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Improve train CLI
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@ -18,6 +18,7 @@ from ..gold import GoldCorpus, minibatch
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from ..util import prints
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from .. import util
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from .. import displacy
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from ..compat import json_dumps
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@plac.annotations(
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@ -44,7 +45,7 @@ def train(cmd, lang, output_dir, train_data, dev_data, n_iter=20, n_sents=0,
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train_path = util.ensure_path(train_data)
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dev_path = util.ensure_path(dev_data)
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if not output_path.exists():
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prints(output_path, title="Output directory not found", exits=1)
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output_path.mkdir()
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if not train_path.exists():
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prints(train_path, title="Training data not found", exits=1)
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if dev_path and not dev_path.exists():
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@ -74,7 +75,7 @@ def train(cmd, lang, output_dir, train_data, dev_data, n_iter=20, n_sents=0,
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else:
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nlp = lang_class(pipeline=pipeline)
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corpus = GoldCorpus(train_path, dev_path, limit=n_sents)
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n_train_docs = corpus.count_train()
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n_train_words = corpus.count_train()
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optimizer = nlp.begin_training(lambda: corpus.train_tuples, device=use_gpu)
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@ -83,7 +84,7 @@ def train(cmd, lang, output_dir, train_data, dev_data, n_iter=20, n_sents=0,
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for i in range(n_iter):
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if resume:
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i += 20
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with tqdm.tqdm(total=corpus.count_train(), leave=False) as pbar:
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with tqdm.tqdm(total=n_train_words, leave=False) as pbar:
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train_docs = corpus.train_docs(nlp, projectivize=True,
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gold_preproc=False, max_length=0)
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losses = {}
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@ -91,7 +92,7 @@ def train(cmd, lang, output_dir, train_data, dev_data, n_iter=20, n_sents=0,
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docs, golds = zip(*batch)
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nlp.update(docs, golds, sgd=optimizer,
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drop=next(dropout_rates), losses=losses)
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pbar.update(len(docs))
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pbar.update(sum(len(doc) for doc in docs))
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with nlp.use_params(optimizer.averages):
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util.set_env_log(False)
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@ -105,6 +106,9 @@ def train(cmd, lang, output_dir, train_data, dev_data, n_iter=20, n_sents=0,
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corpus.dev_docs(
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nlp_loaded,
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gold_preproc=False))
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acc_loc =(output_path / ('model%d' % i) / 'accuracy.json')
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with acc_loc.open('w') as file_:
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file_.write(json_dumps(scorer.scores))
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util.set_env_log(True)
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print_progress(i, losses, scorer.scores)
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finally:
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