Bump lightning from 2.2.5 to 2.3.3 - #445

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Bump lightning from 2.2.5 to 2.3.3#445
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Bumps lightning from 2.2.5 to 2.3.3.

Release notes

Sourced from lightning's releases.

Patch release v2.3.3

This release removes the code from the main lightning package that was reported in CVE-2024-5980.

Patch release v2.3.2

Includes a minor bugfix that avoids a conflict with the entrypoint command with another package #20041.

Patch release v2.3.1

Includes minor bugfixes and stability improvements.

Full Changelog: Lightning-AI/pytorch-lightning@2.3.0...2.3.1

Lightning v2.3: Tensor Parallelism and 2D Parallelism

Lightning AI is excited to announce the release of Lightning 2.3 ⚡

Did you know? The Lightning philosophy extends beyond a boilerplate-free deep learning framework: We've been hard at work bringing you Lightning Studio. Code together, prototype, train, deploy, host AI web apps. All from your browser, with zero setup.

This release introduces experimental support for Tensor Parallelism and 2D Parallelism, PyTorch 2.3 support, and several bugfixes and stability improvements.

Highlights

Tensor Parallelism (beta)

Tensor parallelism (TP) is a technique that splits up the computation of selected layers across GPUs to save memory and speed up distributed models. To enable TP as well as other forms of parallelism, we introduce a ModelParallelStrategy for both Lightning Trainer and Fabric. Under the hood, TP is enabled through new experimental PyTorch APIs like DTensor and torch.distributed.tensor.parallel.

PyTorch Lightning

Enabling TP in a model with PyTorch Lightning requires you to implement the LightningModule.configure_model() method where you convert selected layers of a model to paralellized layers. This is an advanced feature, because it requires a deep understanding of the model architecture. Open the tutorial Studio to learn the basics of Tensor Parallelism.

... (truncated)

Commits

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Bump lightning from 2.2.5 to 2.3.3
5ba0452
Bumps [lightning](https://github.com/Lightning-AI/pytorch-lightning) from 2.2.5 to 2.3.3.
- [Release notes](https://github.com/Lightning-AI/pytorch-lightning/releases)
- [Commits](Lightning-AI/pytorch-lightning@2.2.5...2.3.3)
---
updated-dependencies:
- dependency-name: lightning
dependency-version: 2.3.3
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
Bump lightning from 2.2.5 to 2.3.3 - #445
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Bump lightning from 2.2.5 to 2.3.3#445
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Bumps lightning from 2.2.5 to 2.3.3.
Release notes
Sourced from lightning's releases.
Patch release v2.3.3
This release removes the code from the main lightning package that was reported in CVE-2024-5980.
Patch release v2.3.2
Includes a minor bugfix that avoids a conflict with the entrypoint command with another package #20041.
Patch release v2.3.1
Includes minor bugfixes and stability improvements.
Full Changelog: Lightning-AI/pytorch-lightning@2.3.0...2.3.1
Lightning v2.3: Tensor Parallelism and 2D Parallelism
Lightning AI is excited to announce the release of Lightning 2.3 ⚡
Did you know? The Lightning philosophy extends beyond a boilerplate-free deep learning framework: We've been hard at work bringing you Lightning Studio. Code together, prototype, train, deploy, host AI web apps. All from your browser, with zero setup.
This release introduces experimental support for Tensor Parallelism and 2D Parallelism, PyTorch 2.3 support, and several bugfixes and stability improvements.
Highlights
Tensor Parallelism (beta)
Tensor parallelism (TP) is a technique that splits up the computation of selected layers across GPUs to save memory and speed up distributed models. To enable TP as well as other forms of parallelism, we introduce a ModelParallelStrategy for both Lightning Trainer and Fabric. Under the hood, TP is enabled through new experimental PyTorch APIs like DTensor and torch.distributed.tensor.parallel.
PyTorch Lightning
Enabling TP in a model with PyTorch Lightning requires you to implement the LightningModule.configure_model() method where you convert selected layers of a model to paralellized layers. This is an advanced feature, because it requires a deep understanding of the model architecture. Open the tutorial Studio to learn the basics of Tensor Parallelism.
... (truncated)
Commits

