Trying to get rid of the error on app not initializing and updating the EnergyStarAI to AIEnergyScore

Dockerfile

@@ -76,4 +76,4 @@ RUN --mount=type=secret,id=DEBUG,mode=0444,required=true \
  git init && \
  git remote add origin $(cat /run/secrets/DEBUG)
 
-ENTRYPOINT ["/entrypoint.sh"]
+CMD ["/entrypoint.sh"]

create_results.py

@@ -13,12 +13,12 @@ out_dir = sys.argv[1]
 #Uploading results
 api.upload_folder(
     folder_path=out_dir,
-    repo_id="EnergyStarAI/results_debug",
+    repo_id="AIEnergyScore/results_debug",
     repo_type="dataset",
 )
 
 #Updating requests
-requests = load_dataset("EnergyStarAI/requests_debug", split="test", token=TOKEN)
+requests = load_dataset("AIEnergyScore/requests_debug", split="test", token=TOKEN)
 requests_dset = requests.to_pandas()
 
 models_ran=[]
@@ -33,5 +33,5 @@ print("Models ran are: " + str(models_ran))
 
 requests_dset.loc[requests_dset["model"].isin(models_ran), ['status']] = "COMPLETED"
 updated_dset =Dataset.from_pandas(requests_dset)
-updated_dset.push_to_hub("EnergyStarAI/requests_debug", split="test", token=TOKEN)
+updated_dset.push_to_hub("AIEnergyScore/requests_debug", split="test", token=TOKEN)
 print("Updated model status")

entrypoint.sh

@@ -1,6 +1,6 @@
 #!/bin/bash
 
-export SPACE="EnergyStarAI/launch-computation-example"
+export SPACE="AIEnergyScore/launch-computation-example"
 
 echo "Not checking h100 -- already know it's not there."
 #python /check_h100.py
@@ -19,7 +19,9 @@ python /parse_requests.py | while read -r line; do
     mkdir -p "$run_dir"
 
     # Let the benchmarking begin!
-    optimum-benchmark --config-name "${experiment_name}"  --config-dir /optimum-benchmark/examples/energy_star/ backend.model="${backend_model}" backend.processor="${backend_model}" hydra.run.dir="${run_dir}" 2> "${run_dir}/error.log" || (python /failed_run.py --run_dir "${run_dir}" --model_name "${backend_model}" && rm -rf $run_dir)
+    optimum-benchmark --config-name "${experiment_name}"  --config-dir /optimum-benchmark/examples/energy_star/ backend.model="${backend_model}" backend.processor="${backend_model}" hydra.run.dir="${run_dir}" 2> "${run_dir}/error.log" ||
+    # If the benchmark fails, update accordingly. Remove the run directory for that specific model.
+    (python /failed_run.py --run_dir "${run_dir}" --model_name "${backend_model}" && rm -rf $run_dir)
 done
 
 echo "Finished; uploading dataset results"

failed_run.py

@@ -27,7 +27,7 @@ parser.add_argument(
 args = parser.parse_args()
 
 # Updating request
-dataset = load_dataset("EnergyStarAI/requests_debug", split="test", token=TOKEN).to_pandas()
+dataset = load_dataset("AIEnergyScore/requests_debug", split="test", token=TOKEN).to_pandas()
 
 # Set benchmark to failed
 # TODO: This doesn't have to be try-except, we could actually check if the file is there.
@@ -46,4 +46,4 @@ except FileNotFoundError as e:
     print(f"Could not find {args.run_dir}/error.log")
     
 updated_dataset = Dataset.from_pandas(dataset)
-updated_dataset.push_to_hub("EnergyStarAI/requests_debug", split="test", token=TOKEN)
+updated_dataset.push_to_hub("AIEnergyScore/requests_debug", split="test", token=TOKEN)

upload_run_folder.py

@@ -20,7 +20,7 @@ try:
     api.upload_folder(
         folder_path=args.run_dir,
         path_in_repo=args.run_dir,
-        repo_id="EnergyStarAI/backend_runs_directory",
+        repo_id="AIEnergyScore/backend_runs_directory",
         repo_type="dataset",
     )
 except Exception as e: