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rtest

by helper2424 - opened Nov 22, 2025

base: refs/heads/main

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from: refs/pr/1

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.gitattributes +0 -1
index.html +371 -425
static/experiments/experiment_log.txt +0 -378
static/experiments/pi05_steps_100_sigma_0.1/denoising_correction_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.1/denoising_vt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.1/denoising_x1t_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.1/denoising_xt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.1/final_actions_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.1_fulltrajectory_false/denoising_correction_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.1_fulltrajectory_false/denoising_vt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.1_fulltrajectory_false/denoising_x1t_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.1_fulltrajectory_false/denoising_xt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.1_fulltrajectory_false/final_actions_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.1_fulltrajectory_true/denoising_correction_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.1_fulltrajectory_true/denoising_vt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.1_fulltrajectory_true/denoising_x1t_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.1_fulltrajectory_true/denoising_xt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.1_fulltrajectory_true/final_actions_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2/denoising_correction_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2/denoising_vt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2/denoising_x1t_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2/denoising_xt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2/final_actions_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_false/denoising_correction_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_false/denoising_vt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_false/denoising_x1t_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_false/denoising_xt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_false/final_actions_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_true/denoising_correction_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_true/denoising_vt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_true/denoising_x1t_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_true/denoising_xt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_true/final_actions_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5/denoising_correction_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5/denoising_vt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5/denoising_x1t_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5/denoising_xt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5/final_actions_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_false/denoising_correction_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_false/denoising_vt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_false/denoising_x1t_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_false/denoising_xt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_false/final_actions_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_true/denoising_correction_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_true/denoising_vt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_true/denoising_x1t_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_true/denoising_xt_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_true/final_actions_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.8/denoising_correction_comparison.png +0 -3
static/experiments/pi05_steps_100_sigma_0.8/denoising_vt_comparison.png +0 -3

.gitattributes CHANGED Viewed

@@ -46,4 +46,3 @@ static/videos/shiba.mp4 filter=lfs diff=lfs merge=lfs -text
 static/videos/steve.mp4 filter=lfs diff=lfs merge=lfs -text
 static/videos/teaser.mp4 filter=lfs diff=lfs merge=lfs -text
 static/videos/toby.mp4 filter=lfs diff=lfs merge=lfs -text
-*.png filter=lfs diff=lfs merge=lfs -text

 static/videos/steve.mp4 filter=lfs diff=lfs merge=lfs -text
 static/videos/teaser.mp4 filter=lfs diff=lfs merge=lfs -text
 static/videos/toby.mp4 filter=lfs diff=lfs merge=lfs -text

index.html CHANGED Viewed

@@ -2,170 +2,29 @@
 <html>
 <head>
   <meta charset="utf-8">
-  <meta name="description" content="Real-Time Chunking (RTC) Experiments - Flow Matching Steps and Sigma_d Parameter Analysis">
-  <meta name="keywords" content="RTC, Real-Time Chunking, LeRobot, PI0.5, SmolVLA">
   <meta name="viewport" content="width=device-width, initial-scale=1">
-  <title>RTC Experiments: Flow Matching Steps & Sigma Analysis</title>
-  <link href="https://fonts.googleapis.com/css?family=Google+Sans|Noto+Sans|Castoro" rel="stylesheet">
   <link rel="stylesheet" href="./static/css/bulma.min.css">
   <link rel="stylesheet" href="./static/css/fontawesome.all.min.css">
-  <link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/jpswalsh/academicons@1/css/academicons.min.css">
   <link rel="stylesheet" href="./static/css/index.css">
   <link rel="icon" href="./static/images/favicon.svg">
   <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.5.1/jquery.min.js"></script>
   <script defer src="./static/js/fontawesome.all.min.js"></script>
-  <style>
-    .experiment-grid {
-      display: grid;
-      grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
-      gap: 20px;
-      margin-top: 20px;
-    }
-    .experiment-card {
-      border: 1px solid #ddd;
-      border-radius: 8px;
-      padding: 15px;
-      background: white;
-      box-shadow: 0 2px 4px rgba(0,0,0,0.1);
-      transition: transform 0.2s;
-    }
-    .experiment-card:hover {
-      transform: translateY(-5px);
-      box-shadow: 0 4px 8px rgba(0,0,0,0.2);
-    }
-    .experiment-card h3 {
-      margin-bottom: 10px;
-      color: #363636;
-      font-size: 1.1rem;
-      font-weight: 600;
-    }
-    .experiment-card img {
-      width: 100%;
-      height: auto;
-      border-radius: 4px;
-      margin-bottom: 10px;
-      cursor: pointer;
-    }
-    .visualization-tabs {
-      display: flex;
-      flex-wrap: wrap;
-      gap: 5px;
-      margin-bottom: 10px;
-    }
-    .visualization-tab {
-      padding: 5px 10px;
-      background: #f5f5f5;
-      border: 1px solid #ddd;
-      border-radius: 4px;
-      cursor: pointer;
-      font-size: 0.85rem;
-      transition: all 0.2s;
-    }
-    .visualization-tab:hover {
-      background: #e8e8e8;
-    }
-    .visualization-tab.active {
-      background: #3273dc;
-      color: white;
-      border-color: #3273dc;
-    }
-    .section-header {
-      background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-      color: white;
-      padding: 20px;
-      border-radius: 8px;
-      margin-bottom: 30px;
-    }
-    .model-section {
-      margin-bottom: 60px;
-    }
-    .steps-group {
-      margin-bottom: 40px;
-      padding: 20px;
-      background: #f9f9f9;
-      border-radius: 8px;
-    }
-    .steps-group h2 {
-      color: #363636;
-      margin-bottom: 20px;
-      padding-bottom: 10px;
-      border-bottom: 2px solid #3273dc;
-    }
-    .image-modal {
-      display: none;
-      position: fixed;
-      z-index: 1000;
-      left: 0;
-      top: 0;
-      width: 100%;
-      height: 100%;
-      background-color: rgba(0,0,0,0.9);
-    }
-    .image-modal img {
-      margin: auto;
-      display: block;
-      max-width: 90%;
-      max-height: 90%;
-      position: absolute;
-      top: 50%;
-      left: 50%;
-      transform: translate(-50%, -50%);
-    }
-    .close-modal {
-      position: absolute;
-      top: 20px;
-      right: 35px;
-      color: #f1f1f1;
-      font-size: 40px;
-      font-weight: bold;
-      cursor: pointer;
-    }
-    .nav-tabs {
-      display: flex;
-      gap: 10px;
-      margin-bottom: 20px;
-      flex-wrap: wrap;
-    }
-    .nav-tab {
-      padding: 10px 20px;
-      background: #f5f5f5;
-      border: 2px solid #ddd;
-      border-radius: 6px;
-      cursor: pointer;
-      font-weight: 600;
-      transition: all 0.3s;
-    }
-    .nav-tab:hover {
-      background: #e8e8e8;
-    }
-    .nav-tab.active {
-      background: #3273dc;
-      color: white;
-      border-color: #3273dc;
-    }
-  </style>
 </head>
 <body>
@@ -174,10 +33,86 @@
     <div class="container is-max-desktop">
       <div class="columns is-centered">
         <div class="column has-text-centered">
-          <h1 class="title is-1 publication-title">Real-Time Chunking Experiments</h1>
-          <h2 class="subtitle is-3">Flow Matching Steps & Sigma_d Parameter Analysis</h2>
           <div class="is-size-5 publication-authors">
-            <span class="author-block">LeRobot RTC Integration Tests</span>
           </div>
         </div>
       </div>
@@ -185,305 +120,316 @@
   </div>
 </section>
-<section class="section">
   <div class="container is-max-desktop">
-    <div class="section-header">
-      <h2 class="title is-3" style="color: white; margin-bottom: 10px;">Experiment Overview</h2>
-      <div class="content has-text-justified" style="color: white;">
-        <p>
-          This page presents comprehensive results from Real-Time Chunking (RTC) experiments across different models,
-          flow matching steps, and sigma_d values. The experiments demonstrate how these parameters affect the
-          denoising process and final action predictions.
-        </p>
-        <p>
-          <strong>Models tested:</strong> PI0.5, SmolVLA<br>
-          <strong>Flow matching steps:</strong> 10, 20, 50, 100<br>
