change: convert TF legacy mode parameters to hyperparameters in v2 migration script - #1534

Merged
laurenyu merged 4 commits into
aws:zweifrom
laurenyu:migration-script-tf-legacy-parameters
May 29, 2020
Merged

change: convert TF legacy mode parameters to hyperparameters in v2 migration script#1534
laurenyu merged 4 commits into
aws:zweifrom
laurenyu:migration-script-tf-legacy-parameters

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@laurenyulaurenyu commented May 29, 2020•
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Issue #, if available:
#1478, #1462

Description of changes:
follow-up to #1510. I'll add another modifier class to handle fit(run_tensorboard_locally=True) in a separate PR to try and keep these PRs manageable.

Testing done:
ran locally:

$ cat input.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow()
TensorFlow(script_mode=True)
TensorFlow(py_version="py3")
TensorFlow(
checkpoint_path="s3://foo/bar",
training_steps=100,
evaluation_steps=10,
requirements_file="source/requirements.txt",
)
TensorFlow(training_steps=100, evaluation_steps=10, script_mode=False)
TensorFlow(
framework_version="1.4",
training_steps=100,
evaluation_steps=10,
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo'}
)
random()
random.made_up_function()
$ sagemaker-upgrade-v2 --in-file input.py --out-file output.py
$ cat output.py
Overwriting file output.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow(framework_version='1.11.0', script_mode=False)
TensorFlow(framework_version='1.11.0', script_mode=True)
TensorFlow(framework_version='1.11.0', py_version="py3")
TensorFlow(
framework_version='1.11.0',
hyperparameters={'checkpoint_path': "s3://foo/bar", 'training_steps': 100, 'evaluation_steps': 10, 'sagemaker_requirements': "source/requirements.txt"},
script_mode=False,
)
TensorFlow(framework_version='1.11.0', hyperparameters={'training_steps': 100, 'evaluation_steps': 10}, script_mode=False)
TensorFlow(
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo', 'training_steps': 100, 'evaluation_steps': 10},
script_mode=False,
framework_version="1.4")
random()
random.made_up_function()

also added some unit tests and ran those

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  • I have checked that my tests are not configured for a specific region or account (if appropriate)
  • I have used unique_name_from_base to create resource names in integ tests (if appropriate)

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

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looks good to me

Comment threadsrc/sagemaker/cli/compatibility/v2/modifiers/tf_legacy_mode.py
Comment threadsrc/sagemaker/cli/compatibility/v2/ast_transformer.py
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looks good to me

@laurenyu
laurenyu merged commit a680be1 into aws:zweiMay 29, 2020
@laurenyu
laurenyu deleted the migration-script-tf-legacy-parameters branch May 29, 2020 23:17
@laurenyulaurenyu mentioned this pull request May 30, 2020
Merged
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Evan-W-ang added a commit to Evan-W-ang/sagemaker-python-sdk that referenced this pull request Jun 8, 2026
@Evan-W-ang
change: convert TF legacy mode parameters to hyperparameters in v2 mi…
479e62c
…gration script (aws#1534)
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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
} 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
change: convert TF legacy mode parameters to hyperparameters in v2 migration script - #1534
Merged
laurenyu merged 4 commits into
aws:zweifrom 
laurenyu:migration-script-tf-legacy-parameters
May 29, 2020
Merged
change: convert TF legacy mode parameters to hyperparameters in v2 migration script#1534
laurenyu merged 4 commits into
aws:zweifrom 
laurenyu:migration-script-tf-legacy-parameters
Conversation
@laurenyu
@laurenyulaurenyu
commented
May 29, 2020•

edited

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Contributor
Issue #, if available:
#1478, #1462
Description of changes:

follow-up to #1510. I'll add another modifier class to handle fit(run_tensorboard_locally=True) in a separate PR to try and keep these PRs manageable.
Testing done:

