def load_data_and_labels():
"""
Loads MR polarity data from files, splits the data into words and generates labels.
Returns split sentences and labels.
"""
# Load data from files
positive_examples = list(open("./data/rt-polaritydata/rt-polarity.pos", "r").readlines())
positive_examples = [s.strip() for s in positive_examples]
negative_examples = list(open("./data/rt-polaritydata/rt-polarity.neg", "r").readlines())
negative_examples = [s.strip() for s in negative_examples]
# Split by words
#x_text = list(open("./trainUNK.txt", "r").readlines())
x_text = positive_examples + negative_examples
x_text = [clean_str(sent) for sent in x_text]
x_text = [s.split(" ") for s in x_text]
# Generate labels
positive_labels = [[0, 1] for _ in positive_examples]
negative_labels = [[1, 0] for _ in negative_examples]
y = np.concatenate([positive_labels, negative_labels], 0)
return [x_text, y]
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