diff --git a/aidge_export_arm_cortexm/templates/memory/mem_info.jinja b/aidge_export_arm_cortexm/templates/memory/mem_info.jinja
deleted file mode 100644
index f835d9649a599c9339256c59d5941fcfc8f1b545..0000000000000000000000000000000000000000
--- a/aidge_export_arm_cortexm/templates/memory/mem_info.jinja
+++ /dev/null
@@ -1,16 +0,0 @@
-#ifndef MEM_INFO_H
-#define MEM_INFO_H
-
-#define MEMORY_SIZE {{ mem_size }}
-#define MEMORY_ALIGNMENT {{ mem_alignment }}
-
-{% for i in range(mem_info|length) -%}
-{%- set layer_name = mem_info[i][0] %}
-/* {{layer_name}} memory */
-{% for j in range(1, mem_info[i]|length) %}
-#define {{ layer_name|upper }}_MEM_{{ mem_info_legends[j]|upper }} {{ mem_info[i][j] }}
-{%- endfor %}
-{% endfor %}
-
-
-#endif /* MEM_INFO_H */
diff --git a/aidge_export_arm_cortexm/templates/network/dnn_header.jinja b/aidge_export_arm_cortexm/templates/network/dnn_header.jinja
deleted file mode 100644
index 7b238c167b9849cb41bad7b61ef0c596f8d29abd..0000000000000000000000000000000000000000
--- a/aidge_export_arm_cortexm/templates/network/dnn_header.jinja
+++ /dev/null
@@ -1,22 +0,0 @@
-{#- For name header -#}
-#ifndef DNN_H
-#define DNN_H
-
-#ifdef __cplusplus
-extern "C" {
-#endif
-
-{#- For libraries #}
-{% for lib in libraries %}
-#include <{{ lib }}>
-{%- endfor %}
-
-{% for func in functions %}
-{{ func }}
-{% endfor %}
-
-#ifdef __cplusplus
-}
-#endif
-
-#endif /* DNN_H */
\ No newline at end of file
diff --git a/aidge_export_arm_cortexm/templates/network/network_forward.jinja b/aidge_export_arm_cortexm/templates/network/network_forward.jinja
deleted file mode 100644
index bde5553020d1a36f225a1402172715a7446c4496..0000000000000000000000000000000000000000
--- a/aidge_export_arm_cortexm/templates/network/network_forward.jinja
+++ /dev/null
@@ -1,28 +0,0 @@
-{#- For libraries -#}
-
-#include <stdint.h>
-
-#include "dnn.h"
-#include "network_functions.h"
-
-// Layer & memory configurations
-{%- for header in headers %}
-#include "{{ header }}"
-{%- endfor %}
-
-{# mem has the datatype of the firt input #}
-{#- Change here to improve it -#}
-{% if inputs[0][0] %}
-static {{inputs[0][0]}} mem[MEMORY_SIZE];
-{% else %}
-static float mem[MEMORY_SIZE];
-{% endif %}
-
-{# Forward function #}
-{#- Support multiple inputs with different datatypes and multiple outputs with different datatypes -#}
-void model_forward({% for inp in inputs %}const {{inp[0]}}* {{inp[1]}}, {% endfor %}{% for out in outputs %}{{out[0]}}* {{out[1]}}{{ ", " if not loop.last else "" }}{% endfor %})
-{
- {%- for action in actions %}
- {{ action }}
- {%- endfor %}
-}
diff --git a/aidge_export_arm_cortexm/templates/network/network_prototypes.jinja b/aidge_export_arm_cortexm/templates/network/network_prototypes.jinja
deleted file mode 100644
index 4d2f3452f1c2434c1d767ba654a0ca26ac2bae2a..0000000000000000000000000000000000000000
--- a/aidge_export_arm_cortexm/templates/network/network_prototypes.jinja
+++ /dev/null
@@ -1,19 +0,0 @@
-{#- For name header -#}
-#ifndef NETWORK_FUNCTIONS_HPP
-#define NETWORK_FUNCTIONS_HPP
-
-{#- For libraries #}
-{% for lib in libraries %}
-#include <{{ lib }}>
-{%- endfor %}
-
-{% for file in files %}
-#include "{{ file }}"
-{%- endfor %}
-
-{% for func in functions %}
-{{ func }}
-{% endfor %}
-
-
-#endif /* NETWORK_FUNCTIONS_HPP */
\ No newline at end of file
