fix: Support using PipelineDefinitionConfig in local mode#4352

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
Jan 24, 2024
Merged

fix: Support using PipelineDefinitionConfig in local mode #4352

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
12 changes: 9 additions & 3 deletions src/sagemaker/local/pipeline.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -273,8 +273,10 @@ class _TrainingStepExecutor(_StepExecutor):
"""Executor class to execute TrainingStep locally"""

def execute(self):
job_name = unique_name_from_base(self.step.name)
step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
job_name = step_arguments.pop("TrainingJobName", None) or unique_name_from_base(
Comment thread
qidewenwhen marked this conversation as resolved.
self.step.name
)
try:
self.pipline_executor.local_sagemaker_client.create_training_job(
job_name, **step_arguments
Expand All@@ -290,8 +292,10 @@ class _ProcessingStepExecutor(_StepExecutor):
"""Executor class to execute ProcessingStep locally"""

def execute(self):
job_name = unique_name_from_base(self.step.name)
step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
job_name = step_arguments.pop("ProcessingJobName", None) or unique_name_from_base(
self.step.name
)
try:
self.pipline_executor.local_sagemaker_client.create_processing_job(
job_name, **step_arguments
Expand DownExpand Up@@ -482,8 +486,10 @@ class _TransformStepExecutor(_StepExecutor):
"""Executor class to execute TransformStep locally"""

def execute(self):
job_name = unique_name_from_base(self.step.name)
step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
job_name = step_arguments.pop("TransformJobName", None) or unique_name_from_base(
self.step.name
)
try:
self.pipline_executor.local_sagemaker_client.create_transform_job(
job_name, **step_arguments
Expand Down
95 changes: 93 additions & 2 deletions tests/unit/sagemaker/local/test_local_pipeline.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@
from sagemaker.workflow.parameters import ParameterInteger, ParameterString
from sagemaker.workflow.pipeline import Pipeline
from sagemaker.workflow.pipeline_context import PipelineSession
from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
from sagemaker.workflow.step_outputs import get_step
from sagemaker.workflow.steps import (
ProcessingStep,
Expand DownExpand Up@@ -111,6 +112,7 @@
"Result": [1, 2, 3], "Exception": null
}
"""
TEST_JOB_NAME = "test-job-name"


@pytest.fixture
Expand DownExpand Up@@ -188,6 +190,8 @@ def training_step(pipeline_session):
sagemaker_session=pipeline_session,
output_path="s3://a/b",
use_spot_instances=False,
# base_job_name would be popped out if no pipeline_definition_config configured
base_job_name=TEST_JOB_NAME,
)
training_input = TrainingInput(s3_data=f"s3://{BUCKET}/train_manifest")
step_args = estimator.fit(inputs=training_input)
Expand All@@ -207,6 +211,8 @@ def processing_step(pipeline_session):
instance_count=1,
instance_type=INSTANCE_TYPE,
sagemaker_session=pipeline_session,
# base_job_name would be popped out if no pipeline_definition_config configured
base_job_name=TEST_JOB_NAME,
)
processing_input = [
ProcessingInput(
Expand DownExpand Up@@ -239,6 +245,8 @@ def transform_step(pipeline_session):
instance_count=1,
output_path="s3://my-bucket/my-output-path",
sagemaker_session=pipeline_session,
# base_transform_job_name would be popped out if no pipeline_definition_config configured
base_transform_job_name=TEST_JOB_NAME,
)
transform_inputs = TransformInput(data="s3://my-bucket/my-data")
step_args = transformer.transform(
Expand DownExpand Up@@ -871,8 +879,8 @@ def depends_step():
)


@patch("sagemaker.local.image._SageMakerContainer.process")
def test_execute_pipeline_processing_step(process, local_sagemaker_session, processing_step):
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_execute_pipeline_processing_step(local_sagemaker_session, processing_step):
pipeline = Pipeline(
name="MyPipeline2",
steps=[processing_step],
Expand DownExpand Up@@ -1362,3 +1370,86 @@ def test_execute_pipeline_step_create_transform_job_fail(
step_execution = execution.step_execution
assert step_execution[transform_step.name].status == _LocalExecutionStatus.FAILED.value
assert "Dummy RuntimeError" in step_execution[transform_step.name].failure_reason


@patch(
"sagemaker.local.image._SageMakerContainer.train",
MagicMock(return_value="/some/path/to/model"),
)
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_pipeline_definition_config_in_local_mode_for_train_process_steps(
processing_step,
training_step,
local_sagemaker_session,
):
exe_steps = [processing_step, training_step]

def _verify_execution(exe_step_name, execution, with_custom_job_prefix):
assert not execution.failure_reason
assert execution.status == _LocalExecutionStatus.SUCCEEDED.value

step_execution = execution.step_execution[exe_step_name]
assert step_execution.status == _LocalExecutionStatus.SUCCEEDED.value

if step_execution.type == StepTypeEnum.PROCESSING:
job_name_field = "ProcessingJobName"
elif step_execution.type == StepTypeEnum.TRAINING:
job_name_field = "TrainingJobName"

if with_custom_job_prefix:
assert step_execution.properties[job_name_field] == TEST_JOB_NAME
else:
assert step_execution.properties[job_name_field].startswith(step_execution.name)

for exe_step in exe_steps:
pipeline = Pipeline(
name="MyPipelineX-" + exe_step.name,
steps=[exe_step],
sagemaker_session=local_sagemaker_session,
parameters=[INSTANCE_COUNT_PIPELINE_PARAMETER],
)

execution = LocalPipelineExecutor(
_LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
local_sagemaker_session,
).execute()

_verify_execution(
exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=False
)

pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)
execution = LocalPipelineExecutor(
_LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
local_sagemaker_session,
).execute()

_verify_execution(
exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=True
)


