s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError #716

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Closed
s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError#716
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contributions welcometype: bug

Description

@andremoeller
andremoeller
opened on Mar 21, 2019

Please fill out the form below.

System Information

  • Python Version: 3.6
  • Python SDK Version: 1.18

Describe the problem

I'm trying to fit with an Estimator on Gzipped data with Pipe mode. I don't have input_mode set on the Estimator, but I do have it set in the s3_input, which should override the Estimator's input_mode:

sagemaker-python-sdk/src/sagemaker/session.py

Lines 1329 to 1336 in c2bac8f

input_mode (str): Optional override for this channel's input mode (default: None). By default, channels will
use the input mode defined on ``sagemaker.estimator.EstimatorBase.input_mode``, but they will ignore
that setting if this parameter is set.
* None - Amazon SageMaker will use the input mode specified in the ``Estimator``.
* 'File' - Amazon SageMaker copies the training dataset from the S3 location to a local directory.
* 'Pipe' - Amazon SageMaker streams data directly from S3 to the container via a Unix-named pipe.

My s3_input is:

training_s3_input = s3_input('s3://my_training_data', compression='Gzip', input_mode='Pipe', shuffle_config=ShuffleConfig(1))

Trying to fit on an Estimator gives me back this ValidationError, even though I specify Pipe, not File:

An error occurred (ValidationException) when calling the CreateTrainingJob operation: Invalid compression type for channel training: File mode only supports NONE, got Gzip instead

Setting input_mode='Pipe' directly on the Estimator works as expected.

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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
      s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError #716
      Closed
      Closed
      s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError#716
      Labels
      contributions welcometype: bug
      Description
      @andremoeller
      andremoeller
      opened on Mar 21, 2019
      Please fill out the form below.
      System Information
      • Python Version: 3.6
      • Python SDK Version: 1.18
      Describe the problem
      I'm trying to fit with an Estimator on Gzipped data with Pipe mode. I don't have input_mode set on the Estimator, but I do have it set in the s3_input, which should override the Estimator's input_mode:
      sagemaker-python-sdk/src/sagemaker/session.py
      
Lines 1329 to 1336
in
c2bac8f
       input_mode (str): Optional override for this channel's input mode (default: None). By default, channels will
       use the input mode defined on ``sagemaker.estimator.EstimatorBase.input_mode``, but they will ignore
       that setting if this parameter is set.
       * None - Amazon SageMaker will use the input mode specified in the ``Estimator``.
       * 'File' - Amazon SageMaker copies the training dataset from the S3 location to a local directory.
       * 'Pipe' - Amazon SageMaker streams data directly from S3 to the container via a Unix-named pipe.
      My s3_input is:
      training_s3_input = s3_input('s3://my_training_data', compression='Gzip', input_mode='Pipe', shuffle_config=ShuffleConfig(1))
      Trying to fit on an Estimator gives me back this ValidationError, even though I specify Pipe, not File:
      An error occurred (ValidationException) when calling the CreateTrainingJob operation: Invalid compression type for channel training: File mode only supports NONE, got Gzip instead
      Setting input_mode='Pipe' directly on the Estimator works as expected.
      Activity
      Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
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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
          s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError #716
          Closed
          Closed
          s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError#716
          Labels
          contributions welcometype: bug
          Description
          @andremoeller
          andremoeller
          opened on Mar 21, 2019
          Please fill out the form below.
          System Information
          • Python Version: 3.6
          • Python SDK Version: 1.18
          Describe the problem
          I'm trying to fit with an Estimator on Gzipped data with Pipe mode. I don't have input_mode set on the Estimator, but I do have it set in the s3_input, which should override the Estimator's input_mode:
          sagemaker-python-sdk/src/sagemaker/session.py
          
Lines 1329 to 1336
in
c2bac8f
           input_mode (str): Optional override for this channel's input mode (default: None). By default, channels will
           use the input mode defined on ``sagemaker.estimator.EstimatorBase.input_mode``, but they will ignore
           that setting if this parameter is set.
           * None - Amazon SageMaker will use the input mode specified in the ``Estimator``.
           * 'File' - Amazon SageMaker copies the training dataset from the S3 location to a local directory.
           * 'Pipe' - Amazon SageMaker streams data directly from S3 to the container via a Unix-named pipe.
          My s3_input is:
          training_s3_input = s3_input('s3://my_training_data', compression='Gzip', input_mode='Pipe', shuffle_config=ShuffleConfig(1))
          Trying to fit on an Estimator gives me back this ValidationError, even though I specify Pipe, not File:
          An error occurred (ValidationException) when calling the CreateTrainingJob operation: Invalid compression type for channel training: File mode only supports NONE, got Gzip instead
          Setting input_mode='Pipe' directly on the Estimator works as expected.
          Activity
          Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
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            contributions welcometype: bug
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              No branches or pull requests
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