diff --git a/aidge_export_arm_cortexm/utils/__init__.py b/aidge_export_arm_cortexm/utils/__init__.py
deleted file mode 100644
index bd48bd6a7b39cccf74f0f723124b6af2e7db478d..0000000000000000000000000000000000000000
--- a/aidge_export_arm_cortexm/utils/__init__.py
+++ /dev/null
@@ -1,33 +0,0 @@
-from pathlib import Path
-
-# Constants
-FILE = Path(__file__).resolve()
-ROOT = FILE.parents[1]
-
-
-def get_all_available_boards():
- boards = {}
-
- directory_path = Path(str(ROOT / "boards"))
-
- for subfolder in directory_path.rglob('*'):
- if subfolder.is_dir() and \
- subfolder.name != "__pycache__" and \
- (subfolder.parent / '__init__.py').exists() and \
- not (subfolder / '__init__.py').exists():
-
- # Get relative path to boards directory
- relpath = str(subfolder.relative_to(directory_path))
-
- # Get board name
- board_name = relpath.replace('/', '').replace('\\', '')
-
- boards[board_name.lower()] = str(subfolder)
-
- return boards
-
-AVAILABLE_BOARDS = get_all_available_boards()
-
-
-def has_board(board_name: str) -> bool:
- return board_name.lower() in AVAILABLE_BOARDS.keys()
diff --git a/aidge_export_arm_cortexm/utils/converter.py b/aidge_export_arm_cortexm/utils/converter.py
deleted file mode 100644
index 3bc2f392b9f48b96972f3ff744bbba3bf945ca13..0000000000000000000000000000000000000000
--- a/aidge_export_arm_cortexm/utils/converter.py
+++ /dev/null
@@ -1,55 +0,0 @@
-import numpy as np
-import aidge_core
-
-def numpy_dtype2ctype(dtype):
- if dtype == np.int8:
- return "int8_t"
- elif dtype == np.uint8:
- return "uint8_t"
- elif dtype == np.int16:
- return "int16_t"
- elif dtype == np.int32:
- return "int32_t"
- elif dtype == np.int64:
- return "int64_t"
- elif dtype == np.float32:
- return "float"
- elif dtype == np.float64:
- return "double"
- # Add more dtype mappings as needed
- else:
- raise ValueError(f"Unsupported {dtype} dtype")
-
-
-def aidge_datatype2ctype(datatype):
- if datatype == aidge_core.dtype.int8:
- return "int8_t"
- elif datatype == aidge_core.dtype.uint8:
- return "uint8_t"
- elif datatype == aidge_core.dtype.int32:
- return "int32_t"
- elif datatype == aidge_core.dtype.int64:
- return "int64_t"
- elif datatype == aidge_core.dtype.float32:
- return "float"
- elif datatype == aidge_core.dtype.float64:
- return "double"
- # Add more dtype mappings as needed
- else:
- raise ValueError(f"Unsupported {datatype} aidge dtype")
-
-
-def aidge_datatype2dataformat(datatype):
- if datatype == aidge_core.dtype.int8:
- return "int8"
- elif datatype == aidge_core.dtype.int32:
- return "int32"
- elif datatype == aidge_core.dtype.int64:
- return "int64"
- elif datatype == aidge_core.dtype.float32:
- return "float32"
- elif datatype == aidge_core.dtype.float64:
- return "float64"
- # Add more dtype mappings as needed
- else:
- raise ValueError(f"Unsupported {datatype} aidge dtype")
diff --git a/examples/README.md b/examples/README.md
deleted file mode 100644
index 643f196717043d908c7e0342f61883abcb3806f6..0000000000000000000000000000000000000000
--- a/examples/README.md
+++ /dev/null
@@ -1,6 +0,0 @@
-# Examples on how to use this module Aidge ARM CortexM Export
-
-This folder contains some examples on how to use the `Aidge ARM CortexM Export` module in your projects.
-- [LeNet export for MNIST dataset](./export_LeNet/)
-
-Feel free to propose your own contributions with this module !
