print_imdb_sample.py

index_offset = 3
word_index = imdb.get_word_index(path="imdb_word_index.json")
word_index = {k: (v + index_offset) for k,v in word_index.items()}
word_index["<PAD>"] = 0
word_index["<START>"] = 1
word_index["<UNK>"] = 2
word_index["<UNUSED>"] = 3
index_to_word = { v: k for k, v in word_index.items()}

def recover_text(sample, index_to_word):
    return ' '.join([index_to_word[i] for i in sample])

recover_text(x_train[50], index_to_word)