Deploy() returns NoneType #1965

Closed
Closed
Deploy() returns NoneType#1965

Description

@vbabu29
vbabu29
opened on Oct 21, 2020

Describe the bug

Trying t o instantiate a Python SDK trained model which is stored in S3. The deploy() func returns a NoneType

Here is my code:

semsegtrainedmodel = sagemaker.model.Model(model_data=path,
image='811284229777.dkr.ecr.us-east-1.amazonaws.com/semantic-segmentation:latest',
role=role)

ss_predictor = semsegtrainedmodel.deploy(initial_instance_count=1, instance_type='ml.c4.xlarge')

Screenshots or logs
print(type(ss_predictor))
NoneType

System information
A description of your system. Please provide:

  • SageMaker Python SDK version: '1.72.1'
  • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Semantic Segmentation
  • Framework version:
  • Python version: 3.6.1
  • CPU or GPU:
  • Custom Docker image (Y/N):

Additional context
Add any other context about the problem here.

Activity

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      , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
       blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

      Skip to content
      Deploy() returns NoneType #1965
      Closed
      Closed
      Deploy() returns NoneType#1965
      Description
      @vbabu29
      vbabu29
      opened on Oct 21, 2020
      Describe the bug
      Trying t o instantiate a Python SDK trained model which is stored in S3. The deploy() func returns a NoneType
      Here is my code:
      semsegtrainedmodel = sagemaker.model.Model(model_data=path,
      
image='811284229777.dkr.ecr.us-east-1.amazonaws.com/semantic-segmentation:latest',
      
role=role)
      ss_predictor = semsegtrainedmodel.deploy(initial_instance_count=1, instance_type='ml.c4.xlarge')
      Screenshots or logs
      
print(type(ss_predictor))
      
NoneType
      System information
      
A description of your system. Please provide:
      • SageMaker Python SDK version: '1.72.1'
      • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Semantic Segmentation
      • Framework version:
      • Python version: 3.6.1
      • CPU or GPU:
      • Custom Docker image (Y/N):
      Additional context
      
Add any other context about the problem here.
      Activity
      Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
      Metadata
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      No one assigned
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          Milestone
          No milestone
          Relationships
          None yet
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          No branches or pull requests
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

          Skip to content
          Deploy() returns NoneType #1965
          Closed
          Closed
          Deploy() returns NoneType#1965
          Description
          @vbabu29
          vbabu29
          opened on Oct 21, 2020
          Describe the bug
          Trying t o instantiate a Python SDK trained model which is stored in S3. The deploy() func returns a NoneType
          Here is my code:
          semsegtrainedmodel = sagemaker.model.Model(model_data=path,
          
image='811284229777.dkr.ecr.us-east-1.amazonaws.com/semantic-segmentation:latest',
          
role=role)
          ss_predictor = semsegtrainedmodel.deploy(initial_instance_count=1, instance_type='ml.c4.xlarge')
          Screenshots or logs
          
print(type(ss_predictor))
          
NoneType
          System information
          
A description of your system. Please provide:
          • SageMaker Python SDK version: '1.72.1'
          • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Semantic Segmentation
          • Framework version:
          • Python version: 3.6.1
          • CPU or GPU:
          • Custom Docker image (Y/N):
          Additional context
          
Add any other context about the problem here.
          Activity
          Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
          Metadata
          Metadata
          Assignees
          No one assigned
            Labels
            No labels
            No labels
            Type
            No type
            Projects
            No projects
              Milestone
              No milestone
              Relationships
              None yet
              Development
              No branches or pull requests
              Issue actions
              
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

              Skip to content
              Deploy() returns NoneType #1965
              Closed
              Closed
              Deploy() returns NoneType#1965
              Description
              @vbabu29
              vbabu29
              opened on Oct 21, 2020
              Describe the bug
              Trying t o instantiate a Python SDK trained model which is stored in S3. The deploy() func returns a NoneType
              Here is my code:
              semsegtrainedmodel = sagemaker.model.Model(model_data=path,
              
image='811284229777.dkr.ecr.us-east-1.amazonaws.com/semantic-segmentation:latest',
              
role=role)
              ss_predictor = semsegtrainedmodel.deploy(initial_instance_count=1, instance_type='ml.c4.xlarge')
              Screenshots or logs
              
print(type(ss_predictor))
              
NoneType
              System information
              
A description of your system. Please provide:
              • SageMaker Python SDK version: '1.72.1'
              • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Semantic Segmentation
              • Framework version:
              • Python version: 3.6.1
              • CPU or GPU:
              • Custom Docker image (Y/N):
              Additional context
              
Add any other context about the problem here.
              Activity
              Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
              Metadata
              Metadata
              Assignees
              No one assigned
                Labels
                No labels
                No labels
                Type
                No type
                Projects
                No projects
                  Milestone
                  No milestone
                  Relationships
                  None yet
                  Development
                  No branches or pull requests
                  Issue actions
                  
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

                  Skip to content
                  Deploy() returns NoneType #1965
                  Closed
                  Closed
                  Deploy() returns NoneType#1965
                  Description
                  @vbabu29
                  vbabu29
                  opened on Oct 21, 2020
                  Describe the bug
                  Trying t o instantiate a Python SDK trained model which is stored in S3. The deploy() func returns a NoneType
                  Here is my code:
                  semsegtrainedmodel = sagemaker.model.Model(model_data=path,
                  
image='811284229777.dkr.ecr.us-east-1.amazonaws.com/semantic-segmentation:latest',
                  
role=role)
                  ss_predictor = semsegtrainedmodel.deploy(initial_instance_count=1, instance_type='ml.c4.xlarge')
                  Screenshots or logs
                  
print(type(ss_predictor))
                  