-          <strong>Sigma_d values:</strong> 0.1, 0.2, 0.5, 0.8, 1.0, 1.2, 1.5<br>
-          <strong>Modes:</strong> Classical RTC (fulltrajectory=false), Full Trajectory (fulltrajectory=true)
-        </p>
-        <p style="margin-top: 10px; font-size: 0.95em;">
-          <strong>Classical RTC:</strong> Uses RTC guidance during denoising with chunked trajectory processing.<br>
-          <strong>Full Trajectory:</strong> Processes the complete trajectory without chunking.
-        </p>
-      </div>
     </div>
-    <!-- Navigation Tabs -->
-    <div class="nav-tabs">
-      <div class="nav-tab active" onclick="showModel('pi05')">PI0.5 Model</div>
-      <div class="nav-tab" onclick="showModel('smolvla')">SmolVLA Model</div>
-    </div>
-    <!-- Mode Selector -->
-    <div class="nav-tabs" style="margin-top: 15px;">
-      <div class="nav-tab active" onclick="showMode('classical')">Classical RTC</div>
-      <div class="nav-tab" onclick="showMode('fulltrajectory')">Full Trajectory</div>
     </div>
-    <!-- PI0.5 Model Section -->
-    <div id="pi05-section" class="model-section">
-      <h1 class="title is-2">PI0.5 Model Results</h1>
-      <!-- Steps 2 -->
-      <div class="steps-group">
-        <h2 class="title is-3">Flow Matching Steps: 2</h2>
-        <div class="experiment-grid" id="pi05-steps-2"></div>
       </div>
-      <!-- Steps 5 -->
-      <div class="steps-group">
-        <h2 class="title is-3">Flow Matching Steps: 5</h2>
-        <div class="experiment-grid" id="pi05-steps-5"></div>
       </div>
-      <!-- Steps 10 -->
-      <div class="steps-group">
-        <h2 class="title is-3">Flow Matching Steps: 10</h2>
-        <div class="experiment-grid" id="pi05-steps-10"></div>
-      </div>
-      <!-- Steps 20 -->
-      <div class="steps-group">
-        <h2 class="title is-3">Flow Matching Steps: 20</h2>
-        <div class="experiment-grid" id="pi05-steps-20"></div>
-      </div>
-      <!-- Steps 50 -->
-      <div class="steps-group">
-        <h2 class="title is-3">Flow Matching Steps: 50</h2>
-        <div class="experiment-grid" id="pi05-steps-50"></div>
       </div>
-      <!-- Steps 100 -->
-      <div class="steps-group">
-        <h2 class="title is-3">Flow Matching Steps: 100</h2>
-        <div class="experiment-grid" id="pi05-steps-100"></div>
       </div>
     </div>
-    <!-- SmolVLA Model Section -->
-    <div id="smolvla-section" class="model-section" style="display: none;">
-      <h1 class="title is-2">SmolVLA Model Results</h1>
-      <!-- Steps 2 -->
-      <div class="steps-group">
-        <h2 class="title is-3">Flow Matching Steps: 2</h2>
-        <div class="experiment-grid" id="smolvla-steps-2"></div>
-      </div>
-      <!-- Steps 5 -->
-      <div class="steps-group">
-        <h2 class="title is-3">Flow Matching Steps: 5</h2>
-        <div class="experiment-grid" id="smolvla-steps-5"></div>
       </div>
-      <!-- Steps 10 -->
-      <div class="steps-group">
-        <h2 class="title is-3">Flow Matching Steps: 10</h2>
-        <div class="experiment-grid" id="smolvla-steps-10"></div>
       </div>
-      <!-- Steps 20 -->
-      <div class="steps-group">
-        <h2 class="title is-3">Flow Matching Steps: 20</h2>
-        <div class="experiment-grid" id="smolvla-steps-20"></div>
-      </div>
-      <!-- Steps 50 -->
-      <div class="steps-group">
-        <h2 class="title is-3">Flow Matching Steps: 50</h2>
-        <div class="experiment-grid" id="smolvla-steps-50"></div>
-      </div>
-      <!-- Steps 100 -->
-      <div class="steps-group">
-        <h2 class="title is-3">Flow Matching Steps: 100</h2>
-        <div class="experiment-grid" id="smolvla-steps-100"></div>
-      </div>
-    </div>
   </div>
 </section>
-<!-- Image Modal -->
-<div id="imageModal" class="image-modal" onclick="closeModal()">
-  <span class="close-modal">&times;</span>
-  <img id="modalImage" src="">
-</div>
 <footer class="footer">
   <div class="container">
     <div class="content has-text-centered">
-      <p>
-        RTC Experiments for LeRobot - Real-Time Chunking Integration
-      </p>
     </div>
   </div>
 </footer>
-<script>
-  // Global state
-  let currentMode = 'classical'; // 'classical' or 'fulltrajectory'
-  // Experiment data structure
-  // Only steps 10, 20, 50, 100 have fulltrajectory mode experiments
-  const experiments = {
-    pi05: {
-      10: ['0.1', '0.2', '0.5', '0.8', '1.0', '1.2', '1.5'],
-      20: ['0.1', '0.2', '0.5', '0.8', '1.0', '1.2', '1.5'],
-      50: ['0.1', '0.2', '0.5', '0.8', '1.0', '1.2', '1.5'],
-      100: ['0.1', '0.2', '0.5', '0.8', '1.0', '1.2', '1.5']
-    },
-    smolvla: {
-      10: ['0.1', '0.2', '0.5', '0.8', '1.0', '1.2', '1.5'],
-      20: ['0.1', '0.2', '0.5', '0.8', '1.0', '1.2', '1.5'],
-      50: ['0.1', '0.2', '0.5', '0.8', '1.0', '1.2', '1.5'],
-      100: ['0.1', '0.2', '0.5', '0.8', '1.0', '1.2', '1.5']
-    }
-  };
-  const visualizations = {
-    'final': 'final_actions_comparison.png',
-    'xt': 'denoising_xt_comparison.png',
-    'vt': 'denoising_vt_comparison.png',
-    'x1t': 'denoising_x1t_comparison.png',
-    'correction': 'denoising_correction_comparison.png'
-  };
-  const visualizationNames = {
-    'final': 'Final Actions',
-    'xt': 'X_t',
-    'vt': 'V_t (Velocity)',
-    'x1t': 'X1_t',
-    'correction': 'Correction'
-  };
-  // Generate experiment cards
-  function generateExperimentCards() {
-    for (const model in experiments) {
-      for (const steps in experiments[model]) {
-        const sigmas = experiments[model][steps];
-        const gridId = `${model}-steps-${steps}`;
-        const grid = document.getElementById(gridId);
-        if (!grid) continue;
-        sigmas.forEach(sigma => {
-          const card = createExperimentCard(model, steps, sigma);
-          grid.appendChild(card);
-        });
-      }
-    }
-  }
-  function createExperimentCard(model, steps, sigma) {
-    const card = document.createElement('div');
-    card.className = 'experiment-card';
-    const title = document.createElement('h3');
-    title.textContent = `Sigma_d: ${sigma}`;
-    card.appendChild(title);
-    // Create visualization tabs
-    const tabs = document.createElement('div');
-    tabs.className = 'visualization-tabs';
-    let firstTab = true;
-    for (const vizKey in visualizations) {
-      const tab = document.createElement('div');
-      tab.className = 'visualization-tab' + (firstTab ? ' active' : '');
-      tab.textContent = visualizationNames[vizKey];
-      tab.onclick = () => switchVisualization(card, model, steps, sigma, vizKey);
-      tabs.appendChild(tab);
-      firstTab = false;
-    }
-    card.appendChild(tabs);
-    // Create image element
-    const img = document.createElement('img');
-    const modeSuffix = currentMode === 'classical' ? '_fulltrajectory_false' : '_fulltrajectory_true';
-    const expPath = `./static/experiments/${model}_steps_${steps}_sigma_${sigma}${modeSuffix}`;
-    img.src = `${expPath}/${visualizations['final']}`;
-    img.alt = `${model} - Steps: ${steps}, Sigma: ${sigma} - ${currentMode === 'classical' ? 'Classical RTC' : 'Full Trajectory'}`;
-    img.onclick = () => openModal(img.src);
-    card.appendChild(img);
-    return card;
-  }
-  function switchVisualization(card, model, steps, sigma, vizKey) {
-    // Update active tab
-    const tabs = card.querySelectorAll('.visualization-tab');
-    tabs.forEach(tab => {
-      tab.classList.remove('active');
-      if (tab.textContent === visualizationNames[vizKey]) {
-        tab.classList.add('active');
-      }
-    });
-    // Update image
-    const img = card.querySelector('img');
-    const modeSuffix = currentMode === 'classical' ? '_fulltrajectory_false' : '_fulltrajectory_true';
-    const expPath = `./static/experiments/${model}_steps_${steps}_sigma_${sigma}${modeSuffix}`;
-    img.src = `${expPath}/${visualizations[vizKey]}`;
-  }
-  function showModel(model) {
-    // Update nav tabs (only in the first nav-tabs div)
-    const modelTabs = document.querySelectorAll('.nav-tabs')[0].querySelectorAll('.nav-tab');
-    modelTabs.forEach(tab => {
-      tab.classList.remove('active');
-      if (tab.textContent.toLowerCase().includes(model.replace('smolvla', 'smol'))) {
-        tab.classList.add('active');
-      }
-    });
-    // Show/hide sections
-    document.getElementById('pi05-section').style.display = model === 'pi05' ? 'block' : 'none';
-    document.getElementById('smolvla-section').style.display = model === 'smolvla' ? 'block' : 'none';
-  }
-  function showMode(mode) {
-    // Update mode
-    currentMode = mode;
-    // Update nav tabs (only in the second nav-tabs div)
-    const modeTabs = document.querySelectorAll('.nav-tabs')[1].querySelectorAll('.nav-tab');
-    modeTabs.forEach(tab => {
-      tab.classList.remove('active');
-      if ((mode === 'classical' && tab.textContent.includes('Classical')) ||
-          (mode === 'fulltrajectory' && tab.textContent.includes('Full Trajectory'))) {
-        tab.classList.add('active');
-      }
-    });
-    // Regenerate all experiment cards with new mode
-    document.querySelectorAll('.experiment-grid').forEach(grid => {
-      grid.innerHTML = '';
-    });
-    generateExperimentCards();
-  }
-  function openModal(src) {
-    const modal = document.getElementById('imageModal');
-    const modalImg = document.getElementById('modalImage');
-    modal.style.display = 'block';
-    modalImg.src = src;
-  }
-  function closeModal() {
-    document.getElementById('imageModal').style.display = 'none';
-  }
-  // Close modal with Escape key
-  document.addEventListener('keydown', function(event) {
-    if (event.key === 'Escape') {
-      closeModal();
-    }
-  });
-  // Initialize
-  generateExperimentCards();
-</script>
 </body>
 </html>

