Create Tune API in the Katib SDK

README.md

@@ -189,10 +189,51 @@ katib-ui-5767cfccdc-pwg2x 1/1 Running 0 36s
 
 For the Katib Experiments check the [complete examples list](./examples/v1beta1).
 
+# Quickstart
+
+You can run your first HyperParameter Tuning Experiment using [Katib Python SDK](./sdk/python/v1beta1).
+
+In the following example we are going to maximize a simple objective function:
+$F(a,b) = 4a - b^2$. The bigger $a$ and the lesser $b$ value, the bigger the function value $F$.
+
+```python
+import kubeflow.katib as katib
+
+# Step 1. Create an objective function.
+def objective(parameters):
+ # Import required packages.
+ import time
+ time.sleep(5)
+ # Calculate objective function.
+ result = 4 * int(parameters["a"]) - float(parameters["b"]) ** 2
+ # Katib parses metrics in this format: <metric-name>=<metric-value>.
+ print(f"result={result}")
+
+# Step 2. Create HyperParameter search space.
+parameters = {
+ "a": katib.search.int(min=10, max=20),
+ "b": katib.search.double(min=0.1, max=0.2)
+}
+
+# Step 3. Create Katib Experiment.
+katib_client = katib.KatibClient()
+name = "tune-experiment"
+katib_client.tune(
+ name=name,
+ objective=objective,
+ parameters=parameters,
+ objective_metric_name="result",
+ max_trial_count=12
+)
+
+# Step 4. Get the best HyperParameters.
+print(katib_client.get_optimal_hyperparameters(name))
+```
+
 # Documentation
 
-- Run your first Katib Experiment in the
- [getting started guide](https://www.kubeflow.org/docs/components/katib/hyperparameter/#example-using-random-algorithm).
+- Check
+ [the Katib getting started guide](https://www.kubeflow.org/docs/components/katib/hyperparameter/#example-using-random-search-algorithm).
 
 - Learn about Katib **Concepts** in this
  [guide](https://www.kubeflow.org/docs/components/katib/overview/#katib-concepts).

hack/gen-python-sdk/post_gen.py

@@ -37,10 +37,17 @@ def _rewrite_helper(input_file, output_file, rewrite_rules):
  if not any(l in line for l in IGNORE_LINES):
  lines.append(line)
 
- # Add Katib client to init file.
+ # Add Katib APIs to the init file.
  if (output_file == "sdk/python/v1beta1/kubeflow/katib/__init__.py"):
  lines.append("# Import Katib API client.\n")
  lines.append("from kubeflow.katib.api.katib_client import KatibClient\n")
+ lines.append("# Import Katib helper functions.\n")
+ lines.append("import kubeflow.katib.api.search as search\n")
+ lines.append("# Import Katib helper constants.\n")
+ lines.append("from kubeflow.katib.constants.constants import BASE_IMAGE_TENSORFLOW\n")
+ lines.append("from kubeflow.katib.constants.constants import BASE_IMAGE_TENSORFLOW_GPU\n")
+ lines.append("from kubeflow.katib.constants.constants import BASE_IMAGE_PYTORCH\n")
+ lines.append("from kubeflow.katib.constants.constants import BASE_IMAGE_MXNET\n")
 
  # Add Kubernetes models to proper deserialization of Katib models.
  if (output_file == "sdk/python/v1beta1/kubeflow/katib/models/__init__.py"):

sdk/python/v1beta1/.gitignore

@@ -0,0 +1,2 @@
+# Distribution / packaging
+dist/

sdk/python/v1beta1/kubeflow/katib/__init__.py

@@ -71,3 +71,10 @@
 
 # Import Katib API client.
 from kubeflow.katib.api.katib_client import KatibClient
+# Import Katib helper functions.
+import kubeflow.katib.api.search as search
+# Import Katib helper constants.
+from kubeflow.katib.constants.constants import BASE_IMAGE_TENSORFLOW
+from kubeflow.katib.constants.constants import BASE_IMAGE_TENSORFLOW_GPU
+from kubeflow.katib.constants.constants import BASE_IMAGE_PYTORCH
+from kubeflow.katib.constants.constants import BASE_IMAGE_MXNET