Sagemaker training smdebug/core/state_store.py FileNotFoundError #1791

Description

@guptaanshul201989

Hello,

I am trying to train a model using MXnet estimator. As soon as training starts I see following error when Sagemaker tries to upload checkpoints:

File "/opt/ml/code/translation.py", line 224, in __call__
return super(NMTModel, self).__call__(src_seq, tgt_seq, src_valid_length, tgt_valid_length)
File "/usr/local/lib/python3.6/site-packages/mxnet/gluon/block.py", line 756, in __call__
hook(self, args)
File "/usr/local/lib/python3.6/site-packages/smdebug/mxnet/hook.py", line 143, in forward_pre_hook
self._increment_step()
File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 511, in _increment_step
self._write_state()
File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 523, in _write_state
if self.state_store.is_checkpoint_updated():
File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in is_checkpoint_updated
cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in <listcomp>
cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
File "/usr/local/lib/python3.6/genericpath.py", line 50, in getsize
return os.stat(filename).st_size
FileNotFoundError: [Errno 2] No such file or directory: '/opt/ml/checkpoints/metadata.json.sagemaker-uploading'
[2020-07-31 05:38:53.405 ip-10-2-236-41.ec2.internal:144 INFO utils.py:25] The end of training job file will not be written for jobs running under SageMaker.
2020-07-31 05:38:54,756 sagemaker-training-toolkit ERROR ExecuteUserScriptError:

Few details about the job:

  1. I am using Mxnet estimator with distributed setting
  2. Using 4 p3.16xlarge instances

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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

      Sagemaker training smdebug/core/state_store.py FileNotFoundError #1791

      Description

      @guptaanshul201989

      Hello,

      I am trying to train a model using MXnet estimator. As soon as training starts I see following error when Sagemaker tries to upload checkpoints:

      File "/opt/ml/code/translation.py", line 224, in __call__
      return super(NMTModel, self).__call__(src_seq, tgt_seq, src_valid_length, tgt_valid_length)
      File "/usr/local/lib/python3.6/site-packages/mxnet/gluon/block.py", line 756, in __call__
      hook(self, args)
      File "/usr/local/lib/python3.6/site-packages/smdebug/mxnet/hook.py", line 143, in forward_pre_hook
      self._increment_step()
      File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 511, in _increment_step
      self._write_state()
      File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 523, in _write_state
      if self.state_store.is_checkpoint_updated():
      File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in is_checkpoint_updated
      cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
      File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in <listcomp>
      cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
      File "/usr/local/lib/python3.6/genericpath.py", line 50, in getsize
      return os.stat(filename).st_size
      FileNotFoundError: [Errno 2] No such file or directory: '/opt/ml/checkpoints/metadata.json.sagemaker-uploading'
      [2020-07-31 05:38:53.405 ip-10-2-236-41.ec2.internal:144 INFO utils.py:25] The end of training job file will not be written for jobs running under SageMaker.
      2020-07-31 05:38:54,756 sagemaker-training-toolkit ERROR ExecuteUserScriptError:
      

      Few details about the job:

      1. I am using Mxnet estimator with distributed setting
      2. Using 4 p3.16xlarge instances

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      Metadata

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      No one assigned

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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

          Sagemaker training smdebug/core/state_store.py FileNotFoundError #1791

          Description

          @guptaanshul201989

          Hello,

          I am trying to train a model using MXnet estimator. As soon as training starts I see following error when Sagemaker tries to upload checkpoints:

          File "/opt/ml/code/translation.py", line 224, in __call__
          return super(NMTModel, self).__call__(src_seq, tgt_seq, src_valid_length, tgt_valid_length)
          File "/usr/local/lib/python3.6/site-packages/mxnet/gluon/block.py", line 756, in __call__
          hook(self, args)
          File "/usr/local/lib/python3.6/site-packages/smdebug/mxnet/hook.py", line 143, in forward_pre_hook
          self._increment_step()
          File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 511, in _increment_step
          self._write_state()
          File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 523, in _write_state
          if self.state_store.is_checkpoint_updated():
          File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in is_checkpoint_updated
          cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
          File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in <listcomp>
          cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
          File "/usr/local/lib/python3.6/genericpath.py", line 50, in getsize
          return os.stat(filename).st_size
          FileNotFoundError: [Errno 2] No such file or directory: '/opt/ml/checkpoints/metadata.json.sagemaker-uploading'
          [2020-07-31 05:38:53.405 ip-10-2-236-41.ec2.internal:144 INFO utils.py:25] The end of training job file will not be written for jobs running under SageMaker.
          2020-07-31 05:38:54,756 sagemaker-training-toolkit ERROR ExecuteUserScriptError:
          