 <html>
 <head>
   <meta charset="utf-8">
+  <meta name="description"
+        content="Deformable Neural Radiance Fields creates free-viewpoint portraits (nerfies) from casually captured videos.">
+  <meta name="keywords" content="Nerfies, D-NeRF, NeRF">
   <meta name="viewport" content="width=device-width, initial-scale=1">
+  <title>Nerfies: Deformable Neural Radiance Fields</title>
+  <link href="https://fonts.googleapis.com/css?family=Google+Sans|Noto+Sans|Castoro"
+        rel="stylesheet">
   <link rel="stylesheet" href="./static/css/bulma.min.css">
+  <link rel="stylesheet" href="./static/css/bulma-carousel.min.css">
+  <link rel="stylesheet" href="./static/css/bulma-slider.min.css">
   <link rel="stylesheet" href="./static/css/fontawesome.all.min.css">
+  <link rel="stylesheet"
+        href="https://cdn.jsdelivr.net/gh/jpswalsh/academicons@1/css/academicons.min.css">
   <link rel="stylesheet" href="./static/css/index.css">
   <link rel="icon" href="./static/images/favicon.svg">
   <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.5.1/jquery.min.js"></script>
   <script defer src="./static/js/fontawesome.all.min.js"></script>
+  <script src="./static/js/bulma-carousel.min.js"></script>
+  <script src="./static/js/bulma-slider.min.js"></script>
+  <script src="./static/js/index.js"></script>
 </head>
 <body>
     <div class="container is-max-desktop">
       <div class="columns is-centered">
         <div class="column has-text-centered">
+          <h1 class="title is-1 publication-title">Nerfies: Deformable Neural Radiance Fields</h1>
+          <div class="is-size-5 publication-authors">
+            <span class="author-block">
+              <a href="https://keunhong.com" target="_blank">Keunhong Park</a><sup>1</sup>,</span>
+            <span class="author-block">
+              <a href="https://utkarshsinha.com" target="_blank">Utkarsh Sinha</a><sup>2</sup>,</span>
+            <span class="author-block">
+              <a href="https://jonbarron.info" target="_blank">Jonathan T. Barron</a><sup>2</sup>,
+            </span>
+            <span class="author-block">
+              <a href="http://sofienbouaziz.com" target="_blank">Sofien Bouaziz</a><sup>2</sup>,
+            </span>
+            <span class="author-block">
+              <a href="https://www.danbgoldman.com" target="_blank">Dan B Goldman</a><sup>2</sup>,
+            </span>
+            <span class="author-block">
+              <a href="https://homes.cs.washington.edu/~seitz/" target="_blank">Steven M. Seitz</a><sup>1,2</sup>,
+            </span>
+            <span class="author-block">
+              <a href="http://www.ricardomartinbrualla.com" target="_blank">Ricardo Martin-Brualla</a><sup>2</sup>
+            </span>
+          </div>
           <div class="is-size-5 publication-authors">
+            <span class="author-block"><sup>1</sup>University of Washington,</span>
+            <span class="author-block"><sup>2</sup>Google Research</span>
+          </div>
+          <div class="column has-text-centered">
+            <div class="publication-links">
+              <!-- PDF Link. -->
+              <span class="link-block">
+                <a href="https://arxiv.org/pdf/2011.12948" target="_blank"
+                   class="external-link button is-normal is-rounded is-dark">
+                  <span class="icon">
+                      <i class="fas fa-file-pdf"></i>
+                  </span>
+                  <span>Paper</span>
+                </a>
+              </span>
+              <span class="link-block">
+                <a href="https://arxiv.org/abs/2011.12948" target="_blank"
+                   class="external-link button is-normal is-rounded is-dark">
+                  <span class="icon">
+                      <i class="ai ai-arxiv"></i>
+                  </span>
+                  <span>arXiv</span>
+                </a>
+              </span>
+              <!-- Video Link. -->
+              <span class="link-block">
+                <a href="https://www.youtube.com/watch?v=MrKrnHhk8IA" target="_blank"
+                   class="external-link button is-normal is-rounded is-dark">
+                  <span class="icon">
+                      <i class="fab fa-youtube"></i>
+                  </span>
+                  <span>Video</span>
+                </a>
+              </span>
+              <!-- Code Link. -->
+              <span class="link-block">
+                <a href="https://github.com/google/nerfies" target="_blank"
+                   class="external-link button is-normal is-rounded is-dark">
+                  <span class="icon">
+                      <i class="fab fa-github"></i>
+                  </span>
+                  <span>Code</span>
+                  </a>
+              </span>
+              <!-- Dataset Link. -->
+              <span class="link-block">
+                <a href="https://github.com/google/nerfies/releases/tag/0.1" target="_blank"
+                   class="external-link button is-normal is-rounded is-dark">
+                  <span class="icon">
+                      <i class="far fa-images"></i>
+                  </span>
+                  <span>Data</span>
+                  </a>
+            </div>
           </div>
         </div>
       </div>
   </div>
 </section>
+<section class="hero teaser">
   <div class="container is-max-desktop">
+    <div class="hero-body">
+      <video id="teaser" autoplay muted loop playsinline height="100%">
+        <source src="./static/videos/teaser.mp4"
+                type="video/mp4">
+      </video>
+      <h2 class="subtitle has-text-centered">
+        <span class="dnerf">Nerfies</span> turns selfie videos from your phone into
+        free-viewpoint
+        portraits.
+      </h2>
     </div>
+  </div>
+</section>
+<section class="hero is-light is-small">
+  <div class="hero-body">
+    <div class="container">
+      <div id="results-carousel" class="carousel results-carousel">
+        <div class="item item-steve">
+          <video poster="" id="steve" autoplay controls muted loop playsinline height="100%">
+            <source src="./static/videos/steve.mp4"
+                    type="video/mp4">
+          </video>
+        </div>
+        <div class="item item-chair-tp">
+          <video poster="" id="chair-tp" autoplay controls muted loop playsinline height="100%">
+            <source src="./static/videos/chair-tp.mp4"
+                    type="video/mp4">
+          </video>
+        </div>
+        <div class="item item-shiba">
+          <video poster="" id="shiba" autoplay controls muted loop playsinline height="100%">
+            <source src="./static/videos/shiba.mp4"
+                    type="video/mp4">
+          </video>
+        </div>
+        <div class="item item-fullbody">
+          <video poster="" id="fullbody" autoplay controls muted loop playsinline height="100%">
+            <source src="./static/videos/fullbody.mp4"
+                    type="video/mp4">
+          </video>
+        </div>
+        <div class="item item-blueshirt">
+          <video poster="" id="blueshirt" autoplay controls muted loop playsinline height="100%">
+            <source src="./static/videos/blueshirt.mp4"
+                    type="video/mp4">
+          </video>
+        </div>
+        <div class="item item-mask">
+          <video poster="" id="mask" autoplay controls muted loop playsinline height="100%">
+            <source src="./static/videos/mask.mp4"
+                    type="video/mp4">
+          </video>
+        </div>
+        <div class="item item-coffee">
+          <video poster="" id="coffee" autoplay controls muted loop playsinline height="100%">
+            <source src="./static/videos/coffee.mp4"
+                    type="video/mp4">
+          </video>
+        </div>
+        <div class="item item-toby">
+          <video poster="" id="toby" autoplay controls muted loop playsinline height="100%">
+            <source src="./static/videos/toby2.mp4"
+                    type="video/mp4">
+          </video>
+        </div>
+      </div>
     </div>
+  </div>
+</section>
+<section class="section">
+  <div class="container is-max-desktop">
+    <!-- Abstract. -->
+    <div class="columns is-centered has-text-centered">
+      <div class="column is-four-fifths">
+        <h2 class="title is-3">Abstract</h2>
+        <div class="content has-text-justified">
+          <p>
+            We present the first method capable of photorealistically reconstructing a non-rigidly
+            deforming scene using photos/videos captured casually from mobile phones.
+          </p>
+          <p>
+            Our approach augments neural radiance fields
+            (NeRF) by optimizing an
+            additional continuous volumetric deformation field that warps each observed point into a
+            canonical 5D NeRF.
+            We observe that these NeRF-like deformation fields are prone to local minima, and
+            propose a coarse-to-fine optimization method for coordinate-based models that allows for
+            more robust optimization.
+            By adapting principles from geometry processing and physical simulation to NeRF-like
+            models, we propose an elastic regularization of the deformation field that further
+            improves robustness.
+          </p>
+          <p>
+            We show that <span class="dnerf">Nerfies</span> can turn casually captured selfie
+            photos/videos into deformable NeRF
+            models that allow for photorealistic renderings of the subject from arbitrary
+            viewpoints, which we dub <i>"nerfies"</i>. We evaluate our method by collecting data
+            using a
+            rig with two mobile phones that take time-synchronized photos, yielding train/validation
+            images of the same pose at different viewpoints. We show that our method faithfully
+            reconstructs non-rigidly deforming scenes and reproduces unseen views with high
+            fidelity.
+          </p>
+        </div>
       </div>
+    </div>
+    <!--/ Abstract. -->
+    <!-- Paper video. -->
+    <div class="columns is-centered has-text-centered">
+      <div class="column is-four-fifths">
+        <h2 class="title is-3">Video</h2>
+        <div class="publication-video">
+          <iframe src="https://www.youtube.com/embed/MrKrnHhk8IA?rel=0&amp;showinfo=0"
+                  frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
+        </div>
       </div>
+    </div>
+    <!--/ Paper video. -->
+  </div>
+</section>
+<section class="section">
+  <div class="container is-max-desktop">
+    <div class="columns is-centered">
+      <!-- Visual Effects. -->
+      <div class="column">
+        <div class="content">
+          <h2 class="title is-3">Visual Effects</h2>
+          <p>
+            Using <i>nerfies</i> you can create fun visual effects. This Dolly zoom effect
+            would be impossible without nerfies since it would require going through a wall.
+          </p>
+          <video id="dollyzoom" autoplay controls muted loop playsinline height="100%">
+            <source src="./static/videos/dollyzoom-stacked.mp4"
+                    type="video/mp4">
+          </video>
+        </div>
       </div>
+      <!--/ Visual Effects. -->
+      <!-- Matting. -->
+      <div class="column">
+        <h2 class="title is-3">Matting</h2>
+        <div class="columns is-centered">
+          <div class="column content">
+            <p>
+              As a byproduct of our method, we can also solve the matting problem by ignoring
+              samples that fall outside of a bounding box during rendering.
+            </p>
+            <video id="matting-video" controls playsinline height="100%">
+              <source src="./static/videos/matting.mp4"
+                      type="video/mp4">
+            </video>
+          </div>
+        </div>
       </div>
     </div>
+    <!--/ Matting. -->
+    <!-- Animation. -->
+    <div class="columns is-centered">
+      <div class="column is-full-width">
+        <h2 class="title is-3">Animation</h2>
+        <!-- Interpolating. -->
+        <h3 class="title is-4">Interpolating states</h3>
+        <div class="content has-text-justified">
+          <p>
+            We can also animate the scene by interpolating the deformation latent codes of two input
+            frames. Use the slider here to linearly interpolate between the left frame and the right
+            frame.
+          </p>
+        </div>
+        <div class="columns is-vcentered interpolation-panel">
+          <div class="column is-3 has-text-centered">
+            <img src="./static/images/interpolate_start.jpg"
+                 class="interpolation-image"
+                 alt="Interpolate start reference image."/>
+            <p>Start Frame</p>
+          </div>
+          <div class="column interpolation-video-column">
+            <div id="interpolation-image-wrapper">
+              Loading...
+            </div>
+            <input class="slider is-fullwidth is-large is-info"
+                   id="interpolation-slider"
+                   step="1" min="0" max="100" value="0" type="range">
+          </div>
+          <div class="column is-3 has-text-centered">
+            <img src="./static/images/interpolate_end.jpg"
+                 class="interpolation-image"
+                 alt="Interpolation end reference image."/>
+            <p class="is-bold">End Frame</p>
+          </div>
+        </div>
+        <br/>
+        <!--/ Interpolating. -->
+        <!-- Re-rendering. -->
+        <h3 class="title is-4">Re-rendering the input video</h3>
+        <div class="content has-text-justified">
+          <p>
+            Using <span class="dnerf">Nerfies</span>, you can re-render a video from a novel
+            viewpoint such as a stabilized camera by playing back the training deformations.
+          </p>
+        </div>
+        <div class="content has-text-centered">
+          <video id="replay-video"
+                 controls
+                 muted
+                 preload
+                 playsinline
+                 width="75%">
+            <source src="./static/videos/replay.mp4"
+                    type="video/mp4">
+          </video>
+        </div>
+        <!--/ Re-rendering. -->
       </div>
+    </div>
+    <!--/ Animation. -->
+    <!-- Concurrent Work. -->
+    <div class="columns is-centered">
+      <div class="column is-full-width">
+        <h2 class="title is-3">Related Links</h2>
+        <div class="content has-text-justified">
+          <p>
+            There's a lot of excellent work that was introduced around the same time as ours.
+          </p>
+          <p>
+            <a href="https://arxiv.org/abs/2104.09125" target="_blank">Progressive Encoding for Neural Optimization</a> introduces an idea similar to our windowed position encoding for coarse-to-fine optimization.
+          </p>
+          <p>
+            <a href="https://www.albertpumarola.com/research/D-NeRF/index.html" target="_blank">D-NeRF</a> and <a href="https://gvv.mpi-inf.mpg.de/projects/nonrigid_nerf/" target="_blank">NR-NeRF</a>
+            both use deformation fields to model non-rigid scenes.
+          </p>
+          <p>
+            Some works model videos with a NeRF by directly modulating the density, such as <a href="https://video-nerf.github.io/" target="_blank">Video-NeRF</a>, <a href="https://www.cs.cornell.edu/~zl548/NSFF/" target="_blank">NSFF</a>, and <a href="https://neural-3d-video.github.io/" target="_blank">DyNeRF</a>
+          </p>
+          <p>
+            There are probably many more by the time you are reading this. Check out <a href="https://dellaert.github.io/NeRF/" target="_blank">Frank Dellart's survey on recent NeRF papers</a>, and <a href="https://github.com/yenchenlin/awesome-NeRF" target="_blank">Yen-Chen Lin's curated list of NeRF papers</a>.
+          </p>
+        </div>
       </div>
+    </div>
+    <!--/ Concurrent Work. -->
+  </div>
+</section>
+<section class="section" id="BibTeX">
+  <div class="container is-max-desktop content">
+    <h2 class="title">BibTeX</h2>
+    <pre><code>@article{park2021nerfies,
+  author    = {Park, Keunhong and Sinha, Utkarsh and Barron, Jonathan T. and Bouaziz, Sofien and Goldman, Dan B and Seitz, Steven M. and Martin-Brualla, Ricardo},
+  title     = {Nerfies: Deformable Neural Radiance Fields},
+  journal   = {ICCV},
+  year      = {2021},
+}</code></pre>
   </div>
 </section>
 <footer class="footer">
   <div class="container">
     <div class="content has-text-centered">
+      <a class="icon-link" target="_blank"
+         href="./static/videos/nerfies_paper.pdf">
+        <i class="fas fa-file-pdf"></i>
+      </a>
+      <a class="icon-link" href="https://github.com/keunhong" target="_blank" class="external-link" disabled>
+        <i class="fab fa-github"></i>
+      </a>
+    </div>
+    <div class="columns is-centered">
+      <div class="column is-8">
+        <div class="content">
+          <p>
+            This website is licensed under a <a rel="license" target="_blank"
+                                                href="http://creativecommons.org/licenses/by-sa/4.0/">Creative
+            Commons Attribution-ShareAlike 4.0 International License</a>.
+          </p>
+          <p>
+            This means you are free to borrow the <a target="_blank"
+              href="https://github.com/nerfies/nerfies.github.io">source code</a> of this website,
+            we just ask that you link back to this page in the footer.
+            Please remember to remove the analytics code included in the header of the website which
+            you do not want on your website.
+          </p>
+        </div>
+      </div>
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static/experiments/experiment_log.txt DELETED Viewed

