Merge pull request #325 from sunya-ch/bump-kepler-0.7.11

Sunil Thaha · web-flow · commit 6690a4cf8ba7 · 2024-07-25T16:54:31.000+10:00
bump kepler version 0.7.11
diff --git a/.github/workflows/pr.yml b/.github/workflows/pr.yml
@@ -18,7 +18,7 @@ on:
       - '**/*.md'
 
 env:
-  TAG: "v0.7.7"
+  TAG: "v0.7.11"
 
 jobs:
   check-branch:
@@ -207,7 +207,7 @@ jobs:
       docker_secret: ${{ needs.check-secret.outputs.docker-secret }}
       image_repo: ${{ vars.IMAGE_REPO || 'docker.io/library' }}
       image_tag: ${{ needs.check-branch.outputs.tag }}
-      kepler_tag: release-0.7.7
+      kepler_tag: release-0.7.11
       additional_opts: " TEST"
 
   integration-test-with-exporter:
@@ -219,7 +219,7 @@ jobs:
       docker_secret: ${{ needs.check-secret.outputs.docker-secret }}
       image_repo: ${{ vars.IMAGE_REPO || 'docker.io/library' }}
       image_tag: ${{ needs.check-branch.outputs.tag }}
-      kepler_tag: release-0.7.7
+      kepler_tag: release-0.7.11
       additional_opts: ""
 
   integration-test-with-exporter-and-db:
@@ -231,7 +231,7 @@ jobs:
       docker_secret: ${{ needs.check-secret.outputs.docker-secret }}
       image_repo: ${{ vars.IMAGE_REPO || 'docker.io/library' }}
       image_tag: ${{ needs.check-branch.outputs.tag }}
-      kepler_tag: release-0.7.7
+      kepler_tag: release-0.7.11
       additional_opts: " DB"
 
   verify_model_training_script:
diff --git a/.github/workflows/tekton-test.yml b/.github/workflows/tekton-test.yml
@@ -154,7 +154,7 @@ jobs:
             - name: MACHINE_ID
               value: test
             - name: ENERGY_SOURCE
-              value: intel_rapl
+              value: trained_power_model
             - name: FEATURE_GROUP
               value: BPFOnly
             - name: TRAINERS
@@ -190,6 +190,8 @@ jobs:
               value: ${{ inputs.trainers }}
             - name: DYN_TRAINERS
               value: ${{ inputs.trainers }}
+            - name: ENERGY_SOURCE
+              value: trained_power_model
             pipelineRef:
               name: complete-retrain-pipeline
           EOF
diff --git a/.github/workflows/train-model.yml b/.github/workflows/train-model.yml
@@ -45,7 +45,7 @@ on:
         description: 'Target energy source'
         required: false
         type: string
-        default: intel_rapl
+        default: rapl-sysfs
       feature_group:
         description: 'Target feature group'
         required: false
diff --git a/cmd/README.md b/cmd/README.md
@@ -40,7 +40,7 @@ Use kepler model server function as a standalone docker container.
     ├── profile # if --profile is providied
     │   ├── acpi.json
     │   └── rapl.json
-    ├── <energy_source> # provided by --energy-source (default: intel_rapl)
+    ├── <energy_source> # provided by --energy-source (default: rapl-sysfs)
     │   ├── <model_type> # AbsPower or DynPower
     │   │   ├── <feature_group>  # e.g., BPFOnly
     │   │   │   ├── <model_name>
diff --git a/cmd/cmd_plot.py b/cmd/cmd_plot.py
@@ -206,7 +206,7 @@ def _plot_models(models, cpu_ms_max, energy_source, output_folder, name, max_plo
     main_feature_col = BPF_FEATURES[0]
     predicted_col = {
         "acpi": "default_platform_power",
-        "intel_rapl": "default_package_power"
+        "rapl-sysfs": "default_package_power"
     }
 
