mirror of
https://github.com/azaion/detections.git
synced 2026-06-23 13:21:08 +00:00
Oleksandr Bezdieniezhnykh
8116b55813
- Updated the autopilot state to reflect the current task status as in progress. - Refactored the inference module to streamline model downloading and conversion processes, replacing the download_model method with a more efficient load_source method. - Introduced asynchronous model building in the inference module to enhance performance during model conversion. - Enhanced the engine factory to include a new method for building and caching models, improving error handling and logging during the upload process. - Added calibration cache handling in the Jetson TensorRT engine for better resource management. Made-with: Cursor
40 lines
1.5 KiB
Cython
40 lines
1.5 KiB
Cython
import os
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import tempfile
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from engines.tensorrt_engine cimport TensorRTEngine
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from loader_http_client cimport LoaderHttpClient, LoadResult
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cdef class JetsonTensorRTEngine(TensorRTEngine):
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@staticmethod
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def convert_from_source(bytes onnx_model, LoaderHttpClient loader_client, str models_dir):
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cdef str calib_cache_path
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calib_cache_path = JetsonTensorRTEngine._download_calib_cache(loader_client, models_dir)
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try:
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return TensorRTEngine.convert_from_source(onnx_model, calib_cache_path)
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finally:
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if calib_cache_path is not None:
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try:
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os.unlink(calib_cache_path)
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except Exception:
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pass
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@staticmethod
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def _download_calib_cache(LoaderHttpClient loader_client, str models_dir):
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cdef LoadResult res
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import constants_inf
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try:
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res = loader_client.load_big_small_resource(
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constants_inf.INT8_CALIB_CACHE_FILE, models_dir
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)
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if res.err is not None:
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constants_inf.log(f"INT8 calibration cache not available: {res.err}")
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return None
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fd, path = tempfile.mkstemp(suffix=".cache")
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with os.fdopen(fd, "wb") as f:
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f.write(res.data)
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constants_inf.log("INT8 calibration cache downloaded")
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return path
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except Exception as e:
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constants_inf.log(f"INT8 calibration cache download failed: {str(e)}")
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return None
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