This file was not needed.

training.py

@@ -1,85 +0,0 @@
-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):
-    # 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')):
-
-    background_tasks.add_task(invoke_training, max_epochs, val_check_interval, warmup_steps, model_in_use)
-
-    return {"message": "Dnote Donut ML training started in the background"}
-
-
-def invoke_evaluate(model_in_use):
-    # 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')):
-
-    background_tasks.add_task(invoke_evaluate, model_in_use)
-
-    return {"message": "Dnote Donut 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