@patch("sagemaker.local.local_session.LocalSagemakerClient.create_transform_job")
def test_pipeline_definition_config_in_local_mode_for_transform_step(
create_transform_job, local_sagemaker_session, transform_step
):
pipeline = Pipeline(
name="MyPipelineX-" + transform_step.name,
steps=[transform_step],
sagemaker_session=local_sagemaker_session,
)
LocalPipelineExecutor(
_LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
local_sagemaker_session,
).execute()

assert create_transform_job.call_args.args[0].startswith(transform_step.name)

pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)

LocalPipelineExecutor(
_LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
local_sagemaker_session,
).execute()

assert create_transform_job.call_args.args[0] == TEST_JOB_NAME
, '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: Support using PipelineDefinitionConfig in local mode#4352

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

Jan 24, 2024
 Merged


fix: Support using PipelineDefinitionConfig in local mode
#4352
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

Jump to file


Failed to load files. 
Loading
 Diff view

 Diff view


12 changes: 9 additions & 3 deletions
src/sagemaker/local/pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -273,8 +273,10 @@ class _TrainingStepExecutor(_StepExecutor):
 """Executor class to execute TrainingStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("TrainingJobName", None) or unique_name_from_base(
Comment thread
qidewenwhen marked this conversation as resolved.

 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_training_job(
 job_name, **step_arguments
Expand All@@ -290,8 +292,10 @@ class _ProcessingStepExecutor(_StepExecutor):
 """Executor class to execute ProcessingStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("ProcessingJobName", None) or unique_name_from_base(
 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_processing_job(
 job_name, **step_arguments
Expand DownExpand Up@@ -482,8 +486,10 @@ class _TransformStepExecutor(_StepExecutor):
 """Executor class to execute TransformStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("TransformJobName", None) or unique_name_from_base(
 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_transform_job(
 job_name, **step_arguments
Expand Down

95 changes: 93 additions & 2 deletions
tests/unit/sagemaker/local/test_local_pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@
from sagemaker.workflow.parameters import ParameterInteger, ParameterString
from sagemaker.workflow.pipeline import Pipeline
from sagemaker.workflow.pipeline_context import PipelineSession
from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
from sagemaker.workflow.step_outputs import get_step
from sagemaker.workflow.steps import (
 ProcessingStep,
Expand DownExpand Up@@ -111,6 +112,7 @@
 "Result": [1, 2, 3], "Exception": null
}
"""
TEST_JOB_NAME = "test-job-name"


@pytest.fixture
Expand DownExpand Up@@ -188,6 +190,8 @@ def training_step(pipeline_session):
 sagemaker_session=pipeline_session,
 output_path="s3://a/b",
 use_spot_instances=False,
 # base_job_name would be popped out if no pipeline_definition_config configured
 base_job_name=TEST_JOB_NAME,
 )
 training_input = TrainingInput(s3_data=f"s3://{BUCKET}/train_manifest")
 step_args = estimator.fit(inputs=training_input)
Expand All@@ -207,6 +211,8 @@ def processing_step(pipeline_session):
 instance_count=1,
 instance_type=INSTANCE_TYPE,
 sagemaker_session=pipeline_session,
 # base_job_name would be popped out if no pipeline_definition_config configured
 base_job_name=TEST_JOB_NAME,
 )
 processing_input = [
 ProcessingInput(
Expand DownExpand Up@@ -239,6 +245,8 @@ def transform_step(pipeline_session):
 instance_count=1,
 output_path="s3://my-bucket/my-output-path",
 sagemaker_session=pipeline_session,
 # base_transform_job_name would be popped out if no pipeline_definition_config configured
 base_transform_job_name=TEST_JOB_NAME,
 )
 transform_inputs = TransformInput(data="s3://my-bucket/my-data")
 step_args = transformer.transform(
Expand DownExpand Up@@ -871,8 +879,8 @@ def depends_step():
 )


@patch("sagemaker.local.image._SageMakerContainer.process")
def test_execute_pipeline_processing_step(process, local_sagemaker_session, processing_step):
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_execute_pipeline_processing_step(local_sagemaker_session, processing_step):
 pipeline = Pipeline(
 name="MyPipeline2",
 steps=[processing_step],
Expand DownExpand Up@@ -1362,3 +1370,86 @@ def test_execute_pipeline_step_create_transform_job_fail(
 step_execution = execution.step_execution
 assert step_execution[transform_step.name].status == _LocalExecutionStatus.FAILED.value
 assert "Dummy RuntimeError" in step_execution[transform_step.name].failure_reason


@patch(
 "sagemaker.local.image._SageMakerContainer.train",
 MagicMock(return_value="/some/path/to/model"),
)
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_pipeline_definition_config_in_local_mode_for_train_process_steps(
 processing_step,
 training_step,
 local_sagemaker_session,
):
 exe_steps = [processing_step, training_step]

 def _verify_execution(exe_step_name, execution, with_custom_job_prefix):
 assert not execution.failure_reason
 assert execution.status == _LocalExecutionStatus.SUCCEEDED.value

 step_execution = execution.step_execution[exe_step_name]
 assert step_execution.status == _LocalExecutionStatus.SUCCEEDED.value

 if step_execution.type == StepTypeEnum.PROCESSING:
 job_name_field = "ProcessingJobName"
 elif step_execution.type == StepTypeEnum.TRAINING:
 job_name_field = "TrainingJobName"

 if with_custom_job_prefix:
 assert step_execution.properties[job_name_field] == TEST_JOB_NAME
 else:
 assert step_execution.properties[job_name_field].startswith(step_execution.name)

 for exe_step in exe_steps:
 pipeline = Pipeline(
 name="MyPipelineX-" + exe_step.name,
 steps=[exe_step],
 sagemaker_session=local_sagemaker_session,
 parameters=[INSTANCE_COUNT_PIPELINE_PARAMETER],
 )

 execution = LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 _verify_execution(
 exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=False
 )

 pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)
 execution = LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 _verify_execution(
 exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=True
 )


