fix: use unique names for test training jobs#765

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chuyang-deng merged 2 commits into from
Apr 25, 2019
Merged

fix: use unique names for test training jobs #765

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e184cb9
fix: use unique names for test training jobs
Apr 24, 2019
05a1596
Merge branch 'master' into unique_job_name
chuyang-deng Apr 24, 2019
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11 changes: 7 additions & 4 deletions tests/integ/test_rl.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -18,7 +18,7 @@
import pytest

from sagemaker.rl import RLEstimator, RLFramework, RLToolkit
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand All@@ -29,9 +29,10 @@
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
estimator = _test_coach(sagemaker_session, RLFramework.MXNET, rl_coach_mxnet_full_version)
job_name = unique_name_from_base('test-coach-mxnet')

with timeout(minutes=15):
estimator.fit(wait='False')
estimator.fit(wait='False', job_name=job_name)

estimator = RLEstimator.attach(estimator.latest_training_job.name,
sagemaker_session=sagemaker_session)
Expand All@@ -52,9 +53,10 @@ def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_tf(sagemaker_session, rl_coach_tf_full_version):
estimator = _test_coach(sagemaker_session, RLFramework.TENSORFLOW, rl_coach_tf_full_version)
job_name = unique_name_from_base('test-coach-tf')

with timeout(minutes=15):
estimator.fit()
estimator.fit(job_name=job_name)

endpoint_name = 'test-tf-coach-deploy-{}'.format(sagemaker_timestamp())

Expand DownExpand Up@@ -104,9 +106,10 @@ def test_ray_tf(sagemaker_session, rl_ray_full_version):
role='SageMakerRole',
train_instance_type=CPU_INSTANCE,
train_instance_count=1)
job_name = unique_name_from_base('test-ray-tf')

with timeout(minutes=15):
estimator.fit()
estimator.fit(job_name=job_name)

with pytest.raises(NotImplementedError) as e:
estimator.deploy(1, CPU_INSTANCE)
Expand Down
11 changes: 7 additions & 4 deletions tests/integ/test_sklearn_train.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -21,7 +21,7 @@
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.sklearn import SKLearn
from sagemaker.sklearn import SKLearnModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION, TRAINING_DEFAULT_TIMEOUT_MINUTES
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand DownExpand Up@@ -49,8 +49,9 @@ def test_training_with_additional_hyperparameters(sagemaker_session, sklearn_ful
key_prefix='integ-test-data/sklearn_mnist/train')
test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
key_prefix='integ-test-data/sklearn_mnist/test')
job_name = unique_name_from_base('test-sklearn-hp')

sklearn.fit({'train': train_input, 'test': test_input})
sklearn.fit({'train': train_input, 'test': test_input}, job_name=job_name)
return sklearn.latest_training_job.name


Expand DownExpand Up@@ -109,9 +110,10 @@ def test_failed_training_job(sagemaker_session, sklearn_full_version):

train_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'train'),
key_prefix='integ-test-data/sklearn_mnist/train')
job_name = unique_name_from_base('test-sklearn-failed')

with pytest.raises(ValueError):
sklearn.fit(train_input)
sklearn.fit(train_input, job_name=job_name)


def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_version, wait=True):
Expand All@@ -130,8 +132,9 @@ def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_versi
key_prefix='integ-test-data/sklearn_mnist/train')
test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
key_prefix='integ-test-data/sklearn_mnist/test')
job_name = unique_name_from_base('test-sklearn-mnist')

sklearn.fit({'train': train_input, 'test': test_input}, wait=wait)
sklearn.fit({'train': train_input, 'test': test_input}, wait=wait, job_name=job_name)
return sklearn.latest_training_job.name


Expand Down
14 changes: 9 additions & 5 deletions tests/integ/test_tf.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -19,7 +19,7 @@

import tests.integ
from sagemaker.tensorflow import TensorFlow, TensorFlowModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, PYTHON_VERSION
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout
from tests.integ.vpc_test_utils import get_or_create_vpc_resources, setup_security_group_for_encryption
Expand All@@ -46,7 +46,8 @@ def tf_training_job(sagemaker_session, tf_full_version):
base_job_name='test-tf')

inputs = sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
estimator.fit(inputs)
job_name = unique_name_from_base('test-tf-train')
estimator.fit(inputs, job_name=job_name)
print('job succeeded: {}'.format(estimator.latest_training_job.name))

return estimator.latest_training_job.name
Expand DownExpand Up@@ -123,7 +124,8 @@ def test_tf_async(sagemaker_session):
base_job_name='test-tf')

inputs = estimator.sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
estimator.fit(inputs, wait=False)
job_name = unique_name_from_base('test-tf-async')
estimator.fit(inputs, wait=False, job_name=job_name)
training_job_name = estimator.latest_training_job.name
time.sleep(20)

Expand DownExpand Up@@ -166,9 +168,10 @@ def test_tf_vpc_multi(sagemaker_session, tf_full_version):
subnets=subnet_ids,
security_group_ids=[security_group_id],
encrypt_inter_container_traffic=True)
job_name = unique_name_from_base('test-tf-vpc-multi')

with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
estimator.fit(train_input)
estimator.fit(train_input, job_name=job_name)
print('training job succeeded: {}'.format(estimator.latest_training_job.name))

job_desc = sagemaker_session.sagemaker_client.describe_training_job(
Expand DownExpand Up@@ -209,7 +212,8 @@ def test_failed_tf_training(sagemaker_session, tf_full_version):
train_instance_count=1,
train_instance_type='ml.c4.xlarge',
sagemaker_session=sagemaker_session)
job_name = unique_name_from_base('test-tf-fail')

with pytest.raises(ValueError) as e:
estimator.fit()
estimator.fit(job_name=job_name)
assert 'This failure is expected' in str(e.value)
5 changes: 4 additions & 1 deletion tests/integ/test_tf_cifar.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base

PICKLE_CONTENT_TYPE = 'application/python-pickle'

Expand DownExpand Up@@ -55,7 +56,9 @@ def test_cifar(sagemaker_session, tf_full_version):

inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
key_prefix='data/cifar10')
estimator.fit(inputs, logs=False)
job_name = unique_name_from_base('test-tf-cifar')

estimator.fit(inputs, logs=False, job_name=job_name)
print('job succeeded: {}'.format(estimator.latest_training_job.name))

endpoint_name = estimator.latest_training_job.name
Expand Down
4 changes: 3 additions & 1 deletion tests/integ/test_tf_keras.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -21,6 +21,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base


@pytest.mark.canary_quick
Expand All@@ -43,8 +44,9 @@ def test_keras(sagemaker_session, tf_full_version):

inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
key_prefix='data/cifar10')
job_name = unique_name_from_base('test-tf-keras')

estimator.fit(inputs)
estimator.fit(inputs, job_name=job_name)

endpoint_name = estimator.latest_training_job.name
with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
Expand Down
12 changes: 9 additions & 3 deletions tests/integ/test_transformer.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from sagemaker import KMeans
from sagemaker.mxnet import MXNet
from sagemaker.transformer import Transformer
from sagemaker.utils import unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, TRANSFORM_DEFAULT_TIMEOUT_MINUTES
from tests.integ.kms_utils import get_or_create_kms_key
from tests.integ.timeout import timeout, timeout_and_delete_model_with_transformer
Expand All@@ -41,9 +42,10 @@ def test_transform_mxnet(sagemaker_session, mxnet_full_version):
key_prefix='integ-test-data/mxnet_mnist/train')
test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
key_prefix='integ-test-data/mxnet_mnist/test')
job_name = unique_name_from_base('test-mxnet-transform')

with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
mx.fit({'train': train_input, 'test': test_input})
mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

transform_input_path = os.path.join(data_path, 'transform', 'data.csv')
transform_input_key_prefix = 'integ-test-data/mxnet_mnist/transform'
Expand DownExpand Up@@ -86,8 +88,11 @@ def test_attach_transform_kmeans(sagemaker_session):
kmeans.epochs = 1

records = kmeans.record_set(train_set[0][:100])

job_name = unique_name_from_base('test-kmeans-attach')

with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
kmeans.fit(records)
kmeans.fit(records, job_name=job_name)

transform_input_path = os.path.join(data_path, 'transform_input.csv')
transform_input_key_prefix = 'integ-test-data/one_p_mnist/transform'
Expand DownExpand Up@@ -120,9 +125,10 @@ def test_transform_mxnet_vpc(sagemaker_session, mxnet_full_version):
key_prefix='integ-test-data/mxnet_mnist/train')
test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
key_prefix='integ-test-data/mxnet_mnist/test')
job_name = unique_name_from_base('test-mxnet-vpc')

with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
mx.fit({'train': train_input, 'test': test_input})
mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

job_desc = sagemaker_session.sagemaker_client.describe_training_job(TrainingJobName=mx.latest_training_job.name)
assert set(subnet_ids) == set(job_desc['VpcConfig']['Subnets'])
Expand Down
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 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
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try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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fix: use unique names for test training jobs#765

