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+# Proposal for Supporting various parameter distributions in Katib
+
+## Summary
+The goal of this project is to enhance the existing Katib Experiment APIs to support various parameter distributions such as uniform, log-uniform, and qlog-uniform. Then extend the suggestion services to be able to configure distributions for search space using libraries provided in each framework.
+
+## Motivation
+Currently, Katib is limited to supporting only uniform distribution for integer, float, and categorical hyperparameters. By introducing additional distributions, Katib will become more flexible and powerful in conducting hyperparameter optimization tasks.
+
+## Proposal
+
+### Maintaining two versions of CRD APIs
+- Introduce `v1beta2` API version
+- The (conversion webhook)[https://book.kubebuilder.io/multiversion-tutorial/conversion.html] will serve as a critical component in managing transitions between different API versions (`v1beta1` to `v1beta2`).
+- TODO 
+> I will create a correspondence table between v1beta1 and v1beta2. Maybe, we only need to create a table for the `ParameterType` and the `FeasibleSpace`.
+Look into this.
+- A specific field will be added to the katib-config `katib/pkg/util/v1beta1/katibconfig/config.go` to handle different gRPC client versions required by the suggestion controller. (One approach could be this for maintaining two versions of gRPC APIs).
+- TODO Based on this comment here:
+https://github.com/kubeflow/katib/pull/2059#discussion_r1049329229
+Look how to maintain two versions of gRPC APIs
+
+### Experiment API changes
+Scope: `pkg/apis/controller/experiments/v1beta1/experiment_types.go`
+- Modifying the `ParameterSpec` struct to include a new field called Distribution.
+
+```go
+type ParameterSpec struct {
+    Name          string       `json:"name,omitempty"`
+    Distribution  Distribution `json:"distribution,omitempty"`
+    FeasibleSpace FeasibleSpace `json:"feasibleSpace,omitempty"`
+}
+```
+
+- Renaming Parameters
+
+```go
+type Distribution string
+
+const (
+ 	CategoricalDistribution     Distribution = "categorical"
+ 	IntUniformDistribution      Distribution = "intUniform"
+ 	IntLogUniformDistribution   Distribution = "intLogUniform"
+ 	FloatUniformDistribution    Distribution = "floatUniform"
+)
+```
+
+### Suggestion Service Logic
+- For each suggestion service (e.g., Optuna, Hyperopt), the logic will be updated to handle the new parameter distributions.
+- This involves modifying the conversion functions to map Katib distributions to the corresponding framework-specific distributions.
+
+#### Optuna
+ref: https://optuna.readthedocs.io/en/stable/reference/distributions.html
+
+For example:
+- Update the `_get_optuna_search_space` for new parameters.
+scope: `pkg/suggestion/v1beta1/optuna/base_service.py`
+```python
+    def _get_optuna_search_space(self):
+        search_space = {}
+        for param in self.search_space.params:
+            if param.type == INTEGER:
+                search_space[param.name] = optuna.distributions.IntDistribution(int(param.min), int(param.max))
+            elif param.type == DOUBLE:
+                search_space[param.name] = optuna.distributions.FloatDistribution(float(param.min), float(param.max))
+            elif param.type == CATEGORICAL or param.type == DISCRETE:
+                search_space[param.name] = optuna.distributions.CategoricalDistribution(param.list)
+        return search_space
+```
+
+#### Chocolate
+ref: https://chocolate.readthedocs.io/en/latest/api/space.html
+
+#### Goptuna
+ref: https://github.com/c-bata/goptuna/blob/2245ddd9e8d1edba750839893c8a618f852bc1cf/distribution.go
+
+#### Hyperopt
+ref: http://hyperopt.github.io/hyperopt/getting-started/search_spaces/#parameter-expressions
+
+#### Scikit Optimize
+ref: https://scikit-optimize.github.io/stable/modules/classes.html#module-skopt.space.space
+
+### Testing
+- Write unit tests for the conversion webhook to ensure all fields are correctly converted.
+- Write unit tests for the new parameter distributions to ensure they are processed correctly by the controller.
+