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import torch.nn as nn
import torch.nn.functional as F
from torch.backends.cuda import sdp_kernel, SDPBackend
import time
import torch
import torch.utils.benchmark as benchmark


# check dependency
assert torch.cuda.is_available(), 'CUDA is expected.'

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from pathlib import Path
from pprint import pprint
import cv2
import numpy as np
import matplotlib.pyplot as plt
import concurrent
from tqdm import tqdm

# Just for visualization. By default it is inactive
def display_img(img_list):

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import torch

y_pred = torch.tensor([
    [1, 1, 0, 1, 1, 1]
    ], dtype=torch.float)

y_truth_id = torch.tensor([2], dtype=torch.long)
y_truth_id_tmp  = y_truth_id.unsqueeze(0)
y_truth_one_hot = torch.zeros(y_truth_id_tmp.size(0), 6).scatter_(1, y_truth_id_tmp, 1.)

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docker history --no-trunc c3555fec4fe6 $argv  | tac | tr -s ' ' | cut -d " " -f 5- | sed 's,^/bin/sh -c #(nop) ,,g' | sed 's,^/bin/sh -c,RUN,g' | sed 's, && ,\n  & ,g' | sed 's,\s*[0-9]*[\.]*[0-9]*[kMG]*B\s*$,,g' | head -n -1

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docker history --no-trunc c3555fec4fe6 $argv  | tac | tr -s ' ' | cut -d " " -f 5- | sed 's,^/bin/sh -c #(nop) ,,g' | sed 's,^/bin/sh -c,RUN,g' | sed 's, && ,\n  & ,g' | sed 's,\s*[0-9]*[\.]*[0-9]*[kMG]*B\s*$,,g' | head -n -1

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def get_usb_camera_id():
    from subprocess import check_output
    out = check_output(["ls /dev/video*"], shell=True)
    out = out.decode('utf-8').strip().split('\n')

    if len(out) == 0:
        raise Exception('No camera Module Found')

    cam_id = None
    for dev in out:

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Install Latest Nvidia Driver in Ubuntu 18.04 LTS

Step: 1

Remove previous installation

sudo apt-get purge nvidia*
sudo apt-get autoremove 

---

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import numpy as np
import scipy.stats
from pprint import pprint
import matplotlib.pyplot as plt
import logging
logging.basicConfig(level=logging.DEBUG)

# source: https://stackoverflow.com/a/50629604/4257991
def my_distribution(min_val, max_val, mean, std):
    scale = max_val - min_val

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def my_plot(img_list):
    fig = plt.figure(figsize=(8, 8))
    plt.tight_layout()
    
    sqr_arm = round(math.ceil(math.sqrt(len(img_list))))
    print(sqr_arm)
    columns, rows = sqr_arm, sqr_arm 
    for i, data in enumerate(img_list):
        img, title = data if (isinstance(data, tuple) or isinstance(data, list)) else (data, '')
        ax = plt.subplot(rows, columns, i+1)

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Run remote jupyter in localhost using ssh tunnel

in remote server

jupyter notebook --no-browser --port=8889

in local server