          Few details about the job:

          1. I am using Mxnet estimator with distributed setting
          2. Using 4 p3.16xlarge instances

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          No one assigned

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            No type

            Projects

            No projects

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              No milestone

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              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

              Sagemaker training smdebug/core/state_store.py FileNotFoundError #1791

              Description

              @guptaanshul201989

              Hello,

              I am trying to train a model using MXnet estimator. As soon as training starts I see following error when Sagemaker tries to upload checkpoints:

              File "/opt/ml/code/translation.py", line 224, in __call__
              return super(NMTModel, self).__call__(src_seq, tgt_seq, src_valid_length, tgt_valid_length)
              File "/usr/local/lib/python3.6/site-packages/mxnet/gluon/block.py", line 756, in __call__
              hook(self, args)
              File "/usr/local/lib/python3.6/site-packages/smdebug/mxnet/hook.py", line 143, in forward_pre_hook
              self._increment_step()
              File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 511, in _increment_step
              self._write_state()
              File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 523, in _write_state
              if self.state_store.is_checkpoint_updated():
              File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in is_checkpoint_updated
              cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
              File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in <listcomp>
              cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
              File "/usr/local/lib/python3.6/genericpath.py", line 50, in getsize
              return os.stat(filename).st_size
              FileNotFoundError: [Errno 2] No such file or directory: '/opt/ml/checkpoints/metadata.json.sagemaker-uploading'
              [2020-07-31 05:38:53.405 ip-10-2-236-41.ec2.internal:144 INFO utils.py:25] The end of training job file will not be written for jobs running under SageMaker.
              2020-07-31 05:38:54,756 sagemaker-training-toolkit ERROR ExecuteUserScriptError:
              

              Few details about the job:

              1. I am using Mxnet estimator with distributed setting
              2. Using 4 p3.16xlarge instances

              Metadata

              Metadata

              Assignees

              No one assigned

                Type

                No type

                Projects

                No projects

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                  No milestone

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                  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

                  Sagemaker training smdebug/core/state_store.py FileNotFoundError #1791

                  Description

                  @guptaanshul201989

                  Hello,

                  I am trying to train a model using MXnet estimator. As soon as training starts I see following error when Sagemaker tries to upload checkpoints:

                  File "/opt/ml/code/translation.py", line 224, in __call__
                  return super(NMTModel, self).__call__(src_seq, tgt_seq, src_valid_length, tgt_valid_length)
                  File "/usr/local/lib/python3.6/site-packages/mxnet/gluon/block.py", line 756, in __call__
                  hook(self, args)
                  File "/usr/local/lib/python3.6/site-packages/smdebug/mxnet/hook.py", line 143, in forward_pre_hook
                  self._increment_step()
                  File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 511, in _increment_step
                  self._write_state()
                  File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 523, in _write_state
                  if self.state_store.is_checkpoint_updated():
                  File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in is_checkpoint_updated
                  cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
                  File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in <listcomp>
                  cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
                  File "/usr/local/lib/python3.6/genericpath.py", line 50, in getsize
                  return os.stat(filename).st_size
                  FileNotFoundError: [Errno 2] No such file or directory: '/opt/ml/checkpoints/metadata.json.sagemaker-uploading'
                  [2020-07-31 05:38:53.405 ip-10-2-236-41.ec2.internal:144 INFO utils.py:25] The end of training job file will not be written for jobs running under SageMaker.
                  2020-07-31 05:38:54,756 sagemaker-training-toolkit ERROR ExecuteUserScriptError:
                  

                  Few details about the job:

                  1. I am using Mxnet estimator with distributed setting
                  2. Using 4 p3.16xlarge instances

                  Metadata

                  Metadata

                  Assignees

                  No one assigned

                    Type

                    No type

                    Projects

                    No projects

                      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("// 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

                      Sagemaker training smdebug/core/state_store.py FileNotFoundError #1791

                      Description

                      @guptaanshul201989

                      Hello,

                      I am trying to train a model using MXnet estimator. As soon as training starts I see following error when Sagemaker tries to upload checkpoints:

                      File "/opt/ml/code/translation.py", line 224, in __call__
                      return super(NMTModel, self).__call__(src_seq, tgt_seq, src_valid_length, tgt_valid_length)
                      File "/usr/local/lib/python3.6/site-packages/mxnet/gluon/block.py", line 756, in __call__
                      hook(self, args)
                      File "/usr/local/lib/python3.6/site-packages/smdebug/mxnet/hook.py", line 143, in forward_pre_hook
                      self._increment_step()
                      File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 511, in _increment_step
                      self._write_state()
                      File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 523, in _write_state
                      if self.state_store.is_checkpoint_updated():
                      File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in is_checkpoint_updated
                      cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
                      File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in <listcomp>
                      cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
                      File "/usr/local/lib/python3.6/genericpath.py", line 50, in getsize
                      return os.stat(filename).st_size
                      FileNotFoundError: [Errno 2] No such file or directory: '/opt/ml/checkpoints/metadata.json.sagemaker-uploading'
                      [2020-07-31 05:38:53.405 ip-10-2-236-41.ec2.internal:144 INFO utils.py:25] The end of training job file will not be written for jobs running under SageMaker.
                      2020-07-31 05:38:54,756 sagemaker-training-toolkit ERROR ExecuteUserScriptError:
                      

                      Few details about the job:

                      1. I am using Mxnet estimator with distributed setting
                      2. Using 4 p3.16xlarge instances

                      Metadata

                      Metadata

                      Assignees

                      No one assigned

                        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

                          Sagemaker training smdebug/core/state_store.py FileNotFoundError #1791

                          Description

                          @guptaanshul201989

                          Hello,

                          I am trying to train a model using MXnet estimator. As soon as training starts I see following error when Sagemaker tries to upload checkpoints:

                          File "/opt/ml/code/translation.py", line 224, in __call__
                          return super(NMTModel, self).__call__(src_seq, tgt_seq, src_valid_length, tgt_valid_length)
                          File "/usr/local/lib/python3.6/site-packages/mxnet/gluon/block.py", line 756, in __call__
                          hook(self, args)
                          File "/usr/local/lib/python3.6/site-packages/smdebug/mxnet/hook.py", line 143, in forward_pre_hook
                          self._increment_step()
                          File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 511, in _increment_step
                          self._write_state()
                          File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 523, in _write_state
                          if self.state_store.is_checkpoint_updated():
                          File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in is_checkpoint_updated
                          cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
                          File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in <listcomp>
                          cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
                          File "/usr/local/lib/python3.6/genericpath.py", line 50, in getsize
                          return os.stat(filename).st_size
                          FileNotFoundError: [Errno 2] No such file or directory: '/opt/ml/checkpoints/metadata.json.sagemaker-uploading'
                          [2020-07-31 05:38:53.405 ip-10-2-236-41.ec2.internal:144 INFO utils.py:25] The end of training job file will not be written for jobs running under SageMaker.
                          2020-07-31 05:38:54,756 sagemaker-training-toolkit ERROR ExecuteUserScriptError:
                          

                          Few details about the job:

                          1. I am using Mxnet estimator with distributed setting
                          2. Using 4 p3.16xlarge instances

                          Metadata

                          Metadata

                          Assignees

                          No one assigned

                            Type

                            No type

                            Projects

                            No projects

                              Milestone

                              No milestone

                              Relationships

                              None yet

                              Development

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                              , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
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                              Sagemaker training smdebug/core/state_store.py FileNotFoundError #1791

                              Description

                              @guptaanshul201989

                              Hello,

                              I am trying to train a model using MXnet estimator. As soon as training starts I see following error when Sagemaker tries to upload checkpoints:

                              File "/opt/ml/code/translation.py", line 224, in __call__
                              return super(NMTModel, self).__call__(src_seq, tgt_seq, src_valid_length, tgt_valid_length)
                              File "/usr/local/lib/python3.6/site-packages/mxnet/gluon/block.py", line 756, in __call__
                              hook(self, args)
                              File "/usr/local/lib/python3.6/site-packages/smdebug/mxnet/hook.py", line 143, in forward_pre_hook
                              self._increment_step()
                              File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 511, in _increment_step
                              self._write_state()
                              File "/usr/local/lib/python3.6/site-packages/smdebug/core/hook.py", line 523, in _write_state
                              if self.state_store.is_checkpoint_updated():
                              File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in is_checkpoint_updated
                              cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
                              File "/usr/local/lib/python3.6/site-packages/smdebug/core/state_store.py", line 112, in <listcomp>
                              cp_file_sizes = [os.path.getsize(file) for file in checkpoint_files]
                              File "/usr/local/lib/python3.6/genericpath.py", line 50, in getsize
                              return os.stat(filename).st_size
                              FileNotFoundError: [Errno 2] No such file or directory: '/opt/ml/checkpoints/metadata.json.sagemaker-uploading'
                              [2020-07-31 05:38:53.405 ip-10-2-236-41.ec2.internal:144 INFO utils.py:25] The end of training job file will not be written for jobs running under SageMaker.
                              2020-07-31 05:38:54,756 sagemaker-training-toolkit ERROR ExecuteUserScriptError:
                              

                              Few details about the job:

                              1. I am using Mxnet estimator with distributed setting
                              2. Using 4 p3.16xlarge instances

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