Apply mdformat to optunahub-registry packages.

package/pruners/median/README.md

@@ -1,16 +1,18 @@
 ---
-author: 'Optuna team'
-title: 'Median Pruner'
-description: 'Pruner using the median stopping rule.'
-tags: ['pruner', 'built-in']
-optuna_versions: ['3.6.1']
-license: 'MIT License'
+author: Optuna team
+title: Median Pruner
+description: Pruner using the median stopping rule.
+tags: [pruner, built-in]
+optuna_versions: [3.6.1]
+license: MIT License
 ---
 
 ## Class or Function Names
+
 - MedianPruner
 
 ## Example
+
 ```python
 import optuna
 from optuna.pruners import MedianPruner
@@ -33,5 +35,5 @@ study.optimize(objective, n_trials=20)
 ```
 
 ## Others
-See the [documentation](https://optuna.readthedocs.io/en/stable/reference/generated/optuna.pruners.MedianPruner.html) for more details.
 
+See the [documentation](https://optuna.readthedocs.io/en/stable/reference/generated/optuna.pruners.MedianPruner.html) for more details.

package/pruners/percentile/README.md

@@ -1,16 +1,18 @@
 ---
-author: 'Optuna team'
-title: 'Percentile Pruner'
-description: 'Pruner to keep the specified percentile of the trials.'
-tags: ['pruner', 'built-in']
-optuna_versions: ['3.6.1']
-license: 'MIT License'
+author: Optuna team
+title: Percentile Pruner
+description: Pruner to keep the specified percentile of the trials.
+tags: [pruner, built-in]
+optuna_versions: [3.6.1]
+license: MIT License
 ---
 
 ## Class or Function Names
+
 - PercentilePruner
 
 ## Example
+
 ```python
 import optuna
 from optuna.pruners import PercentilePruner
@@ -33,5 +35,5 @@ study.optimize(objective, n_trials=20)
 ```
 
 ## Others
-See the [documentation](https://optuna.readthedocs.io/en/stable/reference/generated/optuna.pruners.PercentilePruner.html) for more details.
 
+See the [documentation](https://optuna.readthedocs.io/en/stable/reference/generated/optuna.pruners.PercentilePruner.html) for more details.

package/samplers/botorch_sampler/README.md

@@ -1,26 +1,29 @@
 ---
-author: 'Optuna team'
-title: 'BoTorch Sampler'
-description: 'A Sampler using botorch library as the backend.'
-tags: ['sampler', 'built-in']
-optuna_versions: ['3.6.1']
-license: 'MIT License'
+author: Optuna team
+title: BoTorch Sampler
+description: A Sampler using botorch library as the backend.
+tags: [sampler, built-in]
+optuna_versions: [3.6.1]
+license: MIT License
 ---
 
 ## Class or Function Names
+
 - BoTorchSampler
 
 ## Installation
+
 ```bash
 pip install optuna-integration botorch
 ```
 
 ## Example
+
 ```python
 from optuna_integration import BoTorchSampler
 sampler = BoTorchSampler()
 ```
 
 ## Others
-See the [documentation](https://optuna-integration.readthedocs.io/en/latest/reference/generated/optuna_integration.BoTorchSampler.html) for more details.
 
+See the [documentation](https://optuna-integration.readthedocs.io/en/latest/reference/generated/optuna_integration.BoTorchSampler.html) for more details.

package/samplers/brute_force/README.md

@@ -1,16 +1,18 @@
 ---
-author: 'Optuna team'
-title: 'Brute Force Search'
-description: 'Sampler using brute force.'
-tags: ['sampler', 'built-in']
-optuna_versions: ['3.6.1']
-license: 'MIT License'
+author: Optuna team
+title: Brute Force Search
+description: Sampler using brute force.
+tags: [sampler, built-in]
+optuna_versions: [3.6.1]
+license: MIT License
 ---
 
 ## Class or Function Names
+
 - BruteForceSampler
 
 ## Example
+
 ```python
 import optuna
 from optuna.samplers import BruteForceSampler
@@ -27,5 +29,5 @@ study.optimize(objective, n_trials=10)
 ```
 
 ## Others
-See the [documentation](https://optuna.readthedocs.io/en/stable/reference/samplers/generated/optuna.samplers.BruteForceSampler.html) for more details.
 
