-
Generate a 2048-bit RSA private key
openssl genrsa -out private_key.pem 2048
-
Convert private Key to PKCS#8 format (so Java can read it)
openssl pkcs8 -topk8 -inform pem -in private_key.pem -outform der -nocrypt -out private_key.der.pkcs8
| function sjira() { | |
| local __usage=" | |
| Usage: sjira GROW-3599 [-poc] | |
| Options: | |
| -p, --print Print genereated URL | |
| -o, --open Open generated URL in browser (Default) | |
| -c, --copy Copy generated URL to clipboard | |
| " | |
| if [ "$#" -lt 1 ]; then |
Generate a 2048-bit RSA private key
openssl genrsa -out private_key.pem 2048Convert private Key to PKCS#8 format (so Java can read it)
openssl pkcs8 -topk8 -inform pem -in private_key.pem -outform der -nocrypt -out private_key.der.pkcs8
| @Composable | |
| fun AutoCompleteTextField( | |
| initialText: String, | |
| itemList: List<String>, | |
| onQuery: (String) -> Unit, | |
| onClearResults: () -> Unit, | |
| modifier: Modifier = Modifier | |
| ) { | |
| val (field, changeField) = savedInstanceState(saver = TextFieldValue.Saver) { TextFieldValue(text = initialText) } | |
| LaunchedEffect(subject = field.text) { |
| #!/bin/bash | |
| check_if_assets_empty() { | |
| release_id=$1 | |
| assets=$(curl -q https://api.github.com/repos/android/compose-samples/releases/$release_id/assets 2>/dev/null) | |
| [ ${#assets[@]} -eq 0 ] | |
| } | |
| ask() { | |
| read -ep "$1" answer |
| // Hide the keyboard on button click | |
| val imm = getSystemService(Context.INPUT_METHOD_SERVICE) as InputMethodManager | |
| imm.hideSoftInputFromWindow(view.windowToken, 0) | |
| // hide the menu item if doesn't resolve | |
| // getShareIntent() is supposed to return your intent object | |
| if (null == getShareIntent().resolveActivity(activity!!.packageManager)) { | |
| menu.findItem(R.id.share).setVisible(false) | |
| } |
| from pytorch_lightning import Callback | |
| from IPython.display import display, clear_output | |
| import copy | |
| import pandas as pd | |
| import torch | |
| from torch import nn | |
| import matplotlib.pyplot as plt | |
| import math | |
| imagenet_stats = ([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]) |
| lbl_dict = dict( | |
| n02086240= 'Shih-Tzu', | |
| n02087394= 'Rhodesian ridgeback', | |
| n02088364= 'Beagle', | |
| n02089973= 'English foxhound', | |
| n02093754= 'Australian terrier', | |
| n02096294= 'Border terrier', | |
| n02099601= 'Golden retriever', | |
| n02105641= 'Old English sheepdog', | |
| n02111889= 'Samoyed', |
| import torch | |
| from pytorch_lightning import Callback | |
| from IPython.display import display, clear_output | |
| import copy | |
| import pandas as pd | |
| def unwrap(x): | |
| if isinstance(x,torch.Tensor): | |
| return x.item() | |
| return x |
| #!/bin/bash | |
| if [ ! -e /content/models ]; then | |
| mkdir -p /root/.fastai/data | |
| ln -s /root/.cache/torch/checkpoints/ /content | |
| ln -s /root/.fastai/data /content | |
| rm -rf /content/sample_data/ | |
| mkdir /content/models | |
| fi | |
| echo Installing dependencies | |
| pip install -q feather-format kornia pyarrow wandb nbdev fastprogress --upgrade |
| /** | |
| * <input type="file" id="xmlFile" /> | |
| * include this tag in your html file | |
| * you can use the following xml file for testing | |
| * file URL: https://drive.google.com/file/d/1Ifef0RCqCq5apRT2LQbB6HguD43VpTXF/view?usp=sharing | |
| */ | |
| document.querySelector('#xmlFile').addEventListener('change', readFile, false); | |
| function readFile(e) { |