From 69c7c642c2c3a9c51d0b7c1c1e5e67848f9b7953 Mon Sep 17 00:00:00 2001 From: Matthew Honnibal Date: Sun, 1 Oct 2017 14:04:32 -0500 Subject: [PATCH] Add spacy evaluate --- spacy/__main__.py | 3 +- spacy/cli/__init__.py | 1 + spacy/cli/evaluate.py | 93 +++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 96 insertions(+), 1 deletion(-) create mode 100644 spacy/cli/evaluate.py diff --git a/spacy/__main__.py b/spacy/__main__.py index d02242d68..0ec96e4a1 100644 --- a/spacy/__main__.py +++ b/spacy/__main__.py @@ -7,7 +7,7 @@ if __name__ == '__main__': import plac import sys from spacy.cli import download, link, info, package, train, convert, model - from spacy.cli import profile + from spacy.cli import profile, evaluate from spacy.util import prints commands = { @@ -15,6 +15,7 @@ if __name__ == '__main__': 'link': link, 'info': info, 'train': train, + 'evaluate': evaluate, 'convert': convert, 'package': package, 'model': model, diff --git a/spacy/cli/__init__.py b/spacy/cli/__init__.py index e58c94642..ebe185f24 100644 --- a/spacy/cli/__init__.py +++ b/spacy/cli/__init__.py @@ -4,5 +4,6 @@ from .link import link from .package import package from .profile import profile from .train import train +from .evaluate import evaluate from .convert import convert from .model import model diff --git a/spacy/cli/evaluate.py b/spacy/cli/evaluate.py new file mode 100644 index 000000000..209660529 --- /dev/null +++ b/spacy/cli/evaluate.py @@ -0,0 +1,93 @@ +# coding: utf8 +from __future__ import unicode_literals, division, print_function + +import plac +import json +from collections import defaultdict +import cytoolz +from pathlib import Path +import dill +import tqdm +from thinc.neural._classes.model import Model +from thinc.neural.optimizers import linear_decay +from timeit import default_timer as timer +import random +import numpy.random + +from ..tokens.doc import Doc +from ..scorer import Scorer +from ..gold import GoldParse, merge_sents +from ..gold import GoldCorpus, minibatch +from ..util import prints +from .. import util +from .. import about +from .. import displacy +from ..compat import json_dumps + +random.seed(0) +numpy.random.seed(0) + + +@plac.annotations( + model=("Model name or path", "positional", None, str), + data_path=("Location of JSON-formatted evaluation data", "positional", None, str), + gold_preproc=("Use gold preprocessing", "flag", "G", bool), +) +def evaluate(cmd, model, data_path, gold_preproc=False): + """ + Train a model. Expects data in spaCy's JSON format. + """ + util.set_env_log(True) + data_path = util.ensure_path(data_path) + if not data_path.exists(): + prints(data_path, title="Evaluation data not found", exits=1) + corpus = GoldCorpus(data_path, data_path) + nlp = util.load_model(model) + scorer = nlp.evaluate(list(corpus.dev_docs(nlp, gold_preproc=gold_preproc))) + print_results(scorer) + + +def _render_parses(i, to_render): + to_render[0].user_data['title'] = "Batch %d" % i + with Path('/tmp/entities.html').open('w') as file_: + html = displacy.render(to_render[:5], style='ent', page=True) + file_.write(html) + with Path('/tmp/parses.html').open('w') as file_: + html = displacy.render(to_render[:5], style='dep', page=True) + file_.write(html) + + +def print_progress(itn, losses, dev_scores, wps=0.0): + scores = {} + for col in ['dep_loss', 'tag_loss', 'uas', 'tags_acc', 'token_acc', + 'ents_p', 'ents_r', 'ents_f', 'wps']: + scores[col] = 0.0 + scores['dep_loss'] = losses.get('parser', 0.0) + scores['ner_loss'] = losses.get('ner', 0.0) + scores['tag_loss'] = losses.get('tagger', 0.0) + scores.update(dev_scores) + scores['wps'] = wps + tpl = '\t'.join(( + '{:d}', + '{dep_loss:.3f}', + '{ner_loss:.3f}', + '{uas:.3f}', + '{ents_p:.3f}', + '{ents_r:.3f}', + '{ents_f:.3f}', + '{tags_acc:.3f}', + '{token_acc:.3f}', + '{wps:.1f}')) + print(tpl.format(itn, **scores)) + + +def print_results(scorer): + results = { + 'TOK': '%.2f' % scorer.token_acc, + 'POS': '%.2f' % scorer.tags_acc, + 'UAS': '%.2f' % scorer.uas, + 'LAS': '%.2f' % scorer.las, + 'NER P': '%.2f' % scorer.ents_p, + 'NER R': '%.2f' % scorer.ents_r, + 'NER F': '%.2f' % scorer.ents_f} + util.print_table(results, title="Results")