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Bump lightning from 2.2.5 to 2.3.3
5ba0452
Bumps [lightning](https://github.com/Lightning-AI/pytorch-lightning) from 2.2.5 to 2.3.3.
- [Release notes](https://github.com/Lightning-AI/pytorch-lightning/releases)
- [Commits](Lightning-AI/pytorch-lightning@2.2.5...2.3.3)
---
updated-dependencies:
- dependency-name: lightning
dependency-version: 2.3.3
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Bump lightning from 2.2.5 to 2.3.3 - #445
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Bump lightning from 2.2.5 to 2.3.3#445
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Bumps lightning from 2.2.5 to 2.3.3.
Release notes
Sourced from lightning's releases.
Patch release v2.3.3
This release removes the code from the main lightning package that was reported in CVE-2024-5980.
Patch release v2.3.2
Includes a minor bugfix that avoids a conflict with the entrypoint command with another package #20041.
Patch release v2.3.1
Includes minor bugfixes and stability improvements.
Full Changelog: Lightning-AI/pytorch-lightning@2.3.0...2.3.1
Lightning v2.3: Tensor Parallelism and 2D Parallelism
Lightning AI is excited to announce the release of Lightning 2.3 ⚡
Did you know? The Lightning philosophy extends beyond a boilerplate-free deep learning framework: We've been hard at work bringing you Lightning Studio. Code together, prototype, train, deploy, host AI web apps. All from your browser, with zero setup.
This release introduces experimental support for Tensor Parallelism and 2D Parallelism, PyTorch 2.3 support, and several bugfixes and stability improvements.
Highlights
Tensor Parallelism (beta)
Tensor parallelism (TP) is a technique that splits up the computation of selected layers across GPUs to save memory and speed up distributed models. To enable TP as well as other forms of parallelism, we introduce a ModelParallelStrategy for both Lightning Trainer and Fabric. Under the hood, TP is enabled through new experimental PyTorch APIs like DTensor and torch.distributed.tensor.parallel.
PyTorch Lightning
Enabling TP in a model with PyTorch Lightning requires you to implement the LightningModule.configure_model() method where you convert selected layers of a model to paralellized layers. This is an advanced feature, because it requires a deep understanding of the model architecture. Open the tutorial Studio to learn the basics of Tensor Parallelism.
... (truncated)
Commits

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You can trigger Dependabot actions by commenting on this PR:
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  • @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
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Bump lightning from 2.2.5 to 2.3.3
5ba0452
Bumps [lightning](https://github.com/Lightning-AI/pytorch-lightning) from 2.2.5 to 2.3.3.
- [Release notes](https://github.com/Lightning-AI/pytorch-lightning/releases)
- [Commits](Lightning-AI/pytorch-lightning@2.2.5...2.3.3)
---
updated-dependencies:
- dependency-name: lightning
dependency-version: 2.3.3
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Bump lightning from 2.2.5 to 2.3.3 - #445
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Bump lightning from 2.2.5 to 2.3.3#445
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Bumps lightning from 2.2.5 to 2.3.3.
Release notes
Sourced from lightning's releases.
Patch release v2.3.3
This release removes the code from the main lightning package that was reported in CVE-2024-5980.
Patch release v2.3.2
Includes a minor bugfix that avoids a conflict with the entrypoint command with another package #20041.
Patch release v2.3.1
Includes minor bugfixes and stability improvements.
Full Changelog: Lightning-AI/pytorch-lightning@2.3.0...2.3.1
Lightning v2.3: Tensor Parallelism and 2D Parallelism
Lightning AI is excited to announce the release of Lightning 2.3 ⚡
Did you know? The Lightning philosophy extends beyond a boilerplate-free deep learning framework: We've been hard at work bringing you Lightning Studio. Code together, prototype, train, deploy, host AI web apps. All from your browser, with zero setup.
This release introduces experimental support for Tensor Parallelism and 2D Parallelism, PyTorch 2.3 support, and several bugfixes and stability improvements.
Highlights
Tensor Parallelism (beta)
Tensor parallelism (TP) is a technique that splits up the computation of selected layers across GPUs to save memory and speed up distributed models. To enable TP as well as other forms of parallelism, we introduce a ModelParallelStrategy for both Lightning Trainer and Fabric. Under the hood, TP is enabled through new experimental PyTorch APIs like DTensor and torch.distributed.tensor.parallel.
PyTorch Lightning
Enabling TP in a model with PyTorch Lightning requires you to implement the LightningModule.configure_model() method where you convert selected layers of a model to paralellized layers. This is an advanced feature, because it requires a deep understanding of the model architecture. Open the tutorial Studio to learn the basics of Tensor Parallelism.
... (truncated)
Commits

