fix: pipeline upsert failed to pass parallelism_config to update#4066

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Merged
knikure merged 1 commit into from
Aug 17, 2023
Merged

fix: pipeline upsert failed to pass parallelism_config to update #4066

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2 changes: 1 addition & 1 deletion src/sagemaker/workflow/pipeline.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -294,7 +294,7 @@ def upsert(
if not (error_code == "ValidationException" and "already exists" in error_message):
raise ce
# already exists
response = self.update(role_arn, description)
response = self.update(role_arn, description, parallelism_config=parallelism_config)
# add new tags to existing resource
if tags is not None:
old_tags = self.sagemaker_session.sagemaker_client.list_tags(
Expand Down
96 changes: 95 additions & 1 deletion tests/integ/sagemaker/workflow/test_workflow.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -24,6 +24,7 @@

import pandas as pd

from sagemaker.utils import retry_with_backoff
from tests.integ.sagemaker.workflow.helpers import wait_pipeline_execution
from tests.integ.s3_utils import extract_files_from_s3
from sagemaker.workflow.model_step import (
Expand DownExpand Up@@ -1002,7 +1003,7 @@ def test_create_and_update_with_parallelism_config(
assert response["ParallelismConfiguration"]["MaxParallelExecutionSteps"] == 50

pipeline.parameters = [ParameterInteger(name="InstanceCount", default_value=1)]
response = pipeline.update(role, parallelism_config={"MaxParallelExecutionSteps": 55})
response = pipeline.upsert(role, parallelism_config={"MaxParallelExecutionSteps": 55})
update_arn = response["PipelineArn"]
assert re.match(
rf"arn:aws:sagemaker:{region_name}:\d{{12}}:pipeline/{pipeline_name}",
Expand All@@ -1019,6 +1020,99 @@ def test_create_and_update_with_parallelism_config(
pass


def test_create_and_start_without_parallelism_config_override(
pipeline_session, role, pipeline_name, script_dir
):
sklearn_train = SKLearn(
framework_version="0.20.0",
entry_point=os.path.join(script_dir, "train.py"),
instance_type="ml.m5.xlarge",
sagemaker_session=pipeline_session,
role=role,
)

train_steps = [
TrainingStep(
name=f"my-train-{count}",
display_name="TrainingStep",
description="description for Training step",
step_args=sklearn_train.fit(),
)
for count in range(2)
]
pipeline = Pipeline(
name=pipeline_name,
steps=train_steps,
sagemaker_session=pipeline_session,
)

try:
pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
# No ParallelismConfiguration given in pipeline.start, so it won't override that in pipeline.create
execution = pipeline.start()

def validate():
# Only one step would be scheduled initially
assert len(execution.list_steps()) == 1
Comment thread
qidewenwhen marked this conversation as resolved.

retry_with_backoff(validate, num_attempts=4)

wait_pipeline_execution(execution=execution)

finally:
try:
pipeline.delete()
except Exception:
pass


def test_create_and_start_with_parallelism_config_override(
pipeline_session, role, pipeline_name, script_dir
):
sklearn_train = SKLearn(
framework_version="0.20.0",
entry_point=os.path.join(script_dir, "train.py"),
instance_type="ml.m5.xlarge",
sagemaker_session=pipeline_session,
role=role,
)

train_steps = [
TrainingStep(
name=f"my-train-{count}",
display_name="TrainingStep",
description="description for Training step",
step_args=sklearn_train.fit(),
)
for count in range(2)
]
pipeline = Pipeline(
name=pipeline_name,
steps=train_steps,
sagemaker_session=pipeline_session,
)

try:
pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
# Override ParallelismConfiguration in pipeline.start
execution = pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=2))

def validate():
assert len(execution.list_steps()) == 2
for step in execution.list_steps():
assert step["StepStatus"] == "Executing"

retry_with_backoff(validate, num_attempts=4)

wait_pipeline_execution(execution=execution)

finally:
try:
pipeline.delete()
except Exception:
pass


def test_model_registration_with_tuning_model(
pipeline_session,
role,
Expand Down
49 changes: 44 additions & 5 deletions tests/unit/sagemaker/workflow/test_pipeline.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -26,7 +26,6 @@
from sagemaker.workflow.execution_variables import ExecutionVariables
from sagemaker.workflow.parameters import ParameterString
from sagemaker.workflow.pipeline import Pipeline, PipelineGraph
from sagemaker.workflow.parallelism_config import ParallelismConfiguration
from sagemaker.workflow.pipeline_experiment_config import (
PipelineExperimentConfig,
PipelineExperimentConfigProperties,
Expand DownExpand Up@@ -126,10 +125,12 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
name="MyPipeline",
parameters=[],
steps=[],
pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
sagemaker_session=sagemaker_session_mock,
)
pipeline.create(role_arn=role_arn)
pipeline.create(
role_arn=role_arn,
parallelism_config=dict(MaxParallelExecutionSteps=10),
)
assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
PipelineName="MyPipeline",
PipelineDefinition=pipeline.definition(),
Expand All@@ -138,6 +139,42 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
)


def test_pipeline_create_and_start_with_parallelism_config(sagemaker_session_mock, role_arn):
pipeline = Pipeline(
name="MyPipeline",
parameters=[],
steps=[],
sagemaker_session=sagemaker_session_mock,
)
pipeline.create(
role_arn=role_arn,
parallelism_config=dict(MaxParallelExecutionSteps=10),
)
assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
PipelineName="MyPipeline",
PipelineDefinition=pipeline.definition(),
RoleArn=role_arn,
ParallelismConfiguration={"MaxParallelExecutionSteps": 10},
)

sagemaker_session_mock.sagemaker_client.start_pipeline_execution.return_value = dict(
PipelineExecutionArn="pipeline-execution-arn"
)

# No ParallelismConfiguration specified
pipeline.start()
assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.call_args[1] == {
"PipelineName": "MyPipeline"
}

# Specify ParallelismConfiguration to another value which will be honored in backend
pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=20))
assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.called_with(
PipelineName="MyPipeline",
ParallelismConfiguration={"MaxParallelExecutionSteps": 20},
)


@patch("sagemaker.s3.S3Uploader.upload_string_as_file_body")
def test_large_pipeline_create(sagemaker_session_mock, role_arn):
sagemaker_session_mock.sagemaker_config = {}
Expand DownExpand Up@@ -200,10 +237,12 @@ def test_pipeline_update_with_parallelism_config(sagemaker_session_mock, role_ar
name="MyPipeline",
parameters=[],
steps=[],
pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
Comment thread
qidewenwhen marked this conversation as resolved.
sagemaker_session=sagemaker_session_mock,
)
pipeline.create(role_arn=role_arn)
pipeline.create(
role_arn=role_arn,
parallelism_config=dict(MaxParallelExecutionSteps=10),
)
assert sagemaker_session_mock.sagemaker_client.update_pipeline.called_with(
PipelineName="MyPipeline",
PipelineDefinition=pipeline.definition(),
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
fix: pipeline upsert failed to pass parallelism_config to update#4066