     num_bins = len(cpu_ms_max)//cpu_time_bin_num + 1
diff --git a/cmd/cmd_util.py b/cmd/cmd_util.py
@@ -61,7 +61,7 @@ def summary_validation(validate_df):
         "bpf": "kepler_container_bpf_cpu_time_ms_total",
     }
     metric_to_validate_power = {
-        "intel_rapl": "kepler_node_package_joules_total",
+        "rapl-sysfs": "kepler_node_package_joules_total",
         "acpi": "kepler_node_platform_joules_total"
     }
     for metric, query in metric_to_validate_pod.items():
@@ -101,6 +101,7 @@ def get_validate_df(data_path, benchmark_filename, query_response):
     items = []
     query_results = prom_responses_to_results(query_response)
     container_queries = [query for query in query_results.keys() if "container" in query]
+    print("Container Queries: ", container_queries)
     status_data = load_json(data_path, benchmark_filename)
     if status_data is None or status_data.get("status", None) == None:
         # select all with keyword
@@ -166,6 +167,7 @@ def get_validate_df(data_path, benchmark_filename, query_response):
                     item["total"] = filtered_df[query].max()
                     items += [item]
     energy_queries = [query for query in query_results.keys() if "_joules" in query]
+    print("Energy Queries: ", container_queries)
     for energy_source, energy_components in PowerSourceMap.items():
         for component in energy_components:
             query = energy_component_to_query(component)
@@ -217,6 +219,8 @@ def get_validate_df(data_path, benchmark_filename, query_response):
     validate_df = pd.DataFrame(items)
     if not validate_df.empty:
         print(validate_df.groupby(["scenarioID", "query"]).sum()[["count", ">0"]])
+    else:
+        print("Validate dataframe is empty.")
     return validate_df
 
 def check_ot_fg(args, valid_fg):
diff --git a/cmd/main.py b/cmd/main.py
@@ -879,7 +879,7 @@ def plot_scenario(args):
     parser.add_argument("--target-hints", type=str, help="Specify dynamic workload container name hints (used by TrainIsolator)")
     parser.add_argument("--bg-hints", type=str, help="Specify background workload container name hints (used by TrainIsolator)")
     parser.add_argument("--abs-pipeline-name", type=str, help="Specify AbsPower model pipeline (used by TrainIsolator)", default="")
-    parser.add_argument("-e", "--energy-source", type=str, help="Specify energy source.", default="intel_rapl")
+    parser.add_argument("-e", "--energy-source", type=str, help="Specify energy source.", default="rapl-sysfs")
     parser.add_argument("--abs-trainers", type=str, help="Specify trainer names for train command (use comma(,) as delimiter).", default="default")
     parser.add_argument("--dyn-trainers", type=str, help="Specify trainer names for train command (use comma(,) as delimiter).", default="default")
     parser.add_argument("--trainers", type=str, help="Specify trainer names for train_from_data command (use comma(,) as delimiter).", default="XgboostFitTrainer")
diff --git a/hack/aws_helper.sh b/hack/aws_helper.sh
@@ -29,7 +29,7 @@ MACHINE_SPEC_DIR="machine_spec"
 MACHINE_ID=""
 
 PIPELINE_NAME="${PIPELINE_NAME:-std_v0.7}"
-POWER_SOURCE="${POWER_SOURCE:-intel_rapl}"
+POWER_SOURCE="${POWER_SOURCE:-rapl-sysfs}"
 MODEL_TYPE="${MODEL_TYPE:-AbsPower}"
 FEATURE_NAME="${FEATURE_NAME:-BPFOnly}"
 TRAINER_NAME="${TRAINER_NAME:-XgboostFitTrainer_0}"
diff --git a/manifests/kepler/patch/patch-ci.yaml b/manifests/kepler/patch/patch-ci.yaml
@@ -17,4 +17,4 @@ spec:
       containers:
       - name: kepler-exporter
         imagePullPolicy: IfNotPresent
-        image: quay.io/sustainable_computing_io/kepler:release-0.7.7
+        image: quay.io/sustainable_computing_io/kepler:release-0.7.11
diff --git a/model_training/deployment/kepler.yaml b/model_training/deployment/kepler.yaml
@@ -190,8 +190,7 @@ spec:
     spec:
       containers:
       - args:
-        - /usr/bin/kepler -v=1 -kernel-source-dir=/usr/share/kepler/kernel_sources
-          -redfish-cred-file-path=/etc/redfish/redfish.csv
+        - /usr/bin/kepler -v=1 -redfish-cred-file-path=/etc/redfish/redfish.csv
         command:
         - /bin/sh
         - -c
@@ -204,7 +203,7 @@ spec:
           valueFrom:
             fieldRef:
               fieldPath: spec.nodeName
-        image: quay.io/sustainable_computing_io/kepler:release-0.7.7
+        image: quay.io/sustainable_computing_io/kepler:release-0.7.11
         imagePullPolicy: IfNotPresent
         livenessProbe:
           failureThreshold: 5
diff --git a/model_training/s3/src/s3/__about__.py b/model_training/s3/src/s3/__about__.py
@@ -1,4 +1,4 @@
 # SPDX-FileCopyrightText: 2024-present Sunil Thaha <sthaha@redhat.com>
 #
 # SPDX-License-Identifier: Apache-2.0
-__version__ = "0.7.7"
+__version__ = "0.7.11"
diff --git a/model_training/script.sh b/model_training/script.sh
@@ -17,7 +17,7 @@ export CLUSTER_PROVIDER=${CLUSTER_PROVIDER:-kind}
 export KIND_CLUSTER_NAME=${KIND_CLUSTER_NAME:-kind-for-training}
 export KIND_REGISTRY_NAME=${KIND_REGISTRY_NAME:-kind-registry-for-training}
 export PROM_SERVER=${PROM_SERVER:-http://localhost:9090}
-export ENERGY_SOURCE=${ENERGY_SOURCE:-intel_rapl,acpi}
+export ENERGY_SOURCE=${ENERGY_SOURCE:-rapl-sysfs,acpi}
 export VERSION=${VERSION-v0.7}
 export PIPELINE_PREFIX=${PIPELINE_PREFIX-"std_"}
 export DATAPATH=${DATAPATH-"$(pwd)/data"}
diff --git a/model_training/tekton/README.md b/model_training/tekton/README.md
@@ -17,7 +17,7 @@ Previous step: [Prepare cluster](./README.md#1-prepare-cluster)
 1. Install Tekton
 
