change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics#730

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Merged
icywang86rui merged 9 commits into from
Apr 2, 2019
Merged

change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics #730

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fc2fcc0
Make start time, end time and period configurable in analytics.Traini…
icywang86rui Mar 27, 2019
e838cb4
Add analytics integ test to the TensorFlow script mode minist test
icywang86rui Mar 29, 2019
6572452
Merge branch 'master' into fix-analytics
icywang86rui Apr 1, 2019
fa79676
Minor changes due to PR comments and to make flake8 happy
icywang86rui Apr 1, 2019
520c48b
Merge branch 'master' into fix-analytics
icywang86rui Apr 1, 2019
896381e
More minor changes
icywang86rui Apr 2, 2019
b88df7b
Merge branch 'master' into fix-analytics
icywang86rui Apr 2, 2019
c46a1e3
One more minor change
icywang86rui Apr 2, 2019
bf608a6
Merge branch 'master' into fix-analytics
laurenyu Apr 2, 2019
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17 changes: 13 additions & 4 deletions src/sagemaker/analytics.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,8 @@
# Any subsequent attempt to use pandas will raise the ImportError
pd = DeferredError(e)

METRICS_PERIOD_DEFAULT = 60 # seconds


class AnalyticsMetricsBase(with_metaclass(ABCMeta, object)):
"""Base class for tuning job or training job analytics classes.
Expand DownExpand Up@@ -201,7 +203,8 @@ class TrainingJobAnalytics(AnalyticsMetricsBase):

CLOUDWATCH_NAMESPACE = '/aws/sagemaker/TrainingJobs'

def __init__(self, training_job_name, metric_names=None, sagemaker_session=None):
def __init__(self, training_job_name, metric_names=None, sagemaker_session=None,
start_time=None, end_time=None, period=None):
"""Initialize a ``TrainingJobAnalytics`` instance.

Args:
Expand All@@ -216,6 +219,10 @@ def __init__(self, training_job_name, metric_names=None, sagemaker_session=None)
self._sage_client = sagemaker_session.sagemaker_client
self._cloudwatch = sagemaker_session.boto_session.client('cloudwatch')
self._training_job_name = training_job_name
self._start_time = start_time
self._end_time = end_time
self._period = period or METRICS_PERIOD_DEFAULT

if metric_names:
self._metric_names = metric_names
else:
Expand DownExpand Up@@ -245,13 +252,15 @@ def _determine_timeinterval(self):
covering the interval of the training job
"""
description = self._sage_client.describe_training_job(TrainingJobName=self.name)
start_time = description[u'TrainingStartTime'] # datetime object
start_time = self._start_time or description[u'TrainingStartTime'] # datetime object
# Incrementing end time by 1 min since CloudWatch drops seconds before finding the logs.
# This results in logs being searched in the time range in which the correct log line was not present.
# Example - Log time - 2018-10-22 08:25:55
# Here calculated end time would also be 2018-10-22 08:25:55 (without 1 min addition)
# CW will consider end time as 2018-10-22 08:25 and will not be able to search the correct log.
end_time = description.get(u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
end_time = self._end_time or description.get(
u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
Comment thread
laurenyu marked this conversation as resolved.

return {
'start_time': start_time,
'end_time': end_time,
Expand All@@ -276,7 +285,7 @@ def _fetch_metric(self, metric_name):
],
'StartTime': self._time_interval['start_time'],
'EndTime': self._time_interval['end_time'],
'Period': 60,
'Period': self._period,
'Statistics': ['Average'],
}
raw_cwm_data = self._cloudwatch.get_metric_statistics(**request)['Datapoints']
Expand Down
4 changes: 4 additions & 0 deletions tests/integ/test_tf_script_mode.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@ def test_mnist(sagemaker_session, instance_type):
sagemaker_session=sagemaker_session,
py_version='py3',
framework_version=TensorFlow.LATEST_VERSION,
metric_definitions=[{'Name': 'train:global_steps', 'Regex': r'global_step\/sec:\s(.*)'}],
base_job_name='test-tf-sm-mnist')
inputs = estimator.sagemaker_session.upload_data(
path=os.path.join(RESOURCE_PATH, 'data'),
Expand All@@ -56,6 +57,9 @@ def test_mnist(sagemaker_session, instance_type):
estimator.fit(inputs)
_assert_s3_files_exist(estimator.model_dir,
['graph.pbtxt', 'model.ckpt-0.index', 'model.ckpt-0.meta'])
df = estimator.training_job_analytics.dataframe()
print(df)
assert df.size > 0


def test_server_side_encryption(sagemaker_session):
Expand Down
17 changes: 17 additions & 0 deletions tests/unit/test_analytics.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -245,3 +245,20 @@ def test_trainer_dataframe():
trainer.export_csv(tmp_name)
assert os.path.isfile(tmp_name)
os.unlink(tmp_name)


def test_start_time_end_time_and_period_specified():
describe_training_result = {
'TrainingStartTime': datetime.datetime(2018, 5, 16, 1, 2, 3),
'TrainingEndTime': datetime.datetime(2018, 5, 16, 5, 6, 7),
}
session = create_sagemaker_session(describe_training_result)
start_time = datetime.datetime(2018, 5, 16, 1, 3, 4)
end_time = datetime.datetime(2018, 5, 16, 5, 1, 1)
period = 300
trainer = TrainingJobAnalytics('my-training-job', ['metric'],
sagemaker_session=session, start_time=start_time, end_time=end_time, period=period)

assert trainer._time_interval['start_time'] == start_time
assert trainer._time_interval['end_time'] == end_time
assert trainer._period == period
, '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" + '

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change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics#730

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 Merged

icywang86rui
merged 9 commits into

from

Apr 2, 2019
 Merged


change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics
#730
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fc2fcc0

