diff --git a/.gitignore b/.gitignore
index 8eb208c0cff93ea86a79a962adbc89978b7ae50e..55ab6d78711f9af47af0458596f474ba44379676 100644
--- a/.gitignore
+++ b/.gitignore
@@ -31,4 +31,4 @@ ENV/
xml*/
# Model parameters
-*.onnx
\ No newline at end of file
+*.onnx
diff --git a/aidge_export_arm_cortexm/export.py b/aidge_export_arm_cortexm/export.py
index de1de735401fb6a2790cd0d97215012f1aad42bd..f211fbbe957f55629bc48b77999b12c7c48d2c8a 100644
--- a/aidge_export_arm_cortexm/export.py
+++ b/aidge_export_arm_cortexm/export.py
@@ -4,7 +4,7 @@ import shutil
from pathlib import Path
import numpy as np
-from aidge_core.export_utils.code_generation import *
+from aidge_core.export.code_generation import *
from aidge_export_arm_cortexm.utils import (ROOT, AVAILABLE_BOARDS, has_board, \
OPERATORS_REGISTRY, supported_operators)
import aidge_export_arm_cortexm.operators
@@ -94,23 +94,28 @@ def export(export_folder_name,
# It supposes the entry nodes are producers with constant=false
# Store the datatype & name
list_inputs_name = []
+ first_element_added = False
for node in graphview.get_nodes():
if node.type() == "Producer":
+ if not first_element_added:
+ export_type = aidge_datatype2ctype(node.get_operator().get_output(0).dtype())
+ list_inputs_name.append((export_type, node.name()))
+ first_element_added = True
if not node.get_operator().attr.constant:
export_type = aidge_datatype2ctype(node.get_operator().get_output(0).dtype())
list_inputs_name.append((export_type, node.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:
- # print(node.name(), node.get_operator())
- # if node.get_operator().attr is not None:
- # # Temporary fix because impossible to set DataType of a generic operator
- # export_type = aidge_datatype2ctype(node.get_operator().attr.dtype)
- # else:
- export_type = aidge_datatype2ctype(node.get_operator().get_output(0).dtype())
+ if node.get_operator().attr.has_attr('dtype'):
+ # Temporary fix because impossible to set DataType of a generic operator
+ export_type = aidge_datatype2ctype(node.get_operator().attr.dtype)
+ else:
+ export_type = aidge_datatype2ctype(node.get_operator().get_output(0).dtype())
list_outputs_name.append((export_type, node.name()))
diff --git a/aidge_export_arm_cortexm/memory.py b/aidge_export_arm_cortexm/memory.py
index 859e441bf9fb61d42459700d4017e6dbafe820ac..7f7983fc7898bbd2d7fa383ecc0b5f16f290918f 100644
--- a/aidge_export_arm_cortexm/memory.py
+++ b/aidge_export_arm_cortexm/memory.py
@@ -29,7 +29,7 @@ MEMORY_INFO_TEMPLATE = ["layer_name", "size", "stride", "length", "count", "cont
# Default memory management, which can be used for development
def compute_default_mem_info(scheduler: aidge_core.Scheduler):
- list_forward_nodes = scheduler.get_static_scheduling()
+ list_forward_nodes = scheduler
mem_info = []
mem_size = 0
diff --git a/aidge_export_arm_cortexm/operators.py b/aidge_export_arm_cortexm/operators.py
index 3a504dba94a23b8c78b6bfff57972659a23353c3..0d2a3c6f7f5773684ea71a8d562d97243cd5fae5 100644
--- a/aidge_export_arm_cortexm/operators.py
+++ b/aidge_export_arm_cortexm/operators.py
@@ -8,7 +8,7 @@ from typing import Tuple, List, Union, Dict
import aidge_core
from aidge_core import ExportNode
-from aidge_core.export_utils.code_generation import *
+from aidge_core.export.code_generation import *
from aidge_export_arm_cortexm.utils import ROOT, operator_register
from aidge_export_arm_cortexm.utils.converter import numpy_dtype2ctype, aidge_datatype2dataformat, aidge_datatype2ctype
from aidge_export_arm_cortexm.utils.generation import *
@@ -275,9 +275,10 @@ class Conv_ARMCortexM(ExportNode):
# Use PaddedConv to add padding attribute
self.padding = [0, 0]
- self.nb_channels = node.get_operator().attr.in_channels
- self.nb_outputs = node.get_operator().attr.out_channels
-
+ self.nb_channels = node.get_operator().in_channels()
+ self.nb_outputs = node.get_operator().out_channels()
+ if self.inputs[0] is None :
+ raise RuntimeError("")