    ```bash
-   kubectl apply --filename https://storage.googleapis.com/tekton-releases/pipeline/latest/release.yaml
+   kubectl apply --filename https://storage.googleapis.com/tekton-releases/pipeline/0.54.1/release.yaml
    ```
 
    > official guideline: <https://tekton.dev/docs/installation/pipelines/>
diff --git a/model_training/tekton/examples/single-train/abs-power.yaml b/model_training/tekton/examples/single-train/abs-power.yaml
@@ -1,5 +1,5 @@
 # example-abs-train-pipeline:
-#   running pipelines with all default value to train AbsPower model (intel_rapl, BPFOnly)
+#   running pipelines with all default value to train AbsPower model (rapl-sysfs, BPFOnly)
 apiVersion: tekton.dev/v1
 kind: PipelineRun
 metadata:
diff --git a/model_training/tekton/examples/single-train/default.yaml b/model_training/tekton/examples/single-train/default.yaml
@@ -1,5 +1,5 @@
 # kepler-default
-#   running pipelines with all default value to train AbsPower model (intel_rapl, BPFOnly) with COS
+#   running pipelines with all default value to train AbsPower model (rapl-sysfs, BPFOnly) with COS
 apiVersion: tekton.dev/v1
 kind: PipelineRun
 metadata:
diff --git a/model_training/tekton/examples/test-retrain.yaml b/model_training/tekton/examples/test-retrain.yaml
@@ -1,5 +1,5 @@
 # example-abs-train-pipeline:
-#   running pipelines with all default value to train AbsPower model (intel_rapl, BPFOnly)
+#   running pipelines with all default value to train AbsPower model (rapl-sysfs, BPFOnly)
 apiVersion: tekton.dev/v1
 kind: PipelineRun
 metadata:
diff --git a/model_training/tekton/pipelines/complete-retrain.yaml b/model_training/tekton/pipelines/complete-retrain.yaml
@@ -22,7 +22,7 @@ spec:
     description: Specify pipeline name (output prefix/folder)
   - name: ENERGY_SOURCE
     description: Specify target energy sources (check https://sustainable-computing.io/kepler_model_server/pipeline/#energy-source)
-    default: acpi,intel_rapl
+    default: acpi,rapl-sysfs
   - name: EXTRACTOR
     description: Specify extractor class (default or smooth)
     default: default
diff --git a/model_training/tekton/pipelines/complete-train.yaml b/model_training/tekton/pipelines/complete-train.yaml
@@ -25,7 +25,7 @@ spec:
     description: Specify pipeline name (output prefix/folder)
   - name: ENERGY_SOURCE
     description: Specify target energy sources (check https://sustainable-computing.io/kepler_model_server/pipeline/#energy-source)
-    default: acpi,intel_rapl
+    default: acpi,rapl-sysfs
   - name: IDLE_COLLECT_INTERVAL
     description: Specify interval time to collect profile (idle) data before start the workload
     default: 100
diff --git a/model_training/tekton/pipelines/single-retrain.yaml b/model_training/tekton/pipelines/single-retrain.yaml
@@ -25,7 +25,7 @@ spec:
     description: Specify target output type (check https://sustainable-computing.io/kepler_model_server/pipeline/#power-isolation)
   - name: ENERGY_SOURCE
     description: Specify target energy source (check https://sustainable-computing.io/kepler_model_server/pipeline/#energy-source)
-    default: intel_rapl
+    default: rapl-sysfs
   - name: FEATURE_GROUP
     description: Specify target feature group (check https://sustainable-computing.io/kepler_model_server/pipeline/#feature-group)
     default: BPFOnly
diff --git a/model_training/tekton/pipelines/single-train.yaml b/model_training/tekton/pipelines/single-train.yaml
