Error while exporting model to cpp

What commit version of aidge do you use

Main branch, updated today

Problem description

Error while exporting model to cpp. Note that I do not provide a label.

Loading onnx model
Native operators: 60 (10 types)
- Add: 3
- Conv2D: 7
- MatMul: 3
- MaxPooling2D: 7
- Pad2D: 7
- Producer: 21
- ReLU: 9
- ReduceMean: 1
- Reshape: 1
- Sigmoid: 1
Generic operators: 0 (0 types)
Native types coverage: 100.0% (10/10)
Native operators coverage: 100.0% (60/60)
(defaultdict(<class 'int'>, {'MaxPooling2D': 7, 'MatMul': 3, 'Sigmoid': 1, 'ReLU': 9, 'Conv2D': 7, 'Pad2D': 7, 'ReduceMean': 1, 'Producer': 21, 'Add': 3, 'Reshape': 1}), defaultdict(<class 'int'>, {}))
Generating scheduler
Testing model with random input data
Exporting model to CPP
Removing existing export directory...
Traceback (most recent call last):
  File "/data1/is156025/fa125436/env_aidge/lib/python3.12/site-packages/aidge_core/export_utils/node_export.py", line 527, in export
    code_generation.generate_file(
  File "/data1/is156025/fa125436/env_aidge/lib/python3.12/site-packages/aidge_core/export_utils/code_generation.py", line 29, in generate_file
    file.write(generate_str(template_path, **kwargs))
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/data1/is156025/fa125436/env_aidge/lib/python3.12/site-packages/aidge_core/export_utils/code_generation.py", line 45, in generate_str
    template_path.parent), undefined=StrictUndefined, keep_trailing_newline=True).get_template(template_path.name).render(kwargs)
                                                                                                                   ^^^^^^^^^^^^^^
  File "/data1/is156025/fa125436/env_aidge/lib/python3.12/site-packages/jinja2/environment.py", line 1295, in render
    self.environment.handle_exception()
  File "/data1/is156025/fa125436/env_aidge/lib/python3.12/site-packages/jinja2/environment.py", line 942, in handle_exception
    raise rewrite_traceback_stack(source=source)
  File "/data1/is156025/fa125436/env_aidge/lib/python3.12/site-packages/aidge_export_cpp/templates/configuration/activation_config.jinja", line 7, in top-level template code
    {%- set nb_data = in_chan[0] * in_height[0] * in_width[0] %}
    ^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: unsupported operand type(s) for *: 'NoneType' and 'NoneType'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/data1/is156025/fa125436/Confluence/Aidge/mini.py", line 65, in <module>
    aidge_export_cpp.export(EXPORT_FOLDER,
  File "/data1/is156025/fa125436/env_aidge/lib/python3.12/site-packages/aidge_export_cpp/export.py", line 61, in export
    scheduler_export(scheduler,
  File "/data1/is156025/fa125436/env_aidge/lib/python3.12/site-packages/aidge_core/export_utils/scheduler_export.py", line 131, in scheduler_export
    list_configs += op.export(dnn_folder)
                    ^^^^^^^^^^^^^^^^^^^^^
  File "/data1/is156025/fa125436/env_aidge/lib/python3.12/site-packages/aidge_core/export_utils/node_export.py", line 533, in export
    raise RuntimeError(f"Error when creating config file for {self.node.name()}[{self.node.type()}].") from e
RuntimeError: Error when creating config file for final_feedforward_classifier_classifier_1_Relu[ReLU].

Reproducible example code

import aidge_core.utils
import numpy as np

# Aidge Modules
import aidge_core
import aidge_onnx
import aidge_backend_cpu
import aidge_export_cpp

from aidge_export_cpp.export_utils import (
    cpp_fuse_to_metaops,
    set_nodes_names,
    set_nodes_datatypes,
    exclude_unwanted_producers)

from aidge_core.export_utils import remove_optional_inputs, get_node_from_metaop

# Setting Aidge verbose level
aidge_core.Log.set_console_level(aidge_core.Level.Error)

MODEL_FOLDER  = 'models/'
MODEL_NAME    = 'simplified_cnn'
EXPORT_FOLDER = f"export_{MODEL_NAME}_float32"

# Define the target path and filename
file_path = MODEL_FOLDER + MODEL_NAME + ".onnx"
print("Loading onnx model")
model = aidge_onnx.load_onnx(file_path, verbose=False)
aidge_core.remove_flatten(model)
aidge_core.fuse_batchnorm(model)
aidge_core.expand_metaops(model)
print(aidge_onnx.native_coverage_report(model))

# Set up the backend
model.set_datatype(aidge_core.dtype.float32)
model.set_backend("cpu")

# Create the Scheduler
print("Generating scheduler")
scheduler = aidge_core.SequentialScheduler(model)
scheduler.generate_scheduling()  

# Test the model
print("Testing model with random input data")
sample = np.random.rand(1,1,399,128)
input_tensor = aidge_core.Tensor(sample)
input_tensor.set_datatype(aidge_core.dtype.float32)
scheduler.forward(True, [input_tensor])
output_node = model.get_output_nodes().pop()
output_tensor = output_node.get_operator().get_output(0)

# Export to cpp
print("Exporting model to CPP")
aidge_export_cpp.export(EXPORT_FOLDER,
                        model,
                        scheduler,
                        input_tensor)