DNN library is not found.

I have installed the Hailo AI Software Suite
Dataflow Compiler
HailoRT
Model Zoo

When I execute hailo mz compiler yolov10b --calib-path optimize image/
I get the following error

(v10_hailo_new) yungkai@yungkai:~/Desktop/v10_hailo_new$ hailomz compile yolov10b --calib-path optimize_image/
Start run for network yolov10b …
Initializing the hailo8 runner…
[info] Translation started on ONNX model yolov10b
[info] Restored ONNX model yolov10b (completion time: 00:00:00.35)
[info] Extracted ONNXRuntime meta-data for Hailo model (completion time: 00:00:01.47)
[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.23/one2one_cv2.0/one2one_cv2.0.2/Conv /model.23/one2one_cv3.0/one2one_cv3.0.2/Conv /model.23/one2one_cv3.1/one2one_cv3.1.2/Conv /model.23/one2one_cv2.1/one2one_cv2.1.2/Conv /model.23/one2one_cv3.2/one2one_cv3.2.2/Conv /model.23/one2one_cv2.2/one2one_cv2.2.2/Conv.
[info] Start nodes mapped from original model: ‘images’: ‘yolov10b/input_layer1’.
[info] End nodes mapped from original model: ‘/model.23/one2one_cv2.0/one2one_cv2.0.2/Conv’, ‘/model.23/one2one_cv3.0/one2one_cv3.0.2/Conv’, ‘/model.23/one2one_cv2.1/one2one_cv2.1.2/Conv’, ‘/model.23/one2one_cv3.1/one2one_cv3.1.2/Conv’, ‘/model.23/one2one_cv2.2/one2one_cv2.2.2/Conv’, ‘/model.23/one2one_cv3.2/one2one_cv3.2.2/Conv’.
[info] Translation completed on ONNX model yolov10b (completion time: 00:00:02.59)
[info] Appending model script commands to yolov10b from string
[info] Added nms postprocess command to model script.
[info] Saved HAR to: /home/yungkai/Desktop/v10_hailo_new/yolov10b.har
Preparing calibration data…
[info] Loading model script commands to yolov10b from /home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/cfg/alls/generic/yolov10b.alls
[info] Starting Model Optimization
[warning] Reducing compression level to 0 because requested optimization level equal or less than 1
[warning] Running model optimization with zero level of optimization is not recommended for production use and might lead to suboptimal accuracy results
[info] Model received quantization params from the hn
[info] MatmulDecompose skipped
[info] Starting Mixed Precision
[info] Model Optimization Algorithm Mixed Precision is done (completion time is 00:00:00.81)
[info] LayerNorm Decomposition skipped
[info] Starting Statistics Collector
[info] Using dataset with 64 entries for calibration
Calibration: 0%| | 0/64 [00:50<?, ?entries/s]
Traceback (most recent call last):
File “/home/yungkai/Desktop/v10_hailo_new/bin/hailomz”, line 8, in
sys.exit(main())
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/main.py”, line 122, in main
run(args)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/main.py”, line 111, in run
return handlersargs.command
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/main_driver.py”, line 250, in compile
runner = _ensure_optimized(runner, logger, args, network_info)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/main_driver.py”, line 91, in _ensure_optimized
optimize_model(
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/core/main_utils.py”, line 353, in optimize_model
runner.optimize(calib_feed_callback)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_common/states/states.py”, line 16, in wrapped_func
return func(self, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_client/runner/client_runner.py”, line 2128, in optimize
self._optimize(calib_data, data_type=data_type, work_dir=work_dir)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_common/states/states.py”, line 16, in wrapped_func
return func(self, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_client/runner/client_runner.py”, line 1970, in _optimize
self._sdk_backend.full_quantization(calib_data, data_type=data_type, work_dir=work_dir)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_client/sdk_backend/sdk_backend.py”, line 1125, in full_quantization
self._full_acceleras_run(self.calibration_data, data_type)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_client/sdk_backend/sdk_backend.py”, line 1319, in _full_acceleras_run
optimization_flow.run()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/orchestator.py”, line 306, in wrapper
return func(self, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/flows/optimization_flow.py”, line 335, in run
step_func()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/orchestator.py”, line 250, in wrapped
result = method(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/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 “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/subprocess_wrapper.py”, line 73, in child_wrapper
func(self, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/flows/optimization_flow.py”, line 353, in step1
self.pre_quantization_optimization()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/orchestator.py”, line 250, in wrapped
result = method(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/flows/optimization_flow.py”, line 400, in pre_quantization_optimization
self._collect_stats()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/orchestator.py”, line 250, in wrapped
result = method(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/flows/optimization_flow.py”, line 475, in _collect_stats
stats_collector.run()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/algorithms/optimization_algorithm.py”, line 54, in run
return super().run()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/algorithms/algorithm_base.py”, line 150, in run
self._run_int()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/algorithms/stats_collection/stats_collection.py”, line 41, in _run_int
stats_collector.collect_stats(
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/statistics/stats_collector.py”, line 118, in collect_stats
acceleras_model.predict_on_batch(preprocessed_data)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/training.py”, line 2603, in predict_on_batch
outputs = self.predict_function(iterator)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/tensorflow/python/util/traceback_utils.py”, line 153, in error_handler
raise e.with_traceback(filtered_tb) from None
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/tensorflow/python/eager/execute.py”, line 52, in quick_execute
tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.UnimplementedError: Graph execution error:

Detected at node ‘yolov10b/conv1/conv_op/Conv2D’ defined at (most recent call last):
File “/home/yungkai/Desktop/v10_hailo_new/bin/hailomz”, line 8, in
sys.exit(main())
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/main.py”, line 122, in main
run(args)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/main.py”, line 111, in run
return handlersargs.command
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/main_driver.py”, line 250, in compile
runner = _ensure_optimized(runner, logger, args, network_info)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/main_driver.py”, line 91, in _ensure_optimized
optimize_model(
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/core/main_utils.py”, line 353, in optimize_model
runner.optimize(calib_feed_callback)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_common/states/states.py”, line 16, in wrapped_func
return func(self, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_client/runner/client_runner.py”, line 2128, in optimize
self._optimize(calib_data, data_type=data_type, work_dir=work_dir)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_common/states/states.py”, line 16, in wrapped_func
return func(self, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_client/runner/client_runner.py”, line 1970, in _optimize
self._sdk_backend.full_quantization(calib_data, data_type=data_type, work_dir=work_dir)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_client/sdk_backend/sdk_backend.py”, line 1125, in full_quantization
self._full_acceleras_run(self.calibration_data, data_type)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_client/sdk_backend/sdk_backend.py”, line 1319, in _full_acceleras_run
optimization_flow.run()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/orchestator.py”, line 306, in wrapper
return func(self, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/flows/optimization_flow.py”, line 335, in run
step_func()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/orchestator.py”, line 250, in wrapped
result = method(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/subprocess_wrapper.py”, line 94, in parent_wrapper
proc.start()
File “/usr/lib/python3.8/multiprocessing/process.py”, line 121, in start
self._popen = self._Popen(self)
File “/usr/lib/python3.8/multiprocessing/context.py”, line 224, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File “/usr/lib/python3.8/multiprocessing/context.py”, line 277, in _Popen
return Popen(process_obj)
File “/usr/lib/python3.8/multiprocessing/popen_fork.py”, line 19, in init
self._launch(process_obj)
File “/usr/lib/python3.8/multiprocessing/popen_fork.py”, line 75, in _launch
code = process_obj._bootstrap(parent_sentinel=child_r)
File “/usr/lib/python3.8/multiprocessing/process.py”, line 315, in _bootstrap
self.run()
File “/usr/lib/python3.8/multiprocessing/process.py”, line 108, in run
self._target(*self._args, **self._kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/subprocess_wrapper.py”, line 73, in child_wrapper
func(self, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/flows/optimization_flow.py”, line 353, in step1
self.pre_quantization_optimization()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/orchestator.py”, line 250, in wrapped
result = method(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/flows/optimization_flow.py”, line 400, in pre_quantization_optimization
self._collect_stats()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/orchestator.py”, line 250, in wrapped
result = method(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/flows/optimization_flow.py”, line 475, in _collect_stats
stats_collector.run()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/algorithms/optimization_algorithm.py”, line 54, in run
return super().run()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/algorithms/algorithm_base.py”, line 150, in run
self._run_int()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/algorithms/stats_collection/stats_collection.py”, line 41, in _run_int
stats_collector.collect_stats(
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/statistics/stats_collector.py”, line 118, in collect_stats
acceleras_model.predict_on_batch(preprocessed_data)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/training.py”, line 2603, in predict_on_batch
outputs = self.predict_function(iterator)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/training.py”, line 2169, in predict_function
return step_function(self, iterator)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/training.py”, line 2155, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/training.py”, line 2143, in run_step
outputs = model.predict_step(data)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/training.py”, line 2111, in predict_step
return self(x, training=False)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/utils/traceback_utils.py”, line 65, in error_handler
return fn(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/training.py”, line 558, in call
return super().call(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/utils/traceback_utils.py”, line 65, in error_handler
return fn(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/base_layer.py”, line 1145, in call
outputs = call_fn(inputs, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/utils/traceback_utils.py”, line 96, in error_handler
return fn(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/model/hailo_model/hailo_model.py”, line 1203, in call
for lname in self.flow.toposort():
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/model/hailo_model/hailo_model.py”, line 1210, in call
output = self._call_layer(
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/model/hailo_model/hailo_model.py”, line 1334, in _call_layer
