wallaroo.wallaroo_ml_ops_api_client.models.v1_model_get_model_by_id_response_200_model_config
1from typing import Any, Dict, List, Type, TypeVar, Union 2 3import attr 4 5from ..models.v1_model_get_model_by_id_response_200_model_config_tensor_fields import \ 6 V1ModelGetModelByIdResponse200ModelConfigTensorFields 7from ..types import UNSET, Unset 8 9T = TypeVar("T", bound="V1ModelGetModelByIdResponse200ModelConfig") 10 11@attr.s(auto_attribs=True) 12class V1ModelGetModelByIdResponse200ModelConfig: 13 """ A possible Model Configuration 14 15 Attributes: 16 id (int): The primary id of the model configuration. 17 runtime (str): The model configuration runtime. 18 tensor_fields (Union[Unset, None, V1ModelGetModelByIdResponse200ModelConfigTensorFields]): Optional Tensor 19 Fields for the model. 20 filter_threshold (Union[Unset, None, float]): An optional filter threshold 21 """ 22 23 id: int 24 runtime: str 25 tensor_fields: Union[Unset, None, V1ModelGetModelByIdResponse200ModelConfigTensorFields] = UNSET 26 filter_threshold: Union[Unset, None, float] = UNSET 27 additional_properties: Dict[str, Any] = attr.ib(init=False, factory=dict) 28 29 30 def to_dict(self) -> Dict[str, Any]: 31 id = self.id 32 runtime = self.runtime 33 tensor_fields: Union[Unset, None, Dict[str, Any]] = UNSET 34 if not isinstance(self.tensor_fields, Unset): 35 tensor_fields = self.tensor_fields.to_dict() if self.tensor_fields else None 36 37 filter_threshold = self.filter_threshold 38 39 field_dict: Dict[str, Any] = {} 40 field_dict.update(self.additional_properties) 41 field_dict.update({ 42 "id": id, 43 "runtime": runtime, 44 }) 45 if tensor_fields is not UNSET: 46 field_dict["tensor_fields"] = tensor_fields 47 if filter_threshold is not UNSET: 48 field_dict["filter_threshold"] = filter_threshold 49 50 return field_dict 51 52 53 54 @classmethod 55 def from_dict(cls: Type[T], src_dict: Dict[str, Any]) -> T: 56 d = src_dict.copy() 57 id = d.pop("id") 58 59 runtime = d.pop("runtime") 60 61 _tensor_fields = d.pop("tensor_fields", UNSET) 62 tensor_fields: Union[Unset, None, V1ModelGetModelByIdResponse200ModelConfigTensorFields] 63 if _tensor_fields is None: 64 tensor_fields = None 65 elif isinstance(_tensor_fields, Unset): 66 tensor_fields = UNSET 67 else: 68 tensor_fields = V1ModelGetModelByIdResponse200ModelConfigTensorFields.from_dict(_tensor_fields) 69 70 71 72 73 filter_threshold = d.pop("filter_threshold", UNSET) 74 75 v1_model_get_model_by_id_response_200_model_config = cls( 76 id=id, 77 runtime=runtime, 78 tensor_fields=tensor_fields, 79 filter_threshold=filter_threshold, 80 ) 81 82 v1_model_get_model_by_id_response_200_model_config.additional_properties = d 83 return v1_model_get_model_by_id_response_200_model_config 84 85 @property 86 def additional_keys(self) -> List[str]: 87 return list(self.additional_properties.keys()) 88 89 def __getitem__(self, key: str) -> Any: 90 return self.additional_properties[key] 91 92 def __setitem__(self, key: str, value: Any) -> None: 93 self.additional_properties[key] = value 94 95 def __delitem__(self, key: str) -> None: 96 del self.additional_properties[key] 97 98 def __contains__(self, key: str) -> bool: 99 return key in self.additional_properties
@attr.s(auto_attribs=True)
class
V1ModelGetModelByIdResponse200ModelConfig:
12@attr.s(auto_attribs=True) 13class V1ModelGetModelByIdResponse200ModelConfig: 14 """ A possible Model Configuration 15 16 Attributes: 17 id (int): The primary id of the model configuration. 18 runtime (str): The model configuration runtime. 19 tensor_fields (Union[Unset, None, V1ModelGetModelByIdResponse200ModelConfigTensorFields]): Optional Tensor 20 Fields for the model. 21 filter_threshold (Union[Unset, None, float]): An optional filter threshold 22 """ 23 24 id: int 25 runtime: str 26 tensor_fields: Union[Unset, None, V1ModelGetModelByIdResponse200ModelConfigTensorFields] = UNSET 27 filter_threshold: Union[Unset, None, float] = UNSET 28 additional_properties: Dict[str, Any] = attr.ib(init=False, factory=dict) 29 30 31 def to_dict(self) -> Dict[str, Any]: 32 id = self.id 33 runtime = self.runtime 34 tensor_fields: Union[Unset, None, Dict[str, Any]] = UNSET 35 if not isinstance(self.tensor_fields, Unset): 36 tensor_fields = self.tensor_fields.to_dict() if self.tensor_fields else None 37 38 filter_threshold = self.filter_threshold 39 40 field_dict: Dict[str, Any] = {} 41 field_dict.update(self.additional_properties) 42 field_dict.update({ 43 "id": id, 44 "runtime": runtime, 45 }) 46 if tensor_fields is not UNSET: 