training_config does not return MetricDefinitions #1448

Closed
Closed
training_config does not return MetricDefinitions#1448
Labels
status: pending releaseThe fix have been merged but not yet released to PyPItype: bug

Description

@shunjd
shunjd
opened on May 1, 2020

Describe the bug
sagemaker.workflow.airflow.training_config does not return the MetricDefinitions when it is provided in the estimator. However, tuning_config does have it.

Related: aws/aws-step-functions-data-science-sdk-python#40

MetricDefinitions in tuning_config

sagemaker-python-sdk/src/sagemaker/workflow/airflow.py

Line 372 in aceb8e0

train_config["AlgorithmSpecification"]["MetricDefinitions"] =tuner.metric_definitions

To reproduce

estimator = sagemaker.estimator.Estimator(
PCA_IMAGE,
role=EXECUTION_ROLE,
train_instance_count=1,
train_instance_type='ml.c4.xlarge',
output_path=s3_output_location,
metric_definitions=[{'Name': 'foo', 'Regex': 'bar=(.*?);'}]
)
result = training_config(estimator)
print(result)

Expected behavior
MetricDefinitions should be included in the result.

Screenshots or logs
N/A

System information
A description of your system. Please provide:

  • SageMaker Python SDK version: latest
  • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Estimator/TensforFlow
  • Framework version:
  • Python version:
  • CPU or GPU:
  • Custom Docker image (Y/N): N

Additional context
N/A

Metadata

Metadata

Assignees

No one assigned

    Labels

    status: pending releaseThe fix have been merged but not yet released to PyPItype: bug

    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("// 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
      training_config does not return MetricDefinitions #1448
      Closed
      Closed
      training_config does not return MetricDefinitions#1448
      Labels
      status: pending releaseThe fix have been merged but not yet released to PyPItype: bug
      Description
      @shunjd
      shunjd
      opened on May 1, 2020
      Describe the bug
      sagemaker.workflow.airflow.training_config does not return the MetricDefinitions when it is provided in the estimator. However, tuning_config does have it.
      Related: aws/aws-step-functions-data-science-sdk-python#40
      MetricDefinitions in tuning_config
      sagemaker-python-sdk/src/sagemaker/workflow/airflow.py
      
Line 372
in
aceb8e0
      train_config["AlgorithmSpecification"]["MetricDefinitions"] =tuner.metric_definitions
      To reproduce
      estimator = sagemaker.estimator.Estimator(
PCA_IMAGE,
role=EXECUTION_ROLE,
train_instance_count=1,
train_instance_type='ml.c4.xlarge',
output_path=s3_output_location,
metric_definitions=[{'Name': 'foo', 'Regex': 'bar=(.*?);'}]
)
result = training_config(estimator)
print(result)

      Expected behavior
      MetricDefinitions should be included in the result.
      Screenshots or logs
      
N/A
      System information
      
A description of your system. Please provide:
      • SageMaker Python SDK version: latest
      • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Estimator/TensforFlow
      • Framework version:
      • Python version:
      • CPU or GPU:
      • Custom Docker image (Y/N): N
      Additional context
      
N/A
      Metadata
      Metadata
      Assignees
      No one assigned
        Labels
        status: pending releaseThe fix have been merged but not yet released to PyPItype: bug
        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("// 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
          training_config does not return MetricDefinitions #1448
          Closed
          Closed
          training_config does not return MetricDefinitions#1448
          Labels
          status: pending releaseThe fix have been merged but not yet released to PyPItype: bug
          Description
          @shunjd
          shunjd
          opened on May 1, 2020
          Describe the bug
          sagemaker.workflow.airflow.training_config does not return the MetricDefinitions when it is provided in the estimator. However, tuning_config does have it.
          Related: aws/aws-step-functions-data-science-sdk-python#40
          MetricDefinitions in tuning_config
          sagemaker-python-sdk/src/sagemaker/workflow/airflow.py
          
Line 372
in
aceb8e0
          train_config["AlgorithmSpecification"]["MetricDefinitions"] =tuner.metric_definitions
          To reproduce
          estimator = sagemaker.estimator.Estimator(
PCA_IMAGE,
role=EXECUTION_ROLE,
train_instance_count=1,
train_instance_type='ml.c4.xlarge',
output_path=s3_output_location,
metric_definitions=[{'Name': 'foo', 'Regex': 'bar=(.*?);'}]
)
result = training_config(estimator)
print(result)

          Expected behavior
          MetricDefinitions should be included in the result.
          Screenshots or logs
          
N/A
          System information
          
A description of your system. Please provide:
          • SageMaker Python SDK version: latest
          • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Estimator/TensforFlow
          • Framework version:
          • Python version:
          • CPU or GPU:
          • Custom Docker image (Y/N): N
          Additional context
          
