goddoe

<!-- Ref: https://daily-dev-tips.com/posts/making-gradient-text-with-tailwind-css/ -->
<div class="grid place-items-center h-screen">
  <h1 class="text-8xl font-extrabold text-transparent bg-clip-text bg-gradient-to-r from-purple-400 to-pink-600">
    Tailwind CSS
  </h1>
</div>

goddoe

def find_all_span(d, s):
    span_list = []

    offset = -1
    while True:
        start_idx = d.find(s, offset + 1)

        if start_idx == -1:
            break

goddoe

from functools import partial
import pandas as pd
import numpy as np

def apply(df, func):
    return df.apply(func, axis=1)

def parallel_apply(df, func, n_cores):
    df_split = np.array_split(df, n_cores)
    pool = Pool(n_cores)

goddoe

def binary_search(arr, target):
    low, high = 0, len(arr) - 1
    while low <= high:
        mid = (low+high) // 2
        if arr[mid] > target:
            high = mid -1
        elif arr[mid] == target:
            return mid
        else:
            low = mid + 1

goddoe

model_path_list=($(ls -d ${model_ckpt_dir}/model_*))

goddoe

# for loop array
# Reference: https://www.tutorialkart.com/bash-shell-scripting/bash-append-an-array-to-another-array/
array=( one two three )
for i in "${array[@]}"
do
	echo "$i"
done

# append array
# Reference: https://www.tutorialkart.com/bash-shell-scripting/bash-append-an-array-to-another-array/

goddoe

forward_args = inspect.getfullargspec(self.model.forward).args[1:]
x = {k: v for k, vin self.transform(text) if k in forward_args}

goddoe

#!/bin/bash
# Reference: https://www.baeldung.com/linux/bash-parse-command-line-arguments

VALID_ARGS=$(getopt -o abg:d: --long alpha,beta,gamma:,delta: -- "$@")
if [[ $? -ne 0 ]]; then
    exit 1;
fi

eval set -- "$VALID_ARGS"
while [ : ]; do

goddoe

# Reference: https://stackoverflow.com/questions/3601515/how-to-check-if-a-variable-is-set-in-bash
if [ -z ${var+x} ]; then echo "var is unset"; else echo "var is set to '$var'"; fi

goddoe

import pandas as pd
import numpy as np

import torch
from transformers import GPTJForCausalLM, AutoTokenizer


###########################################################
# Load Model