              Skip to content
              s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError #716
              Closed
              Closed
              s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError#716
              Labels
              contributions welcometype: bug
              Description
              @andremoeller
              andremoeller
              opened on Mar 21, 2019
              Please fill out the form below.
              System Information
              • Python Version: 3.6
              • Python SDK Version: 1.18
              Describe the problem
              I'm trying to fit with an Estimator on Gzipped data with Pipe mode. I don't have input_mode set on the Estimator, but I do have it set in the s3_input, which should override the Estimator's input_mode:
              sagemaker-python-sdk/src/sagemaker/session.py
              
Lines 1329 to 1336
in
c2bac8f
               input_mode (str): Optional override for this channel's input mode (default: None). By default, channels will
               use the input mode defined on ``sagemaker.estimator.EstimatorBase.input_mode``, but they will ignore
               that setting if this parameter is set.
               * None - Amazon SageMaker will use the input mode specified in the ``Estimator``.
               * 'File' - Amazon SageMaker copies the training dataset from the S3 location to a local directory.
               * 'Pipe' - Amazon SageMaker streams data directly from S3 to the container via a Unix-named pipe.
              My s3_input is:
              training_s3_input = s3_input('s3://my_training_data', compression='Gzip', input_mode='Pipe', shuffle_config=ShuffleConfig(1))
              Trying to fit on an Estimator gives me back this ValidationError, even though I specify Pipe, not File:
              An error occurred (ValidationException) when calling the CreateTrainingJob operation: Invalid compression type for channel training: File mode only supports NONE, got Gzip instead
              Setting input_mode='Pipe' directly on the Estimator works as expected.
              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
                contributions welcometype: bug
                Type
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                  No milestone
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                  None yet
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                  No branches or pull requests
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

                  Skip to content
                  s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError #716
                  Closed
                  Closed
                  s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError#716
                  Labels
                  contributions welcometype: bug
                  Description
                  @andremoeller
                  andremoeller
                  opened on Mar 21, 2019
                  Please fill out the form below.
                  System Information
                  • Python Version: 3.6
                  • Python SDK Version: 1.18
                  Describe the problem
                  I'm trying to fit with an Estimator on Gzipped data with Pipe mode. I don't have input_mode set on the Estimator, but I do have it set in the s3_input, which should override the Estimator's input_mode:
                  sagemaker-python-sdk/src/sagemaker/session.py
                  
Lines 1329 to 1336
in
c2bac8f
                   input_mode (str): Optional override for this channel's input mode (default: None). By default, channels will
                   use the input mode defined on ``sagemaker.estimator.EstimatorBase.input_mode``, but they will ignore
                   that setting if this parameter is set.
                   * None - Amazon SageMaker will use the input mode specified in the ``Estimator``.
                   * 'File' - Amazon SageMaker copies the training dataset from the S3 location to a local directory.
                   * 'Pipe' - Amazon SageMaker streams data directly from S3 to the container via a Unix-named pipe.
                  My s3_input is:
                  training_s3_input = s3_input('s3://my_training_data', compression='Gzip', input_mode='Pipe', shuffle_config=ShuffleConfig(1))
                  Trying to fit on an Estimator gives me back this ValidationError, even though I specify Pipe, not File:
                  An error occurred (ValidationException) when calling the CreateTrainingJob operation: Invalid compression type for channel training: File mode only supports NONE, got Gzip instead
                  Setting input_mode='Pipe' directly on the Estimator works as expected.
                  Activity
                  Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
                  Metadata
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                  Assignees
                  No one assigned
                    Labels
                    contributions welcometype: bug
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                    No projects
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                      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
                      s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError #716
                      Closed
                      Closed
                      s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError#716
                      Labels
                      contributions welcometype: bug
                      Description
                      @andremoeller
                      andremoeller
                      opened on Mar 21, 2019
                      Please fill out the form below.
                      System Information
                      • Python Version: 3.6
                      • Python SDK Version: 1.18
                      Describe the problem
                      I'm trying to fit with an Estimator on Gzipped data with Pipe mode. I don't have input_mode set on the Estimator, but I do have it set in the s3_input, which should override the Estimator's input_mode:
                      sagemaker-python-sdk/src/sagemaker/session.py
                      