N/A
          Metadata
          Metadata
          Assignees
          No one assigned
            Labels
            status: pending releaseThe fix have been merged but not yet released to PyPItype: bug
            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
              training_config does not return MetricDefinitions #1448
              Closed
              Closed
              training_config does not return MetricDefinitions#1448
              Labels
              status: pending releaseThe fix have been merged but not yet released to PyPItype: bug
              Description
              @shunjd
              shunjd
              opened on May 1, 2020
              Describe the bug
              sagemaker.workflow.airflow.training_config does not return the MetricDefinitions when it is provided in the estimator. However, tuning_config does have it.
              Related: aws/aws-step-functions-data-science-sdk-python#40
              MetricDefinitions in tuning_config
              sagemaker-python-sdk/src/sagemaker/workflow/airflow.py
              
Line 372
in
aceb8e0
              train_config["AlgorithmSpecification"]["MetricDefinitions"] =tuner.metric_definitions
              To reproduce
              estimator = sagemaker.estimator.Estimator(
PCA_IMAGE,
role=EXECUTION_ROLE,
train_instance_count=1,
train_instance_type='ml.c4.xlarge',
output_path=s3_output_location,
metric_definitions=[{'Name': 'foo', 'Regex': 'bar=(.*?);'}]
)
result = training_config(estimator)
print(result)

              Expected behavior
              MetricDefinitions should be included in the result.
              Screenshots or logs
              
N/A
              System information
              
A description of your system. Please provide:
              • SageMaker Python SDK version: latest
              • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Estimator/TensforFlow
              • Framework version:
              • Python version:
              • CPU or GPU:
              • Custom Docker image (Y/N): N
              Additional context
              
N/A
              Metadata
              Metadata
              Assignees
              No one assigned
                Labels
                status: pending releaseThe fix have been merged but not yet released to PyPItype: bug
                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
                  training_config does not return MetricDefinitions #1448
                  Closed
                  Closed
                  training_config does not return MetricDefinitions#1448
                  Labels
                  status: pending releaseThe fix have been merged but not yet released to PyPItype: bug
                  Description
                  @shunjd
                  shunjd
                  opened on May 1, 2020
                  Describe the bug
                  sagemaker.workflow.airflow.training_config does not return the MetricDefinitions when it is provided in the estimator. However, tuning_config does have it.
                  Related: aws/aws-step-functions-data-science-sdk-python#40
                  MetricDefinitions in tuning_config
                  sagemaker-python-sdk/src/sagemaker/workflow/airflow.py
                  
Line 372
in
aceb8e0
                  train_config["AlgorithmSpecification"]["MetricDefinitions"] =tuner.metric_definitions
                  To reproduce
                  estimator = sagemaker.estimator.Estimator(
PCA_IMAGE,
role=EXECUTION_ROLE,
train_instance_count=1,
train_instance_type='ml.c4.xlarge',
output_path=s3_output_location,
metric_definitions=[{'Name': 'foo', 'Regex': 'bar=(.*?);'}]
)
result = training_config(estimator)
print(result)

                  Expected behavior
                  MetricDefinitions should be included in the result.
                  Screenshots or logs
                  
N/A
                  System information
                  
A description of your system. Please provide:
                  • SageMaker Python SDK version: latest
                  • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Estimator/TensforFlow
                  • Framework version:
                  • Python version:
                  • CPU or GPU:
                  • Custom Docker image (Y/N): N
                  Additional context
                  
N/A
                  Metadata
                  Metadata
                  Assignees
                  No one assigned
                    Labels
                    status: pending releaseThe fix have been merged but not yet released to PyPItype: bug
                    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
                      training_config does not return MetricDefinitions #1448
                      Closed
                      Closed
                      training_config does not return MetricDefinitions#1448
                      Labels
                      status: pending releaseThe fix have been merged but not yet released to PyPItype: bug
                      Description
                      @shunjd
                      shunjd
                      opened on May 1, 2020
                      Describe the bug
                      sagemaker.workflow.airflow.training_config does not return the MetricDefinitions when it is provided in the estimator. However, tuning_config does have it.
                      Related: aws/aws-step-functions-data-science-sdk-python#40
                      MetricDefinitions in tuning_config
                      sagemaker-python-sdk/src/sagemaker/workflow/airflow.py
                      
