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Tuatini Godard EKami

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View Hwinfo.csv
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Date,Time,"Virtual Memory Committed [MB]","Virtual Memory Available [MB]","Virtual Memory Load [%]","Physical Memory Used [MB]","Physical Memory Available [MB]","Physical Memory Load [%]","Page File Usage [%]","Core VIDs (avg) [V]","Core 0 VID [V]","Core 1 VID [V]","Core 2 VID [V]","Core 3 VID [V]","Core 4 VID [V]","Core 5 VID [V]","Core 6 VID [V]","Core 7 VID [V]","Core 8 VID [V]","Core 9 VID [V]","Core 10 VID [V]","Core 11 VID [V]","Core 12 VID [V]","Core 13 VID [V]","Core 14 VID [V]","Core 15 VID [V]","Core Clocks (avg) [MHz]","Core 0 Clock (perf #1/2) [MHz]","Core 1 Clock (perf #1/1) [MHz]","Core 2 Clock (perf #5/6) [MHz]","Core 3 Clock (perf #6/7) [MHz]","Core 4 Clock (perf #4/5) [MHz]","Core 5 Clock (perf #7/8) [MHz]","Core 6 Clock (perf #2/3) [MHz]","Core 7 Clock (perf #3/4) [MHz]","Core 8 Clock (perf #13/14) [MHz]","Core 9 Clock (perf #14/15) [MHz]","Core 10 Clock (perf #15/16) [MHz]","Core 11 Clock (perf #12/13) [MHz]","Core 12 Clock (perf #10/11) [MHz]","Core 13 Clock (perf #11/12) [MHz]","Core 14 C
View docker_pwd_ecr_assume_role.sh
#!/bin/bash
set -e
if [ -z "$AWS_ACCESS_KEY_ID" ] || [ -z "$AWS_SECRET_ACCESS_KEY" ]; then
echo "Please provide AWS credentials"
exit 1
fi
if [ -z "$IAM_ROLE_ARN" ]; then
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EKami / launch_focus_min_wayland.sh
Last active October 19, 2022 07:18
Open and close terminator on Gnome 3 wayland
View launch_focus_min_wayland.sh
#!/bin/bash
# https://superuser.com/questions/142945/bash-command-to-focus-a-specific-window/1627429#1627429
# To use, set a shortcut in Gnome like this: bash -c '/home/user/launch_focus_min_wayland.sh terminator'
# To check the available function names, do ALT + F2 and type "lg"
app=$1
if [[ $app == terminator ]]; then
process_name=/usr/bin/terminator
else
process_name=$app
View GPG pubkey GODARD Tuatini
-----BEGIN PGP PUBLIC KEY BLOCK-----
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KSA8ZW1haWxAdHVhdGluaS5tZT6JAU4EEwEIADgWIQSW3rJ7WQ+eYBAPigy80Dgv
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EKami / amazon_forest_notebook.ipynb
Created July 9, 2018 15:32
Planet: Understanding the Amazon deforestation from Space challenge
View amazon_forest_notebook.ipynb
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View area.py
mask_img = np.array(Image.open(mask.file, mode='r').convert('1'))
# Absolute WSI coordinates
dx = max(patch_x, mask.x)
dx2 = min(patch_x + self.crop_size, mask.x + mask.width)
dy = max(patch_y, mask.y)
dy2 = min(patch_y + self.crop_size, mask.y + mask.height)
# Make the coordinates relative to the mask position
dx = dx - mask.x
View stacktrace.py
Traceback (most recent call last):
File "/Users/Ekami/Programs/anaconda/envs/dl/lib/python3.6/site-packages/django/core/handlers/exception.py", line 35, in inner
response = get_response(request)
File "/Users/Ekami/Programs/anaconda/envs/dl/lib/python3.6/site-packages/django/core/handlers/base.py", line 128, in _get_response
response = self.process_exception_by_middleware(e, request)
File "/Users/Ekami/Programs/anaconda/envs/dl/lib/python3.6/site-packages/django/core/handlers/base.py", line 126, in _get_response
response = wrapped_callback(request, *callback_args, **callback_kwargs)
File "/Users/Ekami/Programs/anaconda/envs/dl/lib/python3.6/site-packages/django/views/generic/base.py", line 69, in view
return self.dispatch(request, *args, **kwargs)
File "/Users/Ekami/Programs/anaconda/envs/dl/lib/python3.6/site-packages/django/views/generic/base.py", line 89, in dispatch
View error.py
Error: Failed to start algorithm - Traceback (most recent call last):
File "/opt/algorithm/bin/pipe.py", line 14, in <module>
algorithm = __import__('src.'+config['algoname'], fromlist=["apply"])
File "/opt/algorithm/src/srgan_algorithmia.py", line 6, in <module>
from torchlite.eval import eval
File "/opt/algorithm/dependencies/torchlite/eval/eval.py", line 5, in <module>
from torchlite.data.datasets.srgan import EvalDataset
File "/opt/algorithm/dependencies/torchlite/data/datasets/srgan.py", line 3, in <module>
import torchlite.nn.transforms as ttransforms
File "/opt/algorithm/dependencies/torchlite/nn/transforms.py", line 20, in <module>
View algorithmia1.py
import os
import requests
from io import BytesIO
import Algorithmia
from Algorithmia.acl import ReadAcl
from torchlite.eval import eval
from pathlib import Path
from PIL import Image
import uuid
View gist:fc078fc0d3274d94a3c03364e4b68bd5
import os
import requests
from io import BytesIO
import Algorithmia
from Algorithmia.acl import ReadAcl
from torchlite.eval import eval
from pathlib import Path
from PIL import Image
import uuid