diff --git a/aidge_export_cpp/export_utils.py b/aidge_export_cpp/export_utils.py
index c82c64318b39b799c3ad78bc45a35d5a8b123e78..b8f9eaf74d1ec604e1b837b33e77bd0e60c3ddba 100644
--- a/aidge_export_cpp/export_utils.py
+++ b/aidge_export_cpp/export_utils.py
@@ -2,6 +2,7 @@ import os
from collections import OrderedDict
import aidge_core
+from aidge_core.export_utils import get_node
def cpp_fuse_to_metaops(graph_view: aidge_core.GraphView):
"""
@@ -197,17 +198,15 @@ def set_scaling_attributes(export_node: aidge_core.export_utils.ExportNode, node
:type node: aidge_core.Node
"""
- if node.type() == "Quantizer":
- for n in node.get_operator().get_micro_graph().get_nodes():
+ QNode = get_node(node, "Quantizer")
+
+ if QNode is not None:
+ for n in QNode.get_operator().get_micro_graph().get_nodes():
if n.type() == "BitShift":
export_node.attributes["shift_value"] = n.get_operator().get_input(1)[0]
elif n.type() == "Mul":
export_node.attributes["coef_value"] = n.get_operator().get_input(1)[0]
- elif isinstance(node.get_operator(), aidge_core.MetaOperatorOp):
- for n in node.get_operator().get_micro_graph().get_nodes():
- set_scaling_attributes(export_node, n)
-
def normalize(array):
diff --git a/aidge_export_cpp/operators/Activation.py b/aidge_export_cpp/operators/Activation.py
index 8bb52f9a6eb4450bdd6a2b60f5b07f2068bf42e9..55e7e19425e0a5b61790b58a2d36a8f233f75228 100644
--- a/aidge_export_cpp/operators/Activation.py
+++ b/aidge_export_cpp/operators/Activation.py
@@ -40,9 +40,7 @@ class QReLU(ReLU):
super().__init__(node, mem_info)
# Browse the metaop to update kernel attributes
- for n in node.get_operator().get_micro_graph().get_nodes():
- if n.type() == "Quantizer":
- set_scaling_attributes(self, n)
+ set_scaling_attributes(self, node)
# Update the scaling type
if self.attributes["coef_value"] != 1:
diff --git a/aidge_export_cpp/operators/Conv.py b/aidge_export_cpp/operators/Conv.py
index e2562f79c2e8428efe7a23ec6290515827eeb48a..4207184b6417f96064f5f8c1f6dcca38df07c13a 100644
--- a/aidge_export_cpp/operators/Conv.py
+++ b/aidge_export_cpp/operators/Conv.py
@@ -1,5 +1,5 @@
import aidge_core
-from aidge_core.export_utils import ExportNodeCpp
+from aidge_core.export_utils import ExportNodeCpp, get_node
from aidge_export_cpp import ROOT, ExportLibCpp, set_scaling_attributes
@ExportLibCpp.register("Conv2D", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.any)))
@@ -17,7 +17,10 @@ class Conv(ExportNodeCpp):
self.attributes["shift_value"] = 0
# Browse the metaop to update kernel attributes
- self.get_conv_attributes(node)
+ ConvNode = get_node(node, "Conv2D")
+ self.attributes["kernel_dims"] = ConvNode.get_operator().attr.kernel_dims
+ self.attributes["stride_dims"] = ConvNode.get_operator().attr.stride_dims
+ self.attributes["dilation_dims"] = ConvNode.get_operator().attr.dilation_dims
# Template for layer configutation file generation
self.config_template = str(ROOT / "templates" / "configuration" / "convolution_config.jinja")
@@ -35,17 +38,7 @@ class Conv(ExportNodeCpp):
# Include aidge outputs within the fwd file
if self.attributes["aidge_cmp"]:
self.include_list.append("network/utils.hpp") # aidge_cmp function
- self.include_list.append("data/aidge_outputs/" + node.name() + ".hpp")
-
- def get_conv_attributes(self, node):
- if isinstance(node.get_operator(), aidge_core.MetaOperatorOp):
- for n in node.get_operator().get_micro_graph().get_nodes():
- self.get_conv_attributes(n)
-
- elif node.type() == "Conv2D":
- self.attributes["kernel_dims"] = node.get_operator().attr.kernel_dims
- self.attributes["stride_dims"] = node.get_operator().attr.stride_dims
- self.attributes["dilation_dims"] = node.get_operator().attr.dilation_dims
+ self.include_list.append("data/aidge_outputs/" + node.name() + ".hpp")
@ExportLibCpp.register_metaop("QConv", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.any)))
@@ -67,9 +60,8 @@ class PadConv(QConv):
super().__init__(node, mem_info)
# Browse the metaop to update kernel attributes
- for n in node.get_operator().get_micro_graph().get_nodes():
- if n.type() == "Pad2D":
- self.attributes["padding"] = n.get_operator().attr.begin_end_borders
+ PadNode = get_node(node, "Pad2D")
+ self.attributes["padding"] = PadNode.get_operator().attr.begin_end_borders
@ExportLibCpp.register_metaop("ConvAct", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.any)))
@@ -78,13 +70,11 @@ class ConvAct(QConv):
super().__init__(node, mem_info)
# Browse the metaop to update kernel attributes
- for n in node.get_operator().get_micro_graph().get_nodes():
- if n.type() == "ReLU":
- self.attributes["activation"] = "Rectifier"
- elif n.type() == "LeakyReLU":
- aidge_core.Log.fatal(f"{n.type()} activation is not yet supported.")