ran locally:
$ cat input.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow()
TensorFlow(script_mode=True)
TensorFlow(py_version="py3")
TensorFlow(
checkpoint_path="s3://foo/bar",
training_steps=100,
evaluation_steps=10,
requirements_file="source/requirements.txt",
)
TensorFlow(training_steps=100, evaluation_steps=10, script_mode=False)
TensorFlow(
framework_version="1.4",
training_steps=100,
evaluation_steps=10,
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo'}
)
random()
random.made_up_function()
$ sagemaker-upgrade-v2 --in-file input.py --out-file output.py
$ cat output.py
Overwriting file output.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow(framework_version='1.11.0', script_mode=False)
TensorFlow(framework_version='1.11.0', script_mode=True)
TensorFlow(framework_version='1.11.0', py_version="py3")
TensorFlow(
framework_version='1.11.0',
hyperparameters={'checkpoint_path': "s3://foo/bar", 'training_steps': 100, 'evaluation_steps': 10, 'sagemaker_requirements': "source/requirements.txt"},
script_mode=False,
)
TensorFlow(framework_version='1.11.0', hyperparameters={'training_steps': 100, 'evaluation_steps': 10}, script_mode=False)
TensorFlow(
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo', 'training_steps': 100, 'evaluation_steps': 10},
script_mode=False,
framework_version="1.4")
random()
random.made_up_function()

also added some unit tests and ran those
Merge Checklist
Put an x in the boxes that apply. You can also fill these out after creating the PR. If you're unsure about any of them, don't hesitate to ask. We're here to help! This is simply a reminder of what we are going to look for before merging your pull request.
General
  •  I have read the CONTRIBUTING doc
  •  I used the commit message format described in CONTRIBUTING
  •  I have passed the region in to any/all clients that I've initialized as part of this change.
  •  I have updated any necessary documentation, including READMEs and API docs (if appropriate)
Tests
  •  I have added tests that prove my fix is effective or that my feature works (if appropriate)
  •  I have checked that my tests are not configured for a specific region or account (if appropriate)
  •  I have used unique_name_from_base to create resource names in integ tests (if appropriate)
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
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looks good to me
Comment threadsrc/sagemaker/cli/compatibility/v2/modifiers/tf_legacy_mode.py
Comment threadsrc/sagemaker/cli/compatibility/v2/ast_transformer.py
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looks good to me
@laurenyu
laurenyu
merged commit a680be1
into
aws:zweiMay 29, 2020
@laurenyu
laurenyu
deleted the

migration-script-tf-legacy-parameters

branch
May 29, 2020 23:17
@laurenyulaurenyu
mentioned this pull request
May 30, 2020
 Merged

7 tasks
Evan-W-ang added a commit
to Evan-W-ang/sagemaker-python-sdk
that referenced
this pull request
Jun 8, 2026
@Evan-W-ang
change: convert TF legacy mode parameters to hyperparameters in v2 mi…
479e62c
…gration script (aws#1534)
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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
change: convert TF legacy mode parameters to hyperparameters in v2 migration script - #1534
Merged
laurenyu merged 4 commits into
aws:zweifrom 
laurenyu:migration-script-tf-legacy-parameters
May 29, 2020
Merged
change: convert TF legacy mode parameters to hyperparameters in v2 migration script#1534
laurenyu merged 4 commits into
aws:zweifrom 
laurenyu:migration-script-tf-legacy-parameters
Conversation
@laurenyu
@laurenyulaurenyu
commented
May 29, 2020•

edited

Loading

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Contributor
Issue #, if available:
#1478, #1462
Description of changes:

follow-up to #1510. I'll add another modifier class to handle fit(run_tensorboard_locally=True) in a separate PR to try and keep these PRs manageable.
Testing done:

ran locally:
$ cat input.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow()
TensorFlow(script_mode=True)
TensorFlow(py_version="py3")
TensorFlow(
checkpoint_path="s3://foo/bar",
training_steps=100,
evaluation_steps=10,
requirements_file="source/requirements.txt",
)
TensorFlow(training_steps=100, evaluation_steps=10, script_mode=False)
TensorFlow(
framework_version="1.4",
training_steps=100,
evaluation_steps=10,
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo'}
)
random()
random.made_up_function()
$ sagemaker-upgrade-v2 --in-file input.py --out-file output.py
$ cat output.py
Overwriting file output.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow(framework_version='1.11.0', script_mode=False)
TensorFlow(framework_version='1.11.0', script_mode=True)
TensorFlow(framework_version='1.11.0', py_version="py3")
TensorFlow(
framework_version='1.11.0',
hyperparameters={'checkpoint_path': "s3://foo/bar", 'training_steps': 100, 'evaluation_steps': 10, 'sagemaker_requirements': "source/requirements.txt"},
script_mode=False,
)
TensorFlow(framework_version='1.11.0', hyperparameters={'training_steps': 100, 'evaluation_steps': 10}, script_mode=False)
TensorFlow(
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo', 'training_steps': 100, 'evaluation_steps': 10},
script_mode=False,
framework_version="1.4")
random()
random.made_up_function()