@@ -1,378 +0,0 @@
-RTC Evaluation Experiments - Sat Nov 22 23:39:40 +07 2025
-======================================
-Sat Nov 22 23:39:40 +07 2025: Starting pi05 steps=10 sigma_d=0.1
-WARNING:lerobot.configs.policies:Device 'cuda' is not available. Switching to 'mps'.
-WARNING:lerobot.configs.policies:Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:39:46 _dataset.py:959 ================================================================================
-INFO 2025-11-22 23:39:46 _dataset.py:960 RTC Dataset Evaluation
-INFO 2025-11-22 23:39:46 _dataset.py:961 Config: RTCEvalConfig(policy=PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=<FeatureType.STATE: 'STATE'>, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=<FeatureType.ACTION: 'ACTION'>, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path='lerobot/pi05_libero_finetuned', paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=None, image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'VISUAL': <NormalizationMode.IDENTITY: 'IDENTITY'>}, gradient_checkpointing=True, compile_model=True, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06), dataset=DatasetConfig(repo_id='HuggingFaceVLA/libero', root=None, episodes=None, image_transforms=ImageTransformsConfig(enable=False, max_num_transforms=3, random_order=False, tfs={'brightness': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'brightness': (0.8, 1.2)}), 'contrast': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'contrast': (0.8, 1.2)}), 'saturation': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'saturation': (0.5, 1.5)}), 'hue': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'hue': (-0.05, 0.05)}), 'sharpness': ImageTransformConfig(weight=1.0, type='SharpnessJitter', kwargs={'sharpness': (0.5, 1.5)}), 'affine': ImageTransformConfig(weight=1.0, type='RandomAffine', kwargs={'degrees': (-5.0, 5.0), 'translate': (0.05, 0.05)})}), revision=None, use_imagenet_stats=True, video_backend='torchcodec', streaming=False), rtc=RTCConfig(enabled=False, prefix_attention_schedule=<RTCAttentionSchedule.EXP: 'EXP'>, max_guidance_weight=None, execution_horizon=8, sigma_d=0.1, debug=False, debug_maxlen=100), device='mps', output_dir='rtc_experiments_results/pi05_steps_10_sigma_0.1', seed=10, inference_delay=4, num_inference_steps=10, use_torch_compile=False, torch_compile_backend='inductor', torch_compile_mode='default', torch_compile_disable_cudagraphs=True)
-INFO 2025-11-22 23:39:46 _dataset.py:962 ================================================================================
-INFO 2025-11-22 23:39:46 _dataset.py:256 Loading dataset: HuggingFaceVLA/libero
-INFO 2025-11-22 23:39:46 _dataset.py:269 Dataset loaded: 273465 samples, 1693 episodes
-INFO 2025-11-22 23:39:49 _dataset.py:280 ================================================================================
-INFO 2025-11-22 23:39:49 _dataset.py:281 Ready to run evaluation with sequential policy loading:
-INFO 2025-11-22 23:39:49 _dataset.py:282   1. policy_prev_chunk - Generate reference chunk, then destroy
-INFO 2025-11-22 23:39:49 _dataset.py:283   2. policy_no_rtc - Generate without RTC, then destroy
-INFO 2025-11-22 23:39:49 _dataset.py:284   3. policy_rtc - Generate with RTC, then destroy
-INFO 2025-11-22 23:39:49 _dataset.py:285   Note: Only one policy in memory at a time for efficient memory usage
-INFO 2025-11-22 23:39:49 _dataset.py:286 ================================================================================
-INFO 2025-11-22 23:39:49 _dataset.py:445 Output directory: rtc_experiments_results/pi05_steps_10_sigma_0.1
-INFO 2025-11-22 23:39:49 _dataset.py:447 ================================================================================
-INFO 2025-11-22 23:39:49 _dataset.py:448 Starting RTC evaluation
-INFO 2025-11-22 23:39:49 _dataset.py:449 Inference delay: 4
-INFO 2025-11-22 23:39:49 _dataset.py:451 Number of flow matching steps: 10
-INFO 2025-11-22 23:39:49 _dataset.py:454 ================================================================================
-INFO 2025-11-22 23:39:49 _dataset.py:469 ================================================================================
-INFO 2025-11-22 23:39:49 _dataset.py:470 Step 1: Generating previous chunk with policy_prev_chunk
-INFO 2025-11-22 23:39:49 _dataset.py:471 ================================================================================
-INFO 2025-11-22 23:39:49 _dataset.py:299 Initializing policy_prev_chunk...
-INFO 2025-11-22 23:39:49 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:39:49 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:39:49 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:39:49 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:39:49 _dataset.py:316   Overriding num_inference_steps for pi05: 10
-INFO 2025-11-22 23:40:58 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model
-WARNING 2025-11-22 23:41:01 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias
-WARNING 2025-11-22 23:41:01 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight
-INFO 2025-11-22 23:41:02 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC
-INFO 2025-11-22 23:41:02 _dataset.py:336   RTC enabled: False
-INFO 2025-11-22 23:41:02 _dataset.py:337   RTC debug: False
-INFO 2025-11-22 23:41:02 _dataset.py:338   Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=<FeatureType.STATE: 'STATE'>, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=<FeatureType.ACTION: 'ACTION'>, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=False, prefix_attention_schedule=<RTCAttentionSchedule.EXP: 'EXP'>, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=False, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'VISUAL': <NormalizationMode.IDENTITY: 'IDENTITY'>}, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06)
-INFO 2025-11-22 23:41:02 _dataset.py:344 ✓ policy_prev_chunk initialized successfully
-INFO 2025-11-22 23:41:04 _dataset.py:483   Generated prev_chunk shape: torch.Size([25, 7])
-INFO 2025-11-22 23:41:04 _dataset.py:410   Destroying policy_prev_chunk and freeing memory...
-INFO 2025-11-22 23:41:05 _dataset.py:430   ✓ policy_prev_chunk destroyed and memory freed
-INFO 2025-11-22 23:41:05 _dataset.py:491 ================================================================================
-INFO 2025-11-22 23:41:05 _dataset.py:492 Step 2: Generating actions WITHOUT RTC with policy_no_rtc
-INFO 2025-11-22 23:41:05 _dataset.py:493 ================================================================================
-INFO 2025-11-22 23:41:05 _dataset.py:299 Initializing policy_no_rtc...
-INFO 2025-11-22 23:41:07 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:41:07 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:41:07 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:41:07 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:41:07 _dataset.py:316   Overriding num_inference_steps for pi05: 10
-INFO 2025-11-22 23:42:17 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model
-WARNING 2025-11-22 23:42:19 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias
-WARNING 2025-11-22 23:42:19 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight
-INFO 2025-11-22 23:42:25 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC
-INFO 2025-11-22 23:42:25 _dataset.py:336   RTC enabled: False
-INFO 2025-11-22 23:42:25 _dataset.py:337   RTC debug: True
-INFO 2025-11-22 23:42:25 _dataset.py:338   Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=<FeatureType.STATE: 'STATE'>, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=<FeatureType.ACTION: 'ACTION'>, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=False, prefix_attention_schedule=<RTCAttentionSchedule.EXP: 'EXP'>, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=True, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'VISUAL': <NormalizationMode.IDENTITY: 'IDENTITY'>}, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06)
-INFO 2025-11-22 23:42:25 _dataset.py:344 ✓ policy_no_rtc initialized successfully
-INFO 2025-11-22 23:42:28 _dataset.py:515   Tracked 10 steps without RTC
-INFO 2025-11-22 23:42:28 _dataset.py:516   Generated no_rtc_actions shape: torch.Size([1, 50, 7])
-INFO 2025-11-22 23:42:28 _dataset.py:410   Destroying policy_no_rtc and freeing memory...
-INFO 2025-11-22 23:42:30 _dataset.py:430   ✓ policy_no_rtc destroyed and memory freed
-INFO 2025-11-22 23:42:30 _dataset.py:524 ================================================================================
-INFO 2025-11-22 23:42:30 _dataset.py:525 Step 3: Generating actions WITH RTC with policy_rtc
-INFO 2025-11-22 23:42:30 _dataset.py:526 ================================================================================
-INFO 2025-11-22 23:42:30 _dataset.py:299 Initializing policy_rtc...
-INFO 2025-11-22 23:42:31 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:42:31 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:42:31 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:42:31 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:42:31 _dataset.py:316   Overriding num_inference_steps for pi05: 10
-INFO 2025-11-22 23:43:39 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model
-WARNING 2025-11-22 23:43:41 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias
-WARNING 2025-11-22 23:43:41 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight
-INFO 2025-11-22 23:43:56 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC
-INFO 2025-11-22 23:43:56 _dataset.py:336   RTC enabled: True
-INFO 2025-11-22 23:43:56 _dataset.py:337   RTC debug: True
-INFO 2025-11-22 23:43:56 _dataset.py:338   Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=<FeatureType.STATE: 'STATE'>, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=<FeatureType.ACTION: 'ACTION'>, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=True, prefix_attention_schedule=<RTCAttentionSchedule.EXP: 'EXP'>, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=True, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'VISUAL': <NormalizationMode.IDENTITY: 'IDENTITY'>}, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06)
-INFO 2025-11-22 23:43:56 _dataset.py:344 ✓ policy_rtc initialized successfully
-INFO 2025-11-22 23:43:59 _dataset.py:546   Tracked 10 steps with RTC
-INFO 2025-11-22 23:43:59 _dataset.py:547   Generated rtc_actions shape: torch.Size([1, 50, 7])
-ERROR 2025-11-22 23:43:59 _dataset.py:553   Error getting num_steps: 'PI05Config' object has no attribute 'num_steps'
-WARNING 2025-11-22 23:43:59 _dataset.py:555   Using num_inference_steps: 10 instead of num_steps
-INFO 2025-11-22 23:43:59 _dataset.py:410   Destroying policy_rtc and freeing memory...
