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#
# Source: https://thepihut.com/blogs/raspberry-pi-tutorials/27968772-turning-on-an-led-with-your-raspberry-pis-gpio-pins
#

import RPi.GPIO as GPIO              # Import Raspberry Pi GPIO library
from time import sleep               # Import the sleep function

pinLED = 27                          # LED GPIO Pin LED
GPIO.setmode(GPIO.BCM)               # Use GPIO pin number
GPIO.setwarnings(False)              # Ignore warnings in our case

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import argparse
import inspect
import warnings
from typing import List, Optional, Union


from tqdm.auto import tqdm
import torch
from torch import autocast

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import numpy as np


def draw_msra_gaussian(heatmap, channel, center, sigma=2):
    """Draw a gaussian on heatmap channel (inplace function).

    Args:
        heatmap (np.ndarray): heatmap matrix, expected shapes [C, W, H].
        channel (int): channel to use for drawing a gaussian.
        center (Tuple[int, int]): gaussian center coordinates.

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import Jetson.GPIO as GPIO
import time


class Motor:
    def __init__(self, ena, in1, in2):
        self.ena = ena
        self.in1 = in1
        self.in2 = in2

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import torch
import collections
from typing import List


def checkpoints_weights_avg(inputs: List[str]):
    """Loads checkpoints from inputs and returns a model with averaged weights.

    Args:
      inputs: An iterable of string paths of checkpoints to load from.

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import torch
import torch.nn as nn
from transformers import AutoConfig, AutoModel


class PooledLstmTransfModel(nn.Module):
    def __init__(self,
                 pretrain_dir: str,
                 num_classes: int = 1):
        super(PooledLstmTransfModel, self).__init__()

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import numpy as np
from numba import njit, prange


@njit(parallel=True)
def _fast_f_beta_score_by_row(y_pred: np.ndarray, y_true: np.ndarray, beta: float) -> float:
    num_rows: int = y_true.shape[0]
    num_cols: int = y_true.shape[1]
    score: float = 0
    b2 = beta * beta