outputs = acceleras_layer(inputs, training=training, encoding_tensors=encoding_tensors, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/utils/traceback_utils.py”, line 65, in error_handler
return fn(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/base_layer.py”, line 1145, in call
outputs = call_fn(inputs, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/utils/traceback_utils.py”, line 96, in error_handler
return fn(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/hailo_layers/base_hailo_layer.py”, line 152, in call
for op_name in self._layer_flow.toposort_ops():
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/hailo_layers/base_hailo_layer.py”, line 163, in call
op_result = op(
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/utils/traceback_utils.py”, line 65, in error_handler
return fn(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/base_layer.py”, line 1145, in call
outputs = call_fn(inputs, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/utils/traceback_utils.py”, line 96, in error_handler
return fn(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/atomic_ops/base_atomic_op.py”, line 1141, in call
if fully_native:
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/atomic_ops/base_atomic_op.py”, line 1142, in call
outputs = self._native_run(inputs, training=training, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/atomic_ops/base_atomic_op.py”, line 1235, in _native_run
outputs = self.call_native(native_input, training=training, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/atomic_ops/conv_stripped_op.py”, line 981, in call_native
return self._call_conv_internal(inputs[0], self.kernel, self.padding_const_value)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/atomic_ops/conv_stripped_op.py”, line 1232, in _call_conv_internal
if self.is_depthwise and self.strides[0] == self.strides[1]:
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/atomic_ops/conv_stripped_op.py”, line 1241, in _call_conv_internal
elif self.groups == 1 and not self.is_depthwise:
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/atomic_ops/conv_stripped_op.py”, line 1242, in _call_conv_internal
output = tf.nn.conv2d(
Node: ‘yolov10b/conv1/conv_op/Conv2D’
Detected at node ‘yolov10b/conv1/conv_op/Conv2D’ defined at (most recent call last):
File “/home/yungkai/Desktop/v10_hailo_new/bin/hailomz”, line 8, in
sys.exit(main())
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/main.py”, line 122, in main
run(args)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/main.py”, line 111, in run
return handlersargs.command
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/main_driver.py”, line 250, in compile
runner = _ensure_optimized(runner, logger, args, network_info)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/main_driver.py”, line 91, in _ensure_optimized
optimize_model(
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_zoo/core/main_utils.py”, line 353, in optimize_model
runner.optimize(calib_feed_callback)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_common/states/states.py”, line 16, in wrapped_func
return func(self, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_client/runner/client_runner.py”, line 2128, in optimize
self._optimize(calib_data, data_type=data_type, work_dir=work_dir)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_common/states/states.py”, line 16, in wrapped_func
return func(self, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_client/runner/client_runner.py”, line 1970, in _optimize
self._sdk_backend.full_quantization(calib_data, data_type=data_type, work_dir=work_dir)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_client/sdk_backend/sdk_backend.py”, line 1125, in full_quantization
self._full_acceleras_run(self.calibration_data, data_type)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_sdk_client/sdk_backend/sdk_backend.py”, line 1319, in _full_acceleras_run
optimization_flow.run()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/orchestator.py”, line 306, in wrapper
return func(self, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/flows/optimization_flow.py”, line 335, in run
step_func()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/orchestator.py”, line 250, in wrapped
result = method(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/subprocess_wrapper.py”, line 94, in parent_wrapper
proc.start()
File “/usr/lib/python3.8/multiprocessing/process.py”, line 121, in start
self._popen = self._Popen(self)
File “/usr/lib/python3.8/multiprocessing/context.py”, line 224, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File “/usr/lib/python3.8/multiprocessing/context.py”, line 277, in _Popen
return Popen(process_obj)
File “/usr/lib/python3.8/multiprocessing/popen_fork.py”, line 19, in init
self._launch(process_obj)
File “/usr/lib/python3.8/multiprocessing/popen_fork.py”, line 75, in _launch
code = process_obj._bootstrap(parent_sentinel=child_r)
File “/usr/lib/python3.8/multiprocessing/process.py”, line 315, in _bootstrap
self.run()
File “/usr/lib/python3.8/multiprocessing/process.py”, line 108, in run
self._target(*self._args, **self._kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/subprocess_wrapper.py”, line 73, in child_wrapper
func(self, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/flows/optimization_flow.py”, line 353, in step1
self.pre_quantization_optimization()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/orchestator.py”, line 250, in wrapped
result = method(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/flows/optimization_flow.py”, line 400, in pre_quantization_optimization
self._collect_stats()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/tools/orchestator.py”, line 250, in wrapped
result = method(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/flows/optimization_flow.py”, line 475, in _collect_stats
