diff --git a/aidge_export_arm_cortexm/export.py b/aidge_export_arm_cortexm/export.py
index 2041ca3ad6545607ef37ac3114c7d2a3be24fe2f..5179937e86974de4e3134f9652e99ef2918751bc 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.code_generation import *
+from aidge_core.export_utils.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
@@ -15,13 +15,13 @@ from aidge_export_arm_cortexm.memory import *
-def export(export_folder_name,
+def export(export_folder_name,
graphview,
scheduler = None,
board:str ="stm32h7",
library:str = "aidge",
mem_wrapping = False):
-
+
# Create export directory
export_folder = Path().absolute() / export_folder_name
os.makedirs(str(export_folder), exist_ok=True)
@@ -36,7 +36,7 @@ def export(export_folder_name,
board_path = AVAILABLE_BOARDS[board]
else:
raise ValueError(f"{board} not found in the package. Please among those boards: {list(AVAILABLE_BOARDS.keys())}")
-
+
# Copy all static files in the export
shutil.copytree(board_path, str(export_folder), dirs_exist_ok=True)
diff --git a/aidge_export_arm_cortexm/operators.py b/aidge_export_arm_cortexm/operators.py
index dbcfc096dceae1144564579712791c6e4223d239..b0f4f60b68d7ca414c50b821551e7664d05ca27a 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.code_generation import *
+from aidge_core.export_utils.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 *
@@ -78,23 +78,23 @@ class Producer_ARMCortexM:
def export(self, export_file:Path, format:str = "NHWC"):
- if (len(self.values.shape) == 4):
+ if (len(self.values.shape) == 4):
# Suppose original dataformat is NCHW
if format == "NCHW":
- export_params(self.name,
- self.values.reshape(-1),
+ export_params(self.name,
+ self.values.reshape(-1),
str(export_file))
elif format == "NHWC":
- export_params(self.name,
- np.transpose(self.values, (0, 2, 3, 1)).reshape(-1),
+ export_params(self.name,
+ np.transpose(self.values, (0, 2, 3, 1)).reshape(-1),
str(export_file))
else:
raise RuntimeError("Producer format export not supported.")
else:
- export_params(self.name,
- self.values.reshape(-1),
+ export_params(self.name,
+ self.values.reshape(-1),
str(export_file))
-
+
class Scaling():
class ScalingMode:
@@ -158,7 +158,7 @@ class Scaling():
assert precision >= 1.0
return power_of_2_divs, precision
-
+
def __call__(self, mode:str) -> dict:
"""Get dictionnary of scale values in function of the mode
@@ -168,9 +168,9 @@ class Scaling():
- fixed_point (16 or 32 bits)
- single_shift
- double_shift
-
+
"""
-
+
if mode == "floating_point":
self.scaling = {"scaling_type": "floating_point",
"scaling_value": self.scaling_factor}
@@ -189,7 +189,7 @@ class Scaling():
self.scaling = {"scaling_type": "single_shift",
"shift_value": shift_value[0]}
-
+
elif mode == "double_shift":
shift_value, _ = self.approximate_shift_scaling(self.scaling_factor, 2)
@@ -200,7 +200,7 @@ class Scaling():
self.scaling = {"scaling_type": "no_scaling"}
return self.scaling
-
+
@operator_register("ReLU")
class ReLU_ARMCortexM(ExportNode):
@@ -300,7 +300,7 @@ class Conv_ARMCortexM(ExportNode):
# Convert the biases to int32
if self.dataformat != "float32":
self.producers[1].values = self.producers[1].values.astype(np.int32)
-
+
self.producers[1].export(export_folder / "parameters" / f"{self.producers[1].name}.h")
list_configs.append(f"parameters/{self.producers[1].name}.h")
@@ -323,7 +323,7 @@ class Conv_ARMCortexM(ExportNode):
stride=self.stride,
padding=self.padding,
dilation=self.dilation)
-
+
elif self.library == "n2d2":
# Export configuration file
generate_file(
@@ -368,9 +368,9 @@ class Conv_ARMCortexM(ExportNode):
biases_name=self.inputs[2].name(),
outputs_name=self.name
))
-
+
return list_actions
-
+
@operator_register("PaddedConv")
class PaddedConv_ARMCortexM(Conv_ARMCortexM):
@@ -406,7 +406,7 @@ class PaddedConv_ARMCortexM(Conv_ARMCortexM):
if len(self.outputs_dims[0]) == 4:
# if dims == [batch, nb_outputs]
# transform to [nb_outputs, 1, 1]
- self.outputs_dims[0] = self.outputs_dims[0][1:]
+ self.outputs_dims[0] = self.outputs_dims[0][1:]
@operator_register("ConvReluScaling")
@@ -431,7 +431,7 @@ class ConvReluScaling_ARMCortexM(Conv_ARMCortexM):
# Impose Single Shift (perhaps change it to have a more modular system)
self.scaling = Scaling(self.operator.get_attr("scalingFactor"),
self.operator.get_attr("quantizedNbBits"))("floating_point")
-
+
class Pooling_ARMCortexM(ExportNode):
def __init__(self, node, board, library):
@@ -474,7 +474,7 @@ class Pooling_ARMCortexM(ExportNode):
copyfile(str(ROOT / "_Aidge_Arm" / "kernels" / "SupportFunctions" / "aidge_supportfunctions.h"),
str(Path(export_folder) / "include"))
- # Export configuration file
+ # Export configuration file
generate_file(
str(export_folder / "layers" / f"{self.name}.h"),
str(ROOT / "_Aidge_Arm" / "templates" / "configuration" / "pooling.jinja"),
@@ -485,8 +485,8 @@ class Pooling_ARMCortexM(ExportNode):
stride=self.stride,
padding=self.padding,
pool_type=self.pool_type)
-
-
+
+
elif self.library == "n2d2":
# Nothing to copy
@@ -572,7 +572,7 @@ class FC_ARMCortexM(ExportNode):
# if dims == [batch, nb_channels, height, width]
# transform to [nb_channels, height, width]
self.inputs_dims[0] = self.inputs_dims[0][1:]
-
+
# It also means that we need to change the dataformat of the weights
weights = self.producers[0].values
if len(weights.shape) == 2:
@@ -623,7 +623,7 @@ class FC_ARMCortexM(ExportNode):
channel_height=self.inputs_dims[0][1],
channel_width=self.inputs_dims[0][2],
nb_outputs=self.outputs_dims[0][0])
-
+
elif self.library == "n2d2":
# Export configuration file
@@ -635,7 +635,7 @@ class FC_ARMCortexM(ExportNode):
output_dims=self.outputs_dims[0],
activation=self.activation,
**self.scaling)
-
+
return list_configs
def forward(self, list_actions:list):
@@ -666,7 +666,7 @@ class FC_ARMCortexM(ExportNode):
return list_actions
-
+
@operator_register("FcScaling")
class FCScaling_ARMCortexM(FC_ARMCortexM):