- # TODO : Should not be checked manually for each activation
-
+ if get_node(node, "ReLU") is not None:
+ self.attributes["activation"] = "Rectifier"
+ elif get_node(node, "LeakyReLU") is not None:
+ aidge_core.Log.fatal(f"{node.type()} activation is not yet supported.")
+ # TODO : Should not be checked manually for each activation
@ExportLibCpp.register_metaop("PadConvAct", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.any)))
class PadConvAct(PadConv, ConvAct):
diff --git a/aidge_export_cpp/operators/ElemWise.py b/aidge_export_cpp/operators/ElemWise.py
index c27c351451aeff90203ea1481fe2fbd5318ce065..6a9ee7e4d2241ed424262f6af9d401aa3aaf52ba 100644
--- a/aidge_export_cpp/operators/ElemWise.py
+++ b/aidge_export_cpp/operators/ElemWise.py
@@ -1,5 +1,5 @@
import aidge_core
-from aidge_core.export_utils import ExportNodeCpp
+from aidge_core.export_utils import ExportNodeCpp, get_node
from aidge_export_cpp import ROOT, ExportLibCpp, set_scaling_attributes
class ElemWise(ExportNodeCpp):
@@ -38,9 +38,7 @@ class QElemWise(ElemWise):
super().__init__(node, mem_info)
# Browse the metaop to update kernel attributes
- for n in node.get_operator().get_micro_graph().get_nodes():
- if n.type() == "Quantizer":
- set_scaling_attributes(self, n)
+ set_scaling_attributes(self, node)
## Set the scaling type
if self.attributes["coef_value"] != 1:
@@ -68,12 +66,11 @@ class AddAct(QAdd):
super().__init__(node, mem_info)
# Browse the metaop to update kernel attributes
- for n in node.get_operator().get_micro_graph().get_nodes():
- if n.type() == "ReLU":
- self.attributes["activation"] = "Rectifier"
- elif n.type() == "LeakyReLU":
- aidge_core.Log.fatal(f"{n.type()} activation is not yet supported.")
- # TODO : Should not be checked manually for each activation
+ if get_node(node, "ReLU") is not None:
+ self.attributes["activation"] = "Rectifier"
+ elif get_node(node, "LeakyReLU") is not None:
+ aidge_core.Log.fatal(f"{node.type()} activation is not yet supported.")
+ # TODO : Should not be checked manually for each activation
@ExportLibCpp.register("Sub", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.any)))
@@ -95,12 +92,11 @@ class SubAct(QSub):
super().__init__(node, mem_info)
# Browse the metaop to update kernel attributes
- for n in node.get_operator().get_micro_graph().get_nodes():
- if n.type() == "ReLU":
- self.attributes["activation"] = "Rectifier"
- elif n.type() == "LeakyReLU":
- aidge_core.Log.fatal(f"{n.type()} activation is not yet supported.")
- # TODO : Should not be checked manually for each activation
+ if get_node(node, "ReLU") is not None:
+ self.attributes["activation"] = "Rectifier"
+ elif get_node(node, "LeakyReLU") is not None:
+ aidge_core.Log.fatal(f"{node.type()} activation is not yet supported.")
