Deal with custom field validation

Author: Val Brodsky

libs/labelbox/src/labelbox/data/annotation_types/types.py

@@ -7,7 +7,7 @@
 from packaging import version
 import numpy as np
 
-from pydantic import Field
+from pydantic import ValidationInfo
 
 Cuid = Annotated[str, StringConstraints(min_length=25, max_length=25)]
 
@@ -22,14 +22,11 @@ def __get_validators__(cls):
         yield cls.validate
 
     @classmethod
-    def validate(cls, val, field: pydantic_compat.ModelField):
+    def validate(cls, val, field: ValidationInfo):
         if not isinstance(val, np.ndarray):
             raise TypeError(f"Expected numpy array. Found {type(val)}")
 
-        if sys.version_info.minor > 6:
-            actual_dtype = field.sub_fields[-1].type_.__args__[0]
-        else:
-            actual_dtype = field.sub_fields[-1].type_.__values__[0]
+        actual_dtype = field.sub_fields[-1].type_.__args__[0]
 
         if val.dtype != actual_dtype:
             raise TypeError(

libs/labelbox/src/labelbox/schema/data_row_metadata.py

@@ -40,9 +40,8 @@ class DataRowMetadataSchema(BaseModel):
 
 DataRowMetadataSchema.update_forward_refs()
 
-Embedding: Type[List[float]] = Annotated[List[float], Field(
-                                                       min_items=128,
-                                                       max_items=128)]
+Embedding: Type[List[float]] = Annotated[List[float],
+                                         Field(min_items=128, max_items=128)]
 String: Type[str] = Annotated[List[str], Field(max_length=4096)]