When I tried to compile yolov8m’s hef using model zoo today, an error occurred. can you help me 
<Hailo Model Zoo INFO> Start run for network yolov8m ...
<Hailo Model Zoo INFO> Initializing the hailo8 runner...
[info] Translation started on ONNX model yolov8m
[info] Restored ONNX model yolov8m (completion time: 00:00:00.43)
[info] Extracted ONNXRuntime meta-data for Hailo model (completion time: 00:00:02.35)
[info] NMS structure of yolov8 (or equivalent architecture) was detected.
[info] In order to use HailoRT post-processing capabilities, these end node names should be used: /model.22/cv2.0/cv2.0.2/Conv /model.22/cv3.0/cv3.0.2/Conv /model.22/cv2.1/cv2.1.2/Conv /model.22/cv3.1/cv3.1.2/Conv /model.22/cv2.2/cv2.2.2/Conv /model.22/cv3.2/cv3.2.2/Conv.
[info] Start nodes mapped from original model: 'images': 'yolov8m/input_layer1'.
[info] End nodes mapped from original model: '/model.22/cv2.0/cv2.0.2/Conv', '/model.22/cv3.0/cv3.0.2/Conv', '/model.22/cv2.1/cv2.1.2/Conv', '/model.22/cv3.1/cv3.1.2/Conv', '/model.22/cv2.2/cv2.2.2/Conv', '/model.22/cv3.2/cv3.2.2/Conv'.
[info] Translation completed on ONNX model yolov8m (completion time: 00:00:03.80)
[info] Saved HAR to: /home/deepvision/deepvision/Pictures/相机设备1/imgs/result/20241113-223939/weights/yolov8m.har
<Hailo Model Zoo INFO> Preparing calibration data...
[info] Loading model script commands to yolov8m from /root/hailo_model_zoo/hailo_model_zoo/cfg/alls/generic/yolov8m.alls
[info] Loading model script commands to yolov8m from string
[info] Starting Model Optimization
[warning] Reducing optimization level to 1 (the accuracy won't be optimized and compression won't be used) because there's less data than the recommended amount (1024)
[info] Model received quantization params from the hn
[info] Starting Mixed Precision
[info] Mixed Precision is done (completion time is 00:00:00.88)
[info] Layer Norm Decomposition skipped
[info] Starting Stats Collector
[info] Using dataset with 64 entries for calibration
Calibration: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 64/64 [00:27<00:00, 2.32entries/s]
[info] Stats Collector is done (completion time is 00:00:30.24)
[warning] The force_range command has been used, notice that its behavior was changed on this version. The old behavior forced the range on the collected calibration set statistics, but allowed the range to change during the optimization algorithms.
The new behavior forces the range throughout all optimization stages.
The old method could be restored by adding the flag weak_force_range_out=enabled to the force_range command on the following layers ['yolov8m/conv42', 'yolov8m/conv53', 'yolov8m/conv63']
Traceback (most recent call last):
File "/root/hailo_venv/bin/hailomz", line 33, in <module>
sys.exit(load_entry_point('hailo-model-zoo', 'console_scripts', 'hailomz')())
File "/root/hailo_model_zoo/hailo_model_zoo/main.py", line 122, in main
run(args)
File "/root/hailo_model_zoo/hailo_model_zoo/main.py", line 111, in run
return handlers[args.command](args)
File "/root/hailo_model_zoo/hailo_model_zoo/main_driver.py", line 250, in compile
_ensure_optimized(runner, logger, args, network_info)
File "/root/hailo_model_zoo/hailo_model_zoo/main_driver.py", line 91, in _ensure_optimized
optimize_model(
File "/root/hailo_model_zoo/hailo_model_zoo/core/main_utils.py", line 326, in optimize_model
runner.optimize(calib_feed_callback)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_sdk_common/states/states.py", line 16, in wrapped_func
return func(self, *args, **kwargs)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_sdk_client/runner/client_runner.py", line 2093, in optimize
self._optimize(calib_data, data_type=data_type, work_dir=work_dir)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_sdk_common/states/states.py", line 16, in wrapped_func
return func(self, *args, **kwargs)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_sdk_client/runner/client_runner.py", line 1935, in _optimize
self._sdk_backend.full_quantization(calib_data, data_type=data_type, work_dir=work_dir)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_sdk_client/sdk_backend/sdk_backend.py", line 1045, in full_quantization
self._full_acceleras_run(self.calibration_data, data_type)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_sdk_client/sdk_backend/sdk_backend.py", line 1229, in _full_acceleras_run
optimization_flow.run()