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 Merged

knikure
merged 1 commit into

from

Aug 17, 2023
 Merged


fix: pipeline upsert failed to pass parallelism_config to update
#4066
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2 changes: 1 addition & 1 deletion
src/sagemaker/workflow/pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -294,7 +294,7 @@ def upsert(
 if not (error_code == "ValidationException" and "already exists" in error_message):
 raise ce
 # already exists
 response = self.update(role_arn, description)
 response = self.update(role_arn, description, parallelism_config=parallelism_config)
 # add new tags to existing resource
 if tags is not None:
 old_tags = self.sagemaker_session.sagemaker_client.list_tags(
Expand Down

96 changes: 95 additions & 1 deletion
tests/integ/sagemaker/workflow/test_workflow.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -24,6 +24,7 @@

import pandas as pd

from sagemaker.utils import retry_with_backoff
from tests.integ.sagemaker.workflow.helpers import wait_pipeline_execution
from tests.integ.s3_utils import extract_files_from_s3
from sagemaker.workflow.model_step import (
Expand DownExpand Up@@ -1002,7 +1003,7 @@ def test_create_and_update_with_parallelism_config(
 assert response["ParallelismConfiguration"]["MaxParallelExecutionSteps"] == 50

 pipeline.parameters = [ParameterInteger(name="InstanceCount", default_value=1)]
 response = pipeline.update(role, parallelism_config={"MaxParallelExecutionSteps": 55})
 response = pipeline.upsert(role, parallelism_config={"MaxParallelExecutionSteps": 55})
 update_arn = response["PipelineArn"]
 assert re.match(
 rf"arn:aws:sagemaker:{region_name}:\d{{12}}:pipeline/{pipeline_name}",
Expand All@@ -1019,6 +1020,99 @@ def test_create_and_update_with_parallelism_config(
 pass


def test_create_and_start_without_parallelism_config_override(
 pipeline_session, role, pipeline_name, script_dir
):
 sklearn_train = SKLearn(
 framework_version="0.20.0",
 entry_point=os.path.join(script_dir, "train.py"),
 instance_type="ml.m5.xlarge",
 sagemaker_session=pipeline_session,
 role=role,
 )

 train_steps = [
 TrainingStep(
 name=f"my-train-{count}",
 display_name="TrainingStep",
 description="description for Training step",
 step_args=sklearn_train.fit(),
 )
 for count in range(2)
 ]
 pipeline = Pipeline(
 name=pipeline_name,
 steps=train_steps,
 sagemaker_session=pipeline_session,
 )

 try:
 pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
 # No ParallelismConfiguration given in pipeline.start, so it won't override that in pipeline.create
 execution = pipeline.start()

 def validate():
 # Only one step would be scheduled initially
 assert len(execution.list_steps()) == 1
Comment thread
qidewenwhen marked this conversation as resolved.


 retry_with_backoff(validate, num_attempts=4)

 wait_pipeline_execution(execution=execution)

 finally:
 try:
 pipeline.delete()
 except Exception:
 pass


def test_create_and_start_with_parallelism_config_override(
 pipeline_session, role, pipeline_name, script_dir
):
 sklearn_train = SKLearn(
 framework_version="0.20.0",
 entry_point=os.path.join(script_dir, "train.py"),
 instance_type="ml.m5.xlarge",
 sagemaker_session=pipeline_session,
 role=role,
 )

 train_steps = [
 TrainingStep(
 name=f"my-train-{count}",
 display_name="TrainingStep",
 description="description for Training step",
 step_args=sklearn_train.fit(),
 )
 for count in range(2)
 ]
 pipeline = Pipeline(
 name=pipeline_name,
 steps=train_steps,
 sagemaker_session=pipeline_session,
 )

 try:
 pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
 # Override ParallelismConfiguration in pipeline.start
 execution = pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=2))

 def validate():
 assert len(execution.list_steps()) == 2
 for step in execution.list_steps():
 assert step["StepStatus"] == "Executing"

 retry_with_backoff(validate, num_attempts=4)

 wait_pipeline_execution(execution=execution)

 finally:
 try:
 pipeline.delete()
 except Exception:
 pass


def test_model_registration_with_tuning_model(
 pipeline_session,
 role,
Expand Down

49 changes: 44 additions & 5 deletions
tests/unit/sagemaker/workflow/test_pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -26,7 +26,6 @@
from sagemaker.workflow.execution_variables import ExecutionVariables
from sagemaker.workflow.parameters import ParameterString
from sagemaker.workflow.pipeline import Pipeline, PipelineGraph
from sagemaker.workflow.parallelism_config import ParallelismConfiguration
from sagemaker.workflow.pipeline_experiment_config import (
 PipelineExperimentConfig,
 PipelineExperimentConfigProperties,
Expand DownExpand Up@@ -126,10 +125,12 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
 name="MyPipeline",
 parameters=[],
 steps=[],
 pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(role_arn=role_arn)
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
Expand All@@ -138,6 +139,42 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
 )


def test_pipeline_create_and_start_with_parallelism_config(sagemaker_session_mock, role_arn):
 pipeline = Pipeline(
 name="MyPipeline",
 parameters=[],
 steps=[],
 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
 RoleArn=role_arn,
 ParallelismConfiguration={"MaxParallelExecutionSteps": 10},
 )

 sagemaker_session_mock.sagemaker_client.start_pipeline_execution.return_value = dict(
 PipelineExecutionArn="pipeline-execution-arn"
 )

 # No ParallelismConfiguration specified
 pipeline.start()
 assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.call_args[1] == {
 "PipelineName": "MyPipeline"
 }

 # Specify ParallelismConfiguration to another value which will be honored in backend
 pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=20))
 assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.called_with(
 PipelineName="MyPipeline",
 ParallelismConfiguration={"MaxParallelExecutionSteps": 20},
 )


@patch("sagemaker.s3.S3Uploader.upload_string_as_file_body")
def test_large_pipeline_create(sagemaker_session_mock, role_arn):
 sagemaker_session_mock.sagemaker_config = {}
Expand DownExpand Up@@ -200,10 +237,12 @@ def test_pipeline_update_with_parallelism_config(sagemaker_session_mock, role_ar
 name="MyPipeline",
 parameters=[],
 steps=[],
 pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
Comment thread
qidewenwhen marked this conversation as resolved.