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to your account

 Merged

chuyang-deng
merged 2 commits into

from

Apr 25, 2019
 Merged


fix: use unique names for test training jobs
#765
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e184cb9

fix: use unique names for test training jobs

Apr 24, 2019
05a1596

Merge branch 'master' into unique_job_name


chuyang-deng Apr 24, 2019

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11 changes: 7 additions & 4 deletions
tests/integ/test_rl.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -18,7 +18,7 @@
import pytest

from sagemaker.rl import RLEstimator, RLFramework, RLToolkit
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand All@@ -29,9 +29,10 @@
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
 estimator = _test_coach(sagemaker_session, RLFramework.MXNET, rl_coach_mxnet_full_version)
 job_name = unique_name_from_base('test-coach-mxnet')

 with timeout(minutes=15):
 estimator.fit(wait='False')
 estimator.fit(wait='False', job_name=job_name)

 estimator = RLEstimator.attach(estimator.latest_training_job.name,
 sagemaker_session=sagemaker_session)
Expand All@@ -52,9 +53,10 @@ def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_tf(sagemaker_session, rl_coach_tf_full_version):
 estimator = _test_coach(sagemaker_session, RLFramework.TENSORFLOW, rl_coach_tf_full_version)
 job_name = unique_name_from_base('test-coach-tf')

 with timeout(minutes=15):
 estimator.fit()
 estimator.fit(job_name=job_name)

 endpoint_name = 'test-tf-coach-deploy-{}'.format(sagemaker_timestamp())

Expand DownExpand Up@@ -104,9 +106,10 @@ def test_ray_tf(sagemaker_session, rl_ray_full_version):
 role='SageMakerRole',
 train_instance_type=CPU_INSTANCE,
 train_instance_count=1)
 job_name = unique_name_from_base('test-ray-tf')

 with timeout(minutes=15):
 estimator.fit()
 estimator.fit(job_name=job_name)

 with pytest.raises(NotImplementedError) as e:
 estimator.deploy(1, CPU_INSTANCE)
Expand Down

11 changes: 7 additions & 4 deletions
tests/integ/test_sklearn_train.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -21,7 +21,7 @@
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.sklearn import SKLearn
from sagemaker.sklearn import SKLearnModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION, TRAINING_DEFAULT_TIMEOUT_MINUTES
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand DownExpand Up@@ -49,8 +49,9 @@ def test_training_with_additional_hyperparameters(sagemaker_session, sklearn_ful
 key_prefix='integ-test-data/sklearn_mnist/train')
 test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/sklearn_mnist/test')
 job_name = unique_name_from_base('test-sklearn-hp')

 sklearn.fit({'train': train_input, 'test': test_input})
 sklearn.fit({'train': train_input, 'test': test_input}, job_name=job_name)
 return sklearn.latest_training_job.name


Expand DownExpand Up@@ -109,9 +110,10 @@ def test_failed_training_job(sagemaker_session, sklearn_full_version):

 train_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'train'),
 key_prefix='integ-test-data/sklearn_mnist/train')
 job_name = unique_name_from_base('test-sklearn-failed')

 with pytest.raises(ValueError):
 sklearn.fit(train_input)
 sklearn.fit(train_input, job_name=job_name)


def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_version, wait=True):
Expand All@@ -130,8 +132,9 @@ def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_versi
 key_prefix='integ-test-data/sklearn_mnist/train')
 test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/sklearn_mnist/test')
 job_name = unique_name_from_base('test-sklearn-mnist')

 sklearn.fit({'train': train_input, 'test': test_input}, wait=wait)
 sklearn.fit({'train': train_input, 'test': test_input}, wait=wait, job_name=job_name)
 return sklearn.latest_training_job.name


Expand Down

14 changes: 9 additions & 5 deletions
tests/integ/test_tf.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -19,7 +19,7 @@

import tests.integ
from sagemaker.tensorflow import TensorFlow, TensorFlowModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, PYTHON_VERSION
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout
from tests.integ.vpc_test_utils import get_or_create_vpc_resources, setup_security_group_for_encryption
Expand All@@ -46,7 +46,8 @@ def tf_training_job(sagemaker_session, tf_full_version):
 base_job_name='test-tf')

 inputs = sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
 estimator.fit(inputs)
 job_name = unique_name_from_base('test-tf-train')
 estimator.fit(inputs, job_name=job_name)
 print('job succeeded: {}'.format(estimator.latest_training_job.name))

 return estimator.latest_training_job.name
Expand DownExpand Up@@ -123,7 +124,8 @@ def test_tf_async(sagemaker_session):
 base_job_name='test-tf')

 inputs = estimator.sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
 estimator.fit(inputs, wait=False)
 job_name = unique_name_from_base('test-tf-async')
 estimator.fit(inputs, wait=False, job_name=job_name)
 training_job_name = estimator.latest_training_job.name
 time.sleep(20)

Expand DownExpand Up@@ -166,9 +168,10 @@ def test_tf_vpc_multi(sagemaker_session, tf_full_version):
 subnets=subnet_ids,
 security_group_ids=[security_group_id],
 encrypt_inter_container_traffic=True)
 job_name = unique_name_from_base('test-tf-vpc-multi')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 estimator.fit(train_input)
 estimator.fit(train_input, job_name=job_name)
 print('training job succeeded: {}'.format(estimator.latest_training_job.name))

 job_desc = sagemaker_session.sagemaker_client.describe_training_job(
Expand DownExpand Up@@ -209,7 +212,8 @@ def test_failed_tf_training(sagemaker_session, tf_full_version):
 train_instance_count=1,
 train_instance_type='ml.c4.xlarge',
 sagemaker_session=sagemaker_session)
 job_name = unique_name_from_base('test-tf-fail')

 with pytest.raises(ValueError) as e:
 estimator.fit()
 estimator.fit(job_name=job_name)
 assert 'This failure is expected' in str(e.value)

5 changes: 4 additions & 1 deletion
tests/integ/test_tf_cifar.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base

PICKLE_CONTENT_TYPE = 'application/python-pickle'

Expand DownExpand Up@@ -55,7 +56,9 @@ def test_cifar(sagemaker_session, tf_full_version):

 inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
 key_prefix='data/cifar10')
 estimator.fit(inputs, logs=False)
 job_name = unique_name_from_base('test-tf-cifar')

 estimator.fit(inputs, logs=False, job_name=job_name)
 print('job succeeded: {}'.format(estimator.latest_training_job.name))

 endpoint_name = estimator.latest_training_job.name
Expand Down

4 changes: 3 additions & 1 deletion
tests/integ/test_tf_keras.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -21,6 +21,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base


@pytest.mark.canary_quick
Expand All@@ -43,8 +44,9 @@ def test_keras(sagemaker_session, tf_full_version):

 inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
 key_prefix='data/cifar10')
 job_name = unique_name_from_base('test-tf-keras')

 estimator.fit(inputs)
 estimator.fit(inputs, job_name=job_name)

 endpoint_name = estimator.latest_training_job.name
 with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
Expand Down

12 changes: 9 additions & 3 deletions
tests/integ/test_transformer.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from sagemaker import KMeans
from sagemaker.mxnet import MXNet
from sagemaker.transformer import Transformer
from sagemaker.utils import unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, TRANSFORM_DEFAULT_TIMEOUT_MINUTES
from tests.integ.kms_utils import get_or_create_kms_key
from tests.integ.timeout import timeout, timeout_and_delete_model_with_transformer
Expand All@@ -41,9 +42,10 @@ def test_transform_mxnet(sagemaker_session, mxnet_full_version):
 key_prefix='integ-test-data/mxnet_mnist/train')
 test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/mxnet_mnist/test')
 job_name = unique_name_from_base('test-mxnet-transform')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 mx.fit({'train': train_input, 'test': test_input})
 mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

 transform_input_path = os.path.join(data_path, 'transform', 'data.csv')
 transform_input_key_prefix = 'integ-test-data/mxnet_mnist/transform'
Expand DownExpand Up@@ -86,8 +88,11 @@ def test_attach_transform_kmeans(sagemaker_session):
 kmeans.epochs = 1

 records = kmeans.record_set(train_set[0][:100])

 job_name = unique_name_from_base('test-kmeans-attach')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 kmeans.fit(records)
 kmeans.fit(records, job_name=job_name)

 transform_input_path = os.path.join(data_path, 'transform_input.csv')
 transform_input_key_prefix = 'integ-test-data/one_p_mnist/transform'
Expand DownExpand Up@@ -120,9 +125,10 @@ def test_transform_mxnet_vpc(sagemaker_session, mxnet_full_version):
 key_prefix='integ-test-data/mxnet_mnist/train')
 test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/mxnet_mnist/test')
 job_name = unique_name_from_base('test-mxnet-vpc')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 mx.fit({'train': train_input, 'test': test_input})
 mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

 job_desc = sagemaker_session.sagemaker_client.describe_training_job(TrainingJobName=mx.latest_training_job.name)
 assert set(subnet_ids) == set(job_desc['VpcConfig']['Subnets'])
Expand Down

, '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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fix: use unique names for test training jobs#765

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chuyang-deng
merged 2 commits into

