Running Custom NER training using local en_core_web_lg in config file #10148
Description
I've made the following config file to make a custom NER:
[paths]
train = null
dev = null
vectors = null
init_tok2vec = null
[system]
gpu_allocator = null
seed = 0
[nlp]
lang = "en"
pipeline = ["tok2vec","ner"]
batch_size = 1000
disabled = []
before_creation = null
after_creation = null
after_pipeline_creation = null
tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
[components]
[components.ner]
factory = "ner"
incorrect_spans_key = null
moves = null
scorer = {"@scorers":"spacy.ner_scorer.v1"}
update_with_oracle_cut_size = 100
[components.ner.model]
@architectures = "spacy.TransitionBasedParser.v2"
state_type = "ner"
extra_state_tokens = false
hidden_width = 64
maxout_pieces = 2
use_upper = true
nO = null
[components.ner.model.tok2vec]
@architectures = "spacy.Tok2VecListener.v1"
width = ${components.tok2vec.model.encode.width}
upstream = "*"
[components.tok2vec]
factory = "tok2vec"
[components.tok2vec.model]
@architectures = "spacy.Tok2Vec.v2"
[components.tok2vec.model.embed]
@architectures = "spacy.MultiHashEmbed.v2"
width = ${components.tok2vec.model.encode.width}
attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
rows = [5000,2500,2500,2500]
include_static_vectors = true
[components.tok2vec.model.encode]
@architectures = "spacy.MaxoutWindowEncoder.v2"
width = 256
depth = 8
window_size = 1
maxout_pieces = 3
[corpora]
[corpora.dev]
@readers = "spacy.Corpus.v1"
path = ${paths.dev}
max_length = 0
gold_preproc = false
limit = 0
augmenter = null
[corpora.train]
@readers = "spacy.Corpus.v1"
path = ${paths.train}
max_length = 0
gold_preproc = false
limit = 0
augmenter = null
[training]
dev_corpus = "corpora.dev"
train_corpus = "corpora.train"
seed = ${system.seed}
gpu_allocator = ${system.gpu_allocator}
dropout = 0.1
accumulate_gradient = 1
patience = 1600
max_epochs = 0
max_steps = 20000
eval_frequency = 200
frozen_components = []
annotating_components = []
before_to_disk = null
[training.batcher]
@batchers = "spacy.batch_by_words.v1"
discard_oversize = false
tolerance = 0.2
get_length = null
[training.batcher.size]
@schedules = "compounding.v1"
start = 100
stop = 1000
compound = 1.001
t = 0.0
[training.logger]
@loggers = "spacy.ConsoleLogger.v1"
progress_bar = false
[training.optimizer]
@optimizers = "Adam.v1"
beta1 = 0.9
beta2 = 0.999
L2_is_weight_decay = true
L2 = 0.01
grad_clip = 1.0
use_averages = false
eps = 0.00000001
learn_rate = 0.001
[training.score_weights]
ents_f = 1.0
ents_p = 0.0
ents_r = 0.0
ents_per_type = null
[pretraining]
[initialize]
vectors = "P:\Documents\Python Scripts\newPythonEnv\Additive_NER_Spacy3\en_core_web_lg-3.2.0.tar\en_core_web_lg-3.2.0\en_core_web_lg\en_core_web_lg-3.2.0\vocab\vectors"
init_tok2vec = ${paths.init_tok2vec}
vocab_data = null
lookups = null
before_init = null
after_init = null
[initialize.components]
[initialize.tokenizer]
Towards the end I had to change the vectors path from en_core_web_lg to "P:\Documents\Python Scripts\newPythonEnv\Additive_NER_Spacy3\en_core_web_lg-3.2.0.tar\en_core_web_lg-3.2.0\en_core_web_lg\en_core_web_lg-3.2.0\vocab\vectors" this is because I can not fetch the en_core_web_lg model from online servers but only can do that locally (due to work restriction). However I get the following error:
[2022-01-27 16:21:16,595] [INFO] Set up nlp object from config
[2022-01-27 16:21:16,608] [INFO] Pipeline: ['tok2vec', 'ner']
[2022-01-27 16:21:16,613] [INFO] Created vocabulary
Traceback (most recent call last):
