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import json
from pathlib import Path
from codecarbon import EmissionsTracker
from datasets import load_dataset
from sklearn.metrics import accuracy_score
from model import FastModel, save_pipeline
dataset = load_dataset("rfcx/frugalai")
train_dataset = dataset["train"]
test_dataset = dataset["test"]
tracker = EmissionsTracker(allow_multiple_runs=True)
with open("../config.json", "r") as file:
config = json.load(file)
model = FastModel(
config["audio_processing_params"],
config["features_params"],
config["lgbm_params"],
)
model.fit(dataset["train"])
# INFERENCE
tracker.start()
tracker.start_task("inference")
true_label = dataset["test"]["label"]
predictions = model.predict(dataset["test"])
emissions_data = tracker.stop_task()
print(accuracy_score(true_label, predictions))
print("energy_consumed_wh", emissions_data.energy_consumed * 1000)
print("emissions_gco2eq", emissions_data.emissions * 1000)
save_pipeline(model, Path("../")) |