 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(role_arn=role_arn)
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.update_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
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('^' + ".*" + '

Skip to content
fix: pipeline upsert failed to pass parallelism_config to update#4066

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Already on GitHub?
Sign in
to your account

 Merged

knikure
merged 1 commit into

from

Aug 17, 2023
 Merged


fix: pipeline upsert failed to pass parallelism_config to update
#4066
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2 changes: 1 addition & 1 deletion
src/sagemaker/workflow/pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -294,7 +294,7 @@ def upsert(
 if not (error_code == "ValidationException" and "already exists" in error_message):
 raise ce
 # already exists
 response = self.update(role_arn, description)
 response = self.update(role_arn, description, parallelism_config=parallelism_config)
 # add new tags to existing resource
 if tags is not None:
 old_tags = self.sagemaker_session.sagemaker_client.list_tags(
Expand Down

96 changes: 95 additions & 1 deletion
tests/integ/sagemaker/workflow/test_workflow.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -24,6 +24,7 @@

import pandas as pd

from sagemaker.utils import retry_with_backoff
from tests.integ.sagemaker.workflow.helpers import wait_pipeline_execution
from tests.integ.s3_utils import extract_files_from_s3
from sagemaker.workflow.model_step import (
Expand DownExpand Up@@ -1002,7 +1003,7 @@ def test_create_and_update_with_parallelism_config(
 assert response["ParallelismConfiguration"]["MaxParallelExecutionSteps"] == 50

 pipeline.parameters = [ParameterInteger(name="InstanceCount", default_value=1)]
 response = pipeline.update(role, parallelism_config={"MaxParallelExecutionSteps": 55})
 response = pipeline.upsert(role, parallelism_config={"MaxParallelExecutionSteps": 55})
 update_arn = response["PipelineArn"]
 assert re.match(
 rf"arn:aws:sagemaker:{region_name}:\d{{12}}:pipeline/{pipeline_name}",
Expand All@@ -1019,6 +1020,99 @@ def test_create_and_update_with_parallelism_config(
 pass


def test_create_and_start_without_parallelism_config_override(
 pipeline_session, role, pipeline_name, script_dir
):
 sklearn_train = SKLearn(
 framework_version="0.20.0",
 entry_point=os.path.join(script_dir, "train.py"),
 instance_type="ml.m5.xlarge",
 sagemaker_session=pipeline_session,
 role=role,
 )

 train_steps = [
 TrainingStep(
 name=f"my-train-{count}",
 display_name="TrainingStep",
 description="description for Training step",
 step_args=sklearn_train.fit(),
 )
 for count in range(2)
 ]
 pipeline = Pipeline(
 name=pipeline_name,
 steps=train_steps,
 sagemaker_session=pipeline_session,
 )

 try:
 pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
 # No ParallelismConfiguration given in pipeline.start, so it won't override that in pipeline.create
 execution = pipeline.start()

 def validate():
 # Only one step would be scheduled initially
 assert len(execution.list_steps()) == 1
Comment thread
qidewenwhen marked this conversation as resolved.


 retry_with_backoff(validate, num_attempts=4)

 wait_pipeline_execution(execution=execution)

 finally:
 try:
 pipeline.delete()
 except Exception:
 pass


def test_create_and_start_with_parallelism_config_override(
 pipeline_session, role, pipeline_name, script_dir
):
 sklearn_train = SKLearn(
 framework_version="0.20.0",
 entry_point=os.path.join(script_dir, "train.py"),
 instance_type="ml.m5.xlarge",
 sagemaker_session=pipeline_session,
 role=role,
 )

 train_steps = [
 TrainingStep(
 name=f"my-train-{count}",
 display_name="TrainingStep",
 description="description for Training step",
 step_args=sklearn_train.fit(),
 )
 for count in range(2)
 ]
 pipeline = Pipeline(
 name=pipeline_name,
 steps=train_steps,
 sagemaker_session=pipeline_session,
 )

 try:
 pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
 # Override ParallelismConfiguration in pipeline.start
 execution = pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=2))

 def validate():
 assert len(execution.list_steps()) == 2
 for step in execution.list_steps():
 assert step["StepStatus"] == "Executing"

 retry_with_backoff(validate, num_attempts=4)

 wait_pipeline_execution(execution=execution)

 finally:
 try:
 pipeline.delete()
 except Exception:
 pass


def test_model_registration_with_tuning_model(
 pipeline_session,
 role,
Expand Down

49 changes: 44 additions & 5 deletions
tests/unit/sagemaker/workflow/test_pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -26,7 +26,6 @@
from sagemaker.workflow.execution_variables import ExecutionVariables
from sagemaker.workflow.parameters import ParameterString
from sagemaker.workflow.pipeline import Pipeline, PipelineGraph
from sagemaker.workflow.parallelism_config import ParallelismConfiguration
from sagemaker.workflow.pipeline_experiment_config import (
 PipelineExperimentConfig,
 PipelineExperimentConfigProperties,
Expand DownExpand Up@@ -126,10 +125,12 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
 name="MyPipeline",
 parameters=[],
 steps=[],
 pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(role_arn=role_arn)
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
Expand All@@ -138,6 +139,42 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
 )


def test_pipeline_create_and_start_with_parallelism_config(sagemaker_session_mock, role_arn):
 pipeline = Pipeline(
 name="MyPipeline",
 parameters=[],
 steps=[],
 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
 RoleArn=role_arn,
 ParallelismConfiguration={"MaxParallelExecutionSteps": 10},
 )

 sagemaker_session_mock.sagemaker_client.start_pipeline_execution.return_value = dict(
 PipelineExecutionArn="pipeline-execution-arn"
 )

 # No ParallelismConfiguration specified
 pipeline.start()
 assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.call_args[1] == {
 "PipelineName": "MyPipeline"
 }

 # Specify ParallelismConfiguration to another value which will be honored in backend
 pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=20))
 assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.called_with(
 PipelineName="MyPipeline",
 ParallelismConfiguration={"MaxParallelExecutionSteps": 20},
 )


@patch("sagemaker.s3.S3Uploader.upload_string_as_file_body")
def test_large_pipeline_create(sagemaker_session_mock, role_arn):
 sagemaker_session_mock.sagemaker_config = {}
Expand DownExpand Up@@ -200,10 +237,12 @@ def test_pipeline_update_with_parallelism_config(sagemaker_session_mock, role_ar
 name="MyPipeline",
 parameters=[],
 steps=[],
 pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
Comment thread
qidewenwhen marked this conversation as resolved.