also added some unit tests and ran those
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looks good to me
Comment threadsrc/sagemaker/cli/compatibility/v2/modifiers/tf_legacy_mode.py
Comment threadsrc/sagemaker/cli/compatibility/v2/ast_transformer.py
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looks good to me
@laurenyu
laurenyu
merged commit a680be1
into
aws:zweiMay 29, 2020
@laurenyu
laurenyu
deleted the

migration-script-tf-legacy-parameters

branch
May 29, 2020 23:17
@laurenyulaurenyu
mentioned this pull request
May 30, 2020
 Merged

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to Evan-W-ang/sagemaker-python-sdk
that referenced
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Jun 8, 2026
@Evan-W-ang
change: convert TF legacy mode parameters to hyperparameters in v2 mi…
479e62c
…gration script (aws#1534)
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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
change: convert TF legacy mode parameters to hyperparameters in v2 migration script - #1534
Merged
laurenyu merged 4 commits into
aws:zweifrom 
laurenyu:migration-script-tf-legacy-parameters
May 29, 2020
Merged
change: convert TF legacy mode parameters to hyperparameters in v2 migration script#1534
laurenyu merged 4 commits into
aws:zweifrom 
laurenyu:migration-script-tf-legacy-parameters
Conversation
@laurenyu
@laurenyulaurenyu
commented
May 29, 2020•

edited

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Issue #, if available:
#1478, #1462
Description of changes:

follow-up to #1510. I'll add another modifier class to handle fit(run_tensorboard_locally=True) in a separate PR to try and keep these PRs manageable.
Testing done:

ran locally:
$ cat input.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow()
TensorFlow(script_mode=True)
TensorFlow(py_version="py3")
TensorFlow(
checkpoint_path="s3://foo/bar",
training_steps=100,
evaluation_steps=10,
requirements_file="source/requirements.txt",
)
TensorFlow(training_steps=100, evaluation_steps=10, script_mode=False)
TensorFlow(
framework_version="1.4",
training_steps=100,
evaluation_steps=10,
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo'}
)
random()
random.made_up_function()
$ sagemaker-upgrade-v2 --in-file input.py --out-file output.py
$ cat output.py
Overwriting file output.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow(framework_version='1.11.0', script_mode=False)
TensorFlow(framework_version='1.11.0', script_mode=True)
TensorFlow(framework_version='1.11.0', py_version="py3")
TensorFlow(
framework_version='1.11.0',
hyperparameters={'checkpoint_path': "s3://foo/bar", 'training_steps': 100, 'evaluation_steps': 10, 'sagemaker_requirements': "source/requirements.txt"},
script_mode=False,
)
TensorFlow(framework_version='1.11.0', hyperparameters={'training_steps': 100, 'evaluation_steps': 10}, script_mode=False)
TensorFlow(
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo', 'training_steps': 100, 'evaluation_steps': 10},
script_mode=False,
framework_version="1.4")
random()
random.made_up_function()

also added some unit tests and ran those
Merge Checklist
Put an x in the boxes that apply. You can also fill these out after creating the PR. If you're unsure about any of them, don't hesitate to ask. We're here to help! This is simply a reminder of what we are going to look for before merging your pull request.
General
  •  I have read the CONTRIBUTING doc
  •  I used the commit message format described in CONTRIBUTING
  •  I have passed the region in to any/all clients that I've initialized as part of this change.
  •  I have updated any necessary documentation, including READMEs and API docs (if appropriate)
Tests
  •  I have added tests that prove my fix is effective or that my feature works (if appropriate)
  •  I have checked that my tests are not configured for a specific region or account (if appropriate)
  •  I have used unique_name_from_base to create resource names in integ tests (if appropriate)
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
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looks good to me
Comment threadsrc/sagemaker/cli/compatibility/v2/modifiers/tf_legacy_mode.py
Comment threadsrc/sagemaker/cli/compatibility/v2/ast_transformer.py
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looks good to me
@laurenyu
laurenyu
merged commit a680be1
into
aws:zweiMay 29, 2020
@laurenyu
laurenyu
deleted the

migration-script-tf-legacy-parameters

branch
May 29, 2020 23:17
@laurenyulaurenyu
mentioned this pull request
May 30, 2020
 Merged

