add custom handler

handler.py

@@ -1,4 +1,5 @@
 from typing import Dict, List, Any
+import base64
 
 import tensorflow as tf
 from keras_cv.models.generative.stable_diffusion.text_encoder import TextEncoder
@@ -47,7 +48,7 @@ class EndpointHandler():
         context = encoded_text
 
         unconditional_context = tf.repeat(
-            _get_unconditional_context(), batch_size, axis=0
+            self._get_unconditional_context(), batch_size, axis=0
         )  
 
         return context, unconditional_context
@@ -57,7 +58,13 @@ class EndpointHandler():
         prompt = data.pop("inputs", data)
         batch_size = data.pop("batch_size", 1)
 
-        encoded_text = encode_text(prompt)
-        context, unconditional_context = get_contexts(encoded_text, batch_size)        
+        encoded_text = self.encode_text(prompt)
+        context, unconditional_context = self.get_contexts(encoded_text, batch_size)
 
-        return context, unconditional_context
+        context_b64 = base64.b64encode(context.numpy().tobytes())
+        context_b64str = context_b64.decode()
+
+        unconditional_context_b64 = base64.b64encode(unconditional_context.numpy().tobytes())
+        unconditional_context_b64str = unconditional_context_b64.decode()        
+
+        return context_b64str, unconditional_context_b64str