@patch("sagemaker.local.local_session.LocalSagemakerClient.create_transform_job")
def test_pipeline_definition_config_in_local_mode_for_transform_step(
 create_transform_job, local_sagemaker_session, transform_step
):
 pipeline = Pipeline(
 name="MyPipelineX-" + transform_step.name,
 steps=[transform_step],
 sagemaker_session=local_sagemaker_session,
 )
 LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 assert create_transform_job.call_args.args[0].startswith(transform_step.name)

 pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)

 LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 assert create_transform_job.call_args.args[0] == TEST_JOB_NAME

, '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: Support using PipelineDefinitionConfig in local mode#4352

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

Jan 24, 2024
 Merged


fix: Support using PipelineDefinitionConfig in local mode
#4352
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

Jump to file


Failed to load files. 
Loading
 Diff view

 Diff view


12 changes: 9 additions & 3 deletions
src/sagemaker/local/pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -273,8 +273,10 @@ class _TrainingStepExecutor(_StepExecutor):
 """Executor class to execute TrainingStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("TrainingJobName", None) or unique_name_from_base(
Comment thread
qidewenwhen marked this conversation as resolved.

 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_training_job(
 job_name, **step_arguments
Expand All@@ -290,8 +292,10 @@ class _ProcessingStepExecutor(_StepExecutor):
 """Executor class to execute ProcessingStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("ProcessingJobName", None) or unique_name_from_base(
 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_processing_job(
 job_name, **step_arguments
Expand DownExpand Up@@ -482,8 +486,10 @@ class _TransformStepExecutor(_StepExecutor):
 """Executor class to execute TransformStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("TransformJobName", None) or unique_name_from_base(
 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_transform_job(
 job_name, **step_arguments
Expand Down

95 changes: 93 additions & 2 deletions
tests/unit/sagemaker/local/test_local_pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@
from sagemaker.workflow.parameters import ParameterInteger, ParameterString
from sagemaker.workflow.pipeline import Pipeline
from sagemaker.workflow.pipeline_context import PipelineSession
from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
from sagemaker.workflow.step_outputs import get_step
from sagemaker.workflow.steps import (
 ProcessingStep,
Expand DownExpand Up@@ -111,6 +112,7 @@
 "Result": [1, 2, 3], "Exception": null
}
"""
TEST_JOB_NAME = "test-job-name"


@pytest.fixture
Expand DownExpand Up@@ -188,6 +190,8 @@ def training_step(pipeline_session):
 sagemaker_session=pipeline_session,
 output_path="s3://a/b",
 use_spot_instances=False,
 # base_job_name would be popped out if no pipeline_definition_config configured
 base_job_name=TEST_JOB_NAME,
 )
 training_input = TrainingInput(s3_data=f"s3://{BUCKET}/train_manifest")
 step_args = estimator.fit(inputs=training_input)
Expand All@@ -207,6 +211,8 @@ def processing_step(pipeline_session):
 instance_count=1,
 instance_type=INSTANCE_TYPE,
 sagemaker_session=pipeline_session,
 # base_job_name would be popped out if no pipeline_definition_config configured
 base_job_name=TEST_JOB_NAME,
 )
 processing_input = [
 ProcessingInput(
Expand DownExpand Up@@ -239,6 +245,8 @@ def transform_step(pipeline_session):
 instance_count=1,
 output_path="s3://my-bucket/my-output-path",
 sagemaker_session=pipeline_session,
 # base_transform_job_name would be popped out if no pipeline_definition_config configured
 base_transform_job_name=TEST_JOB_NAME,
 )
 transform_inputs = TransformInput(data="s3://my-bucket/my-data")
 step_args = transformer.transform(
Expand DownExpand Up@@ -871,8 +879,8 @@ def depends_step():
 )


@patch("sagemaker.local.image._SageMakerContainer.process")
def test_execute_pipeline_processing_step(process, local_sagemaker_session, processing_step):
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_execute_pipeline_processing_step(local_sagemaker_session, processing_step):
 pipeline = Pipeline(
 name="MyPipeline2",
 steps=[processing_step],
Expand DownExpand Up@@ -1362,3 +1370,86 @@ def test_execute_pipeline_step_create_transform_job_fail(
 step_execution = execution.step_execution
 assert step_execution[transform_step.name].status == _LocalExecutionStatus.FAILED.value
 assert "Dummy RuntimeError" in step_execution[transform_step.name].failure_reason


@patch(
 "sagemaker.local.image._SageMakerContainer.train",
 MagicMock(return_value="/some/path/to/model"),
)
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_pipeline_definition_config_in_local_mode_for_train_process_steps(
 processing_step,
 training_step,
 local_sagemaker_session,
):
 exe_steps = [processing_step, training_step]

 def _verify_execution(exe_step_name, execution, with_custom_job_prefix):
 assert not execution.failure_reason
 assert execution.status == _LocalExecutionStatus.SUCCEEDED.value

 step_execution = execution.step_execution[exe_step_name]
 assert step_execution.status == _LocalExecutionStatus.SUCCEEDED.value

 if step_execution.type == StepTypeEnum.PROCESSING:
 job_name_field = "ProcessingJobName"
 elif step_execution.type == StepTypeEnum.TRAINING:
 job_name_field = "TrainingJobName"

 if with_custom_job_prefix:
 assert step_execution.properties[job_name_field] == TEST_JOB_NAME
 else:
 assert step_execution.properties[job_name_field].startswith(step_execution.name)

 for exe_step in exe_steps:
 pipeline = Pipeline(
 name="MyPipelineX-" + exe_step.name,
 steps=[exe_step],
 sagemaker_session=local_sagemaker_session,
 parameters=[INSTANCE_COUNT_PIPELINE_PARAMETER],
 )

 execution = LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 _verify_execution(
 exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=False
 )

 pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)
 execution = LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 _verify_execution(
 exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=True
 )