 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(role_arn=role_arn)
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.update_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
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('^' + ".*" + '

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fix: pipeline upsert failed to pass parallelism_config to update#4066

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knikure
merged 1 commit into

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Aug 17, 2023
 Merged


fix: pipeline upsert failed to pass parallelism_config to update
#4066
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2 changes: 1 addition & 1 deletion
src/sagemaker/workflow/pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -294,7 +294,7 @@ def upsert(
 if not (error_code == "ValidationException" and "already exists" in error_message):
 raise ce
 # already exists
 response = self.update(role_arn, description)
 response = self.update(role_arn, description, parallelism_config=parallelism_config)
 # add new tags to existing resource
 if tags is not None:
 old_tags = self.sagemaker_session.sagemaker_client.list_tags(
Expand Down

96 changes: 95 additions & 1 deletion
tests/integ/sagemaker/workflow/test_workflow.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -24,6 +24,7 @@

import pandas as pd

from sagemaker.utils import retry_with_backoff
from tests.integ.sagemaker.workflow.helpers import wait_pipeline_execution
from tests.integ.s3_utils import extract_files_from_s3
from sagemaker.workflow.model_step import (
Expand DownExpand Up@@ -1002,7 +1003,7 @@ def test_create_and_update_with_parallelism_config(
 assert response["ParallelismConfiguration"]["MaxParallelExecutionSteps"] == 50

 pipeline.parameters = [ParameterInteger(name="InstanceCount", default_value=1)]
 response = pipeline.update(role, parallelism_config={"MaxParallelExecutionSteps": 55})
 response = pipeline.upsert(role, parallelism_config={"MaxParallelExecutionSteps": 55})
 update_arn = response["PipelineArn"]
 assert re.match(
 rf"arn:aws:sagemaker:{region_name}:\d{{12}}:pipeline/{pipeline_name}",
Expand All@@ -1019,6 +1020,99 @@ def test_create_and_update_with_parallelism_config(
 pass


def test_create_and_start_without_parallelism_config_override(
 pipeline_session, role, pipeline_name, script_dir
):
 sklearn_train = SKLearn(
 framework_version="0.20.0",
 entry_point=os.path.join(script_dir, "train.py"),
 instance_type="ml.m5.xlarge",
 sagemaker_session=pipeline_session,
 role=role,
 )

 train_steps = [
 TrainingStep(
 name=f"my-train-{count}",
 display_name="TrainingStep",
 description="description for Training step",
 step_args=sklearn_train.fit(),
 )
 for count in range(2)
 ]
 pipeline = Pipeline(
 name=pipeline_name,
 steps=train_steps,
 sagemaker_session=pipeline_session,
 )

 try:
 pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
 # No ParallelismConfiguration given in pipeline.start, so it won't override that in pipeline.create
 execution = pipeline.start()

 def validate():
 # Only one step would be scheduled initially
 assert len(execution.list_steps()) == 1
Comment thread
qidewenwhen marked this conversation as resolved.


 retry_with_backoff(validate, num_attempts=4)

 wait_pipeline_execution(execution=execution)

 finally:
 try:
 pipeline.delete()
 except Exception:
 pass


def test_create_and_start_with_parallelism_config_override(
 pipeline_session, role, pipeline_name, script_dir
):
 sklearn_train = SKLearn(
 framework_version="0.20.0",
 entry_point=os.path.join(script_dir, "train.py"),
 instance_type="ml.m5.xlarge",
 sagemaker_session=pipeline_session,
 role=role,
 )

 train_steps = [
 TrainingStep(
 name=f"my-train-{count}",
 display_name="TrainingStep",
 description="description for Training step",
 step_args=sklearn_train.fit(),
 )
 for count in range(2)
 ]
 pipeline = Pipeline(
 name=pipeline_name,
 steps=train_steps,
 sagemaker_session=pipeline_session,
 )

 try:
 pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
 # Override ParallelismConfiguration in pipeline.start
 execution = pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=2))

 def validate():
 assert len(execution.list_steps()) == 2
 for step in execution.list_steps():
 assert step["StepStatus"] == "Executing"

 retry_with_backoff(validate, num_attempts=4)

 wait_pipeline_execution(execution=execution)

 finally:
 try:
 pipeline.delete()
 except Exception:
 pass


def test_model_registration_with_tuning_model(
 pipeline_session,
 role,
Expand Down

49 changes: 44 additions & 5 deletions
tests/unit/sagemaker/workflow/test_pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -26,7 +26,6 @@
from sagemaker.workflow.execution_variables import ExecutionVariables
from sagemaker.workflow.parameters import ParameterString
from sagemaker.workflow.pipeline import Pipeline, PipelineGraph
from sagemaker.workflow.parallelism_config import ParallelismConfiguration
from sagemaker.workflow.pipeline_experiment_config import (
 PipelineExperimentConfig,
 PipelineExperimentConfigProperties,
Expand DownExpand Up@@ -126,10 +125,12 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
 name="MyPipeline",
 parameters=[],
 steps=[],
 pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(role_arn=role_arn)
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
Expand All@@ -138,6 +139,42 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
 )


def test_pipeline_create_and_start_with_parallelism_config(sagemaker_session_mock, role_arn):
 pipeline = Pipeline(
 name="MyPipeline",
 parameters=[],
 steps=[],
 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
 RoleArn=role_arn,
 ParallelismConfiguration={"MaxParallelExecutionSteps": 10},
 )

 sagemaker_session_mock.sagemaker_client.start_pipeline_execution.return_value = dict(
 PipelineExecutionArn="pipeline-execution-arn"
 )

 # No ParallelismConfiguration specified
 pipeline.start()
 assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.call_args[1] == {
 "PipelineName": "MyPipeline"
 }

 # Specify ParallelismConfiguration to another value which will be honored in backend
 pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=20))
 assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.called_with(
 PipelineName="MyPipeline",
 ParallelismConfiguration={"MaxParallelExecutionSteps": 20},
 )


@patch("sagemaker.s3.S3Uploader.upload_string_as_file_body")
def test_large_pipeline_create(sagemaker_session_mock, role_arn):
 sagemaker_session_mock.sagemaker_config = {}
Expand DownExpand Up@@ -200,10 +237,12 @@ def test_pipeline_update_with_parallelism_config(sagemaker_session_mock, role_ar
 name="MyPipeline",
 parameters=[],
 steps=[],
 pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
Comment thread
qidewenwhen marked this conversation as resolved.

