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kernels-benchmarks / causal_conv1d /impls /hf_kernels_causal_conv1d.html
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<title>hf_kernels_causal_conv1d</title>
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white-space: pre;
/* keep line breaks, NO wrapping */
display: inline-block;
/* shrink-to-content */
min-width: max-content;
/* allow very long lines to define intrinsic width */
font-family: ui-monospace, SFMono-Regular, Menlo, Consolas, monospace;
tab-size: 2;
}
.cell-stderr {
background: var(--bg-error);
border-left: 2px solid var(--border-error);
padding: 1rem;
margin: 0.5rem 0;
font-family: inherit;
font-size: 0.9rem;
color: var(--text-error);
white-space: pre-wrap;
}
.uv-install-logs {
margin: 0.5rem 0;
}
.uv-logs-header {
cursor: pointer;
padding: 0.75rem;
border-left: 3px solid var(--border-color);
font-family: inherit;
font-size: 0.85rem;
color: var(--text-secondary);
user-select: none;
}
.uv-logs-content {
background: var(--bg-secondary);
padding: 1rem;
border-left: 3px solid var(--border-color);
white-space: pre-wrap;
font-family: monospace;
font-size: 0.85rem;
color: var(--text-secondary);
overflow-x: auto;
}
.cell-artifacts {
margin: 1rem 0;
}
.cell-artifacts h4 {
margin: 0 0 0.5rem 0;
color: var(--text-secondary);
font-size: 0.9rem;
}
.artifact {
display: inline-block;
background: var(--bg-artifact);
padding: 0.25rem 0.5rem;
border-radius: 1px;
margin: 0.25rem 0.5rem 0.25rem 0;
font-family: inherit;
font-size: 0.8rem;
color: var(--text-link);
text-decoration: none;
transition: background-color 0.2s ease;
border: 1px solid var(--border-primary);
}
.artifact:hover {
background: var(--bg-artifact-hover);
}
.artifact-preview {
margin-top: 1rem;
}
.artifact-preview img {
max-width: 100%;
height: auto;
border: 1px solid var(--border-primary);
border-radius: 1px;
}
.artifact-preview svg {
max-width: 100%;
height: auto;
border: 1px solid var(--border-primary);
border-radius: 1px;
display: block;
}
/* Style SVG text elements */
.artifact-preview svg g {
fill: var(--text-primary) !important;
}
/* Auto-theme SVG elements */
.artifact-preview svg {
background: transparent;
}
/* Invert SVG images in dark mode */
:root[data-theme="dark"] .artifact-preview img[src$=".svg"] {
filter: invert(0.9) hue-rotate(180deg);
}
/* Keep SVG images readable in monocolor mode */
:root[data-ui="monocolor"] .artifact-preview img[src$=".svg"] {
filter: none;
}
/* CSV table styling */
.artifact-csv {
margin-top: 1rem;
overflow-x: auto;
}
.csv-table {
width: 100%;
border-collapse: collapse;
font-size: 0.9rem;
background: var(--bg-secondary);
border: 1px solid var(--border-primary);
border-radius: 1px;
}
.csv-table th,
.csv-table td {
padding: 0.5rem 0.75rem;
text-align: left;
border: 1px solid var(--border-primary);
}
.csv-table th {
background: var(--bg-tertiary);
font-weight: 600;
color: var(--text-primary);
}
.csv-table tbody tr:hover {
background: var(--bg-artifact-hover);
}
.artifact-csv-error {
margin-top: 1rem;
padding: 1rem;
background: var(--bg-error);
color: var(--text-error);
border: 1px solid var(--border-error);
border-radius: 1px;
}
.cell-failed {
border-color: var(--border-cell-failed);
}
.cell-failed .cell-header {
background: var(--bg-error);
color: var(--text-error);
}
.cell-commented {
opacity: 0.6;
border-style: dashed;
}
.cell-commented .cell-header {
background: var(--bg-secondary);
color: var(--text-secondary);
font-style: italic;
}
.run-btn {
background: var(--bg-tertiary);
border: 1px solid var(--border-primary);
padding: 2px 6px;
border-radius: 2px;
color: var(--text-secondary);
cursor: pointer;
font-size: 0.75em;
font-family: inherit;
margin-left: 4px;
}
.run-btn:hover {
color: var(--text-primary);
background: var(--bg-primary);
}
.run-btn:disabled {
opacity: 0.6;
cursor: not-allowed;
}
.copy-btn {
background: var(--bg-tertiary);
border: 1px solid var(--border-primary);
padding: 2px 6px;
border-radius: 2px;
color: var(--text-secondary);
cursor: pointer;
font-size: 0.75em;
font-family: inherit;
margin-left: 4px;
}
.copy-btn:hover {
color: var(--text-primary);
background: var(--bg-primary);
}
.copy-btn:disabled {
opacity: 0.6;
cursor: not-allowed;
}
.copy-btn.copied {
color: #4caf50;
background: var(--bg-primary);
border-color: #4caf50;
transition: all 0.2s ease;
}
.raw-btn {
background: var(--bg-tertiary);
border: 1px solid var(--border-primary);
padding: 2px 6px;
border-radius: 2px;
color: var(--text-secondary);
cursor: pointer;
font-size: 0.75em;
font-family: inherit;
margin-left: 4px;
text-decoration: none;
display: inline-block;
}
.raw-btn:hover {
color: var(--text-primary);
background: var(--bg-primary);
text-decoration: none;
}
.github-btn {
background: var(--bg-tertiary);
border: 1px solid var(--border-primary);
padding: 2px 6px;
border-radius: 2px;
color: var(--text-secondary);
cursor: pointer;
font-size: 0.75em;
font-family: inherit;
margin-left: 4px;
text-decoration: none;
display: inline-block;
}
.github-btn:hover {
color: var(--text-primary);
background: var(--bg-primary);
text-decoration: none;
}
.hf-btn {
background: var(--bg-tertiary);
border: 1px solid var(--border-primary);
padding: 2px 6px;
border-radius: 2px;
color: var(--text-secondary);
cursor: pointer;
font-size: 0.75em;
font-family: inherit;
margin-left: 4px;
text-decoration: none;
display: inline-block;
}
.hf-btn:hover {
color: var(--text-primary);
background: var(--bg-primary);
text-decoration: none;
}
.output-stale {
opacity: 0.5;
position: relative;
}
.output-stale::after {
content: '⏳ updating...';
position: absolute;
top: 8px;
right: 8px;
background: var(--bg-secondary);
padding: 4px 8px;
border-radius: 2px;
font-size: 0.75em;
color: var(--text-secondary);
border: 1px solid var(--border-primary);
}
h1,
h2,
h3,
h4,
h5,
h6 {
margin-top: 1.5rem;
margin-bottom: 0.75rem;
color: var(--text-primary);
}
h1 {
margin-top: 0;
margin-bottom: 1rem;
}
p {
margin: 0.75rem 0;
color: var(--text-primary);
}
a {
color: var(--text-link);
}
img {
max-width: 100%;
height: auto;
border-radius: 1px;
box-shadow: none;
}
pre,
code {
font-family: 'Cascadia Mono', 'Cascadia Code', 'JetBrains Mono', 'SF Mono', Monaco, 'Consolas', monospace;
font-size: var(--code-font-size);
}
.code-wrap {
position: relative;
}
.code-line-highlight {
display: none;
position: absolute;
left: 0;
right: 0;
height: 1.5em;
background: rgba(255, 235, 170, 0.35);
pointer-events: none;
border-left: 3px solid #f4c542;
}
.line-number {
cursor: pointer;
text-decoration: none;
color: var(--text-secondary);
padding: 0 0.25rem;
}
.line-number.selected {
background: rgba(255, 235, 170, 0.4);
color: var(--text-primary);
}
/* Line numbers */
.highlight-with-lines {
display: flex;
}
.line-numbers {
background: var(--bg-tertiary);
padding: var(--code-pad-y) 0.5rem;
font-family: 'Cascadia Mono', 'Cascadia Code', 'JetBrains Mono', 'SF Mono', Monaco, 'Consolas', monospace;
font-size: var(--code-font-size);
line-height: var(--code-line-height);
color: var(--text-secondary);
user-select: none;
text-align: right;
border-right: 1px solid var(--border-primary);
}
.line-numbers .line-number {
display: block;
line-height: var(--code-line-height);
}
.highlight-with-lines .highlight {
flex: 1;
}
.highlight .hll {
background-color: transparent;
}
/* don't conflict with our highlight */
.highlight pre {
white-space: pre;
margin: 0;
padding: var(--code-pad-y) 0.75rem;
line-height: var(--code-line-height);
}
/* Collapsed code styling */
.cell-code.collapsed {
display: none;
}
.cell-code.expanded {
display: block;
}
{
% if config.collapse_code %
}
.cell-code {
display: none;
}
{
% else %
}
.cell-code {
display: block;
border-bottom: 1px solid var(--border-primary);
}
{
% endif %
}
{
{
pygments_css
}
}
/* Ensure our code metrics override Pygments defaults */
.highlight pre {
white-space: pre;
margin: 0;
padding: var(--code-pad-y) 0.75rem !important;
line-height: var(--code-line-height) !important;
font-size: var(--code-font-size) !important;
font-family: 'Cascadia Mono', 'Cascadia Code', 'JetBrains Mono', 'SF Mono', Monaco, 'Consolas', monospace !important;
border: none;
}
.line-numbers {
line-height: var(--code-line-height) !important;
}
.line-numbers .line-number {
line-height: var(--code-line-height) !important;
}
/* Custom CSS from frontmatter */
{
{
config.custom_css
}
}
{
# Override code font size from frontmatter (accept number as px) #
}
{
% if config.code_font_size is not none %
}
{
% if config.code_font_size is string %
}
:root {
--code-font-size: {
{
config.code_font_size
}
}
;
}
{
% else %
}
:root {
--code-font-size: {
{
config.code_font_size
}
}
px;
}
{
% endif %
}
{
% endif %
}
/* Cursor for tools */
body[data-tool="arrow"] .main-content {
cursor: url('data:image/svg+xml;utf8,<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="%23e53935" stroke-width="2"><path d="M12 19l7-7 3 3-7 7-3-3z"/><path d="M18 13l-1.5-7.5L2 2l3.5 14.5L13 18l5-5z"/><path d="M2 2l7.586 7.586"/><circle cx="11" cy="11" r="2"/></svg>') 12 12, crosshair;
}
body[data-tool="pen"] .main-content {
cursor: url('data:image/svg+xml;utf8,<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="%23e53935" stroke-width="2"><path d="M12 19l7-7 3 3-7 7-3-3z"/><path d="M18 13l-1.5-7.5L2 2l3.5 14.5L13 18l5-5z"/><circle cx="4" cy="20" r="2" fill="%23e53935"/></svg>') 4 20, pointer;
}
body[data-tool="eraser"] .main-content {
cursor: url('data:image/svg+xml;utf8,<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="%23e53935" stroke-width="2"><path d="M20 20H7l-7-7 7-7h13v14z"/><path d="M13 13l7-7"/><path d="M13 13L9 9"/></svg>') 12 12, auto;
}
/* Color picker styles */
.tools-section-title {
font-weight: bold;
color: var(--text-secondary);
font-size: 0.65rem;
margin: 0.75rem 0 0.5rem 0;
text-transform: uppercase;
letter-spacing: 0.5px;
}
.color-row {
display: grid;
grid-template-columns: repeat(6, 1fr);
gap: 0.25rem;
margin-bottom: 0.5rem;
}
.color-swatch {
width: 18px;
height: 18px;
border: 2px solid var(--border-primary);
border-radius: 3px;
cursor: pointer;
transition: all 0.2s ease;
position: relative;
}
.color-swatch:hover {
transform: scale(1.1);
border-color: var(--text-secondary);
}
.color-swatch.selected {
border-color: var(--text-primary);
box-shadow: 0 0 0 2px var(--text-link);
}
.color-swatch.selected::after {
content: '✓';
position: absolute;
top: 50%;
left: 50%;
transform: translate(-50%, -50%);
color: white;
font-size: 10px;
font-weight: bold;
text-shadow: 1px 1px 1px black;
}
.color-input {
width: 24px;
height: 24px;
border: 2px solid var(--border-primary);
border-radius: 3px;
cursor: pointer;
background: none;
padding: 0;
grid-column: span 2;
justify-self: center;
}
.color-input:hover {
border-color: var(--text-secondary);
}
/* Thickness slider styles */
.thickness-row {
display: flex;
align-items: center;
gap: 0.5rem;
margin-top: 0.75rem;
}
.thickness-slider {
flex: 1;
-webkit-appearance: none;
appearance: none;
height: 4px;
background: var(--border-primary);
border-radius: 2px;
outline: none;
opacity: 0.7;
transition: opacity 0.2s;
}
.thickness-slider:hover {
opacity: 1;
}
.thickness-slider::-webkit-slider-thumb {
-webkit-appearance: none;
appearance: none;
width: 12px;
height: 12px;
background: var(--text-link);
border-radius: 50%;
cursor: pointer;
}
.thickness-slider::-moz-range-thumb {
width: 12px;
height: 12px;
background: var(--text-link);
border-radius: 50%;
cursor: pointer;
border: none;
}
.thickness-value {
font-size: 0.7rem;
color: var(--text-secondary);
min-width: 20px;
text-align: right;
}
.highlight {
background: none !important;
}
/* Loading animations */
.loading-spinner {
display: inline-block;
width: 16px;
height: 16px;
border: 2px solid var(--border-primary);
border-radius: 50%;
border-top-color: var(--text-link);
animation: spin 1s linear infinite;
margin-right: 8px;
vertical-align: middle;
}
@keyframes spin {
to {
transform: rotate(360deg);
}
}
.loading-skeleton {
display: inline-block;
background: var(--bg-tertiary);
background: linear-gradient(90deg,
var(--bg-tertiary) 25%,
var(--bg-secondary) 50%,
var(--bg-tertiary) 75%);
background-size: 200% 100%;
animation: loading-shimmer 2s ease-in-out infinite;
border-radius: 2px;
height: 1em;
width: 80px;
vertical-align: middle;
}
@keyframes loading-shimmer {
0% {
background-position: -200% 0;
}
100% {
background-position: 200% 0;