@patch("sagemaker.local.local_session.LocalSagemakerClient.create_transform_job")
def test_pipeline_definition_config_in_local_mode_for_transform_step(
 create_transform_job, local_sagemaker_session, transform_step
):
 pipeline = Pipeline(
 name="MyPipelineX-" + transform_step.name,
 steps=[transform_step],
 sagemaker_session=local_sagemaker_session,
 )
 LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 assert create_transform_job.call_args.args[0].startswith(transform_step.name)

 pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)

 LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 assert create_transform_job.call_args.args[0] == TEST_JOB_NAME

, '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: Support using PipelineDefinitionConfig in local mode#4352

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

Jan 24, 2024
 Merged


fix: Support using PipelineDefinitionConfig in local mode
#4352
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

Jump to file


Failed to load files. 
Loading
 Diff view

 Diff view


12 changes: 9 additions & 3 deletions
src/sagemaker/local/pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -273,8 +273,10 @@ class _TrainingStepExecutor(_StepExecutor):
 """Executor class to execute TrainingStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("TrainingJobName", None) or unique_name_from_base(
Comment thread
qidewenwhen marked this conversation as resolved.

 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_training_job(
 job_name, **step_arguments
Expand All@@ -290,8 +292,10 @@ class _ProcessingStepExecutor(_StepExecutor):
 """Executor class to execute ProcessingStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("ProcessingJobName", None) or unique_name_from_base(
 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_processing_job(
 job_name, **step_arguments
Expand DownExpand Up@@ -482,8 +486,10 @@ class _TransformStepExecutor(_StepExecutor):
 """Executor class to execute TransformStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("TransformJobName", None) or unique_name_from_base(
 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_transform_job(
 job_name, **step_arguments
Expand Down

95 changes: 93 additions & 2 deletions
tests/unit/sagemaker/local/test_local_pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@
from sagemaker.workflow.parameters import ParameterInteger, ParameterString
from sagemaker.workflow.pipeline import Pipeline
from sagemaker.workflow.pipeline_context import PipelineSession
from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
from sagemaker.workflow.step_outputs import get_step
from sagemaker.workflow.steps import (
 ProcessingStep,
Expand DownExpand Up@@ -111,6 +112,7 @@
 "Result": [1, 2, 3], "Exception": null
}
"""
TEST_JOB_NAME = "test-job-name"


@pytest.fixture
Expand DownExpand Up@@ -188,6 +190,8 @@ def training_step(pipeline_session):
 sagemaker_session=pipeline_session,
 output_path="s3://a/b",
 use_spot_instances=False,
 # base_job_name would be popped out if no pipeline_definition_config configured
 base_job_name=TEST_JOB_NAME,
 )
 training_input = TrainingInput(s3_data=f"s3://{BUCKET}/train_manifest")
 step_args = estimator.fit(inputs=training_input)
Expand All@@ -207,6 +211,8 @@ def processing_step(pipeline_session):
 instance_count=1,
 instance_type=INSTANCE_TYPE,
 sagemaker_session=pipeline_session,
 # base_job_name would be popped out if no pipeline_definition_config configured
 base_job_name=TEST_JOB_NAME,
 )
 processing_input = [
 ProcessingInput(
Expand DownExpand Up@@ -239,6 +245,8 @@ def transform_step(pipeline_session):
 instance_count=1,
 output_path="s3://my-bucket/my-output-path",
 sagemaker_session=pipeline_session,
 # base_transform_job_name would be popped out if no pipeline_definition_config configured
 base_transform_job_name=TEST_JOB_NAME,
 )
 transform_inputs = TransformInput(data="s3://my-bucket/my-data")
 step_args = transformer.transform(
Expand DownExpand Up@@ -871,8 +879,8 @@ def depends_step():
 )


@patch("sagemaker.local.image._SageMakerContainer.process")
def test_execute_pipeline_processing_step(process, local_sagemaker_session, processing_step):
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_execute_pipeline_processing_step(local_sagemaker_session, processing_step):
 pipeline = Pipeline(
 name="MyPipeline2",
 steps=[processing_step],
Expand DownExpand Up@@ -1362,3 +1370,86 @@ def test_execute_pipeline_step_create_transform_job_fail(
 step_execution = execution.step_execution
 assert step_execution[transform_step.name].status == _LocalExecutionStatus.FAILED.value
 assert "Dummy RuntimeError" in step_execution[transform_step.name].failure_reason


@patch(
 "sagemaker.local.image._SageMakerContainer.train",
 MagicMock(return_value="/some/path/to/model"),
)
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_pipeline_definition_config_in_local_mode_for_train_process_steps(
 processing_step,
 training_step,
 local_sagemaker_session,
):
 exe_steps = [processing_step, training_step]

 def _verify_execution(exe_step_name, execution, with_custom_job_prefix):
 assert not execution.failure_reason
 assert execution.status == _LocalExecutionStatus.SUCCEEDED.value

 step_execution = execution.step_execution[exe_step_name]
 assert step_execution.status == _LocalExecutionStatus.SUCCEEDED.value

 if step_execution.type == StepTypeEnum.PROCESSING:
 job_name_field = "ProcessingJobName"
 elif step_execution.type == StepTypeEnum.TRAINING:
 job_name_field = "TrainingJobName"

 if with_custom_job_prefix:
 assert step_execution.properties[job_name_field] == TEST_JOB_NAME
 else:
 assert step_execution.properties[job_name_field].startswith(step_execution.name)

 for exe_step in exe_steps:
 pipeline = Pipeline(
 name="MyPipelineX-" + exe_step.name,
 steps=[exe_step],
 sagemaker_session=local_sagemaker_session,
 parameters=[INSTANCE_COUNT_PIPELINE_PARAMETER],
 )

 execution = LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 _verify_execution(
 exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=False
 )

 pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)
 execution = LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 _verify_execution(
 exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=True
 )