stats_collector.run()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/algorithms/optimization_algorithm.py”, line 54, in run
return super().run()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/algorithms/algorithm_base.py”, line 150, in run
self._run_int()
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/algorithms/stats_collection/stats_collection.py”, line 41, in _run_int
stats_collector.collect_stats(
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/statistics/stats_collector.py”, line 118, in collect_stats
acceleras_model.predict_on_batch(preprocessed_data)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/training.py”, line 2603, in predict_on_batch
outputs = self.predict_function(iterator)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/training.py”, line 2169, in predict_function
return step_function(self, iterator)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/training.py”, line 2155, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/training.py”, line 2143, in run_step
outputs = model.predict_step(data)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/training.py”, line 2111, in predict_step
return self(x, training=False)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/utils/traceback_utils.py”, line 65, in error_handler
return fn(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/training.py”, line 558, in call
return super().call(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/utils/traceback_utils.py”, line 65, in error_handler
return fn(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/base_layer.py”, line 1145, in call
outputs = call_fn(inputs, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/utils/traceback_utils.py”, line 96, in error_handler
return fn(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/model/hailo_model/hailo_model.py”, line 1203, in call
for lname in self.flow.toposort():
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/model/hailo_model/hailo_model.py”, line 1210, in call
output = self._call_layer(
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/model/hailo_model/hailo_model.py”, line 1334, in _call_layer
outputs = acceleras_layer(inputs, training=training, encoding_tensors=encoding_tensors, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/utils/traceback_utils.py”, line 65, in error_handler
return fn(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/base_layer.py”, line 1145, in call
outputs = call_fn(inputs, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/utils/traceback_utils.py”, line 96, in error_handler
return fn(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/hailo_layers/base_hailo_layer.py”, line 152, in call
for op_name in self._layer_flow.toposort_ops():
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/hailo_layers/base_hailo_layer.py”, line 163, in call
op_result = op(
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/utils/traceback_utils.py”, line 65, in error_handler
return fn(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/engine/base_layer.py”, line 1145, in call
outputs = call_fn(inputs, *args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/keras/utils/traceback_utils.py”, line 96, in error_handler
return fn(*args, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/atomic_ops/base_atomic_op.py”, line 1141, in call
if fully_native:
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/atomic_ops/base_atomic_op.py”, line 1142, in call
outputs = self._native_run(inputs, training=training, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/atomic_ops/base_atomic_op.py”, line 1235, in _native_run
outputs = self.call_native(native_input, training=training, **kwargs)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/atomic_ops/conv_stripped_op.py”, line 981, in call_native
return self._call_conv_internal(inputs[0], self.kernel, self.padding_const_value)
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/atomic_ops/conv_stripped_op.py”, line 1232, in _call_conv_internal
if self.is_depthwise and self.strides[0] == self.strides[1]:
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/atomic_ops/conv_stripped_op.py”, line 1241, in _call_conv_internal
elif self.groups == 1 and not self.is_depthwise:
File “/home/yungkai/Desktop/v10_hailo_new/lib/python3.8/site-packages/hailo_model_optimization/acceleras/atomic_ops/conv_stripped_op.py”, line 1242, in _call_conv_internal
output = tf.nn.conv2d(
Node: ‘yolov10b/conv1/conv_op/Conv2D’
2 root error(s) found.
(0) UNIMPLEMENTED: DNN library is not found.
[[{{node yolov10b/conv1/conv_op/Conv2D}}]]
[[yolov10b/yolov8_nms_postprocess/ExpandDims/_66]]
(1) UNIMPLEMENTED: DNN library is not found.
[[{{node yolov10b/conv1/conv_op/Conv2D}}]]
0 successful operations.
0 derived errors ignored. [Op:__inference_predict_function_165936]

Hey @user97,

Welcome to the Hailo Community!

Is the DFC (Dataflow Compiler) installed in the same environment?

Also, the recommended model compilation flow is this:

hailomz parse yolov10b
hailomz optimize yolov10b --calib-path /path/to/calibration/data
hailomz compile yolov10b

Try running it this way and let me know how it goes. If you encounter any issues, I’m here to help.

I have the same error,while I find the reason is tensorFlow and cudnn versions are not compatible.If you’re using conda, make sure to add the cudnn library from your conda environment to the environment variables.

Same issue here after a re-install. How do you fix that exactly ?
Thanks.

In your conda environment, install the correct versions of CUDA and cuDNN, and then add CUDA and cuDNN to the environment variables. Otherwise, the system may use the CUDA and cuDNN from a non-conda environment, which could lead to version mismatch issues.