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Apr 25, 2019
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fix: use unique names for test training jobs
#765
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e184cb9

fix: use unique names for test training jobs

Apr 24, 2019
05a1596

Merge branch 'master' into unique_job_name


chuyang-deng Apr 24, 2019

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11 changes: 7 additions & 4 deletions
tests/integ/test_rl.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -18,7 +18,7 @@
import pytest

from sagemaker.rl import RLEstimator, RLFramework, RLToolkit
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand All@@ -29,9 +29,10 @@
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
 estimator = _test_coach(sagemaker_session, RLFramework.MXNET, rl_coach_mxnet_full_version)
 job_name = unique_name_from_base('test-coach-mxnet')

 with timeout(minutes=15):
 estimator.fit(wait='False')
 estimator.fit(wait='False', job_name=job_name)

 estimator = RLEstimator.attach(estimator.latest_training_job.name,
 sagemaker_session=sagemaker_session)
Expand All@@ -52,9 +53,10 @@ def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_tf(sagemaker_session, rl_coach_tf_full_version):
 estimator = _test_coach(sagemaker_session, RLFramework.TENSORFLOW, rl_coach_tf_full_version)
 job_name = unique_name_from_base('test-coach-tf')

 with timeout(minutes=15):
 estimator.fit()
 estimator.fit(job_name=job_name)

 endpoint_name = 'test-tf-coach-deploy-{}'.format(sagemaker_timestamp())

Expand DownExpand Up@@ -104,9 +106,10 @@ def test_ray_tf(sagemaker_session, rl_ray_full_version):
 role='SageMakerRole',
 train_instance_type=CPU_INSTANCE,
 train_instance_count=1)
 job_name = unique_name_from_base('test-ray-tf')

 with timeout(minutes=15):
 estimator.fit()
 estimator.fit(job_name=job_name)

 with pytest.raises(NotImplementedError) as e:
 estimator.deploy(1, CPU_INSTANCE)
Expand Down

11 changes: 7 additions & 4 deletions
tests/integ/test_sklearn_train.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -21,7 +21,7 @@
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.sklearn import SKLearn
from sagemaker.sklearn import SKLearnModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION, TRAINING_DEFAULT_TIMEOUT_MINUTES
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand DownExpand Up@@ -49,8 +49,9 @@ def test_training_with_additional_hyperparameters(sagemaker_session, sklearn_ful
 key_prefix='integ-test-data/sklearn_mnist/train')
 test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/sklearn_mnist/test')
 job_name = unique_name_from_base('test-sklearn-hp')

 sklearn.fit({'train': train_input, 'test': test_input})
 sklearn.fit({'train': train_input, 'test': test_input}, job_name=job_name)
 return sklearn.latest_training_job.name


Expand DownExpand Up@@ -109,9 +110,10 @@ def test_failed_training_job(sagemaker_session, sklearn_full_version):

 train_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'train'),
 key_prefix='integ-test-data/sklearn_mnist/train')
 job_name = unique_name_from_base('test-sklearn-failed')

 with pytest.raises(ValueError):
 sklearn.fit(train_input)
 sklearn.fit(train_input, job_name=job_name)


def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_version, wait=True):
Expand All@@ -130,8 +132,9 @@ def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_versi
 key_prefix='integ-test-data/sklearn_mnist/train')
 test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/sklearn_mnist/test')
 job_name = unique_name_from_base('test-sklearn-mnist')

 sklearn.fit({'train': train_input, 'test': test_input}, wait=wait)
 sklearn.fit({'train': train_input, 'test': test_input}, wait=wait, job_name=job_name)
 return sklearn.latest_training_job.name


Expand Down

14 changes: 9 additions & 5 deletions
tests/integ/test_tf.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -19,7 +19,7 @@

import tests.integ
from sagemaker.tensorflow import TensorFlow, TensorFlowModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, PYTHON_VERSION
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout
from tests.integ.vpc_test_utils import get_or_create_vpc_resources, setup_security_group_for_encryption
Expand All@@ -46,7 +46,8 @@ def tf_training_job(sagemaker_session, tf_full_version):
 base_job_name='test-tf')

 inputs = sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
 estimator.fit(inputs)
 job_name = unique_name_from_base('test-tf-train')
 estimator.fit(inputs, job_name=job_name)
 print('job succeeded: {}'.format(estimator.latest_training_job.name))

 return estimator.latest_training_job.name
Expand DownExpand Up@@ -123,7 +124,8 @@ def test_tf_async(sagemaker_session):
 base_job_name='test-tf')

 inputs = estimator.sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
 estimator.fit(inputs, wait=False)
 job_name = unique_name_from_base('test-tf-async')
 estimator.fit(inputs, wait=False, job_name=job_name)
 training_job_name = estimator.latest_training_job.name
 time.sleep(20)

Expand DownExpand Up@@ -166,9 +168,10 @@ def test_tf_vpc_multi(sagemaker_session, tf_full_version):
 subnets=subnet_ids,
 security_group_ids=[security_group_id],
 encrypt_inter_container_traffic=True)
 job_name = unique_name_from_base('test-tf-vpc-multi')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 estimator.fit(train_input)
 estimator.fit(train_input, job_name=job_name)
 print('training job succeeded: {}'.format(estimator.latest_training_job.name))

 job_desc = sagemaker_session.sagemaker_client.describe_training_job(
Expand DownExpand Up@@ -209,7 +212,8 @@ def test_failed_tf_training(sagemaker_session, tf_full_version):
 train_instance_count=1,
 train_instance_type='ml.c4.xlarge',
 sagemaker_session=sagemaker_session)
 job_name = unique_name_from_base('test-tf-fail')

 with pytest.raises(ValueError) as e:
 estimator.fit()
 estimator.fit(job_name=job_name)
 assert 'This failure is expected' in str(e.value)

5 changes: 4 additions & 1 deletion
tests/integ/test_tf_cifar.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base

PICKLE_CONTENT_TYPE = 'application/python-pickle'

Expand DownExpand Up@@ -55,7 +56,9 @@ def test_cifar(sagemaker_session, tf_full_version):

 inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
 key_prefix='data/cifar10')
 estimator.fit(inputs, logs=False)
 job_name = unique_name_from_base('test-tf-cifar')

 estimator.fit(inputs, logs=False, job_name=job_name)
 print('job succeeded: {}'.format(estimator.latest_training_job.name))

 endpoint_name = estimator.latest_training_job.name
Expand Down

4 changes: 3 additions & 1 deletion
tests/integ/test_tf_keras.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -21,6 +21,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base


@pytest.mark.canary_quick
Expand All@@ -43,8 +44,9 @@ def test_keras(sagemaker_session, tf_full_version):

 inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
 key_prefix='data/cifar10')
 job_name = unique_name_from_base('test-tf-keras')

 estimator.fit(inputs)
 estimator.fit(inputs, job_name=job_name)

 endpoint_name = estimator.latest_training_job.name
 with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
Expand Down

12 changes: 9 additions & 3 deletions
tests/integ/test_transformer.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from sagemaker import KMeans
from sagemaker.mxnet import MXNet
from sagemaker.transformer import Transformer
from sagemaker.utils import unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, TRANSFORM_DEFAULT_TIMEOUT_MINUTES
from tests.integ.kms_utils import get_or_create_kms_key
from tests.integ.timeout import timeout, timeout_and_delete_model_with_transformer
Expand All@@ -41,9 +42,10 @@ def test_transform_mxnet(sagemaker_session, mxnet_full_version):
 key_prefix='integ-test-data/mxnet_mnist/train')
 test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/mxnet_mnist/test')
 job_name = unique_name_from_base('test-mxnet-transform')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 mx.fit({'train': train_input, 'test': test_input})
 mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

 transform_input_path = os.path.join(data_path, 'transform', 'data.csv')
 transform_input_key_prefix = 'integ-test-data/mxnet_mnist/transform'
Expand DownExpand Up@@ -86,8 +88,11 @@ def test_attach_transform_kmeans(sagemaker_session):
 kmeans.epochs = 1

 records = kmeans.record_set(train_set[0][:100])

 job_name = unique_name_from_base('test-kmeans-attach')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 kmeans.fit(records)
 kmeans.fit(records, job_name=job_name)

 transform_input_path = os.path.join(data_path, 'transform_input.csv')
 transform_input_key_prefix = 'integ-test-data/one_p_mnist/transform'
Expand DownExpand Up@@ -120,9 +125,10 @@ def test_transform_mxnet_vpc(sagemaker_session, mxnet_full_version):
 key_prefix='integ-test-data/mxnet_mnist/train')
 test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/mxnet_mnist/test')
 job_name = unique_name_from_base('test-mxnet-vpc')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 mx.fit({'train': train_input, 'test': test_input})
 mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

 job_desc = sagemaker_session.sagemaker_client.describe_training_job(TrainingJobName=mx.latest_training_job.name)
 assert set(subnet_ids) == set(job_desc['VpcConfig']['Subnets'])
Expand Down

, '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
fix: use unique names for test training jobs#765