}
}
/* Loading state for cell output */
.cell-output:has(.loading-spinner) {
opacity: 0.7;
background: var(--bg-secondary);
/* border-left: 3px solid var(--text-link); */
}
</style>
<script>
// --- Drag utilities ---
function clamp(val, min, max) { return Math.max(min, Math.min(max, val)); }
function restorePosition(el, storageKey) {
try {
const raw = localStorage.getItem(storageKey);
if (!raw) return;
const pos = JSON.parse(raw);
if (typeof pos.left === 'number' && typeof pos.top === 'number') {
el.style.left = pos.left + 'px';
el.style.top = pos.top + 'px';
el.style.right = 'auto';
el.style.bottom = 'auto';
}
} catch (_) {}
}
function savePosition(el, storageKey) {
try {
const left = parseFloat(el.style.left || 'NaN');
const top = parseFloat(el.style.top || 'NaN');
if (!Number.isNaN(left) && !Number.isNaN(top)) {
localStorage.setItem(storageKey, JSON.stringify({ left, top }));
}
} catch (_) {}
}
function makeDraggable(el, storageKey, handleEl) {
let dragging = false;
let startX = 0, startY = 0; // cursor
let origLeft = 0, origTop = 0; // element
const onMove = (e) => {
if (!dragging) return;
const clientX = e.touches ? e.touches[0].clientX : e.clientX;
const clientY = e.touches ? e.touches[0].clientY : e.clientY;
const dx = clientX - startX;
const dy = clientY - startY;
const w = el.offsetWidth;
const h = el.offsetHeight;
const maxX = window.innerWidth - w;
const maxY = window.innerHeight - h;
const newLeft = clamp(origLeft + dx, 0, maxX);
const newTop = clamp(origTop + dy, 0, maxY);
el.style.left = newLeft + 'px';
el.style.top = newTop + 'px';
el.style.right = 'auto';
el.style.bottom = 'auto';
};
const endDrag = () => {
if (!dragging) return;
dragging = false;
document.removeEventListener('mousemove', onMove);
document.removeEventListener('mouseup', endDrag);
document.removeEventListener('touchmove', onMove);
document.removeEventListener('touchend', endDrag);
handleEl && (handleEl.style.cursor = 'grab');
savePosition(el, storageKey);
// ensure no-overlap constraint after a drag
try { layoutWidgetsStackedBottomRight(); } catch (_) {}
};
const startDrag = (e) => {
// Start from element's current on-screen rect
const elRect = el.getBoundingClientRect();
el.style.left = elRect.left + 'px';
el.style.top = elRect.top + 'px';
el.style.right = 'auto';
el.style.bottom = 'auto';
dragging = true;
startX = e.touches ? e.touches[0].clientX : e.clientX;
startY = e.touches ? e.touches[0].clientY : e.clientY;
origLeft = elRect.left;
origTop = elRect.top;
document.addEventListener('mousemove', onMove);
document.addEventListener('mouseup', endDrag);
document.addEventListener('touchmove', onMove, { passive: false });
document.addEventListener('touchend', endDrag);
handleEl && (handleEl.style.cursor = 'grabbing');
e.preventDefault();
};
(handleEl || el).addEventListener('mousedown', startDrag);
(handleEl || el).addEventListener('touchstart', startDrag, { passive: false });
// Apply any saved position on init
restorePosition(el, storageKey);
}
function toggleCell(cellId) {
const codeElement = document.getElementById('code-' + cellId);
const outputElement = document.getElementById('output-' + cellId);
if (codeElement) {
codeElement.classList.toggle('collapsed');
}
if (outputElement) {
outputElement.classList.toggle('collapsed');
}
updateIndicators(cellId);
encodeToolStateToUrl();
}
function toggleCode(cellId) {
const codeElement = document.getElementById('code-' + cellId);
if (codeElement) {
codeElement.classList.toggle('collapsed');
updateIndicators(cellId);
encodeToolStateToUrl();
}
}
function toggleOutput(cellId) {
const outputElement = document.getElementById('output-' + cellId);
if (outputElement) {
outputElement.classList.toggle('collapsed');
updateIndicators(cellId);
encodeToolStateToUrl();
}
}
function toggleUvLogs(headerElement) {
const contentElement = headerElement.nextElementSibling;
if (contentElement) {
const isCollapsed = contentElement.style.display === 'none';
contentElement.style.display = isCollapsed ? 'block' : 'none';
headerElement.textContent = isCollapsed ? '▼ UV Install Logs' : '▶ UV Install Logs';
// Update the header indicator if it exists
const uvLogsDiv = headerElement.parentElement;
if (uvLogsDiv && uvLogsDiv.id && uvLogsDiv.id.startsWith('uv-logs-')) {
const cellId = uvLogsDiv.id.replace('uv-logs-', '');
const indicatorElement = document.getElementById('uv-indicator-' + cellId);
if (indicatorElement) {
indicatorElement.textContent = isCollapsed ? '▼ uv-logs' : '▶ uv-logs';
}
}
}
}
function toggleUvLogsFromHeader(cellId) {
const uvLogsElement = document.getElementById('uv-logs-' + cellId);
const indicatorElement = document.getElementById('uv-indicator-' + cellId);
if (uvLogsElement) {
const headerElement = uvLogsElement.querySelector('.uv-logs-header');
const contentElement = uvLogsElement.querySelector('.uv-logs-content');
if (contentElement && headerElement) {
const isCollapsed = contentElement.style.display === 'none';
contentElement.style.display = isCollapsed ? 'block' : 'none';
headerElement.textContent = isCollapsed ? '▼ UV Install Logs' : '▶ UV Install Logs';
if (indicatorElement) {
indicatorElement.textContent = isCollapsed ? '▼ uv-logs' : '▶ uv-logs';
}
}
}
}
function updateIndicators(cellId) {
const codeElement = document.getElementById('code-' + cellId);
const outputElement = document.getElementById('output-' + cellId);
const indicators = document.querySelector(`[onclick*="${cellId}"]`)?.closest('.cell-header')?.querySelector('.collapse-indicators');
if (indicators) {
const codeCollapsed = codeElement && codeElement.classList.contains('collapsed');
const outputCollapsed = outputElement && outputElement.classList.contains('collapsed');
const codeIcon = codeCollapsed ? '▶' : '▼';
const outputIcon = outputCollapsed ? '▶' : '▼';
const codeSpan = indicators.querySelector('[onclick*="toggleCode"]');
const outputSpan = indicators.querySelector('[onclick*="toggleOutput"]');
if (codeSpan) codeSpan.innerHTML = `${codeIcon} code`;
if (outputSpan) outputSpan.innerHTML = `${outputIcon} output`;
}
}
function toggleTheme() {
const html = document.documentElement;
const currentTheme = html.getAttribute('data-theme');
const newTheme = currentTheme === 'dark' ? 'light' : 'dark';
html.setAttribute('data-theme', newTheme);
localStorage.setItem('uvnote-theme', newTheme);
updateThemeIcon();
updateUiDebug();
}
// Two panel code removed
function updateThemeIcon() {
const theme = document.documentElement.getAttribute('data-theme');
const toggle = document.querySelector('.theme-toggle');
if (toggle) {
toggle.textContent = theme === 'dark' ? 'light' : 'dark';
}
}
function setUiTheme(newUi) {
if (newUi !== 'default' && newUi !== 'none' && newUi !== 'monocolor') return;
const html = document.documentElement;
html.setAttribute('data-ui', newUi);
try { localStorage.setItem('uvnote-ui', newUi); } catch (_) {}
updateUiMenu();
updateUiDebug();
}
function updateUiMenu() {
const ui = document.documentElement.getAttribute('data-ui') || 'default';
const checks = {
default: document.getElementById('checkbox-ui-default'),
none: document.getElementById('checkbox-ui-none'),
monocolor: document.getElementById('checkbox-ui-monocolor')
};
if (checks.default) checks.default.textContent = ui === 'default' ? '☑' : '☐';
if (checks.none) checks.none.textContent = ui === 'none' ? '☑' : '☐';
if (checks.monocolor) checks.monocolor.textContent = ui === 'monocolor' ? '☑' : '☐';
}
function updateUiDebug() {
const ui = document.documentElement.getAttribute('data-ui') || 'default';
const color = document.documentElement.getAttribute('data-theme') || 'light';
const el = document.getElementById('ui-debug');
if (el) {
el.textContent = `UI: ${ui} | Color: ${color}`;
}
}
// Line selection and deep-linking
function clearLineSelections() {
try {
document.querySelectorAll('.code-line-highlight').forEach(el => { el.style.display = 'none'; });
document.querySelectorAll('.line-number.selected').forEach(el => el.classList.remove('selected'));
} catch (_) {}
}
let _selection = null; // { cellId, a, b }
function clearSelection(updateUrl) {
clearLineSelections();
_selection = null;
if (updateUrl) {
try {
const url = new URL(window.location.href);
url.searchParams.delete('cell');
url.searchParams.delete('line');
history.replaceState(null, '', url.toString());
} catch (_) {}
}
updateStateIndicator();
}
function selectCellLine(cellId, line, updateUrl) {
try {
// Ensure only one selection across the whole document
clearLineSelections();
const codeBox = document.getElementById(`code-${cellId}`);
if (!codeBox) return;
const pre = codeBox.querySelector('.highlight pre');
const overlay = document.getElementById(`line-highlight-${cellId}`);
const numbers = document.getElementById(`lines-${cellId}`);
if (!pre || !overlay) return;
// Measure line height directly from computed style
const preStyle = getComputedStyle(pre);
const padTop = parseFloat(preStyle.paddingTop || '0');
const lh = parseFloat(preStyle.lineHeight || '20');
// Position overlay
overlay.style.display = 'block';
overlay.style.height = `${lh}px`;
overlay.style.top = `${pre.offsetTop + padTop + (line - 1) * lh}px`;
// Update selected class in line numbers
if (numbers) {
numbers.querySelectorAll('.line-number').forEach(a => a.classList.remove('selected'));
const sel = numbers.querySelector(`.line-number[data-line="${line}"]`);
if (sel) sel.classList.add('selected');
}
if (updateUrl) {
const url = new URL(window.location.href);
url.searchParams.set('cell', cellId);
url.searchParams.set('line', String(line));
history.replaceState(null, '', url.toString());
}
_selection = { cellId, a: line, b: line };
updateStateIndicator();
} catch (e) { console.warn('selectCellLine error', e); }
}
function selectCellLines(cellId, startLine, endLine, updateUrl) {
try {
// normalize order
const a = Math.min(startLine, endLine);
const b = Math.max(startLine, endLine);
clearLineSelections();
const codeBox = document.getElementById(`code-${cellId}`);
if (!codeBox) return;
const pre = codeBox.querySelector('.highlight pre');
const overlay = document.getElementById(`line-highlight-${cellId}`);
const numbers = document.getElementById(`lines-${cellId}`);
if (!pre || !overlay) return;
const preStyle = getComputedStyle(pre);
const padTop = parseFloat(preStyle.paddingTop || '0');
const lh = parseFloat(preStyle.lineHeight || '20');
overlay.style.display = 'block';
overlay.style.top = `${pre.offsetTop + padTop + (a - 1) * lh}px`;
overlay.style.height = `${(b - a + 1) * lh}px`;
if (numbers) {
numbers.querySelectorAll('.line-number').forEach(a => a.classList.remove('selected'));
for (let i = a; i <= b; i++) {
const el = numbers.querySelector(`.line-number[data-line="${i}"]`);
if (el) el.classList.add('selected');
}
}
if (updateUrl) {
const url = new URL(window.location.href);
url.searchParams.set('cell', cellId);
if (a === b) url.searchParams.set('line', String(a));
else url.searchParams.set('line', `${a}-${b}`);
history.replaceState(null, '', url.toString());
}
_selection = { cellId, a, b };
updateStateIndicator();
} catch (e) { console.warn('selectCellLines error', e); }
}
// Drag-to-select support on line numbers
let _lineDrag = { active: false, cellId: null, start: 0 };
function onLineNumberMouseDown(e) {
const a = e.target.closest('.line-number');
if (!a) return;
e.preventDefault();
const cellId = a.dataset.cell;
const line = parseInt(a.dataset.line || '1', 10) || 1;
// Toggle off if this exact single line is already the only selection
const numbers = document.getElementById(`lines-${cellId}`);
if (numbers) {
const selected = Array.from(numbers.querySelectorAll('.line-number.selected')).map(n => parseInt(n.dataset.line||'0',10)).filter(Boolean);
if (selected.length === 1 && selected[0] === line) {
clearSelection(true);
return;
}
}
_lineDrag.active = true;
_lineDrag.cellId = cellId;
_lineDrag.start = line;
selectCellLines(_lineDrag.cellId, _lineDrag.start, _lineDrag.start, false);
}
function onDocMouseMove(e) {
if (!_lineDrag.active) return;
const el = document.elementFromPoint(e.clientX, e.clientY);
if (!el) return;
const a = el.closest && el.closest('.line-number');
if (!a) return;
if (a.dataset.cell !== _lineDrag.cellId) return;
const cur = parseInt(a.dataset.line || '1', 10) || 1;
selectCellLines(_lineDrag.cellId, _lineDrag.start, cur, false);
}
function onDocMouseUp(e) {
if (!_lineDrag.active) return;
const last = document.querySelector('.line-number.selected:last-of-type');
// finalize URL using the current selected range
const numbers = document.getElementById(`lines-${_lineDrag.cellId}`);
if (numbers) {
const selected = Array.from(numbers.querySelectorAll('.line-number.selected')).map(n => parseInt(n.dataset.line||'0',10)).filter(Boolean);
if (selected.length) {
const a = Math.min(...selected); const b = Math.max(...selected);
selectCellLines(_lineDrag.cellId, a, b, true);
}
}
_lineDrag.active = false; _lineDrag.cellId = null; _lineDrag.start = 0;
}
function applyLocationFromUrl() {
try {
const url = new URL(window.location.href);
const cell = url.searchParams.get('cell');
const lineParam = url.searchParams.get('line');
if (cell && lineParam) {
if (lineParam.includes('-')) {
const [a, b] = lineParam.split('-').map(x => parseInt(x, 10));
if (!Number.isNaN(a) && !Number.isNaN(b)) selectCellLines(cell, a, b, false);
} else {
const l = parseInt(lineParam, 10);
if (!Number.isNaN(l)) selectCellLine(cell, l, false);
}
}
// Apply tool parameters from URL
applyToolsFromUrl(url.searchParams);
// Cell states will be applied later in DOMContentLoaded with proper timing
const encodedCellStates = url.searchParams.get('cells');
console.log('Encoded cell states from URL:', encodedCellStates);
} catch (_) {}
}
function applyToolsFromUrl(params) {
try {
// Check if tools widget should be shown
const showTools = params.get('tools');
if (showTools === '1') {
// Mark that tool was loaded from URL
_urlLoadedTool = true;
// Apply color
const color = params.get('color');
if (color && /^[0-9a-fA-F]{6}$/.test(color)) {
setStoredArrowColor('#' + color);
}
// Apply thickness
const thickness = params.get('thickness');
if (thickness) {
const value = parseInt(thickness, 10);
if (value >= 1 && value <= 10) {
setStoredLineThickness(value);
}
}
// Don't override fadeout time for URL-loaded tools - let individual shapes decide
// Load shapes from URL
const encodedShapes = params.get('shapes');
if (encodedShapes) {
const decodedShapes = decodeShapesFromUrl(encodedShapes);
if (decodedShapes.length > 0) {
_shapes = decodedShapes;
saveShapes();
// Trigger render after overlay is initialized
setTimeout(() => {
renderOverlay();
}, 300);
}
}
// Wait for widgets to be initialized before showing tools
setTimeout(() => {
const toolsWidget = document.querySelector('.tools-widget');
const checkbox = document.getElementById('checkbox-tools');
if (toolsWidget && checkbox) {
toolsWidget.style.display = 'block';
checkbox.textContent = '☑';
localStorage.setItem('uvnote-widget-tools', 'visible');
}
// Apply active tool
const activeTool = params.get('tool');
if (activeTool && ['arrow', 'pen', 'eraser', 'spotlight'].includes(activeTool)) {
const toolBtn = Array.from(document.querySelectorAll('.tool-button')).find(btn => btn.textContent === activeTool);
if (toolBtn) {
toolBtn.click();
}
}
// Re-layout widgets after showing tools
layoutWidgetsStackedBottomRight();
}, 200);
}
} catch (_) {}
}
function captureInitialCellStates() {
const cells = document.querySelectorAll('.cell');
cells.forEach(cell => {
const cellId = cell.id.replace('cell-', '');
const codeEl = document.getElementById('code-' + cellId);
const outputEl = document.getElementById('output-' + cellId);
if (codeEl || outputEl) {
const state = {};
if (codeEl) {
state.c = codeEl.classList.contains('collapsed') ? 0 : 1;
}
if (outputEl) {
state.o = outputEl.classList.contains('collapsed') ? 0 : 1;
}
_initialCellStates[cellId] = state;
}
});
console.log('Captured initial cell states:', _initialCellStates);
}
function encodeCellStatesToUrl() {
// Get all cells and their collapse states
const cells = document.querySelectorAll('.cell');
const cellStates = {};
console.log('Found cells:', cells.length);
cells.forEach(cell => {
const cellId = cell.id.replace('cell-', '');
const codeEl = document.getElementById('code-' + cellId);
const outputEl = document.getElementById('output-' + cellId);
const initialState = _initialCellStates[cellId] || {};
console.log(`Encoding cell ${cellId}:`, {
codeEl: !!codeEl,
outputEl: !!outputEl,
codeCollapsed: codeEl ? codeEl.classList.contains('collapsed') : 'N/A',
outputCollapsed: outputEl ? outputEl.classList.contains('collapsed') : 'N/A',
initialState: initialState
});
if (codeEl || outputEl) {
const state = {};
let hasChanges = false;
if (codeEl) {
const currentCodeState = codeEl.classList.contains('collapsed') ? 0 : 1;
const initialCodeState = initialState.c;
// Only encode if different from initial state
if (initialCodeState !== undefined && currentCodeState !== initialCodeState) {
state.c = currentCodeState;
hasChanges = true;
}
}
if (outputEl) {
const currentOutputState = outputEl.classList.contains('collapsed') ? 0 : 1;
const initialOutputState = initialState.o;
// Only encode if different from initial state
if (initialOutputState !== undefined && currentOutputState !== initialOutputState) {
state.o = currentOutputState;
hasChanges = true;
}
}
// Only include cell if it has changes from initial state
if (hasChanges) {
cellStates[cellId] = state;
console.log(`Added cell ${cellId}:`, state);
}
}
});
console.log('Final cell states to encode:', cellStates);
// Return empty string if no changed cells
if (Object.keys(cellStates).length === 0) return '';
// Encode as compact base64 string
const encoded = btoa(JSON.stringify(cellStates));
console.log('Encoded cell states:', encoded);
return encoded;
}
function decodeCellStatesFromUrl(encodedStates) {
if (!encodedStates) return {};
try {
return JSON.parse(atob(encodedStates));
} catch (e) {
console.error('Failed to decode cell states:', e);
return {};
}
}
function applyCellStatesFromUrl(cellStates) {
console.log('Applying cell states from URL:', cellStates);
Object.entries(cellStates).forEach(([cellId, state]) => {
const codeEl = document.getElementById('code-' + cellId);
const outputEl = document.getElementById('output-' + cellId);
console.log(`Cell ${cellId}:`, {
codeEl: !!codeEl,
outputEl: !!outputEl,
state: state
});
if (codeEl && state.c !== undefined) {
if (state.c === 0) {
codeEl.classList.add('collapsed');
console.log(`Collapsed code for cell ${cellId}`, {
hasCollapsedClass: codeEl.classList.contains('collapsed'),
computedDisplay: getComputedStyle(codeEl).display,
classList: Array.from(codeEl.classList),
elementId: codeEl.id
});
} else {
codeEl.classList.remove('collapsed');
codeEl.classList.add('expanded'); // Explicitly add expanded class
console.log(`Expanded code for cell ${cellId}`, {
hasCollapsedClass: codeEl.classList.contains('collapsed'),
hasExpandedClass: codeEl.classList.contains('expanded'),
computedDisplay: getComputedStyle(codeEl).display,
classList: Array.from(codeEl.classList),
elementId: codeEl.id
});
}
}
if (outputEl && state.o !== undefined) {
if (state.o === 0) {
outputEl.classList.add('collapsed');
console.log(`Collapsed output for cell ${cellId}`);
} else {
outputEl.classList.remove('collapsed');
console.log(`Expanded output for cell ${cellId}`);
}
}
// Update visual indicators and force style recalculation
try {
updateIndicators(cellId);
// Force browser to recalculate styles
if (codeEl) {
codeEl.offsetHeight; // Force reflow
console.log(`After indicators update - code visible: ${getComputedStyle(codeEl).display !== 'none'}`);
}
if (outputEl) {
outputEl.offsetHeight; // Force reflow
console.log(`After indicators update - output visible: ${getComputedStyle(outputEl).display !== 'none'}`);
}
} catch (e) {
console.error(`Error updating indicators for cell ${cellId}:`, e);
}
});
}
function encodeShapesToUrl() {
// Encode shapes as compact base64 string
if (_shapes.length === 0) return '';
const shapeData = _shapes.map(shape => {
const baseData = {
ct: shape.createdAt, // creation timestamp
fo: shape.fadeoutTime || getFadeoutTime() // fadeout time for this shape
};
if (shape.type === 'arrow') {
return {
...baseData,
t: 'a',
x1: Math.round(shape.x1),
y1: Math.round(shape.y1),
x2: Math.round(shape.x2),
y2: Math.round(shape.y2),
c: shape.color.substring(1), // remove #
w: shape.width
};
} else if (shape.type === 'pen') {
return {
...baseData,
t: 'p',
pts: shape.points.map(p => [Math.round(p.x), Math.round(p.y)]),
c: shape.color.substring(1),
w: shape.width
};
} else if (shape.type === 'spotlight') {
return {
...baseData,
t: 's',
x: Math.round(shape.x),
y: Math.round(shape.y),
r: Math.round(shape.radius)
};
}
}).filter(Boolean);
return btoa(JSON.stringify(shapeData));
}
function decodeShapesFromUrl(encodedShapes) {
if (!encodedShapes) return [];
try {
const shapeData = JSON.parse(atob(encodedShapes));
return shapeData.map(data => {
const base = {
createdAt: data.ct || Date.now(), // use encoded timestamp or current time
fadeoutTime: data.fo || 0, // use encoded fadeout time or 0 (never fade)
opacity: 1.0
};
if (data.t === 'a') {
return {
...base,
type: 'arrow',
x1: data.x1,
y1: data.y1,
x2: data.x2,
y2: data.y2,
color: '#' + data.c,
width: data.w
};
} else if (data.t === 'p') {
return {
...base,
type: 'pen',
points: data.pts.map(([x, y]) => ({ x, y })),
color: '#' + data.c,
width: data.w
};
} else if (data.t === 's') {
return {
...base,
type: 'spotlight',
x: data.x,
y: data.y,
radius: data.r,
color: '#000000'
};
}
}).filter(Boolean);
} catch (e) {
console.error('Failed to decode shapes:', e);
return [];
}
}
function encodeToolStateToUrl() {
// Don't update URL during initialization
if (_isInitializing) {
return window.location.href;
}
const params = new URLSearchParams(window.location.search);
// Check if tools widget is visible and has an active tool
const toolsWidget = document.querySelector('.tools-widget');
const activeTool = document.body.dataset.tool;
const hasActiveTool = activeTool && activeTool !== 'none';
const toolsWidgetVisible = toolsWidget && getComputedStyle(toolsWidget).display !== 'none';
// Always handle shapes regardless of tool state
const encodedShapes = encodeShapesToUrl();
if (encodedShapes) {
params.set('shapes', encodedShapes);
} else {
params.delete('shapes');
}
// Always preserve existing cell states from URL if present
const existingCellStates = params.get('cells');
if (existingCellStates) {
// Keep existing cell states - don't re-encode from DOM
params.set('cells', existingCellStates);
} else {
// Only encode new cell states if none exist in URL
const encodedCellStates = encodeCellStatesToUrl();
if (encodedCellStates) {
params.set('cells', encodedCellStates);
}
}
if (toolsWidgetVisible && hasActiveTool) {
// Include tool params when widget is visible AND tool is active
params.set('tools', '1');
params.set('tool', activeTool);
// Get color (without # prefix)
const color = getArrowColor();
if (color && color.startsWith('#')) {
params.set('color', color.substring(1));
}
// Get thickness
const thickness = getLineThickness();
params.set('thickness', thickness.toString());
} else {
// Remove tool state params but keep shapes
params.delete('tools');
params.delete('tool');
params.delete('color');
params.delete('thickness');
params.delete('fadeout');
}
// Update URL without reloading
const newUrl = window.location.pathname + (params.toString() ? '?' + params.toString() : '') + window.location.hash;
window.history.replaceState(null, '', newUrl);
return window.location.href;
}
function resetLayout() {
try {
// Clear all uvnote-* keys
const allKeys = Object.keys(localStorage);
const uvnoteKeys = allKeys.filter(key => key.startsWith('uvnote-'));
uvnoteKeys.forEach(k => localStorage.removeItem(k));
} catch (_) {}
// Clear any active selection and remove URL params
try { clearSelection(true); } catch(_) {}
// Reset active tool if any
try { window.setActiveTool('none'); } catch(_) {}
// Clear shapes
try { _shapes = []; saveShapes(); } catch(_) {}
// Reset URL-loaded tool flag
try { _urlLoadedTool = false; } catch(_) {}
// Reset all cells to expanded state
try {
const cells = document.querySelectorAll('.cell');
cells.forEach(cell => {
const cellId = cell.id.replace('cell-', '');
const codeEl = document.getElementById('code-' + cellId);
const outputEl = document.getElementById('output-' + cellId);
if (codeEl) codeEl.classList.remove('collapsed');
if (outputEl) outputEl.classList.remove('collapsed');
updateIndicators(cellId);
});
} catch(_) {}
// Clear ALL URL parameters and reload with clean URL
try {