 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(role_arn=role_arn)
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.update_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
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" + '

Skip to content
fix: pipeline upsert failed to pass parallelism_config to update#4066

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 Merged

knikure
merged 1 commit into

from

Aug 17, 2023
 Merged


fix: pipeline upsert failed to pass parallelism_config to update
#4066
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2 changes: 1 addition & 1 deletion
src/sagemaker/workflow/pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -294,7 +294,7 @@ def upsert(
 if not (error_code == "ValidationException" and "already exists" in error_message):
 raise ce
 # already exists
 response = self.update(role_arn, description)
 response = self.update(role_arn, description, parallelism_config=parallelism_config)
 # add new tags to existing resource
 if tags is not None:
 old_tags = self.sagemaker_session.sagemaker_client.list_tags(
Expand Down

96 changes: 95 additions & 1 deletion
tests/integ/sagemaker/workflow/test_workflow.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -24,6 +24,7 @@

import pandas as pd

from sagemaker.utils import retry_with_backoff
from tests.integ.sagemaker.workflow.helpers import wait_pipeline_execution
from tests.integ.s3_utils import extract_files_from_s3
from sagemaker.workflow.model_step import (
Expand DownExpand Up@@ -1002,7 +1003,7 @@ def test_create_and_update_with_parallelism_config(
 assert response["ParallelismConfiguration"]["MaxParallelExecutionSteps"] == 50

 pipeline.parameters = [ParameterInteger(name="InstanceCount", default_value=1)]
 response = pipeline.update(role, parallelism_config={"MaxParallelExecutionSteps": 55})
 response = pipeline.upsert(role, parallelism_config={"MaxParallelExecutionSteps": 55})
 update_arn = response["PipelineArn"]
 assert re.match(
 rf"arn:aws:sagemaker:{region_name}:\d{{12}}:pipeline/{pipeline_name}",
Expand All@@ -1019,6 +1020,99 @@ def test_create_and_update_with_parallelism_config(
 pass


def test_create_and_start_without_parallelism_config_override(
 pipeline_session, role, pipeline_name, script_dir
):
 sklearn_train = SKLearn(
 framework_version="0.20.0",
 entry_point=os.path.join(script_dir, "train.py"),
 instance_type="ml.m5.xlarge",
 sagemaker_session=pipeline_session,
 role=role,
 )

 train_steps = [
 TrainingStep(
 name=f"my-train-{count}",
 display_name="TrainingStep",
 description="description for Training step",
 step_args=sklearn_train.fit(),
 )
 for count in range(2)
 ]
 pipeline = Pipeline(
 name=pipeline_name,
 steps=train_steps,
 sagemaker_session=pipeline_session,
 )

 try:
 pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
 # No ParallelismConfiguration given in pipeline.start, so it won't override that in pipeline.create
 execution = pipeline.start()

 def validate():
 # Only one step would be scheduled initially
 assert len(execution.list_steps()) == 1
Comment thread
qidewenwhen marked this conversation as resolved.


 retry_with_backoff(validate, num_attempts=4)

 wait_pipeline_execution(execution=execution)

 finally:
 try:
 pipeline.delete()
 except Exception:
 pass


def test_create_and_start_with_parallelism_config_override(
 pipeline_session, role, pipeline_name, script_dir
):
 sklearn_train = SKLearn(
 framework_version="0.20.0",
 entry_point=os.path.join(script_dir, "train.py"),
 instance_type="ml.m5.xlarge",
 sagemaker_session=pipeline_session,
 role=role,
 )

 train_steps = [
 TrainingStep(
 name=f"my-train-{count}",
 display_name="TrainingStep",
 description="description for Training step",
 step_args=sklearn_train.fit(),
 )
 for count in range(2)
 ]
 pipeline = Pipeline(
 name=pipeline_name,
 steps=train_steps,
 sagemaker_session=pipeline_session,
 )

 try:
 pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
 # Override ParallelismConfiguration in pipeline.start
 execution = pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=2))

 def validate():
 assert len(execution.list_steps()) == 2
 for step in execution.list_steps():
 assert step["StepStatus"] == "Executing"

 retry_with_backoff(validate, num_attempts=4)

 wait_pipeline_execution(execution=execution)

 finally:
 try:
 pipeline.delete()
 except Exception:
 pass


def test_model_registration_with_tuning_model(
 pipeline_session,
 role,
Expand Down

49 changes: 44 additions & 5 deletions
tests/unit/sagemaker/workflow/test_pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -26,7 +26,6 @@
from sagemaker.workflow.execution_variables import ExecutionVariables
from sagemaker.workflow.parameters import ParameterString
from sagemaker.workflow.pipeline import Pipeline, PipelineGraph
from sagemaker.workflow.parallelism_config import ParallelismConfiguration
from sagemaker.workflow.pipeline_experiment_config import (
 PipelineExperimentConfig,
 PipelineExperimentConfigProperties,
Expand DownExpand Up@@ -126,10 +125,12 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
 name="MyPipeline",
 parameters=[],
 steps=[],
 pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(role_arn=role_arn)
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
Expand All@@ -138,6 +139,42 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
 )


def test_pipeline_create_and_start_with_parallelism_config(sagemaker_session_mock, role_arn):
 pipeline = Pipeline(
 name="MyPipeline",
 parameters=[],
 steps=[],
 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
 RoleArn=role_arn,
 ParallelismConfiguration={"MaxParallelExecutionSteps": 10},
 )

 sagemaker_session_mock.sagemaker_client.start_pipeline_execution.return_value = dict(
 PipelineExecutionArn="pipeline-execution-arn"
 )

 # No ParallelismConfiguration specified
 pipeline.start()
 assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.call_args[1] == {
 "PipelineName": "MyPipeline"
 }

 # Specify ParallelismConfiguration to another value which will be honored in backend
 pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=20))
 assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.called_with(
 PipelineName="MyPipeline",
 ParallelismConfiguration={"MaxParallelExecutionSteps": 20},
 )


@patch("sagemaker.s3.S3Uploader.upload_string_as_file_body")
def test_large_pipeline_create(sagemaker_session_mock, role_arn):
 sagemaker_session_mock.sagemaker_config = {}
Expand DownExpand Up@@ -200,10 +237,12 @@ def test_pipeline_update_with_parallelism_config(sagemaker_session_mock, role_ar
 name="MyPipeline",
 parameters=[],
 steps=[],
 pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
Comment thread
qidewenwhen marked this conversation as resolved.

 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(role_arn=role_arn)
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.update_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
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: pipeline upsert failed to pass parallelism_config to update#4066

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.

 Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and
privacy statement. We’ll occasionally send you account related emails.