Make start time, end time and period configurable in analytics.Traini…


icywang86rui Mar 27, 2019
e838cb4

Add analytics integ test to the TensorFlow script mode minist test


icywang86rui Mar 29, 2019
6572452

Merge branch 'master' into fix-analytics


icywang86rui Apr 1, 2019
fa79676

Minor changes due to PR comments and to make flake8 happy


icywang86rui Apr 1, 2019
520c48b

Merge branch 'master' into fix-analytics


icywang86rui Apr 1, 2019
896381e

More minor changes


icywang86rui Apr 2, 2019
b88df7b

Merge branch 'master' into fix-analytics


icywang86rui Apr 2, 2019
c46a1e3

One more minor change


icywang86rui Apr 2, 2019
bf608a6

Merge branch 'master' into fix-analytics


laurenyu Apr 2, 2019

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17 changes: 13 additions & 4 deletions
src/sagemaker/analytics.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,8 @@
 # Any subsequent attempt to use pandas will raise the ImportError
 pd = DeferredError(e)

METRICS_PERIOD_DEFAULT = 60 # seconds


class AnalyticsMetricsBase(with_metaclass(ABCMeta, object)):
 """Base class for tuning job or training job analytics classes.
Expand DownExpand Up@@ -201,7 +203,8 @@ class TrainingJobAnalytics(AnalyticsMetricsBase):

 CLOUDWATCH_NAMESPACE = '/aws/sagemaker/TrainingJobs'

 def __init__(self, training_job_name, metric_names=None, sagemaker_session=None):
 def __init__(self, training_job_name, metric_names=None, sagemaker_session=None,
 start_time=None, end_time=None, period=None):
 """Initialize a ``TrainingJobAnalytics`` instance.

 Args:
Expand All@@ -216,6 +219,10 @@ def __init__(self, training_job_name, metric_names=None, sagemaker_session=None)
 self._sage_client = sagemaker_session.sagemaker_client
 self._cloudwatch = sagemaker_session.boto_session.client('cloudwatch')
 self._training_job_name = training_job_name
 self._start_time = start_time
 self._end_time = end_time
 self._period = period or METRICS_PERIOD_DEFAULT

 if metric_names:
 self._metric_names = metric_names
 else:
Expand DownExpand Up@@ -245,13 +252,15 @@ def _determine_timeinterval(self):
 covering the interval of the training job
 """
 description = self._sage_client.describe_training_job(TrainingJobName=self.name)
 start_time = description[u'TrainingStartTime'] # datetime object
 start_time = self._start_time or description[u'TrainingStartTime'] # datetime object
 # Incrementing end time by 1 min since CloudWatch drops seconds before finding the logs.
 # This results in logs being searched in the time range in which the correct log line was not present.
 # Example - Log time - 2018-10-22 08:25:55
 # Here calculated end time would also be 2018-10-22 08:25:55 (without 1 min addition)
 # CW will consider end time as 2018-10-22 08:25 and will not be able to search the correct log.
 end_time = description.get(u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
 end_time = self._end_time or description.get(
 u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
Comment thread
laurenyu marked this conversation as resolved.


 return {
 'start_time': start_time,
 'end_time': end_time,
Expand All@@ -276,7 +285,7 @@ def _fetch_metric(self, metric_name):
 ],
 'StartTime': self._time_interval['start_time'],
 'EndTime': self._time_interval['end_time'],
 'Period': 60,
 'Period': self._period,
 'Statistics': ['Average'],
 }
 raw_cwm_data = self._cloudwatch.get_metric_statistics(**request)['Datapoints']
Expand Down

4 changes: 4 additions & 0 deletions
tests/integ/test_tf_script_mode.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@ def test_mnist(sagemaker_session, instance_type):
 sagemaker_session=sagemaker_session,
 py_version='py3',
 framework_version=TensorFlow.LATEST_VERSION,
 metric_definitions=[{'Name': 'train:global_steps', 'Regex': r'global_step\/sec:\s(.*)'}],
 base_job_name='test-tf-sm-mnist')
 inputs = estimator.sagemaker_session.upload_data(
 path=os.path.join(RESOURCE_PATH, 'data'),
Expand All@@ -56,6 +57,9 @@ def test_mnist(sagemaker_session, instance_type):
 estimator.fit(inputs)
 _assert_s3_files_exist(estimator.model_dir,
 ['graph.pbtxt', 'model.ckpt-0.index', 'model.ckpt-0.meta'])
 df = estimator.training_job_analytics.dataframe()
 print(df)
 assert df.size > 0


def test_server_side_encryption(sagemaker_session):
Expand Down

17 changes: 17 additions & 0 deletions
tests/unit/test_analytics.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -245,3 +245,20 @@ def test_trainer_dataframe():
 trainer.export_csv(tmp_name)
 assert os.path.isfile(tmp_name)
 os.unlink(tmp_name)


def test_start_time_end_time_and_period_specified():
 describe_training_result = {
 'TrainingStartTime': datetime.datetime(2018, 5, 16, 1, 2, 3),
 'TrainingEndTime': datetime.datetime(2018, 5, 16, 5, 6, 7),
 }
 session = create_sagemaker_session(describe_training_result)
 start_time = datetime.datetime(2018, 5, 16, 1, 3, 4)
 end_time = datetime.datetime(2018, 5, 16, 5, 1, 1)
 period = 300
 trainer = TrainingJobAnalytics('my-training-job', ['metric'],
 sagemaker_session=session, start_time=start_time, end_time=end_time, period=period)

 assert trainer._time_interval['start_time'] == start_time
 assert trainer._time_interval['end_time'] == end_time
 assert trainer._period == period

, '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('^' + ".*" + '

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change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics#730

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 Merged

icywang86rui
merged 9 commits into

from

Apr 2, 2019
 Merged


change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics
#730
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fc2fcc0

