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Update app.py
Browse files
app.py
CHANGED
@@ -7,30 +7,9 @@ TOKEN = os.environ.get("BULK_ENERGY_TOKEN")
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API = HfApi(token=TOKEN)
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REPO_ID = "AIEnergyScore/BulkCalcSpace"
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app = FastAPI()
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def check_for_traceback(run_dir):
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# run_dir="./runs/${experiment_name}/${backend_model}/${now}"
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found_error = False
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error_message = ""
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try:
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# Read error message
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with open(f"{run_dir}/error.log", 'r') as f:
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# There may be a better way to do this that finds the
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# index of Traceback, then prints from there : end-of-file index (the file length-1).
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for line in f:
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# Question: Do we even need to check for this? The presence of the
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# error file, or at least a non-empty one,
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# means there's been an error, no?
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if 'Traceback (most recent call last):' in line:
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found_error = True
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if found_error:
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error_message += line
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except FileNotFoundError as e:
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# When does this happen?
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print(f"Could not find {run_dir}/error.log")
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return error_message
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@app.get("/")
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def start_train():
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model_file = open("models.txt", "r+").readlines()
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@@ -38,7 +17,7 @@ def start_train():
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hardware_file = open("hardware.txt", "r+").readlines()
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for hardware in hardware_file:
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hardware = hardware.strip()
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print(f"
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curr_runtime = API.get_space_runtime(repo_id=REPO_ID)
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print(f"Current hardware is {curr_runtime}")
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if curr_runtime != hardware:
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@@ -46,18 +25,22 @@ def start_train():
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API.request_space_hardware(repo_id=REPO_ID, hardware=hardware)
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for model in model_file:
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model = model.strip()
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for task in task_file:
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task = task.strip()
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# Create the name of the directory for output.
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now = time.time()
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run_dir = f"/runs
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os.system(f"./entrypoint.sh {REPO_ID} {model} {task} {hardware} {run_dir}")
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API = HfApi(token=TOKEN)
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REPO_ID = "AIEnergyScore/BulkCalcSpace"
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RESULTS_DSET = "AIEnergyScore/BulkCalcResults"
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app = FastAPI()
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@app.get("/")
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def start_train():
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model_file = open("models.txt", "r+").readlines()
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hardware_file = open("hardware.txt", "r+").readlines()
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for hardware in hardware_file:
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hardware = hardware.strip()
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print(f"Requested hardware is {hardware}")
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curr_runtime = API.get_space_runtime(repo_id=REPO_ID)
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print(f"Current hardware is {curr_runtime}")
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if curr_runtime != hardware:
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API.request_space_hardware(repo_id=REPO_ID, hardware=hardware)
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for model in model_file:
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model = model.strip()
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print(f"Attempting to benchmark model {model}.")
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for task in task_file:
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task = task.strip()
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print(f"Attempting to benchmark model {model} on task {task}.")
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# Create the name of the directory for output.
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now = time.time()
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run_dir = f"/runs/{task}/{model}/{now}"
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os.system(f"./entrypoint.sh {REPO_ID} {model} {task} {hardware} {run_dir}")
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# Uploads all run output to the results dataset.
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print(f"Uploading {run_dir} to {RESULTS_DSET}")
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try:
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API.create_repo(repo_id=f"{RESULTS_DSET}", repo_type="dataset",)
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print(f"Created results dataset repository")
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except:
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print(f"Using pre-existing dataset respository.")
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API.upload_folder(folder_path=run_dir, repo_id=f"{RESULTS_DSET}", repo_type="dataset",)
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print("Pausing space")
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API.pause_space(REPO_ID)
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#return {"Status": "Done"}
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