\ No newline at end of file
diff --git a/examples/export_LeNet/export_lenet_fp32.ipynb b/examples/export_LeNet/export_lenet_fp32.ipynb
deleted file mode 100644
index 08b64318ec66e55754aa1e2302d0576854557e05..0000000000000000000000000000000000000000
--- a/examples/export_LeNet/export_lenet_fp32.ipynb
+++ /dev/null
@@ -1,281 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Export a MNIST model to a CPP standalone project"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "%pip install requests numpy ipywidgets ipycanvas"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Download the model"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "import os\n",
- "import requests"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "# Download onnx file if it has not been done before\n",
- "if not os.path.isfile(\"./lenet_mnist.onnx\"):\n",
- " response = requests.get(\"https://huggingface.co/vtemplier/LeNet_MNIST/resolve/main/lenet_mnist.onnx?download=true\")\n",
- " if response.status_code == 200:\n",
- " with open(\"lenet_mnist.onnx\", 'wb') as f:\n",
- " f.write(response.content)\n",
- " print(\"ONNX model downloaded successfully.\")\n",
- " else:\n",
- " print(\"Failed to download ONNX model. Status code:\", response.status_code)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Load the model in Aidge and manipulate it"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "import aidge_core\n",
- "import aidge_backend_cpu\n",
- "import aidge_onnx\n",
- "import aidge_export_cpp\n",
- "import aidge_export_arm_cortexm"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "model = aidge_onnx.load_onnx(\"lenet_mnist.onnx\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "# Remove Flatten node, useless in the CPP export\n",
- "aidge_core.remove_flatten(model)\n",
- "\n",
- "# Freeze the model by setting constant to parameters producers\n",
- "for node in model.get_nodes():\n",
- " if node.type() == \"Producer\":\n",
- " node.get_operator().set_attr(\"Constant\", True)\n",
- "\n",
- "# Create Producer Node for the Graph\n",
- "input_node = aidge_core.Producer([1, 1, 28, 28], \"input\")\n",
- "input_node.add_child(model)\n",
- "model.add(input_node)\n",
- "\n",
- "# Configuration for the model + forward dimensions\n",
- "model.compile(\"cpu\", aidge_core.DataType.Float32)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "# Generate scheduling of the model\n",
- "scheduler = aidge_core.SequentialScheduler(model)\n",
- "scheduler.generate_scheduling()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Export the model"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "aidge_export_arm_cortexm.export(\"lenet_export_fp32\", model, scheduler, board=\"stm32h7\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Draw your own number"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "from ipywidgets import HBox, VBox, Button, Layout\n",
- "from ipycanvas import RoughCanvas, hold_canvas\n",
- "\n",
- "img_name = \"my_number.png\"\n",
- "\n",
- "canvas = RoughCanvas(width=28, height=28, sync_image_data=True)\n",
- "\n",
- "button_gen = Button(description=\"Generate PNG\")\n",
- "button_clear = Button(description=\"Clear\")\n",
- "\n",
- "drawing = False\n",
- "position = None\n",
- "shape = []\n",
- "\n",
- "def on_erase_button_clicked(b):\n",
- " canvas.clear()\n",
- "\n",
- "def on_generate_button_clicked(b):\n",
- " try:\n",
- " canvas.to_file(img_name)\n",
- " print(f\"Image generated to {img_name} !\")\n",
- " except:\n",
- " print(\"Draw a number before generating the image.\")\n",
- "\n",
- "button_clear.on_click(on_erase_button_clicked)\n",
- "button_gen.on_click(on_generate_button_clicked)\n",
- "\n",
- "def on_mouse_down(x, y):\n",
- " global drawing\n",
- " global position\n",
- " global shape\n",
- "\n",
- " drawing = True\n",
- " position = (x, y)\n",
- " shape = [position]\n",
- "\n",
- "def on_mouse_move(x, y):\n",
- " global drawing\n",
- " global position\n",
- " global shape\n",
- "\n",
- " if not drawing:\n",
- " return\n",
- "\n",
- " with hold_canvas():\n",
- " canvas.stroke_line(position[0], position[1], x, y)\n",
- " position = (x, y)\n",
- "\n",
- " shape.append(position)\n",
- "\n",
- "def on_mouse_up(x, y):\n",
- " global drawing\n",
- " global position\n",
- " global shape\n",
- "\n",
- " drawing = False\n",
- "\n",
- " with hold_canvas():\n",
- " canvas.stroke_line(position[0], position[1], x, y)\n",
- "\n",
- " shape = []\n",
- "\n",
- "canvas.on_mouse_down(on_mouse_down)\n",
- "canvas.on_mouse_move(on_mouse_move)\n",
- "canvas.on_mouse_up(on_mouse_up)\n",
- "\n",
- "canvas.stroke_style = \"#000000\"\n",
- "\n",
- "VBox((canvas, HBox((button_gen, button_clear))),\n",
- " layout=Layout(height='auto', width=\"300px\"))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Generate inputs for testing the model from your drawing"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "try:\n",
- " number_np = canvas.get_image_data()\n",
- " # We got a numpy array with the shape of (28,28,4)\n",
- " # Transform it to (28,28)\n",
- " x = number_np[:, :, 3].astype(\"float32\")\n",
- " # Convert from [0, 255] to [0, 1] and export it\n",
- " aidge_export_cpp.generate_input_file(export_folder=\"lenet_export_fp32\",\n",
- " array_name=\"inputs\",\n",
- " array=x / 255)\n",
- "except:\n",
- " print(\"Please draw a number in the previous cell before running this one.\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Compile the export and test it"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "!cd lenet_export_fp32 && make build_image_docker && make build_docker"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "env",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.9.16"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}