2Vh!dZddlZddlZddlmZddlmZddlm Z ed d dZ edd d Z y) z&IMDB sentiment classification dataset.N) keras_export)get_file)remove_long_seqzkeras.datasets.imdb.load_datac bd} t|| dzd}tj|d5} | d| d} } | d | d }} d d d tjj |}tj t  }|j|| |}  |} tj t  }|j|| |} |}|M| Dcgc]}|g|Dcgc]}||z c}z} }}| Dcgc]}|g|Dcgc]}||z c}z} }}n|rE| Dcgc]}|Dcgc]}||z c}} }}| Dcgc]}|Dcgc]}||z c}} }}n>| Dcgc]}|Dcgc]}|c}} }}| Dcgc]}|Dcgc]}|c}} }}|rzload_data..|s+1A+sobject)dtype)rnploadrandom RandomStatearangelenshuffler ValueErrorstr concatenaterarray)path num_wordsskip_topmaxlenseed start_charoov_char index_fromkwargs origin_folderfr labels_trainr labels_testrngindicesrwxslabelsidxrrs r load_datar9 sMB G z) N  D D )7Q !) a lk1X; 7 ))   %CiiG %GKKgG(LiiF $GKK G_Fg&KGNO!J<1"=a1z>"==OOFLM:,!!!1-a1z>->>+23aq>!A>33*01Qa.1.11 / N-ffkJ fDv;-GI  6 B ^^\;7 8F +++  FG G8q,9,Q8 ; G  DF Fa!9Qx18y8q9 F F g,Cxx4C96$3O!<M.@->!3 1, H : FsK  K+ K7K K) K$K)/ K48 K/ K4 K? K: &K?4 L = L L  L L %L" L +L L  L+L& ,L& 3L+ KK$K)/K4:K?L LL &L+z"keras.datasets.imdb.get_word_indexcd}t||dzd}t|5}tj|cdddS#1swYyxYw)aRetrieves a dict mapping words to their index in the IMDB dataset. 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: ```python # 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]) ``` rimdb_word_index.json bfafd718b763782e994055a2d397834fr N)ropenjsonr)r&r/r0s rget_word_indexr?sTJ G 554 D dqyy|s >A)rNrNq)r;) __doc__r>numpyrkeras.src.api_exportrkeras.src.utils.file_utilsrkeras.src.utils.python_utilsrr9r?rrKsf, -/8-.     0/0D23,4,rJ