diff --git a/aidge_export_arm_cortexm/export.py b/aidge_export_arm_cortexm/export.py
index cff56ed77e20a904e6e2d8b605bb318c3978d5ee..2041ca3ad6545607ef37ac3114c7d2a3be24fe2f 100644
--- a/aidge_export_arm_cortexm/export.py
+++ b/aidge_export_arm_cortexm/export.py
@@ -9,7 +9,7 @@ from aidge_export_arm_cortexm.utils import (ROOT, AVAILABLE_BOARDS, has_board, \
OPERATORS_REGISTRY, supported_operators)
import aidge_export_arm_cortexm.operators
from aidge_export_arm_cortexm.utils.scheduler import topological_sort
-from aidge_export_arm_cortexm.utils.generation import get_functions_from_c_file, get_functions_from_c_folder
+from aidge_export_arm_cortexm.utils.generation import get_functions_from_c_file, get_functions_from_c_folder, get_filenames_from_folder
from aidge_export_arm_cortexm.utils.converter import *
from aidge_export_arm_cortexm.memory import *
@@ -19,7 +19,8 @@ def export(export_folder_name,
graphview,
scheduler = None,
board:str ="stm32h7",
- library:str = "aidge"):
+ library:str = "aidge",
+ mem_wrapping = False):
# Create export directory
export_folder = Path().absolute() / export_folder_name
@@ -39,14 +40,24 @@ def export(export_folder_name,
# Copy all static files in the export
shutil.copytree(board_path, str(export_folder), dirs_exist_ok=True)
+ # For N2D2 library, copy static folder to export/include
+ if library == "n2d2":
+ dnn_include_folder = dnn_folder / "include"
+ os.makedirs(str(dnn_include_folder), exist_ok=True)
+ shutil.copytree(str(ROOT / "_N2D2" / "static"), str(dnn_include_folder), dirs_exist_ok=True)
+
+ # Create statistics directory
+ stats_folder = export_folder / "statistics"
+ os.makedirs(str(stats_folder), exist_ok=True)
+
# Sort layers according to a scheduler
- if not scheduler:
- # No scheduler provided by the user
- # use the default scheduler
+ if not isinstance(scheduler, aidge_core.Scheduler):
+ # No scheduler provided by the user, use the default one
list_forward_nodes = topological_sort(graphview)
+ mem_size, mem_info = compute_default_mem_info(list_forward_nodes)
else:
list_forward_nodes = scheduler.get_static_scheduling()
-
+ mem_size, mem_info = generate_optimized_memory_info(stats_folder, scheduler, mem_wrapping)
# Set some lists of elements for generating forward file
list_actions = []
@@ -54,6 +65,10 @@ def export(export_folder_name,
# Export layer configurations
for node in list_forward_nodes:
+ if node.type() == "Producer":
+ # We do not treat Producer here but i the nodes which use them
+ continue
+
if node.type() in supported_operators():
op = OPERATORS_REGISTRY[node.type()](node, board, library)
@@ -62,10 +77,8 @@ def export(export_folder_name,
# Add forward kernel
list_actions = op.forward(list_actions)
-
- # Memory management
- # TODO put the condition if no scheduler provided
- mem_size, mem_info = compute_default_mem_info(scheduler)
+ else:
+ print(f"Warning: {node.type()} is not supported in the export.\nPlease add the implementation.")
# Generate the memory file
generate_file(
@@ -73,7 +86,8 @@ def export(export_folder_name,
str(ROOT / "templates" / "memory" / "mem_info.jinja"),
mem_size = mem_size,
mem_info_legends = MEMORY_INFO_TEMPLATE,
- mem_info = mem_info
+ mem_info = mem_info,
+ mem_alignment = 1 # Fixed memory alignement so far, feel free to adapt it
)
list_configs.append("memory/mem_info.h")
@@ -92,12 +106,22 @@ def export(export_folder_name,
list_outputs_name = []
for node in graphview.get_nodes():
if len(node.get_children()) == 0:
- export_type = aidge_datatype2ctype(node.get_operator().get_output(0).dtype())
+ if node.get_operator().has_attr("DataType"):
+ # Temporary fix because impossible to set DataType of a generic operator
+ export_type = aidge_datatype2ctype(node.get_operator().get_attr("DataType"))
+ else:
+ export_type = aidge_datatype2ctype(node.get_operator().get_output(0).dtype())
+
list_outputs_name.append((export_type, node.name()))
+ if library == "n2d2":
+ forward_file = "forward.cpp"
+ else:
+ forward_file = "forward.c"
+
# Generate forward file
generate_file(
- str(dnn_folder / "src" / "forward.c"),
+ str(dnn_folder / "src" / forward_file),
str(ROOT / "templates" / "network" / "network_forward.jinja"),
headers=list_configs,
actions=list_actions,
@@ -106,18 +130,28 @@ def export(export_folder_name,
)
# Generate dnn internal API
- aidge_export_arm_cortexm.operators.generate_file(
- str(dnn_folder / "include" / "network_functions.h"),
- str(ROOT / "templates" / "network" / "dnn_header.jinja"),
- libraries=[],
- functions=get_functions_from_c_folder(str(dnn_folder / "src" / "kernels")),
- )
+ if library == "aidge":
+ # For Aidge, parse all kernels source code and retrieve function prototypes
+ generate_file(
+ str(dnn_folder / "include" / "network_functions.h"),
+ str(ROOT / "templates" / "network" / "network_prototypes.jinja"),
+ libraries=[],
+ functions=get_functions_from_c_folder(str(dnn_folder / "src" / "kernels")),
+ )
+ elif library == "n2d2":
+ # For N2D2, parse all the files in include/kernel/ and retrieve the names of the files
+ generate_file(
+ str(dnn_folder / "include" / "network_functions.h"),
+ str(ROOT / "templates" / "network" / "network_prototypes.jinja"),
+ libraries=[],
+ files=[str(Path("kernels") / x) for x in get_filenames_from_folder(str(dnn_folder / "include" / "kernels"), r'^.*\.hpp$')],
+ )
# Generate dnn API
- aidge_export_arm_cortexm.operators.generate_file(
+ generate_file(
str(dnn_folder / "include" / "dnn.h"),
str(ROOT / "templates" / "network" / "dnn_header.jinja"),
- libraries=[],
- functions=get_functions_from_c_file(str(dnn_folder / "src" / "forward.c")),
+ libraries=["stdint.h"],
+ functions=get_functions_from_c_file(str(dnn_folder / "src" / forward_file)),
)