mirror of
https://github.com/immich-app/immich.git
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93 lines
2.8 KiB
Python
93 lines
2.8 KiB
Python
# This code is from leafqycc/rknn-multi-threaded
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# Following Apache License 2.0
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import os
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from concurrent.futures import ThreadPoolExecutor
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from queue import Queue
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import numpy as np
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from typing import Callable
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from numpy.typing import NDArray
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from app.config import log
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supported_socs = ["rk3566", "rk3588"]
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coremask_supported_socs = ["rk3576","rk3588"]
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try:
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from rknnlite.api import RKNNLite
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with open("/proc/device-tree/compatible") as f:
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device_compatible_str = f.read()
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for soc in supported_socs:
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if soc in device_compatible_str:
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is_available = True
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soc_name = soc
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break
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else:
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is_available = False
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soc_name = None
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is_available = is_available and os.path.exists("/sys/kernel/debug/rknpu/load")
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except (FileNotFoundError, ImportError):
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log.debug("RKNN is not available")
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is_available = False
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soc_name = None
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def init_rknn(rknnModel, id) -> Callable:
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if not is_available:
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raise RuntimeError("rknn is not available!")
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rknn_lite = RKNNLite()
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ret = rknn_lite.load_rknn(rknnModel)
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if ret != 0:
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raise RuntimeError("Load RKNN rknnModel failed")
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if soc_name in coremask_supported_socs:
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if id == 0:
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ret = rknn_lite.init_runtime(core_mask=RKNNLite.NPU_CORE_0)
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elif id == 1:
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ret = rknn_lite.init_runtime(core_mask=RKNNLite.NPU_CORE_1)
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elif id == 2:
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ret = rknn_lite.init_runtime(core_mask=RKNNLite.NPU_CORE_2)
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elif id == -1:
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ret = rknn_lite.init_runtime(core_mask=RKNNLite.NPU_CORE_0_1_2)
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else:
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ret = rknn_lite.init_runtime()
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else:
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ret = rknn_lite.init_runtime() # Please do not set this parameter on other platforms.
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if ret != 0:
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raise RuntimeError("Init runtime environment failed")
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return rknn_lite
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def init_rknns(rknnModel, tpes) -> list[Callable]:
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rknn_list = []
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for i in range(tpes):
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rknn_list.append(init_rknn(rknnModel, i % 3))
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return rknn_list
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class RknnPoolExecutor:
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def __init__(self, rknnModel: str, tpes: int, func):
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self.tpes = tpes
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self.queue = Queue()
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self.rknn_pool = init_rknns(rknnModel, tpes)
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self.pool = ThreadPoolExecutor(max_workers=tpes)
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self.func = func
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self.num = 0
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def put(self, inputs) -> None:
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self.queue.put(self.pool.submit(self.func, self.rknn_pool[self.num % self.tpes], inputs))
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self.num += 1
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def get(self) -> list[list[NDArray[np.float32]], bool]:
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if self.queue.empty():
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return None
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fut = self.queue.get()
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return fut.result()
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def release(self) -> None:
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self.pool.shutdown()
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for rknn_lite in self.rknn_pool:
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rknn_lite.release()
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