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X = [[word2idx[w[0]] for w in s] for s in sentences]

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word2idx = {w: i for i, w in enumerate(words)}
tag2idx = {t: i for i, t in enumerate(tags)}

idx2word = {i: w for w, i in word2idx.items()}
idx2tag = {i: w for w, i in tag2idx.items()}

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class SentenceGetter(object):
    
    def __init__(self, data):
        self.n_sent = 1
        self.data = data
        self.empty = False
        
        agg_func = lambda s: [(w, p, t) for w, p, t in zip(s["Word"].values.tolist(),
                                                           s["POS"].values.tolist(),
                                                           s["Tag"].values.tolist())]

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txt = ["call to save manufacturing jobs the trades union congress (tuc) is calling on the government to stem job losses in manufacturing firms by reviewing the help it gives companies.  the tuc said in its submission before the budget that action is needed because of 105 000 jobs lost from the sector over the last year. it calls for better pensions  child care provision and decent wages. the 36-page submission also urges the government to examine support other european countries provide to industry. tuc general secretary brendan barber called for  a commitment to policies that will make a real difference to the lives of working people.    greater investment in childcare strategies and the people delivering that childcare will increases the options available to working parents   he said.  a commitment to our public services and manufacturing sector ensures that we can continue to compete on a global level and deliver the frontline services that this country needs.  he also called for  practical measures  to he

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txt = ["blair prepares to name poll date tony blair is likely to name 5 may as election day when parliament returns from its easter break  the bbc s political editor has learned.  andrew marr says mr blair will ask the queen on 4 or 5 april to dissolve parliament at the end of that week. mr blair has so far resisted calls for him to name the day but all parties have stepped up campaigning recently. downing street would not be drawn on the claim  saying election timing was a matter for the prime minister.  a number 10 spokeswoman would only say:  he will announce an election when he wants to announce an election.  the move will signal a frantic week at westminster as the government is likely to try to get key legislation through parliament. the government needs its finance bill  covering the budget plans  to be passed before the commons closes for business at the end of the session on 7 april.  but it will also seek to push through its serious and organised crime bill and id cards bill. mr marr said on wednesd

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num_epochs = 10
history = model.fit(train_padded, training_label_seq, epochs=num_epochs, validation_data=(validation_padded, validation_label_seq), verbose=2)

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opt = tf.keras.optimizers.Adam(lr=0.001, decay=1e-6)
model.compile(
    loss='sparse_categorical_crossentropy',
    optimizer=opt,
    metrics=['accuracy'],
)

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label_tokenizer = Tokenizer()
label_tokenizer.fit_on_texts(labels)

training_label_seq = np.array(label_tokenizer.texts_to_sequences(train_labels))
validation_label_seq = np.array(label_tokenizer.texts_to_sequences(validation_labels))

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tokenizer = Tokenizer(num_words = vocab_size, oov_token=oov_tok)
tokenizer.fit_on_texts(train_articles)
word_index = tokenizer.word_index

train_sequences = tokenizer.texts_to_sequences(train_articles)
train_padded = pad_sequences(train_sequences, maxlen=max_length, padding=padding_type, truncating=trunc_type)

validation_sequences = tokenizer.texts_to_sequences(validation_articles)
validation_padded = pad_sequences(validation_sequences, maxlen=max_length, padding=padding_type, truncating=trunc_type)

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train_padded = pad_sequences(train_sequences, maxlen=max_length, padding=padding_type, truncating=trunc_type)