Update cnnrnn.py

cnnrnn.py

@@ -36,10 +36,11 @@ def getModel(image):
     embedding_matrix_vocab = np.load('my_embedding_matrix.npy')
 
     input_shape = (image.shape[1],) 
+    text_input_shape = (153,)
     input1 = Input(shape=input_shape, name='Image_input')
     dense1 = Dense(256, kernel_initializer=tf.keras.initializers.glorot_uniform(seed = 56), name='dense_encoder')(input1)
 
-    input2 = Input(shape=(153), name='Text_Input')
+    input2 = Input(shape=text_input_shape, name='Text_Input')
     embedding_layer = Embedding(input_dim = 1427, output_dim = 300, input_length=153, mask_zero=True, trainable=False,
                 weights=[embedding_matrix_vocab], name="Embedding_layer")
     emb = embedding_layer(input2)