Merge branch 'main' into bump_torch_python

.gitignore

@@ -23,6 +23,7 @@ examples/notebooks/models_training/my_model/
 examples/showcases copy/*
 examples/notebooks/models_training/generate.py
 dummy_output_dir/*
+tests/dummy_output_dir/
 examples/notebooks/models_training/my_model/*
 examples/notebooks/test.ipynb
 examples/notebooks/dummy_output_dir/*

.readthedocs.yml

@@ -5,7 +5,7 @@ version: 2
 build:
   os: ubuntu-22.04
   tools:
-    python: "3.11"
+    python: "3.10"
 
 # Build from the docs/ directory with Sphinx
 sphinx:

README.md

@@ -107,6 +107,7 @@ VAE with Inverse Autoregressive Flows (VAE_IAF) |  [![Open In Colab](https://col
 | Regularized AE with L2 decoder param (RAE_L2) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/clementchadebec/benchmark_VAE/blob/main/examples/notebooks/models_training/rae_l2_training.ipynb) | [link](https://arxiv.org/abs/1903.12436) | [link](https://github.com/ParthaEth/Regularized_autoencoders-RAE-/tree/master/) |
 | Regularized AE with gradient penalty (RAE_GP) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/clementchadebec/benchmark_VAE/blob/main/examples/notebooks/models_training/rae_gp_training.ipynb) | [link](https://arxiv.org/abs/1903.12436) | [link](https://github.com/ParthaEth/Regularized_autoencoders-RAE-/tree/master/) |
 | Riemannian Hamiltonian VAE (RHVAE) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/clementchadebec/benchmark_VAE/blob/main/examples/notebooks/models_training/rhvae_training.ipynb) | [link](https://arxiv.org/abs/2105.00026) | [link](https://github.com/clementchadebec/pyraug)|
+| Hierarchical Residual Quantization (HRQVAE) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/clementchadebec/benchmark_VAE/blob/main/examples/notebooks/models_training/hrqvae_training.ipynb) | [link](https://aclanthology.org/2022.acl-long.178/) | [link](https://github.com/tomhosking/hrq-vae)|
 
 **See [reconstruction](#Reconstruction) and [generation](#Generation) results for all aforementionned models**