Make start time, end time and period configurable in analytics.Traini…


icywang86rui Mar 27, 2019
e838cb4

Add analytics integ test to the TensorFlow script mode minist test


icywang86rui Mar 29, 2019
6572452

Merge branch 'master' into fix-analytics


icywang86rui Apr 1, 2019
fa79676

Minor changes due to PR comments and to make flake8 happy


icywang86rui Apr 1, 2019
520c48b

Merge branch 'master' into fix-analytics


icywang86rui Apr 1, 2019
896381e

More minor changes


icywang86rui Apr 2, 2019
b88df7b

Merge branch 'master' into fix-analytics


icywang86rui Apr 2, 2019
c46a1e3

One more minor change


icywang86rui Apr 2, 2019
bf608a6

Merge branch 'master' into fix-analytics


laurenyu Apr 2, 2019

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17 changes: 13 additions & 4 deletions
src/sagemaker/analytics.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,8 @@
 # Any subsequent attempt to use pandas will raise the ImportError
 pd = DeferredError(e)

METRICS_PERIOD_DEFAULT = 60 # seconds


class AnalyticsMetricsBase(with_metaclass(ABCMeta, object)):
 """Base class for tuning job or training job analytics classes.
Expand DownExpand Up@@ -201,7 +203,8 @@ class TrainingJobAnalytics(AnalyticsMetricsBase):

 CLOUDWATCH_NAMESPACE = '/aws/sagemaker/TrainingJobs'

 def __init__(self, training_job_name, metric_names=None, sagemaker_session=None):
 def __init__(self, training_job_name, metric_names=None, sagemaker_session=None,
 start_time=None, end_time=None, period=None):
 """Initialize a ``TrainingJobAnalytics`` instance.

 Args:
Expand All@@ -216,6 +219,10 @@ def __init__(self, training_job_name, metric_names=None, sagemaker_session=None)
 self._sage_client = sagemaker_session.sagemaker_client
 self._cloudwatch = sagemaker_session.boto_session.client('cloudwatch')
 self._training_job_name = training_job_name
 self._start_time = start_time
 self._end_time = end_time
 self._period = period or METRICS_PERIOD_DEFAULT

 if metric_names:
 self._metric_names = metric_names
 else:
Expand DownExpand Up@@ -245,13 +252,15 @@ def _determine_timeinterval(self):
 covering the interval of the training job
 """
 description = self._sage_client.describe_training_job(TrainingJobName=self.name)
 start_time = description[u'TrainingStartTime'] # datetime object
 start_time = self._start_time or description[u'TrainingStartTime'] # datetime object
 # Incrementing end time by 1 min since CloudWatch drops seconds before finding the logs.
 # This results in logs being searched in the time range in which the correct log line was not present.
 # Example - Log time - 2018-10-22 08:25:55
 # Here calculated end time would also be 2018-10-22 08:25:55 (without 1 min addition)
 # CW will consider end time as 2018-10-22 08:25 and will not be able to search the correct log.
 end_time = description.get(u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
 end_time = self._end_time or description.get(
 u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
Comment thread
laurenyu marked this conversation as resolved.


 return {
 'start_time': start_time,
 'end_time': end_time,
Expand All@@ -276,7 +285,7 @@ def _fetch_metric(self, metric_name):
 ],
 'StartTime': self._time_interval['start_time'],
 'EndTime': self._time_interval['end_time'],
 'Period': 60,
 'Period': self._period,
 'Statistics': ['Average'],
 }
 raw_cwm_data = self._cloudwatch.get_metric_statistics(**request)['Datapoints']
Expand Down

4 changes: 4 additions & 0 deletions
tests/integ/test_tf_script_mode.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@ def test_mnist(sagemaker_session, instance_type):
 sagemaker_session=sagemaker_session,
 py_version='py3',
 framework_version=TensorFlow.LATEST_VERSION,
 metric_definitions=[{'Name': 'train:global_steps', 'Regex': r'global_step\/sec:\s(.*)'}],
 base_job_name='test-tf-sm-mnist')
 inputs = estimator.sagemaker_session.upload_data(
 path=os.path.join(RESOURCE_PATH, 'data'),
Expand All@@ -56,6 +57,9 @@ def test_mnist(sagemaker_session, instance_type):
 estimator.fit(inputs)
 _assert_s3_files_exist(estimator.model_dir,
 ['graph.pbtxt', 'model.ckpt-0.index', 'model.ckpt-0.meta'])
 df = estimator.training_job_analytics.dataframe()
 print(df)
 assert df.size > 0


def test_server_side_encryption(sagemaker_session):
Expand Down

17 changes: 17 additions & 0 deletions
tests/unit/test_analytics.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -245,3 +245,20 @@ def test_trainer_dataframe():
 trainer.export_csv(tmp_name)
 assert os.path.isfile(tmp_name)
 os.unlink(tmp_name)


def test_start_time_end_time_and_period_specified():
 describe_training_result = {
 'TrainingStartTime': datetime.datetime(2018, 5, 16, 1, 2, 3),
 'TrainingEndTime': datetime.datetime(2018, 5, 16, 5, 6, 7),
 }
 session = create_sagemaker_session(describe_training_result)
 start_time = datetime.datetime(2018, 5, 16, 1, 3, 4)
 end_time = datetime.datetime(2018, 5, 16, 5, 1, 1)
 period = 300
 trainer = TrainingJobAnalytics('my-training-job', ['metric'],
 sagemaker_session=session, start_time=start_time, end_time=end_time, period=period)

 assert trainer._time_interval['start_time'] == start_time
 assert trainer._time_interval['end_time'] == end_time
 assert trainer._period == period

, '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('^' + ".*" + '

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change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics#730

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 Merged

icywang86rui
merged 9 commits into

from

Apr 2, 2019
 Merged


change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics
#730
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Select commit
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fc2fcc0