const cleanUrl = window.location.pathname + window.location.hash;
window.location.href = cleanUrl; // Use window.location.href instead of history.replaceState + reload
} catch (_) {
// Fallback - reload current page
location.reload();
}
}
function toggleMenu() {
const menuButton = document.querySelector('.menu-button');
if (menuButton) {
menuButton.classList.toggle('active');
}
}
function toggleWidget(widgetName) {
let widget;
let checkbox;
// Close the menu first
const menuButton = document.querySelector('.menu-button');
if (menuButton) {
menuButton.classList.remove('active');
}
switch(widgetName) {
case 'tools':
widget = document.querySelector('.tools-widget');
checkbox = document.getElementById('checkbox-tools');
break;
case 'file-explorer':
widget = document.querySelector('.file-explorer');
checkbox = document.getElementById('checkbox-file-explorer');
break;
case 'minimap':
widget = document.querySelector('.minimap');
checkbox = document.getElementById('checkbox-minimap');
break;
case 'status':
widget = document.querySelector('.status-widget');
checkbox = document.getElementById('checkbox-status');
break;
default:
return;
}
if (widget && checkbox) {
const isVisible = getComputedStyle(widget).display !== 'none';
widget.style.display = isVisible ? 'none' : 'block';
checkbox.textContent = isVisible ? '☐' : '☑';
// Save state to localStorage
try {
localStorage.setItem(`uvnote-widget-${widgetName}`, isVisible ? 'hidden' : 'visible');
} catch (_) {}
// Re-layout widgets after visibility change
try {
layoutWidgetsStackedBottomRight();
} catch (_) {}
// Update URL when tools widget visibility changes
if (widgetName === 'tools') {
encodeToolStateToUrl();
}
}
}
function initializeWidgetVisibility() {
const widgets = [
{ name: 'tools', selector: '.tools-widget' },
{ name: 'file-explorer', selector: '.file-explorer' },
{ name: 'minimap', selector: '.minimap' },
{ name: 'status', selector: '.status-widget' }
];
widgets.forEach(({ name, selector }) => {
const defaultState = name === 'status' ? 'visible' : 'hidden';
const savedState = localStorage.getItem(`uvnote-widget-${name}`) || defaultState;
const widget = document.querySelector(selector);
const checkbox = document.getElementById(`checkbox-${name}`);
if (widget && checkbox) {
const isVisible = savedState === 'visible';
widget.style.display = isVisible ? 'block' : 'none';
checkbox.textContent = isVisible ? '☑' : '☐';
}
});
}
// Close menu when clicking outside
document.addEventListener('click', function(event) {
const menuButton = document.querySelector('.menu-button');
// Don't close if clicking on a menu item (let the item handler close it)
if (menuButton && !menuButton.contains(event.target)) {
menuButton.classList.remove('active');
}
});
// Layout: stack widgets bottom-right and equalize widths
function hasCustomWidgetPositions() {
try {
return (
localStorage.getItem('uvnote-minimap-pos') ||
localStorage.getItem('uvnote-file-explorer-pos') ||
localStorage.getItem('uvnote-tools-pos')
);
} catch (_) { return false; }
}
function rectsOverlap(r1, r2) {
return !(r1.right <= r2.left || r2.right <= r1.left || r1.bottom <= r2.top || r2.bottom <= r1.top);
}
function widgetsOverlap(widgets) {
for (let i = 0; i < widgets.length; i++) {
const a = widgets[i];
const ra = a.getBoundingClientRect();
for (let j = i + 1; j < widgets.length; j++) {
const b = widgets[j];
const rb = b.getBoundingClientRect();
if (rectsOverlap(ra, rb)) return true;
}
}
return false;
}
function applyStackLayout(widgets, order) {
if (!widgets.length) return;
// Fixed equal width
const fixedWidth = 220;
widgets.forEach(el => { el.style.width = fixedWidth + 'px'; });
// Fit heights if needed to avoid overflow
const gap = 12;
const available = Math.max(0, window.innerHeight - 40 - gap * (order.length - 1));
const eachMax = Math.floor(available / order.length);
order.forEach(el => {
el.style.maxHeight = eachMax + 'px';
el.style.overflowY = 'auto';
});
// Stack bottom-up in the requested order
let bottomOffset = 20; // base gutter
order.forEach(el => {
el.style.left = 'auto';
el.style.top = 'auto';
el.style.right = '20px';
el.style.bottom = bottomOffset + 'px';
bottomOffset += el.offsetHeight + gap;
});
}
function layoutWidgetsStackedBottomRight() {
const minimap = document.querySelector('.minimap');
const fileExplorer = document.querySelector('.file-explorer');
const tools = document.querySelector('.tools-widget');
const status = document.querySelector('.status-widget');
const widgets = [minimap, fileExplorer, tools, status].filter(el => el && getComputedStyle(el).display !== 'none');
if (!widgets.length) return;
const order = [minimap, fileExplorer, tools, status].filter(Boolean).filter(el => getComputedStyle(el).display !== 'none');
// If user placed custom positions and there is no overlap, respect them.
if (hasCustomWidgetPositions() && !widgetsOverlap(widgets)) return;
applyStackLayout(widgets, order);
}
// Panel icon removed
let _minimapScrollContainer = null;
let _minimapScrollHandler = null;
function initMinimap() {
// Generate minimap content
const minimap = createMinimap();
document.body.appendChild(minimap);
// Make draggable (use title as handle)
const mTitle = minimap.querySelector('.minimap-title');
makeDraggable(minimap, 'uvnote-minimap-pos', mTitle);
// Attach scroll listener to window (two-panel removed)
_minimapScrollContainer = window;
if (_minimapScrollContainer) {
_minimapScrollHandler = () => updateMinimapActive();
if (_minimapScrollContainer === window) {
window.addEventListener('scroll', _minimapScrollHandler);
} else {
_minimapScrollContainer.addEventListener('scroll', _minimapScrollHandler);
}
}
updateMinimapActive();
}
function teardownMinimap() {
const minimap = document.querySelector('.minimap');
if (minimap && minimap.parentNode) minimap.parentNode.removeChild(minimap);
if (_minimapScrollContainer && _minimapScrollHandler) {
if (_minimapScrollContainer === window) {
window.removeEventListener('scroll', _minimapScrollHandler);
} else {
_minimapScrollContainer.removeEventListener('scroll', _minimapScrollHandler);
}
}
_minimapScrollContainer = null;
_minimapScrollHandler = null;
}
function initFileExplorer() {
// Generate file explorer content
const fileExplorer = createFileExplorer();
document.body.appendChild(fileExplorer);
}
function createMinimap() {
const minimap = document.createElement('div');
minimap.className = 'minimap';
const title = document.createElement('div');
title.className = 'minimap-title';
title.textContent = 'navigation';
minimap.appendChild(title);
// Find all headings and cells
const root = document.querySelector('.main-content') || document;
const headings = root.querySelectorAll('h1, h2, h3, h4, h5, h6');
const cells = root.querySelectorAll('.cell');
// Combine and sort by position
const items = [];
headings.forEach(heading => {
const id = heading.id || generateId(heading.textContent);
if (!heading.id) heading.id = id;
items.push({
element: heading,
type: 'heading',
level: parseInt(heading.tagName.charAt(1)),
text: heading.textContent.trim(),
id: id,
position: heading.getBoundingClientRect().top + window.scrollY
});
});
cells.forEach(cell => {
const header = cell.querySelector('.cell-header');
if (header) {
const id = cell.id || `cell-${Date.now()}-${Math.random().toString(36).substr(2, 9)}`;
if (!cell.id) cell.id = id;
items.push({
element: cell,
type: 'cell',
text: header.textContent.trim(),
id: id,
position: cell.getBoundingClientRect().top + window.scrollY
});
}
});
// Sort by position
items.sort((a, b) => a.position - b.position);
// Create minimap items
items.forEach(item => {
const link = document.createElement('a');
link.className = `minimap-item ${item.type === 'heading' ? 'minimap-heading' : 'minimap-cell'}`;
if (item.type === 'heading') {
link.classList.add(`h${item.level}`);
}
link.textContent = item.text.length > 25 ? item.text.substring(0, 22) + '...' : item.text;
link.href = `#${item.id}`;
link.onclick = function(e) {
e.preventDefault();
item.element.scrollIntoView({ behavior: 'smooth', block: 'start' });
};
minimap.appendChild(link);
});
return minimap;
}
function generateId(text) {
return text.toLowerCase()
.replace(/[^a-z0-9]+/g, '-')
.replace(/^-+|-+$/g, '')
.substring(0, 20);
}
function updateMinimapActive() {
const minimapItems = document.querySelectorAll('.minimap-item');
const container = _minimapScrollContainer || window;
const containerRect = container === window ? null : container.getBoundingClientRect();
const scrollPos = (container === window ? window.scrollY : container.scrollTop) + 100; // Offset for better detection
let activeItem = null;
minimapItems.forEach(item => {
const targetId = item.getAttribute('href').substring(1);
const target = document.getElementById(targetId);
if (target) {
const rectTop = target.getBoundingClientRect().top;
const targetPos = (container === window)
? rectTop + window.scrollY
: rectTop - containerRect.top + container.scrollTop;
if (targetPos <= scrollPos) {
activeItem = item;
}
}
item.classList.remove('active');
});
if (activeItem) {
activeItem.classList.add('active');
}
}
function createFileExplorer() {
const fileExplorer = document.createElement('div');
fileExplorer.className = 'file-explorer';
const title = document.createElement('div');
title.className = 'file-explorer-title';
title.textContent = 'files';
fileExplorer.appendChild(title);
// Make draggable (use title as handle)
makeDraggable(fileExplorer, 'uvnote-file-explorer-pos', title);
// Scripts section
const scriptsSection = document.createElement('div');
scriptsSection.className = 'file-explorer-section';
const scriptsTitle = document.createElement('div');
scriptsTitle.className = 'file-explorer-section-title';
scriptsTitle.textContent = 'scripts';
scriptsSection.appendChild(scriptsTitle);
// Find all cells and list their script files (single panel)
const root = document.querySelector('.main-content') || document;
const cells = root.querySelectorAll('.cell');
cells.forEach(cell => {
const header = cell.querySelector('.cell-header');
if (header) {
const cellText = header.textContent.trim();
const cellMatch = cellText.match(/Cell: ([a-zA-Z_][a-zA-Z0-9_]*)/);
if (cellMatch) {
const cellId = cellMatch[1];
const scriptItem = document.createElement('div');
scriptItem.className = 'file-explorer-item script';
scriptItem.textContent = `${cellId}.py`;
scriptItem.onclick = function() {
cell.scrollIntoView({ behavior: 'smooth', block: 'start' });
};
scriptsSection.appendChild(scriptItem);
}
}
});
fileExplorer.appendChild(scriptsSection);
// Artifacts section
const artifactsSection = document.createElement('div');
artifactsSection.className = 'file-explorer-section';
const artifactsTitle = document.createElement('div');
artifactsTitle.className = 'file-explorer-section-title';
artifactsTitle.textContent = 'artifacts';
artifactsSection.appendChild(artifactsTitle);
// Find all artifact links (single panel)
const artifactsRoot = document.querySelector('.main-content') || document;
const artifacts = artifactsRoot.querySelectorAll('.artifact');
if (artifacts.length === 0) {
const noArtifacts = document.createElement('div');
noArtifacts.className = 'file-explorer-item artifact';
noArtifacts.textContent = '(none)';
noArtifacts.style.opacity = '0.5';
artifactsSection.appendChild(noArtifacts);
} else {
artifacts.forEach(artifact => {
const artifactItem = document.createElement('div');
artifactItem.className = 'file-explorer-item artifact';
artifactItem.textContent = artifact.textContent;
artifactItem.onclick = function() {
artifact.click();
};
artifactsSection.appendChild(artifactItem);
});
}
fileExplorer.appendChild(artifactsSection);
return fileExplorer;
}
function initStatusWidget() {
let el = document.querySelector('.status-widget');
if (!el) {
el = document.createElement('div');
el.className = 'status-widget';
el.id = 'status-widget';
el.textContent = 'ready — Esc';
document.body.appendChild(el);
}
}
// Tools widget
let _cursorX = 0;
let _cursorY = 0;
let _cursorVisible = false;
function setActiveTool(tool) {
if (!tool || tool === 'none') {
document.body.dataset.tool = 'none';
localStorage.setItem('uvnote-active-tool', 'none');
setOverlayActive(false);
_cursorVisible = false;
// Remove active class from all tool buttons when deactivating
const toolButtons = document.querySelectorAll('.tools-widget .tool-button');