Dependabot compatibility score
Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.
Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR:
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  • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
  • @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
  • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
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Bump lightning from 2.2.5 to 2.3.3
5ba0452
Bumps [lightning](https://github.com/Lightning-AI/pytorch-lightning) from 2.2.5 to 2.3.3.
- [Release notes](https://github.com/Lightning-AI/pytorch-lightning/releases)
- [Commits](Lightning-AI/pytorch-lightning@2.2.5...2.3.3)
---
updated-dependencies:
- dependency-name: lightning
dependency-version: 2.3.3
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
@dependabotdependabotBot
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
Bump lightning from 2.2.5 to 2.3.3 - #445
Open
dependabot[bot] wants to merge 1 commit into
masterfrom 
dependabot/pip/lightning-2.3.3
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Bump lightning from 2.2.5 to 2.3.3#445
dependabot[bot] wants to merge 1 commit into
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Bumps lightning from 2.2.5 to 2.3.3.
Release notes
Sourced from lightning's releases.
Patch release v2.3.3
This release removes the code from the main lightning package that was reported in CVE-2024-5980.
Patch release v2.3.2
Includes a minor bugfix that avoids a conflict with the entrypoint command with another package #20041.
Patch release v2.3.1
Includes minor bugfixes and stability improvements.
Full Changelog: Lightning-AI/pytorch-lightning@2.3.0...2.3.1
Lightning v2.3: Tensor Parallelism and 2D Parallelism
Lightning AI is excited to announce the release of Lightning 2.3 ⚡
Did you know? The Lightning philosophy extends beyond a boilerplate-free deep learning framework: We've been hard at work bringing you Lightning Studio. Code together, prototype, train, deploy, host AI web apps. All from your browser, with zero setup.
This release introduces experimental support for Tensor Parallelism and 2D Parallelism, PyTorch 2.3 support, and several bugfixes and stability improvements.
Highlights
Tensor Parallelism (beta)
Tensor parallelism (TP) is a technique that splits up the computation of selected layers across GPUs to save memory and speed up distributed models. To enable TP as well as other forms of parallelism, we introduce a ModelParallelStrategy for both Lightning Trainer and Fabric. Under the hood, TP is enabled through new experimental PyTorch APIs like DTensor and torch.distributed.tensor.parallel.
PyTorch Lightning
Enabling TP in a model with PyTorch Lightning requires you to implement the LightningModule.configure_model() method where you convert selected layers of a model to paralellized layers. This is an advanced feature, because it requires a deep understanding of the model architecture. Open the tutorial Studio to learn the basics of Tensor Parallelism.
... (truncated)
Commits

Dependabot compatibility score
Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.
Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR:
  • @dependabot rebase will rebase this PR
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  • @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
  • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
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You can disable automated security fix PRs for this repo from the Security Alerts page.
@dependabot
Bump lightning from 2.2.5 to 2.3.3
5ba0452
Bumps [lightning](https://github.com/Lightning-AI/pytorch-lightning) from 2.2.5 to 2.3.3.
- [Release notes](https://github.com/Lightning-AI/pytorch-lightning/releases)
- [Commits](Lightning-AI/pytorch-lightning@2.2.5...2.3.3)
---
updated-dependencies:
- dependency-name: lightning
dependency-version: 2.3.3
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
@dependabotdependabotBot
added