-INFO 2025-11-22 23:44:01 _dataset.py:430   ✓ policy_rtc destroyed and memory freed
-INFO 2025-11-22 23:44:01 _dataset.py:561 ================================================================================
-INFO 2025-11-22 23:44:01 _dataset.py:562 Plotting results...
-INFO 2025-11-22 23:44:01 _dataset.py:818 ================================================================================
-INFO 2025-11-22 23:44:01 _dataset.py:819 Plotting 10 steps
-INFO 2025-11-22 23:44:02 _dataset.py:818 ================================================================================
-INFO 2025-11-22 23:44:02 _dataset.py:819 Plotting 10 steps
-INFO 2025-11-22 23:44:02 _dataset.py:905 Plotting final no-RTC x_t step as orange dashed reference
-INFO 2025-11-22 23:44:03 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.1/denoising_xt_comparison.png
-INFO 2025-11-22 23:44:03 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.1/denoising_vt_comparison.png
-INFO 2025-11-22 23:44:04 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.1/denoising_correction_comparison.png
-INFO 2025-11-22 23:44:05 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.1/denoising_x1t_comparison.png
-INFO 2025-11-22 23:44:05 _dataset.py:566 ================================================================================
-INFO 2025-11-22 23:44:05 _dataset.py:567 Plotting final actions comparison...
-INFO 2025-11-22 23:44:05 _dataset.py:687 Saved final actions comparison to rtc_experiments_results/pi05_steps_10_sigma_0.1/final_actions_comparison.png
-INFO 2025-11-22 23:44:05 _dataset.py:570 ================================================================================
-INFO 2025-11-22 23:44:05 _dataset.py:571 Evaluation completed successfully
-The PI05 model is a direct port of the OpenPI implementation.
-This implementation follows the original OpenPI structure for compatibility.
-Original implementation: https://github.com/Physical-Intelligence/openpi
-Loading model from: lerobot/pi05_libero_finetuned
-✓ Loaded state dict from model.safetensors
-Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy:
-	Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight".
-The PI05 model is a direct port of the OpenPI implementation.
-This implementation follows the original OpenPI structure for compatibility.
-Original implementation: https://github.com/Physical-Intelligence/openpi
-Loading model from: lerobot/pi05_libero_finetuned
-✓ Loaded state dict from model.safetensors
-Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy:
-	Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight".
-The PI05 model is a direct port of the OpenPI implementation.
-This implementation follows the original OpenPI structure for compatibility.
-Original implementation: https://github.com/Physical-Intelligence/openpi
-Loading model from: lerobot/pi05_libero_finetuned
-✓ Loaded state dict from model.safetensors
-Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy:
-	Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight".
-Sat Nov 22 23:44:08 +07 2025: SUCCESS pi05 steps=10 sigma_d=0.1
-Sat Nov 22 23:44:08 +07 2025: Starting pi05 steps=10 sigma_d=0.2
-WARNING:lerobot.configs.policies:Device 'cuda' is not available. Switching to 'mps'.
-WARNING:lerobot.configs.policies:Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:44:14 _dataset.py:959 ================================================================================
-INFO 2025-11-22 23:44:14 _dataset.py:960 RTC Dataset Evaluation
-INFO 2025-11-22 23:44:14 _dataset.py:961 Config: RTCEvalConfig(policy=PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=<FeatureType.STATE: 'STATE'>, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=<FeatureType.ACTION: 'ACTION'>, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path='lerobot/pi05_libero_finetuned', paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=None, image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'VISUAL': <NormalizationMode.IDENTITY: 'IDENTITY'>}, gradient_checkpointing=True, compile_model=True, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06), dataset=DatasetConfig(repo_id='HuggingFaceVLA/libero', root=None, episodes=None, image_transforms=ImageTransformsConfig(enable=False, max_num_transforms=3, random_order=False, tfs={'brightness': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'brightness': (0.8, 1.2)}), 'contrast': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'contrast': (0.8, 1.2)}), 'saturation': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'saturation': (0.5, 1.5)}), 'hue': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'hue': (-0.05, 0.05)}), 'sharpness': ImageTransformConfig(weight=1.0, type='SharpnessJitter', kwargs={'sharpness': (0.5, 1.5)}), 'affine': ImageTransformConfig(weight=1.0, type='RandomAffine', kwargs={'degrees': (-5.0, 5.0), 'translate': (0.05, 0.05)})}), revision=None, use_imagenet_stats=True, video_backend='torchcodec', streaming=False), rtc=RTCConfig(enabled=False, prefix_attention_schedule=<RTCAttentionSchedule.EXP: 'EXP'>, max_guidance_weight=None, execution_horizon=8, sigma_d=0.2, debug=False, debug_maxlen=100), device='mps', output_dir='rtc_experiments_results/pi05_steps_10_sigma_0.2', seed=10, inference_delay=4, num_inference_steps=10, use_torch_compile=False, torch_compile_backend='inductor', torch_compile_mode='default', torch_compile_disable_cudagraphs=True)
-INFO 2025-11-22 23:44:14 _dataset.py:962 ================================================================================
-INFO 2025-11-22 23:44:14 _dataset.py:256 Loading dataset: HuggingFaceVLA/libero
-INFO 2025-11-22 23:44:15 _dataset.py:269 Dataset loaded: 273465 samples, 1693 episodes
-INFO 2025-11-22 23:44:17 _dataset.py:280 ================================================================================
-INFO 2025-11-22 23:44:17 _dataset.py:281 Ready to run evaluation with sequential policy loading:
-INFO 2025-11-22 23:44:17 _dataset.py:282   1. policy_prev_chunk - Generate reference chunk, then destroy
-INFO 2025-11-22 23:44:17 _dataset.py:283   2. policy_no_rtc - Generate without RTC, then destroy
-INFO 2025-11-22 23:44:17 _dataset.py:284   3. policy_rtc - Generate with RTC, then destroy
-INFO 2025-11-22 23:44:17 _dataset.py:285   Note: Only one policy in memory at a time for efficient memory usage
-INFO 2025-11-22 23:44:17 _dataset.py:286 ================================================================================
-INFO 2025-11-22 23:44:17 _dataset.py:445 Output directory: rtc_experiments_results/pi05_steps_10_sigma_0.2
-INFO 2025-11-22 23:44:17 _dataset.py:447 ================================================================================
-INFO 2025-11-22 23:44:17 _dataset.py:448 Starting RTC evaluation
-INFO 2025-11-22 23:44:17 _dataset.py:449 Inference delay: 4
-INFO 2025-11-22 23:44:17 _dataset.py:451 Number of flow matching steps: 10
-INFO 2025-11-22 23:44:17 _dataset.py:454 ================================================================================
-INFO 2025-11-22 23:44:17 _dataset.py:469 ================================================================================
-INFO 2025-11-22 23:44:17 _dataset.py:470 Step 1: Generating previous chunk with policy_prev_chunk
-INFO 2025-11-22 23:44:17 _dataset.py:471 ================================================================================
-INFO 2025-11-22 23:44:17 _dataset.py:299 Initializing policy_prev_chunk...
-INFO 2025-11-22 23:44:17 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:44:17 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:44:17 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:44:17 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:44:17 _dataset.py:316   Overriding num_inference_steps for pi05: 10
-INFO 2025-11-22 23:45:26 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model
-WARNING 2025-11-22 23:45:28 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias
-WARNING 2025-11-22 23:45:28 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight
-INFO 2025-11-22 23:45:31 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC
-INFO 2025-11-22 23:45:31 _dataset.py:336   RTC enabled: False
-INFO 2025-11-22 23:45:31 _dataset.py:337   RTC debug: False
-INFO 2025-11-22 23:45:31 _dataset.py:338   Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=<FeatureType.STATE: 'STATE'>, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=<FeatureType.ACTION: 'ACTION'>, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=False, prefix_attention_schedule=<RTCAttentionSchedule.EXP: 'EXP'>, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=False, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'VISUAL': <NormalizationMode.IDENTITY: 'IDENTITY'>}, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06)
-INFO 2025-11-22 23:45:31 _dataset.py:344 ✓ policy_prev_chunk initialized successfully
-INFO 2025-11-22 23:45:33 _dataset.py:483   Generated prev_chunk shape: torch.Size([25, 7])
-INFO 2025-11-22 23:45:33 _dataset.py:410   Destroying policy_prev_chunk and freeing memory...
-INFO 2025-11-22 23:45:34 _dataset.py:430   ✓ policy_prev_chunk destroyed and memory freed
-INFO 2025-11-22 23:45:34 _dataset.py:491 ================================================================================
-INFO 2025-11-22 23:45:34 _dataset.py:492 Step 2: Generating actions WITHOUT RTC with policy_no_rtc
-INFO 2025-11-22 23:45:34 _dataset.py:493 ================================================================================
-INFO 2025-11-22 23:45:34 _dataset.py:299 Initializing policy_no_rtc...
-INFO 2025-11-22 23:45:34 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:45:34 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:45:35 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:45:35 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:45:35 _dataset.py:316   Overriding num_inference_steps for pi05: 10
-INFO 2025-11-22 23:46:43 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model
-WARNING 2025-11-22 23:46:44 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias
-WARNING 2025-11-22 23:46:44 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight
-INFO 2025-11-22 23:46:46 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC
-INFO 2025-11-22 23:46:46 _dataset.py:336   RTC enabled: False
-INFO 2025-11-22 23:46:46 _dataset.py:337   RTC debug: True
-INFO 2025-11-22 23:46:46 _dataset.py:338   Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=<FeatureType.STATE: 'STATE'>, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=<FeatureType.ACTION: 'ACTION'>, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=False, prefix_attention_schedule=<RTCAttentionSchedule.EXP: 'EXP'>, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=True, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'VISUAL': <NormalizationMode.IDENTITY: 'IDENTITY'>}, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06)