+ # TODO : Should not be checked manually for each activation
@ExportLibCpp.register("Mul", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.any)))
@@ -122,9 +118,8 @@ class MulAct(QMul):
super().__init__(node, mem_info)
# Browse the metaop to update kernel attributes
- for n in node.get_operator().get_micro_graph().get_nodes():
- if n.type() == "ReLU":
- self.attributes["activation"] = "Rectifier"
- elif n.type() == "LeakyReLU":
- aidge_core.Log.fatal(f"{n.type()} activation is not yet supported.")
- # TODO : Should not be checked manually for each activation
\ No newline at end of file
+ if get_node(node, "ReLU") is not None:
+ self.attributes["activation"] = "Rectifier"
+ elif get_node(node, "LeakyReLU") is not None:
+ aidge_core.Log.fatal(f"{node.type()} activation is not yet supported.")
+ # TODO : Should not be checked manually for each activation
\ No newline at end of file
diff --git a/aidge_export_cpp/operators/Fc.py b/aidge_export_cpp/operators/Fc.py
index 05eff821467478a22fc9d7885b78e6ff2c3f6e71..b83754be36bc8f79dc981cbeb41bb9a86aa4e50a 100644
--- a/aidge_export_cpp/operators/Fc.py
+++ b/aidge_export_cpp/operators/Fc.py
@@ -40,9 +40,7 @@ class QFC(FC):
super().__init__(node, mem_info)
# Browse the metaop to update kernel attributes
- for n in node.get_operator().get_micro_graph().get_nodes():
- if n.type() == "Quantizer":
- set_scaling_attributes(self, n)
+ set_scaling_attributes(self, node)
## Set the scaling type
if self.attributes["shift_value"] != 0:
diff --git a/aidge_export_cpp/operators/Pool.py b/aidge_export_cpp/operators/Pool.py
index 558ec1bd522fb0005c1d47fcac7ca84c4992fd7e..5b483bdeb8b634391f8edaa9340a901a100d4aad 100644
--- a/aidge_export_cpp/operators/Pool.py
+++ b/aidge_export_cpp/operators/Pool.py
@@ -1,5 +1,5 @@
import aidge_core
-from aidge_core.export_utils import ExportNodeCpp
+from aidge_core.export_utils import ExportNodeCpp, get_node
from aidge_export_cpp import ROOT
from aidge_export_cpp import ExportLibCpp
@@ -37,9 +37,8 @@ class PadPool(Pool):
super().__init__(node, mem_info)
# Browse the metaop to update kernel attributes
- for n in node.get_operator().get_micro_graph().get_nodes():
- if n.type() == "Pad2D":
- self.attributes["padding"] = n.get_operator().attr.begin_end_borders
+ PadNode = get_node(node, "Pad2D")
+ self.attributes["padding"] = PadNode.get_operator().attr.begin_end_borders
class PoolAct(Pool):
@@ -47,12 +46,11 @@ class PoolAct(Pool):
super().__init__(node, mem_info)
# Browse the metaop to update kernel attributes
- for n in node.get_operator().get_micro_graph().get_nodes():
- if n.type() == "ReLU":
- self.attributes["activation"] = "Rectifier"
- elif n.type() == "LeakyReLU":
- aidge_core.Log.fatal(f"{n.type()} activation is not yet supported.")
- # TODO : Should not be checked manually for each activation
+ if get_node(node, "ReLU") is not None:
+ self.attributes["activation"] = "Rectifier"
+ elif get_node(node, "LeakyReLU") is not None:
+ aidge_core.Log.fatal(f"{node.type()} activation is not yet supported.")