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 Merged

chuyang-deng
merged 2 commits into

from

Apr 25, 2019
 Merged


fix: use unique names for test training jobs
#765
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e184cb9

fix: use unique names for test training jobs

Apr 24, 2019
05a1596

Merge branch 'master' into unique_job_name


chuyang-deng Apr 24, 2019

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11 changes: 7 additions & 4 deletions
tests/integ/test_rl.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -18,7 +18,7 @@
import pytest

from sagemaker.rl import RLEstimator, RLFramework, RLToolkit
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand All@@ -29,9 +29,10 @@
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
 estimator = _test_coach(sagemaker_session, RLFramework.MXNET, rl_coach_mxnet_full_version)
 job_name = unique_name_from_base('test-coach-mxnet')

 with timeout(minutes=15):
 estimator.fit(wait='False')
 estimator.fit(wait='False', job_name=job_name)

 estimator = RLEstimator.attach(estimator.latest_training_job.name,
 sagemaker_session=sagemaker_session)
Expand All@@ -52,9 +53,10 @@ def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_tf(sagemaker_session, rl_coach_tf_full_version):
 estimator = _test_coach(sagemaker_session, RLFramework.TENSORFLOW, rl_coach_tf_full_version)
 job_name = unique_name_from_base('test-coach-tf')

 with timeout(minutes=15):
 estimator.fit()
 estimator.fit(job_name=job_name)

 endpoint_name = 'test-tf-coach-deploy-{}'.format(sagemaker_timestamp())

Expand DownExpand Up@@ -104,9 +106,10 @@ def test_ray_tf(sagemaker_session, rl_ray_full_version):
 role='SageMakerRole',
 train_instance_type=CPU_INSTANCE,
 train_instance_count=1)
 job_name = unique_name_from_base('test-ray-tf')

 with timeout(minutes=15):
 estimator.fit()
 estimator.fit(job_name=job_name)

 with pytest.raises(NotImplementedError) as e:
 estimator.deploy(1, CPU_INSTANCE)
Expand Down

11 changes: 7 additions & 4 deletions
tests/integ/test_sklearn_train.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -21,7 +21,7 @@
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.sklearn import SKLearn
from sagemaker.sklearn import SKLearnModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION, TRAINING_DEFAULT_TIMEOUT_MINUTES
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand DownExpand Up@@ -49,8 +49,9 @@ def test_training_with_additional_hyperparameters(sagemaker_session, sklearn_ful
 key_prefix='integ-test-data/sklearn_mnist/train')
 test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/sklearn_mnist/test')
 job_name = unique_name_from_base('test-sklearn-hp')

 sklearn.fit({'train': train_input, 'test': test_input})
 sklearn.fit({'train': train_input, 'test': test_input}, job_name=job_name)
 return sklearn.latest_training_job.name


Expand DownExpand Up@@ -109,9 +110,10 @@ def test_failed_training_job(sagemaker_session, sklearn_full_version):

 train_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'train'),
 key_prefix='integ-test-data/sklearn_mnist/train')
 job_name = unique_name_from_base('test-sklearn-failed')

 with pytest.raises(ValueError):
 sklearn.fit(train_input)
 sklearn.fit(train_input, job_name=job_name)


def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_version, wait=True):
Expand All@@ -130,8 +132,9 @@ def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_versi
 key_prefix='integ-test-data/sklearn_mnist/train')
 test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/sklearn_mnist/test')
 job_name = unique_name_from_base('test-sklearn-mnist')

 sklearn.fit({'train': train_input, 'test': test_input}, wait=wait)
 sklearn.fit({'train': train_input, 'test': test_input}, wait=wait, job_name=job_name)
 return sklearn.latest_training_job.name


Expand Down

14 changes: 9 additions & 5 deletions
tests/integ/test_tf.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -19,7 +19,7 @@

import tests.integ
from sagemaker.tensorflow import TensorFlow, TensorFlowModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, PYTHON_VERSION
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout
from tests.integ.vpc_test_utils import get_or_create_vpc_resources, setup_security_group_for_encryption
Expand All@@ -46,7 +46,8 @@ def tf_training_job(sagemaker_session, tf_full_version):
 base_job_name='test-tf')

 inputs = sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
 estimator.fit(inputs)
 job_name = unique_name_from_base('test-tf-train')
 estimator.fit(inputs, job_name=job_name)
 print('job succeeded: {}'.format(estimator.latest_training_job.name))

 return estimator.latest_training_job.name
Expand DownExpand Up@@ -123,7 +124,8 @@ def test_tf_async(sagemaker_session):
 base_job_name='test-tf')

 inputs = estimator.sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
 estimator.fit(inputs, wait=False)
 job_name = unique_name_from_base('test-tf-async')
 estimator.fit(inputs, wait=False, job_name=job_name)
 training_job_name = estimator.latest_training_job.name
 time.sleep(20)

Expand DownExpand Up@@ -166,9 +168,10 @@ def test_tf_vpc_multi(sagemaker_session, tf_full_version):
 subnets=subnet_ids,
 security_group_ids=[security_group_id],
 encrypt_inter_container_traffic=True)
 job_name = unique_name_from_base('test-tf-vpc-multi')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 estimator.fit(train_input)
 estimator.fit(train_input, job_name=job_name)
 print('training job succeeded: {}'.format(estimator.latest_training_job.name))

 job_desc = sagemaker_session.sagemaker_client.describe_training_job(
Expand DownExpand Up@@ -209,7 +212,8 @@ def test_failed_tf_training(sagemaker_session, tf_full_version):
 train_instance_count=1,
 train_instance_type='ml.c4.xlarge',
 sagemaker_session=sagemaker_session)
 job_name = unique_name_from_base('test-tf-fail')

 with pytest.raises(ValueError) as e:
 estimator.fit()
 estimator.fit(job_name=job_name)
 assert 'This failure is expected' in str(e.value)

5 changes: 4 additions & 1 deletion
tests/integ/test_tf_cifar.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base

PICKLE_CONTENT_TYPE = 'application/python-pickle'

Expand DownExpand Up@@ -55,7 +56,9 @@ def test_cifar(sagemaker_session, tf_full_version):

 inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
 key_prefix='data/cifar10')
 estimator.fit(inputs, logs=False)
 job_name = unique_name_from_base('test-tf-cifar')

 estimator.fit(inputs, logs=False, job_name=job_name)
 print('job succeeded: {}'.format(estimator.latest_training_job.name))

 endpoint_name = estimator.latest_training_job.name
Expand Down

4 changes: 3 additions & 1 deletion
tests/integ/test_tf_keras.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -21,6 +21,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base


@pytest.mark.canary_quick
Expand All@@ -43,8 +44,9 @@ def test_keras(sagemaker_session, tf_full_version):

 inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
 key_prefix='data/cifar10')
 job_name = unique_name_from_base('test-tf-keras')

 estimator.fit(inputs)
 estimator.fit(inputs, job_name=job_name)

 endpoint_name = estimator.latest_training_job.name
 with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
Expand Down

12 changes: 9 additions & 3 deletions
tests/integ/test_transformer.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from sagemaker import KMeans
from sagemaker.mxnet import MXNet
from sagemaker.transformer import Transformer
from sagemaker.utils import unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, TRANSFORM_DEFAULT_TIMEOUT_MINUTES
from tests.integ.kms_utils import get_or_create_kms_key
from tests.integ.timeout import timeout, timeout_and_delete_model_with_transformer
Expand All@@ -41,9 +42,10 @@ def test_transform_mxnet(sagemaker_session, mxnet_full_version):
 key_prefix='integ-test-data/mxnet_mnist/train')
 test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/mxnet_mnist/test')
 job_name = unique_name_from_base('test-mxnet-transform')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 mx.fit({'train': train_input, 'test': test_input})
 mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

 transform_input_path = os.path.join(data_path, 'transform', 'data.csv')
 transform_input_key_prefix = 'integ-test-data/mxnet_mnist/transform'
Expand DownExpand Up@@ -86,8 +88,11 @@ def test_attach_transform_kmeans(sagemaker_session):
 kmeans.epochs = 1

 records = kmeans.record_set(train_set[0][:100])

 job_name = unique_name_from_base('test-kmeans-attach')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 kmeans.fit(records)
 kmeans.fit(records, job_name=job_name)

 transform_input_path = os.path.join(data_path, 'transform_input.csv')
 transform_input_key_prefix = 'integ-test-data/one_p_mnist/transform'
Expand DownExpand Up@@ -120,9 +125,10 @@ def test_transform_mxnet_vpc(sagemaker_session, mxnet_full_version):
 key_prefix='integ-test-data/mxnet_mnist/train')
 test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/mxnet_mnist/test')
 job_name = unique_name_from_base('test-mxnet-vpc')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 mx.fit({'train': train_input, 'test': test_input})
 mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

 job_desc = sagemaker_session.sagemaker_client.describe_training_job(TrainingJobName=mx.latest_training_job.name)
 assert set(subnet_ids) == set(job_desc['VpcConfig']['Subnets'])
Expand Down

, '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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fix: use unique names for test training jobs#765

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chuyang-deng
merged 2 commits into

