I installed python 3.8 and hailo hailo_ai_sw_suite_2025-01.run in virtual environment. I tried to run simple model using yaml. I consistently getting the Missing key parser
error, even with a very simple ONNX model and YAML file. pip list shows
hailo-dataflow-compiler 3.30.0
hailo_model_zoo 2.14.0 /home/x/Downloads/hailo_model_zoo
hailort 4.20.0
this is hailomz script
#!/home/logi14/Downloads/hailo_new_env/bin/python3
# EASY-INSTALL-ENTRY-SCRIPT: 'hailo-model-zoo','console_scripts','hailomz'
import re
import sys
# for compatibility with easy_install; see #2198
__requires__ = 'hailo-model-zoo'
try:
from importlib.metadata import distribution
except ImportError:
try:
from importlib_metadata import distribution
except ImportError:
from pkg_resources import load_entry_point
def importlib_load_entry_point(spec, group, name):
dist_name, _, _ = spec.partition('==')
matches = (
entry_point
for entry_point in distribution(dist_name).entry_points
if entry_point.group == group and entry_point.name == name
)
return next(matches).load()
globals().setdefault('load_entry_point', importlib_load_entry_point)
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(load_entry_point('hailo-model-zoo', 'console_scripts', 'hailomz')())
this is model
import torch
import torch.nn as nn
import torch.onnx
class SimpleModel(nn.Module):
def __init__(self):
super(SimpleModel, self).__init__()
self.linear = nn.Linear(10, 5) # Simple linear layer
def forward(self, x):
return self.linear(x)
# Create an instance of the model
model = SimpleModel()
# Create a dummy input
dummy_input = torch.randn(1, 10) # Batch size 1, input size 10
# Export to ONNX
torch.onnx.export(model, dummy_input, "simple_model.onnx", verbose=True)
print("Simple PyTorch model converted to ONNX: simple_model.onnx")
this is .yml
network:
network_name: simple_model
task_type: classification
parser:
start_node_names: ["input"]
start_node_shapes:
- input_name: "input"
shape: [1, 3, 224, 224]
end_node_names: ["output"]
end_node_shapes:
- output_name: "output"
shape: [1, 10]
results_dir: /home/logi14/Downloads/results
How can i do this_