+ # TODO : Should not be checked manually for each activation
@ExportLibCpp.register("MaxPooling2D", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.any)))
@@ -61,17 +59,10 @@ class MaxPool(Pool):
super().__init__(node, mem_info)
# Browse the metaop to update kernel attributes
- self.get_maxpool_attributes(node)
-
- def get_maxpool_attributes(self, node):
- if isinstance(node.get_operator(), aidge_core.MetaOperatorOp):
- for n in node.get_operator().get_micro_graph().get_nodes():
- self.get_maxpool_attributes(n)
-
- elif node.type() == "MaxPooling2D":
- self.attributes["pool_type"] = "Max"
- self.attributes["kernel_dims"] = node.get_operator().attr.kernel_dims
- self.attributes["stride_dims"] = node.get_operator().attr.stride_dims
+ PoolNode = get_node(node, "MaxPooling2D")
+ self.attributes["pool_type"] = "Max"
+ self.attributes["kernel_dims"] = PoolNode.get_operator().attr.kernel_dims
+ self.attributes["stride_dims"] = PoolNode.get_operator().attr.stride_dims
@ExportLibCpp.register_metaop("PadMaxPool", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.any)))
@@ -98,17 +89,10 @@ class AvgPool(Pool):
super().__init__(node, mem_info)
# Browse the metaop to update kernel attributes
- self.get_avgpool_attributes(node)
-
- def get_avgpool_attributes(self, node):
- if isinstance(node.get_operator(), aidge_core.MetaOperatorOp):
- for n in node.get_operator().get_micro_graph().get_nodes():
- self.get_avgpool_attributes(n)
-
- elif node.type() == "AvgPooling2D":
- self.attributes["pool_type"] = "Average"
- self.attributes["kernel_dims"] = node.get_operator().attr.kernel_dims
- self.attributes["stride_dims"] = node.get_operator().attr.stride_dims
+ PoolNode = get_node(node, "AvgPooling2D")
+ self.attributes["pool_type"] = "Average"
+ self.attributes["kernel_dims"] = PoolNode.get_operator().attr.kernel_dims
+ self.attributes["stride_dims"] = PoolNode.get_operator().attr.stride_dims
@ExportLibCpp.register_metaop("PadAvgPool", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.any)))
@@ -134,17 +118,8 @@ class GlobalAvgPool(Pool):
def __init__(self, node, mem_info):
super().__init__(node, mem_info)
- # Browse the metaop to update kernel attributes
- self.get_globalavgpool_attributes(node)
-
- def get_globalavgpool_attributes(self, node):
- if isinstance(node.get_operator(), aidge_core.MetaOperatorOp):
- for n in node.get_operator().get_micro_graph().get_nodes():
- self.get_globalavgpool_attributes(n)
-
- elif node.type() == "GlobalAvgPooling":
- self.attributes["pool_type"] = "Average"
- self.attributes["kernel_dims"] = [self.attributes["in_width"][0], self.attributes["in_height"][0]]
+ self.attributes["pool_type"] = "Average"
+ self.attributes["kernel_dims"] = [self.attributes["in_width"][0], self.attributes["in_height"][0]]
@ExportLibCpp.register_metaop("PadGlobalAvgPool", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.any)))
diff --git a/aidge_export_cpp/operators/Quantizer.py b/aidge_export_cpp/operators/Quantizer.py
index 8a6c1ae824b60682286cced7cdc2300cef5a1ba0..cadc3bf6d77ee91e16e864ec90af49da74820b7c 100644
--- a/aidge_export_cpp/operators/Quantizer.py
+++ b/aidge_export_cpp/operators/Quantizer.py
@@ -1,5 +1,5 @@
import aidge_core
-from aidge_core.export_utils import ExportNodeCpp
+from aidge_core.export_utils import ExportNodeCpp, get_node
from aidge_export_cpp import ROOT, ExportLibCpp, set_scaling_attributes
@ExportLibCpp.register_metaop("Quantizer", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.any)))
@@ -12,14 +12,14 @@ class CppRescaling(ExportNodeCpp):
self.attributes["rescaling"] = "NoScaling"
self.attributes["shift_value"] = 0
self.attributes["coef_value"] = 1
+ self.attributes["aidge_cmp"] = node.attributes().has_attr("aidge_cmp")
# Browse the metaop to update kernel attributes
- for n in node.get_operator().get_micro_graph().get_nodes():
- if n.type() == "ReLU":
- self.attributes["activation"] = "Rectifier"
- elif n.type() == "LeakyReLU":
- aidge_core.Log.fatal(f"{n.type()} activation is not yet supported.")
- # TODO : Should not be checked manually for each activation
+ if get_node(node, "ReLU") is not None:
+ self.attributes["activation"] = "Rectifier"
+ elif get_node(node, "LeakyReLU") is not None:
+ aidge_core.Log.fatal(f"{node.type()} activation is not yet supported.")
+ # TODO : Should not be checked manually for each activation
# Set scaling attributes
set_scaling_attributes(self, node)