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Apr 25, 2019
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fix: use unique names for test training jobs
#765
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e184cb9

fix: use unique names for test training jobs

Apr 24, 2019
05a1596

Merge branch 'master' into unique_job_name


chuyang-deng Apr 24, 2019

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11 changes: 7 additions & 4 deletions
tests/integ/test_rl.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -18,7 +18,7 @@
import pytest

from sagemaker.rl import RLEstimator, RLFramework, RLToolkit
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand All@@ -29,9 +29,10 @@
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
 estimator = _test_coach(sagemaker_session, RLFramework.MXNET, rl_coach_mxnet_full_version)
 job_name = unique_name_from_base('test-coach-mxnet')

 with timeout(minutes=15):
 estimator.fit(wait='False')
 estimator.fit(wait='False', job_name=job_name)

 estimator = RLEstimator.attach(estimator.latest_training_job.name,
 sagemaker_session=sagemaker_session)
Expand All@@ -52,9 +53,10 @@ def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_tf(sagemaker_session, rl_coach_tf_full_version):
 estimator = _test_coach(sagemaker_session, RLFramework.TENSORFLOW, rl_coach_tf_full_version)
 job_name = unique_name_from_base('test-coach-tf')

 with timeout(minutes=15):
 estimator.fit()
 estimator.fit(job_name=job_name)

 endpoint_name = 'test-tf-coach-deploy-{}'.format(sagemaker_timestamp())

Expand DownExpand Up@@ -104,9 +106,10 @@ def test_ray_tf(sagemaker_session, rl_ray_full_version):
 role='SageMakerRole',
 train_instance_type=CPU_INSTANCE,
 train_instance_count=1)
 job_name = unique_name_from_base('test-ray-tf')

 with timeout(minutes=15):
 estimator.fit()
 estimator.fit(job_name=job_name)

 with pytest.raises(NotImplementedError) as e:
 estimator.deploy(1, CPU_INSTANCE)
Expand Down

11 changes: 7 additions & 4 deletions
tests/integ/test_sklearn_train.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -21,7 +21,7 @@
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.sklearn import SKLearn
from sagemaker.sklearn import SKLearnModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION, TRAINING_DEFAULT_TIMEOUT_MINUTES
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand DownExpand Up@@ -49,8 +49,9 @@ def test_training_with_additional_hyperparameters(sagemaker_session, sklearn_ful
 key_prefix='integ-test-data/sklearn_mnist/train')
 test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/sklearn_mnist/test')
 job_name = unique_name_from_base('test-sklearn-hp')

 sklearn.fit({'train': train_input, 'test': test_input})
 sklearn.fit({'train': train_input, 'test': test_input}, job_name=job_name)
 return sklearn.latest_training_job.name


Expand DownExpand Up@@ -109,9 +110,10 @@ def test_failed_training_job(sagemaker_session, sklearn_full_version):

 train_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'train'),
 key_prefix='integ-test-data/sklearn_mnist/train')
 job_name = unique_name_from_base('test-sklearn-failed')

 with pytest.raises(ValueError):
 sklearn.fit(train_input)
 sklearn.fit(train_input, job_name=job_name)


def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_version, wait=True):
Expand All@@ -130,8 +132,9 @@ def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_versi
 key_prefix='integ-test-data/sklearn_mnist/train')
 test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/sklearn_mnist/test')
 job_name = unique_name_from_base('test-sklearn-mnist')

 sklearn.fit({'train': train_input, 'test': test_input}, wait=wait)
 sklearn.fit({'train': train_input, 'test': test_input}, wait=wait, job_name=job_name)
 return sklearn.latest_training_job.name


Expand Down

14 changes: 9 additions & 5 deletions
tests/integ/test_tf.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -19,7 +19,7 @@

import tests.integ
from sagemaker.tensorflow import TensorFlow, TensorFlowModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, PYTHON_VERSION
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout
from tests.integ.vpc_test_utils import get_or_create_vpc_resources, setup_security_group_for_encryption
Expand All@@ -46,7 +46,8 @@ def tf_training_job(sagemaker_session, tf_full_version):
 base_job_name='test-tf')

 inputs = sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
 estimator.fit(inputs)
 job_name = unique_name_from_base('test-tf-train')
 estimator.fit(inputs, job_name=job_name)
 print('job succeeded: {}'.format(estimator.latest_training_job.name))

 return estimator.latest_training_job.name
Expand DownExpand Up@@ -123,7 +124,8 @@ def test_tf_async(sagemaker_session):
 base_job_name='test-tf')

 inputs = estimator.sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
 estimator.fit(inputs, wait=False)
 job_name = unique_name_from_base('test-tf-async')
 estimator.fit(inputs, wait=False, job_name=job_name)
 training_job_name = estimator.latest_training_job.name
 time.sleep(20)

Expand DownExpand Up@@ -166,9 +168,10 @@ def test_tf_vpc_multi(sagemaker_session, tf_full_version):
 subnets=subnet_ids,
 security_group_ids=[security_group_id],
 encrypt_inter_container_traffic=True)
 job_name = unique_name_from_base('test-tf-vpc-multi')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 estimator.fit(train_input)
 estimator.fit(train_input, job_name=job_name)
 print('training job succeeded: {}'.format(estimator.latest_training_job.name))

 job_desc = sagemaker_session.sagemaker_client.describe_training_job(
Expand DownExpand Up@@ -209,7 +212,8 @@ def test_failed_tf_training(sagemaker_session, tf_full_version):
 train_instance_count=1,
 train_instance_type='ml.c4.xlarge',
 sagemaker_session=sagemaker_session)
 job_name = unique_name_from_base('test-tf-fail')

 with pytest.raises(ValueError) as e:
 estimator.fit()
 estimator.fit(job_name=job_name)
 assert 'This failure is expected' in str(e.value)

5 changes: 4 additions & 1 deletion
tests/integ/test_tf_cifar.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base

PICKLE_CONTENT_TYPE = 'application/python-pickle'

Expand DownExpand Up@@ -55,7 +56,9 @@ def test_cifar(sagemaker_session, tf_full_version):

 inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
 key_prefix='data/cifar10')
 estimator.fit(inputs, logs=False)
 job_name = unique_name_from_base('test-tf-cifar')

 estimator.fit(inputs, logs=False, job_name=job_name)
 print('job succeeded: {}'.format(estimator.latest_training_job.name))

 endpoint_name = estimator.latest_training_job.name
Expand Down

4 changes: 3 additions & 1 deletion
tests/integ/test_tf_keras.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -21,6 +21,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base


@pytest.mark.canary_quick
Expand All@@ -43,8 +44,9 @@ def test_keras(sagemaker_session, tf_full_version):

 inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
 key_prefix='data/cifar10')
 job_name = unique_name_from_base('test-tf-keras')

 estimator.fit(inputs)
 estimator.fit(inputs, job_name=job_name)

 endpoint_name = estimator.latest_training_job.name
 with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
Expand Down

12 changes: 9 additions & 3 deletions
tests/integ/test_transformer.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from sagemaker import KMeans
from sagemaker.mxnet import MXNet
from sagemaker.transformer import Transformer
from sagemaker.utils import unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, TRANSFORM_DEFAULT_TIMEOUT_MINUTES
from tests.integ.kms_utils import get_or_create_kms_key
from tests.integ.timeout import timeout, timeout_and_delete_model_with_transformer
Expand All@@ -41,9 +42,10 @@ def test_transform_mxnet(sagemaker_session, mxnet_full_version):
 key_prefix='integ-test-data/mxnet_mnist/train')
 test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/mxnet_mnist/test')
 job_name = unique_name_from_base('test-mxnet-transform')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 mx.fit({'train': train_input, 'test': test_input})
 mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

 transform_input_path = os.path.join(data_path, 'transform', 'data.csv')
 transform_input_key_prefix = 'integ-test-data/mxnet_mnist/transform'
Expand DownExpand Up@@ -86,8 +88,11 @@ def test_attach_transform_kmeans(sagemaker_session):
 kmeans.epochs = 1

 records = kmeans.record_set(train_set[0][:100])

 job_name = unique_name_from_base('test-kmeans-attach')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 kmeans.fit(records)
 kmeans.fit(records, job_name=job_name)

 transform_input_path = os.path.join(data_path, 'transform_input.csv')
 transform_input_key_prefix = 'integ-test-data/one_p_mnist/transform'
Expand DownExpand Up@@ -120,9 +125,10 @@ def test_transform_mxnet_vpc(sagemaker_session, mxnet_full_version):
 key_prefix='integ-test-data/mxnet_mnist/train')
 test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/mxnet_mnist/test')
 job_name = unique_name_from_base('test-mxnet-vpc')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 mx.fit({'train': train_input, 'test': test_input})
 mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

 job_desc = sagemaker_session.sagemaker_client.describe_training_job(TrainingJobName=mx.latest_training_job.name)
 assert set(subnet_ids) == set(job_desc['VpcConfig']['Subnets'])
Expand Down

, '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
fix: use unique names for test training jobs#765

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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privacy statement. We’ll occasionally send you account related emails.