-INFO 2025-11-22 23:46:46 _dataset.py:344 ✓ policy_no_rtc initialized successfully
-INFO 2025-11-22 23:46:48 _dataset.py:515   Tracked 10 steps without RTC
-INFO 2025-11-22 23:46:48 _dataset.py:516   Generated no_rtc_actions shape: torch.Size([1, 50, 7])
-INFO 2025-11-22 23:46:48 _dataset.py:410   Destroying policy_no_rtc and freeing memory...
-INFO 2025-11-22 23:46:49 _dataset.py:430   ✓ policy_no_rtc destroyed and memory freed
-INFO 2025-11-22 23:46:49 _dataset.py:524 ================================================================================
-INFO 2025-11-22 23:46:49 _dataset.py:525 Step 3: Generating actions WITH RTC with policy_rtc
-INFO 2025-11-22 23:46:49 _dataset.py:526 ================================================================================
-INFO 2025-11-22 23:46:49 _dataset.py:299 Initializing policy_rtc...
-INFO 2025-11-22 23:46:49 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:46:49 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:46:49 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:46:49 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:46:49 _dataset.py:316   Overriding num_inference_steps for pi05: 10
-INFO 2025-11-22 23:47:56 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model
-WARNING 2025-11-22 23:47:58 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias
-WARNING 2025-11-22 23:47:58 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight
-INFO 2025-11-22 23:48:07 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC
-INFO 2025-11-22 23:48:07 _dataset.py:336   RTC enabled: True
-INFO 2025-11-22 23:48:07 _dataset.py:337   RTC debug: True
-INFO 2025-11-22 23:48:07 _dataset.py:338   Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=<FeatureType.STATE: 'STATE'>, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=<FeatureType.ACTION: 'ACTION'>, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=True, prefix_attention_schedule=<RTCAttentionSchedule.EXP: 'EXP'>, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=True, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'VISUAL': <NormalizationMode.IDENTITY: 'IDENTITY'>}, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06)
-INFO 2025-11-22 23:48:07 _dataset.py:344 ✓ policy_rtc initialized successfully
-INFO 2025-11-22 23:48:10 _dataset.py:546   Tracked 10 steps with RTC
-INFO 2025-11-22 23:48:10 _dataset.py:547   Generated rtc_actions shape: torch.Size([1, 50, 7])
-ERROR 2025-11-22 23:48:10 _dataset.py:553   Error getting num_steps: 'PI05Config' object has no attribute 'num_steps'
-WARNING 2025-11-22 23:48:10 _dataset.py:555   Using num_inference_steps: 10 instead of num_steps
-INFO 2025-11-22 23:48:10 _dataset.py:410   Destroying policy_rtc and freeing memory...
-INFO 2025-11-22 23:48:12 _dataset.py:430   ✓ policy_rtc destroyed and memory freed
-INFO 2025-11-22 23:48:12 _dataset.py:561 ================================================================================
-INFO 2025-11-22 23:48:12 _dataset.py:562 Plotting results...
-INFO 2025-11-22 23:48:12 _dataset.py:818 ================================================================================
-INFO 2025-11-22 23:48:12 _dataset.py:819 Plotting 10 steps
-INFO 2025-11-22 23:48:13 _dataset.py:818 ================================================================================
-INFO 2025-11-22 23:48:13 _dataset.py:819 Plotting 10 steps
-INFO 2025-11-22 23:48:13 _dataset.py:905 Plotting final no-RTC x_t step as orange dashed reference
-INFO 2025-11-22 23:48:14 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.2/denoising_xt_comparison.png
-INFO 2025-11-22 23:48:15 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.2/denoising_vt_comparison.png
-INFO 2025-11-22 23:48:15 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.2/denoising_correction_comparison.png
-INFO 2025-11-22 23:48:16 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.2/denoising_x1t_comparison.png
-INFO 2025-11-22 23:48:16 _dataset.py:566 ================================================================================
-INFO 2025-11-22 23:48:16 _dataset.py:567 Plotting final actions comparison...
-INFO 2025-11-22 23:48:17 _dataset.py:687 Saved final actions comparison to rtc_experiments_results/pi05_steps_10_sigma_0.2/final_actions_comparison.png
-INFO 2025-11-22 23:48:17 _dataset.py:570 ================================================================================
-INFO 2025-11-22 23:48:17 _dataset.py:571 Evaluation completed successfully
-The PI05 model is a direct port of the OpenPI implementation.
-This implementation follows the original OpenPI structure for compatibility.
-Original implementation: https://github.com/Physical-Intelligence/openpi
-Loading model from: lerobot/pi05_libero_finetuned
-✓ Loaded state dict from model.safetensors
-Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy:
-	Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight".
-The PI05 model is a direct port of the OpenPI implementation.
-This implementation follows the original OpenPI structure for compatibility.
-Original implementation: https://github.com/Physical-Intelligence/openpi
-Loading model from: lerobot/pi05_libero_finetuned
-✓ Loaded state dict from model.safetensors
-Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy:
-	Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight".
-The PI05 model is a direct port of the OpenPI implementation.
-This implementation follows the original OpenPI structure for compatibility.
-Original implementation: https://github.com/Physical-Intelligence/openpi
-Loading model from: lerobot/pi05_libero_finetuned
-✓ Loaded state dict from model.safetensors
-Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy:
-	Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight".
-Sat Nov 22 23:48:19 +07 2025: SUCCESS pi05 steps=10 sigma_d=0.2
-Sat Nov 22 23:48:19 +07 2025: Starting pi05 steps=10 sigma_d=0.5
-WARNING:lerobot.configs.policies:Device 'cuda' is not available. Switching to 'mps'.
-WARNING:lerobot.configs.policies:Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:48:25 _dataset.py:959 ================================================================================
-INFO 2025-11-22 23:48:25 _dataset.py:960 RTC Dataset Evaluation
-INFO 2025-11-22 23:48:25 _dataset.py:961 Config: RTCEvalConfig(policy=PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=<FeatureType.STATE: 'STATE'>, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=<FeatureType.ACTION: 'ACTION'>, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path='lerobot/pi05_libero_finetuned', paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=None, image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'VISUAL': <NormalizationMode.IDENTITY: 'IDENTITY'>}, gradient_checkpointing=True, compile_model=True, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06), dataset=DatasetConfig(repo_id='HuggingFaceVLA/libero', root=None, episodes=None, image_transforms=ImageTransformsConfig(enable=False, max_num_transforms=3, random_order=False, tfs={'brightness': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'brightness': (0.8, 1.2)}), 'contrast': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'contrast': (0.8, 1.2)}), 'saturation': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'saturation': (0.5, 1.5)}), 'hue': ImageTransformConfig(weight=1.0, type='ColorJitter', kwargs={'hue': (-0.05, 0.05)}), 'sharpness': ImageTransformConfig(weight=1.0, type='SharpnessJitter', kwargs={'sharpness': (0.5, 1.5)}), 'affine': ImageTransformConfig(weight=1.0, type='RandomAffine', kwargs={'degrees': (-5.0, 5.0), 'translate': (0.05, 0.05)})}), revision=None, use_imagenet_stats=True, video_backend='torchcodec', streaming=False), rtc=RTCConfig(enabled=False, prefix_attention_schedule=<RTCAttentionSchedule.EXP: 'EXP'>, max_guidance_weight=None, execution_horizon=8, sigma_d=0.5, debug=False, debug_maxlen=100), device='mps', output_dir='rtc_experiments_results/pi05_steps_10_sigma_0.5', seed=10, inference_delay=4, num_inference_steps=10, use_torch_compile=False, torch_compile_backend='inductor', torch_compile_mode='default', torch_compile_disable_cudagraphs=True)
-INFO 2025-11-22 23:48:25 _dataset.py:962 ================================================================================
-INFO 2025-11-22 23:48:25 _dataset.py:256 Loading dataset: HuggingFaceVLA/libero
-INFO 2025-11-22 23:48:26 _dataset.py:269 Dataset loaded: 273465 samples, 1693 episodes
-INFO 2025-11-22 23:48:28 _dataset.py:280 ================================================================================
-INFO 2025-11-22 23:48:28 _dataset.py:281 Ready to run evaluation with sequential policy loading:
-INFO 2025-11-22 23:48:28 _dataset.py:282   1. policy_prev_chunk - Generate reference chunk, then destroy
-INFO 2025-11-22 23:48:28 _dataset.py:283   2. policy_no_rtc - Generate without RTC, then destroy
-INFO 2025-11-22 23:48:28 _dataset.py:284   3. policy_rtc - Generate with RTC, then destroy
-INFO 2025-11-22 23:48:28 _dataset.py:285   Note: Only one policy in memory at a time for efficient memory usage
-INFO 2025-11-22 23:48:28 _dataset.py:286 ================================================================================
-INFO 2025-11-22 23:48:28 _dataset.py:445 Output directory: rtc_experiments_results/pi05_steps_10_sigma_0.5
-INFO 2025-11-22 23:48:28 _dataset.py:447 ================================================================================
-INFO 2025-11-22 23:48:28 _dataset.py:448 Starting RTC evaluation
-INFO 2025-11-22 23:48:28 _dataset.py:449 Inference delay: 4
-INFO 2025-11-22 23:48:28 _dataset.py:451 Number of flow matching steps: 10
-INFO 2025-11-22 23:48:28 _dataset.py:454 ================================================================================
-INFO 2025-11-22 23:48:28 _dataset.py:469 ================================================================================
-INFO 2025-11-22 23:48:28 _dataset.py:470 Step 1: Generating previous chunk with policy_prev_chunk
-INFO 2025-11-22 23:48:28 _dataset.py:471 ================================================================================
-INFO 2025-11-22 23:48:28 _dataset.py:299 Initializing policy_prev_chunk...
-INFO 2025-11-22 23:48:28 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:48:28 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:48:28 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:48:28 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:48:28 _dataset.py:316   Overriding num_inference_steps for pi05: 10