@patch("sagemaker.local.local_session.LocalSagemakerClient.create_transform_job")
def test_pipeline_definition_config_in_local_mode_for_transform_step(
 create_transform_job, local_sagemaker_session, transform_step
):
 pipeline = Pipeline(
 name="MyPipelineX-" + transform_step.name,
 steps=[transform_step],
 sagemaker_session=local_sagemaker_session,
 )
 LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 assert create_transform_job.call_args.args[0].startswith(transform_step.name)

 pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)

 LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 assert create_transform_job.call_args.args[0] == TEST_JOB_NAME

, '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: Support using PipelineDefinitionConfig in local mode#4352

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

Jan 24, 2024
 Merged


fix: Support using PipelineDefinitionConfig in local mode
#4352
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

Jump to file


Failed to load files. 
Loading
 Diff view

 Diff view


12 changes: 9 additions & 3 deletions
src/sagemaker/local/pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -273,8 +273,10 @@ class _TrainingStepExecutor(_StepExecutor):
 """Executor class to execute TrainingStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("TrainingJobName", None) or unique_name_from_base(
Comment thread
qidewenwhen marked this conversation as resolved.

 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_training_job(
 job_name, **step_arguments
Expand All@@ -290,8 +292,10 @@ class _ProcessingStepExecutor(_StepExecutor):
 """Executor class to execute ProcessingStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("ProcessingJobName", None) or unique_name_from_base(
 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_processing_job(
 job_name, **step_arguments
Expand DownExpand Up@@ -482,8 +486,10 @@ class _TransformStepExecutor(_StepExecutor):
 """Executor class to execute TransformStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("TransformJobName", None) or unique_name_from_base(
 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_transform_job(
 job_name, **step_arguments
Expand Down

95 changes: 93 additions & 2 deletions
tests/unit/sagemaker/local/test_local_pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@
from sagemaker.workflow.parameters import ParameterInteger, ParameterString
from sagemaker.workflow.pipeline import Pipeline
from sagemaker.workflow.pipeline_context import PipelineSession
from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
from sagemaker.workflow.step_outputs import get_step
from sagemaker.workflow.steps import (
 ProcessingStep,
Expand DownExpand Up@@ -111,6 +112,7 @@
 "Result": [1, 2, 3], "Exception": null
}
"""
TEST_JOB_NAME = "test-job-name"


@pytest.fixture
Expand DownExpand Up@@ -188,6 +190,8 @@ def training_step(pipeline_session):
 sagemaker_session=pipeline_session,
 output_path="s3://a/b",
 use_spot_instances=False,
 # base_job_name would be popped out if no pipeline_definition_config configured
 base_job_name=TEST_JOB_NAME,
 )
 training_input = TrainingInput(s3_data=f"s3://{BUCKET}/train_manifest")
 step_args = estimator.fit(inputs=training_input)
Expand All@@ -207,6 +211,8 @@ def processing_step(pipeline_session):
 instance_count=1,
 instance_type=INSTANCE_TYPE,
 sagemaker_session=pipeline_session,
 # base_job_name would be popped out if no pipeline_definition_config configured
 base_job_name=TEST_JOB_NAME,
 )
 processing_input = [
 ProcessingInput(
Expand DownExpand Up@@ -239,6 +245,8 @@ def transform_step(pipeline_session):
 instance_count=1,
 output_path="s3://my-bucket/my-output-path",
 sagemaker_session=pipeline_session,
 # base_transform_job_name would be popped out if no pipeline_definition_config configured
 base_transform_job_name=TEST_JOB_NAME,
 )
 transform_inputs = TransformInput(data="s3://my-bucket/my-data")
 step_args = transformer.transform(
Expand DownExpand Up@@ -871,8 +879,8 @@ def depends_step():
 )


@patch("sagemaker.local.image._SageMakerContainer.process")
def test_execute_pipeline_processing_step(process, local_sagemaker_session, processing_step):
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_execute_pipeline_processing_step(local_sagemaker_session, processing_step):
 pipeline = Pipeline(
 name="MyPipeline2",
 steps=[processing_step],
Expand DownExpand Up@@ -1362,3 +1370,86 @@ def test_execute_pipeline_step_create_transform_job_fail(
 step_execution = execution.step_execution
 assert step_execution[transform_step.name].status == _LocalExecutionStatus.FAILED.value
 assert "Dummy RuntimeError" in step_execution[transform_step.name].failure_reason


@patch(
 "sagemaker.local.image._SageMakerContainer.train",
 MagicMock(return_value="/some/path/to/model"),
)
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_pipeline_definition_config_in_local_mode_for_train_process_steps(
 processing_step,
 training_step,
 local_sagemaker_session,
):
 exe_steps = [processing_step, training_step]

 def _verify_execution(exe_step_name, execution, with_custom_job_prefix):
 assert not execution.failure_reason
 assert execution.status == _LocalExecutionStatus.SUCCEEDED.value

 step_execution = execution.step_execution[exe_step_name]
 assert step_execution.status == _LocalExecutionStatus.SUCCEEDED.value

 if step_execution.type == StepTypeEnum.PROCESSING:
 job_name_field = "ProcessingJobName"
 elif step_execution.type == StepTypeEnum.TRAINING:
 job_name_field = "TrainingJobName"

 if with_custom_job_prefix:
 assert step_execution.properties[job_name_field] == TEST_JOB_NAME
 else:
 assert step_execution.properties[job_name_field].startswith(step_execution.name)

 for exe_step in exe_steps:
 pipeline = Pipeline(
 name="MyPipelineX-" + exe_step.name,
 steps=[exe_step],
 sagemaker_session=local_sagemaker_session,
 parameters=[INSTANCE_COUNT_PIPELINE_PARAMETER],
 )

 execution = LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 _verify_execution(
 exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=False
 )

 pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)
 execution = LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 _verify_execution(
 exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=True
 )


