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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 |