7 tasks
Evan-W-ang added a commit
to Evan-W-ang/sagemaker-python-sdk
that referenced
this pull request
Jun 8, 2026
@Evan-W-ang
change: convert TF legacy mode parameters to hyperparameters in v2 mi…
479e62c
…gration script (aws#1534)
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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
change: convert TF legacy mode parameters to hyperparameters in v2 migration script - #1534
Merged
laurenyu merged 4 commits into
aws:zweifrom 
laurenyu:migration-script-tf-legacy-parameters
May 29, 2020
Merged
change: convert TF legacy mode parameters to hyperparameters in v2 migration script#1534
laurenyu merged 4 commits into
aws:zweifrom 
laurenyu:migration-script-tf-legacy-parameters
Conversation
@laurenyu
@laurenyulaurenyu
commented
May 29, 2020•

edited

Loading

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Contributor
Issue #, if available:
#1478, #1462
Description of changes:

follow-up to #1510. I'll add another modifier class to handle fit(run_tensorboard_locally=True) in a separate PR to try and keep these PRs manageable.
Testing done:

ran locally:
$ cat input.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow()
TensorFlow(script_mode=True)
TensorFlow(py_version="py3")
TensorFlow(
checkpoint_path="s3://foo/bar",
training_steps=100,
evaluation_steps=10,
requirements_file="source/requirements.txt",
)
TensorFlow(training_steps=100, evaluation_steps=10, script_mode=False)
TensorFlow(
framework_version="1.4",
training_steps=100,
evaluation_steps=10,
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo'}
)
random()
random.made_up_function()
$ sagemaker-upgrade-v2 --in-file input.py --out-file output.py
$ cat output.py
Overwriting file output.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow(framework_version='1.11.0', script_mode=False)
TensorFlow(framework_version='1.11.0', script_mode=True)
TensorFlow(framework_version='1.11.0', py_version="py3")
TensorFlow(
framework_version='1.11.0',
hyperparameters={'checkpoint_path': "s3://foo/bar", 'training_steps': 100, 'evaluation_steps': 10, 'sagemaker_requirements': "source/requirements.txt"},
script_mode=False,
)
TensorFlow(framework_version='1.11.0', hyperparameters={'training_steps': 100, 'evaluation_steps': 10}, script_mode=False)
TensorFlow(
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo', 'training_steps': 100, 'evaluation_steps': 10},
script_mode=False,
framework_version="1.4")
random()
random.made_up_function()

also added some unit tests and ran those
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looks good to me
Comment threadsrc/sagemaker/cli/compatibility/v2/modifiers/tf_legacy_mode.py
Comment threadsrc/sagemaker/cli/compatibility/v2/ast_transformer.py
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looks good to me
@laurenyu
laurenyu
merged commit a680be1
into
aws:zweiMay 29, 2020
@laurenyu
laurenyu
deleted the

migration-script-tf-legacy-parameters

branch
May 29, 2020 23:17
@laurenyulaurenyu
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@Evan-W-ang
change: convert TF legacy mode parameters to hyperparameters in v2 mi…
479e62c
…gration script (aws#1534)
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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
change: convert TF legacy mode parameters to hyperparameters in v2 migration script - #1534
Merged
laurenyu merged 4 commits into
aws:zweifrom 
laurenyu:migration-script-tf-legacy-parameters
May 29, 2020
Merged
change: convert TF legacy mode parameters to hyperparameters in v2 migration script#1534
laurenyu merged 4 commits into
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laurenyu:migration-script-tf-legacy-parameters
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@laurenyu
@laurenyulaurenyu
commented
May 29, 2020•

edited

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Issue #, if available:
#1478, #1462
Description of changes:

follow-up to #1510. I'll add another modifier class to handle fit(run_tensorboard_locally=True) in a separate PR to try and keep these PRs manageable.
Testing done:

ran locally:
$ cat input.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow()
TensorFlow(script_mode=True)
TensorFlow(py_version="py3")
TensorFlow(
checkpoint_path="s3://foo/bar",
training_steps=100,
evaluation_steps=10,
requirements_file="source/requirements.txt",
)
TensorFlow(training_steps=100, evaluation_steps=10, script_mode=False)
TensorFlow(
framework_version="1.4",
training_steps=100,
evaluation_steps=10,
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo'}
)
random()
random.made_up_function()
$ sagemaker-upgrade-v2 --in-file input.py --out-file output.py
$ cat output.py
Overwriting file output.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow(framework_version='1.11.0', script_mode=False)
TensorFlow(framework_version='1.11.0', script_mode=True)
TensorFlow(framework_version='1.11.0', py_version="py3")
TensorFlow(
framework_version='1.11.0',
hyperparameters={'checkpoint_path': "s3://foo/bar", 'training_steps': 100, 'evaluation_steps': 10, 'sagemaker_requirements': "source/requirements.txt"},
script_mode=False,
)
TensorFlow(framework_version='1.11.0', hyperparameters={'training_steps': 100, 'evaluation_steps': 10}, script_mode=False)
TensorFlow(
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo', 'training_steps': 100, 'evaluation_steps': 10},
script_mode=False,
framework_version="1.4")
random()
random.made_up_function()

also added some unit tests and ran those
Merge Checklist
Put an x in the boxes that apply. You can also fill these out after creating the PR. If you're unsure about any of them, don't hesitate to ask. We're here to help! This is simply a reminder of what we are going to look for before merging your pull request.
General
  •  I have read the CONTRIBUTING doc
  •  I used the commit message format described in CONTRIBUTING
  •  I have passed the region in to any/all clients that I've initialized as part of this change.
  •  I have updated any necessary documentation, including READMEs and API docs (if appropriate)
Tests
  •  I have added tests that prove my fix is effective or that my feature works (if appropriate)
  •  I have checked that my tests are not configured for a specific region or account (if appropriate)
  •  I have used unique_name_from_base to create resource names in integ tests (if appropriate)
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
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looks good to me
Comment threadsrc/sagemaker/cli/compatibility/v2/modifiers/tf_legacy_mode.py
Comment threadsrc/sagemaker/cli/compatibility/v2/ast_transformer.py
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looks good to me
@laurenyu
laurenyu
merged commit a680be1
into
aws:zweiMay 29, 2020
@laurenyu
laurenyu
deleted the

migration-script-tf-legacy-parameters

branch
May 29, 2020 23:17
@laurenyulaurenyu
mentioned this pull request
May 30, 2020
 Merged

7 tasks
Evan-W-ang added a commit
to Evan-W-ang/sagemaker-python-sdk
that referenced
this pull request
Jun 8, 2026
@Evan-W-ang
change: convert TF legacy mode parameters to hyperparameters in v2 mi…
479e62c
…gration script (aws#1534)
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, '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
change: convert TF legacy mode parameters to hyperparameters in v2 migration script - #1534
Merged
laurenyu merged 4 commits into
aws:zweifrom 
laurenyu:migration-script-tf-legacy-parameters
May 29, 2020
Merged
change: convert TF legacy mode parameters to hyperparameters in v2 migration script#1534
laurenyu merged 4 commits into
aws:zweifrom 
laurenyu:migration-script-tf-legacy-parameters
Conversation
@laurenyu
@laurenyulaurenyu
commented
May 29, 2020•

edited

Loading

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Contributor
Issue #, if available:
#1478, #1462
Description of changes:

follow-up to #1510. I'll add another modifier class to handle fit(run_tensorboard_locally=True) in a separate PR to try and keep these PRs manageable.
Testing done:

ran locally:
$ cat input.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow()
TensorFlow(script_mode=True)
TensorFlow(py_version="py3")
TensorFlow(
checkpoint_path="s3://foo/bar",
training_steps=100,
evaluation_steps=10,
requirements_file="source/requirements.txt",
)
TensorFlow(training_steps=100, evaluation_steps=10, script_mode=False)
TensorFlow(
framework_version="1.4",
training_steps=100,
evaluation_steps=10,
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo'}
)
random()
random.made_up_function()
$ sagemaker-upgrade-v2 --in-file input.py --out-file output.py
$ cat output.py
Overwriting file output.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow(framework_version='1.11.0', script_mode=False)
TensorFlow(framework_version='1.11.0', script_mode=True)
TensorFlow(framework_version='1.11.0', py_version="py3")
TensorFlow(
framework_version='1.11.0',
hyperparameters={'checkpoint_path': "s3://foo/bar", 'training_steps': 100, 'evaluation_steps': 10, 'sagemaker_requirements': "source/requirements.txt"},
script_mode=False,
)
TensorFlow(framework_version='1.11.0', hyperparameters={'training_steps': 100, 'evaluation_steps': 10}, script_mode=False)
TensorFlow(
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo', 'training_steps': 100, 'evaluation_steps': 10},
script_mode=False,
framework_version="1.4")
random()
random.made_up_function()

