."}]')

The json result is

[{'text': 'Bob Dylan is a singer.', 'disambiguated_entities': []}]

I am very interested in your work. I follow your training script in the readme "classy train qa data/aida -n ex --profile aida-longformer-large-gam -pd extend" to train the file, but the error "FileExistsError: [Errno 17] File exists: '/home/ta/zgb/extend-main/experiments/ex/2023-08-03/23-40-46/resources/allenai/longformer-large-4096'". But I didn't create such a file before this. Can you help me with this question, thank you very much.

Hi,

How can i use this code to name entities which are non-ambiguous and disambiguate entities which are ambiguous? Currently this code seems to resolve entities which are ambiguous. I want to name entities in the same code which are non-ambiguous too.
Pls suggest.

Hi,

Run spacy with the "extend" but got below error.

(extend) ubuntu@ip-172-31-3-241:~/extend$ python spacy_test.py 
Some weights of the model checkpoint at allenai/longformer-large-4096 were not used when initializing LongformerForQuestionAnswering: ['lm_head.layer_norm.weight', 'lm_head.bias', 'lm_head.decoder.weight', 'lm_head.dense.bias', 'lm_head.layer_norm.bias', 'lm_head.dense.weight']
- This IS expected if you are initializing LongformerForQuestionAnswering 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 LongformerForQuestionAnswering from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Some weights of LongformerForQuestionAnswering were not initialized from the model checkpoint at allenai/longformer-large-4096 and are newly initialized: ['qa_outputs.weight', 'qa_outputs.bias']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
Traceback (most recent call last):
  File "spacy_test.py", line 13, in <module>
    nlp.add_pipe("extend", after="ner", config=extend_config)
  File "/home/ubuntu/miniconda3/envs/extend/lib/python3.8/site-packages/spacy/language.py", line 792, in add_pipe
    pipe_component = self.create_pipe(
  File "/home/ubuntu/miniconda3/envs/extend/lib/python3.8/site-packages/spacy/language.py", line 674, in create_pipe
    resolved = registry.resolve(cfg, validate=validate)
  File "/home/ubuntu/miniconda3/envs/extend/lib/python3.8/site-packages/thinc/config.py", line 746, in resolve
    resolved, _ = cls._make(
  File "/home/ubuntu/miniconda3/envs/extend/lib/python3.8/site-packages/thinc/config.py", line 795, in _make
    filled, _, resolved = cls._fill(
  File "/home/ubuntu/miniconda3/envs/extend/lib/python3.8/site-packages/thinc/config.py", line 867, in _fill
    getter_result = getter(*args, **kwargs)
  File "/home/ubuntu/extend/extend/spacy_component.py", line 86, in __init__
    self.model = load_checkpoint(checkpoint_path, device)
  File "/home/ubuntu/extend/extend/spacy_component.py", line 24, in load_checkpoint
    model.to(torch.device(device))
  File "/home/ubuntu/miniconda3/envs/extend/lib/python3.8/site-packages/pytorch_lightning/core/mixins/device_dtype_mixin.py", line 111, in to
    return super().to(*args, **kwargs)
  File "/home/ubuntu/miniconda3/envs/extend/lib/python3.8/site-packages/torch/nn/modules/module.py", line 852, in to
    return self._apply(convert)
  File "/home/ubuntu/miniconda3/envs/extend/lib/python3.8/site-packages/torch/nn/modules/module.py", line 530, in _apply
    module._apply(fn)
  File "/home/ubuntu/miniconda3/envs/extend/lib/python3.8/site-packages/torch/nn/modules/module.py", line 530, in _apply
    module._apply(fn)
  File "/home/ubuntu/miniconda3/envs/extend/lib/python3.8/site-packages/torch/nn/modules/module.py", line 530, in _apply
    module._apply(fn)
  [Previous line repeated 1 more time]
  File "/home/ubuntu/miniconda3/envs/extend/lib/python3.8/site-packages/torch/nn/modules/module.py", line 552, in _apply
    param_applied = fn(param)
  File "/home/ubuntu/miniconda3/envs/extend/lib/python3.8/site-packages/torch/nn/modules/module.py", line 850, in convert
    return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking)
  File "/home/ubuntu/miniconda3/envs/extend/lib/python3.8/site-packages/torch/cuda/__init__.py", line 166, in _lazy_init
    raise AssertionError("Torch not compiled with CUDA enabled")
AssertionError: Torch not compiled with CUDA enabled

I think we can't install Cuda without GPU on the machine.
Can we solve this without GPU?

Thanks

Hi, nice work!

I would like to reproduce your training process. I installed the dependencies and downloaded the dataset following the README. I have renamed aida-train-kilt.jsonl to train.jsonl etc. I used the following command in the root directory

classy train qa data/aida -n my-model-name --profile aida-longformer-large-gam -pd extend

and got the following error

Error executing job with overrides: ['device=cuda', 'exp_name=my-model-name', 'data.datamodule.dataset_path=data/aida']
Traceback (most recent call last):
  File "/home/ICT2000/jxu/miniconda3/envs/extend/lib/python3.8/site-packages/classy/scripts/cli/train.py", line 620, in <lambda>
    lambda cfg: _main_mock(cfg, blames=blames if args.print else None)
  File "/home/ICT2000/jxu/miniconda3/envs/extend/lib/python3.8/site-packages/classy/scripts/cli/train.py", line 208, in _main_mock
    train(cfg)
  File "/home/ICT2000/jxu/miniconda3/envs/extend/lib/python3.8/site-packages/classy/scripts/model/train.py", line 22, in train
    pl_data_module.prepare_data()
  File "/home/ICT2000/jxu/miniconda3/envs/extend/lib/python3.8/site-packages/pytorch_lightning/core/datamodule.py", line 474, in wrapped_fn
    fn(*args, **kwargs)
  File "/home/ICT2000/jxu/miniconda3/envs/extend/lib/python3.8/site-packages/classy/data/data_modules.py", line 161, in prepare_data
    shuffle_and_store_dataset(
  File "/home/ICT2000/jxu/miniconda3/envs/extend/lib/python3.8/site-packages/classy/utils/data.py", line 39, in shuffle_and_store_dataset
    samples = shuffle_dataset(dataset_path, data_driver)
  File "/home/ICT2000/jxu/miniconda3/envs/extend/lib/python3.8/site-packages/classy/utils/data.py", line 29, in shuffle_dataset
    samples = load_dataset(dataset_path, data_driver)
  File "/home/ICT2000/jxu/miniconda3/envs/extend/lib/python3.8/site-packages/classy/utils/data.py", line 22, in load_dataset
    return list(data_driver.read_from_path(dataset_path))
  File "/home/ICT2000/jxu/miniconda3/envs/extend/lib/python3.8/site-packages/classy/data/data_drivers.py", line 620, in read
    yield QASample(**json.loads(line))
TypeError: __init__() missing 2 required positional arguments: 'context' and 'question'

I see that in extend/data you have another data_drivers, but classy still used their version of it. Since I am new to classy I am not sure what should I proceed next.
Thank you!