Package
model_navigator.package.package
Package module - structure to snapshot optimization result.
Package
Class for storing pipeline execution status.
Initialize object.
Parameters:
-
status
(
Status
) –A navigator execution status
-
workspace
(
Workspace
) –Workspace for package files
-
model
(
Optional[object]
) –An optional model
Source code in model_navigator/package/package.py
config
property
Generate configuration from package.
Returns:
-
CommonConfig
–The configuration object
framework
property
Framework for which package was created.
Returns:
-
Framework
–Framework object for package
_create_status_file
Create a status.yaml file for package.
Source code in model_navigator/package/package.py
_delete_status_file
_get_custom_configs
Build custom configs from config data.
Parameters:
-
custom_configs
(
Dict[str, Union[Dict, CustomConfigForFormat]]
) –Dictionary with custom configs data
Returns:
-
Dict
–List with mapped objects
Source code in model_navigator/package/package.py
_get_runner
Load runner.
Parameters:
-
model_key
(
str
) –Unique key of the model.
-
runner_name
(
str
) –Name of the runner.
-
return_type
(
TensorType
) –Type of the runner output.
Returns:
-
NavigatorRunner
–NavigatorRunner object
Source code in model_navigator/package/package.py
get_best_model_status
Returns ModelStatus of best model for given strategy.
Parameters:
-
strategy
(
Optional[RuntimeSearchStrategy]
) –Strategy for finding the best runtime. Defaults to
MaxThroughputAndMinLatencyStrategy
. -
include_source
(
bool
) –Flag if Python based model has to be included in analysis
Returns:
-
ModelStatus
–ModelStatus of best model for given strategy or None.
Source code in model_navigator/package/package.py
get_model_path
Return path of the model.
Parameters:
-
model_key
(
str
) –Unique key of the model.
Raises:
-
ModelNavigatorNotFoundError
–When model not found.
Returns:
Source code in model_navigator/package/package.py
get_runner
Get the runner according to the strategy.
Parameters:
-
strategy
(
Optional[RuntimeSearchStrategy]
) –Strategy for finding the best runtime. Defaults to
MaxThroughputAndMinLatencyStrategy
. -
include_source
(
bool
) –Flag if Python based model has to be included in analysis
-
return_type
(
TensorType
) –The type of the output tensor. Defaults to
TensorType.NUMPY
. If the return_type supports CUDA tensors (e.g. TensorType.TORCH) and the input tensors are on CUDA, there will be no additional data transfer between CPU and GPU.
Returns:
-
NavigatorRunner
–The optimal runner for the optimized model.
Source code in model_navigator/package/package.py
is_empty
Validate if package is empty - no models were produced.
Returns:
-
bool
–True if empty package, False otherwise.
Source code in model_navigator/package/package.py
load_source_model
Load model defined in Python code.
Parameters:
-
model
(
object
) –A model object