Already on GitHub?
Sign in
to your account

 Merged

knikure
merged 1 commit into

from

Aug 17, 2023
 Merged


fix: pipeline upsert failed to pass parallelism_config to update
#4066
Show file tree
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2 changes: 1 addition & 1 deletion
src/sagemaker/workflow/pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -294,7 +294,7 @@ def upsert(
 if not (error_code == "ValidationException" and "already exists" in error_message):
 raise ce
 # already exists
 response = self.update(role_arn, description)
 response = self.update(role_arn, description, parallelism_config=parallelism_config)
 # add new tags to existing resource
 if tags is not None:
 old_tags = self.sagemaker_session.sagemaker_client.list_tags(
Expand Down

96 changes: 95 additions & 1 deletion
tests/integ/sagemaker/workflow/test_workflow.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -24,6 +24,7 @@

import pandas as pd

from sagemaker.utils import retry_with_backoff
from tests.integ.sagemaker.workflow.helpers import wait_pipeline_execution
from tests.integ.s3_utils import extract_files_from_s3
from sagemaker.workflow.model_step import (
Expand DownExpand Up@@ -1002,7 +1003,7 @@ def test_create_and_update_with_parallelism_config(
 assert response["ParallelismConfiguration"]["MaxParallelExecutionSteps"] == 50

 pipeline.parameters = [ParameterInteger(name="InstanceCount", default_value=1)]
 response = pipeline.update(role, parallelism_config={"MaxParallelExecutionSteps": 55})
 response = pipeline.upsert(role, parallelism_config={"MaxParallelExecutionSteps": 55})
 update_arn = response["PipelineArn"]
 assert re.match(
 rf"arn:aws:sagemaker:{region_name}:\d{{12}}:pipeline/{pipeline_name}",
Expand All@@ -1019,6 +1020,99 @@ def test_create_and_update_with_parallelism_config(
 pass


def test_create_and_start_without_parallelism_config_override(
 pipeline_session, role, pipeline_name, script_dir
):
 sklearn_train = SKLearn(
 framework_version="0.20.0",
 entry_point=os.path.join(script_dir, "train.py"),
 instance_type="ml.m5.xlarge",
 sagemaker_session=pipeline_session,
 role=role,
 )

 train_steps = [
 TrainingStep(
 name=f"my-train-{count}",
 display_name="TrainingStep",
 description="description for Training step",
 step_args=sklearn_train.fit(),
 )
 for count in range(2)
 ]
 pipeline = Pipeline(
 name=pipeline_name,
 steps=train_steps,
 sagemaker_session=pipeline_session,
 )

 try:
 pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
 # No ParallelismConfiguration given in pipeline.start, so it won't override that in pipeline.create
 execution = pipeline.start()

 def validate():
 # Only one step would be scheduled initially
 assert len(execution.list_steps()) == 1
Comment thread
qidewenwhen marked this conversation as resolved.


 retry_with_backoff(validate, num_attempts=4)

 wait_pipeline_execution(execution=execution)

 finally:
 try:
 pipeline.delete()
 except Exception:
 pass


def test_create_and_start_with_parallelism_config_override(
 pipeline_session, role, pipeline_name, script_dir
):
 sklearn_train = SKLearn(
 framework_version="0.20.0",
 entry_point=os.path.join(script_dir, "train.py"),
 instance_type="ml.m5.xlarge",
 sagemaker_session=pipeline_session,
 role=role,
 )

 train_steps = [
 TrainingStep(
 name=f"my-train-{count}",
 display_name="TrainingStep",
 description="description for Training step",
 step_args=sklearn_train.fit(),
 )
 for count in range(2)
 ]
 pipeline = Pipeline(
 name=pipeline_name,
 steps=train_steps,
 sagemaker_session=pipeline_session,
 )

 try:
 pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
 # Override ParallelismConfiguration in pipeline.start
 execution = pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=2))

 def validate():
 assert len(execution.list_steps()) == 2
 for step in execution.list_steps():
 assert step["StepStatus"] == "Executing"

 retry_with_backoff(validate, num_attempts=4)

 wait_pipeline_execution(execution=execution)

 finally:
 try:
 pipeline.delete()
 except Exception:
 pass


def test_model_registration_with_tuning_model(
 pipeline_session,
 role,
Expand Down

49 changes: 44 additions & 5 deletions
tests/unit/sagemaker/workflow/test_pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -26,7 +26,6 @@
from sagemaker.workflow.execution_variables import ExecutionVariables
from sagemaker.workflow.parameters import ParameterString
from sagemaker.workflow.pipeline import Pipeline, PipelineGraph
from sagemaker.workflow.parallelism_config import ParallelismConfiguration
from sagemaker.workflow.pipeline_experiment_config import (
 PipelineExperimentConfig,
 PipelineExperimentConfigProperties,
Expand DownExpand Up@@ -126,10 +125,12 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
 name="MyPipeline",
 parameters=[],
 steps=[],
 pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(role_arn=role_arn)
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
Expand All@@ -138,6 +139,42 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
 )


def test_pipeline_create_and_start_with_parallelism_config(sagemaker_session_mock, role_arn):
 pipeline = Pipeline(
 name="MyPipeline",
 parameters=[],
 steps=[],
 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
 RoleArn=role_arn,
 ParallelismConfiguration={"MaxParallelExecutionSteps": 10},
 )

 sagemaker_session_mock.sagemaker_client.start_pipeline_execution.return_value = dict(
 PipelineExecutionArn="pipeline-execution-arn"
 )

 # No ParallelismConfiguration specified
 pipeline.start()
 assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.call_args[1] == {
 "PipelineName": "MyPipeline"
 }

 # Specify ParallelismConfiguration to another value which will be honored in backend
 pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=20))
 assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.called_with(
 PipelineName="MyPipeline",
 ParallelismConfiguration={"MaxParallelExecutionSteps": 20},
 )


@patch("sagemaker.s3.S3Uploader.upload_string_as_file_body")
def test_large_pipeline_create(sagemaker_session_mock, role_arn):
 sagemaker_session_mock.sagemaker_config = {}
Expand DownExpand Up@@ -200,10 +237,12 @@ def test_pipeline_update_with_parallelism_config(sagemaker_session_mock, role_ar
 name="MyPipeline",
 parameters=[],
 steps=[],
 pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
Comment thread
qidewenwhen marked this conversation as resolved.