also added some unit tests and ran those
Merge Checklist
Put an x in the boxes that apply. You can also fill these out after creating the PR. If you're unsure about any of them, don't hesitate to ask. We're here to help! This is simply a reminder of what we are going to look for before merging your pull request.
General
  •  I have read the CONTRIBUTING doc
  •  I used the commit message format described in CONTRIBUTING
  •  I have passed the region in to any/all clients that I've initialized as part of this change.
  •  I have updated any necessary documentation, including READMEs and API docs (if appropriate)
Tests
  •  I have added tests that prove my fix is effective or that my feature works (if appropriate)
  •  I have checked that my tests are not configured for a specific region or account (if appropriate)
  •  I have used unique_name_from_base to create resource names in integ tests (if appropriate)
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
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looks good to me
Comment threadsrc/sagemaker/cli/compatibility/v2/modifiers/tf_legacy_mode.py
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looks good to me
@laurenyu
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@Evan-W-ang
change: convert TF legacy mode parameters to hyperparameters in v2 mi…
479e62c
…gration script (aws#1534)
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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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change: convert TF legacy mode parameters to hyperparameters in v2 migration script - #1534
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laurenyu:migration-script-tf-legacy-parameters
May 29, 2020
Merged
change: convert TF legacy mode parameters to hyperparameters in v2 migration script#1534
laurenyu merged 4 commits into
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laurenyu:migration-script-tf-legacy-parameters
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May 29, 2020•

edited

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Issue #, if available:
#1478, #1462
Description of changes:

follow-up to #1510. I'll add another modifier class to handle fit(run_tensorboard_locally=True) in a separate PR to try and keep these PRs manageable.
Testing done:

ran locally:
$ cat input.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow()
TensorFlow(script_mode=True)
TensorFlow(py_version="py3")
TensorFlow(
checkpoint_path="s3://foo/bar",
training_steps=100,
evaluation_steps=10,
requirements_file="source/requirements.txt",
)
TensorFlow(training_steps=100, evaluation_steps=10, script_mode=False)
TensorFlow(
framework_version="1.4",
training_steps=100,
evaluation_steps=10,
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo'}
)
random()
random.made_up_function()
$ sagemaker-upgrade-v2 --in-file input.py --out-file output.py
$ cat output.py
Overwriting file output.py
from random import random
from sagemaker.tensorflow import TensorFlow
TensorFlow(framework_version='1.11.0', script_mode=False)
TensorFlow(framework_version='1.11.0', script_mode=True)
TensorFlow(framework_version='1.11.0', py_version="py3")
TensorFlow(
framework_version='1.11.0',
hyperparameters={'checkpoint_path': "s3://foo/bar", 'training_steps': 100, 'evaluation_steps': 10, 'sagemaker_requirements': "source/requirements.txt"},
script_mode=False,
)
TensorFlow(framework_version='1.11.0', hyperparameters={'training_steps': 100, 'evaluation_steps': 10}, script_mode=False)
TensorFlow(
hyperparameters={'learning_rate': 0.1, 'epochs': 10, 'random_string': 'foo', 'training_steps': 100, 'evaluation_steps': 10},
script_mode=False,
framework_version="1.4")
random()
random.made_up_function()

also added some unit tests and ran those
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looks good to me
Comment threadsrc/sagemaker/cli/compatibility/v2/modifiers/tf_legacy_mode.py
Comment threadsrc/sagemaker/cli/compatibility/v2/ast_transformer.py
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@laurenyu
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merged commit a680be1
into
aws:zweiMay 29, 2020
@laurenyu
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migration-script-tf-legacy-parameters

branch
May 29, 2020 23:17
@laurenyulaurenyu
mentioned this pull request
May 30, 2020
 Merged

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Evan-W-ang added a commit
to Evan-W-ang/sagemaker-python-sdk
that referenced
this pull request
Jun 8, 2026
@Evan-W-ang
change: convert TF legacy mode parameters to hyperparameters in v2 mi…
479e62c
…gration script (aws#1534)
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