@@ -28,7 +28,7 @@ spec:
     description: Specify target output type (check https://sustainable-computing.io/kepler_model_server/pipeline/#power-isolation)
   - name: ENERGY_SOURCE
     description: Specify target energy source (check https://sustainable-computing.io/kepler_model_server/pipeline/#energy-source)
-    default: intel_rapl
+    default: rapl-sysfs
   - name: FEATURE_GROUP
     description: Specify target feature group (check https://sustainable-computing.io/kepler_model_server/pipeline/#feature-group)
     default: BPFOnly
diff --git a/model_training/tekton/tasks/extract-task.yaml b/model_training/tekton/tasks/extract-task.yaml
@@ -21,7 +21,7 @@ spec:
     description: Specify target output type (check https://sustainable-computing.io/kepler_model_server/pipeline/#power-isolation)
   - name: ENERGY_SOURCE
     description: Specify target energy source (check https://sustainable-computing.io/kepler_model_server/pipeline/#energy-source)
-    default: intel_rapl
+    default: rapl-sysfs
   - name: FEATURE_GROUP
     description: Specify target feature group (check https://sustainable-computing.io/kepler_model_server/pipeline/#feature-group)
     default: BPFOnly
diff --git a/model_training/tekton/tasks/isolate-task.yaml b/model_training/tekton/tasks/isolate-task.yaml
@@ -19,7 +19,7 @@ spec:
     default: default
   - name: ENERGY_SOURCE
     description: Specify target energy source (check https://sustainable-computing.io/kepler_model_server/pipeline/#energy-source)
-    default: intel_rapl
+    default: rapl-sysfs
   - name: FEATURE_GROUP
     description: Specify target feature group (check https://sustainable-computing.io/kepler_model_server/pipeline/#feature-group)
     default: BPFOnly
diff --git a/model_training/tekton/tasks/original-pipeline-task.yaml b/model_training/tekton/tasks/original-pipeline-task.yaml
@@ -31,7 +31,7 @@ spec:
     default: default
   - name: ENERGY_SOURCE
     description: Specify target energy source (check https://sustainable-computing.io/kepler_model_server/pipeline/#energy-source)
-    default: acpi,intel_rapl
+    default: acpi,rapl-sysfs
   - name: TARGET_HINTS
     description: Specify target process keywords to keep in DynPower model training
     default: stress
diff --git a/model_training/tekton/tasks/train-task.yaml b/model_training/tekton/tasks/train-task.yaml
@@ -24,7 +24,7 @@ spec:
     default: AbsPower
   - name: ENERGY_SOURCE
     description: Specify target energy source (check https://sustainable-computing.io/kepler_model_server/pipeline/#energy-source)
-    default: intel_rapl
+    default: rapl-sysfs
   - name: FEATURE_GROUP
     description: Specify target feature group (check https://sustainable-computing.io/kepler_model_server/pipeline/#feature-group)
     default: BPFOnly
diff --git a/src/__about__.py b/src/__about__.py
@@ -1,4 +1,4 @@
 # SPDX-FileCopyrightText: 2024-present
 #
 # SPDX-License-Identifier: Apache-2.0
-__version__ = "0.7.7"
+__version__ = "0.7.11"
diff --git a/src/estimate/estimator.py b/src/estimate/estimator.py
@@ -59,7 +59,7 @@ def handle_request(data):
     output_type = ModelOutputType[power_request.output_type]
     # TODO: need revisit if get more than one rapl energy source
     if power_request.energy_source is None or "rapl" in power_request.energy_source:
-        power_request.energy_source = "intel_rapl"
+        power_request.energy_source = "rapl-sysfs"
 
