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from fastapi import APIRouter, Form, BackgroundTasks
from config import settings
import os
import json
from routers.donut_evaluate import run_evaluate_donut
from routers.donut_training import run_training_donut
import utils
router = APIRouter()
def invoke_training(max_epochs, val_check_interval, warmup_steps, model_in_use, sparrow_key):
if sparrow_key != settings.sparrow_key:
return {"error": "Invalid Sparrow key."}
if model_in_use == 'donut':
processing_time = run_training_donut(max_epochs, val_check_interval, warmup_steps)
utils.log_stats(settings.training_stats_file, [processing_time, settings.model])
print(f"Processing time training: {processing_time:.2f} seconds")
@router.post("/training")
async def run_training(background_tasks: BackgroundTasks,
max_epochs: int = Form(30),
val_check_interval: float = Form(0.4),
warmup_steps: int = Form(81),
model_in_use: str = Form('donut'),
sparrow_key: str = Form(None)):
background_tasks.add_task(invoke_training, max_epochs, val_check_interval, warmup_steps, model_in_use, sparrow_key)
return {"message": "Sparrow ML training started in the background"}
def invoke_evaluate(model_in_use, sparrow_key):
if sparrow_key != settings.sparrow_key:
return {"error": "Invalid Sparrow key."}
if model_in_use == 'donut':
scores, accuracy, processing_time = run_evaluate_donut()
utils.log_stats(settings.evaluate_stats_file, [processing_time, scores, accuracy, settings.model])
print(f"Processing time evaluate: {processing_time:.2f} seconds")
@router.post("/evaluate")
async def run_evaluate(background_tasks: BackgroundTasks,
model_in_use: str = Form('donut'),
sparrow_key: str = Form(None)):
background_tasks.add_task(invoke_evaluate, model_in_use, sparrow_key)
return {"message": "Sparrow ML model evaluation started in the background"}
@router.get("/statistics/training")
async def get_statistics_training():
file_path = settings.training_stats_file
# Check if the file exists, and read its content
if os.path.exists(file_path):
with open(file_path, 'r') as file:
try:
content = json.load(file)
except json.JSONDecodeError:
content = []
else:
content = []
return content
@router.get("/statistics/evaluate")
async def get_statistics_evaluate():
file_path = settings.evaluate_stats_file
# Check if the file exists, and read its content
if os.path.exists(file_path):
with open(file_path, 'r') as file:
try:
content = json.load(file)
except json.JSONDecodeError:
content = []
else:
content = []
return content |