Make start time, end time and period configurable in analytics.Traini…


icywang86rui Mar 27, 2019
e838cb4

Add analytics integ test to the TensorFlow script mode minist test


icywang86rui Mar 29, 2019
6572452

Merge branch 'master' into fix-analytics


icywang86rui Apr 1, 2019
fa79676

Minor changes due to PR comments and to make flake8 happy


icywang86rui Apr 1, 2019
520c48b

Merge branch 'master' into fix-analytics


icywang86rui Apr 1, 2019
896381e

More minor changes


icywang86rui Apr 2, 2019
b88df7b

Merge branch 'master' into fix-analytics


icywang86rui Apr 2, 2019
c46a1e3

One more minor change


icywang86rui Apr 2, 2019
bf608a6

Merge branch 'master' into fix-analytics


laurenyu Apr 2, 2019

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17 changes: 13 additions & 4 deletions
src/sagemaker/analytics.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,8 @@
 # Any subsequent attempt to use pandas will raise the ImportError
 pd = DeferredError(e)

METRICS_PERIOD_DEFAULT = 60 # seconds


class AnalyticsMetricsBase(with_metaclass(ABCMeta, object)):
 """Base class for tuning job or training job analytics classes.
Expand DownExpand Up@@ -201,7 +203,8 @@ class TrainingJobAnalytics(AnalyticsMetricsBase):

 CLOUDWATCH_NAMESPACE = '/aws/sagemaker/TrainingJobs'

 def __init__(self, training_job_name, metric_names=None, sagemaker_session=None):
 def __init__(self, training_job_name, metric_names=None, sagemaker_session=None,
 start_time=None, end_time=None, period=None):
 """Initialize a ``TrainingJobAnalytics`` instance.

 Args:
Expand All@@ -216,6 +219,10 @@ def __init__(self, training_job_name, metric_names=None, sagemaker_session=None)
 self._sage_client = sagemaker_session.sagemaker_client
 self._cloudwatch = sagemaker_session.boto_session.client('cloudwatch')
 self._training_job_name = training_job_name
 self._start_time = start_time
 self._end_time = end_time
 self._period = period or METRICS_PERIOD_DEFAULT

 if metric_names:
 self._metric_names = metric_names
 else:
Expand DownExpand Up@@ -245,13 +252,15 @@ def _determine_timeinterval(self):
 covering the interval of the training job
 """
 description = self._sage_client.describe_training_job(TrainingJobName=self.name)
 start_time = description[u'TrainingStartTime'] # datetime object
 start_time = self._start_time or description[u'TrainingStartTime'] # datetime object
 # Incrementing end time by 1 min since CloudWatch drops seconds before finding the logs.
 # This results in logs being searched in the time range in which the correct log line was not present.
 # Example - Log time - 2018-10-22 08:25:55
 # Here calculated end time would also be 2018-10-22 08:25:55 (without 1 min addition)
 # CW will consider end time as 2018-10-22 08:25 and will not be able to search the correct log.
 end_time = description.get(u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
 end_time = self._end_time or description.get(
 u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
Comment thread
laurenyu marked this conversation as resolved.


 return {
 'start_time': start_time,
 'end_time': end_time,
Expand All@@ -276,7 +285,7 @@ def _fetch_metric(self, metric_name):
 ],
 'StartTime': self._time_interval['start_time'],
 'EndTime': self._time_interval['end_time'],
 'Period': 60,
 'Period': self._period,
 'Statistics': ['Average'],
 }
 raw_cwm_data = self._cloudwatch.get_metric_statistics(**request)['Datapoints']
Expand Down

4 changes: 4 additions & 0 deletions
tests/integ/test_tf_script_mode.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@ def test_mnist(sagemaker_session, instance_type):
 sagemaker_session=sagemaker_session,
 py_version='py3',
 framework_version=TensorFlow.LATEST_VERSION,
 metric_definitions=[{'Name': 'train:global_steps', 'Regex': r'global_step\/sec:\s(.*)'}],
 base_job_name='test-tf-sm-mnist')
 inputs = estimator.sagemaker_session.upload_data(
 path=os.path.join(RESOURCE_PATH, 'data'),
Expand All@@ -56,6 +57,9 @@ def test_mnist(sagemaker_session, instance_type):
 estimator.fit(inputs)
 _assert_s3_files_exist(estimator.model_dir,
 ['graph.pbtxt', 'model.ckpt-0.index', 'model.ckpt-0.meta'])
 df = estimator.training_job_analytics.dataframe()
 print(df)
 assert df.size > 0


def test_server_side_encryption(sagemaker_session):
Expand Down

17 changes: 17 additions & 0 deletions
tests/unit/test_analytics.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -245,3 +245,20 @@ def test_trainer_dataframe():
 trainer.export_csv(tmp_name)
 assert os.path.isfile(tmp_name)
 os.unlink(tmp_name)


def test_start_time_end_time_and_period_specified():
 describe_training_result = {
 'TrainingStartTime': datetime.datetime(2018, 5, 16, 1, 2, 3),
 'TrainingEndTime': datetime.datetime(2018, 5, 16, 5, 6, 7),
 }
 session = create_sagemaker_session(describe_training_result)
 start_time = datetime.datetime(2018, 5, 16, 1, 3, 4)
 end_time = datetime.datetime(2018, 5, 16, 5, 1, 1)
 period = 300
 trainer = TrainingJobAnalytics('my-training-job', ['metric'],
 sagemaker_session=session, start_time=start_time, end_time=end_time, period=period)

 assert trainer._time_interval['start_time'] == start_time
 assert trainer._time_interval['end_time'] == end_time
 assert trainer._period == period

, '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" + '

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change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics#730

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 Merged

icywang86rui
merged 9 commits into

from

Apr 2, 2019
 Merged


change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics
#730
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fc2fcc0