toolButtons.forEach(btn => btn.classList.remove('active'));
updateStateIndicator();
encodeToolStateToUrl();
return;
}
document.body.dataset.tool = tool;
localStorage.setItem('uvnote-active-tool', tool);
setOverlayActive(true);
_cursorVisible = true;
updateStateIndicator();
encodeToolStateToUrl();
}
// Make setActiveTool globally accessible for ESC key handler
window.setActiveTool = setActiveTool;
function getArrowColor() {
const saved = localStorage.getItem('uvnote-arrow-color');
if (saved) return saved;
return '#e53935'; // Default red color
}
function setStoredArrowColor(color) {
try { localStorage.setItem('uvnote-arrow-color', color); } catch (_) {}
}
function getLineThickness() {
const saved = localStorage.getItem('uvnote-line-thickness');
if (saved) return parseInt(saved, 10);
return 6; // default thickness
}
function setStoredLineThickness(thickness) {
try { localStorage.setItem('uvnote-line-thickness', thickness); } catch (_) {}
}
function getFadeoutTime() {
const saved = localStorage.getItem('uvnote-fadeout-time');
if (saved) return parseInt(saved, 10);
return 5; // default 5 seconds
}
function setStoredFadeoutTime(seconds) {
try { localStorage.setItem('uvnote-fadeout-time', seconds); } catch (_) {}
}
function createToolsWidget() {
const tools = document.createElement('div');
tools.className = 'tools-widget';
const title = document.createElement('div');
title.className = 'tools-title';
title.textContent = 'tools';
tools.appendChild(title);
const row = document.createElement('div');
row.className = 'tools-row';
tools.appendChild(row);
// Arrow tool
const arrowBtn = document.createElement('div');
arrowBtn.className = 'tool-button';
arrowBtn.textContent = 'arrow';
arrowBtn.onclick = function() {
const isActive = arrowBtn.classList.contains('active');
if (isActive) {
arrowBtn.classList.remove('active');
setActiveTool('none');
} else {
tools.querySelectorAll('.tool-button').forEach(b => b.classList.remove('active'));
arrowBtn.classList.add('active');
setActiveTool('arrow');
}
};
row.appendChild(arrowBtn);
// Pen tool
const penBtn = document.createElement('div');
penBtn.className = 'tool-button';
penBtn.textContent = 'pen';
penBtn.onclick = function() {
const isActive = penBtn.classList.contains('active');
if (isActive) {
penBtn.classList.remove('active');
setActiveTool('none');
} else {
tools.querySelectorAll('.tool-button').forEach(b => b.classList.remove('active'));
penBtn.classList.add('active');
setActiveTool('pen');
}
};
row.appendChild(penBtn);
// Eraser tool
const eraseBtn = document.createElement('div');
eraseBtn.className = 'tool-button';
eraseBtn.textContent = 'eraser';
eraseBtn.onclick = function() {
const isActive = eraseBtn.classList.contains('active');
if (isActive) {
eraseBtn.classList.remove('active');
setActiveTool('none');
} else {
tools.querySelectorAll('.tool-button').forEach(b => b.classList.remove('active'));
eraseBtn.classList.add('active');
setActiveTool('eraser');
}
};
row.appendChild(eraseBtn);
// Spotlight tool
const spotlightBtn = document.createElement('div');
spotlightBtn.className = 'tool-button';
spotlightBtn.textContent = 'spotlight';
spotlightBtn.onclick = function() {
const isActive = spotlightBtn.classList.contains('active');
if (isActive) {
spotlightBtn.classList.remove('active');
setActiveTool('none');
} else {
tools.querySelectorAll('.tool-button').forEach(b => b.classList.remove('active'));
spotlightBtn.classList.add('active');
setActiveTool('spotlight');
}
};
row.appendChild(spotlightBtn);
// Clear all
const clearBtn = document.createElement('div');
clearBtn.className = 'tool-button';
clearBtn.textContent = 'clear';
clearBtn.onclick = function() {
_shapes = [];
saveShapes();
renderOverlay();
};
row.appendChild(clearBtn);
// We'll add the copy button at the end of the widget
// Restore active state from storage
const saved = localStorage.getItem('uvnote-active-tool') || 'none';
if (saved === 'arrow') {
arrowBtn.classList.add('active');
setActiveTool('arrow');
} else if (saved === 'pen') {
penBtn.classList.add('active');
setActiveTool('pen');
} else if (saved === 'eraser') {
eraseBtn.classList.add('active');
setActiveTool('eraser');
} else if (saved === 'spotlight') {
spotlightBtn.classList.add('active');
setActiveTool('spotlight');
}
// Color selector
const colorTitle = document.createElement('div');
colorTitle.className = 'tools-section-title';
colorTitle.textContent = 'color';
tools.appendChild(colorTitle);
const colorRow = document.createElement('div');
colorRow.className = 'tools-row color-row';
tools.appendChild(colorRow);
const swatchColors = [
// Primary colors
'#e53935', '#fb8c00', '#fdd835', '#43a047', '#1e88e5', '#8e24aa',
// Additional useful colors
'#ff5722', '#795548', '#607d8b', '#9c27b0',
// Grayscale
'#000000', '#424242', '#9e9e9e', '#ffffff'
];
const swatches = [];
swatchColors.forEach(c => {
const s = document.createElement('div');
s.className = 'color-swatch';
s.style.backgroundColor = c;
s.title = c;
s.onclick = () => {
setStoredArrowColor(c);
refreshColorUI(c);
if (_cursorVisible) renderOverlay();
encodeToolStateToUrl();
};
colorRow.appendChild(s);
swatches.push(s);
});
const colorInput = document.createElement('input');
colorInput.type = 'color';
colorInput.className = 'color-input';
colorInput.oninput = () => {
setStoredArrowColor(colorInput.value);
refreshColorUI(colorInput.value);
if (_cursorVisible) renderOverlay();
encodeToolStateToUrl();
};
colorRow.appendChild(colorInput);
function refreshColorUI(selected) {
const selectedHex = selected.startsWith('#') ? selected.toLowerCase() : rgbToHex(selected);
swatches.forEach((s, i) => {
const swatchHex = swatchColors[i].toLowerCase();
if (swatchHex === selectedHex) {
s.classList.add('selected');
} else {
s.classList.remove('selected');
}
});
try {
colorInput.value = selectedHex;
} catch (_) {}
}
function rgbToHex(rgb) {
const m = rgb.match(/rgba?\((\d+),\s*(\d+),\s*(\d+)\)/i);
if (!m) return '#000000';
const r = parseInt(m[1]).toString(16).padStart(2, '0');
const g = parseInt(m[2]).toString(16).padStart(2, '0');
const b = parseInt(m[3]).toString(16).padStart(2, '0');
return `#${r}${g}${b}`;
}
// Restore color selection
refreshColorUI(getArrowColor());
// Thickness slider
const thicknessTitle = document.createElement('div');
thicknessTitle.className = 'tools-section-title';
thicknessTitle.textContent = 'thickness';
tools.appendChild(thicknessTitle);
const thicknessRow = document.createElement('div');
thicknessRow.className = 'thickness-row';
tools.appendChild(thicknessRow);
const thicknessSlider = document.createElement('input');
thicknessSlider.type = 'range';
thicknessSlider.className = 'thickness-slider';
thicknessSlider.min = '1';
thicknessSlider.max = '10';
thicknessSlider.value = getLineThickness();
const thicknessValue = document.createElement('span');
thicknessValue.className = 'thickness-value';
thicknessValue.textContent = thicknessSlider.value + 'px';
thicknessSlider.oninput = function() {
const value = parseInt(thicknessSlider.value, 10);
setStoredLineThickness(value);
thicknessValue.textContent = value + 'px';
if (_cursorVisible) renderOverlay();
encodeToolStateToUrl();
};
thicknessRow.appendChild(thicknessSlider);
thicknessRow.appendChild(thicknessValue);
// Fadeout time slider
const fadeoutTitle = document.createElement('div');
fadeoutTitle.className = 'tools-section-title';
fadeoutTitle.textContent = 'fadeout time';
tools.appendChild(fadeoutTitle);
const fadeoutRow = document.createElement('div');
fadeoutRow.className = 'thickness-row';
tools.appendChild(fadeoutRow);
const fadeoutSlider = document.createElement('input');
fadeoutSlider.type = 'range';
fadeoutSlider.className = 'thickness-slider';
fadeoutSlider.min = '0';
fadeoutSlider.max = '30';
fadeoutSlider.value = getFadeoutTime();
const fadeoutValue = document.createElement('span');
fadeoutValue.className = 'thickness-value';
fadeoutValue.textContent = fadeoutSlider.value === '0' ? 'never' : fadeoutSlider.value + 's';
fadeoutSlider.oninput = function() {
const value = parseInt(fadeoutSlider.value, 10);
setStoredFadeoutTime(value);
fadeoutValue.textContent = value === 0 ? 'never' : value + 's';
encodeToolStateToUrl();
};
fadeoutRow.appendChild(fadeoutSlider);
fadeoutRow.appendChild(fadeoutValue);
// Draggable behavior
makeDraggable(tools, 'uvnote-tools-pos', title);
return tools;
}
function initTools() {
const widget = createToolsWidget();
document.body.appendChild(widget);
}
function teardownTools() {
const w = document.querySelector('.tools-widget');
if (w && w.parentNode) w.parentNode.removeChild(w);
}
// --- Canvas overlay for tools ---
let _overlay = null;
let _overlayCtx = null;
let _overlayContainer = null; // window
let _overlayMode = 'single';
let _overlayResizeHandler = null;
let _overlayScrollHandler = null;
let _drawing = null; // current in-progress arrow {x1,y1,x2,y2}
let _shapes = []; // committed shapes for current mode
let _fadeTimer = null; // timer for fade animation
let _urlLoadedTool = false; // track if tool was loaded from URL
let _isInitializing = true; // prevent URL updates during initialization
let _initialCellStates = {}; // track initial cell states from page load
function getOverlayStorageKey() { return 'uvnote-shapes'; }
function loadShapes() {
try {
const raw = localStorage.getItem(getOverlayStorageKey());
_shapes = raw ? JSON.parse(raw) : [];
} catch (_) { _shapes = []; }
}
function saveShapes() {
try {
localStorage.setItem(getOverlayStorageKey(), JSON.stringify(_shapes));
// Always update URL when shapes change
encodeToolStateToUrl();
} catch (_) {}
}
function updateShapesFade() {
const now = Date.now();
let needsUpdate = false;
for (let i = _shapes.length - 1; i >= 0; i--) {
const shape = _shapes[i];
if (!shape.createdAt) continue; // Skip old shapes without timestamps
// Use individual shape's fadeout time, or global if not set
const shapesFadeoutSeconds = shape.fadeoutTime !== undefined ? shape.fadeoutTime : getFadeoutTime();
// Skip fading if fadeout is disabled for this shape
if (shapesFadeoutSeconds === 0) continue;
const fadeStartTime = Math.max(0, (shapesFadeoutSeconds - 2) * 1000); // Start fading 2s before end
const fadeEndTime = shapesFadeoutSeconds * 1000; // Fully gone after specified time
const age = now - shape.createdAt;
if (age >= fadeEndTime) {
// Remove completely faded shapes
_shapes.splice(i, 1);
needsUpdate = true;
} else if (age >= fadeStartTime) {
// Update opacity for fading shapes
const fadeProgress = (age - fadeStartTime) / (fadeEndTime - fadeStartTime);
const newOpacity = 1 - fadeProgress;
if (Math.abs(shape.opacity - newOpacity) > 0.01) {
shape.opacity = newOpacity;
needsUpdate = true;
}
}
}
if (needsUpdate) {
saveShapes();
renderOverlay();
// Update URL to remove faded shapes
encodeToolStateToUrl();
}
}
function getContentContainer() { return window; }
function updateOverlayModeAndContainer() {
_overlayContainer = window;
_overlayMode = 'single';
}
function updateOverlayBounds() {
if (!_overlay) return;
if (_overlayContainer === window) {
_overlay.style.position = 'fixed';
_overlay.style.left = '0px';
_overlay.style.top = '0px';
_overlay.width = window.innerWidth;
_overlay.height = window.innerHeight;
} else {
const rect = _overlayContainer.getBoundingClientRect();
_overlay.style.position = 'fixed';
_overlay.style.left = rect.left + 'px';
_overlay.style.top = rect.top + 'px';
_overlay.width = Math.max(0, Math.floor(rect.width));
_overlay.height = Math.max(0, Math.floor(rect.height));
}
renderOverlay();
}
function containerScrollLeft() {
return (_overlayContainer === window) ? (window.scrollX || 0) : (_overlayContainer.scrollLeft || 0);
}
function containerScrollTop() {
return (_overlayContainer === window) ? (window.scrollY || 0) : (_overlayContainer.scrollTop || 0);
}
function toCanvasCoords(clientX, clientY) {
const rect = _overlay.getBoundingClientRect();
return { x: clientX - rect.left, y: clientY - rect.top };
}
function onPointerDown(e) {
const tool = document.body.dataset.tool;
if (tool === 'arrow') {
startDrawArrow(e);
} else if (tool === 'pen') {
startDrawPen(e);
} else if (tool === 'eraser') {
eraseAt(e);
} else if (tool === 'spotlight') {
startDrawSpotlight(e);
}
}
function onPointerMove(e) {
// Update cursor position
const pt = toCanvasCoords(e.touches ? e.touches[0].clientX : e.clientX, e.touches ? e.touches[0].clientY : e.clientY);
