Retrieves a dict mapping words to their index in the IMDB dataset.
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Compat aliases for migration
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more details.
`tf.compat.v1.keras.datasets.imdb.get_word_index`
tf.keras.datasets.imdb.get_word_index(
path='imdb_word_index.json'
)
Args |
path
|
where to cache the data (relative to ~/.keras/dataset ).
|
Returns |
The word index dictionary. Keys are word strings, values are their
index.
|
Example:
# Use the default parameters to keras.datasets.imdb.load_data
start_char = 1
oov_char = 2
index_from = 3
# Retrieve the training sequences.
(x_train, _), _ = keras.datasets.imdb.load_data(
start_char=start_char, oov_char=oov_char, index_from=index_from
)
# Retrieve the word index file mapping words to indices
word_index = keras.datasets.imdb.get_word_index()
# Reverse the word index to obtain a dict mapping indices to words
# And add `index_from` to indices to sync with `x_train`
inverted_word_index = dict(
(i + index_from, word) for (word, i) in word_index.items()
)
# Update `inverted_word_index` to include `start_char` and `oov_char`
inverted_word_index[start_char] = "[START]"
inverted_word_index[oov_char] = "[OOV]"
# Decode the first sequence in the dataset
decoded_sequence = " ".join(inverted_word_index[i] for i in x_train[0])