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Commit 15a0329f authored by Cyril Moineau's avatar Cyril Moineau
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Update export cpp to the new ExportLib object.

parent 73fa43b6
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3 merge requests!27v0.2.0,!22v0.4.0,!15Export refactor
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aidge_export_cpp/__init__.py
+ 1
− 0
View file @ 15a0329f
......@@ -2,6 +2,7 @@ r"""
Aidge Export for CPP standalone projects
"""
from .export_registry import ExportLibCpp
from .operators import *
from collections import defaultdict
......
aidge_export_cpp/export.py
+ 3
− 3
View file @ 15a0329f
......@@ -13,6 +13,7 @@ from aidge_core.export_utils.code_generation import *
from aidge_export_cpp.utils import (ROOT, OPERATORS_REGISTRY, supported_operators)
from aidge_export_cpp.utils.converter import numpy_dtype2ctype
import aidge_export_cpp.operators
from aidge_export_cpp import ExportLibCpp
from aidge_export_cpp.utils.generation import *
from aidge_export_cpp.memory import *
......@@ -50,9 +51,8 @@ def export(export_folder_name, graphview, scheduler, mem_wrapping=False):
list_forward_nodes = scheduler.get_static_scheduling()
for node in list_forward_nodes:
if node.type() in supported_operators():
op = OPERATORS_REGISTRY[node.type()](node)
if ExportLibCpp.exportable(node):
op = ExportLibCpp.get_export_node(node)
# For configuration files
list_configs = op.export(dnn_folder, list_configs)
......
aidge_export_cpp/operators.py
+ 131
− 67
View file @ 15a0329f
......@@ -3,39 +3,39 @@ import shutil
import numpy as np
from pathlib import Path
from jinja2 import Environment, FileSystemLoader
from aidge_core import ExportNode, ExportNodeCpp
from aidge_core.export_utils.code_generation import *
from aidge_export_cpp.utils import ROOT, operator_register
from aidge_core.export_utils import ExportNode, ExportNodeCpp, operator_register, generate_str, generate_file
from aidge_export_cpp.utils import ROOT
from aidge_export_cpp.utils.converter import numpy_dtype2ctype
from aidge_export_cpp.utils.generation import *
from aidge_export_cpp import ExportLibCpp
##############################################
################### Utils ####################
##############################################
def get_node_parents(node):
parents = []
for parent in node.get_parents():
if parent.type() != "Producer":
parents.append(parent)
return parents
def get_producer_parents(node):
parents = []
for parent in node.get_parents():
if parent.type() == "Producer":
parents.append(parent)
return parents
# def get_node_parents(node):
# parents = []
# for parent in node.get_parents():
# if parent.type() != "Producer":
# parents.append(parent)
# return parents
# def get_producer_parents(node):
# parents = []
# for parent in node.get_parents():
# if parent.type() == "Producer":
# parents.append(parent)
# return parents
##############################################
############## Export functions ##############
##############################################
def export_params(name:str,
def export_params(name: str,
array: np.ndarray,
filepath:str):
filepath: str):
# Get directory name of the file
dirname = os.path.dirname(filepath)
......@@ -47,9 +47,9 @@ def export_params(name:str,
generate_file(
filepath,
str(ROOT / "templates" / "data" / "parameters.jinja"),
name = name,
data_t = numpy_dtype2ctype(array.dtype),
values = array.tolist()
name=name,
data_t=numpy_dtype2ctype(array.dtype),
values=array.tolist()
)
......@@ -58,17 +58,17 @@ def export_params(name:str,
##############################################
@operator_register("Producer")
@operator_register(ExportLibCpp, "Producer")
class ProducerCPP(ExportNode):
def __init__(self, node):
super().__init__(node)
self.values = np.array(self.operator.get_output(0))
if len(self.values.shape) == 4: # Note: export in HWC
if len(self.values.shape) == 4: # Note: export in HWC
self.values = np.transpose(self.values, (0, 2, 3, 1))
def export(self, export_folder:Path, list_configs:list):
def export(self, export_folder: Path, list_configs: list):
list_configs.append(f"parameters/{self.attributes['name']}.h")
export_params(
......@@ -78,26 +78,36 @@ class ProducerCPP(ExportNode):
return list_configs
def forward(self, list_actions:list):
def forward(self, list_actions: list):
# A Producer does nothing during forward
return list_actions
@classmethod
def exportable(cls, node):
return True # TODO add check i/o NCHW
@operator_register("ReLU")
@operator_register(ExportLibCpp, "ReLU")
class ReLUCPP(ExportNodeCpp):
def __init__(self, node):
super().__init__(node)
self.attributes["activation"] = "Rectifier"
self.attributes["rescaling"] = "NoScaling"
self.config_template = str(ROOT / "templates" / "configuration" / "activation_config.jinja")
self.forward_template = str(ROOT / "templates" / "kernel_forward" / "activation_forward.jinja")
self.config_template = str(
ROOT / "templates" / "configuration" / "activation_config.jinja")
self.forward_template = str(
ROOT / "templates" / "kernel_forward" / "activation_forward.jinja")
self.include_list = []
self.kernels_to_copy = [
str(ROOT / "kernels" / "activation.hpp"),