Already on GitHub?
Sign in
to your account

 Merged

chuyang-deng
merged 2 commits into

from

Apr 25, 2019
 Merged


fix: use unique names for test training jobs
#765
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e184cb9

fix: use unique names for test training jobs

Apr 24, 2019
05a1596

Merge branch 'master' into unique_job_name


chuyang-deng Apr 24, 2019

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11 changes: 7 additions & 4 deletions
tests/integ/test_rl.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -18,7 +18,7 @@
import pytest

from sagemaker.rl import RLEstimator, RLFramework, RLToolkit
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand All@@ -29,9 +29,10 @@
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
 estimator = _test_coach(sagemaker_session, RLFramework.MXNET, rl_coach_mxnet_full_version)
 job_name = unique_name_from_base('test-coach-mxnet')

 with timeout(minutes=15):
 estimator.fit(wait='False')
 estimator.fit(wait='False', job_name=job_name)

 estimator = RLEstimator.attach(estimator.latest_training_job.name,
 sagemaker_session=sagemaker_session)
Expand All@@ -52,9 +53,10 @@ def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_tf(sagemaker_session, rl_coach_tf_full_version):
 estimator = _test_coach(sagemaker_session, RLFramework.TENSORFLOW, rl_coach_tf_full_version)
 job_name = unique_name_from_base('test-coach-tf')

 with timeout(minutes=15):
 estimator.fit()
 estimator.fit(job_name=job_name)

 endpoint_name = 'test-tf-coach-deploy-{}'.format(sagemaker_timestamp())

Expand DownExpand Up@@ -104,9 +106,10 @@ def test_ray_tf(sagemaker_session, rl_ray_full_version):
 role='SageMakerRole',
 train_instance_type=CPU_INSTANCE,
 train_instance_count=1)
 job_name = unique_name_from_base('test-ray-tf')

 with timeout(minutes=15):
 estimator.fit()
 estimator.fit(job_name=job_name)

 with pytest.raises(NotImplementedError) as e:
 estimator.deploy(1, CPU_INSTANCE)
Expand Down

11 changes: 7 additions & 4 deletions
tests/integ/test_sklearn_train.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -21,7 +21,7 @@
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.sklearn import SKLearn
from sagemaker.sklearn import SKLearnModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION, TRAINING_DEFAULT_TIMEOUT_MINUTES
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand DownExpand Up@@ -49,8 +49,9 @@ def test_training_with_additional_hyperparameters(sagemaker_session, sklearn_ful
 key_prefix='integ-test-data/sklearn_mnist/train')
 test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/sklearn_mnist/test')
 job_name = unique_name_from_base('test-sklearn-hp')

 sklearn.fit({'train': train_input, 'test': test_input})
 sklearn.fit({'train': train_input, 'test': test_input}, job_name=job_name)
 return sklearn.latest_training_job.name


Expand DownExpand Up@@ -109,9 +110,10 @@ def test_failed_training_job(sagemaker_session, sklearn_full_version):

 train_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'train'),
 key_prefix='integ-test-data/sklearn_mnist/train')
 job_name = unique_name_from_base('test-sklearn-failed')

 with pytest.raises(ValueError):
 sklearn.fit(train_input)
 sklearn.fit(train_input, job_name=job_name)


def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_version, wait=True):
Expand All@@ -130,8 +132,9 @@ def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_versi
 key_prefix='integ-test-data/sklearn_mnist/train')
 test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/sklearn_mnist/test')
 job_name = unique_name_from_base('test-sklearn-mnist')

 sklearn.fit({'train': train_input, 'test': test_input}, wait=wait)
 sklearn.fit({'train': train_input, 'test': test_input}, wait=wait, job_name=job_name)
 return sklearn.latest_training_job.name


Expand Down

14 changes: 9 additions & 5 deletions
tests/integ/test_tf.py

View file


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Original file line numberDiff line numberDiff line change
Expand Up@@ -19,7 +19,7 @@

import tests.integ
from sagemaker.tensorflow import TensorFlow, TensorFlowModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, PYTHON_VERSION
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout
from tests.integ.vpc_test_utils import get_or_create_vpc_resources, setup_security_group_for_encryption
Expand All@@ -46,7 +46,8 @@ def tf_training_job(sagemaker_session, tf_full_version):
 base_job_name='test-tf')

 inputs = sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
 estimator.fit(inputs)
 job_name = unique_name_from_base('test-tf-train')
 estimator.fit(inputs, job_name=job_name)
 print('job succeeded: {}'.format(estimator.latest_training_job.name))

 return estimator.latest_training_job.name
Expand DownExpand Up@@ -123,7 +124,8 @@ def test_tf_async(sagemaker_session):
 base_job_name='test-tf')

 inputs = estimator.sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
 estimator.fit(inputs, wait=False)
 job_name = unique_name_from_base('test-tf-async')
 estimator.fit(inputs, wait=False, job_name=job_name)
 training_job_name = estimator.latest_training_job.name
 time.sleep(20)

Expand DownExpand Up@@ -166,9 +168,10 @@ def test_tf_vpc_multi(sagemaker_session, tf_full_version):
 subnets=subnet_ids,
 security_group_ids=[security_group_id],
 encrypt_inter_container_traffic=True)
 job_name = unique_name_from_base('test-tf-vpc-multi')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 estimator.fit(train_input)
 estimator.fit(train_input, job_name=job_name)
 print('training job succeeded: {}'.format(estimator.latest_training_job.name))

 job_desc = sagemaker_session.sagemaker_client.describe_training_job(
Expand DownExpand Up@@ -209,7 +212,8 @@ def test_failed_tf_training(sagemaker_session, tf_full_version):
 train_instance_count=1,
 train_instance_type='ml.c4.xlarge',
 sagemaker_session=sagemaker_session)
 job_name = unique_name_from_base('test-tf-fail')

 with pytest.raises(ValueError) as e:
 estimator.fit()
 estimator.fit(job_name=job_name)
 assert 'This failure is expected' in str(e.value)

5 changes: 4 additions & 1 deletion
tests/integ/test_tf_cifar.py

View file


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Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base

PICKLE_CONTENT_TYPE = 'application/python-pickle'

Expand DownExpand Up@@ -55,7 +56,9 @@ def test_cifar(sagemaker_session, tf_full_version):

 inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
 key_prefix='data/cifar10')
 estimator.fit(inputs, logs=False)
 job_name = unique_name_from_base('test-tf-cifar')

 estimator.fit(inputs, logs=False, job_name=job_name)
 print('job succeeded: {}'.format(estimator.latest_training_job.name))

 endpoint_name = estimator.latest_training_job.name
Expand Down

4 changes: 3 additions & 1 deletion
tests/integ/test_tf_keras.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -21,6 +21,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base


@pytest.mark.canary_quick
Expand All@@ -43,8 +44,9 @@ def test_keras(sagemaker_session, tf_full_version):

 inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
 key_prefix='data/cifar10')
 job_name = unique_name_from_base('test-tf-keras')

 estimator.fit(inputs)
 estimator.fit(inputs, job_name=job_name)

 endpoint_name = estimator.latest_training_job.name
 with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
Expand Down

12 changes: 9 additions & 3 deletions
tests/integ/test_transformer.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from sagemaker import KMeans
from sagemaker.mxnet import MXNet
from sagemaker.transformer import Transformer
from sagemaker.utils import unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, TRANSFORM_DEFAULT_TIMEOUT_MINUTES
from tests.integ.kms_utils import get_or_create_kms_key
from tests.integ.timeout import timeout, timeout_and_delete_model_with_transformer
Expand All@@ -41,9 +42,10 @@ def test_transform_mxnet(sagemaker_session, mxnet_full_version):
 key_prefix='integ-test-data/mxnet_mnist/train')
 test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/mxnet_mnist/test')
 job_name = unique_name_from_base('test-mxnet-transform')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 mx.fit({'train': train_input, 'test': test_input})
 mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

 transform_input_path = os.path.join(data_path, 'transform', 'data.csv')
 transform_input_key_prefix = 'integ-test-data/mxnet_mnist/transform'
Expand DownExpand Up@@ -86,8 +88,11 @@ def test_attach_transform_kmeans(sagemaker_session):
 kmeans.epochs = 1

 records = kmeans.record_set(train_set[0][:100])

 job_name = unique_name_from_base('test-kmeans-attach')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 kmeans.fit(records)
 kmeans.fit(records, job_name=job_name)

 transform_input_path = os.path.join(data_path, 'transform_input.csv')
 transform_input_key_prefix = 'integ-test-data/one_p_mnist/transform'
Expand DownExpand Up@@ -120,9 +125,10 @@ def test_transform_mxnet_vpc(sagemaker_session, mxnet_full_version):
 key_prefix='integ-test-data/mxnet_mnist/train')
 test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/mxnet_mnist/test')
 job_name = unique_name_from_base('test-mxnet-vpc')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 mx.fit({'train': train_input, 'test': test_input})
 mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

 job_desc = sagemaker_session.sagemaker_client.describe_training_job(TrainingJobName=mx.latest_training_job.name)
 assert set(subnet_ids) == set(job_desc['VpcConfig']['Subnets'])
Expand Down

, '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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fix: use unique names for test training jobs#765

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chuyang-deng
merged 2 commits into

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Apr 25, 2019
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fix: use unique names for test training jobs
#765
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e184cb9

fix: use unique names for test training jobs

Apr 24, 2019
05a1596

Merge branch 'master' into unique_job_name


chuyang-deng Apr 24, 2019

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11 changes: 7 additions & 4 deletions
tests/integ/test_rl.py

