Fix Katib documentation links (#1690)

* Fix Katib nas example link

* Fix other Katib links

content/docs/components/hyperparameter-tuning/experiment.md

@@ -49,7 +49,7 @@ These are the fields in the experiment configuration spec:
   of allowed values for each hyperparameter.
   Katib generates hyperparameter combinations in the range based on the
   hyperparameter tuning algorithm that you specify. See the [`ParameterSpec` 
-  type](https://github.com/kubeflow/katib/blob/master/pkg/apis/controller/experiments/v1alpha3/experiment_types.go#L142-L163).
+  type](https://github.com/kubeflow/katib/blob/master/pkg/apis/controller/experiments/v1alpha3/experiment_types.go#L157-L178).
 
 
 * **objective**: The metric that you want to optimize. 
@@ -87,7 +87,7 @@ These are the fields in the experiment configuration spec:
       distributed execution).
 
     See the [TrialTemplate 
-    type](https://github.com/kubeflow/katib/blob/master/pkg/apis/controller/experiments/v1alpha3/experiment_types.go#L165-L179).
+    type](https://github.com/kubeflow/katib/blob/master/pkg/apis/controller/experiments/v1alpha3/experiment_types.go#L180-L194).
     The template 
     uses the [Go template format](https://golang.org/pkg/text/template/).
 
@@ -117,15 +117,15 @@ These are the fields in the experiment configuration spec:
   You can specify the configurations of the neural network design that you want
   to optimize, including the number of layers in the network, the types of
   operations, and more.
-  See the [NasConfig type](https://github.com/kubeflow/katib/blob/master/pkg/apis/controller/experiments/v1alpha3/experiment_types.go#L205).
+  See the [NasConfig type](https://github.com/kubeflow/katib/blob/master/pkg/apis/controller/experiments/v1alpha3/experiment_types.go#L220).
   As an example, see the YAML file for the
-  [nasjob-example-RL](https://github.com/kubeflow/katib/blob/master/examples/v1alpha3/nasjob-example-RL.yaml).
+  [nasjob-example-RL-gpu](https://github.com/kubeflow/katib/blob/master/examples/v1alpha3/nasjob-example-RL-gpu.yaml).
   The example aims to show all the possible operations. Due to the large search 
   space, the example is not likely to generate a good result.
 
 *Background information about Katib's `Experiment` type:* In Kubernetes 
 terminology, Katib's
-[`Experiment`](https://github.com/kubeflow/katib/blob/master/pkg/apis/controller/experiments/v1alpha3/experiment_types.go#L187)
+[`Experiment`](https://github.com/kubeflow/katib/blob/master/pkg/apis/controller/experiments/v1alpha3/experiment_types.go#L202)
 type is a [custom resource 
 (CR)](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/).
 The YAML file that you create for your experiment is the CR specification.
@@ -358,7 +358,7 @@ To define the metrics collector for your experiment:
       storage of its own metrics.
 
 1. Specify the metrics output location in the `source` field. See the 
-  [MetricsCollectorSpec type](https://github.com/kubeflow/katib/blob/master/pkg/apis/controller/common/v1alpha3/common_types.go#L74-L143) for default values.
+  [MetricsCollectorSpec type](https://github.com/kubeflow/katib/blob/master/pkg/apis/controller/common/v1alpha3/common_types.go#L81-L150) for default values.
 1. Write code in your training container to print metrics in the format
    specified in the `metricsCollectorSpec.source.filter.metricsFormat`
    field. The default format is `([\w|-]+)\s*=\s*((-?\d+)(\.\d+)?)`.