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-rw-r--r--nlp.py33
1 files changed, 17 insertions, 16 deletions
diff --git a/nlp.py b/nlp.py
index e54713e..9f36b58 100644
--- a/nlp.py
+++ b/nlp.py
@@ -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'