View file


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Original file line numberDiff line numberDiff line change
Expand Up@@ -18,7 +18,7 @@
import pytest

from sagemaker.rl import RLEstimator, RLFramework, RLToolkit
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand All@@ -29,9 +29,10 @@
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
 estimator = _test_coach(sagemaker_session, RLFramework.MXNET, rl_coach_mxnet_full_version)
 job_name = unique_name_from_base('test-coach-mxnet')

 with timeout(minutes=15):
 estimator.fit(wait='False')
 estimator.fit(wait='False', job_name=job_name)

 estimator = RLEstimator.attach(estimator.latest_training_job.name,
 sagemaker_session=sagemaker_session)
Expand All@@ -52,9 +53,10 @@ def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_tf(sagemaker_session, rl_coach_tf_full_version):
 estimator = _test_coach(sagemaker_session, RLFramework.TENSORFLOW, rl_coach_tf_full_version)
 job_name = unique_name_from_base('test-coach-tf')

 with timeout(minutes=15):
 estimator.fit()
 estimator.fit(job_name=job_name)

 endpoint_name = 'test-tf-coach-deploy-{}'.format(sagemaker_timestamp())

Expand DownExpand Up@@ -104,9 +106,10 @@ def test_ray_tf(sagemaker_session, rl_ray_full_version):
 role='SageMakerRole',
 train_instance_type=CPU_INSTANCE,
 train_instance_count=1)
 job_name = unique_name_from_base('test-ray-tf')

 with timeout(minutes=15):
 estimator.fit()
 estimator.fit(job_name=job_name)

 with pytest.raises(NotImplementedError) as e:
 estimator.deploy(1, CPU_INSTANCE)
Expand Down

11 changes: 7 additions & 4 deletions
tests/integ/test_sklearn_train.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -21,7 +21,7 @@
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.sklearn import SKLearn
from sagemaker.sklearn import SKLearnModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION, TRAINING_DEFAULT_TIMEOUT_MINUTES
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand DownExpand Up@@ -49,8 +49,9 @@ def test_training_with_additional_hyperparameters(sagemaker_session, sklearn_ful
 key_prefix='integ-test-data/sklearn_mnist/train')
 test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/sklearn_mnist/test')
 job_name = unique_name_from_base('test-sklearn-hp')

 sklearn.fit({'train': train_input, 'test': test_input})
 sklearn.fit({'train': train_input, 'test': test_input}, job_name=job_name)
 return sklearn.latest_training_job.name


Expand DownExpand Up@@ -109,9 +110,10 @@ def test_failed_training_job(sagemaker_session, sklearn_full_version):

 train_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'train'),
 key_prefix='integ-test-data/sklearn_mnist/train')
 job_name = unique_name_from_base('test-sklearn-failed')

 with pytest.raises(ValueError):
 sklearn.fit(train_input)
 sklearn.fit(train_input, job_name=job_name)


def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_version, wait=True):
Expand All@@ -130,8 +132,9 @@ def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_versi
 key_prefix='integ-test-data/sklearn_mnist/train')
 test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/sklearn_mnist/test')
 job_name = unique_name_from_base('test-sklearn-mnist')

 sklearn.fit({'train': train_input, 'test': test_input}, wait=wait)
 sklearn.fit({'train': train_input, 'test': test_input}, wait=wait, job_name=job_name)
 return sklearn.latest_training_job.name


Expand Down

14 changes: 9 additions & 5 deletions
tests/integ/test_tf.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -19,7 +19,7 @@

import tests.integ
from sagemaker.tensorflow import TensorFlow, TensorFlowModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, PYTHON_VERSION
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout
from tests.integ.vpc_test_utils import get_or_create_vpc_resources, setup_security_group_for_encryption
Expand All@@ -46,7 +46,8 @@ def tf_training_job(sagemaker_session, tf_full_version):
 base_job_name='test-tf')

 inputs = sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
 estimator.fit(inputs)
 job_name = unique_name_from_base('test-tf-train')
 estimator.fit(inputs, job_name=job_name)
 print('job succeeded: {}'.format(estimator.latest_training_job.name))

 return estimator.latest_training_job.name
Expand DownExpand Up@@ -123,7 +124,8 @@ def test_tf_async(sagemaker_session):
 base_job_name='test-tf')

 inputs = estimator.sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
 estimator.fit(inputs, wait=False)
 job_name = unique_name_from_base('test-tf-async')
 estimator.fit(inputs, wait=False, job_name=job_name)
 training_job_name = estimator.latest_training_job.name
 time.sleep(20)

Expand DownExpand Up@@ -166,9 +168,10 @@ def test_tf_vpc_multi(sagemaker_session, tf_full_version):
 subnets=subnet_ids,
 security_group_ids=[security_group_id],
 encrypt_inter_container_traffic=True)
 job_name = unique_name_from_base('test-tf-vpc-multi')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 estimator.fit(train_input)
 estimator.fit(train_input, job_name=job_name)
 print('training job succeeded: {}'.format(estimator.latest_training_job.name))

 job_desc = sagemaker_session.sagemaker_client.describe_training_job(
Expand DownExpand Up@@ -209,7 +212,8 @@ def test_failed_tf_training(sagemaker_session, tf_full_version):
 train_instance_count=1,
 train_instance_type='ml.c4.xlarge',
 sagemaker_session=sagemaker_session)
 job_name = unique_name_from_base('test-tf-fail')

 with pytest.raises(ValueError) as e:
 estimator.fit()
 estimator.fit(job_name=job_name)
 assert 'This failure is expected' in str(e.value)

5 changes: 4 additions & 1 deletion
tests/integ/test_tf_cifar.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base

PICKLE_CONTENT_TYPE = 'application/python-pickle'

Expand DownExpand Up@@ -55,7 +56,9 @@ def test_cifar(sagemaker_session, tf_full_version):

 inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
 key_prefix='data/cifar10')
 estimator.fit(inputs, logs=False)
 job_name = unique_name_from_base('test-tf-cifar')

 estimator.fit(inputs, logs=False, job_name=job_name)
 print('job succeeded: {}'.format(estimator.latest_training_job.name))

 endpoint_name = estimator.latest_training_job.name
Expand Down

4 changes: 3 additions & 1 deletion
tests/integ/test_tf_keras.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -21,6 +21,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base


@pytest.mark.canary_quick
Expand All@@ -43,8 +44,9 @@ def test_keras(sagemaker_session, tf_full_version):

 inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
 key_prefix='data/cifar10')
 job_name = unique_name_from_base('test-tf-keras')

 estimator.fit(inputs)
 estimator.fit(inputs, job_name=job_name)

 endpoint_name = estimator.latest_training_job.name
 with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
Expand Down

12 changes: 9 additions & 3 deletions
tests/integ/test_transformer.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from sagemaker import KMeans
from sagemaker.mxnet import MXNet
from sagemaker.transformer import Transformer
from sagemaker.utils import unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, TRANSFORM_DEFAULT_TIMEOUT_MINUTES
from tests.integ.kms_utils import get_or_create_kms_key
from tests.integ.timeout import timeout, timeout_and_delete_model_with_transformer
Expand All@@ -41,9 +42,10 @@ def test_transform_mxnet(sagemaker_session, mxnet_full_version):
 key_prefix='integ-test-data/mxnet_mnist/train')
 test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/mxnet_mnist/test')
 job_name = unique_name_from_base('test-mxnet-transform')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 mx.fit({'train': train_input, 'test': test_input})
 mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

 transform_input_path = os.path.join(data_path, 'transform', 'data.csv')
 transform_input_key_prefix = 'integ-test-data/mxnet_mnist/transform'
Expand DownExpand Up@@ -86,8 +88,11 @@ def test_attach_transform_kmeans(sagemaker_session):
 kmeans.epochs = 1

 records = kmeans.record_set(train_set[0][:100])

 job_name = unique_name_from_base('test-kmeans-attach')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 kmeans.fit(records)
 kmeans.fit(records, job_name=job_name)

 transform_input_path = os.path.join(data_path, 'transform_input.csv')
 transform_input_key_prefix = 'integ-test-data/one_p_mnist/transform'
Expand DownExpand Up@@ -120,9 +125,10 @@ def test_transform_mxnet_vpc(sagemaker_session, mxnet_full_version):
 key_prefix='integ-test-data/mxnet_mnist/train')
 test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/mxnet_mnist/test')
 job_name = unique_name_from_base('test-mxnet-vpc')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 mx.fit({'train': train_input, 'test': test_input})
 mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

 job_desc = sagemaker_session.sagemaker_client.describe_training_job(TrainingJobName=mx.latest_training_job.name)
 assert set(subnet_ids) == set(job_desc['VpcConfig']['Subnets'])
Expand Down

, '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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fix: use unique names for test training jobs#765

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chuyang-deng
merged 2 commits into