47 field_dict["tensor_fields"] = tensor_fields 48 if filter_threshold is not UNSET: 49 field_dict["filter_threshold"] = filter_threshold 50 51 return field_dict 52 53 54 55 @classmethod 56 def from_dict(cls: Type[T], src_dict: Dict[str, Any]) -> T: 57 d = src_dict.copy() 58 id = d.pop("id") 59 60 runtime = d.pop("runtime") 61 62 _tensor_fields = d.pop("tensor_fields", UNSET) 63 tensor_fields: Union[Unset, None, V1ModelGetModelByIdResponse200ModelConfigTensorFields] 64 if _tensor_fields is None: 65 tensor_fields = None 66 elif isinstance(_tensor_fields, Unset): 67 tensor_fields = UNSET 68 else: 69 tensor_fields = V1ModelGetModelByIdResponse200ModelConfigTensorFields.from_dict(_tensor_fields) 70 71 72 73 74 filter_threshold = d.pop("filter_threshold", UNSET) 75 76 v1_model_get_model_by_id_response_200_model_config = cls( 77 id=id, 78 runtime=runtime, 79 tensor_fields=tensor_fields, 80 filter_threshold=filter_threshold, 81 ) 82 83 v1_model_get_model_by_id_response_200_model_config.additional_properties = d 84 return v1_model_get_model_by_id_response_200_model_config 85 86 @property 87 def additional_keys(self) -> List[str]: 88 return list(self.additional_properties.keys()) 89 90 def __getitem__(self, key: str) -> Any: 91 return self.additional_properties[key] 92 93 def __setitem__(self, key: str, value: Any) -> None: 94 self.additional_properties[key] = value 95 96 def __delitem__(self, key: str) -> None: 97 del self.additional_properties[key] 98 99 def __contains__(self, key: str) -> bool: 100 return key in self.additional_properties
A possible Model Configuration
Attributes: id (int): The primary id of the model configuration. runtime (str): The model configuration runtime. tensor_fields (Union[Unset, None, V1ModelGetModelByIdResponse200ModelConfigTensorFields]): Optional Tensor Fields for the model. filter_threshold (Union[Unset, None, float]): An optional filter threshold
V1ModelGetModelByIdResponse200ModelConfig( id: int, runtime: str, tensor_fields: Union[wallaroo.wallaroo_ml_ops_api_client.types.Unset, NoneType, wallaroo.wallaroo_ml_ops_api_client.models.v1_model_get_model_by_id_response_200_model_config_tensor_fields.V1ModelGetModelByIdResponse200ModelConfigTensorFields] = <wallaroo.wallaroo_ml_ops_api_client.types.Unset object>, filter_threshold: Union[wallaroo.wallaroo_ml_ops_api_client.types.Unset, NoneType, float] = <wallaroo.wallaroo_ml_ops_api_client.types.Unset object>)
2def __init__(self, id, runtime, tensor_fields=attr_dict['tensor_fields'].default, filter_threshold=attr_dict['filter_threshold'].default): 3 self.id = id 4 self.runtime = runtime 5 self.tensor_fields = tensor_fields 6 self.filter_threshold = filter_threshold 7 self.additional_properties = __attr_factory_additional_properties()
Method generated by attrs for class V1ModelGetModelByIdResponse200ModelConfig.
def
to_dict(self) -> Dict[str, Any]:
31 def to_dict(self) -> Dict[str, Any]: 32 id = self.id 33 runtime = self.runtime 34 tensor_fields: Union[Unset, None, Dict[str, Any]] = UNSET 35 if not isinstance(self.tensor_fields, Unset): 36 tensor_fields = self.tensor_fields.to_dict() if self.tensor_fields else None 37 38 filter_threshold = self.filter_threshold 39 40 field_dict: Dict[str, Any] = {} 41 field_dict.update(self.additional_properties) 42 field_dict.update({ 43 "id": id, 44 "runtime": runtime, 45 }) 46 if tensor_fields is not UNSET: 47 field_dict["tensor_fields"] = tensor_fields 48 if filter_threshold is not UNSET: 49 field_dict["filter_threshold"] = filter_threshold 50 51 return field_dict
@classmethod
def
from_dict(cls: Type[~T], src_dict: Dict[str, Any]) -> ~T:
55 @classmethod 56 def from_dict(cls: Type[T], src_dict: Dict[str, Any]) -> T: 57 d = src_dict.copy() 58 id = d.pop("id") 59 60 runtime = d.pop("runtime") 61 62 _tensor_fields = d.pop("tensor_fields", UNSET) 63 tensor_fields: Union[Unset, None, V1ModelGetModelByIdResponse200ModelConfigTensorFields] 64 if _tensor_fields is None: 65 tensor_fields = None 66 elif isinstance(_tensor_fields, Unset): 67 tensor_fields = UNSET 68 else: 69 tensor_fields = V1ModelGetModelByIdResponse200ModelConfigTensorFields.from_dict(_tensor_fields) 70 71 72 73 74 filter_threshold = d.pop("filter_threshold", UNSET) 75 76 v1_model_get_model_by_id_response_200_model_config = cls( 77 id=id, 78 runtime=runtime, 79 tensor_fields=tensor_fields, 80 filter_threshold=filter_threshold, 81 ) 82 83 v1_model_get_model_by_id_response_200_model_config.additional_properties = d 84 return v1_model_get_model_by_id_response_200_model_config