How I can run a model with hailo sw without hw

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_

First I would recommend using the Hailo AI Software Suite Docker. This will make installation and updates easier.

Second please work trough the tutorials to get familiar with the workflow. Inside the Docker call:

hailo tutorial

This will start a Jupyter Notebook server with notebooks for each step of the process including running the model in the emulator in native and quantized mode.