Lines 1329 to 1336
in
c2bac8f
                       input_mode (str): Optional override for this channel's input mode (default: None). By default, channels will
                       use the input mode defined on ``sagemaker.estimator.EstimatorBase.input_mode``, but they will ignore
                       that setting if this parameter is set.
                       * None - Amazon SageMaker will use the input mode specified in the ``Estimator``.
                       * 'File' - Amazon SageMaker copies the training dataset from the S3 location to a local directory.
                       * 'Pipe' - Amazon SageMaker streams data directly from S3 to the container via a Unix-named pipe.
                      My s3_input is:
                      training_s3_input = s3_input('s3://my_training_data', compression='Gzip', input_mode='Pipe', shuffle_config=ShuffleConfig(1))
                      Trying to fit on an Estimator gives me back this ValidationError, even though I specify Pipe, not File:
                      An error occurred (ValidationException) when calling the CreateTrainingJob operation: Invalid compression type for channel training: File mode only supports NONE, got Gzip instead
                      Setting input_mode='Pipe' directly on the Estimator works as expected.
                      Activity
                      Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
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                      Assignees
                      No one assigned
                        Labels
                        contributions welcometype: bug
                        Type
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                        Projects
                        No projects
                          Milestone
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                          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
                          s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError #716
                          Closed
                          Closed
                          s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError#716
                          Labels
                          contributions welcometype: bug
                          Description
                          @andremoeller
                          andremoeller
                          opened on Mar 21, 2019
                          Please fill out the form below.
                          System Information
                          • Python Version: 3.6
                          • Python SDK Version: 1.18
                          Describe the problem
                          I'm trying to fit with an Estimator on Gzipped data with Pipe mode. I don't have input_mode set on the Estimator, but I do have it set in the s3_input, which should override the Estimator's input_mode:
                          sagemaker-python-sdk/src/sagemaker/session.py
                          
Lines 1329 to 1336
in
c2bac8f
                           input_mode (str): Optional override for this channel's input mode (default: None). By default, channels will
                           use the input mode defined on ``sagemaker.estimator.EstimatorBase.input_mode``, but they will ignore
                           that setting if this parameter is set.
                           * None - Amazon SageMaker will use the input mode specified in the ``Estimator``.
                           * 'File' - Amazon SageMaker copies the training dataset from the S3 location to a local directory.
                           * 'Pipe' - Amazon SageMaker streams data directly from S3 to the container via a Unix-named pipe.
                          My s3_input is:
                          training_s3_input = s3_input('s3://my_training_data', compression='Gzip', input_mode='Pipe', shuffle_config=ShuffleConfig(1))
                          Trying to fit on an Estimator gives me back this ValidationError, even though I specify Pipe, not File:
                          An error occurred (ValidationException) when calling the CreateTrainingJob operation: Invalid compression type for channel training: File mode only supports NONE, got Gzip instead
                          Setting input_mode='Pipe' directly on the Estimator works as expected.
                          Activity
                          Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
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                          Assignees
                          No one assigned
                            Labels
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                            Type
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                            No projects
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                              None yet
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                              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); }
})();
})();

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                              s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError #716
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                              s3_input with "compression='Gzip', input_mode='Pipe'" fails with ValidationError#716
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                              contributions welcometype: bug
                              Description
                              @andremoeller
                              andremoeller
                              opened on Mar 21, 2019
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                              System Information
                              • Python Version: 3.6
                              • Python SDK Version: 1.18
                              Describe the problem
                              I'm trying to fit with an Estimator on Gzipped data with Pipe mode. I don't have input_mode set on the Estimator, but I do have it set in the s3_input, which should override the Estimator's input_mode:
                              sagemaker-python-sdk/src/sagemaker/session.py
                              
Lines 1329 to 1336
in
c2bac8f
                               input_mode (str): Optional override for this channel's input mode (default: None). By default, channels will
                               use the input mode defined on ``sagemaker.estimator.EstimatorBase.input_mode``, but they will ignore
                               that setting if this parameter is set.
                               * None - Amazon SageMaker will use the input mode specified in the ``Estimator``.
                               * 'File' - Amazon SageMaker copies the training dataset from the S3 location to a local directory.
                               * 'Pipe' - Amazon SageMaker streams data directly from S3 to the container via a Unix-named pipe.
                              My s3_input is:
                              training_s3_input = s3_input('s3://my_training_data', compression='Gzip', input_mode='Pipe', shuffle_config=ShuffleConfig(1))
                              Trying to fit on an Estimator gives me back this ValidationError, even though I specify Pipe, not File:
                              An error occurred (ValidationException) when calling the CreateTrainingJob operation: Invalid compression type for channel training: File mode only supports NONE, got Gzip instead
                              Setting input_mode='Pipe' directly on the Estimator works as expected.
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