-INFO 2025-11-22 23:49:37 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model
-WARNING 2025-11-22 23:49:39 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias
-WARNING 2025-11-22 23:49:39 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight
-INFO 2025-11-22 23:49:42 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC
-INFO 2025-11-22 23:49:42 _dataset.py:336   RTC enabled: False
-INFO 2025-11-22 23:49:42 _dataset.py:337   RTC debug: False
-INFO 2025-11-22 23:49:42 _dataset.py:338   Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=<FeatureType.STATE: 'STATE'>, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=<FeatureType.ACTION: 'ACTION'>, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=False, prefix_attention_schedule=<RTCAttentionSchedule.EXP: 'EXP'>, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=False, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'VISUAL': <NormalizationMode.IDENTITY: 'IDENTITY'>}, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06)
-INFO 2025-11-22 23:49:42 _dataset.py:344 ✓ policy_prev_chunk initialized successfully
-INFO 2025-11-22 23:49:44 _dataset.py:483   Generated prev_chunk shape: torch.Size([25, 7])
-INFO 2025-11-22 23:49:44 _dataset.py:410   Destroying policy_prev_chunk and freeing memory...
-INFO 2025-11-22 23:49:45 _dataset.py:430   ✓ policy_prev_chunk destroyed and memory freed
-INFO 2025-11-22 23:49:45 _dataset.py:491 ================================================================================
-INFO 2025-11-22 23:49:45 _dataset.py:492 Step 2: Generating actions WITHOUT RTC with policy_no_rtc
-INFO 2025-11-22 23:49:45 _dataset.py:493 ================================================================================
-INFO 2025-11-22 23:49:45 _dataset.py:299 Initializing policy_no_rtc...
-INFO 2025-11-22 23:49:46 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:49:46 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:49:46 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:49:46 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:49:46 _dataset.py:316   Overriding num_inference_steps for pi05: 10
-INFO 2025-11-22 23:50:55 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model
-WARNING 2025-11-22 23:50:57 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias
-WARNING 2025-11-22 23:50:57 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight
-INFO 2025-11-22 23:50:58 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC
-INFO 2025-11-22 23:50:58 _dataset.py:336   RTC enabled: False
-INFO 2025-11-22 23:50:58 _dataset.py:337   RTC debug: True
-INFO 2025-11-22 23:50:58 _dataset.py:338   Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=<FeatureType.STATE: 'STATE'>, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=<FeatureType.ACTION: 'ACTION'>, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=False, prefix_attention_schedule=<RTCAttentionSchedule.EXP: 'EXP'>, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=True, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'VISUAL': <NormalizationMode.IDENTITY: 'IDENTITY'>}, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06)
-INFO 2025-11-22 23:50:58 _dataset.py:344 ✓ policy_no_rtc initialized successfully
-INFO 2025-11-22 23:51:00 _dataset.py:515   Tracked 10 steps without RTC
-INFO 2025-11-22 23:51:00 _dataset.py:516   Generated no_rtc_actions shape: torch.Size([1, 50, 7])
-INFO 2025-11-22 23:51:00 _dataset.py:410   Destroying policy_no_rtc and freeing memory...
-INFO 2025-11-22 23:51:01 _dataset.py:430   ✓ policy_no_rtc destroyed and memory freed
-INFO 2025-11-22 23:51:01 _dataset.py:524 ================================================================================
-INFO 2025-11-22 23:51:01 _dataset.py:525 Step 3: Generating actions WITH RTC with policy_rtc
-INFO 2025-11-22 23:51:01 _dataset.py:526 ================================================================================
-INFO 2025-11-22 23:51:01 _dataset.py:299 Initializing policy_rtc...
-INFO 2025-11-22 23:51:01 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:51:01 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:51:02 ils/utils.py:46 Metal backend detected, using mps.
-WARNING 2025-11-22 23:51:02 /policies.py:82 Device 'cuda' is not available. Switching to 'mps'.
-INFO 2025-11-22 23:51:02 _dataset.py:316   Overriding num_inference_steps for pi05: 10
-INFO 2025-11-22 23:52:12 ing_pi05.py:558 Enabled gradient checkpointing for PI05Pytorch model
-WARNING 2025-11-22 23:52:13 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.bias
-WARNING 2025-11-22 23:52:13 ng_pi05.py:1071 Vision embedding key might need handling: model.paligemma_with_expert.paligemma.model.vision_tower.vision_model.embeddings.patch_embedding.weight
-INFO 2025-11-22 23:52:24 ng_pi05.py:1097 Using num of steps 10 as max guidance weight for RTC
-INFO 2025-11-22 23:52:24 _dataset.py:336   RTC enabled: True
-INFO 2025-11-22 23:52:24 _dataset.py:337   RTC debug: True
-INFO 2025-11-22 23:52:24 _dataset.py:338   Policy config: PI05Config(n_obs_steps=1, input_features={'observation.images.image': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.images.image2': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 256, 256)), 'observation.state': PolicyFeature(type=<FeatureType.STATE: 'STATE'>, shape=(8,)), 'observation.images.empty_camera_0': PolicyFeature(type=<FeatureType.VISUAL: 'VISUAL'>, shape=(3, 224, 224))}, output_features={'action': PolicyFeature(type=<FeatureType.ACTION: 'ACTION'>, shape=(7,))}, device='mps', use_amp=False, push_to_hub=True, repo_id='pepijn223/pi05_libero_31_9_non_q', private=None, tags=None, license=None, pretrained_path=PosixPath('lerobot/pi05_libero'), paligemma_variant='gemma_2b', action_expert_variant='gemma_300m', dtype='bfloat16', chunk_size=50, n_action_steps=50, max_state_dim=32, max_action_dim=32, num_inference_steps=10, time_sampling_beta_alpha=1.5, time_sampling_beta_beta=1.0, time_sampling_scale=0.999, time_sampling_offset=0.001, min_period=0.004, max_period=4.0, rtc_config=RTCConfig(enabled=True, prefix_attention_schedule=<RTCAttentionSchedule.EXP: 'EXP'>, max_guidance_weight=10, execution_horizon=8, sigma_d=1.0, debug=True, debug_maxlen=100), image_resolution=(224, 224), empty_cameras=1, tokenizer_max_length=200, normalization_mapping={'ACTION': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'VISUAL': <NormalizationMode.IDENTITY: 'IDENTITY'>}, gradient_checkpointing=True, compile_model=False, compile_mode='max-autotune', optimizer_lr=2.5e-05, optimizer_betas=(0.9, 0.95), optimizer_eps=1e-08, optimizer_weight_decay=0.01, optimizer_grad_clip_norm=1.0, scheduler_warmup_steps=1000, scheduler_decay_steps=6000, scheduler_decay_lr=2.5e-06)
-INFO 2025-11-22 23:52:24 _dataset.py:344 ✓ policy_rtc initialized successfully
-INFO 2025-11-22 23:52:27 _dataset.py:546   Tracked 10 steps with RTC
-INFO 2025-11-22 23:52:27 _dataset.py:547   Generated rtc_actions shape: torch.Size([1, 50, 7])
-ERROR 2025-11-22 23:52:27 _dataset.py:553   Error getting num_steps: 'PI05Config' object has no attribute 'num_steps'
-WARNING 2025-11-22 23:52:27 _dataset.py:555   Using num_inference_steps: 10 instead of num_steps
-INFO 2025-11-22 23:52:27 _dataset.py:410   Destroying policy_rtc and freeing memory...
-INFO 2025-11-22 23:52:29 _dataset.py:430   ✓ policy_rtc destroyed and memory freed
-INFO 2025-11-22 23:52:29 _dataset.py:561 ================================================================================
-INFO 2025-11-22 23:52:29 _dataset.py:562 Plotting results...
-INFO 2025-11-22 23:52:29 _dataset.py:818 ================================================================================
-INFO 2025-11-22 23:52:29 _dataset.py:819 Plotting 10 steps
-INFO 2025-11-22 23:52:30 _dataset.py:818 ================================================================================
-INFO 2025-11-22 23:52:30 _dataset.py:819 Plotting 10 steps
-INFO 2025-11-22 23:52:30 _dataset.py:905 Plotting final no-RTC x_t step as orange dashed reference
-INFO 2025-11-22 23:52:31 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.5/denoising_xt_comparison.png
-INFO 2025-11-22 23:52:32 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.5/denoising_vt_comparison.png
-INFO 2025-11-22 23:52:32 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.5/denoising_correction_comparison.png
-INFO 2025-11-22 23:52:33 _dataset.py:800 Saved figure to rtc_experiments_results/pi05_steps_10_sigma_0.5/denoising_x1t_comparison.png
-INFO 2025-11-22 23:52:33 _dataset.py:566 ================================================================================
-INFO 2025-11-22 23:52:33 _dataset.py:567 Plotting final actions comparison...
-INFO 2025-11-22 23:52:34 _dataset.py:687 Saved final actions comparison to rtc_experiments_results/pi05_steps_10_sigma_0.5/final_actions_comparison.png
-INFO 2025-11-22 23:52:34 _dataset.py:570 ================================================================================
-INFO 2025-11-22 23:52:34 _dataset.py:571 Evaluation completed successfully
-The PI05 model is a direct port of the OpenPI implementation.
-This implementation follows the original OpenPI structure for compatibility.
-Original implementation: https://github.com/Physical-Intelligence/openpi
-Loading model from: lerobot/pi05_libero_finetuned
-✓ Loaded state dict from model.safetensors
-Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy:
-	Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight".
-The PI05 model is a direct port of the OpenPI implementation.
-This implementation follows the original OpenPI structure for compatibility.
-Original implementation: https://github.com/Physical-Intelligence/openpi
-Loading model from: lerobot/pi05_libero_finetuned
-✓ Loaded state dict from model.safetensors
-Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy:
-	Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight".
-The PI05 model is a direct port of the OpenPI implementation.
-This implementation follows the original OpenPI structure for compatibility.
-Original implementation: https://github.com/Physical-Intelligence/openpi
-Loading model from: lerobot/pi05_libero_finetuned
-✓ Loaded state dict from model.safetensors
-Warning: Could not remap state dict keys: Error(s) in loading state_dict for PI05Policy:
-	Missing key(s) in state_dict: "model.paligemma_with_expert.paligemma.model.language_model.embed_tokens.weight".
-Sat Nov 22 23:52:36 +07 2025: SUCCESS pi05 steps=10 sigma_d=0.5
-Sat Nov 22 23:52:36 +07 2025: Starting pi05 steps=10 sigma_d=1.0