Make start time, end time and period configurable in analytics.Traini…


icywang86rui Mar 27, 2019
e838cb4

Add analytics integ test to the TensorFlow script mode minist test


icywang86rui Mar 29, 2019
6572452

Merge branch 'master' into fix-analytics


icywang86rui Apr 1, 2019
fa79676

Minor changes due to PR comments and to make flake8 happy


icywang86rui Apr 1, 2019
520c48b

Merge branch 'master' into fix-analytics


icywang86rui Apr 1, 2019
896381e

More minor changes


icywang86rui Apr 2, 2019
b88df7b

Merge branch 'master' into fix-analytics


icywang86rui Apr 2, 2019
c46a1e3

One more minor change


icywang86rui Apr 2, 2019
bf608a6

Merge branch 'master' into fix-analytics


laurenyu Apr 2, 2019

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17 changes: 13 additions & 4 deletions
src/sagemaker/analytics.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,8 @@
 # Any subsequent attempt to use pandas will raise the ImportError
 pd = DeferredError(e)

METRICS_PERIOD_DEFAULT = 60 # seconds


class AnalyticsMetricsBase(with_metaclass(ABCMeta, object)):
 """Base class for tuning job or training job analytics classes.
Expand DownExpand Up@@ -201,7 +203,8 @@ class TrainingJobAnalytics(AnalyticsMetricsBase):

 CLOUDWATCH_NAMESPACE = '/aws/sagemaker/TrainingJobs'

 def __init__(self, training_job_name, metric_names=None, sagemaker_session=None):
 def __init__(self, training_job_name, metric_names=None, sagemaker_session=None,
 start_time=None, end_time=None, period=None):
 """Initialize a ``TrainingJobAnalytics`` instance.

 Args:
Expand All@@ -216,6 +219,10 @@ def __init__(self, training_job_name, metric_names=None, sagemaker_session=None)
 self._sage_client = sagemaker_session.sagemaker_client
 self._cloudwatch = sagemaker_session.boto_session.client('cloudwatch')
 self._training_job_name = training_job_name
 self._start_time = start_time
 self._end_time = end_time
 self._period = period or METRICS_PERIOD_DEFAULT

 if metric_names:
 self._metric_names = metric_names
 else:
Expand DownExpand Up@@ -245,13 +252,15 @@ def _determine_timeinterval(self):
 covering the interval of the training job
 """
 description = self._sage_client.describe_training_job(TrainingJobName=self.name)
 start_time = description[u'TrainingStartTime'] # datetime object
 start_time = self._start_time or description[u'TrainingStartTime'] # datetime object
 # Incrementing end time by 1 min since CloudWatch drops seconds before finding the logs.
 # This results in logs being searched in the time range in which the correct log line was not present.
 # Example - Log time - 2018-10-22 08:25:55
 # Here calculated end time would also be 2018-10-22 08:25:55 (without 1 min addition)
 # CW will consider end time as 2018-10-22 08:25 and will not be able to search the correct log.
 end_time = description.get(u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
 end_time = self._end_time or description.get(
 u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
Comment thread
laurenyu marked this conversation as resolved.


 return {
 'start_time': start_time,
 'end_time': end_time,
Expand All@@ -276,7 +285,7 @@ def _fetch_metric(self, metric_name):
 ],
 'StartTime': self._time_interval['start_time'],
 'EndTime': self._time_interval['end_time'],
 'Period': 60,
 'Period': self._period,
 'Statistics': ['Average'],
 }
 raw_cwm_data = self._cloudwatch.get_metric_statistics(**request)['Datapoints']
Expand Down

4 changes: 4 additions & 0 deletions
tests/integ/test_tf_script_mode.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@ def test_mnist(sagemaker_session, instance_type):
 sagemaker_session=sagemaker_session,
 py_version='py3',
 framework_version=TensorFlow.LATEST_VERSION,
 metric_definitions=[{'Name': 'train:global_steps', 'Regex': r'global_step\/sec:\s(.*)'}],
 base_job_name='test-tf-sm-mnist')
 inputs = estimator.sagemaker_session.upload_data(
 path=os.path.join(RESOURCE_PATH, 'data'),
Expand All@@ -56,6 +57,9 @@ def test_mnist(sagemaker_session, instance_type):
 estimator.fit(inputs)
 _assert_s3_files_exist(estimator.model_dir,
 ['graph.pbtxt', 'model.ckpt-0.index', 'model.ckpt-0.meta'])
 df = estimator.training_job_analytics.dataframe()
 print(df)
 assert df.size > 0


def test_server_side_encryption(sagemaker_session):
Expand Down

17 changes: 17 additions & 0 deletions
tests/unit/test_analytics.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -245,3 +245,20 @@ def test_trainer_dataframe():
 trainer.export_csv(tmp_name)
 assert os.path.isfile(tmp_name)
 os.unlink(tmp_name)


def test_start_time_end_time_and_period_specified():
 describe_training_result = {
 'TrainingStartTime': datetime.datetime(2018, 5, 16, 1, 2, 3),
 'TrainingEndTime': datetime.datetime(2018, 5, 16, 5, 6, 7),
 }
 session = create_sagemaker_session(describe_training_result)
 start_time = datetime.datetime(2018, 5, 16, 1, 3, 4)
 end_time = datetime.datetime(2018, 5, 16, 5, 1, 1)
 period = 300
 trainer = TrainingJobAnalytics('my-training-job', ['metric'],
 sagemaker_session=session, start_time=start_time, end_time=end_time, period=period)

 assert trainer._time_interval['start_time'] == start_time
 assert trainer._time_interval['end_time'] == end_time
 assert trainer._period == period

, '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('^' + ".*" + '

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change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics#730

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 Merged

icywang86rui
merged 9 commits into

from

Apr 2, 2019
 Merged


change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics
#730
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fc2fcc0

