float scalar datatype supports floating-point numbers (#3172)

Signed-off-by: wangting0128 <ting.wang@zilliz.com>

Author: wangting0128

pymilvus/orm/schema.py

@@ -482,7 +482,9 @@ def __init__(self, name: str, dtype: DataType, description: str = "", **kwargs)
             if self.default_value.WhichOneof("data") is None:
                 self.default_value = None
         else:
-            self.default_value = infer_default_value_bydata(kwargs.get("default_value"))
+            self.default_value = infer_default_value_bydata(
+                kwargs.get("default_value"), dtype=self._dtype
+            )
         self.element_type = kwargs.get("element_type")
         if "mmap_enabled" in kwargs:
             self._type_params["mmap_enabled"] = kwargs["mmap_enabled"]
@@ -1211,13 +1213,13 @@ def check_schema(schema: CollectionSchema):
         raise SchemaNotReadyException(message=ExceptionsMessage.NoVector)
 
 
-def infer_default_value_bydata(data: Any):
+def infer_default_value_bydata(data: Any, dtype: DataType = None):
     if data is None:
         return None
     default_data = schema_types.ValueField()
     d_type = DataType.UNKNOWN
     if is_scalar(data):
-        d_type = infer_dtype_by_scalar_data(data)
+        d_type = infer_dtype_by_scalar_data(data, dtype)
     if d_type is DataType.BOOL:
         default_data.bool_data = data
     elif d_type in (DataType.INT8, DataType.INT16, DataType.INT32):

pymilvus/orm/types.py

@@ -71,10 +71,10 @@ def is_numeric_datatype(data_type: DataType):
     return is_float_datatype(data_type) or is_integer_datatype(data_type)
 
 
-def infer_dtype_by_scalar_data(data: Any):
+def infer_dtype_by_scalar_data(data: Any, dtype: DataType = None):
     if isinstance(data, list):
         return DataType.ARRAY
-    if isinstance(data, np.float32):
+    if isinstance(data, np.float32) or (is_float(data) and dtype == DataType.FLOAT):
         return DataType.FLOAT
     if isinstance(data, (float, np.float64, np.double)) or is_float(data):
         return DataType.DOUBLE