Minor fixes

Author: olokobayusuf

Changelog.md

@@ -1,5 +1,5 @@
 ## 0.0.82
-*INCOMPLETE*
++ Minor fixes.
 
 ## 0.0.81
 + Refactored `Parameter.type` field to `Parameter.dtype`.

muna/beta/openai/annotations.py

@@ -244,7 +244,7 @@ def get_parameter(
     dtype = dtype if isinstance(dtype, set) else { dtype }
     for idx, param in enumerate(parameters):
         if (
-            param.type in dtype and
+            param.dtype in dtype and
             (not denotation or param.denotation == denotation)
         ):
             return idx, param

muna/beta/openai/completions.py

@@ -194,7 +194,7 @@ def __create_delegate(self, tag: str) -> ChatCompletionDelegate:
             idx
             for idx, param in enumerate(signature.outputs)
             if (
-                param.type == Dtype.dict and
+                param.dtype == Dtype.dict and
                 param.value_schema["title"] in { "ChatCompletion", "ChatCompletionChunk" }
             )
         ), None)

muna/beta/remote/remote.py

@@ -135,8 +135,8 @@ def _create_remote_value(obj: Value) -> RemoteValue:
 
 def _parse_remote_value(value: RemoteValue) -> Value:
     buffer = _download_value_data(value.data) if value.data else None
-    is_tensor = value.type in _TENSOR_DTYPES
-    match value.type:
+    is_tensor = value.dtype in _TENSOR_DTYPES
+    match value.dtype:
         case Dtype.null:
             return None
         case _ if is_tensor:
@@ -152,7 +152,7 @@ def _parse_remote_value(value: RemoteValue) -> Value:
         case Dtype.binary:
             return buffer
         case _:
-            raise ValueError(f"Failed to parse remote value with type `{value.type}` because it is not supported")
+            raise ValueError(f"Failed to parse remote value with type `{value.dtype}` because it is not supported")
 
 def _parse_remote_prediction(prediction: RemotePrediction) -> Prediction:
     results = (

muna/c/value.py

@@ -38,7 +38,7 @@ def data(self):
         return data            
 
     @property
-    def type(self) -> Dtype:
+    def dtype(self) -> Dtype:
         dtype = c_int()
         status = get_fxnc().FXNValueGetType(self.__value, byref(dtype))
         if status != FXNStatus.OK:
@@ -47,7 +47,7 @@ def type(self) -> Dtype:
 
     @property
     def shape(self) -> tuple[int, ...] | None:
-        if self.type not in _TENSOR_ISH_DTYPES:
+        if self.dtype not in _TENSOR_ISH_DTYPES:
             return None
         fxnc = get_fxnc()
         dims = c_int32()
@@ -79,7 +79,7 @@ def serialize(self, mime: str=None) -> bytes:
         return result
 
     def to_object(self) -> Object:
-        match self.type:
+        match self.dtype:
             case Dtype.null:    return None
             case t if t in _TENSOR_DTYPES:
                 ctype = as_ctypes_type(dtype(t))
@@ -92,7 +92,7 @@ def to_object(self) -> Object:
                 data = as_array(cast(self.data, POINTER(c_uint8)), self.shape).copy()
                 return Image.fromarray(data.squeeze())
             case Dtype.binary:  return string_at(self.data, self.shape[0])
-            case _:             raise ValueError(f"Failed to convert value with type `{self.type}` to object because it is not supported")
+            case _:             raise ValueError(f"Failed to convert value with type `{self.dtype}` to object because it is not supported")
 
     def __enter__(self):
         return self

test/remote_test.py

@@ -24,7 +24,7 @@ def test_prediction_endpoint_create_eager():
     prediction = _prediction_endpoint_eager(payload)
     assert isinstance(prediction, RemotePrediction)
     assert isinstance(prediction.results, list)
-    assert prediction.results[0].type == Dtype.string
+    assert prediction.results[0].dtype == Dtype.string
 
 def test_prediction_endpoint_stream_eager():
     @prediction_endpoint(tag="@muna/greeting")
@@ -60,7 +60,7 @@ def test_prediction_endpoint_create_generator():
     prediction = _prediction_endpoint_generator(payload)
     assert isinstance(prediction, RemotePrediction)
     assert isinstance(prediction.results, list)
-    assert prediction.results[0].type == Dtype.string
+    assert prediction.results[0].dtype == Dtype.string
 
 def test_prediction_endpoint_stream_generator():
     payload = CreatePredictionInput(

test/value_test.py

@@ -27,5 +27,5 @@ def test_deserialize_png_to_image():
     image_data = Path("test/data/cat.jpg").read_bytes()
     image_value = Value.from_bytes(image_data, mime="image/*")
     # Check
-    assert image_value.type == Dtype.image
+    assert image_value.dtype == Dtype.image
     assert image_value.shape == (224, 224, 3)