]
@operator_register("Conv")
@staticmethod
def compatible(cls, node):
for idx, parent_node_in_id in node.inputs():
parent_node, _ = parent_node_in_id
@classmethod
def exportable(cls, node):
return True # TODO add check i/o NCHW
@operator_register(ExportLibCpp, "Conv")
class ConvCPP(ExportNodeCpp):
def __init__(self, node):
super().__init__(node)
......@@ -106,84 +116,116 @@ class ConvCPP(ExportNodeCpp):
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.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"),
]
@classmethod
def exportable(cls, node):
return True # TODO add check i/o NCHW
@operator_register("PaddedConv")
@operator_register(ExportLibCpp, "PaddedConv")
class PaddedConvCPP(ExportNodeCpp):
def __init__(self, node):
super().__init__(node)
# TODO find a way to retrive attr for meta op
for n in self.operator.get_micro_graph().get_nodes():
if n.type() == "Pad":
self.attributes["padding"] = n.get_operator().attr.begin_end_borders
self.attributes["padding"] = n.get_operator(
).attr.begin_end_borders
if n.type() == "Conv":
self.attributes["kernel_dims"] = n.get_operator().attr.kernel_dims
self.attributes["stride_dims"] = n.get_operator().attr.stride_dims
self.attributes["dilation_dims"] = n.get_operator().attr.dilation_dims
self.attributes["kernel_dims"] = n.get_operator(
).attr.kernel_dims
self.attributes["stride_dims"] = n.get_operator(
).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.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"),
]
@operator_register("Add")
@classmethod
def exportable(cls, node):
return True # TODO add check i/o NCHW
@operator_register(ExportLibCpp, "Add")
class AddCPP(ExportNodeCpp):
def __init__(self, node):
super().__init__(node)
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.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"),
]
@classmethod
def exportable(cls, node):
return True # TODO add check i/o NCHW
@operator_register("Sub")
@operator_register(ExportLibCpp, "Sub")
class SubCPP(ExportNodeCpp):
def __init__(self, node):
super().__init__(node)
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.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"),
]
@classmethod
def exportable(cls, node):
return True # TODO add check i/o NCHW
@operator_register("Mul")
@operator_register(ExportLibCpp, "Mul")
class MulCPP(ExportNodeCpp):
def __init__(self, node):
super().__init__(node)
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.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"),
]
@classmethod
def exportable(cls, node):
return True # TODO add check i/o NCHW
@operator_register("MaxPooling")
@operator_register(ExportLibCpp, "MaxPooling")
class MaxPoolCPP(ExportNodeCpp):
def __init__(self, node):
super().__init__(node)
......@@ -194,37 +236,50 @@ 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.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"),
]
@classmethod
def exportable(cls, node):
return True # TODO add check i/o NCHW
@operator_register("PaddedMaxPooling")
@operator_register(ExportLibCpp, "PaddedMaxPooling")
class PaddedMaxPoolCPP(ExportNodeCpp):
def __init__(self, node):
super().__init__(node)
for n in self.operator.get_micro_graph().get_nodes():
if n.type() == "Pad":
self.attributes["padding"] = n.get_operator().attr.begin_end_borders
self.attributes["padding"] = n.get_operator(
).attr.begin_end_borders
if n.type() == "MaxPooling":
self.attributes["kernel_dims"] = n.get_operator().attr.kernel_dims
self.attributes["stride_dims"] = n.get_operator().attr.stride_dims
self.attributes["kernel_dims"] = n.get_operator(
).attr.kernel_dims
self.attributes["stride_dims"] = n.get_operator(
).attr.stride_dims
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.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"),
]
@classmethod
def exportable(cls, node):
return True # TODO add check i/o NCHW
@operator_register("GlobalAveragePooling")
@operator_register(ExportLibCpp, "GlobalAveragePooling")
class GlobalAveragePoolCPP(ExportNodeCpp):
def __init__(self, node):
super().__init__(node)
......@@ -240,26 +295,35 @@ 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.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"),
]
@classmethod
def exportable(cls, node):
return True # TODO add check i/o NCHW
@operator_register("FC")
@operator_register(ExportLibCpp, "FC")
class FcCPP(ExportNodeCpp):
def __init__(self, node):
super().__init__(node)
self.attributes["activation"] = "Linear"
self.attributes["rescaling"] = "NoScaling"
self.config_template = str(ROOT / "templates" / "configuration" / "fullyconnected_config.jinja")
self.forward_template = str(ROOT / "templates" / "kernel_forward" / "fullyconnected_forward.jinja")
self.config_template = str(
ROOT / "templates" / "configuration" / "fullyconnected_config.jinja")
self.forward_template = str(
ROOT / "templates" / "kernel_forward" / "fullyconnected_forward.jinja")
self.include_list = []
self.kernels_to_copy = [
str(ROOT / "kernels" / "fullyconnected.hpp"),
str(ROOT / "kernels" / "macs.hpp"),
str(ROOT / "kernels" / "activation.hpp"),
]
@classmethod
def exportable(cls, node):
return True # TODO add check i/o NCHW
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