Revert "Add float16 Vector Approve"

pymilvus/client/entity_helper.py

@@ -122,9 +122,6 @@ def pack_field_value_to_field_data(field_value: Any, field_data: Any, field_info
     elif field_type == DataType.BINARY_VECTOR:
         field_data.vectors.dim = len(field_value) * 8
         field_data.vectors.binary_vector += bytes(field_value)
-    elif field_type == DataType.FLOAT16_VECTOR:
-        field_data.vectors.dim = len(field_value) // 2
-        field_data.vectors.float16_vector += bytes(field_value)
     elif field_type == DataType.VARCHAR:
         field_data.scalars.string_data.data.append(
             convert_to_str_array(field_value, field_info, CHECK_STR_ARRAY)

pymilvus/client/types.py

@@ -87,7 +87,6 @@ class DataType(IntEnum):
 
     BINARY_VECTOR = 100
     FLOAT_VECTOR = 101
-    FLOAT16_VECTOR = 102
 
     UNKNOWN = 999
 
@@ -155,7 +154,6 @@ class PlaceholderType(IntEnum):
     NoneType = 0
     BinaryVector = 100
     FloatVector = 101
-    Float16Vector = 102
 
 
 class State(IntEnum):

pymilvus/orm/schema.py

@@ -288,7 +288,6 @@ def _parse_type_params(self):
         if self._dtype not in (
             DataType.BINARY_VECTOR,
             DataType.FLOAT_VECTOR,
-            DataType.FLOAT16_VECTOR,
             DataType.VARCHAR,
             DataType.ARRAY,
         ):
@@ -494,16 +493,10 @@ def prepare_fields_from_dataframe(df: pd.DataFrame):
         for i, dtype in enumerate(data_types):
             if dtype == DataType.UNKNOWN:
                 new_dtype = infer_dtype_bydata(values[i])
-                if new_dtype in (
-                    DataType.BINARY_VECTOR,
-                    DataType.FLOAT_VECTOR,
-                    DataType.FLOAT16_VECTOR,
-                ):
+                if new_dtype in (DataType.BINARY_VECTOR, DataType.FLOAT_VECTOR):
                     vector_type_params = {}
                     if new_dtype == DataType.BINARY_VECTOR:
                         vector_type_params["dim"] = len(values[i]) * 8
-                    elif new_dtype == DataType.FLOAT16_VECTOR:
-                        vector_type_params["dim"] = len(values[i]) / 2
                     else:
                         vector_type_params["dim"] = len(values[i])
                     column_params_map[col_names[i]] = vector_type_params
@@ -522,7 +515,7 @@ def check_schema(schema: CollectionSchema):
         raise SchemaNotReadyException(message=ExceptionsMessage.EmptySchema)
     vector_fields = []
     for field in schema.fields:
-        if field.dtype in (DataType.FLOAT_VECTOR, DataType.BINARY_VECTOR, DataType.FLOAT16_VECTOR):
+        if field.dtype in (DataType.FLOAT_VECTOR, DataType.BINARY_VECTOR):
             vector_fields.append(field.name)
     if len(vector_fields) < 1:
         raise SchemaNotReadyException(message=ExceptionsMessage.NoVector)

tests/test_abstract.py

@@ -168,12 +168,6 @@ def test_search_result_with_fields_data(self, pk):
                     binary_vector=os.urandom(6),
                 ),
             ),
-            schema_pb2.FieldData(type=DataType.FLOAT16_VECTOR, field_name="float16_vector_field", field_id=115,
-                vectors=schema_pb2.VectorField(
-                    dim=16,
-                    float16_vector=os.urandom(32),
-                ),
-            ),
         ]
         result = schema_pb2.SearchResultData(
             fields_data=fields_data,

tests/test_collection.py

@@ -27,8 +27,7 @@ def test_collection_by_DataFrame(self):
         fields = [
             FieldSchema("int64", DataType.INT64),
             FieldSchema("float", DataType.FLOAT),
-            FieldSchema("float_vector", DataType.FLOAT_VECTOR, dim=128),
-            FieldSchema("float16_vector", DataType.FLOAT16_VECTOR, dim=128)
+            FieldSchema("float_vector", DataType.FLOAT_VECTOR, dim=128)
         ]
 
