chore: trying without json

create_zipfiles_and_check_local_endpoint.py

@@ -10,18 +10,6 @@ from sklearn.model_selection import train_test_split
 from concrete.ml.sklearn import LogisticRegression
 from concrete.ml.deployment import FHEModelClient, FHEModelDev
 
-
-def to_json(python_object):
-    if isinstance(python_object, bytes):
-        return {"__class__": "bytes", "__value__": list(python_object)}
-    raise TypeError(repr(python_object) + " is not JSON serializable")
-
-
-def from_json(python_object):
-    if "__class__" in python_object:
-        return bytes(python_object["__value__"])
-
-
 # Fit a model. In the future, we should find an existing model on HF repository
 path_to_model = Path("compiled_model")
 do_training_and_compilation = True
@@ -64,13 +52,13 @@ for i in range(nb_samples):
     # Prepare the payload, including the evaluation keys which are needed server side
     payload = {
         "inputs": "fake",
-        "encrypted_inputs": to_json(encrypted_inputs),
-        "evaluation_keys": to_json(evaluation_keys),
+        "encrypted_inputs": encrypted_inputs,
+        "evaluation_keys": evaluation_keys,
     }
 
     # Run the inference on HF servers
     encrypted_prediction = my_handler(payload)
-    encrypted_prediction = from_json(encrypted_prediction)
+    encrypted_prediction = encrypted_prediction
 
     # Decrypt the result and dequantize
     prediction_proba = fhemodel_client.deserialize_decrypt_dequantize(encrypted_prediction)[0]

handler.py

@@ -3,19 +3,6 @@ import numpy as np
 from concrete.ml.deployment import FHEModelServer
 
 
-def from_json(python_object):
-    if "__class__" in python_object:
-        return bytes(python_object["__value__"])
-
-
-def to_json(python_object):
-    if isinstance(python_object, bytes):
-        return {"__class__": "bytes", "__value__": list(python_object)}
-    # if isinstance(python_object, bytes):
-    #     return list(python_object)
-    raise TypeError(repr(python_object) + " is not JSON serializable")
-
-
 class EndpointHandler:
     def __init__(self, path=""):
 
@@ -32,12 +19,12 @@ class EndpointHandler:
         """
 
         # Get inputs
-        encrypted_inputs = from_json(data.pop("encrypted_inputs", data))
+        encrypted_inputs = data.pop("encrypted_inputs", data)
 
         # Get keys
-        evaluation_keys = from_json(data.pop("evaluation_keys", data))
+        evaluation_keys = data.pop("evaluation_keys", data)
 
         # Run CML prediction
         encrypted_prediction = self.fhemodel_server.run(encrypted_inputs, evaluation_keys)
 
-        return to_json(encrypted_prediction)
+        return encrypted_prediction