40 lines
902 B
Python
40 lines
902 B
Python
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import numpy as np
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def read_text(filename):
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return open(filename, 'r', encoding='UTF-8').read().lower()
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def peek_random_seed(data):
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return np.random.randint(0, len(data) - 1)
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def prepare_text(text, ids, seq_length):
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dataX = []
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dataY = []
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for i in range(0, len(text) - seq_length, 1):
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seq_in = text[i:i + seq_length]
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seq_out = text[i + seq_length]
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dataX.append([ids[char] for char in seq_in])
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dataY.append(ids[seq_out])
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return dataX, dataY
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def generate_text(model, pattern, chars, n_vocab, prediction_len):
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text = ""
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for i in range(prediction_len):
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x = np.reshape(pattern, (1, len(pattern), 1)) / float(n_vocab)
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prediction = model.predict(x, verbose=0)
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index = np.argmax(prediction)
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text += chars[index]
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pattern.append(index)
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pattern = pattern[1:len(pattern)]
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return text
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