+See the [documentation](https://optuna.readthedocs.io/en/stable/reference/samplers/generated/optuna.samplers.BruteForceSampler.html) for more details.

package/samplers/cmaes/README.md

@@ -1,21 +1,24 @@
 ---
-author: 'Optuna team'
-title: 'CMA-ES Sampler'
-description: 'A sampler using cmaes as the backend.'
-tags: ['sampler', 'built-in']
-optuna_versions: ['3.6.1']
-license: 'MIT License'
+author: Optuna team
+title: CMA-ES Sampler
+description: A sampler using cmaes as the backend.
+tags: [sampler, built-in]
+optuna_versions: [3.6.1]
+license: MIT License
 ---
 
 ## Class or Function Names
+
 - CmaEsSampler
 
 ## Installation
+
 ```bash
 pip install cmaes
 ```
 
 ## Example
+
 ```python
 import optuna
 from optuna.samplers import CmaEsSampler
@@ -33,4 +36,5 @@ study.optimize(objective, n_trials=20)
 ```
 
 ## Others
+
 See the [documentation](https://optuna.readthedocs.io/en/stable/reference/samplers/generated/optuna.samplers.CmaEsSampler.html) for more details.

package/samplers/demo/README.md

@@ -1,18 +1,21 @@
 ---
-author: 'Optuna team'
-title: 'Demo Sampler'
-description: 'Demo Sampler of OptunaHub'
-tags: ['sampler']
-optuna_versions: ['3.6.1']
-license: 'MIT License'
+author: Optuna team
+title: Demo Sampler
+description: Demo Sampler of OptunaHub
+tags: [sampler]
+optuna_versions: [3.6.1]
+license: MIT License
 ---
 
 ## Class or Function Names
+
 - DemoSampler
 
 ## Example
+
 ```python
 module = optunahub.load_module("samplers/demo")
 sampler = module.DemoSampler(seed=42)
 ```
+
 See [`example.py`](https://github.com/optuna/optunahub-registry/blob/main/package/samplers/demo/example.py) for more details.

package/samplers/evo_merge/README.md

@@ -1,17 +1,19 @@
 ---
-author: 'Optuna team'
-title: 'Evolutionary LLM Merge Sampler'
-description: 'A sampler for evolutionary LLM merge.'
-tags: ['sampler', 'LLM']
+author: Optuna team
+title: Evolutionary LLM Merge Sampler
+description: A sampler for evolutionary LLM merge.
+tags: [sampler, LLM]
 optuna_versions: [3.6.1]
-license: 'MIT License'
+license: MIT License
 ---
 
 ## Class or Function Names
+
 - EvoMergeSampler
 - EvoMergeTrial
 
 ## Installation
+
 ```bash
 pip install git+https://github.com/arcee-ai/mergekit.git
 pip install sentencepiece accelerate protobuf bitsandbytes langchain langchain-community datasets
@@ -20,6 +22,7 @@ export HF_TOKEN=xxx
 ```
 
 ## Example
+
 ```python
 sampler = EvoMergeSampler(base_config="path/to/config/yml/file")
 study = optuna.create_study(sampler=sampler)
@@ -35,6 +38,7 @@ for _ in range(100):
 
 print(study.trials_dataframe(attrs=("number", "value")))
 ```
+
 See [`example.py`](https://github.com/optuna/optunahub-registry/blob/main/package/samplers/evo_merge/example.py) for a full example. You need GPU with 16G VLAM to run this example.
 The following figures are obtained from the analysis of the optimization.
 ![History Plot](images/history.png "History Plot")
@@ -43,4 +47,5 @@ The following figures are obtained from the analysis of the optimization.
 ## Others
 
 ### Reference
+
 Akiba, T., Shing, M., Tang, Y., Sun, Q., & Ha, D. (2024). Evolutionary Optimization of Model Merging Recipes. arXiv preprint arXiv:2403.13187.

package/samplers/gp/README.md

@@ -1,21 +1,24 @@
 ---
-author: 'Optuna team'
-title: 'Gaussian Process-Based Sampler'
-description: 'Sampler using Gaussian process-based Bayesian optimization.'
-tags: ['sampler', 'built-in']
-optuna_versions: ['3.6.1']
-license: 'MIT License'
+author: Optuna team
+title: Gaussian Process-Based Sampler
+description: Sampler using Gaussian process-based Bayesian optimization.
+tags: [sampler, built-in]
+optuna_versions: [3.6.1]
+license: MIT License
 ---
 