_cursorX = pt.x;
_cursorY = pt.y;
if (!_drawing) {
// Just update cursor position and re-render
if (_cursorVisible) {
renderOverlay();
}
return;
}
if (_drawing.type === 'pen') {
moveDrawPen(e);
} else if (_drawing.type === 'spotlight') {
moveDrawSpotlight(e);
} else {
moveDrawArrow(e);
}
}
function onPointerEnter(e) {
_cursorVisible = document.body.dataset.tool !== 'none';
if (_cursorVisible) {
renderOverlay();
}
}
function onPointerLeave(e) {
_cursorVisible = false;
renderOverlay();
}
function onPointerUp(e) {
if (!_drawing) return;
if (_drawing.type === 'pen') {
endDrawPen();
} else if (_drawing.type === 'spotlight') {
endDrawSpotlight();
} else {
endDrawArrow();
}
}
function startDrawArrow(e) {
if (document.body.dataset.tool !== 'arrow') return;
const pt = toCanvasCoords(e.touches ? e.touches[0].clientX : e.clientX, e.touches ? e.touches[0].clientY : e.clientY);
_drawing = {
x1: pt.x + containerScrollLeft(),
y1: pt.y + containerScrollTop(),
x2: pt.x + containerScrollLeft(),
y2: pt.y + containerScrollTop(),
color: getArrowColor(),
width: getLineThickness()
};
renderOverlay();
e.preventDefault();
}
function moveDrawArrow(e) {
if (!_drawing) return;
const pt = toCanvasCoords(e.touches ? e.touches[0].clientX : e.clientX, e.touches ? e.touches[0].clientY : e.clientY);
_drawing.x2 = pt.x + containerScrollLeft();
_drawing.y2 = pt.y + containerScrollTop();
renderOverlay();
e.preventDefault();
}
function endDrawArrow() {
if (!_drawing) return;
_shapes.push({
type: 'arrow',
..._drawing,
createdAt: Date.now(),
fadeoutTime: getFadeoutTime(),
opacity: 1.0
});
_drawing = null;
saveShapes();
renderOverlay();
}
function startDrawPen(e) {
if (document.body.dataset.tool !== 'pen') return;
const pt = toCanvasCoords(e.touches ? e.touches[0].clientX : e.clientX, e.touches ? e.touches[0].clientY : e.clientY);
_drawing = {
type: 'pen',
points: [{
x: pt.x + containerScrollLeft(),
y: pt.y + containerScrollTop()
}],
color: getArrowColor(),
width: getLineThickness()
};
renderOverlay();
e.preventDefault();
}
function moveDrawPen(e) {
if (!_drawing || _drawing.type !== 'pen') return;
const pt = toCanvasCoords(e.touches ? e.touches[0].clientX : e.clientX, e.touches ? e.touches[0].clientY : e.clientY);
_drawing.points.push({
x: pt.x + containerScrollLeft(),
y: pt.y + containerScrollTop()
});
renderOverlay();
e.preventDefault();
}
function endDrawPen() {
if (!_drawing || _drawing.type !== 'pen') return;
if (_drawing.points.length > 1) {
_shapes.push({
..._drawing,
createdAt: Date.now(),
fadeoutTime: getFadeoutTime(),
opacity: 1.0
});
}
_drawing = null;
saveShapes();
renderOverlay();
}
function startDrawSpotlight(e) {
if (document.body.dataset.tool !== 'spotlight') return;
const pt = toCanvasCoords(e.touches ? e.touches[0].clientX : e.clientX, e.touches ? e.touches[0].clientY : e.clientY);
_drawing = {
type: 'spotlight',
x: pt.x + containerScrollLeft(),
y: pt.y + containerScrollTop(),
radius: getLineThickness() * 20, // Use thickness to control spotlight size (bigger default)
color: getArrowColor()
};
renderOverlay();
e.preventDefault();
}
function moveDrawSpotlight(e) {
if (!_drawing || _drawing.type !== 'spotlight') return;
const pt = toCanvasCoords(e.touches ? e.touches[0].clientX : e.clientX, e.touches ? e.touches[0].clientY : e.clientY);
const dx = pt.x + containerScrollLeft() - _drawing.x;
const dy = pt.y + containerScrollTop() - _drawing.y;
_drawing.radius = Math.max(20, Math.sqrt(dx * dx + dy * dy)); // Minimum radius of 20
renderOverlay();
e.preventDefault();
}
function endDrawSpotlight() {
if (!_drawing || _drawing.type !== 'spotlight') return;
_shapes.push({
..._drawing,
createdAt: Date.now(),
fadeoutTime: getFadeoutTime(),
opacity: 1.0
});
_drawing = null;
saveShapes();
renderOverlay();
}
function distPointToSegment(px, py, x1, y1, x2, y2) {
const dx = x2 - x1, dy = y2 - y1;
if (dx === 0 && dy === 0) return Math.hypot(px - x1, py - y1);
const t = Math.max(0, Math.min(1, ((px - x1) * dx + (py - y1) * dy) / (dx*dx + dy*dy)));
const cx = x1 + t * dx, cy = y1 + t * dy;
return Math.hypot(px - cx, py - cy);
}
function eraseAt(e) {
const pt = toCanvasCoords(e.touches ? e.touches[0].clientX : e.clientX, e.touches ? e.touches[0].clientY : e.clientY);
const x = pt.x + containerScrollLeft();
const y = pt.y + containerScrollTop();
const threshold = 10; // pixels
for (let i = _shapes.length - 1; i >= 0; i--) {
const s = _shapes[i];
if (s.type === 'arrow') {
const d = distPointToSegment(x, y, s.x1, s.y1, s.x2, s.y2);
if (d <= threshold) {
_shapes.splice(i, 1);
saveShapes();
renderOverlay();
break;
}
} else if (s.type === 'pen' && s.points) {
// Check if click is near any line segment in the pen stroke
let minDist = Infinity;
for (let j = 1; j < s.points.length; j++) {
const d = distPointToSegment(x, y, s.points[j-1].x, s.points[j-1].y, s.points[j].x, s.points[j].y);
minDist = Math.min(minDist, d);
}
if (minDist <= threshold) {
_shapes.splice(i, 1);
saveShapes();
renderOverlay();
break;
}
}
}
e.preventDefault();
}
function drawArrow(ctx, x1, y1, x2, y2, color, width, opacity = 1.0) {
// Set opacity
const oldAlpha = ctx.globalAlpha;
ctx.globalAlpha = opacity;
ctx.strokeStyle = color;
ctx.fillStyle = color;
ctx.lineWidth = width;
ctx.lineCap = 'round';
ctx.lineJoin = 'round';
// Check if points are too close (initial state)
const dx = x2 - x1;
const dy = y2 - y1;
const distance = Math.sqrt(dx * dx + dy * dy);
if (distance < 5) {
// Draw just a small arrowhead pointing down-right when first clicked
const defaultAngle = Math.PI / 4; // 45 degrees (down-right)
const headLength = Math.min(15 + width * 1.5, 25);
const headAngle = Math.PI / 6;
// Calculate arrowhead points
const hx1 = x1 + headLength * Math.cos(defaultAngle - headAngle);
const hy1 = y1 + headLength * Math.sin(defaultAngle - headAngle);
const hx2 = x1 + headLength * Math.cos(defaultAngle + headAngle);
const hy2 = y1 + headLength * Math.sin(defaultAngle + headAngle);
// Draw arrowhead only
ctx.beginPath();
ctx.moveTo(x1, y1);
ctx.lineTo(hx1, hy1);
ctx.lineTo(hx2, hy2);
ctx.closePath();
ctx.fill();
} else {
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<div class="main-content">
<h1>HF Kernels - Causal Conv1D</h1>
<h2>GPU Info</h2>
<div class="cell" id="cell-nv">
<div class="cell-header">
<span class="collapse-indicators">
<span onclick="toggleCode('nv')" style="cursor: pointer;">▼ code</span>
<span onclick="toggleOutput('nv')" style="cursor: pointer;">▼ output</span>
<span id="uv-indicator-nv" style="cursor: default; opacity: 0.3;">▶ uv-logs</span>
</span> |
Cell: nv | 0.21s
| <button class="run-btn" onclick="runCell('nv')">▶ run</button>
<button class="copy-btn" onclick="copyCell('nv')">Copy</button>
<a href="cells/nv.py" target="_blank" class="raw-btn">Raw</a>
<a href="https://github.com/huggingface/kernels-benchmarks/blob/main/causal_conv1d/impls/hf_kernels_causal_conv1d.md" target="_blank" class="github-btn">GitHub</a>
<a href="https://huggingface.co/kernels-community/causal-conv1d" target="_blank" class="hf-btn">🤗 HF</a>
</div>
<div id="code-nv" class="cell-code" data-lines="2">
<div class="code-wrap">
<div class="highlight"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">subprocess</span>
<span class="nb">print</span><span class="p">(</span><span class="n">subprocess</span><span class="o">.</span><span class="n">run</span><span class="p">([</span><span class="s2">&quot;nvidia-smi&quot;</span><span class="p">],</span> <span class="n">capture_output</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">text</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">stdout</span><span class="p">)</span>
</pre></div>
<div class="code-line-highlight" id="line-highlight-nv"></div>
</div>
</div>
<div id="output-nv" class="cell-output">
<div class="cell-stdout"><pre class="stdout-text">Fri Oct 31 20:00:25 2025
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 570.195.03 Driver Version: 570.195.03 CUDA Version: 12.8 |
|-----------------------------------------+------------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 NVIDIA L40S On | 00000000:4D:00.0 Off | 0 |
| N/A 33C P0 79W / 350W | 0MiB / 46068MiB | 11% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+
</pre></div>
</div>
</div>
<h2>Causal Conv1D Benchmark</h2>
<div class="cell" id="cell-benchmark">
<div class="cell-header">
<span class="collapse-indicators">
<span onclick="toggleCode('benchmark')" style="cursor: pointer;">▼ code</span>
<span onclick="toggleOutput('benchmark')" style="cursor: pointer;">▼ output</span>
<span id="uv-indicator-benchmark" onclick="toggleUvLogsFromHeader('benchmark')" style="cursor: pointer;">▶ uv-logs</span>
</span> |
Cell: benchmark | 9.11s
| <button class="run-btn" onclick="runCell('benchmark')">▶ run</button>
<button class="copy-btn" onclick="copyCell('benchmark')">Copy</button>
<a href="cells/benchmark.py" target="_blank" class="raw-btn">Raw</a>
<a href="https://github.com/huggingface/kernels-benchmarks/blob/main/causal_conv1d/impls/hf_kernels_causal_conv1d.md" target="_blank" class="github-btn">GitHub</a>
<a href="https://huggingface.co/kernels-community/causal-conv1d" target="_blank" class="hf-btn">🤗 HF</a>
</div>
<div id="code-benchmark" class="cell-code" data-lines="31">
<div class="code-wrap">
<div class="highlight"><pre><span></span><span class="c1"># /// script</span>
<span class="c1"># requires-python = &quot;&gt;=3.10&quot;</span>
<span class="c1"># dependencies = [</span>
<span class="c1"># &quot;numpy&quot;,</span>
<span class="c1"># &quot;torch==2.8.0&quot;,</span>
<span class="c1"># &quot;kernels-benchmark-tools&quot;,</span>
<span class="c1"># &quot;kernels&quot;,</span>
<span class="c1"># ]</span>
<span class="c1">#</span>
<span class="c1"># [tool.uv.sources]</span>
<span class="c1"># kernels-benchmark-tools = { path = &quot;../../../../../tools&quot;, editable = true }</span>
<span class="c1"># ///</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">torch</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">sys</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">kernels_benchmark_tools</span><span class="w"> </span><span class="kn">import</span> <span class="n">KernelTypeEnum</span><span class="p">,</span> <span class="n">run_benchmark</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">kernels</span><span class="w"> </span><span class="kn">import</span> <span class="n">get_kernel</span>
<span class="c1"># Load the causal conv1d kernel</span>
<span class="n">causal_conv1d</span> <span class="o">=</span> <span class="n">get_kernel</span><span class="p">(</span><span class="s2">&quot;kernels-community/causal-conv1d&quot;</span><span class="p">)</span>
<span class="k">def</span><span class="w"> </span><span class="nf">hf_kernels_causal_conv1d</span><span class="p">(</span><span class="n">input_tensor</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">):</span>
<span class="k">return</span> <span class="n">causal_conv1d</span><span class="o">.</span><span class="n">causal_conv1d_fn</span><span class="p">(</span><span class="n">input_tensor</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">bias</span><span class="p">)</span>
<span class="n">run_benchmark</span><span class="p">(</span>
<span class="n">kernel_type</span><span class="o">=</span><span class="n">KernelTypeEnum</span><span class="o">.</span><span class="n">CAUSAL_CONV1D</span><span class="p">,</span>
<span class="n">impl_name</span><span class="o">=</span><span class="s2">&quot;hf_kernels_causal_conv1d&quot;</span><span class="p">,</span>
<span class="n">impl_tags</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;family&quot;</span><span class="p">:</span> <span class="s2">&quot;hf-kernels&quot;</span><span class="p">,</span> <span class="s2">&quot;backend&quot;</span><span class="p">:</span> <span class="s2">&quot;cuda&quot;</span><span class="p">},</span>
<span class="n">impl_func</span><span class="o">=</span><span class="n">hf_kernels_causal_conv1d</span><span class="p">,</span>
<span class="p">)</span>
</pre></div>
<div class="code-line-highlight" id="line-highlight-benchmark"></div>
</div>
</div>
<div id="output-benchmark" class="cell-output">
<div class="cell-stdout"><pre class="stdout-text">Running causal_conv1d benchmark on cuda with 24 workloads.