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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Bump lightning from 2.2.5 to 2.3.3 - #445
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dependabot/pip/lightning-2.3.3
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Bump lightning from 2.2.5 to 2.3.3#445
dependabot[bot] wants to merge 1 commit into
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dependabot/pip/lightning-2.3.3
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Bumps lightning from 2.2.5 to 2.3.3.
Release notes
Sourced from lightning's releases.
Patch release v2.3.3
This release removes the code from the main lightning package that was reported in CVE-2024-5980.
Patch release v2.3.2
Includes a minor bugfix that avoids a conflict with the entrypoint command with another package #20041.
Patch release v2.3.1
Includes minor bugfixes and stability improvements.
Full Changelog: Lightning-AI/pytorch-lightning@2.3.0...2.3.1
Lightning v2.3: Tensor Parallelism and 2D Parallelism
Lightning AI is excited to announce the release of Lightning 2.3 ⚡
Did you know? The Lightning philosophy extends beyond a boilerplate-free deep learning framework: We've been hard at work bringing you Lightning Studio. Code together, prototype, train, deploy, host AI web apps. All from your browser, with zero setup.
This release introduces experimental support for Tensor Parallelism and 2D Parallelism, PyTorch 2.3 support, and several bugfixes and stability improvements.
Highlights
Tensor Parallelism (beta)
Tensor parallelism (TP) is a technique that splits up the computation of selected layers across GPUs to save memory and speed up distributed models. To enable TP as well as other forms of parallelism, we introduce a ModelParallelStrategy for both Lightning Trainer and Fabric. Under the hood, TP is enabled through new experimental PyTorch APIs like DTensor and torch.distributed.tensor.parallel.
PyTorch Lightning
Enabling TP in a model with PyTorch Lightning requires you to implement the LightningModule.configure_model() method where you convert selected layers of a model to paralellized layers. This is an advanced feature, because it requires a deep understanding of the model architecture. Open the tutorial Studio to learn the basics of Tensor Parallelism.
... (truncated)
Commits

Dependabot compatibility score
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Bump lightning from 2.2.5 to 2.3.3
5ba0452
Bumps [lightning](https://github.com/Lightning-AI/pytorch-lightning) from 2.2.5 to 2.3.3.
- [Release notes](https://github.com/Lightning-AI/pytorch-lightning/releases)
- [Commits](Lightning-AI/pytorch-lightning@2.2.5...2.3.3)
---
updated-dependencies:
- dependency-name: lightning
dependency-version: 2.3.3
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
@dependabotdependabotBot
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Jun 10, 2026
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Bump lightning from 2.2.5 to 2.3.3 - #445
Open
dependabot[bot] wants to merge 1 commit into
masterfrom 
dependabot/pip/lightning-2.3.3
Open
Bump lightning from 2.2.5 to 2.3.3#445
dependabot[bot] wants to merge 1 commit into
masterfrom 
dependabot/pip/lightning-2.3.3
Conversation
@dependabot
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Bumps lightning from 2.2.5 to 2.3.3.
Release notes
Sourced from lightning's releases.
Patch release v2.3.3
This release removes the code from the main lightning package that was reported in CVE-2024-5980.
Patch release v2.3.2
Includes a minor bugfix that avoids a conflict with the entrypoint command with another package #20041.
Patch release v2.3.1
Includes minor bugfixes and stability improvements.
Full Changelog: Lightning-AI/pytorch-lightning@2.3.0...2.3.1
Lightning v2.3: Tensor Parallelism and 2D Parallelism
Lightning AI is excited to announce the release of Lightning 2.3 ⚡
Did you know? The Lightning philosophy extends beyond a boilerplate-free deep learning framework: We've been hard at work bringing you Lightning Studio. Code together, prototype, train, deploy, host AI web apps. All from your browser, with zero setup.
This release introduces experimental support for Tensor Parallelism and 2D Parallelism, PyTorch 2.3 support, and several bugfixes and stability improvements.
Highlights
Tensor Parallelism (beta)
Tensor parallelism (TP) is a technique that splits up the computation of selected layers across GPUs to save memory and speed up distributed models. To enable TP as well as other forms of parallelism, we introduce a ModelParallelStrategy for both Lightning Trainer and Fabric. Under the hood, TP is enabled through new experimental PyTorch APIs like DTensor and torch.distributed.tensor.parallel.
PyTorch Lightning
Enabling TP in a model with PyTorch Lightning requires you to implement the LightningModule.configure_model() method where you convert selected layers of a model to paralellized layers. This is an advanced feature, because it requires a deep understanding of the model architecture. Open the tutorial Studio to learn the basics of Tensor Parallelism.
... (truncated)
Commits