         prefix = "pymilvus.client.grpc_handler.GrpcHandler"

tests/test_create_collection.py

@@ -118,45 +118,3 @@ def test_create_collection(self, collection_name):
         return_value = future.result()
         assert return_value.code == 0
         assert return_value.reason == "success"
-
-    def test_create_fp16_collection(self, collection_name):
-        id_field = {
-            "name": "my_id",
-            "type": DataType.INT64,
-            "auto_id": True,
-            "is_primary": True,
-        }
-        vector_field = {
-            "name": "embedding",
-            "type": DataType.FLOAT16_VECTOR,
-            "metric_type": "L2",
-            "params": {"dim": "4"},
-        }
-        fields = {"fields": [id_field, vector_field], "enable_dynamic_field": True}
-        future = self._milvus.create_collection(
-            collection_name=collection_name, fields=fields, _async=True
-        )
-
-        invocation_metadata, request, rpc = self._real_time_channel.take_unary_unary(
-            self._servicer.methods_by_name["CreateCollection"]
-        )
-        rpc.send_initial_metadata(())
-        rpc.terminate(
-            common_pb2.Status(
-                code=ErrorCode.SUCCESS, error_code=common_pb2.Success, reason="success"
-            ),
-            (),
-            grpc.StatusCode.OK,
-            "",
-        )
-
-        request_schema = schema_pb2.CollectionSchema()
-        request_schema.ParseFromString(request.schema)
-
-        assert request.collection_name == collection_name
-        assert Fields.equal(request_schema.fields, fields["fields"])
-        assert request_schema.enable_dynamic_field == fields["enable_dynamic_field"]
-
-        return_value = future.result()
-        assert return_value.code == 0
-        assert return_value.reason == "success"

tests/test_schema.py

@@ -74,15 +74,6 @@ def raw_dict_binary_vector(self):
         _dict["params"] = {"dim": 128}
         return _dict
 
-    @pytest.fixture(scope="function")
-    def raw_dict_float16_vector(self):
-        _dict = dict()
-        _dict["name"] = "TestFieldSchema_name_float16_vector"
-        _dict["description"] = "TestFieldSchema_description_float16_vector"
-        _dict["type"] = DataType.FLOAT16_VECTOR
-        _dict["params"] = {"dim": 128}
-        return _dict
-
     @pytest.fixture(scope="function")
     def raw_dict_norm(self):
         _dict = dict()
@@ -102,14 +93,6 @@ def dataframe1(self):
         df1 = pandas.DataFrame(data)
         return df1
 
-    def test_constructor_from_float16_dict(self, raw_dict_float16_vector):
-        field = FieldSchema.construct_from_dict(raw_dict_float16_vector)
-        assert field.dtype == DataType.FLOAT16_VECTOR
-        assert field.description == raw_dict_float16_vector['description']
-        assert field.is_primary is False
-        assert field.name == raw_dict_float16_vector['name']
-        assert field.dim == raw_dict_float16_vector['params']['dim']
-
     def test_constructor_from_float_dict(self, raw_dict_float_vector):
         field = FieldSchema.construct_from_dict(raw_dict_float_vector)
         assert field.dtype == DataType.FLOAT_VECTOR

tests/test_types.py

@@ -83,8 +83,7 @@ def test_infer_dtype_bydata(self):
             "abc",
             np.int8(1),
             np.int16(1),
-            [np.int8(1)],
-            [np.float16(1.0)]
+            [np.int8(1)]
         ]
 
         wants = [
@@ -99,7 +98,6 @@ def test_infer_dtype_bydata(self):
             DataType.INT8,
             DataType.INT16,
             DataType.FLOAT_VECTOR,
-            DataType.FLOAT16_VECTOR,
         ]
 
         actual = []