 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(role_arn=role_arn)
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.update_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
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: pipeline upsert failed to pass parallelism_config to update#4066

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knikure
merged 1 commit into

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Aug 17, 2023
 Merged


fix: pipeline upsert failed to pass parallelism_config to update
#4066
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2 changes: 1 addition & 1 deletion
src/sagemaker/workflow/pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -294,7 +294,7 @@ def upsert(
 if not (error_code == "ValidationException" and "already exists" in error_message):
 raise ce
 # already exists
 response = self.update(role_arn, description)
 response = self.update(role_arn, description, parallelism_config=parallelism_config)
 # add new tags to existing resource
 if tags is not None:
 old_tags = self.sagemaker_session.sagemaker_client.list_tags(
Expand Down

96 changes: 95 additions & 1 deletion
tests/integ/sagemaker/workflow/test_workflow.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -24,6 +24,7 @@

import pandas as pd

from sagemaker.utils import retry_with_backoff
from tests.integ.sagemaker.workflow.helpers import wait_pipeline_execution
from tests.integ.s3_utils import extract_files_from_s3
from sagemaker.workflow.model_step import (
Expand DownExpand Up@@ -1002,7 +1003,7 @@ def test_create_and_update_with_parallelism_config(
 assert response["ParallelismConfiguration"]["MaxParallelExecutionSteps"] == 50

 pipeline.parameters = [ParameterInteger(name="InstanceCount", default_value=1)]
 response = pipeline.update(role, parallelism_config={"MaxParallelExecutionSteps": 55})
 response = pipeline.upsert(role, parallelism_config={"MaxParallelExecutionSteps": 55})
 update_arn = response["PipelineArn"]
 assert re.match(
 rf"arn:aws:sagemaker:{region_name}:\d{{12}}:pipeline/{pipeline_name}",
Expand All@@ -1019,6 +1020,99 @@ def test_create_and_update_with_parallelism_config(
 pass


def test_create_and_start_without_parallelism_config_override(
 pipeline_session, role, pipeline_name, script_dir
):
 sklearn_train = SKLearn(
 framework_version="0.20.0",
 entry_point=os.path.join(script_dir, "train.py"),
 instance_type="ml.m5.xlarge",
 sagemaker_session=pipeline_session,
 role=role,
 )

 train_steps = [
 TrainingStep(
 name=f"my-train-{count}",
 display_name="TrainingStep",
 description="description for Training step",
 step_args=sklearn_train.fit(),
 )
 for count in range(2)
 ]
 pipeline = Pipeline(
 name=pipeline_name,
 steps=train_steps,
 sagemaker_session=pipeline_session,
 )

 try:
 pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
 # No ParallelismConfiguration given in pipeline.start, so it won't override that in pipeline.create
 execution = pipeline.start()

 def validate():
 # Only one step would be scheduled initially
 assert len(execution.list_steps()) == 1
Comment thread
qidewenwhen marked this conversation as resolved.


 retry_with_backoff(validate, num_attempts=4)

 wait_pipeline_execution(execution=execution)

 finally:
 try:
 pipeline.delete()
 except Exception:
 pass


def test_create_and_start_with_parallelism_config_override(
 pipeline_session, role, pipeline_name, script_dir
):
 sklearn_train = SKLearn(
 framework_version="0.20.0",
 entry_point=os.path.join(script_dir, "train.py"),
 instance_type="ml.m5.xlarge",
 sagemaker_session=pipeline_session,
 role=role,
 )

 train_steps = [
 TrainingStep(
 name=f"my-train-{count}",
 display_name="TrainingStep",
 description="description for Training step",
 step_args=sklearn_train.fit(),
 )
 for count in range(2)
 ]
 pipeline = Pipeline(
 name=pipeline_name,
 steps=train_steps,
 sagemaker_session=pipeline_session,
 )

 try:
 pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
 # Override ParallelismConfiguration in pipeline.start
 execution = pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=2))

 def validate():
 assert len(execution.list_steps()) == 2
 for step in execution.list_steps():
 assert step["StepStatus"] == "Executing"

 retry_with_backoff(validate, num_attempts=4)

 wait_pipeline_execution(execution=execution)

 finally:
 try:
 pipeline.delete()
 except Exception:
 pass


def test_model_registration_with_tuning_model(
 pipeline_session,
 role,
Expand Down

49 changes: 44 additions & 5 deletions
tests/unit/sagemaker/workflow/test_pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -26,7 +26,6 @@
from sagemaker.workflow.execution_variables import ExecutionVariables
from sagemaker.workflow.parameters import ParameterString
from sagemaker.workflow.pipeline import Pipeline, PipelineGraph
from sagemaker.workflow.parallelism_config import ParallelismConfiguration
from sagemaker.workflow.pipeline_experiment_config import (
 PipelineExperimentConfig,
 PipelineExperimentConfigProperties,
Expand DownExpand Up@@ -126,10 +125,12 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
 name="MyPipeline",
 parameters=[],
 steps=[],
 pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(role_arn=role_arn)
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
Expand All@@ -138,6 +139,42 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
 )


def test_pipeline_create_and_start_with_parallelism_config(sagemaker_session_mock, role_arn):
 pipeline = Pipeline(
 name="MyPipeline",
 parameters=[],
 steps=[],
 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
 RoleArn=role_arn,
 ParallelismConfiguration={"MaxParallelExecutionSteps": 10},
 )

 sagemaker_session_mock.sagemaker_client.start_pipeline_execution.return_value = dict(
 PipelineExecutionArn="pipeline-execution-arn"
 )

 # No ParallelismConfiguration specified
 pipeline.start()
 assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.call_args[1] == {
 "PipelineName": "MyPipeline"
 }

 # Specify ParallelismConfiguration to another value which will be honored in backend
 pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=20))
 assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.called_with(
 PipelineName="MyPipeline",
 ParallelismConfiguration={"MaxParallelExecutionSteps": 20},
 )


@patch("sagemaker.s3.S3Uploader.upload_string_as_file_body")
def test_large_pipeline_create(sagemaker_session_mock, role_arn):
 sagemaker_session_mock.sagemaker_config = {}
Expand DownExpand Up@@ -200,10 +237,12 @@ def test_pipeline_update_with_parallelism_config(sagemaker_session_mock, role_ar
 name="MyPipeline",
 parameters=[],
 steps=[],
 pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
Comment thread
qidewenwhen marked this conversation as resolved.

