Fix deployment issues

pipeline.py

@@ -3,7 +3,6 @@ from tensorflow.keras.models import load_model
 from tensorflow.keras.preprocessing.text import tokenizer_from_json
 from tensorflow.keras.preprocessing.sequence import pad_sequences
 import numpy as np
-import tensorflow as tf
 import json
 
 class NewsClassifierPipeline(Pipeline):
@@ -14,16 +13,14 @@ class NewsClassifierPipeline(Pipeline):
             tokenizer_data = json.load(f)
             self.tokenizer = tokenizer_from_json(tokenizer_data)
 
-    def preprocess(self, text):
-        sequence = self.tokenizer.texts_to_sequences([text])
-        padded = pad_sequences(sequence, maxlen=128)
-        return padded
+    def preprocess(self, inputs):
+        sequences = self.tokenizer.texts_to_sequences([inputs])
+        return pad_sequences(sequences, maxlen=128)
 
     def _forward(self, inputs):
-        predictions = self.model.predict(inputs)
-        scores = tf.nn.softmax(predictions, axis=1).numpy()
-        label = np.argmax(scores, axis=1)[0]
-        return [{"label": "foxnews" if label == 0 else "nbc", "score": float(scores[0][label])}]
+        processed = self.preprocess(inputs)
+        predictions = self.model.predict(processed)
+        return [{"label": "foxnews" if predictions[0][0] > 0.5 else "nbc", "score": float(predictions[0][0])}]
 
     def postprocess(self, model_outputs):
         return model_outputs