Update pipeline.py

pipeline.py

@@ -8,13 +8,16 @@ from PIL import Image
 
 class PreTrainedPipeline():
     def __init__(self, path=""):
+        
+        self.model = keras.models.load_model(os.path.join(path, ""))
+
         self.word_to_index = tf.keras.layers.StringLookup(
           mask_token="",
-          vocabulary=self.tokenizer.get_vocabulary())
+          vocabulary=self.model.tokenizer.get_vocabulary())
         
         self.index_to_word = tf.keras.layers.StringLookup(
           mask_token="",
-          vocabulary=self.tokenizer.get_vocabulary(),
+          vocabulary=self.model.tokenizer.get_vocabulary(),
           invert=True)
 
     def load_image(img):
@@ -35,11 +38,11 @@ class PreTrainedPipeline():
         """
         image = load_image(inputs)
         initial = self.word_to_index([['[START]']]) # (batch, sequence)
-        img_features = self.feature_extractor(image[tf.newaxis, ...])
+        img_features = self.model.feature_extractor(image[tf.newaxis, ...])
         temperature = 0
         tokens = initial # (batch, sequence)
         for n in range(50):
-          preds = self((img_features, tokens)).numpy()  # (batch, sequence, vocab)
+          preds = self.model((img_features, tokens)).numpy()  # (batch, sequence, vocab)
           preds = preds[:,-1, :]  #(batch, vocab)
           if temperature==0:
               next = tf.argmax(preds, axis=-1)[:, tf.newaxis]  # (batch, 1)