Address review comments

Author: maaquib

src/sagemaker_huggingface_inference_toolkit/decoder_encoder.py

@@ -87,7 +87,7 @@ def default(self, obj):
             return int(obj)
         elif isinstance(obj, np.floating):
             return float(obj)
-        elif isinstance(obj, np.ndarray) or hasattr(obj, "tolist"):
+        elif hasattr(obj, "tolist"):
             return obj.tolist()
         elif isinstance(obj, datetime.datetime):
             return obj.__str__()

tests/unit/test_decoder_encoder.py

@@ -14,6 +14,7 @@
 import json
 import os
 
+import numpy as np
 import pytest
 from transformers.testing_utils import require_torch
 
@@ -27,6 +28,7 @@
     {"answer": "Nuremberg", "end": 42, "score": 0.9926825761795044, "start": 33},
     {"answer": "Berlin is the capital of Germany", "end": 32, "score": 0.26097726821899414, "start": 0},
 ]
+ENCODE_TOLOIST_INPUT = [1, 0.5, 5.0]
 
 DECODE_JSON_INPUT = {"inputs": "My name is Wolfgang and I live in Berlin"}
 DECODE_CSV_INPUT = "question,context\r\nwhere do i live?,My name is Philipp and I live in Nuremberg\r\nwhere is Berlin?,Berlin is the capital of Germany"
@@ -89,9 +91,13 @@ def test_encode_json():
 def test_encode_json_torch():
     import torch
 
-    DATA = [1, 0.5, 5.0]
-    encoded_data = decoder_encoder.encode_json({"data": torch.tensor(DATA)})
-    assert json.loads(encoded_data) == {"data": DATA}
+    encoded_data = decoder_encoder.encode_json({"data": torch.tensor(ENCODE_TOLOIST_INPUT)})
+    assert json.loads(encoded_data) == {"data": ENCODE_TOLOIST_INPUT}
+
+
+def test_encode_json_numpy():
+    encoded_data = decoder_encoder.encode_json({"data": np.array(ENCODE_TOLOIST_INPUT)})
+    assert json.loads(encoded_data) == {"data": ENCODE_TOLOIST_INPUT}
 
 
 def test_encode_csv():