CAMP-TUM network contributions: Quicknat and Daf3D (Project-MONAI#6306)

Fixes Project-MONAI#5921 

### Description

@Al3xand1a and @ge96lip implement DAF3D[1] and Quicknat[2] networks and
test them in open-source and local datasets. We use as a baseline the
pytorch codes available in [3] and [4]
We are quite confident about the implementation, but feel free to
contact us if you find errors. For any questions send us an email to
ge45qix@mytum.de

We have some questions for the contribution:
For Quicknat:
1) we add the sequential class file in the networks folder because we do
not know where to add it.
2) How do we include the squeeze and excitation requirement (sse and
Csse) if it comes from a GitHub repository?

https://github.com/ai-med/nn-common-modules/releases/download/v1.1/nn_common_modules-1.3-py3-none-any.whl
For Daf3D
3) Are the overwritten blocks fine as they are? or do they have to be
more flexible?
For both:
We run this command line (`./runtests.sh --quick --unittests
--disttests`) but the error we are getting is not related to our
changes, so we run our unit_test independently and they work. Same with
documentation.
 
[1] Deep Attentive Features for Prostate Segmentation in 3D Transrectal
Ultrasound.
Yi Wang, Haoran Dou, Xiaowei Hu, Lei Zhu, Xin Yang, Ming Xu, Jing Qin,
Pheng-Ann Heng, Tianfu Wang, and Dong Ni.
IEEE Transactions on Medical Imaging, 2019.
[2] Roy, A. G., Conjeti, S., Navab, N., Wachinger, C., & Alzheimer's
Disease Neuroimaging Initiative. (2019). QuickNAT: A fully convolutional
network for quick and accurate segmentation of neuroanatomy. NeuroImage,
186, 713-727.
[3] https://github.com/ai-med/quickNAT_pytorch
[4] https://github.com/wulalago/DAF3D

### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [x] New tests added to cover the changes.
- [x] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [] Quick tests passed locally by running `./runtests.sh --quick
--unittests --disttests`.
- [x] In-line docstrings updated.
- [x] Documentation updated, tested `make html` command in the `docs/`
folder.

---------

Signed-off-by: ge96lip <73938628+ge96lip@users.noreply.github.com>
Signed-off-by: vanessagd.2395 <vanessa.gonzalez-duque@eleves.ec-nantes.fr>
Signed-off-by: Al3xand1a <98582325+Al3xand1a@users.noreply.github.com>
Co-authored-by: Alexandra Marquardt <alexandra@MBPvonAlexandra.fritz.box>
Co-authored-by: Carlotta <carlotta.hoelzle@icloud.com>
Co-authored-by: Alexandra Marquardt <alexandra@w223-2e-v4.eduroam.dynamic.rbg.tum.de>
Co-authored-by: Vanessa <vanessa.gonzalezduque@ls2n.fr>
Co-authored-by: ge96lip <73938628+ge96lip@users.noreply.github.com>
Co-authored-by: “Vanessa <“vanessa.gonzalezduque@ls2n.fr”>
Co-authored-by: Eric Kerfoot <17726042+ericspod@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Alexandra Marquardt <alexandra@w192-1i-v4.eduroam.dynamic.rbg.tum.de>
Co-authored-by: Al3xand1a <98582325+Al3xand1a@users.noreply.github.com>
Co-authored-by: Alexandra Marquardt <alexandra@w217-4n-v4.eduroam.dynamic.rbg.tum.de>

.gitignore

@@ -151,3 +151,7 @@ tests/testing_data/CT_2D_head_moving.mha
 # profiling results
 *.prof
 runs
+
+*.gz
+
+*.pth

monai/networks/blocks/denseblock.py

@@ -11,7 +11,7 @@
 
 from __future__ import annotations
 
-from collections.abc import Sequence
+from typing import Sequence
 
 import torch
 import torch.nn as nn

monai/networks/nets/__init__.py

@@ -17,6 +17,7 @@
 from .basic_unet import BasicUNet, BasicUnet, Basicunet, basicunet
 from .basic_unetplusplus import BasicUNetPlusPlus, BasicUnetPlusPlus, BasicunetPlusPlus, basicunetplusplus
 from .classifier import Classifier, Critic, Discriminator
+from .daf3d import DAF3D
 from .densenet import (
     DenseNet,
     Densenet,
@@ -51,6 +52,7 @@
 from .hovernet import Hovernet, HoVernet, HoVerNet, HoverNet
 from .milmodel import MILModel
 from .netadapter import NetAdapter
+from .quicknat import Quicknat
 from .regressor import Regressor
 from .regunet import GlobalNet, LocalNet, RegUNet
 from .resnet import (