if len(self.inputs_dims[0]) == 4:
# if dims == [batch, nb_channels, height, width]
# transform to [nb_channels, height, width]
@@ -414,7 +415,7 @@ class ConvReluScaling_ARMCortexM(Conv_ARMCortexM):
def __init__(self, node, board, library):
super(Conv_ARMCortexM, self).__init__(node, board, library)
- if self.operator.attr.has_attr.begin_end_borders:
+ if self.operator.has_attr("Begin_End_Borders"):
self.padding = self.operator.attr.begin_end_borders
self.activation = "Rectifier"
diff --git a/aidge_export_arm_cortexm/operators_old.py b/aidge_export_arm_cortexm/operators_old.py
index 04a090b65c56a0a503618c80480e51ac4fbd6550..3440b248b1b719f4e5573d5c4dcc9df0b450122c 100644
--- a/aidge_export_arm_cortexm/operators_old.py
+++ b/aidge_export_arm_cortexm/operators_old.py
@@ -403,9 +403,9 @@ class Slice(ExportNode):
def __init__(self, node, board, dataformat, library):
- self.axes = node.get_operator().get_attr("axes")
- self.starts = node.get_operator().get_attr("starts")
- self.ends = node.get_operator().get_attr("ends")
+ self.axes = node.get_operator().attr.axes
+ self.starts = node.get_operator().attr.starts
+ self.ends = node.get_operator().attr.ends
# Compute output dims
out_dims = [self.ends[x-1] - self.starts[x-1] for x in self.axes]
@@ -460,7 +460,7 @@ class Concat(ExportNode):
def __init__(self, node, board, dataformat, library):
- self.axis = node.get_operator().get_attr("axis")
+ self.axis = node.get_operator().attr.axis
out_dims = node.get_operator().get_input(0).dims()
out_dims[self.axis - 1] = 0
diff --git a/aidge_export_arm_cortexm/templates/network/network_forward.jinja b/aidge_export_arm_cortexm/templates/network/network_forward.jinja
index b00e42f813066505cf03dd9f324a4ac418e45818..bde5553020d1a36f225a1402172715a7446c4496 100644
--- a/aidge_export_arm_cortexm/templates/network/network_forward.jinja
+++ b/aidge_export_arm_cortexm/templates/network/network_forward.jinja
@@ -12,7 +12,11 @@
{# 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 -#}
diff --git a/aidge_export_arm_cortexm/utils/converter.py b/aidge_export_arm_cortexm/utils/converter.py
index cffc0df919f15cd48a1dc1c58326f5557a76dc48..9d8bd15b2684986829a542b9c2bf1002605e37e0 100644
--- a/aidge_export_arm_cortexm/utils/converter.py
+++ b/aidge_export_arm_cortexm/utils/converter.py
@@ -21,35 +21,35 @@ def numpy_dtype2ctype(dtype):
raise ValueError(f"Unsupported {dtype} dtype")
-def aidge_datatype2ctype(dtype):
- if dtype == aidge_core.dtype.int8:
+def aidge_datatype2ctype(datatype):
+ if datatype == aidge_core.dtype.int8:
return "int8_t"
- elif dtype == aidge_core.dtype.uint8:
+ elif datatype == aidge_core.dtype.uint8:
return "uint8_t"
- elif dtype == aidge_core.dtype.int32:
+ elif datatype == aidge_core.dtype.int32:
return "int32_t"
- elif dtype == aidge_core.dtype.int64:
+ elif datatype == aidge_core.dtype.int64:
return "int64_t"
- elif dtype == aidge_core.dtype.float32:
+ elif datatype == aidge_core.dtype.float32:
return "float"
- elif dtype == aidge_core.dtype.float64:
+ elif datatype == aidge_core.dtype.float64:
return "double"
# Add more dtype mappings as needed
else:
- raise ValueError(f"Unsupported {dtype} aidge dtype")
+ raise ValueError(f"Unsupported {datatype} aidge dtype")
-def aidge_datatype2dataformat(dtype):
- if dtype == aidge_core.dtype.int8:
+def aidge_datatype2dataformat(datatype):
+ if datatype == aidge_core.dtype.int8:
return "int8"
- elif dtype == aidge_core.dtype.int32:
+ elif datatype == aidge_core.dtype.int32:
return "int32"
- elif dtype == aidge_core.dtype.int64:
+ elif datatype == aidge_core.dtype.int64:
return "int64"
- elif dtype == aidge_core.dtype.float32:
+ elif datatype == aidge_core.dtype.float32:
return "float32"
- elif dtype == aidge_core.dtype.float64:
+ elif datatype == aidge_core.dtype.float64:
return "float64"
# Add more dtype mappings as needed
else:
- raise ValueError(f"Unsupported {dtype} aidge dtype")
+ raise ValueError(f"Unsupported {datatype} aidge dtype")