Add support for JSON encoding torch.tensor to keep it consistent with sagemaker-inference-toolkit

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):
+        elif isinstance(obj, np.ndarray) or hasattr(obj, "tolist"):
             return obj.tolist()
         elif isinstance(obj, datetime.datetime):
             return obj.__str__()

tests/unit/test_decoder_encoder.py

@@ -15,6 +15,7 @@
 import os
 
 import pytest
+from transformers.testing_utils import require_torch
 
 from mms.service import PredictionException
 from PIL import Image
@@ -84,6 +85,15 @@ def test_encode_json():
     assert json.loads(encoded_data) == ENCODE_JSON_INPUT
 
 
+@require_torch
+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}
+
+
 def test_encode_csv():
     decoded_data = decoder_encoder.encode_csv(ENCODE_CSV_INPUT)
     assert (