@patch("sagemaker.local.local_session.LocalSagemakerClient.create_transform_job")
def test_pipeline_definition_config_in_local_mode_for_transform_step(
 create_transform_job, local_sagemaker_session, transform_step
):
 pipeline = Pipeline(
 name="MyPipelineX-" + transform_step.name,
 steps=[transform_step],
 sagemaker_session=local_sagemaker_session,
 )
 LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 assert create_transform_job.call_args.args[0].startswith(transform_step.name)

 pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)

 LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 assert create_transform_job.call_args.args[0] == TEST_JOB_NAME

, '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: Support using PipelineDefinitionConfig in local mode#4352

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

Jan 24, 2024
 Merged


fix: Support using PipelineDefinitionConfig in local mode
#4352
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

Jump to file


Failed to load files. 
Loading
 Diff view

 Diff view


12 changes: 9 additions & 3 deletions
src/sagemaker/local/pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -273,8 +273,10 @@ class _TrainingStepExecutor(_StepExecutor):
 """Executor class to execute TrainingStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("TrainingJobName", None) or unique_name_from_base(
Comment thread
qidewenwhen marked this conversation as resolved.

 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_training_job(
 job_name, **step_arguments
Expand All@@ -290,8 +292,10 @@ class _ProcessingStepExecutor(_StepExecutor):
 """Executor class to execute ProcessingStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("ProcessingJobName", None) or unique_name_from_base(
 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_processing_job(
 job_name, **step_arguments
Expand DownExpand Up@@ -482,8 +486,10 @@ class _TransformStepExecutor(_StepExecutor):
 """Executor class to execute TransformStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("TransformJobName", None) or unique_name_from_base(
 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_transform_job(
 job_name, **step_arguments
Expand Down

95 changes: 93 additions & 2 deletions
tests/unit/sagemaker/local/test_local_pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@
from sagemaker.workflow.parameters import ParameterInteger, ParameterString
from sagemaker.workflow.pipeline import Pipeline
from sagemaker.workflow.pipeline_context import PipelineSession
from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
from sagemaker.workflow.step_outputs import get_step
from sagemaker.workflow.steps import (
 ProcessingStep,
Expand DownExpand Up@@ -111,6 +112,7 @@
 "Result": [1, 2, 3], "Exception": null
}
"""
TEST_JOB_NAME = "test-job-name"


@pytest.fixture
Expand DownExpand Up@@ -188,6 +190,8 @@ def training_step(pipeline_session):
 sagemaker_session=pipeline_session,
 output_path="s3://a/b",
 use_spot_instances=False,
 # base_job_name would be popped out if no pipeline_definition_config configured
 base_job_name=TEST_JOB_NAME,
 )
 training_input = TrainingInput(s3_data=f"s3://{BUCKET}/train_manifest")
 step_args = estimator.fit(inputs=training_input)
Expand All@@ -207,6 +211,8 @@ def processing_step(pipeline_session):
 instance_count=1,
 instance_type=INSTANCE_TYPE,
 sagemaker_session=pipeline_session,
 # base_job_name would be popped out if no pipeline_definition_config configured
 base_job_name=TEST_JOB_NAME,
 )
 processing_input = [
 ProcessingInput(
Expand DownExpand Up@@ -239,6 +245,8 @@ def transform_step(pipeline_session):
 instance_count=1,
 output_path="s3://my-bucket/my-output-path",
 sagemaker_session=pipeline_session,
 # base_transform_job_name would be popped out if no pipeline_definition_config configured
 base_transform_job_name=TEST_JOB_NAME,
 )
 transform_inputs = TransformInput(data="s3://my-bucket/my-data")
 step_args = transformer.transform(
Expand DownExpand Up@@ -871,8 +879,8 @@ def depends_step():
 )


@patch("sagemaker.local.image._SageMakerContainer.process")
def test_execute_pipeline_processing_step(process, local_sagemaker_session, processing_step):
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_execute_pipeline_processing_step(local_sagemaker_session, processing_step):
 pipeline = Pipeline(
 name="MyPipeline2",
 steps=[processing_step],
Expand DownExpand Up@@ -1362,3 +1370,86 @@ def test_execute_pipeline_step_create_transform_job_fail(
 step_execution = execution.step_execution
 assert step_execution[transform_step.name].status == _LocalExecutionStatus.FAILED.value
 assert "Dummy RuntimeError" in step_execution[transform_step.name].failure_reason


@patch(
 "sagemaker.local.image._SageMakerContainer.train",
 MagicMock(return_value="/some/path/to/model"),
)
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_pipeline_definition_config_in_local_mode_for_train_process_steps(
 processing_step,
 training_step,
 local_sagemaker_session,
):
 exe_steps = [processing_step, training_step]

 def _verify_execution(exe_step_name, execution, with_custom_job_prefix):
 assert not execution.failure_reason
 assert execution.status == _LocalExecutionStatus.SUCCEEDED.value

 step_execution = execution.step_execution[exe_step_name]
 assert step_execution.status == _LocalExecutionStatus.SUCCEEDED.value

 if step_execution.type == StepTypeEnum.PROCESSING:
 job_name_field = "ProcessingJobName"
 elif step_execution.type == StepTypeEnum.TRAINING:
 job_name_field = "TrainingJobName"

 if with_custom_job_prefix:
 assert step_execution.properties[job_name_field] == TEST_JOB_NAME
 else:
 assert step_execution.properties[job_name_field].startswith(step_execution.name)

 for exe_step in exe_steps:
 pipeline = Pipeline(
 name="MyPipelineX-" + exe_step.name,
 steps=[exe_step],
 sagemaker_session=local_sagemaker_session,
 parameters=[INSTANCE_COUNT_PIPELINE_PARAMETER],
 )

 execution = LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 _verify_execution(
 exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=False
 )

 pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)
 execution = LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 _verify_execution(
 exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=True
 )