 ## Class or Function Names
+
 - GPSampler
 
 ## Installation
+
 ```bash
 pip install scipy pytorch
 ```
 
 ## Example
+
 ```python
 import optuna
 from optuna.samplers import GPSampler
@@ -32,4 +35,5 @@ study.optimize(objective, n_trials=100)
 ```
 
 ## Others
+
 See the [documentation](https://optuna.readthedocs.io/en/stable/reference/samplers/generated/optuna.samplers.GPSampler.html) for more details.

package/samplers/grid_search/README.md

@@ -1,16 +1,18 @@
 ---
-author: 'Optuna team'
-title: 'Grid Search'
-description: 'Sampler using grid search.'
-tags: ['sampler', 'built-in']
-optuna_versions: ['3.6.1']
-license: 'MIT License'
+author: Optuna team
+title: Grid Search
+description: Sampler using grid search.
+tags: [sampler, built-in]
+optuna_versions: [3.6.1]
+license: MIT License
 ---
 
 ## Class or Function Names
+
 - GridSampler
 
 ## Example
+
 ```python
 import optuna
 from optuna.samplers import GridSampler
@@ -29,4 +31,5 @@ study.optimize(objective)
 ```
 
 ## Others
+
 See the [documentation](https://optuna.readthedocs.io/en/stable/reference/samplers/generated/optuna.samplers.GridSampler.html) for more details.

package/samplers/hebo/README.md

@@ -2,15 +2,17 @@
 author: HideakiImamura
 title: HEBO (Heteroscedastic and Evolutionary Bayesian Optimisation)
 description: HEBO addresses the problem of noisy and heterogeneous objective functions by using a heteroscedastic Gaussian process and an evolutionary algorithm.
-tags: ["sampler", "Bayesian optimization", "Heteroscedastic Gaussian process", "Evolutionary algorithm"]
-optuna_versions: ["3.6.1"]
-license: "MIT License" 
+tags: [sampler, Bayesian optimization, Heteroscedastic Gaussian process, Evolutionary algorithm]
+optuna_versions: [3.6.1]
+license: MIT License
 ---
 
 ## Class or Function Names
+
 - HEBOSampler
 
 ## Installation
+
 ```bash
 pip install -r requirements.txt
 git clone [email protected]:huawei-noah/HEBO.git
@@ -19,6 +21,7 @@ pip install -e .
 ```
 
 ## Example
+
 ```python
 search_space = {
     "x": FloatDistribution(-10, 10),
@@ -28,13 +31,13 @@ search_space = {
 sampler = HEBOSampler(search_space)
 study = optuna.create_study(sampler=sampler)
 ```
+
 See [`example.py`](https://github.com/optuna/optunahub-registry/blob/main/package/samplers/hebo/example.py) for a full example.
 ![History Plot](images/hebo_optimization_history.png "History Plot")
 
-
 ## Others
 
-HEBO is the winning submission to the [NeurIPS 2020 Black-Box Optimisation Challenge](https://bbochallenge.com/leaderboard). 
+HEBO is the winning submission to the [NeurIPS 2020 Black-Box Optimisation Challenge](https://bbochallenge.com/leaderboard).
 Please refer to [the official repository of HEBO](https://github.com/huawei-noah/HEBO/tree/master/HEBO) for more details.
 
 ### Reference

package/samplers/implicit_natural_gradient/README.md

@@ -1,23 +1,27 @@
 ---
-author: 'Yuhei Otomo and Masashi Shibata'
-title: 'Implicit Natural Gradient Sampler'
-description: 'A sampler based on Implicit Natural Gradient.'
-tags: ['sampler']
-optuna_versions: ['3.6.1']
-license: 'MIT License'
+author: Yuhei Otomo and Masashi Shibata
+title: Implicit Natural Gradient Sampler
+description: A sampler based on Implicit Natural Gradient.
+tags: [sampler]
+optuna_versions: [3.6.1]
+license: MIT License
 ---
 
 ## Class or Function Names
+
 - ImplicitNaturalGradientSampler
 
 ## Example
+
 ```python
 mod = optunahub.load_module("samplers/implicit_natural_gradient")
 sampler = mod.ImplicitNaturalGradientSampler()
 ```
+
 See [`example.py`](https://github.com/optuna/optunahub-registry/blob/main/package/samplers/implicit_natural_gradient/example.py) for more details.
 
 ## Others
 
 ### Reference
+
 Yueming Lyu, Ivor W. Tsang (2019). Black-box Optimizer with Implicit Natural Gradient. arXiv:1910.04301