Add example code

Author: Hironsan

examples/download_model.py

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+import os
+
+import anago
+from anago.utils import download
+from anago.reader import load_data_and_labels
+
+dir_path = 'test_dir'
+url = 'https://storage.googleapis.com/chakki/datasets/public/models.zip'
+DATA_ROOT = os.path.join(os.path.dirname(__file__), '../data/conll2003/en/ner')
+
+test_path = os.path.join(DATA_ROOT, 'test.txt')
+x_test, y_test = load_data_and_labels(test_path)
+
+download(url, dir_path)
+
+model = anago.Sequence.load(dir_path)
+model.eval(x_test, y_test)

examples/ner_glove.py

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+import os
+
+import anago
+from anago.reader import load_data_and_labels, load_glove
+
+DATA_ROOT = os.path.join(os.path.dirname(__file__), '../data/conll2003/en/ner')
+EMBEDDING_PATH = 'glove.6B.100d.txt'
+
+train_path = os.path.join(DATA_ROOT, 'train.txt')
+valid_path = os.path.join(DATA_ROOT, 'valid.txt')
+
+print('Loading data...')
+x_train, y_train = load_data_and_labels(train_path)
+x_valid, y_valid = load_data_and_labels(valid_path)
+print(len(x_train), 'train sequences')
+print(len(x_valid), 'valid sequences')
+
+embeddings = load_glove(EMBEDDING_PATH)
+
+# Use pre-trained word embeddings
+model = anago.Sequence(max_epoch=1, embeddings=embeddings)
+model.train(x_train, y_train, x_valid, y_valid)

examples/ner_word2vec.py

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+import os
+
+from gensim.models.keyedvectors import KeyedVectors
+
+import anago
+from anago.reader import load_data_and_labels
+
+DATA_ROOT = os.path.join(os.path.dirname(__file__), '../data/conll2003/en/ner')
+EMBEDDING_PATH = 'model.txt'
+
+train_path = os.path.join(DATA_ROOT, 'train.txt')
+valid_path = os.path.join(DATA_ROOT, 'valid.txt')
+
+print('Loading data...')
+x_train, y_train = load_data_and_labels(train_path)
+x_valid, y_valid = load_data_and_labels(valid_path)
+print(len(x_train), 'train sequences')
+print(len(x_valid), 'valid sequences')
+
+embeddings = KeyedVectors.load_word2vec_format(EMBEDDING_PATH).wv
+
+# Use pre-trained word embeddings
+model = anago.Sequence(max_epoch=1, embeddings=embeddings)
+model.train(x_train, y_train, x_valid, y_valid)