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B2_D64_S128_W2
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 180.703us 4446.43% 180.703us 180.703us 1
hf_kernels_causal_conv1d 8.48% 160.534us 99.62% 1.886ms 1.886ms 0.000us 0.00% 5.504us 5.504us 1
CausalConv1dFn 6.47% 122.423us 91.15% 1.726ms 575.261us 0.000us 0.00% 5.504us 1.835us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 1.51% 28.612us 80.84% 1.531ms 510.207us 4.064us 100.00% 5.504us 1.835us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 4.064us 100.00% 4.064us 1.355us 3
Activity Buffer Request 76.71% 1.452ms 76.71% 1.452ms 1.452ms 1.440us 35.43% 1.440us 1.440us 1
aten::empty_like 1.07% 20.220us 3.84% 72.741us 24.247us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 2.77% 52.521us 2.77% 52.521us 17.507us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 2.62% 49.571us 2.62% 49.571us 16.524us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.38% 7.101us 0.38% 7.101us 7.101us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 1.893ms
Self CUDA time total: 4.064us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B2_D64_S128_W4
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 125.791us 3331.33% 125.791us 125.791us 1
hf_kernels_causal_conv1d 5.58% 96.392us 99.64% 1.721ms 1.721ms 0.000us 0.00% 5.056us 5.056us 1
CausalConv1dFn 4.40% 76.074us 94.06% 1.625ms 541.671us 0.000us 0.00% 5.056us 1.685us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 1.52% 26.231us 87.95% 1.519ms 506.473us 3.776us 100.00% 5.056us 1.685us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 3.776us 100.00% 3.776us 1.259us 3
Activity Buffer Request 84.56% 1.461ms 84.56% 1.461ms 1.461ms 1.280us 33.90% 1.280us 1.280us 1
aten::empty_like 0.44% 7.590us 1.71% 29.520us 9.840us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 1.27% 21.930us 1.27% 21.930us 7.310us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 1.87% 32.290us 1.87% 32.290us 10.763us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.36% 6.200us 0.36% 6.200us 6.200us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 1.728ms
Self CUDA time total: 3.776us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B2_D64_S512_W2
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 125.758us 3330.46% 125.758us 125.758us 1
hf_kernels_causal_conv1d 5.23% 90.742us 99.66% 1.729ms 1.729ms 0.000us 0.00% 5.056us 5.056us 1
CausalConv1dFn 4.39% 76.092us 94.43% 1.638ms 546.081us 0.000us 0.00% 5.056us 1.685us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 1.50% 26.031us 88.31% 1.532ms 510.660us 3.776us 100.00% 5.056us 1.685us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 3.776us 100.00% 3.776us 1.259us 3
Activity Buffer Request 84.98% 1.474ms 84.98% 1.474ms 1.474ms 1.280us 33.90% 1.280us 1.280us 1
aten::empty_like 0.47% 8.201us 1.74% 30.171us 10.057us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 1.27% 21.970us 1.27% 21.970us 7.323us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 1.83% 31.671us 1.83% 31.671us 10.557us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.34% 5.850us 0.34% 5.850us 5.850us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 1.735ms
Self CUDA time total: 3.776us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B2_D64_S512_W4
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 127.584us 3350.42% 127.584us 127.584us 1
hf_kernels_causal_conv1d 4.53% 88.983us 99.75% 1.962ms 1.962ms 0.000us 0.00% 5.088us 5.088us 1
CausalConv1dFn 3.93% 77.252us 95.23% 1.873ms 624.219us 0.000us 0.00% 5.088us 1.696us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 1.36% 26.710us 89.83% 1.766ms 588.805us 3.808us 100.00% 5.088us 1.696us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 3.808us 100.00% 3.808us 1.269us 3
Activity Buffer Request 74.34% 1.462ms 74.34% 1.462ms 1.462ms 1.280us 33.61% 1.280us 1.280us 1
aten::empty_like 0.41% 8.060us 1.47% 28.990us 9.663us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 1.06% 20.930us 1.06% 20.930us 6.977us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 14.13% 277.777us 14.13% 277.777us 92.592us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.25% 4.831us 0.25% 4.831us 4.831us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 1.966ms
Self CUDA time total: 3.808us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B2_D64_S2048_W2
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 126.686us 2639.84% 126.686us 126.686us 1
hf_kernels_causal_conv1d 4.55% 87.622us 99.73% 1.920ms 1.920ms 0.000us 0.00% 6.430us 6.430us 1
CausalConv1dFn 3.92% 75.482us 95.18% 1.832ms 610.789us 0.000us 0.00% 6.430us 2.143us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 1.44% 27.663us 89.66% 1.726ms 575.372us 4.799us 100.00% 6.430us 2.143us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 4.799us 100.00% 4.799us 1.600us 3
Activity Buffer Request 74.49% 1.434ms 74.49% 1.434ms 1.434ms 1.631us 33.99% 1.631us 1.631us 1
aten::empty_like 0.42% 8.140us 1.60% 30.770us 10.257us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 1.18% 22.630us 1.18% 22.630us 7.543us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 13.74% 264.526us 13.74% 264.526us 88.175us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.27% 5.120us 0.27% 5.120us 5.120us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 1.925ms
Self CUDA time total: 4.799us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B2_D64_S2048_W4
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 117.083us 2423.58% 117.083us 117.083us 1
hf_kernels_causal_conv1d 12.24% 83.203us 99.28% 674.957us 674.957us 0.000us 0.00% 6.463us 6.463us 1
CausalConv1dFn 10.43% 70.911us 87.04% 591.754us 197.251us 0.000us 0.00% 6.463us 2.154us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 3.93% 26.710us 72.18% 490.682us 163.561us 4.831us 100.00% 6.463us 2.154us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 4.831us 100.00% 4.831us 1.610us 3
Activity Buffer Request 32.42% 220.416us 32.42% 220.416us 220.416us 1.632us 33.78% 1.632us 1.632us 1
aten::empty_like 1.07% 7.270us 4.44% 30.161us 10.054us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 3.37% 22.891us 3.37% 22.891us 7.630us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 35.83% 243.556us 35.83% 243.556us 81.185us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.72% 4.870us 0.72% 4.870us 4.870us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 679.827us
Self CUDA time total: 4.831us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B2_D2048_S128_W2
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 124.381us 1167.35% 124.381us 124.381us 1
hf_kernels_causal_conv1d 4.48% 85.542us 99.75% 1.904ms 1.904ms 0.000us 0.00% 14.271us 14.271us 1
CausalConv1dFn 3.83% 73.182us 95.27% 1.819ms 606.282us 0.000us 0.00% 14.271us 4.757us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 1.41% 26.960us 89.88% 1.716ms 571.988us 10.655us 100.00% 14.271us 4.757us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 10.655us 100.00% 10.655us 3.552us 3
Activity Buffer Request 76.01% 1.451ms 76.01% 1.451ms 1.451ms 3.616us 33.94% 3.616us 3.616us 1
aten::empty_like 0.43% 8.120us 1.56% 29.700us 9.900us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 1.13% 21.580us 1.13% 21.580us 7.193us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 12.45% 237.787us 12.45% 237.787us 79.262us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.25% 4.860us 0.25% 4.860us 4.860us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 1.909ms
Self CUDA time total: 10.655us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B2_D2048_S128_W4
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 122.652us 1120.72% 122.652us 122.652us 1
hf_kernels_causal_conv1d 12.91% 86.303us 99.27% 663.588us 663.588us 0.000us 0.00% 14.624us 14.624us 1
CausalConv1dFn 10.74% 71.821us 86.36% 577.285us 192.428us 0.000us 0.00% 14.624us 4.875us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 3.81% 25.480us 71.21% 476.023us 158.674us 10.944us 100.00% 14.624us 4.875us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 10.944us 100.00% 10.944us 3.648us 3
Activity Buffer Request 32.82% 219.426us 32.82% 219.426us 219.426us 3.680us 33.63% 3.680us 3.680us 1
aten::empty_like 1.14% 7.591us 4.40% 29.441us 9.814us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 3.27% 21.850us 3.27% 21.850us 7.283us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 34.57% 231.117us 34.57% 231.117us 77.039us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.73% 4.900us 0.73% 4.900us 4.900us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 668.488us
Self CUDA time total: 10.944us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B2_D2048_S512_W2
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 130.430us 1181.43% 130.430us 130.430us 1
hf_kernels_causal_conv1d 4.23% 79.341us 99.73% 1.871ms 1.871ms 0.000us 0.00% 14.784us 14.784us 1
CausalConv1dFn 4.03% 75.521us 95.50% 1.792ms 597.206us 0.000us 0.00% 14.784us 4.928us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 1.43% 26.810us 89.82% 1.685ms 561.675us 11.040us 100.00% 14.784us 4.928us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 11.040us 100.00% 11.040us 3.680us 3
Activity Buffer Request 77.07% 1.446ms 77.07% 1.446ms 1.446ms 3.744us 33.91% 3.744us 3.744us 1
aten::empty_like 0.44% 8.272us 1.66% 31.072us 10.357us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 1.22% 22.800us 1.22% 22.800us 7.600us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 11.32% 212.286us 11.32% 212.286us 70.762us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.27% 5.130us 0.27% 5.130us 5.130us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 1.876ms
Self CUDA time total: 11.040us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B2_D2048_S512_W4
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 120.097us 1060.18% 120.097us 120.097us 1
hf_kernels_causal_conv1d 13.35% 76.301us 99.17% 566.674us 566.674us 0.000us 0.00% 15.168us 15.168us 1
CausalConv1dFn 12.80% 73.153us 85.81% 490.373us 163.458us 0.000us 0.00% 15.168us 5.056us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 4.71% 26.911us 68.00% 388.569us 129.523us 11.328us 100.00% 15.168us 5.056us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 11.328us 100.00% 11.328us 3.776us 3
Activity Buffer Request 34.49% 197.075us 34.49% 197.075us 197.075us 3.840us 33.90% 3.840us 3.840us 1
aten::empty_like 1.29% 7.379us 5.01% 28.651us 9.550us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 3.72% 21.272us 3.72% 21.272us 7.091us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 28.80% 164.583us 28.80% 164.583us 54.861us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.83% 4.760us 0.83% 4.760us 4.760us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 571.434us
Self CUDA time total: 11.328us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B2_D2048_S2048_W2
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 133.919us 265.71% 133.919us 133.919us 1
hf_kernels_causal_conv1d 4.38% 80.552us 99.73% 1.836ms 1.836ms 0.000us 0.00% 83.873us 83.873us 1
CausalConv1dFn 4.09% 75.353us 95.35% 1.755ms 585.145us 0.000us 0.00% 83.873us 27.958us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 1.33% 24.410us 89.50% 1.648ms 549.264us 50.401us 100.00% 83.873us 27.958us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 50.401us 100.00% 50.401us 16.800us 3
Activity Buffer Request 79.01% 1.455ms 79.01% 1.455ms 1.455ms 33.472us 66.41% 33.472us 33.472us 1
aten::empty_like 0.45% 8.369us 1.75% 32.290us 10.763us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 1.30% 23.921us 1.30% 23.921us 7.974us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 9.17% 168.764us 9.17% 168.764us 56.255us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.27% 5.020us 0.27% 5.020us 5.020us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 1.841ms
Self CUDA time total: 50.401us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B2_D2048_S2048_W4
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 131.005us 256.03% 131.005us 131.005us 1
hf_kernels_causal_conv1d 11.69% 77.241us 99.25% 655.717us 655.717us 0.000us 0.00% 85.534us 85.534us 1
CausalConv1dFn 10.97% 72.503us 87.56% 578.476us 192.825us 0.000us 0.00% 85.534us 28.511us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 3.89% 25.692us 71.76% 474.103us 158.034us 51.167us 100.00% 85.534us 28.511us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 51.167us 100.00% 51.167us 17.056us 3
Activity Buffer Request 43.08% 284.587us 43.08% 284.587us 284.587us 34.367us 67.17% 34.367us 34.367us 1
aten::empty_like 1.14% 7.549us 4.82% 31.870us 10.623us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 3.68% 24.321us 3.68% 24.321us 8.107us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 24.80% 163.824us 24.80% 163.824us 54.608us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.75% 4.929us 0.75% 4.929us 4.929us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 660.646us
Self CUDA time total: 51.167us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B4_D64_S128_W2
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 118.686us 3040.89% 118.686us 118.686us 1
hf_kernels_causal_conv1d 11.60% 73.750us 99.24% 631.216us 631.216us 0.000us 0.00% 5.183us 5.183us 1
CausalConv1dFn 11.30% 71.845us 87.65% 557.466us 185.822us 0.000us 0.00% 5.183us 1.728us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 4.22% 26.861us 71.87% 457.101us 152.367us 3.903us 100.00% 5.183us 1.728us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 3.903us 100.00% 3.903us 1.301us 3
Activity Buffer Request 42.38% 269.577us 42.38% 269.577us 269.577us 1.280us 32.80% 1.280us 1.280us 1
aten::empty_like 1.23% 7.810us 4.48% 28.520us 9.507us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 3.26% 20.710us 3.26% 20.710us 6.903us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 25.26% 160.663us 25.26% 160.663us 53.554us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.76% 4.821us 0.76% 4.821us 4.821us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 636.037us
Self CUDA time total: 3.903us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B4_D64_S128_W4
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 120.221us 3029.76% 120.221us 120.221us 1