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Apr 25, 2019
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fix: use unique names for test training jobs
#765
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e184cb9

fix: use unique names for test training jobs

Apr 24, 2019
05a1596

Merge branch 'master' into unique_job_name


chuyang-deng Apr 24, 2019

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11 changes: 7 additions & 4 deletions
tests/integ/test_rl.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -18,7 +18,7 @@
import pytest

from sagemaker.rl import RLEstimator, RLFramework, RLToolkit
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand All@@ -29,9 +29,10 @@
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
 estimator = _test_coach(sagemaker_session, RLFramework.MXNET, rl_coach_mxnet_full_version)
 job_name = unique_name_from_base('test-coach-mxnet')

 with timeout(minutes=15):
 estimator.fit(wait='False')
 estimator.fit(wait='False', job_name=job_name)

 estimator = RLEstimator.attach(estimator.latest_training_job.name,
 sagemaker_session=sagemaker_session)
Expand All@@ -52,9 +53,10 @@ def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version):
@pytest.mark.skipif(PYTHON_VERSION != 'py3', reason="RL images supports only Python 3.")
def test_coach_tf(sagemaker_session, rl_coach_tf_full_version):
 estimator = _test_coach(sagemaker_session, RLFramework.TENSORFLOW, rl_coach_tf_full_version)
 job_name = unique_name_from_base('test-coach-tf')

 with timeout(minutes=15):
 estimator.fit()
 estimator.fit(job_name=job_name)

 endpoint_name = 'test-tf-coach-deploy-{}'.format(sagemaker_timestamp())

Expand DownExpand Up@@ -104,9 +106,10 @@ def test_ray_tf(sagemaker_session, rl_ray_full_version):
 role='SageMakerRole',
 train_instance_type=CPU_INSTANCE,
 train_instance_count=1)
 job_name = unique_name_from_base('test-ray-tf')

 with timeout(minutes=15):
 estimator.fit()
 estimator.fit(job_name=job_name)

 with pytest.raises(NotImplementedError) as e:
 estimator.deploy(1, CPU_INSTANCE)
Expand Down

11 changes: 7 additions & 4 deletions
tests/integ/test_sklearn_train.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -21,7 +21,7 @@
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.sklearn import SKLearn
from sagemaker.sklearn import SKLearnModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, PYTHON_VERSION, TRAINING_DEFAULT_TIMEOUT_MINUTES
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

Expand DownExpand Up@@ -49,8 +49,9 @@ def test_training_with_additional_hyperparameters(sagemaker_session, sklearn_ful
 key_prefix='integ-test-data/sklearn_mnist/train')
 test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/sklearn_mnist/test')
 job_name = unique_name_from_base('test-sklearn-hp')

 sklearn.fit({'train': train_input, 'test': test_input})
 sklearn.fit({'train': train_input, 'test': test_input}, job_name=job_name)
 return sklearn.latest_training_job.name


Expand DownExpand Up@@ -109,9 +110,10 @@ def test_failed_training_job(sagemaker_session, sklearn_full_version):

 train_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'train'),
 key_prefix='integ-test-data/sklearn_mnist/train')
 job_name = unique_name_from_base('test-sklearn-failed')

 with pytest.raises(ValueError):
 sklearn.fit(train_input)
 sklearn.fit(train_input, job_name=job_name)


def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_version, wait=True):
Expand All@@ -130,8 +132,9 @@ def _run_mnist_training_job(sagemaker_session, instance_type, sklearn_full_versi
 key_prefix='integ-test-data/sklearn_mnist/train')
 test_input = sklearn.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/sklearn_mnist/test')
 job_name = unique_name_from_base('test-sklearn-mnist')

 sklearn.fit({'train': train_input, 'test': test_input}, wait=wait)
 sklearn.fit({'train': train_input, 'test': test_input}, wait=wait, job_name=job_name)
 return sklearn.latest_training_job.name


Expand Down

14 changes: 9 additions & 5 deletions
tests/integ/test_tf.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -19,7 +19,7 @@

import tests.integ
from sagemaker.tensorflow import TensorFlow, TensorFlowModel
from sagemaker.utils import sagemaker_timestamp
from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, PYTHON_VERSION
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout
from tests.integ.vpc_test_utils import get_or_create_vpc_resources, setup_security_group_for_encryption
Expand All@@ -46,7 +46,8 @@ def tf_training_job(sagemaker_session, tf_full_version):
 base_job_name='test-tf')

 inputs = sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
 estimator.fit(inputs)
 job_name = unique_name_from_base('test-tf-train')
 estimator.fit(inputs, job_name=job_name)
 print('job succeeded: {}'.format(estimator.latest_training_job.name))

 return estimator.latest_training_job.name
Expand DownExpand Up@@ -123,7 +124,8 @@ def test_tf_async(sagemaker_session):
 base_job_name='test-tf')

 inputs = estimator.sagemaker_session.upload_data(path=DATA_PATH, key_prefix='integ-test-data/tf_iris')
 estimator.fit(inputs, wait=False)
 job_name = unique_name_from_base('test-tf-async')
 estimator.fit(inputs, wait=False, job_name=job_name)
 training_job_name = estimator.latest_training_job.name
 time.sleep(20)

Expand DownExpand Up@@ -166,9 +168,10 @@ def test_tf_vpc_multi(sagemaker_session, tf_full_version):
 subnets=subnet_ids,
 security_group_ids=[security_group_id],
 encrypt_inter_container_traffic=True)
 job_name = unique_name_from_base('test-tf-vpc-multi')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 estimator.fit(train_input)
 estimator.fit(train_input, job_name=job_name)
 print('training job succeeded: {}'.format(estimator.latest_training_job.name))

 job_desc = sagemaker_session.sagemaker_client.describe_training_job(
Expand DownExpand Up@@ -209,7 +212,8 @@ def test_failed_tf_training(sagemaker_session, tf_full_version):
 train_instance_count=1,
 train_instance_type='ml.c4.xlarge',
 sagemaker_session=sagemaker_session)
 job_name = unique_name_from_base('test-tf-fail')

 with pytest.raises(ValueError) as e:
 estimator.fit()
 estimator.fit(job_name=job_name)
 assert 'This failure is expected' in str(e.value)

5 changes: 4 additions & 1 deletion
tests/integ/test_tf_cifar.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base

PICKLE_CONTENT_TYPE = 'application/python-pickle'

Expand DownExpand Up@@ -55,7 +56,9 @@ def test_cifar(sagemaker_session, tf_full_version):

 inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
 key_prefix='data/cifar10')
 estimator.fit(inputs, logs=False)
 job_name = unique_name_from_base('test-tf-cifar')

 estimator.fit(inputs, logs=False, job_name=job_name)
 print('job succeeded: {}'.format(estimator.latest_training_job.name))

 endpoint_name = estimator.latest_training_job.name
Expand Down

4 changes: 3 additions & 1 deletion
tests/integ/test_tf_keras.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -21,6 +21,7 @@
from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout

from sagemaker.tensorflow import TensorFlow
from sagemaker.utils import unique_name_from_base


@pytest.mark.canary_quick
Expand All@@ -43,8 +44,9 @@ def test_keras(sagemaker_session, tf_full_version):

 inputs = estimator.sagemaker_session.upload_data(path=dataset_path,
 key_prefix='data/cifar10')
 job_name = unique_name_from_base('test-tf-keras')

 estimator.fit(inputs)
 estimator.fit(inputs, job_name=job_name)

 endpoint_name = estimator.latest_training_job.name
 with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
Expand Down

12 changes: 9 additions & 3 deletions
tests/integ/test_transformer.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -22,6 +22,7 @@
from sagemaker import KMeans
from sagemaker.mxnet import MXNet
from sagemaker.transformer import Transformer
from sagemaker.utils import unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, TRANSFORM_DEFAULT_TIMEOUT_MINUTES
from tests.integ.kms_utils import get_or_create_kms_key
from tests.integ.timeout import timeout, timeout_and_delete_model_with_transformer
Expand All@@ -41,9 +42,10 @@ def test_transform_mxnet(sagemaker_session, mxnet_full_version):
 key_prefix='integ-test-data/mxnet_mnist/train')
 test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/mxnet_mnist/test')
 job_name = unique_name_from_base('test-mxnet-transform')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 mx.fit({'train': train_input, 'test': test_input})
 mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

 transform_input_path = os.path.join(data_path, 'transform', 'data.csv')
 transform_input_key_prefix = 'integ-test-data/mxnet_mnist/transform'
Expand DownExpand Up@@ -86,8 +88,11 @@ def test_attach_transform_kmeans(sagemaker_session):
 kmeans.epochs = 1

 records = kmeans.record_set(train_set[0][:100])

 job_name = unique_name_from_base('test-kmeans-attach')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 kmeans.fit(records)
 kmeans.fit(records, job_name=job_name)

 transform_input_path = os.path.join(data_path, 'transform_input.csv')
 transform_input_key_prefix = 'integ-test-data/one_p_mnist/transform'
Expand DownExpand Up@@ -120,9 +125,10 @@ def test_transform_mxnet_vpc(sagemaker_session, mxnet_full_version):
 key_prefix='integ-test-data/mxnet_mnist/train')
 test_input = mx.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
 key_prefix='integ-test-data/mxnet_mnist/test')
 job_name = unique_name_from_base('test-mxnet-vpc')

 with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
 mx.fit({'train': train_input, 'test': test_input})
 mx.fit({'train': train_input, 'test': test_input}, job_name=job_name)

 job_desc = sagemaker_session.sagemaker_client.describe_training_job(TrainingJobName=mx.latest_training_job.name)
 assert set(subnet_ids) == set(job_desc['VpcConfig']['Subnets'])
Expand Down