Make start time, end time and period configurable in analytics.Traini…


icywang86rui Mar 27, 2019
e838cb4

Add analytics integ test to the TensorFlow script mode minist test


icywang86rui Mar 29, 2019
6572452

Merge branch 'master' into fix-analytics


icywang86rui Apr 1, 2019
fa79676

Minor changes due to PR comments and to make flake8 happy


icywang86rui Apr 1, 2019
520c48b

Merge branch 'master' into fix-analytics


icywang86rui Apr 1, 2019
896381e

More minor changes


icywang86rui Apr 2, 2019
b88df7b

Merge branch 'master' into fix-analytics


icywang86rui Apr 2, 2019
c46a1e3

One more minor change


icywang86rui Apr 2, 2019
bf608a6

Merge branch 'master' into fix-analytics


laurenyu Apr 2, 2019

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17 changes: 13 additions & 4 deletions
src/sagemaker/analytics.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,8 @@
 # Any subsequent attempt to use pandas will raise the ImportError
 pd = DeferredError(e)

METRICS_PERIOD_DEFAULT = 60 # seconds


class AnalyticsMetricsBase(with_metaclass(ABCMeta, object)):
 """Base class for tuning job or training job analytics classes.
Expand DownExpand Up@@ -201,7 +203,8 @@ class TrainingJobAnalytics(AnalyticsMetricsBase):

 CLOUDWATCH_NAMESPACE = '/aws/sagemaker/TrainingJobs'

 def __init__(self, training_job_name, metric_names=None, sagemaker_session=None):
 def __init__(self, training_job_name, metric_names=None, sagemaker_session=None,
 start_time=None, end_time=None, period=None):
 """Initialize a ``TrainingJobAnalytics`` instance.

 Args:
Expand All@@ -216,6 +219,10 @@ def __init__(self, training_job_name, metric_names=None, sagemaker_session=None)
 self._sage_client = sagemaker_session.sagemaker_client
 self._cloudwatch = sagemaker_session.boto_session.client('cloudwatch')
 self._training_job_name = training_job_name
 self._start_time = start_time
 self._end_time = end_time
 self._period = period or METRICS_PERIOD_DEFAULT

 if metric_names:
 self._metric_names = metric_names
 else:
Expand DownExpand Up@@ -245,13 +252,15 @@ def _determine_timeinterval(self):
 covering the interval of the training job
 """
 description = self._sage_client.describe_training_job(TrainingJobName=self.name)
 start_time = description[u'TrainingStartTime'] # datetime object
 start_time = self._start_time or description[u'TrainingStartTime'] # datetime object
 # Incrementing end time by 1 min since CloudWatch drops seconds before finding the logs.
 # This results in logs being searched in the time range in which the correct log line was not present.
 # Example - Log time - 2018-10-22 08:25:55
 # Here calculated end time would also be 2018-10-22 08:25:55 (without 1 min addition)
 # CW will consider end time as 2018-10-22 08:25 and will not be able to search the correct log.
 end_time = description.get(u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
 end_time = self._end_time or description.get(
 u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
Comment thread
laurenyu marked this conversation as resolved.


 return {
 'start_time': start_time,
 'end_time': end_time,
Expand All@@ -276,7 +285,7 @@ def _fetch_metric(self, metric_name):
 ],
 'StartTime': self._time_interval['start_time'],
 'EndTime': self._time_interval['end_time'],
 'Period': 60,
 'Period': self._period,
 'Statistics': ['Average'],
 }
 raw_cwm_data = self._cloudwatch.get_metric_statistics(**request)['Datapoints']
Expand Down

4 changes: 4 additions & 0 deletions
tests/integ/test_tf_script_mode.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@ def test_mnist(sagemaker_session, instance_type):
 sagemaker_session=sagemaker_session,
 py_version='py3',
 framework_version=TensorFlow.LATEST_VERSION,
 metric_definitions=[{'Name': 'train:global_steps', 'Regex': r'global_step\/sec:\s(.*)'}],
 base_job_name='test-tf-sm-mnist')
 inputs = estimator.sagemaker_session.upload_data(
 path=os.path.join(RESOURCE_PATH, 'data'),
Expand All@@ -56,6 +57,9 @@ def test_mnist(sagemaker_session, instance_type):
 estimator.fit(inputs)
 _assert_s3_files_exist(estimator.model_dir,
 ['graph.pbtxt', 'model.ckpt-0.index', 'model.ckpt-0.meta'])
 df = estimator.training_job_analytics.dataframe()
 print(df)
 assert df.size > 0


def test_server_side_encryption(sagemaker_session):
Expand Down

17 changes: 17 additions & 0 deletions
tests/unit/test_analytics.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -245,3 +245,20 @@ def test_trainer_dataframe():
 trainer.export_csv(tmp_name)
 assert os.path.isfile(tmp_name)
 os.unlink(tmp_name)


def test_start_time_end_time_and_period_specified():
 describe_training_result = {
 'TrainingStartTime': datetime.datetime(2018, 5, 16, 1, 2, 3),
 'TrainingEndTime': datetime.datetime(2018, 5, 16, 5, 6, 7),
 }
 session = create_sagemaker_session(describe_training_result)
 start_time = datetime.datetime(2018, 5, 16, 1, 3, 4)
 end_time = datetime.datetime(2018, 5, 16, 5, 1, 1)
 period = 300
 trainer = TrainingJobAnalytics('my-training-job', ['metric'],
 sagemaker_session=session, start_time=start_time, end_time=end_time, period=period)

 assert trainer._time_interval['start_time'] == start_time
 assert trainer._time_interval['end_time'] == end_time
 assert trainer._period == period

, '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('^' + ".*" + '

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change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics#730