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/tools/orchestator.py", line 306, in wrapper
return func(self, *args, **kwargs)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/flows/optimization_flow.py", line 316, in run
step_func()
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/tools/orchestator.py", line 250, in wrapped
result = method(*args, **kwargs)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/tools/subprocess_wrapper.py", line 111, in parent_wrapper
raise SubprocessTracebackFailure(*child_messages)
hailo_model_optimization.acceleras.utils.acceleras_exceptions.SubprocessTracebackFailure: Subprocess failed with traceback
Traceback (most recent call last):
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/tools/subprocess_wrapper.py", line 73, in child_wrapper
func(self, *args, **kwargs)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/flows/optimization_flow.py", line 335, in step1
self.core_quantization()
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/tools/orchestator.py", line 250, in wrapped
result = method(*args, **kwargs)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/flows/optimization_flow.py", line 385, in core_quantization
self._create_encoding()
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/tools/orchestator.py", line 250, in wrapped
result = method(*args, **kwargs)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/flows/optimization_flow.py", line 461, in _create_encoding
algo.run()
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/algorithms/optimization_algorithm.py", line 50, in run
return super().run()
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/algorithms/algorithm_base.py", line 151, in run
self._run_int()
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/algorithms/create_encoding/create_io_encoding.py", line 70, in _run_int
self._matching_algo.match_components_group(matching_component_group, training=False)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/algorithms/equiv_matching/matching_algo.py", line 518, in match_components_group
self.zp_matching_group(matching_component_group)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/algorithms/equiv_matching/matching_algo.py", line 171, in zp_matching_group
self._sources_zp_matching_group(layers_with_out_ind)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/algorithms/equiv_matching/matching_algo.py", line 182, in _sources_zp_matching_group
new_scale = self.get_new_scale_vector(zp_old, zp, scale_vector, bins)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/algorithms/equiv_matching/matching_algo.py", line 440, in get_new_scale_vector
ratio = cls._get_ratio(zp_old, zp, bins)
File "/root/hailo_venv/lib/python3.9/site-packages/hailo_model_optimization/algorithms/equiv_matching/matching_algo.py", line 466, in _get_ratio
raise MatchingAlgoError
hailo_model_optimization.acceleras.utils.acceleras_exceptions.MatchingAlgoError
my alls
normalization1 = normalization([0.0, 0.0, 0.0], [255.0, 255.0, 255.0])
model_optimization_config(calibration, batch_size=2)
change_output_activation(conv58, sigmoid)
change_output_activation(conv71, sigmoid)
change_output_activation(conv83, sigmoid)
post_quantization_optimization(finetune, policy=enabled, learning_rate=0.000025)
nms_postprocess("../../postprocess_config/yolov8m_nms_config.json", meta_arch=yolov8, engine=cpu)
quantization_param([conv42, conv53, conv63], force_range_out=[0.0, 1.0])
yolov8m.yaml
base:
- base/yolov8.yaml
postprocessing:
device_pre_post_layers:
nms: true
hpp: true
network:
network_name: yolov8m
paths:
network_path:
- models_files/ObjectDetection/Detection-COCO/yolo/yolov8m/2023-02-02/yolov8m.onnx
alls_script: yolov8m.alls
url: https://hailo-model-zoo.s3.eu-west-2.amazonaws.com/ObjectDetection/Detection-COCO/yolo/yolov8m/2023-02-02/yolov8m.zip
parser:
nodes:
- null
- - /model.22/cv2.0/cv2.0.2/Conv
- /model.22/cv3.0/cv3.0.2/Conv
- /model.22/cv2.1/cv2.1.2/Conv
- /model.22/cv3.1/cv3.1.2/Conv
- /model.22/cv2.2/cv2.2.2/Conv
- /model.22/cv3.2/cv3.2.2/Conv
info:
task: object detection
input_shape: 640x640x3
output_shape: 80x5x100
operations: 78.93G
parameters: 25.9M
framework: pytorch
training_data: coco train2017
validation_data: coco val2017
eval_metric: mAP
full_precision_result: 50.08
source: https://github.com/ultralytics/ultralytics
license_url: https://github.com/ultralytics/ultralytics/blob/main/LICENSE
license_name: GPL-3.0