@patch("sagemaker.local.local_session.LocalSagemakerClient.create_transform_job")
def test_pipeline_definition_config_in_local_mode_for_transform_step(
 create_transform_job, local_sagemaker_session, transform_step
):
 pipeline = Pipeline(
 name="MyPipelineX-" + transform_step.name,
 steps=[transform_step],
 sagemaker_session=local_sagemaker_session,
 )
 LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 assert create_transform_job.call_args.args[0].startswith(transform_step.name)

 pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)

 LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 assert create_transform_job.call_args.args[0] == TEST_JOB_NAME

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
fix: Support using PipelineDefinitionConfig in local mode#4352

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

Jan 24, 2024
 Merged


fix: Support using PipelineDefinitionConfig in local mode
#4352
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

Jump to file


Failed to load files. 
Loading
 Diff view

 Diff view


12 changes: 9 additions & 3 deletions
src/sagemaker/local/pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -273,8 +273,10 @@ class _TrainingStepExecutor(_StepExecutor):
 """Executor class to execute TrainingStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("TrainingJobName", None) or unique_name_from_base(
Comment thread
qidewenwhen marked this conversation as resolved.

 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_training_job(
 job_name, **step_arguments
Expand All@@ -290,8 +292,10 @@ class _ProcessingStepExecutor(_StepExecutor):
 """Executor class to execute ProcessingStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("ProcessingJobName", None) or unique_name_from_base(
 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_processing_job(
 job_name, **step_arguments
Expand DownExpand Up@@ -482,8 +486,10 @@ class _TransformStepExecutor(_StepExecutor):
 """Executor class to execute TransformStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("TransformJobName", None) or unique_name_from_base(
 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_transform_job(
 job_name, **step_arguments
Expand Down

95 changes: 93 additions & 2 deletions
tests/unit/sagemaker/local/test_local_pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@
from sagemaker.workflow.parameters import ParameterInteger, ParameterString
from sagemaker.workflow.pipeline import Pipeline
from sagemaker.workflow.pipeline_context import PipelineSession
from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
from sagemaker.workflow.step_outputs import get_step
from sagemaker.workflow.steps import (
 ProcessingStep,
Expand DownExpand Up@@ -111,6 +112,7 @@
 "Result": [1, 2, 3], "Exception": null
}
"""
TEST_JOB_NAME = "test-job-name"


@pytest.fixture
Expand DownExpand Up@@ -188,6 +190,8 @@ def training_step(pipeline_session):
 sagemaker_session=pipeline_session,
 output_path="s3://a/b",
 use_spot_instances=False,
 # base_job_name would be popped out if no pipeline_definition_config configured
 base_job_name=TEST_JOB_NAME,
 )
 training_input = TrainingInput(s3_data=f"s3://{BUCKET}/train_manifest")
 step_args = estimator.fit(inputs=training_input)
Expand All@@ -207,6 +211,8 @@ def processing_step(pipeline_session):
 instance_count=1,
 instance_type=INSTANCE_TYPE,
 sagemaker_session=pipeline_session,
 # base_job_name would be popped out if no pipeline_definition_config configured
 base_job_name=TEST_JOB_NAME,
 )
 processing_input = [
 ProcessingInput(
Expand DownExpand Up@@ -239,6 +245,8 @@ def transform_step(pipeline_session):
 instance_count=1,
 output_path="s3://my-bucket/my-output-path",
 sagemaker_session=pipeline_session,
 # base_transform_job_name would be popped out if no pipeline_definition_config configured
 base_transform_job_name=TEST_JOB_NAME,
 )
 transform_inputs = TransformInput(data="s3://my-bucket/my-data")
 step_args = transformer.transform(
Expand DownExpand Up@@ -871,8 +879,8 @@ def depends_step():
 )


@patch("sagemaker.local.image._SageMakerContainer.process")
def test_execute_pipeline_processing_step(process, local_sagemaker_session, processing_step):
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_execute_pipeline_processing_step(local_sagemaker_session, processing_step):
 pipeline = Pipeline(
 name="MyPipeline2",
 steps=[processing_step],
Expand DownExpand Up@@ -1362,3 +1370,86 @@ def test_execute_pipeline_step_create_transform_job_fail(
 step_execution = execution.step_execution
 assert step_execution[transform_step.name].status == _LocalExecutionStatus.FAILED.value
 assert "Dummy RuntimeError" in step_execution[transform_step.name].failure_reason


@patch(
 "sagemaker.local.image._SageMakerContainer.train",
 MagicMock(return_value="/some/path/to/model"),
)
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_pipeline_definition_config_in_local_mode_for_train_process_steps(
 processing_step,
 training_step,
 local_sagemaker_session,
):
 exe_steps = [processing_step, training_step]

 def _verify_execution(exe_step_name, execution, with_custom_job_prefix):
 assert not execution.failure_reason
 assert execution.status == _LocalExecutionStatus.SUCCEEDED.value

 step_execution = execution.step_execution[exe_step_name]
 assert step_execution.status == _LocalExecutionStatus.SUCCEEDED.value

 if step_execution.type == StepTypeEnum.PROCESSING:
 job_name_field = "ProcessingJobName"
 elif step_execution.type == StepTypeEnum.TRAINING:
 job_name_field = "TrainingJobName"

 if with_custom_job_prefix:
 assert step_execution.properties[job_name_field] == TEST_JOB_NAME
 else:
 assert step_execution.properties[job_name_field].startswith(step_execution.name)

 for exe_step in exe_steps:
 pipeline = Pipeline(
 name="MyPipelineX-" + exe_step.name,
 steps=[exe_step],
 sagemaker_session=local_sagemaker_session,
 parameters=[INSTANCE_COUNT_PIPELINE_PARAMETER],
 )

 execution = LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 _verify_execution(
 exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=False
 )

 pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)
 execution = LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 _verify_execution(
 exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=True
 )