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 Merged

icywang86rui
merged 9 commits into

from

Apr 2, 2019
 Merged


change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics
#730
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fc2fcc0

Make start time, end time and period configurable in analytics.Traini…


icywang86rui Mar 27, 2019
e838cb4

Add analytics integ test to the TensorFlow script mode minist test


icywang86rui Mar 29, 2019
6572452

Merge branch 'master' into fix-analytics


icywang86rui Apr 1, 2019
fa79676

Minor changes due to PR comments and to make flake8 happy


icywang86rui Apr 1, 2019
520c48b

Merge branch 'master' into fix-analytics


icywang86rui Apr 1, 2019
896381e

More minor changes


icywang86rui Apr 2, 2019
b88df7b

Merge branch 'master' into fix-analytics


icywang86rui Apr 2, 2019
c46a1e3

One more minor change


icywang86rui Apr 2, 2019
bf608a6

Merge branch 'master' into fix-analytics


laurenyu Apr 2, 2019

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17 changes: 13 additions & 4 deletions
src/sagemaker/analytics.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,8 @@
 # Any subsequent attempt to use pandas will raise the ImportError
 pd = DeferredError(e)

METRICS_PERIOD_DEFAULT = 60 # seconds


class AnalyticsMetricsBase(with_metaclass(ABCMeta, object)):
 """Base class for tuning job or training job analytics classes.
Expand DownExpand Up@@ -201,7 +203,8 @@ class TrainingJobAnalytics(AnalyticsMetricsBase):

 CLOUDWATCH_NAMESPACE = '/aws/sagemaker/TrainingJobs'

 def __init__(self, training_job_name, metric_names=None, sagemaker_session=None):
 def __init__(self, training_job_name, metric_names=None, sagemaker_session=None,
 start_time=None, end_time=None, period=None):
 """Initialize a ``TrainingJobAnalytics`` instance.

 Args:
Expand All@@ -216,6 +219,10 @@ def __init__(self, training_job_name, metric_names=None, sagemaker_session=None)
 self._sage_client = sagemaker_session.sagemaker_client
 self._cloudwatch = sagemaker_session.boto_session.client('cloudwatch')
 self._training_job_name = training_job_name
 self._start_time = start_time
 self._end_time = end_time
 self._period = period or METRICS_PERIOD_DEFAULT

 if metric_names:
 self._metric_names = metric_names
 else:
Expand DownExpand Up@@ -245,13 +252,15 @@ def _determine_timeinterval(self):
 covering the interval of the training job
 """
 description = self._sage_client.describe_training_job(TrainingJobName=self.name)
 start_time = description[u'TrainingStartTime'] # datetime object
 start_time = self._start_time or description[u'TrainingStartTime'] # datetime object
 # Incrementing end time by 1 min since CloudWatch drops seconds before finding the logs.
 # This results in logs being searched in the time range in which the correct log line was not present.
 # Example - Log time - 2018-10-22 08:25:55
 # Here calculated end time would also be 2018-10-22 08:25:55 (without 1 min addition)
 # CW will consider end time as 2018-10-22 08:25 and will not be able to search the correct log.
 end_time = description.get(u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
 end_time = self._end_time or description.get(
 u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
Comment thread
laurenyu marked this conversation as resolved.


 return {
 'start_time': start_time,
 'end_time': end_time,
Expand All@@ -276,7 +285,7 @@ def _fetch_metric(self, metric_name):
 ],
 'StartTime': self._time_interval['start_time'],
 'EndTime': self._time_interval['end_time'],
 'Period': 60,
 'Period': self._period,
 'Statistics': ['Average'],
 }
 raw_cwm_data = self._cloudwatch.get_metric_statistics(**request)['Datapoints']
Expand Down

4 changes: 4 additions & 0 deletions
tests/integ/test_tf_script_mode.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@ def test_mnist(sagemaker_session, instance_type):
 sagemaker_session=sagemaker_session,
 py_version='py3',
 framework_version=TensorFlow.LATEST_VERSION,
 metric_definitions=[{'Name': 'train:global_steps', 'Regex': r'global_step\/sec:\s(.*)'}],
 base_job_name='test-tf-sm-mnist')
 inputs = estimator.sagemaker_session.upload_data(
 path=os.path.join(RESOURCE_PATH, 'data'),
Expand All@@ -56,6 +57,9 @@ def test_mnist(sagemaker_session, instance_type):
 estimator.fit(inputs)
 _assert_s3_files_exist(estimator.model_dir,
 ['graph.pbtxt', 'model.ckpt-0.index', 'model.ckpt-0.meta'])
 df = estimator.training_job_analytics.dataframe()
 print(df)
 assert df.size > 0


def test_server_side_encryption(sagemaker_session):
Expand Down

17 changes: 17 additions & 0 deletions
tests/unit/test_analytics.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -245,3 +245,20 @@ def test_trainer_dataframe():
 trainer.export_csv(tmp_name)
 assert os.path.isfile(tmp_name)
 os.unlink(tmp_name)


def test_start_time_end_time_and_period_specified():
 describe_training_result = {
 'TrainingStartTime': datetime.datetime(2018, 5, 16, 1, 2, 3),
 'TrainingEndTime': datetime.datetime(2018, 5, 16, 5, 6, 7),
 }
 session = create_sagemaker_session(describe_training_result)
 start_time = datetime.datetime(2018, 5, 16, 1, 3, 4)
 end_time = datetime.datetime(2018, 5, 16, 5, 1, 1)
 period = 300
 trainer = TrainingJobAnalytics('my-training-job', ['metric'],
 sagemaker_session=session, start_time=start_time, end_time=end_time, period=period)

 assert trainer._time_interval['start_time'] == start_time
 assert trainer._time_interval['end_time'] == end_time
 assert trainer._period == period

, '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: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics#730

