diff --git a/aidge_export_cpp/export.py b/aidge_export_cpp/export.py
index 46ee73b89f61826c93a4c24a0167fb5b040ee01f..cf83ba9342042dc83903d49bf8c2782daf539089 100644
--- a/aidge_export_cpp/export.py
+++ b/aidge_export_cpp/export.py
@@ -39,93 +39,97 @@ def generate_input_file(export_folder:str,
def export(export_folder_name, graphview, scheduler, mem_wrapping=False):
+ es = aidge_core.export_utils.ExportScheduler(scheduler)
+ es.export(export_folder_name,
+ ExportLibCpp,
+ memory_manager=compute_default_mem_info)
- export_folder = Path().absolute() / export_folder_name
+ # export_folder = Path().absolute() / export_folder_name
- os.makedirs(str(export_folder), exist_ok=True)
+ # os.makedirs(str(export_folder), exist_ok=True)
- dnn_folder = export_folder / "dnn"
- os.makedirs(str(dnn_folder), exist_ok=True)
+ # dnn_folder = export_folder / "dnn"
+ # os.makedirs(str(dnn_folder), exist_ok=True)
- list_actions = []
- list_configs = []
- peak_mem, mem_info = compute_default_mem_info(scheduler)
- list_forward_nodes = scheduler.get_static_scheduling()
-
- for node in list_forward_nodes:
- if ExportLibCpp.exportable(node):
- op = ExportLibCpp.get_export_node(node)(node, mem_info[node])
- # For configuration files
- list_configs = op.export(dnn_folder, list_configs)
-
- # For forward file
- list_actions = op.forward(list_actions)
- else:
- raise RuntimeError(f"Operator not supported: {node.type()} !")
-
- # Memory management
- # stats_folder = export_folder / "statistics"
- # os.makedirs(str(stats_folder), exist_ok=True)
- # mem_size, mem_info = generate_optimized_memory_info(stats_folder, scheduler, mem_wrapping)
+ # list_actions = []
+ # list_configs = []
# peak_mem, mem_info = compute_default_mem_info(scheduler)
-
- # Generate the memory file
+ # list_forward_nodes = scheduler.get_static_scheduling()
+
+ # for node in list_forward_nodes:
+ # if ExportLibCpp.exportable(node):
+ # op = ExportLibCpp.get_export_node(node)(node, mem_info[node])
+ # # For configuration files
+ # list_configs = op.export(dnn_folder, list_configs)
+
+ # # For forward file
+ # list_actions = op.forward(list_actions)
+ # else:
+ # raise RuntimeError(f"Operator not supported: {node.type()} !")
+
+ # # Memory management
+ # # stats_folder = export_folder / "statistics"
+ # # os.makedirs(str(stats_folder), exist_ok=True)
+ # # mem_size, mem_info = generate_optimized_memory_info(stats_folder, scheduler, mem_wrapping)
+ # # peak_mem, mem_info = compute_default_mem_info(scheduler)
+
+ # # Generate the memory file
+ # # generate_file(
+ # # str(dnn_folder / "memory" / "mem_info.h"),
+ # # str(ROOT / "templates" / "memory" / "mem_info.jinja"),
+ # # mem_size = mem_size,
+ # # mem_info_legends = MEMORY_INFO_TEMPLATE,
+ # # mem_info = mem_info
+ # # )
+ # # list_configs.append("memory/mem_info.h")
+
+ # # Get entry nodes
+ # # Store the datatype & name
+ # list_inputs_name = []
+ # for node in graphview.get_input_nodes():
+ # for idx, node_input_tuple in enumerate(node.inputs()):
+ # node_input, _ = node_input_tuple
+ # if node_input is None:
+ # export_type = aidge2c(node.get_operator().get_output(0).dtype())
+ # list_inputs_name.append((export_type, f"{node.name()}_input_{idx}"))
+ # elif node_input not in graphview.get_nodes():
+ # export_type = aidge2c(node_input.get_operator().get_output(0).dtype())
+ # list_inputs_name.append((export_type, node_input.name()))
+
+
+ # # Get output nodes
+ # # Store the datatype & name, like entry nodes
+ # list_outputs_name = []
+ # for node in graphview.get_nodes():
+ # if len(node.get_children()) == 0:
+ # export_type = aidge2c(node.get_operator().get_output(0).dtype())
+ # list_outputs_name.append((export_type, f"{node.name()}_output_0"))
+
+ # # Generate forward file
+ # # TODO: for now the mem type is bound for all intermediate results, should change.
