El 李天宝 elcolie

## nvidia_gpu_chk.py
import torch
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
print('Using device:', device)
print()

#Additional Info when using cuda
if device.type == 'cuda':
    print(torch.cuda.get_device_name(0))
    print('Memory Usage:')
    print('Allocated:', round(torch.cuda.memory_allocated(0)/1024**3,1), 'GB')

## set_seed.py
import random
import torch
import numpy as np

def seed_everything(seed: int):
    random.seed(seed)
    os.environ['PYTHONHASHSEED'] = str(seed)
    np.random.seed(seed)
    torch.manual_seed(seed)
    if torch.cuda.is_available():

## timeseries.csv

          
            x
            sol

            
              -12.1748046875
              0

            
              11.991466522216797
              0

            
              -12.00814437866211
              0

            
              11.986132621765137
              0

            
              -12.007420539855957
              0

            
              12.002096176147461
              0

            
              12.192679405212402
              0

            
              12.278199195861816
              0

            
              -12.004239082336426
              0

## survey_10th.csv

          
            trcr_time_stamp
            trcr_co2_conc_pct
            predicted_label

            
              2019-03-13 09:51:20
              0.4621884093538548
              0.0

            
              2019-03-13 09:51:30
              0.48048942958314345
              0.0

            
              2019-03-13 09:51:40
              0.5470032574779469
              0.0

            
              2019-03-13 09:51:41
              0.553655402428856
              0.0

            
              2019-03-13 09:51:50
              0.6097581052057149
              0.0

            
              2019-03-13 09:52:00
              0.5908580260933587
              0.0

            
              2019-03-13 09:52:10
              0.49999009190142507
              0.0

            
              2019-03-13 09:52:20
              0.48048942958314345
              0.0

            
              2019-03-13 09:52:30
              0.44938104870363965
              9.0

## transducer.csv

          
            time
            amplitude

            
              0
              0.000096

            
              0.001
              0.000134

            
              0.002
              0.000108

            
              0.003
              0.000112

            
              0.004
              0.000115

            
              0.005
              0.00014

            
              0.006
              0.000144

            
              0.007
              0.000126

            
              0.008
              0.000108

## question.csv

          
            
            0

            
              0
              68.86199951171875

            
              1
              68.77896118164062

            
              2
              68.7582015991211

            
              3
              68.7533187866211

            
              4
              68.7520980834961

            
              5
              68.59825897216797

            
              6
              68.55979919433594

            
              7
              68.69412231445312

            
              8
              68.72769927978516

## load_well.txt
Load well
query solution
http://zbumper:8011/gql/

mutation load_well {
  cmd_load_well_from_tao2db(
    well: {
      opru_fld_nme: "EXAMPLE"
      prod_govt_lse_nbr: "A"
      well_nbr: "A1"

## .pre-commit-config.yaml
default_language_version:
    python: python
repos:
  - repo: https://github.com/pre-commit/pre-commit-hooks
    rev: v2.2.0
    hooks:
    - id: trailing-whitespace
      types: [python]
    - id: end-of-file-fixer
      types: [python]

## query_debugger.py
from django.db import connection, reset_queries
import time
import functools

def query_debugger(func):

    @functools.wraps(func)
    def inner_func(*args, **kwargs):

        reset_queries()

## red_pill.txt
# Unfortunately I am still working with `blob`

====================================
PyCharm
LINE on chrome
MS team on Linux
Slack or use web
WhatsApp or use web

zoom feature in Gnome3 https://unix.stackexchange.com/questions/33243/does-gnome-3-support-desktop-zoom
	import torch
	device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
	print('Using device:', device)
	print()

	#Additional Info when using cuda
	if device.type == 'cuda':
	print(torch.cuda.get_device_name(0))
	print('Memory Usage:')
	print('Allocated:', round(torch.cuda.memory_allocated(0)/1024**3,1), 'GB')
	import random
	import torch
	import numpy as np

	def seed_everything(seed: int):
	random.seed(seed)
	os.environ['PYTHONHASHSEED'] = str(seed)
	np.random.seed(seed)
	torch.manual_seed(seed)
	if torch.cuda.is_available():
	x	sol
	-12.1748046875	0
	11.991466522216797	0
	-12.00814437866211	0
	11.986132621765137	0
	-12.007420539855957	0
	12.002096176147461	0
	12.192679405212402	0
	12.278199195861816	0
	-12.004239082336426	0
trcr_time_stamp	trcr_co2_conc_pct	predicted_label
2019-03-13 09:51:20	0.4621884093538548	0.0
2019-03-13 09:51:30	0.48048942958314345	0.0
2019-03-13 09:51:40	0.5470032574779469	0.0
2019-03-13 09:51:41	0.553655402428856	0.0
2019-03-13 09:51:50	0.6097581052057149	0.0
2019-03-13 09:52:00	0.5908580260933587	0.0
2019-03-13 09:52:10	0.49999009190142507	0.0
2019-03-13 09:52:20	0.48048942958314345	0.0
2019-03-13 09:52:30	0.44938104870363965	9.0
	time	amplitude
	0	0.000096
	0.001	0.000134
	0.002	0.000108
	0.003	0.000112
	0.004	0.000115
	0.005	0.00014
	0.006	0.000144
	0.007	0.000126
	0.008	0.000108
		0
	0	68.86199951171875
	1	68.77896118164062
	2	68.7582015991211
	3	68.7533187866211
	4	68.7520980834961
	5	68.59825897216797
	6	68.55979919433594
	7	68.69412231445312
	8	68.72769927978516
	Load well
	query solution
	http://zbumper:8011/gql/

	mutation load_well {
	cmd_load_well_from_tao2db(
	well: {
	opru_fld_nme: "EXAMPLE"
	prod_govt_lse_nbr: "A"
	well_nbr: "A1"
	default_language_version:
	python: python
	repos:
	- repo: https://github.com/pre-commit/pre-commit-hooks
	rev: v2.2.0
	hooks:
	- id: trailing-whitespace
	types: [python]
	- id: end-of-file-fixer
	types: [python]
	from django.db import connection, reset_queries
	import time
	import functools

	def query_debugger(func):

	@functools.wraps(func)
	def inner_func(args, *kwargs):

	reset_queries()
	# Unfortunately I am still working with `blob`

	====================================
	PyCharm
	LINE on chrome
	MS team on Linux
	Slack or use web
	WhatsApp or use web

	zoom feature in Gnome3 https://unix.stackexchange.com/questions/33243/does-gnome-3-support-desktop-zoom