কলামের নিয়ম সেট করতে, শর্টহ্যান্ড কলাম-রুল বৈশিষ্ট্য ব্যবহার করুন, যা আপনাকে নিম্নলিখিত বৈশিষ্ট্যগুলি সেট করতে দেয় -
column-rule-width: set the width of the rule between columns column-rule-style: set the style of the rule between columns column-rule-color: set the rule of the rule between columns
কলাম নিয়মের মান −
হিসাবে সেট করা যেতে পারেcolumn-rule: column-rule-width column-rule-style column-rule-color|initial|inherit;
উদাহরণ
এখন আরেকটি উদাহরণ দেখা যাক -
<!DOCTYPE html>
<html>
<head>
<style>
.demo {
column-count: 5;
-webkit-column-count: 5; /* Chrome, Safari, Opera */
-moz-column-count: 5; /* Firefox */
-webkit-column-gap: normal; /* Chrome, Safari, Opera */
-moz-column-gap: normal; /* Firefox */
column-gap: normal;
-webkit-column-rule: 5px dotted orange; /* Chrome, Safari, Opera */
-moz-column-rule: 5px dotted orange; /* Firefox */
column-rule: 5px dotted orange;
}
</style>
</head>
<body>
<h1>PyTorch</h1>
<div class="demo">
PyTorch is defined as an open source machine learning library for Python. It is used for applications such as natural language processing. It is initially developed by Facebook artificial-intelligence research group, and Uber’s Pyro software for probabilistic programming which is built on it.
Originally, PyTorch was developed by Hugh Perkins as a Python wrapper for the LusJIT based on Torch framework. There are two PyTorch variants.
PyTorch redesigns and implements Torch in Python while sharing the same core C libraries for the backend code. PyTorch developers tuned this back-end code to run Python efficiently. They also kept the GPU based hardware acceleration as well as the extensibility features that made Lua-based Torch.
</div>
</body>
</html> আউটপুট
উদাহরণ
আসুন একটি উদাহরণ দেখি যেখানে আমরা উপরের সমস্ত বৈশিষ্ট্যগুলিকে শর্টহ্যান্ড প্রপার্টি কলাম-রুল হিসাবে ব্যবহার করছি -
<!DOCTYPE html>
<html>
<head>
<style>
.demo {
column-count: 4;
-webkit-column-count: 4; /* Chrome, Safari, Opera */
-moz-column-count: 4; /* Firefox */
-webkit-column-gap: normal; /* Chrome, Safari, Opera */
-moz-column-gap: normal; /* Firefox */
column-gap: normal;
-webkit-column-rule-width: 5px; /* Chrome, Safari, Opera */
-moz-column-rule-width: 5px; /* Firefox */
column-rule-width: 5px;
-webkit-column-rule-color: blue; /* Chrome, Safari, Opera */
-moz-column-rule-color: blue; /* Firefox */
column-rule-color: blue;
-webkit-column-rule-style: double; /* Chrome, Safari, Opera */
-moz-column-rule-style: double; /* Firefox */
column-rule-style: double;
}
</style>
</head>
<body>
<h1>PyTorch</h1>
<div class="demo">
PyTorch is defined as an open source machine learning library for Python. It is used for applications such as natural language processing. It is initially developed by Facebook artificial-intelligence research group, and Uber’s Pyro software for probabilistic programming which is built on it.
Originally, PyTorch was developed by Hugh Perkins as a Python wrapper for the LusJIT based on Torch framework. There are two PyTorch variants.
PyTorch redesigns and implements Torch in Python while sharing the same core C libraries for the backend code. PyTorch developers tuned this back-end code to run Python efficiently. They also kept the GPU based hardware acceleration as well as the extensibility features that made Lua-based Torch.
</div>
</body>
</html> আউটপুট