+ # # Note that we may have all inputs constants, hence select output type
+ # assert len(list_outputs_name) >= 1, f"TODO: requires some output to determine mem type"
+ # mem_ctype = list_outputs_name[0][0]
# generate_file(
- # str(dnn_folder / "memory" / "mem_info.h"),
- # str(ROOT / "templates" / "memory" / "mem_info.jinja"),
- # mem_size = mem_size,
- # mem_info_legends = MEMORY_INFO_TEMPLATE,
- # mem_info = mem_info
+ # str(dnn_folder / "src" / "forward.cpp"),
+ # str(ROOT / "templates" / "network" / "network_forward.jinja"),
+ # headers=set(list_configs),
+ # actions=list_actions,
+ # inputs= list_inputs_name,
+ # outputs=list_outputs_name,
+ # mem_ctype=mem_ctype,
+ # peak_mem=peak_mem
# )
- # list_configs.append("memory/mem_info.h")
-
- # Get entry nodes
- # Store the datatype & name
- list_inputs_name = []
- for node in graphview.get_input_nodes():
- for idx, node_input_tuple in enumerate(node.inputs()):
- node_input, _ = node_input_tuple
- if node_input is None:
- export_type = aidge2c(node.get_operator().get_output(0).dtype())
- list_inputs_name.append((export_type, f"{node.name()}_input_{idx}"))
- elif node_input not in graphview.get_nodes():
- export_type = aidge2c(node_input.get_operator().get_output(0).dtype())
- list_inputs_name.append((export_type, node_input.name()))
-
-
- # Get output nodes
- # Store the datatype & name, like entry nodes
- list_outputs_name = []
- for node in graphview.get_nodes():
- if len(node.get_children()) == 0:
- export_type = aidge2c(node.get_operator().get_output(0).dtype())
- list_outputs_name.append((export_type, f"{node.name()}_output_0"))
-
- # Generate forward file
- # TODO: for now the mem type is bound for all intermediate results, should change.
- # Note that we may have all inputs constants, hence select output type
- assert len(list_outputs_name) >= 1, f"TODO: requires some output to determine mem type"
- mem_ctype = list_outputs_name[0][0]
- generate_file(
- str(dnn_folder / "src" / "forward.cpp"),
- str(ROOT / "templates" / "network" / "network_forward.jinja"),
- headers=set(list_configs),
- actions=list_actions,
- inputs= list_inputs_name,
- outputs=list_outputs_name,
- mem_ctype=mem_ctype,
- peak_mem=peak_mem
- )
- # Generate dnn API
- generate_file(
- str(dnn_folder / "include" / "dnn.hpp"),
- str(ROOT / "templates" / "network" / "dnn_header.jinja"),
- libraries=[],
- functions=get_functions_from_c_file(str(dnn_folder / "src" / "forward.cpp")),
- )
+ # # Generate dnn API
+ # generate_file(
+ # str(dnn_folder / "include" / "dnn.hpp"),
+ # str(ROOT / "templates" / "network" / "dnn_header.jinja"),
+ # libraries=[],
+ # functions=get_functions_from_c_file(str(dnn_folder / "src" / "forward.cpp")),
+ # )
- # Copy all static files in the export
- shutil.copy(str(ROOT / "static" / "main.cpp"), str(export_folder))
- shutil.copy(str(ROOT / "static" / "Makefile"), str(export_folder))
- shutil.copytree(str(ROOT / "static" / "include"), str(dnn_folder / "include"), dirs_exist_ok=True)
+ # # Copy all static files in the export
+ # shutil.copy(str(ROOT / "static" / "main.cpp"), str(export_folder))
+ # shutil.copy(str(ROOT / "static" / "Makefile"), str(export_folder))
+ # shutil.copytree(str(ROOT / "static" / "include"), str(dnn_folder / "include"), dirs_exist_ok=True)