From b957fede729a835fc0fbeff9e5e797580afe7a58 Mon Sep 17 00:00:00 2001
From: Gallas Gaye <gallasko@gmail.com>
Date: Fri, 21 Feb 2025 10:43:48 +0100
Subject: [PATCH] chore: Refactor duplicate code in operators
---
aidge_export_cpp/operators.py | 161 ++++++++++++++--------------------
1 file changed, 64 insertions(+), 97 deletions(-)
diff --git a/aidge_export_cpp/operators.py b/aidge_export_cpp/operators.py
index 0790877..346928f 100644
--- a/aidge_export_cpp/operators.py
+++ b/aidge_export_cpp/operators.py
@@ -122,6 +122,27 @@ class MatMulCPP(ExportNodeCpp):
str(ROOT / "kernels" / "matmul.hpp"),
]
+def _setup_conv2D(conv):
+ """Common setup code for convolutions: Conv2D and PaddedConv2D."""
+
+ # If biases are not provided we set it as nullptr instead of None
+ if (len(conv.attributes["in_name"]) > 2 and conv.attributes["in_name"][2] is None):
+ conv.attributes["in_name"][2] = "nullptr"
+
+ conv.attributes["activation"] = "Linear"
+ conv.attributes["rescaling"] = "NoScaling"
+ conv.config_template = str(
+ ROOT / "templates" / "configuration" / "convolution_config.jinja")
+ conv.forward_template = str(
+ ROOT / "templates" / "kernel_forward" / "convolution_forward.jinja")
+ conv.include_list = []
+ conv.kernels_to_copy = [
+ str(ROOT / "kernels" / "convolution.hpp"),
+ str(ROOT / "kernels" / "macs.hpp"),
+ str(ROOT / "kernels" / "activation.hpp"),
+ str(ROOT / "kernels" / "rescaling.hpp")
+ ]
+
@ExportLibCpp.register("Conv2D", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.float32)))
class ConvCPP(ExportNodeCpp):
def __init__(self, node, mem_info):
@@ -129,19 +150,8 @@ class ConvCPP(ExportNodeCpp):
# No padding with Conv
# Use PaddedConv to add padding attribute
self.attributes["padding"] = [0, 0]
- self.attributes["activation"] = "Linear"
- self.attributes["rescaling"] = "NoScaling"
- self.config_template = str(
- ROOT / "templates" / "configuration" / "convolution_config.jinja")
- self.forward_template = str(
- ROOT / "templates" / "kernel_forward" / "convolution_forward.jinja")
- self.include_list = []
- self.kernels_to_copy = [
- str(ROOT / "kernels" / "convolution.hpp"),
- str(ROOT / "kernels" / "macs.hpp"),
- str(ROOT / "kernels" / "activation.hpp"),
- str(ROOT / "kernels" / "rescaling.hpp")
- ]
+
+ _setup_conv2D(self)
@ExportLibCpp.register_metaop("PaddedConv2D", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.float32)))
class PaddedConvCPP(ExportNodeCpp):
@@ -159,74 +169,60 @@ class PaddedConvCPP(ExportNodeCpp):
).attr.stride_dims
self.attributes["dilation_dims"] = n.get_operator(
).attr.dilation_dims
- self.attributes["activation"] = "Linear"
- self.attributes["rescaling"] = "NoScaling"
- self.config_template = str(
- ROOT / "templates" / "configuration" / "convolution_config.jinja")
- self.forward_template = str(
- ROOT / "templates" / "kernel_forward" / "convolution_forward.jinja")
- self.include_list = []
- self.kernels_to_copy = [
- str(ROOT / "kernels" / "convolution.hpp"),
- str(ROOT / "kernels" / "macs.hpp"),
- str(ROOT / "kernels" / "activation.hpp"),
- str(ROOT / "kernels" / "rescaling.hpp")
- ]
+
+ _setup_conv2D(self)
+
+def _setup_elemwise_op(elemwise, op):
+ """Common code (template and kernel setup) shared across all the different elementWise operator (Add, Sub,...)."""