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Git LFS Details

SHA256: dabccc0e5e3c390ae99bbff9ef186bfc100cb955a275c569f75a858db1bffdaf
Pointer size: 131 Bytes
Size of remote file: 520 kB

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Git LFS Details

SHA256: fe0a2763bc0be9b5735a29a43d47843a00189b1555728e86ac39acb513d1fed8
Pointer size: 132 Bytes
Size of remote file: 1.02 MB

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Git LFS Details

SHA256: 901a14c053b092f416876f051898ac4f29b8653632a86e30208247cfa4088fa1
Pointer size: 132 Bytes
Size of remote file: 1.05 MB

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Git LFS Details

SHA256: 50c9297755083c3d3c26d5f653a7f51ba18e31715dd6bb52dec686be770eb158
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Size of remote file: 1.35 MB

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Git LFS Details

SHA256: 74df055613b987cb5c3cc1013af1f10676b874946b86ffbcb84b5b92c7bfd430
Pointer size: 131 Bytes
Size of remote file: 350 kB

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Git LFS Details

SHA256: da57e4cde78cba4e576368b04ed7cb23b055c2404c958adea38aefeab67da6e4
Pointer size: 131 Bytes
Size of remote file: 546 kB

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Git LFS Details

SHA256: ef05fad800bc2c15694317ce1e1f48aefdc35a91a297a12f97fca997b23c09bf
Pointer size: 132 Bytes
Size of remote file: 1.33 MB

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Git LFS Details

SHA256: e18ef1d36a94b4675af1fdb401bc02b3343bfc3a62de9ead32b32eaef85a2219
Pointer size: 131 Bytes
Size of remote file: 949 kB

static/experiments/pi05_steps_100_sigma_0.1_fulltrajectory_false/denoising_xt_comparison.png DELETED Viewed

Git LFS Details

SHA256: 44022384445fa29f8af87c0cafed538b0cabbed535018937652f870ebdc97786
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Size of remote file: 1.39 MB

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Git LFS Details

SHA256: f8746a10f3d9fec53b63467979819bbceadbcbb16e302b3b3597ed3c82657589
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Size of remote file: 314 kB

static/experiments/pi05_steps_100_sigma_0.1_fulltrajectory_true/denoising_correction_comparison.png DELETED Viewed

Git LFS Details

SHA256: 378a636fa3a9e60edf7a985074fcfb1a3fec89554fb6e73944f041c0c8313d5a
Pointer size: 131 Bytes
Size of remote file: 515 kB

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Git LFS Details

SHA256: 3521107516bdedfb6da32617074853228956cd32b8e01f8f91cd1bc53ef5ead5
Pointer size: 132 Bytes
Size of remote file: 1.23 MB

static/experiments/pi05_steps_100_sigma_0.1_fulltrajectory_true/denoising_x1t_comparison.png DELETED Viewed

Git LFS Details

SHA256: c9997aedcb51e6917fde982f0650e2c8c1b75b6c4ca9eac009916d7bd26ac976
Pointer size: 131 Bytes
Size of remote file: 953 kB

static/experiments/pi05_steps_100_sigma_0.1_fulltrajectory_true/denoising_xt_comparison.png DELETED Viewed

Git LFS Details

SHA256: 169c7ce86dd41eccf7aa2d9b9927087bc2ed8b1f6eb285869d031f834a5ca6a6
Pointer size: 132 Bytes
Size of remote file: 1.4 MB

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Git LFS Details

SHA256: 2554d927229b56d31a95dd7f7952d2cfca5a2db6fee419e737704b5fa4d3ba93
Pointer size: 131 Bytes
Size of remote file: 316 kB

static/experiments/pi05_steps_100_sigma_0.2/denoising_correction_comparison.png DELETED Viewed

Git LFS Details

SHA256: dabccc0e5e3c390ae99bbff9ef186bfc100cb955a275c569f75a858db1bffdaf
Pointer size: 131 Bytes
Size of remote file: 520 kB

static/experiments/pi05_steps_100_sigma_0.2/denoising_vt_comparison.png DELETED Viewed

Git LFS Details

SHA256: fe0a2763bc0be9b5735a29a43d47843a00189b1555728e86ac39acb513d1fed8
Pointer size: 132 Bytes
Size of remote file: 1.02 MB

static/experiments/pi05_steps_100_sigma_0.2/denoising_x1t_comparison.png DELETED Viewed

Git LFS Details

SHA256: 901a14c053b092f416876f051898ac4f29b8653632a86e30208247cfa4088fa1
Pointer size: 132 Bytes
Size of remote file: 1.05 MB

static/experiments/pi05_steps_100_sigma_0.2/denoising_xt_comparison.png DELETED Viewed

Git LFS Details

SHA256: 50c9297755083c3d3c26d5f653a7f51ba18e31715dd6bb52dec686be770eb158
Pointer size: 132 Bytes
Size of remote file: 1.35 MB

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Git LFS Details

SHA256: 74df055613b987cb5c3cc1013af1f10676b874946b86ffbcb84b5b92c7bfd430
Pointer size: 131 Bytes
Size of remote file: 350 kB

static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_false/denoising_correction_comparison.png DELETED Viewed

Git LFS Details

SHA256: 322aa9974be8842fbc4aff37d2c0814ad6f1eb09aa6c5fb7b8692f10da51086e
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Size of remote file: 539 kB

static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_false/denoising_vt_comparison.png DELETED Viewed

Git LFS Details

SHA256: 943a2794322cfca3d41eac3dd6815330a08fefd626604154d9eb4a6bac37a7ce
Pointer size: 132 Bytes
Size of remote file: 1.33 MB

static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_false/denoising_x1t_comparison.png DELETED Viewed

Git LFS Details

SHA256: 0fd4590f48c6ea6af780bbec6974371fcc7a0bd865f148fd340a80483757fd6a
Pointer size: 131 Bytes
Size of remote file: 948 kB

static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_false/denoising_xt_comparison.png DELETED Viewed

Git LFS Details

SHA256: 5ee823f13b88d83326a9b8cb4d52020395bb1d45564cd217ffd1c0a45cc7a091
Pointer size: 132 Bytes
Size of remote file: 1.39 MB

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Git LFS Details

SHA256: 7a1a8bc9293d46df4e13ea78dfa8c6ccec5b6b4766489a5c08964109545cdcd0
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Size of remote file: 313 kB

static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_true/denoising_correction_comparison.png DELETED Viewed

Git LFS Details

SHA256: aba1ab2ac87be245e2ca990b0828ef05da59a02bf0395f35e1e8b368501a51d0
Pointer size: 131 Bytes
Size of remote file: 515 kB

static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_true/denoising_vt_comparison.png DELETED Viewed

Git LFS Details

SHA256: 8ca82b7fc5f4db73c8d6384cb300718c7e6a87e0d746739163e22f565aac0cc6
Pointer size: 132 Bytes
Size of remote file: 1.27 MB

static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_true/denoising_x1t_comparison.png DELETED Viewed

Git LFS Details

SHA256: ead7008e5dc237cc4e565242a6f0dde07aea7f5c850b3896b860fab9637f7ad1
Pointer size: 131 Bytes
Size of remote file: 954 kB

static/experiments/pi05_steps_100_sigma_0.2_fulltrajectory_true/denoising_xt_comparison.png DELETED Viewed

Git LFS Details

SHA256: 9bd67c13a7cf16dcdfb19fd3b7b10ccdb357cf1de32bcc1029f24f4a30cf2459
Pointer size: 132 Bytes
Size of remote file: 1.4 MB

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Git LFS Details

SHA256: fc2c7eadec3927643af49484f98eb026f0b8fcba94eb2778038d0b4101f1a2b2
Pointer size: 131 Bytes
Size of remote file: 316 kB

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Git LFS Details

SHA256: dabccc0e5e3c390ae99bbff9ef186bfc100cb955a275c569f75a858db1bffdaf
Pointer size: 131 Bytes
Size of remote file: 520 kB

static/experiments/pi05_steps_100_sigma_0.5/denoising_vt_comparison.png DELETED Viewed

Git LFS Details

SHA256: fe0a2763bc0be9b5735a29a43d47843a00189b1555728e86ac39acb513d1fed8
Pointer size: 132 Bytes
Size of remote file: 1.02 MB

static/experiments/pi05_steps_100_sigma_0.5/denoising_x1t_comparison.png DELETED Viewed

Git LFS Details

SHA256: 901a14c053b092f416876f051898ac4f29b8653632a86e30208247cfa4088fa1
Pointer size: 132 Bytes
Size of remote file: 1.05 MB

static/experiments/pi05_steps_100_sigma_0.5/denoising_xt_comparison.png DELETED Viewed

Git LFS Details

SHA256: 50c9297755083c3d3c26d5f653a7f51ba18e31715dd6bb52dec686be770eb158
Pointer size: 132 Bytes
Size of remote file: 1.35 MB

static/experiments/pi05_steps_100_sigma_0.5/final_actions_comparison.png DELETED Viewed

Git LFS Details

SHA256: 74df055613b987cb5c3cc1013af1f10676b874946b86ffbcb84b5b92c7bfd430
Pointer size: 131 Bytes
Size of remote file: 350 kB

static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_false/denoising_correction_comparison.png DELETED Viewed

Git LFS Details

SHA256: 487b14305bd993724756a980e66302e8fe8cfec0037e06fe21435fcb282a0711
Pointer size: 131 Bytes
Size of remote file: 546 kB

static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_false/denoising_vt_comparison.png DELETED Viewed

Git LFS Details

SHA256: ea08732a46edcaad29939fd8ca63593383815138ccce47e8a365676822536666
Pointer size: 132 Bytes
Size of remote file: 1.33 MB

static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_false/denoising_x1t_comparison.png DELETED Viewed

Git LFS Details

SHA256: a4e961bd2c12c1f5bd1c7c3aa8693463981ce051e477b914404d2d1cdda30310
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Size of remote file: 948 kB

static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_false/denoising_xt_comparison.png DELETED Viewed

Git LFS Details

SHA256: 5b2de673e953e2fbbacfbcae88e63f7bbd3b071d5f8383e251a47ebd8dde4894
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Git LFS Details

SHA256: b21307de5ed4834bd284431b22dee0b0c79ddf8291798fb6b38b051865829351
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static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_true/denoising_correction_comparison.png DELETED Viewed

Git LFS Details

SHA256: e55e37c4424be631e59521c3c6ec3edc75e39e9895da49f5200e2bf7a58b801e
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Git LFS Details

SHA256: da131b9f1cec4be81749cab9e9254eabd596f74914d68d9ed2e6152053537961
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static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_true/denoising_x1t_comparison.png DELETED Viewed

Git LFS Details

SHA256: b0b7d34003861b35a90b122f7d0231614e239a502da18e48111e0a4c6fe9deb6
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Size of remote file: 951 kB

static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_true/denoising_xt_comparison.png DELETED Viewed

Git LFS Details

SHA256: 382825183e8ebb4c1113ddcb1de51b078143d9398d932084e326ae67d83cea32
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Size of remote file: 1.4 MB

static/experiments/pi05_steps_100_sigma_0.5_fulltrajectory_true/final_actions_comparison.png DELETED Viewed

Git LFS Details

SHA256: 9036275127714e20c7c124c61948d3ada41a587044cc6aca59cf8fa0684e6811
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static/experiments/pi05_steps_100_sigma_0.8/denoising_correction_comparison.png DELETED Viewed

Git LFS Details

SHA256: dabccc0e5e3c390ae99bbff9ef186bfc100cb955a275c569f75a858db1bffdaf
Pointer size: 131 Bytes
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static/experiments/pi05_steps_100_sigma_0.8/denoising_vt_comparison.png DELETED Viewed

Git LFS Details

SHA256: fe0a2763bc0be9b5735a29a43d47843a00189b1555728e86ac39acb513d1fed8
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