Line 372
in
aceb8e0
                      train_config["AlgorithmSpecification"]["MetricDefinitions"] =tuner.metric_definitions
                      To reproduce
                      estimator = sagemaker.estimator.Estimator(
PCA_IMAGE,
role=EXECUTION_ROLE,
train_instance_count=1,
train_instance_type='ml.c4.xlarge',
output_path=s3_output_location,
metric_definitions=[{'Name': 'foo', 'Regex': 'bar=(.*?);'}]
)
result = training_config(estimator)
print(result)

                      Expected behavior
                      MetricDefinitions should be included in the result.
                      Screenshots or logs
                      
N/A
                      System information
                      
A description of your system. Please provide:
                      • SageMaker Python SDK version: latest
                      • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Estimator/TensforFlow
                      • Framework version:
                      • Python version:
                      • CPU or GPU:
                      • Custom Docker image (Y/N): N
                      Additional context
                      
N/A
                      Metadata
                      Metadata
                      Assignees
                      No one assigned
                        Labels
                        status: pending releaseThe fix have been merged but not yet released to PyPItype: bug
                        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
                          training_config does not return MetricDefinitions #1448
                          Closed
                          Closed
                          training_config does not return MetricDefinitions#1448
                          Labels
                          status: pending releaseThe fix have been merged but not yet released to PyPItype: bug
                          Description
                          @shunjd
                          shunjd
                          opened on May 1, 2020
                          Describe the bug
                          sagemaker.workflow.airflow.training_config does not return the MetricDefinitions when it is provided in the estimator. However, tuning_config does have it.
                          Related: aws/aws-step-functions-data-science-sdk-python#40
                          MetricDefinitions in tuning_config
                          sagemaker-python-sdk/src/sagemaker/workflow/airflow.py
                          
Line 372
in
aceb8e0
                          train_config["AlgorithmSpecification"]["MetricDefinitions"] =tuner.metric_definitions
                          To reproduce
                          estimator = sagemaker.estimator.Estimator(
PCA_IMAGE,
role=EXECUTION_ROLE,
train_instance_count=1,
train_instance_type='ml.c4.xlarge',
output_path=s3_output_location,
metric_definitions=[{'Name': 'foo', 'Regex': 'bar=(.*?);'}]
)
result = training_config(estimator)
print(result)

                          Expected behavior
                          MetricDefinitions should be included in the result.
                          Screenshots or logs
                          
N/A
                          System information
                          
A description of your system. Please provide:
                          • SageMaker Python SDK version: latest
                          • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Estimator/TensforFlow
                          • Framework version:
                          • Python version:
                          • CPU or GPU:
                          • Custom Docker image (Y/N): N
                          Additional context
                          
N/A
                          Metadata
                          Metadata
                          Assignees
                          No one assigned
                            Labels
                            status: pending releaseThe fix have been merged but not yet released to PyPItype: bug
                            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
                              training_config does not return MetricDefinitions #1448
                              Closed
                              Closed
                              training_config does not return MetricDefinitions#1448
                              Labels
                              status: pending releaseThe fix have been merged but not yet released to PyPItype: bug
                              Description
                              @shunjd
                              shunjd
                              opened on May 1, 2020
                              Describe the bug
                              sagemaker.workflow.airflow.training_config does not return the MetricDefinitions when it is provided in the estimator. However, tuning_config does have it.
                              Related: aws/aws-step-functions-data-science-sdk-python#40
                              MetricDefinitions in tuning_config
                              sagemaker-python-sdk/src/sagemaker/workflow/airflow.py
                              
Line 372
in
aceb8e0
                              train_config["AlgorithmSpecification"]["MetricDefinitions"] =tuner.metric_definitions
                              To reproduce
                              estimator = sagemaker.estimator.Estimator(
PCA_IMAGE,
role=EXECUTION_ROLE,
train_instance_count=1,
train_instance_type='ml.c4.xlarge',
output_path=s3_output_location,
metric_definitions=[{'Name': 'foo', 'Regex': 'bar=(.*?);'}]
)
result = training_config(estimator)
print(result)

                              Expected behavior
                              MetricDefinitions should be included in the result.
                              Screenshots or logs
                              
N/A
                              System information
                              
A description of your system. Please provide:
                              • SageMaker Python SDK version: latest
                              • Framework name (eg. PyTorch) or algorithm (eg. KMeans): Estimator/TensforFlow
                              • Framework version:
                              • Python version:
                              • CPU or GPU:
                              • Custom Docker image (Y/N): N
                              Additional context
                              
N/A
                              Metadata
                              Metadata
                              Assignees
                              No one assigned
                                Labels
                                status: pending releaseThe fix have been merged but not yet released to PyPItype: bug
                                Type
                                No type
                                Projects
                                No projects
                                  Milestone
                                  No milestone
                                  Relationships
                                  None yet
                                  Development
                                  No branches or pull requests
                                  Issue actions