+
+ elemwise.attributes["elemwise_op"] = op
+ elemwise.attributes["activation"] = "Linear"
+ elemwise.attributes["rescaling"] = "NoScaling"
+ elemwise.config_template = str(
+ ROOT / "templates" / "configuration" / "elemwise_config.jinja")
+ elemwise.forward_template = str(
+ ROOT / "templates" / "kernel_forward" / "elemwise_forward.jinja")
+ elemwise.include_list = []
+ elemwise.kernels_to_copy = [
+ str(ROOT / "kernels" / "elemwise.hpp"),
+ str(ROOT / "kernels" / "activation.hpp"),
+ str(ROOT / "kernels" / "rescaling.hpp")
+ ]
@ExportLibCpp.register("Add", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.float32)))
class AddCPP(ExportNodeCpp):
def __init__(self, node, mem_info):
super().__init__(node, mem_info)
- self.attributes["elemwise_op"] = "Add"
- self.attributes["activation"] = "Linear"
- self.attributes["rescaling"] = "NoScaling"
- self.config_template = str(
- ROOT / "templates" / "configuration" / "elemwise_config.jinja")
- self.forward_template = str(
- ROOT / "templates" / "kernel_forward" / "elemwise_forward.jinja")
- self.include_list = []
- self.kernels_to_copy = [
- str(ROOT / "kernels" / "elemwise.hpp"),
- str(ROOT / "kernels" / "activation.hpp"),
- str(ROOT / "kernels" / "rescaling.hpp")
- ]
+
+ _setup_elemwise_op(self, "Add")
@ExportLibCpp.register("Sub", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.float32)))
class SubCPP(ExportNodeCpp):
def __init__(self, node, mem_info):
super().__init__(node, mem_info)
- self.attributes["elemwise_op"] = "Sub"
- self.attributes["activation"] = "Linear"
- self.attributes["rescaling"] = "NoScaling"
- self.config_template = str(
- ROOT / "templates" / "configuration" / "elemwise_config.jinja")
- self.forward_template = str(
- ROOT / "templates" / "kernel_forward" / "elemwise_forward.jinja")
- self.include_list = []
- self.kernels_to_copy = [
- str(ROOT / "kernels" / "elemwise.hpp"),
- str(ROOT / "kernels" / "activation.hpp"),
- str(ROOT / "kernels" / "rescaling.hpp")
- ]
+ _setup_elemwise_op(self, "Sub")
@ExportLibCpp.register("Mul", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.float32)))
class MulCPP(ExportNodeCpp):
def __init__(self, node, mem_info):
super().__init__(node, mem_info)
- self.attributes["elemwise_op"] = "Mul"
- self.attributes["activation"] = "Linear"
- self.attributes["rescaling"] = "NoScaling"
- self.config_template = str(
- ROOT / "templates" / "configuration" / "elemwise_config.jinja")
- self.forward_template = str(
- ROOT / "templates" / "kernel_forward" / "elemwise_forward.jinja")
- self.include_list = []
- self.kernels_to_copy = [
- str(ROOT / "kernels" / "elemwise.hpp"),
- str(ROOT / "kernels" / "activation.hpp"),
- str(ROOT / "kernels" / "rescaling.hpp")
- ]
+
+ _setup_elemwise_op(self, "Mul")
+
+def _setup_pooling(pooling):
+ """Common code (template and kernel setup) shared across all the different pooling operator."""
+
+ pooling.config_template = str(
+ ROOT / "templates" / "configuration" / "pooling_config.jinja")
+ pooling.forward_template = str(
+ ROOT / "templates" / "kernel_forward" / "pooling_forward.jinja")
+ pooling.include_list = []
+ pooling.kernels_to_copy = [
+ str(ROOT / "kernels" / "pooling.hpp"),
+ str(ROOT / "kernels" / "activation.hpp"),
+ str(ROOT / "kernels" / "rescaling.hpp")
+ ]
@ExportLibCpp.register("MaxPooling2D", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.float32)))
class MaxPoolCPP(ExportNodeCpp):
@@ -239,17 +235,7 @@ class MaxPoolCPP(ExportNodeCpp):
self.attributes["pool_type"] = "Max"
self.attributes["activation"] = "Linear"
- self.config_template = str(
- ROOT / "templates" / "configuration" / "pooling_config.jinja")
- self.forward_template = str(
- ROOT / "templates" / "kernel_forward" / "pooling_forward.jinja")
- self.include_list = []
- self.kernels_to_copy = [
- str(ROOT / "kernels" / "pooling.hpp"),
- str(ROOT / "kernels" / "activation.hpp"),
- str(ROOT / "kernels" / "rescaling.hpp")
- ]
-
+ _setup_pooling(self)
@ExportLibCpp.register_metaop("PaddedMaxPooling2D", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.float32)))
class PaddedMaxPoolCPP(ExportNodeCpp):
@@ -267,17 +253,7 @@ class PaddedMaxPoolCPP(ExportNodeCpp):
self.attributes["pool_type"] = "Max"
self.attributes["activation"] = "Linear"
- self.config_template = str(
- ROOT / "templates" / "configuration" / "pooling_config.jinja")
- self.forward_template = str(
- ROOT / "templates" / "kernel_forward" / "pooling_forward.jinja")
- self.include_list = []
- self.kernels_to_copy = [
- str(ROOT / "kernels" / "pooling.hpp"),
- str(ROOT / "kernels" / "activation.hpp"),
- str(ROOT / "kernels" / "rescaling.hpp")
- ]
-
+ _setup_pooling(self)
@ExportLibCpp.register("GlobalAveragePooling", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.float32)))
class GlobalAveragePoolCPP(ExportNodeCpp):
@@ -295,16 +271,7 @@ class GlobalAveragePoolCPP(ExportNodeCpp):
self.attributes["pool_type"] = "Average"
self.attributes["activation"] = "Linear"
- self.config_template = str(
- ROOT / "templates" / "configuration" / "pooling_config.jinja")
- self.forward_template = str(
- ROOT / "templates" / "kernel_forward" / "pooling_forward.jinja")
- self.include_list = []
- self.kernels_to_copy = [
- str(ROOT / "kernels" / "pooling.hpp"),
- str(ROOT / "kernels" / "activation.hpp"),
- str(ROOT / "kernels" / "rescaling.hpp")
- ]
+ _setup_pooling(self)
@ExportLibCpp.register("FC", aidge_core.ImplSpec(aidge_core.IOSpec(aidge_core.dtype.float32)))
class FcCPP(ExportNodeCpp):
--
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