def model_output_name(self) -> str:
"""Get output model name."""
output_name = self.model_name
if self.mode == Optimizations.TUNING:
output_name += "_tuned_" + self.output_precision
elif self.mode == Optimizations.GRAPH:
output_name = self.model_name + "_optimized_"
if self.tune:
output_name += "tuned_"
output_name += "_".join([
precision.strip()
for precision in self.output_precision.split(",")
], )
else:
raise ClientErrorException(f"Mode {self.mode} is not supported.")
return output_name + "." + get_file_extension(self.model_path)
def __init__(self, data: Dict[str, Any]):
"""Initialize Workload class."""
super().__init__()
self.config: Config = Config()
self.id: str = str(data.get("id", ""))
if not self.id:
raise ClientErrorException("Workload ID not specified.")
self.model_path: str = data.get("model_path", "")
if not self.model_path:
raise ClientErrorException("Model path is not defined!")
self.model_name = Path(self.model_path).stem
self.domain: str = data.get("domain", None)
if not self.domain:
raise ClientErrorException("Domain is not defined!")
self.framework: str = data.get(
"framework",
get_framework_from_path(self.model_path),
)
self.predefined_config_path = data.get(
"config_path",
get_predefined_config_path(self.framework, self.domain),
)
self.workspace_path = data.get(
"workspace_path",
os.path.dirname(self.model_path),
)
self.workload_path = data.get(
"workload_path",
os.path.join(
self.workspace_path,
"workloads",
f"{self.model_name}_{self.id}",
),
)
self.set_workspace()
self.config_name = "config.yaml"
self.config_path = os.path.join(
self.workload_path,
self.config_name,
)
model_output_name = (self.model_name + "_int8." +
get_file_extension(self.model_path))
self.model_output_path = os.path.join(
self.workload_path,
model_output_name,
)
self.eval_dataset_path: str = data.get("eval_dataset_path", "")
self.calib_dataset_path: str = data.get("eval_dataset_path", "")
self.set_dataset_paths(data)
for dataset_path in [self.eval_dataset_path, self.calib_dataset_path]:
if dataset_path != "no_dataset_location" and not os.path.exists(
dataset_path, ):
raise ClientErrorException(
f'Could not found dataset in specified location: "{dataset_path}".',
)
if not os.path.isfile(self.model_path):
raise ClientErrorException(
f'Could not found model in specified location: "{self.model_path}".',
)
self.accuracy_goal: float = data.get("accuracy_goal", 0.01)
if not os.path.isfile(self.config_path):
self.config.load(self.predefined_config_path)
else:
self.config.load(self.config_path)
self.config.model.name = self.model_name
self.config.set_evaluation_dataset_path(self.eval_dataset_path)
self.config.set_quantization_dataset_path(self.calib_dataset_path)
self.config.set_workspace(self.workload_path)
self.config.set_accuracy_goal(self.accuracy_goal)
def test_get_file_without_extension(self) -> None:
"""Test getting file extension from path."""
path = "/home/user/file"
result = get_file_extension(path)
self.assertEqual(result, "")
def test_get_file_with_dots_extension(self) -> None:
"""Test getting file extension from path."""
path = "/home/user/file.name.ext2"
result = get_file_extension(path)
self.assertEqual(result, "ext2")
def supports_path(path: str) -> bool:
"""Check if given path is of supported model."""
return "onnx" == get_file_extension(path)