 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(role_arn=role_arn)
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.update_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
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); }
})();
})();

Skip to content
fix: pipeline upsert failed to pass parallelism_config to update#4066

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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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Sign in
to your account

 Merged

knikure
merged 1 commit into

from

Aug 17, 2023
 Merged


fix: pipeline upsert failed to pass parallelism_config to update
#4066
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2 changes: 1 addition & 1 deletion
src/sagemaker/workflow/pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -294,7 +294,7 @@ def upsert(
 if not (error_code == "ValidationException" and "already exists" in error_message):
 raise ce
 # already exists
 response = self.update(role_arn, description)
 response = self.update(role_arn, description, parallelism_config=parallelism_config)
 # add new tags to existing resource
 if tags is not None:
 old_tags = self.sagemaker_session.sagemaker_client.list_tags(
Expand Down

96 changes: 95 additions & 1 deletion
tests/integ/sagemaker/workflow/test_workflow.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -24,6 +24,7 @@

import pandas as pd

from sagemaker.utils import retry_with_backoff
from tests.integ.sagemaker.workflow.helpers import wait_pipeline_execution
from tests.integ.s3_utils import extract_files_from_s3
from sagemaker.workflow.model_step import (
Expand DownExpand Up@@ -1002,7 +1003,7 @@ def test_create_and_update_with_parallelism_config(
 assert response["ParallelismConfiguration"]["MaxParallelExecutionSteps"] == 50

 pipeline.parameters = [ParameterInteger(name="InstanceCount", default_value=1)]
 response = pipeline.update(role, parallelism_config={"MaxParallelExecutionSteps": 55})
 response = pipeline.upsert(role, parallelism_config={"MaxParallelExecutionSteps": 55})
 update_arn = response["PipelineArn"]
 assert re.match(
 rf"arn:aws:sagemaker:{region_name}:\d{{12}}:pipeline/{pipeline_name}",
Expand All@@ -1019,6 +1020,99 @@ def test_create_and_update_with_parallelism_config(
 pass


def test_create_and_start_without_parallelism_config_override(
 pipeline_session, role, pipeline_name, script_dir
):
 sklearn_train = SKLearn(
 framework_version="0.20.0",
 entry_point=os.path.join(script_dir, "train.py"),
 instance_type="ml.m5.xlarge",
 sagemaker_session=pipeline_session,
 role=role,
 )

 train_steps = [
 TrainingStep(
 name=f"my-train-{count}",
 display_name="TrainingStep",
 description="description for Training step",
 step_args=sklearn_train.fit(),
 )
 for count in range(2)
 ]
 pipeline = Pipeline(
 name=pipeline_name,
 steps=train_steps,
 sagemaker_session=pipeline_session,
 )

 try:
 pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
 # No ParallelismConfiguration given in pipeline.start, so it won't override that in pipeline.create
 execution = pipeline.start()

 def validate():
 # Only one step would be scheduled initially
 assert len(execution.list_steps()) == 1
Comment thread
qidewenwhen marked this conversation as resolved.


 retry_with_backoff(validate, num_attempts=4)

 wait_pipeline_execution(execution=execution)

 finally:
 try:
 pipeline.delete()
 except Exception:
 pass


def test_create_and_start_with_parallelism_config_override(
 pipeline_session, role, pipeline_name, script_dir
):
 sklearn_train = SKLearn(
 framework_version="0.20.0",
 entry_point=os.path.join(script_dir, "train.py"),
 instance_type="ml.m5.xlarge",
 sagemaker_session=pipeline_session,
 role=role,
 )

 train_steps = [
 TrainingStep(
 name=f"my-train-{count}",
 display_name="TrainingStep",
 description="description for Training step",
 step_args=sklearn_train.fit(),
 )
 for count in range(2)
 ]
 pipeline = Pipeline(
 name=pipeline_name,
 steps=train_steps,
 sagemaker_session=pipeline_session,
 )

 try:
 pipeline.create(role, parallelism_config=dict(MaxParallelExecutionSteps=1))
 # Override ParallelismConfiguration in pipeline.start
 execution = pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=2))

 def validate():
 assert len(execution.list_steps()) == 2
 for step in execution.list_steps():
 assert step["StepStatus"] == "Executing"

 retry_with_backoff(validate, num_attempts=4)

 wait_pipeline_execution(execution=execution)

 finally:
 try:
 pipeline.delete()
 except Exception:
 pass


def test_model_registration_with_tuning_model(
 pipeline_session,
 role,
Expand Down

49 changes: 44 additions & 5 deletions
tests/unit/sagemaker/workflow/test_pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -26,7 +26,6 @@
from sagemaker.workflow.execution_variables import ExecutionVariables
from sagemaker.workflow.parameters import ParameterString
from sagemaker.workflow.pipeline import Pipeline, PipelineGraph
from sagemaker.workflow.parallelism_config import ParallelismConfiguration
from sagemaker.workflow.pipeline_experiment_config import (
 PipelineExperimentConfig,
 PipelineExperimentConfigProperties,
Expand DownExpand Up@@ -126,10 +125,12 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
 name="MyPipeline",
 parameters=[],
 steps=[],
 pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(role_arn=role_arn)
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
Expand All@@ -138,6 +139,42 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar
 )


def test_pipeline_create_and_start_with_parallelism_config(sagemaker_session_mock, role_arn):
 pipeline = Pipeline(
 name="MyPipeline",
 parameters=[],
 steps=[],
 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
 RoleArn=role_arn,
 ParallelismConfiguration={"MaxParallelExecutionSteps": 10},
 )

 sagemaker_session_mock.sagemaker_client.start_pipeline_execution.return_value = dict(
 PipelineExecutionArn="pipeline-execution-arn"
 )

 # No ParallelismConfiguration specified
 pipeline.start()
 assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.call_args[1] == {
 "PipelineName": "MyPipeline"
 }

 # Specify ParallelismConfiguration to another value which will be honored in backend
 pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=20))
 assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.called_with(
 PipelineName="MyPipeline",
 ParallelismConfiguration={"MaxParallelExecutionSteps": 20},
 )


@patch("sagemaker.s3.S3Uploader.upload_string_as_file_body")
def test_large_pipeline_create(sagemaker_session_mock, role_arn):
 sagemaker_session_mock.sagemaker_config = {}
Expand DownExpand Up@@ -200,10 +237,12 @@ def test_pipeline_update_with_parallelism_config(sagemaker_session_mock, role_ar
 name="MyPipeline",
 parameters=[],
 steps=[],
 pipeline_experiment_config=ParallelismConfiguration(max_parallel_execution_steps=10),
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 sagemaker_session=sagemaker_session_mock,
 )
 pipeline.create(role_arn=role_arn)
 pipeline.create(
 role_arn=role_arn,
 parallelism_config=dict(MaxParallelExecutionSteps=10),
 )
 assert sagemaker_session_mock.sagemaker_client.update_pipeline.called_with(
 PipelineName="MyPipeline",
 PipelineDefinition=pipeline.definition(),
Expand Down