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 Merged

icywang86rui
merged 9 commits into

from

Apr 2, 2019
 Merged


change: make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics
#730
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fc2fcc0

Make start time, end time and period configurable in analytics.Traini…


icywang86rui Mar 27, 2019
e838cb4

Add analytics integ test to the TensorFlow script mode minist test


icywang86rui Mar 29, 2019
6572452

Merge branch 'master' into fix-analytics


icywang86rui Apr 1, 2019
fa79676

Minor changes due to PR comments and to make flake8 happy


icywang86rui Apr 1, 2019
520c48b

Merge branch 'master' into fix-analytics


icywang86rui Apr 1, 2019
896381e

More minor changes


icywang86rui Apr 2, 2019
b88df7b

Merge branch 'master' into fix-analytics


icywang86rui Apr 2, 2019
c46a1e3

One more minor change


icywang86rui Apr 2, 2019
bf608a6

Merge branch 'master' into fix-analytics


laurenyu Apr 2, 2019

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17 changes: 13 additions & 4 deletions
src/sagemaker/analytics.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,8 @@
 # Any subsequent attempt to use pandas will raise the ImportError
 pd = DeferredError(e)

METRICS_PERIOD_DEFAULT = 60 # seconds


class AnalyticsMetricsBase(with_metaclass(ABCMeta, object)):
 """Base class for tuning job or training job analytics classes.
Expand DownExpand Up@@ -201,7 +203,8 @@ class TrainingJobAnalytics(AnalyticsMetricsBase):

 CLOUDWATCH_NAMESPACE = '/aws/sagemaker/TrainingJobs'

 def __init__(self, training_job_name, metric_names=None, sagemaker_session=None):
 def __init__(self, training_job_name, metric_names=None, sagemaker_session=None,
 start_time=None, end_time=None, period=None):
 """Initialize a ``TrainingJobAnalytics`` instance.

 Args:
Expand All@@ -216,6 +219,10 @@ def __init__(self, training_job_name, metric_names=None, sagemaker_session=None)
 self._sage_client = sagemaker_session.sagemaker_client
 self._cloudwatch = sagemaker_session.boto_session.client('cloudwatch')
 self._training_job_name = training_job_name
 self._start_time = start_time
 self._end_time = end_time
 self._period = period or METRICS_PERIOD_DEFAULT

 if metric_names:
 self._metric_names = metric_names
 else:
Expand DownExpand Up@@ -245,13 +252,15 @@ def _determine_timeinterval(self):
 covering the interval of the training job
 """
 description = self._sage_client.describe_training_job(TrainingJobName=self.name)
 start_time = description[u'TrainingStartTime'] # datetime object
 start_time = self._start_time or description[u'TrainingStartTime'] # datetime object
 # Incrementing end time by 1 min since CloudWatch drops seconds before finding the logs.
 # This results in logs being searched in the time range in which the correct log line was not present.
 # Example - Log time - 2018-10-22 08:25:55
 # Here calculated end time would also be 2018-10-22 08:25:55 (without 1 min addition)
 # CW will consider end time as 2018-10-22 08:25 and will not be able to search the correct log.
 end_time = description.get(u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
 end_time = self._end_time or description.get(
 u'TrainingEndTime', datetime.datetime.utcnow()) + datetime.timedelta(minutes=1)
Comment thread
laurenyu marked this conversation as resolved.


 return {
 'start_time': start_time,
 'end_time': end_time,
Expand All@@ -276,7 +285,7 @@ def _fetch_metric(self, metric_name):
 ],
 'StartTime': self._time_interval['start_time'],
 'EndTime': self._time_interval['end_time'],
 'Period': 60,
 'Period': self._period,
 'Statistics': ['Average'],
 }
 raw_cwm_data = self._cloudwatch.get_metric_statistics(**request)['Datapoints']
Expand Down

4 changes: 4 additions & 0 deletions
tests/integ/test_tf_script_mode.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@ def test_mnist(sagemaker_session, instance_type):
 sagemaker_session=sagemaker_session,
 py_version='py3',
 framework_version=TensorFlow.LATEST_VERSION,
 metric_definitions=[{'Name': 'train:global_steps', 'Regex': r'global_step\/sec:\s(.*)'}],
 base_job_name='test-tf-sm-mnist')
 inputs = estimator.sagemaker_session.upload_data(
 path=os.path.join(RESOURCE_PATH, 'data'),
Expand All@@ -56,6 +57,9 @@ def test_mnist(sagemaker_session, instance_type):
 estimator.fit(inputs)
 _assert_s3_files_exist(estimator.model_dir,
 ['graph.pbtxt', 'model.ckpt-0.index', 'model.ckpt-0.meta'])
 df = estimator.training_job_analytics.dataframe()
 print(df)
 assert df.size > 0


def test_server_side_encryption(sagemaker_session):
Expand Down

17 changes: 17 additions & 0 deletions
tests/unit/test_analytics.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -245,3 +245,20 @@ def test_trainer_dataframe():
 trainer.export_csv(tmp_name)
 assert os.path.isfile(tmp_name)
 os.unlink(tmp_name)


def test_start_time_end_time_and_period_specified():
 describe_training_result = {
 'TrainingStartTime': datetime.datetime(2018, 5, 16, 1, 2, 3),
 'TrainingEndTime': datetime.datetime(2018, 5, 16, 5, 6, 7),
 }
 session = create_sagemaker_session(describe_training_result)
 start_time = datetime.datetime(2018, 5, 16, 1, 3, 4)
 end_time = datetime.datetime(2018, 5, 16, 5, 1, 1)
 period = 300
 trainer = TrainingJobAnalytics('my-training-job', ['metric'],
 sagemaker_session=session, start_time=start_time, end_time=end_time, period=period)

 assert trainer._time_interval['start_time'] == start_time
 assert trainer._time_interval['end_time'] == end_time
 assert trainer._period == period