2024-11-29 07:42:09 +00:00

64 lines
1.9 KiB
Python

from __future__ import annotations
from pathlib import Path
from typing import Any, List
import numpy as np
from numpy.typing import NDArray
from rknn.api import RKNN # Importing RKNN API
from app.models.constants import SUPPORTED_PROVIDERS
from app.schemas import SessionNode
from ..config import log, settings
class RknnSession:
def __init__(self, model_path: Path | str):
self.model_path = Path(model_path)
self.rknn = RKNN() # Initialize RKNN object
# Load the RKNN model
log.info(f"Loading RKNN model from {self.model_path}")
self._load_model()
def _load_model(self) -> None:
ret = self.rknn.load_rknn(self.model_path.as_posix())
if ret != 0:
raise RuntimeError("Failed to load RKNN model")
ret = self.rknn.init_runtime()
if ret != 0:
raise RuntimeError("Failed to initialize RKNN runtime")
def get_inputs(self) -> List[SessionNode]:
input_attrs = self.rknn.query_inputs()
return input_attrs # RKNN does not provide direct SessionNode equivalent
def get_outputs(self) -> List[SessionNode]:
output_attrs = self.rknn.query_outputs()
return output_attrs
def run(
self,
input_feed: dict[str, NDArray[np.float32] | NDArray[np.int32]],
) -> List[NDArray[np.float32]]:
inputs = [v for v in input_feed.values()]
# Run inference
log.debug(f"Running inference on RKNN model")
ret, outputs = self.rknn.inference(inputs=inputs)
if ret != 0:
raise RuntimeError("Inference failed")
return outputs
def release(self) -> None:
log.info("Releasing RKNN resources")
self.rknn.release()
# Example Usage:
# session = RknnSession(model_path="path/to/model.rknn")
# outputs = session.run(input_feed={"input_name": input_data})
# session.release()