DeploymentSettings_ONNXRuntime_ONNX
CLASS - DeploymentSettings_ONNXRuntime_ONNX(
- graph_author:
Optional[str]
= None- graph_description:
Optional[str]
= None- input_shapes_for_deployment:
Union[list, tuple, List[list], List[tuple], Tuple[tuple], Tuple[list], None]
= None- utilize_full_int_range:
bool
= False)
Ancestors - (BaseDeploymentSettings
)
Use this if you wish to deploy to ONNXRuntime in Settings.deployment_settings
.
Class Variables
- graph_author (
Optional[str]
) - Name of the Author of the Graph to attach to the final Model File. - graph_description (
Optional[str]
) - Any description that should be attached to the final Model file - input_shapes_for_deployment (
Union[list, tuple, List[list], List[tuple], Tuple[tuple], Tuple[list], None]
) - Shapes to use for the deployment of the final Model file. Spatial Dimensions can be None if your model does not depend on it. For example, OK: Conv2d(...) AdaptiveAvgPool(output_size=(1,1)) Flatten() Linear() or Fully Convolutional model NOT OK: Conv2d(...) Flatten() Linear() - utilize_full_int_range (
bool
) - Set to True if you're planning to run the model on a CPU that supports AVX512-VNNI.
See Also
DeploymentSettings_TFLite
CLASS - DeploymentSettings_TFLite(
- graph_author:
Optional[str]
= None- graph_description:
Optional[str]
= None- input_shapes_for_deployment:
Union[list, tuple, List[list], List[tuple], Tuple[tuple], Tuple[list], None]
= None)
Ancestors - (BaseDeploymentSettings
)
Use this if you wish to deploy to TFLite in Settings.deployment_settings
.
Class Variables
- graph_author (
Optional[str]
) - Name of the Author of the Graph to attach to the final Model File. - graph_description (
Optional[str]
) - Any description that should be attached to the final Model file - input_shapes_for_deployment (
Union[list, tuple, List[list], List[tuple], Tuple[tuple], Tuple[list], None]
) - Shapes to use for the deployment of the final Model file. Spatial Dimensions can be None if your model does not depend on it. For example, OK: Conv2d(...) AdaptiveAvgPool(output_size=(1,1)) Flatten() Linear() or Fully Convolutional model NOT OK: Conv2d(...) Flatten() Linear()
DeploymentSettings_TensorRT_ONNX
CLASS - DeploymentSettings_TensorRT_ONNX(
- graph_author:
Optional[str]
= None- graph_description:
Optional[str]
= None- input_shapes_for_deployment:
Union[list, tuple, List[list], List[tuple], Tuple[tuple], Tuple[list], None]
= None)
Ancestors - (BaseDeploymentSettings
)
Use this if you wish to deploy to TensorRT in Settings.deployment_settings
.
Class Variables
- graph_author (
Optional[str]
) - Name of the Author of the Graph to attach to the final Model File. - graph_description (
Optional[str]
) - Any description that should be attached to the final Model file - input_shapes_for_deployment (
Union[list, tuple, List[list], List[tuple], Tuple[tuple], Tuple[list], None]
) - Shapes to use for the deployment of the final Model file. Spatial Dimensions can be None if your model does not depend on it. For example, OK: Conv2d(...) AdaptiveAvgPool(output_size=(1,1)) Flatten() Linear() or Fully Convolutional model NOT OK: Conv2d(...) Flatten() Linear()