NoneType
                  System information
                  
A description of your system. Please provide:
                  • SageMaker Python SDK version: '1.72.1'
                  • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Semantic Segmentation
                  • Framework version:
                  • Python version: 3.6.1
                  • CPU or GPU:
                  • Custom Docker image (Y/N):
                  Additional context
                  
Add any other context about the problem here.
                  Activity
                  Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
                  Metadata
                  Metadata
                  Assignees
                  No one assigned
                    Labels
                    No labels
                    No labels
                    Type
                    No type
                    Projects
                    No projects
                      Milestone
                      No milestone
                      Relationships
                      None yet
                      Development
                      No branches or pull requests
                      Issue actions
                      
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

                      Skip to content
                      Deploy() returns NoneType #1965
                      Closed
                      Closed
                      Deploy() returns NoneType#1965
                      Description
                      @vbabu29
                      vbabu29
                      opened on Oct 21, 2020
                      Describe the bug
                      Trying t o instantiate a Python SDK trained model which is stored in S3. The deploy() func returns a NoneType
                      Here is my code:
                      semsegtrainedmodel = sagemaker.model.Model(model_data=path,
                      
image='811284229777.dkr.ecr.us-east-1.amazonaws.com/semantic-segmentation:latest',
                      
role=role)
                      ss_predictor = semsegtrainedmodel.deploy(initial_instance_count=1, instance_type='ml.c4.xlarge')
                      Screenshots or logs
                      
print(type(ss_predictor))
                      
NoneType
                      System information
                      
A description of your system. Please provide:
                      • SageMaker Python SDK version: '1.72.1'
                      • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Semantic Segmentation
                      • Framework version:
                      • Python version: 3.6.1
                      • CPU or GPU:
                      • Custom Docker image (Y/N):
                      Additional context
                      
Add any other context about the problem here.
                      Activity
                      Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
                      Metadata
                      Metadata
                      Assignees
                      No one assigned
                        Labels
                        No labels
                        No labels
                        Type
                        No type
                        Projects
                        No projects
                          Milestone
                          No milestone
                          Relationships
                          None yet
                          Development
                          No branches or pull requests
                          Issue actions
                          
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

                          Skip to content
                          Deploy() returns NoneType #1965
                          Closed
                          Closed
                          Deploy() returns NoneType#1965
                          Description
                          @vbabu29
                          vbabu29
                          opened on Oct 21, 2020
                          Describe the bug
                          Trying t o instantiate a Python SDK trained model which is stored in S3. The deploy() func returns a NoneType
                          Here is my code:
                          semsegtrainedmodel = sagemaker.model.Model(model_data=path,
                          
image='811284229777.dkr.ecr.us-east-1.amazonaws.com/semantic-segmentation:latest',
                          
role=role)
                          ss_predictor = semsegtrainedmodel.deploy(initial_instance_count=1, instance_type='ml.c4.xlarge')
                          Screenshots or logs
                          
print(type(ss_predictor))
                          
NoneType
                          System information
                          
A description of your system. Please provide:
                          • SageMaker Python SDK version: '1.72.1'
                          • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Semantic Segmentation
                          • Framework version:
                          • Python version: 3.6.1
                          • CPU or GPU:
                          • Custom Docker image (Y/N):
                          Additional context
                          
Add any other context about the problem here.
                          Activity
                          Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
                          Metadata
                          Metadata
                          Assignees
                          No one assigned
                            Labels
                            No labels
                            No labels
                            Type
                            No type
                            Projects
                            No projects
                              Milestone
                              No milestone
                              Relationships
                              None yet
                              Development
                              No branches or pull requests
                              Issue actions
                              
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

                              Skip to content
                              Deploy() returns NoneType #1965
                              Closed
                              Closed
                              Deploy() returns NoneType#1965
                              Description
                              @vbabu29
                              vbabu29
                              opened on Oct 21, 2020
                              Describe the bug
                              Trying t o instantiate a Python SDK trained model which is stored in S3. The deploy() func returns a NoneType
                              Here is my code:
                              semsegtrainedmodel = sagemaker.model.Model(model_data=path,
                              
image='811284229777.dkr.ecr.us-east-1.amazonaws.com/semantic-segmentation:latest',
                              
role=role)
                              ss_predictor = semsegtrainedmodel.deploy(initial_instance_count=1, instance_type='ml.c4.xlarge')
                              Screenshots or logs
                              
print(type(ss_predictor))
                              
NoneType
                              System information
                              
A description of your system. Please provide:
                              • SageMaker Python SDK version: '1.72.1'
                              • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Semantic Segmentation
                              • Framework version:
                              • Python version: 3.6.1
                              • CPU or GPU:
                              • Custom Docker image (Y/N):
                              Additional context
                              
Add any other context about the problem here.
                              Activity
                              Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
                              Metadata
                              Metadata
                              Assignees
                              No one assigned
                                Labels
                                No labels
                                No labels
                                Type
                                No type
                                Projects
                                No projects
                                  Milestone
                                  No milestone
                                  Relationships
                                  None yet
                                  Development
                                  No branches or pull requests
                                  Issue actions