') + ')', 'gi'); if (regex.test(text)) { found = true; var frag = document.createDocumentFragment(); var parts = text.split(regex); parts.forEach(function(part, i) { if (i % 2 === 0) { frag.appendChild(document.createTextNode(part)); } else { var span = document.createElement('span'); span.className = 'userscript-highlight'; span.textContent = part; frag.appendChild(span); } }); node.parentNode.replaceChild(frag, node); } }); } else if (node.nodeType === 1 && node.childNodes) { // element var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT']; if (!skipTags.includes(node.tagName)) { Array.from(node.childNodes).forEach(highlight); } } } highlight(document.body); // Re-highlight on dynamic content var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1 || node.nodeType === 3) highlight(node); }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ', 'i'); if (__m === '*' || __re.test(location.href)) { // Strip utm_, fbclid, gclid, etc. from all links on page (function() { var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content', 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid', 'ref', 'ref_src', 'source', 'medium', 'campaign']; function cleanUrl(url) { try { var u = new URL(url, window.location.origin); var changed = false; trackingParams.forEach(function(p) { if (u.searchParams.has(p)) { u.searchParams.delete(p); changed = true; } }); return changed ? u.toString() : url; } catch (e) { return url; } } function cleanLinks() { document.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } cleanLinks(); var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1) { if (node.tagName === 'A') cleanLinks(); node.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + ', 'i'); if (__m === '*' || __re.test(location.href)) { // Auto-enable theater mode on YouTube (function() { function tryTheater() { var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]'); if (btn && !btn.classList.contains('activated')) { btn.click(); } } // Try immediately tryTheater(); // Try after navigation (SPA) var lastUrl = location.href; setInterval(function() { if (location.href !== lastUrl) { lastUrl = location.href; setTimeout(tryTheater, 500); } }, 1000); // Also try on player load var observer = new MutationObserver(tryTheater); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ', 'i'); if (__m === '*' || __re.test(location.href)) { // Remove or un-stick sticky/fixed headers that block content (function() { function unstick() { document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) { if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') { el.style.position = 'static'; el.style.top = 'auto'; el.style.zIndex = 'auto'; } }); } unstick(); var observer = new MutationObserver(unstick); observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] }); })(); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); })(); Added Scaled Exponential Linear Unit Activation Function by AdarshAcharya5 · Pull Request #9027 · TheAlgorithms/Python · GitHub
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Added Scaled Exponential Linear Unit Activation Function - #9027

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tianyizheng02 merged 11 commits into
TheAlgorithms:masterfrom
AdarshAcharya5:feat/SELU_activation
Sep 6, 2023
Merged

Added Scaled Exponential Linear Unit Activation Function#9027
tianyizheng02 merged 11 commits into
TheAlgorithms:masterfrom
AdarshAcharya5:feat/SELU_activation

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@AdarshAcharya5

@AdarshAcharya5AdarshAcharya5 commented Sep 2, 2023

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Added Scaled Exponential Linear Unit Activation (SELU) Function under TheAlgorithms/Python/neural_network/activation_functions. Description of SELU taken from reference link provided in the top comment section in scaled_exponential_linear_unit.py
Fixes#9010

  • Add an algorithm?

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  • I have read CONTRIBUTING.md.
  • This pull request is all my own work -- I have not plagiarized.
  • I know that pull requests will not be merged if they fail the automated tests.
  • This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
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  • All filenames are in all lowercase characters with no spaces or dashes.
  • All functions and variable names follow Python naming conventions.
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  • All functions have doctests that pass the automated testing.
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  • If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

@algorithms-keeperalgorithms-keeperBot added the awaiting reviews This PR is ready to be reviewed label Sep 2, 2023
@algorithms-keeperalgorithms-keeperBot added the tests are failing Do not merge until tests pass label Sep 2, 2023
@algorithms-keeperalgorithms-keeperBot removed the tests are failing Do not merge until tests pass label Sep 5, 2023
@AdarshAcharya5

AdarshAcharya5 commented Sep 5, 2023

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@tianyizheng02 Thanks for your reply in the discussion section!. All checks passed now.

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tianyizheng02 reviewed Sep 6, 2023
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Comment threadneural_network/activation_functions/scaled_exponential_linear_unit.py Outdated


def scaled_exponential_linear_unit(
vector: np.ndarray, alpha: float = 1.6732, _lambda: float = 1.0507

@tianyizheng02tianyizheng02Sep 6, 2023

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Is there a reason why _lambda has an underscore? Is the user not meant to change this coefficient?

@AdarshAcharya5AdarshAcharya5Sep 6, 2023

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Yes, firstly lambda is a reserved keyword in python. Secondly both alpha and lambda are fixed constants.

@AdarshAcharya5AdarshAcharya5Sep 6, 2023

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The user can change these values, that may yield slightly different behaviour from the function, but the default values given to them are alpha: float = 1.6732, _lambda: float = 1.0507.

@tianyizheng02tianyizheng02Sep 6, 2023

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Yes, firstly lambda is a reserved keyword in python.

Oh yeah, duh 🤦

Could you rename the variable to something like lambda_ instead? Having an underscore at the start of a variable name generally signifies that the user isn't supposed to use it.

@AdarshAcharya5AdarshAcharya5Sep 6, 2023

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Ah. Yes for sure, I'll get it done right away!

@AdarshAcharya5AdarshAcharya5Sep 6, 2023

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Done

@tianyizheng02
tianyizheng02 merged commit 153c35e into TheAlgorithms:masterSep 6, 2023
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AdarshAcharya5 deleted the feat/SELU_activation branch September 10, 2023 03:51
@isidroasisidroas mentioned this pull request Jan 25, 2025
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Other Activation Functions

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