diff options
Diffstat (limited to 'nlp.py')
| -rw-r--r-- | nlp.py | 33 |
1 files changed, 17 insertions, 16 deletions
@@ -48,18 +48,23 @@ with open('./nlp/vocabulary.txt', 'r') as vocab: vocab = vocab.read() # create the CNN model -def create_model(vocab_size, max_length): - model = Sequential() - model.add(Embedding(vocab_size, 32, input_length=max_length)) - model.add(Conv1D(filters=16, kernel_size=4, activation='relu')) - model.add(MaxPooling1D(pool_size=2)) - model.add(Flatten()) - model.add(Dense(10, activation='relu')) - model.add(Dense(1, activation='sigmoid')) - opt = keras.optimizers.Adamax(learning_rate=0.002, beta_1=0.9, beta_2=0.999) +#def create_model(vocab_size, max_length): +model = Sequential() +model.add(Embedding(vocab_size, 32, input_length=max_length)) +model.add(Conv1D(filters=16, kernel_size=4, activation='relu')) +model.add(MaxPooling1D(pool_size=2)) +model.add(Flatten()) +model.add(Dense(10, activation='relu')) +model.add(Dense(1, activation='sigmoid')) +opt = keras.optimizers.Adamax(learning_rate=0.002, beta_1=0.9, beta_2=0.999) +model.compile(loss='binary_crossentropy', optimizer=opt, metrics=[keras.metrics.AUC()]) +model = create_model(23154, 64) +# load the weights +## this is done for every prediction?? +checkpoint_path = "./nlp/weights.ckpt" +model.load_weights(checkpoint_path) - model.compile(loss='binary_crossentropy', optimizer=opt, metrics=[keras.metrics.AUC()]) - return model +#return model def predict_sent(sent_for_pred): max_length = 64 @@ -70,13 +75,9 @@ def predict_sent(sent_for_pred): line = [line] tokenized_sent = tokenizer.texts_to_sequences(line) tokenized_sent = pad_sequences(tokenized_sent, maxlen=max_length, padding='post') - model = create_model(23154, 64) - # load the weights - checkpoint_path = "./nlp/weights.ckpt" - model.load_weights(checkpoint_path) predict_sent = model.predict(tokenized_sent, verbose=0) percent_sent = predict_sent[0,0] if round(percent_sent) == 0: return 'neg' else: - return 'pos'
\ No newline at end of file + return 'pos' |