Rewrite memory manager log_info in Python.

Context

This MR fix !276 (merged)

It began by looking at the memory management of the dinov2 model

Realizing that it is not readable, I rewrited it in python in order to easily tweak it.

Here is the new memory info after rewritting it:

Add display_names parameter to aidge_core.generate_optimized_memory_info which allows to diplay the names or not:

Benefice

This MR remove a dependencie to gnuplot

Log function is easy to use now!

Miscellaneous

After using MetaOperators to simplify the graph we get the follwing memory placement strategy which surprised me as it produces a lower memory peak!

This make sens since by fusing operation we load in RAM data and do not need to save intermediate output.

A little sad to not have found this out before webinar

For reproductibility the code used:

import aidge_core
import aidge_backend_cpu
import aidge_onnx

dinov2_model = aidge_onnx.load_onnx("hf_dinov2_sim.onnx")

aidge_core.fuse_to_metaops(dinov2_model, "MatMul-*>Add", "Linear")

aidge_core.fuse_to_metaops(dinov2_model, "ReduceMean-*>Sub#1~>(Pow#1->ReduceMean-*>Add#1->Sqrt)-*>Div#1-*>Mul#1-*>Add#2;"
                                        "Sub#1~*>Div#1;"
                                        "Pow#1<1~Producer;"
                                        "Add#1<*~Producer;"
                                        "Mul#1<*~Producer;"
                                        "Add#2<*~Producer;"
                                        "Sub#1~>$", "LayerNorm")

aidge_core.fuse_to_metaops(dinov2_model, "MatMul->Div#1->Softmax-*>MatMul;"
                                        "Div#1<1~Producer", "ScaledDotProductAttention")

aidge_core.fuse_to_metaops(dinov2_model, "ScaledDotProductAttention#1->Transpose->Reshape#1->Linear;"
                                        "Reshape#1<1~Producer;"
                                        "ScaledDotProductAttention#1<0-(Transpose<-Reshape#2<-Add#1);"
                                        "ScaledDotProductAttention#1<1-(Transpose<-Reshape#3<-Add#2);"
                                        "ScaledDotProductAttention#1<2-(Transpose<-Reshape#4<-Add#3);"
                                        "Reshape#2<1~Producer;"
                                        "Add#1<*-0-Split#1;"
                                        "Add#2<*-1-Split#1;"
                                        "Add#3<*-2-Split#1;"
                                        "Split#1<-MatMul;"
                                        "Split#1<1~Producer", "MultiHeadAttention")

aidge_core.fuse_to_metaops(dinov2_model, "Div#1->Erf->Add#1-*>Mul->Mul#2;"
                                        "Div#1<1~Producer;"
                                        "Add#1<*~Producer;"
                                        "Mul#2<*~Producer", "GeLU")
dinov2_model.set_ordered_outputs([dinov2_model.get_ordered_outputs()[0][0].inputs()[0], dinov2_model.get_ordered_outputs()[0]])
dinov2_model.set_backend("cpu")
dinov2_model.set_datatype(aidge_core.dtype.float32)
dinov2_model.forward_dims([[1,3,224,224]], True)

s = aidge_core.SequentialScheduler(dinov2_model)
s.generate_scheduling()
aidge_core.generate_optimized_memory_info(s, "stats_dyno", wrapping=False, display_names=False)

## Major modifications

- enhance structure: rewrite `generate_optimized_memory_info`
- add `display_names` parameter to `generate_optimized_memory_info` which allows to diplay the names or not
- add matplotlib dependence for Python package i `pyproject.toml`
- remove a dependency to gnuplot