hf_kernels_causal_conv1d 13.01% 75.082us 99.09% 571.775us 571.775us 0.000us 0.00% 5.248us 5.248us 1
CausalConv1dFn 12.35% 71.241us 86.08% 496.693us 165.564us 0.000us 0.00% 5.248us 1.749us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 4.88% 28.181us 68.58% 395.720us 131.907us 3.968us 100.00% 5.248us 1.749us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 3.968us 100.00% 3.968us 1.323us 3
Activity Buffer Request 36.26% 209.246us 36.26% 209.246us 209.246us 1.280us 32.26% 1.280us 1.280us 1
aten::empty_like 1.42% 8.172us 5.15% 29.732us 9.911us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 3.74% 21.560us 3.74% 21.560us 7.187us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 27.43% 158.293us 27.43% 158.293us 52.764us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.91% 5.270us 0.91% 5.270us 5.270us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 577.045us
Self CUDA time total: 3.968us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B4_D64_S512_W2
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 117.374us 2843.36% 117.374us 117.374us 1
hf_kernels_causal_conv1d 14.38% 74.792us 98.97% 514.843us 514.843us 0.000us 0.00% 5.504us 5.504us 1
CausalConv1dFn 13.25% 68.940us 84.59% 440.051us 146.684us 0.000us 0.00% 5.504us 1.835us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 4.99% 25.981us 65.51% 340.779us 113.593us 4.128us 100.00% 5.504us 1.835us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 4.128us 100.00% 4.128us 1.376us 3
Activity Buffer Request 29.84% 155.214us 29.84% 155.214us 155.214us 1.376us 33.33% 1.376us 1.376us 1
aten::empty_like 1.55% 8.080us 5.83% 30.332us 10.111us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 4.28% 22.252us 4.28% 22.252us 7.417us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 30.68% 159.584us 30.68% 159.584us 53.195us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 1.03% 5.380us 1.03% 5.380us 5.380us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 520.223us
Self CUDA time total: 4.128us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B4_D64_S512_W4
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 116.831us 2875.49% 116.831us 116.831us 1
hf_kernels_causal_conv1d 13.78% 75.282us 99.09% 541.484us 541.484us 0.000us 0.00% 5.439us 5.439us 1
CausalConv1dFn 12.58% 68.741us 85.32% 466.202us 155.401us 0.000us 0.00% 5.439us 1.813us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 4.76% 26.021us 67.34% 367.980us 122.660us 4.063us 100.00% 5.439us 1.813us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 4.063us 100.00% 4.063us 1.354us 3
Activity Buffer Request 33.52% 183.175us 33.52% 183.175us 183.175us 1.376us 33.87% 1.376us 1.376us 1
aten::empty_like 1.37% 7.489us 5.40% 29.481us 9.827us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 4.02% 21.992us 4.02% 21.992us 7.331us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 29.06% 158.784us 29.06% 158.784us 52.928us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.91% 4.951us 0.91% 4.951us 4.951us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 546.435us
Self CUDA time total: 4.063us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B4_D64_S2048_W2
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 119.806us 2228.53% 119.806us 119.806us 1
hf_kernels_causal_conv1d 11.93% 76.073us 99.21% 632.507us 632.507us 0.000us 0.00% 7.200us 7.200us 1
CausalConv1dFn 11.21% 71.480us 87.28% 556.434us 185.478us 0.000us 0.00% 7.200us 2.400us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 4.13% 26.361us 71.46% 455.612us 151.871us 5.376us 100.00% 7.200us 2.400us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 5.376us 100.00% 5.376us 1.792us 3
Activity Buffer Request 42.49% 270.867us 42.49% 270.867us 270.867us 1.824us 33.93% 1.824us 1.824us 1
aten::empty_like 1.24% 7.892us 4.60% 29.342us 9.781us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 3.36% 21.450us 3.36% 21.450us 7.150us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 24.84% 158.384us 24.84% 158.384us 52.795us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.79% 5.050us 0.79% 5.050us 5.050us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 637.557us
Self CUDA time total: 5.376us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B4_D64_S2048_W4
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 119.676us 2174.35% 119.676us 119.676us 1
hf_kernels_causal_conv1d 14.25% 74.352us 99.01% 516.513us 516.513us 0.000us 0.00% 7.392us 7.392us 1
CausalConv1dFn 14.02% 73.122us 84.76% 442.161us 147.387us 0.000us 0.00% 7.392us 2.464us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 5.04% 26.281us 65.18% 340.038us 113.346us 5.504us 100.00% 7.392us 2.464us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 5.504us 100.00% 5.504us 1.835us 3
Activity Buffer Request 30.19% 157.524us 30.19% 157.524us 157.524us 1.888us 34.30% 1.888us 1.888us 1
aten::empty_like 1.50% 7.800us 5.56% 29.001us 9.667us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 4.06% 21.201us 4.06% 21.201us 7.067us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 29.95% 156.233us 29.95% 156.233us 52.078us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.99% 5.180us 0.99% 5.180us 5.180us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 521.693us
Self CUDA time total: 5.504us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B4_D2048_S128_W2
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 124.798us 715.63% 124.798us 124.798us 1
hf_kernels_causal_conv1d 11.85% 75.293us 99.15% 630.167us 630.167us 0.000us 0.00% 23.295us 23.295us 1
CausalConv1dFn 11.06% 70.310us 87.30% 554.874us 184.958us 0.000us 0.00% 23.295us 7.765us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 4.18% 26.540us 71.39% 453.732us 151.244us 17.439us 100.00% 23.295us 7.765us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 17.439us 100.00% 17.439us 5.813us 3
Activity Buffer Request 42.20% 268.237us 42.20% 268.237us 268.237us 5.856us 33.58% 5.856us 5.856us 1
aten::empty_like 1.25% 7.951us 4.85% 30.832us 10.277us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 3.60% 22.881us 3.60% 22.881us 7.627us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 25.01% 158.955us 25.01% 158.955us 52.985us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.85% 5.410us 0.85% 5.410us 5.410us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 635.577us
Self CUDA time total: 17.439us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B4_D2048_S128_W4
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 124.252us 695.89% 124.252us 124.252us 1
hf_kernels_causal_conv1d 15.28% 76.213us 99.04% 494.053us 494.053us 0.000us 0.00% 23.839us 23.839us 1
CausalConv1dFn 14.60% 72.841us 83.76% 417.840us 139.280us 0.000us 0.00% 23.839us 7.946us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 5.38% 26.851us 63.27% 315.607us 105.202us 17.855us 100.00% 23.839us 7.946us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 17.855us 100.00% 17.855us 5.952us 3
Activity Buffer Request 26.40% 131.703us 26.40% 131.703us 131.703us 5.984us 33.51% 5.984us 5.984us 1
aten::empty_like 1.62% 8.090us 5.89% 29.392us 9.797us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 4.27% 21.302us 4.27% 21.302us 7.101us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 31.48% 157.053us 31.48% 157.053us 52.351us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.96% 4.810us 0.96% 4.810us 4.810us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 498.863us
Self CUDA time total: 17.855us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B4_D2048_S512_W2
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 124.253us 695.94% 124.253us 124.253us 1
hf_kernels_causal_conv1d 14.09% 92.581us 99.22% 652.096us 652.096us 0.000us 0.00% 23.838us 23.838us 1
CausalConv1dFn 11.45% 75.254us 85.13% 559.515us 186.505us 0.000us 0.00% 23.838us 7.946us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 3.84% 25.251us 69.30% 455.481us 151.827us 17.854us 100.00% 23.838us 7.946us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 17.854us 100.00% 17.854us 5.951us 3
Activity Buffer Request 41.42% 272.247us 41.42% 272.247us 272.247us 5.984us 33.52% 5.984us 5.984us 1
aten::empty_like 1.19% 7.849us 4.38% 28.780us 9.593us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 3.18% 20.931us 3.18% 20.931us 6.977us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 24.04% 157.983us 24.04% 157.983us 52.661us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.78% 5.140us 0.78% 5.140us 5.140us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 657.236us
Self CUDA time total: 17.854us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B4_D2048_S512_W4
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 121.982us 651.61% 121.982us 121.982us 1
hf_kernels_causal_conv1d 16.26% 76.273us 99.00% 464.343us 464.343us 0.000us 0.00% 25.088us 25.088us 1
CausalConv1dFn 15.20% 71.302us 82.74% 388.070us 129.357us 0.000us 0.00% 25.088us 8.363us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 5.49% 25.750us 61.15% 286.808us 95.603us 18.720us 100.00% 25.088us 8.363us 3
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 18.720us 100.00% 18.720us 6.240us 3
Activity Buffer Request 22.13% 103.813us 22.13% 103.813us 103.813us 6.368us 34.02% 6.368us 6.368us 1
aten::empty_like 1.75% 8.210us 6.39% 29.960us 9.987us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 4.64% 21.750us 4.64% 21.750us 7.250us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 33.53% 157.245us 33.53% 157.245us 52.415us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 1.00% 4.680us 1.00% 4.680us 4.680us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 469.023us
Self CUDA time total: 18.720us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B4_D2048_S2048_W2
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 4.40% 80.973us 99.73% 1.837ms 1.837ms 0.000us 0.00% 162.749us 162.749us 1
CausalConv1dFn 4.14% 76.301us 95.33% 1.756ms 585.285us 0.000us 0.00% 162.749us 54.250us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 1.45% 26.730us 89.50% 1.648ms 549.474us 97.918us 100.00% 162.749us 54.250us 3
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 141.950us 144.97% 141.950us 141.950us 1
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 97.918us 100.00% 97.918us 32.639us 3
Activity Buffer Request 78.99% 1.455ms 78.99% 1.455ms 1.455ms 64.831us 66.21% 64.831us 64.831us 1
aten::empty_like 0.45% 8.340us 1.69% 31.131us 10.377us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 1.24% 22.791us 1.24% 22.791us 7.597us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 9.06% 166.885us 9.06% 166.885us 55.628us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 0.27% 4.980us 0.27% 4.980us 4.980us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 1.842ms
Self CUDA time total: 97.918us
======================================================================
PROFILE TRACE: hf_kernels_causal_conv1d | cuda_B4_D2048_S2048_W4
======================================================================
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
hf_kernels_causal_conv1d 16.07% 76.871us 98.94% 473.172us 473.172us 0.000us 0.00% 163.803us 163.803us 1
CausalConv1dFn 14.96% 71.532us 82.87% 396.301us 132.100us 0.000us 0.00% 163.803us 54.601us 3
_causal_conv1d_90f5a60::causal_conv1d_fwd 5.75% 27.501us 61.56% 294.418us 98.139us 98.685us 100.00% 163.803us 54.601us 3
hf_kernels_causal_conv1d 0.00% 0.000us 0.00% 0.000us 0.000us 133.180us 134.95% 133.180us 133.180us 1
void causal_conv1d_fwd_kernel&lt;Causal_conv1d_fwd_kern... 0.00% 0.000us 0.00% 0.000us 0.000us 98.685us 100.00% 98.685us 32.895us 3
Activity Buffer Request 21.65% 103.543us 21.65% 103.543us 103.543us 65.118us 65.99% 65.118us 65.118us 1
aten::empty_like 1.52% 7.251us 6.35% 30.351us 10.117us 0.000us 0.00% 0.000us 0.000us 3
aten::empty_strided 4.83% 23.100us 4.83% 23.100us 7.700us 0.000us 0.00% 0.000us 0.000us 3
cudaLaunchKernel 34.16% 163.374us 34.16% 163.374us 54.458us 0.000us 0.00% 0.000us 0.000us 3
cudaDeviceSynchronize 1.06% 5.061us 1.06% 5.061us 5.061us 0.000us 0.00% 0.000us 0.000us 1
------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
Self CPU time total: 478.233us
Self CUDA time total: 98.685us
impl wl p50(ms) ok
hf_kernels_causal_conv1d cuda_B2_D2048_S128_W2 0.05 True
hf_kernels_causal_conv1d cuda_B2_D2048_S128_W4 0.05 True
hf_kernels_causal_conv1d cuda_B2_D2048_S2048_W2 0.05 True
hf_kernels_causal_conv1d cuda_B2_D2048_S2048_W4 0.05 True
hf_kernels_causal_conv1d cuda_B2_D2048_S512_W2 0.05 True
hf_kernels_causal_conv1d cuda_B2_D2048_S512_W4 0.05 True
hf_kernels_causal_conv1d cuda_B2_D64_S128_W2 0.05 True
hf_kernels_causal_conv1d cuda_B2_D64_S128_W4 0.05 True
hf_kernels_causal_conv1d cuda_B2_D64_S2048_W2 0.05 True
hf_kernels_causal_conv1d cuda_B2_D64_S2048_W4 0.05 True
hf_kernels_causal_conv1d cuda_B2_D64_S512_W2 0.05 True
hf_kernels_causal_conv1d cuda_B2_D64_S512_W4 0.05 True
hf_kernels_causal_conv1d cuda_B4_D2048_S128_W2 0.05 True
hf_kernels_causal_conv1d cuda_B4_D2048_S128_W4 0.05 True
hf_kernels_causal_conv1d cuda_B4_D2048_S2048_W2 0.05 True
hf_kernels_causal_conv1d cuda_B4_D2048_S2048_W4 0.05 True
hf_kernels_causal_conv1d cuda_B4_D2048_S512_W2 0.05 True
hf_kernels_causal_conv1d cuda_B4_D2048_S512_W4 0.05 True
hf_kernels_causal_conv1d cuda_B4_D64_S128_W2 0.05 True
hf_kernels_causal_conv1d cuda_B4_D64_S128_W4 0.05 True
hf_kernels_causal_conv1d cuda_B4_D64_S2048_W2 0.05 True
hf_kernels_causal_conv1d cuda_B4_D64_S2048_W4 0.05 True
hf_kernels_causal_conv1d cuda_B4_D64_S512_W2 0.05 True
hf_kernels_causal_conv1d cuda_B4_D64_S512_W4 0.05 True
</pre></div>
<div class="uv-install-logs" id="uv-logs-benchmark">
<div class="uv-logs-header" onclick="toggleUvLogs(this)">▶ UV Install Logs</div>
<div class="uv-logs-content" style="display: none;">
Installed 52 packages in 240ms
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<div class="cell-stderr">Fetching 11 files: 0%| | 0/11 [00:00&lt;?, ?it/s]
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Fetching 11 files: 100%|██████████| 11/11 [00:01&lt;00:00, 7.98it/s]</div>
<div class="cell-artifacts">
<h4>Artifacts:</h4>
<a href="artifacts/benchmark/causal_conv1d.jsonl" class="artifact" target="_blank">causal_conv1d.jsonl</a>
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