future_main.py

import os
os.environ["OMP_NUM_THREADS"] = os.environ["SLURM_CPUS_PER_TASK"] # export OMP_NUM_THREADS=1
os.environ["OPENBLAS_NUM_THREADS"] = "4" # export OPENBLAS_NUM_THREADS=1 
os.environ["MKL_NUM_THREADS"] = "4" # export MKL_NUM_THREADS=1
os.environ["VECLIB_MAXIMUM_THREADS"] = "4" # export VECLIB_MAXIMUM_THREADS=1
os.environ["NUMEXPR_NUM_THREADS"] = "4" # export NUMEXPR_NUM_THREADS=1


import torch
#torch.manual_seed(5)#3,5
import random
#random.seed(0)
from multiprocessing import Pool
import psutil
import numpy
import numpy as np
#np.random.seed(0)


from src.evaluation.evaluator_manager import EvaluatorManager
from src.evaluation.future.evaluator_manager_triplets import EvaluatorManager

from src.utils.context import Context
import sys

if __name__ == "__main__":

    print(f"Generating context for: {sys.argv[1]}")
    context = Context.get_context(sys.argv[1])
    context.run_number = int(sys.argv[2]) if len(sys.argv) == 3 else -1


    context.logger.info(f"Executing: {context.config_file} Run: {context.run_number}")
    context.logger.info(
        "Creating the evaluation manager......................................................."
    )    

    context.logger.info(f"Executing: {context.config_file} Run: {context.run_number}")
    context.logger.info("Creating the evaluation manager....................................")

    context.logger.info("Creating the evaluators......................................................")
    eval_manager = EvaluatorManager(context)

    context.logger.info(
        "Evaluating the explainers............................................................."
    )
    eval_manager.evaluate()
    eval_manager.pickle_explanations('./lab/pickles')