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4149ca9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 | import gradio as gr
from src.services.serviceLLM.calculation import calculate_impact_llm
from src.dto.InputData import InputData
def handle_launch(
mode, project_duration, duration_slider, model_details, parameters_count, framework,
quantization, stages, inference_users, inference_requests, inference_tokens,
finetuning_data_size, finetuning_epochs_number, finetuning_batch_size, finetuning_peft,
infra_type, infra_cpu_cores, infra_gpu_count, infra_gpu_memory, infra_memory,
infra_pue_datacenter, infra_pue_machine, location):
"""
Lance le calcul d'impact environnemental à partir des paramètres fournis
et affiche les résultats sur l'interface.
"""
input_parameters = InputData(mode, duration_slider, model_details, parameters_count, framework,
quantization, stages, inference_users, inference_requests,
inference_tokens, finetuning_data_size, finetuning_epochs_number,
finetuning_batch_size, finetuning_peft,
infra_type, infra_cpu_cores, infra_gpu_count, infra_gpu_memory,
infra_memory, infra_pue_datacenter, infra_pue_machine, location)
result, _ = calculate_impact_llm(input_parameters)
best_config = result.more_frugal_conf.split(",")
return (gr.Tabs(selected=1), gr.update(visible=True),
gr.update(value="## 📊 Results for " +
str(duration_slider) + " years"),
result.energy_consumption,
result.carbon_footprint,
result.abiotic_resource_usage,
result.water_usage,
gr.update(value=result.eq_energy_consumption.split("|")[1],
label=result.eq_energy_consumption.split("|")[0]),
gr.update(value=result.eq_carbon_footprint.split("|")[1],
label=result.eq_carbon_footprint.split("|")[0]),
gr.update(value=result.eq_abiotic_resources.split("|")[1],
label=result.eq_abiotic_resources.split("|")[0]),
gr.update(value=result.eq_water_usage.split("|")[1],
label=result.eq_water_usage.split("|")[0]),
result.carbon_footprint_chart,
result.abiotic_resource_chart,
result.water_usage_chart,
gr.update(value="Compare with the most frugal configuration: the model " +
best_config[0] + " with " + best_config[1] + " framework"),
result.percentage_reduction,
gr.update(value=min(project_duration, duration_slider),
maximum=project_duration)
)
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