Dependabot compatibility score
Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.
Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR:
  • @dependabot rebase will rebase this PR
  • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
  • @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
  • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    
You can disable automated security fix PRs for this repo from the Security Alerts page.
@dependabot
Bump lightning from 2.2.5 to 2.3.3
5ba0452
Bumps [lightning](https://github.com/Lightning-AI/pytorch-lightning) from 2.2.5 to 2.3.3.
- [Release notes](https://github.com/Lightning-AI/pytorch-lightning/releases)
- [Commits](Lightning-AI/pytorch-lightning@2.2.5...2.3.3)
---
updated-dependencies:
- dependency-name: lightning
dependency-version: 2.3.3
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
@dependabotdependabotBot
added

dependencies
Pull requests that update a dependency file
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Pull requests that update python code
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Jun 10, 2026
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

Skip to content
Bump lightning from 2.2.5 to 2.3.3 - #445
Open
dependabot[bot] wants to merge 1 commit into
masterfrom 
dependabot/pip/lightning-2.3.3
Open
Bump lightning from 2.2.5 to 2.3.3#445
dependabot[bot] wants to merge 1 commit into
masterfrom 
dependabot/pip/lightning-2.3.3
Conversation
@dependabot
@dependabotdependabotBot
commented
on behalf of githubJun 10, 2026

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Bumps lightning from 2.2.5 to 2.3.3.
Release notes
Sourced from lightning's releases.
Patch release v2.3.3
This release removes the code from the main lightning package that was reported in CVE-2024-5980.
Patch release v2.3.2
Includes a minor bugfix that avoids a conflict with the entrypoint command with another package #20041.
Patch release v2.3.1
Includes minor bugfixes and stability improvements.
Full Changelog: Lightning-AI/pytorch-lightning@2.3.0...2.3.1
Lightning v2.3: Tensor Parallelism and 2D Parallelism
Lightning AI is excited to announce the release of Lightning 2.3 ⚡
Did you know? The Lightning philosophy extends beyond a boilerplate-free deep learning framework: We've been hard at work bringing you Lightning Studio. Code together, prototype, train, deploy, host AI web apps. All from your browser, with zero setup.
This release introduces experimental support for Tensor Parallelism and 2D Parallelism, PyTorch 2.3 support, and several bugfixes and stability improvements.
Highlights
Tensor Parallelism (beta)
Tensor parallelism (TP) is a technique that splits up the computation of selected layers across GPUs to save memory and speed up distributed models. To enable TP as well as other forms of parallelism, we introduce a ModelParallelStrategy for both Lightning Trainer and Fabric. Under the hood, TP is enabled through new experimental PyTorch APIs like DTensor and torch.distributed.tensor.parallel.
PyTorch Lightning
Enabling TP in a model with PyTorch Lightning requires you to implement the LightningModule.configure_model() method where you convert selected layers of a model to paralellized layers. This is an advanced feature, because it requires a deep understanding of the model architecture. Open the tutorial Studio to learn the basics of Tensor Parallelism.
... (truncated)
Commits

Dependabot compatibility score
Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.
Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR:
  • @dependabot rebase will rebase this PR
  • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
  • @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
  • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    
You can disable automated security fix PRs for this repo from the Security Alerts page.
@dependabot
Bump lightning from 2.2.5 to 2.3.3
5ba0452
Bumps [lightning](https://github.com/Lightning-AI/pytorch-lightning) from 2.2.5 to 2.3.3.
- [Release notes](https://github.com/Lightning-AI/pytorch-lightning/releases)
- [Commits](Lightning-AI/pytorch-lightning@2.2.5...2.3.3)
---
updated-dependencies:
- dependency-name: lightning
dependency-version: 2.3.3
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
@dependabotdependabotBot
added

dependencies
Pull requests that update a dependency file
python
Pull requests that update python code
labels
Jun 10, 2026
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