     if output_type.name not in loaded_model:
         loaded_model[output_type.name] = dict()
diff --git a/src/server/model_server.py b/src/server/model_server.py
@@ -23,8 +23,8 @@
 
 
 class ModelRequest:
-    def __init__(self, metrics, output_type, source="intel_rapl", node_type=-1, weight=False, trainer_name="", filter="", pipeline_name="", spec=None):
-        # target source of power metric to be predicted (e.g., intel_rapl, acpi)
+    def __init__(self, metrics, output_type, source="rapl-sysfs", node_type=-1, weight=False, trainer_name="", filter="", pipeline_name="", spec=None):
+        # target source of power metric to be predicted (e.g., rapl-sysfs, acpi)
         self.source = source
         # type of node to select a model learned from similar nodes (default: -1, applied universal model learned by all node_type (TODO))
         self.node_type = node_type
@@ -126,7 +126,7 @@ def get_model():
     energy_source = req.source
     # TODO: need revisit if get more than one rapl energy source
     if energy_source is None or "rapl" in energy_source:
-        energy_source = "intel_rapl"
+        energy_source = "rapl-sysfs"
 
     # find valid feature groups from available metrics in request
     valid_fgs = get_valid_feature_groups(req.metrics)
@@ -180,7 +180,7 @@ def get_available_models():
             output_types = [ModelOutputType[ot]]
         # TODO: need revisit if get more than one rapl energy source
         if energy_source is None or "rapl" in energy_source:
-            energy_source = "intel_rapl"
+            energy_source = "rapl-sysfs"
 
         if filter is None:
             filters = dict()
diff --git a/src/train/ec2_pipeline.py b/src/train/ec2_pipeline.py
@@ -8,8 +8,8 @@
 
 after run:
 example of plot command:
-DATAPATH=/path/to/models python cmd/main.py plot --target-data estimate --input /path/to/data/i3.metal/kepler_query.json --pipeline-name ec2 --energy-source intel_rapl --model-name LinearRegressionTrainer_4 --output-type AbsPower --output i3metal-ec2 --feature-group BPFOnly
-DATAPATH=/path/to/models python cmd/main.py plot --target-data estimate --input /path/to/data/i3.metal/kepler_query.json --pipeline-name ec2 --energy-source intel_rapl --model-name LogarithmicRegressionTrainer_4 --output-type AbsPower --output i3metal-ec2 --feature-group BPFOnly
+DATAPATH=/path/to/models python cmd/main.py plot --target-data estimate --input /path/to/data/i3.metal/kepler_query.json --pipeline-name ec2 --energy-source rapl-sysfs --model-name LinearRegressionTrainer_4 --output-type AbsPower --output i3metal-ec2 --feature-group BPFOnly
+DATAPATH=/path/to/models python cmd/main.py plot --target-data estimate --input /path/to/data/i3.metal/kepler_query.json --pipeline-name ec2 --energy-source rapl-sysfs --model-name LogarithmicRegressionTrainer_4 --output-type AbsPower --output i3metal-ec2 --feature-group BPFOnly
 
 example of export command:
 DATAPATH=/path/to/models python cmd/main.py export --pipeline-name ec2 -o /path/to/kepler-model-db/models --publisher sunya-ch --zip=true --collect-date "July 2024"
@@ -62,7 +62,7 @@ def read_response_in_json(key):
 
 class Ec2PipelineRun():
     def __init__(self, name, abs_trainer_names=default_trainer_names, dyn_trainer_names=default_trainer_names, isolator=MinIdleIsolator()):
-        self.energy_source = "intel_rapl"
+        self.energy_source = "rapl-sysfs"
         self.energy_components = PowerSourceMap[self.energy_source]
         self.pipeline = NewPipeline(name, abs_trainer_names=abs_trainer_names, dyn_trainer_names=dyn_trainer_names, extractor=DefaultExtractor(), isolator=isolator, target_energy_sources=[self.energy_source])
 