File "P:\myPythonEnv\lib\site-packages\spacy\language.py", line 1283, in initialize
init_vocab(
File "P:\myPythonEnv\lib\site-packages\spacy\training\initialize.py", line 131, in init_vocab
load_vectors_into_model(nlp, vectors)
File "P:\myPythonEnv\lib\site-packages\spacy\training\initialize.py", line 152, in load_vectors_into_model
vectors_nlp = load_model(name, vocab=nlp.vocab, exclude=exclude)
File "P:\myPythonEnv\lib\site-packages\spacy\util.py", line 427, in load_model
raise IOError(Errors.E050.format(name=name))
OSError: [E050] Can't find model '"P:\Documents\Python Scripts\newPythonEnv\Additive_NER_Spacy3\en_core_web_lg-3.2.0.tar\en_core_web_lg-3.2.0\en_core_web_lg\en_core_web_lg-3.2.0\vocab\vectors"'. It doesn't seem to be a Python package or a valid path to a data directory.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "P:\myPythonEnv\lib\runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "P:\myPythonEnv\lib\runpy.py", line 87, in _run_code
exec(code, run_globals)
File "P:\myPythonEnv\lib\site-packages\spacy\__main__.py", line 4, in <module>
setup_cli()
File "P:\myPythonEnv\lib\site-packages\spacy\cli\_util.py", line 71, in setup_cli
command(prog_name=COMMAND)
File "P:\myPythonEnv\lib\site-packages\click\core.py", line 829, in __call__
return self.main(*args, **kwargs)
File "P:\myPythonEnv\lib\site-packages\click\core.py", line 782, in main
rv = self.invoke(ctx)
File "P:\myPythonEnv\lib\site-packages\click\core.py", line 1259, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "P:\myPythonEnv\lib\site-packages\click\core.py", line 1066, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "P:\myPythonEnv\lib\site-packages\click\core.py", line 610, in invoke
return callback(*args, **kwargs)
File "P:\myPythonEnv\lib\site-packages\typer\main.py", line 497, in wrapper
return callback(**use_params) # type: ignore
File "P:\myPythonEnv\lib\site-packages\spacy\cli\train.py", line 45, in train_cli
train(config_path, output_path, use_gpu=use_gpu, overrides=overrides)
File "P:\myPythonEnv\lib\site-packages\spacy\cli\train.py", line 72, in train
nlp = init_nlp(config, use_gpu=use_gpu)
File "P:\myPythonEnv\lib\site-packages\spacy\training\initialize.py", line 84, in init_nlp
nlp.initialize(lambda: train_corpus(nlp), sgd=optimizer)
File "P:\myPythonEnv\lib\site-packages\spacy\language.py", line 1287, in initialize
raise IOError(Errors.E884.format(vectors=I["vectors"]))
OSError: [E884] The pipeline could not be initialized because the vectors could not be found at '"P:\Documents\Python Scripts\newPythonEnv\Additive_NER_Spacy3\en_core_web_lg-3.2.0.tar\en_core_web_lg-3.2.0\en_core_web_lg\en_core_web_lg-3.2.0\vocab\vectors"'. If your pipeline was already initialized/trained before, call 'resume_training' instead of 'initialize', or initialize only the components that are new.
I have tried various paths and all of the gave the same error - these non-working paths are:
"P:\Documents\Python Scripts\newPythonEnv\Additive_NER_Spacy3\en_core_web_lg-3.2.0.tar\en_core_web_lg-3.2.0\en_core_web_lg\en_core_web_lg-3.2.0\vocab"
"P:\Documents\Python Scripts\newPythonEnv\Additive_NER_Spacy3\en_core_web_lg-3.2.0.tar\en_core_web_lg-3.2.0\en_core_web_lg\en_core_web_lg-3.2.0\vocab\vectors"
"P:\Documents\Python Scripts\newPythonEnv\Additive_NER_Spacy3\en_core_web_lg-3.2.0.tar\en_core_web_lg-3.2.0\en_core_web_lg\en_core_web_lg-3.2.0"
"en_core_web_lg"
I wonder if there is a way to fetch the model using some proxy in the config file or how can I make sure the vectors are loaded locally in a correct manner?
My Spacy version is 3.2.1.