diff --git a/src/train/extractor/extractor.py b/src/train/extractor/extractor.py
@@ -227,6 +227,8 @@ def get_power_data(self, query_results, energy_components, source):
             aggr_query_data = query_results[query].copy()
             # filter source
             aggr_query_data = aggr_query_data[aggr_query_data[SOURCE_COL] == source]
+            if len(aggr_query_data) == 0:
+                return None
             if unit_col is not None:
                 if usage_ratio_query not in query_results:
                     # sum over mode (idle, dynamic) and unit col
@@ -269,6 +271,8 @@ def get_power_data(self, query_results, energy_components, source):
                 df /= time_diff_values
                 df = df.mask(df.lt(0)).ffill().fillna(0).convert_dtypes()
                 power_data_list += [df]
+        if len(power_data_list) == 0:
+            return None
         power_data = pd.concat(power_data_list, axis=1).dropna()
         return power_data
 
diff --git a/src/train/offline_trainer.py b/src/train/offline_trainer.py
@@ -43,7 +43,7 @@
 """
 TrainRequest
 name - pipeline/model name
-energy_source - target enery source to train for (such as intel_rapl, acpi) 
+energy_source - target enery source to train for (such as rapl-sysfs, acpi) 
 trainer - attribute to construct a training pipeline
     - abs_trainers - trainer class name list for absolute power training 
     - dyn_trainers - trainer class name list for dynamic power training
diff --git a/src/train/profiler/profiler.py b/src/train/profiler/profiler.py
@@ -92,11 +92,14 @@ def process(self, query_results, profile_top_path=default_profile_top_path, save
             #
             # profile = load_profile(source) 
              #######################
+            found = False
             profile = dict()
             if node_types is None:
                 node_types = [replace_node_type]
             for node_type in node_types:
-                power_data= self.extractor.get_power_data(query_results, energy_components, source)
+                power_data = self.extractor.get_power_data(query_results, energy_components, source)
+                if power_data is None:
+                    break
                 if node_info_data is not None:
                     power_data = power_data.join(node_info_data)
                 else:
@@ -126,9 +129,11 @@ def process(self, query_results, profile_top_path=default_profile_top_path, save
                         if max_watt > profile[component][node_type_key][max_watt_key]:
                             profile[component][node_type_key][max_watt_key] = max_watt
                     # print("update:", component, node_type_key, min_watt_key, profile[component][node_type_key][min_watt_key])
-            if save:
-                save_profile(profile_path, source, profile)
-            result[source] = profile 
+                    found = True
+            if found:
+                if save:
+                    save_profile(profile_path, source, profile)
+                result[source] = profile
         return result
 
 class Profile:
diff --git a/src/train/trainer/XGBoostTrainer/main.py b/src/train/trainer/XGBoostTrainer/main.py
diff --git a/src/util/config.py b/src/util/config.py
diff --git a/src/util/loader.py b/src/util/loader.py
diff --git a/src/util/train_types.py b/src/util/train_types.py
diff --git a/tests/README.md b/tests/README.md
diff --git a/tests/data/prom_output/.DS_Store b/tests/data/prom_output/.DS_Store
diff --git a/tests/data/prom_output/idle.json b/tests/data/prom_output/idle.json
diff --git a/tests/data/prom_output/prom_response.json b/tests/data/prom_output/prom_response.json
diff --git a/tests/e2e_test.sh b/tests/e2e_test.sh
diff --git a/tests/estimator_power_request_test.py b/tests/estimator_power_request_test.py
diff --git a/tests/extractor_test.py b/tests/extractor_test.py
diff --git a/tests/minimal_trainer.py b/tests/minimal_trainer.py
diff --git a/tests/model_server_test.py b/tests/model_server_test.py
diff --git a/tests/pipeline_test.py b/tests/pipeline_test.py
diff --git a/tests/xgboost_test.py b/tests/xgboost_test.py

Original file line number	Diff line number	Diff line change
`@@ -206,7 +206,7 @@ def _plot_models(models, cpu_ms_max, energy_source, output_folder, name, max_plo`
`206`	`206`	`main_feature_col = BPF_FEATURES[0]`
`207`	`207`	`predicted_col = {`
`208`	`208`	`"acpi": "default_platform_power",`
`209`		`- "intel_rapl": "default_package_power"`
	`209`	`+ "rapl-sysfs": "default_package_power"`
`210`	`210`	`}`
`211`	`211`
`212`	`212`	`num_bins = len(cpu_ms_max)//cpu_time_bin_num + 1`