@patch("sagemaker.local.local_session.LocalSagemakerClient.create_transform_job")
def test_pipeline_definition_config_in_local_mode_for_transform_step(
 create_transform_job, local_sagemaker_session, transform_step
):
 pipeline = Pipeline(
 name="MyPipelineX-" + transform_step.name,
 steps=[transform_step],
 sagemaker_session=local_sagemaker_session,
 )
 LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 assert create_transform_job.call_args.args[0].startswith(transform_step.name)

 pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)

 LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 assert create_transform_job.call_args.args[0] == TEST_JOB_NAME

, '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: Support using PipelineDefinitionConfig in local mode#4352

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

Jan 24, 2024
 Merged


fix: Support using PipelineDefinitionConfig in local mode
#4352
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

Jump to file


Failed to load files. 
Loading
 Diff view

 Diff view


12 changes: 9 additions & 3 deletions
src/sagemaker/local/pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -273,8 +273,10 @@ class _TrainingStepExecutor(_StepExecutor):
 """Executor class to execute TrainingStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("TrainingJobName", None) or unique_name_from_base(
Comment thread
qidewenwhen marked this conversation as resolved.

 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_training_job(
 job_name, **step_arguments
Expand All@@ -290,8 +292,10 @@ class _ProcessingStepExecutor(_StepExecutor):
 """Executor class to execute ProcessingStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("ProcessingJobName", None) or unique_name_from_base(
 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_processing_job(
 job_name, **step_arguments
Expand DownExpand Up@@ -482,8 +486,10 @@ class _TransformStepExecutor(_StepExecutor):
 """Executor class to execute TransformStep locally"""

 def execute(self):
 job_name = unique_name_from_base(self.step.name)
 step_arguments = self.pipline_executor.evaluate_step_arguments(self.step)
 job_name = step_arguments.pop("TransformJobName", None) or unique_name_from_base(
 self.step.name
 )
 try:
 self.pipline_executor.local_sagemaker_client.create_transform_job(
 job_name, **step_arguments
Expand Down

95 changes: 93 additions & 2 deletions
tests/unit/sagemaker/local/test_local_pipeline.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -47,6 +47,7 @@
from sagemaker.workflow.parameters import ParameterInteger, ParameterString
from sagemaker.workflow.pipeline import Pipeline
from sagemaker.workflow.pipeline_context import PipelineSession
from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
from sagemaker.workflow.step_outputs import get_step
from sagemaker.workflow.steps import (
 ProcessingStep,
Expand DownExpand Up@@ -111,6 +112,7 @@
 "Result": [1, 2, 3], "Exception": null
}
"""
TEST_JOB_NAME = "test-job-name"


@pytest.fixture
Expand DownExpand Up@@ -188,6 +190,8 @@ def training_step(pipeline_session):
 sagemaker_session=pipeline_session,
 output_path="s3://a/b",
 use_spot_instances=False,
 # base_job_name would be popped out if no pipeline_definition_config configured
 base_job_name=TEST_JOB_NAME,
 )
 training_input = TrainingInput(s3_data=f"s3://{BUCKET}/train_manifest")
 step_args = estimator.fit(inputs=training_input)
Expand All@@ -207,6 +211,8 @@ def processing_step(pipeline_session):
 instance_count=1,
 instance_type=INSTANCE_TYPE,
 sagemaker_session=pipeline_session,
 # base_job_name would be popped out if no pipeline_definition_config configured
 base_job_name=TEST_JOB_NAME,
 )
 processing_input = [
 ProcessingInput(
Expand DownExpand Up@@ -239,6 +245,8 @@ def transform_step(pipeline_session):
 instance_count=1,
 output_path="s3://my-bucket/my-output-path",
 sagemaker_session=pipeline_session,
 # base_transform_job_name would be popped out if no pipeline_definition_config configured
 base_transform_job_name=TEST_JOB_NAME,
 )
 transform_inputs = TransformInput(data="s3://my-bucket/my-data")
 step_args = transformer.transform(
Expand DownExpand Up@@ -871,8 +879,8 @@ def depends_step():
 )


@patch("sagemaker.local.image._SageMakerContainer.process")
def test_execute_pipeline_processing_step(process, local_sagemaker_session, processing_step):
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_execute_pipeline_processing_step(local_sagemaker_session, processing_step):
 pipeline = Pipeline(
 name="MyPipeline2",
 steps=[processing_step],
Expand DownExpand Up@@ -1362,3 +1370,86 @@ def test_execute_pipeline_step_create_transform_job_fail(
 step_execution = execution.step_execution
 assert step_execution[transform_step.name].status == _LocalExecutionStatus.FAILED.value
 assert "Dummy RuntimeError" in step_execution[transform_step.name].failure_reason


@patch(
 "sagemaker.local.image._SageMakerContainer.train",
 MagicMock(return_value="/some/path/to/model"),
)
@patch("sagemaker.local.image._SageMakerContainer.process", MagicMock())
def test_pipeline_definition_config_in_local_mode_for_train_process_steps(
 processing_step,
 training_step,
 local_sagemaker_session,
):
 exe_steps = [processing_step, training_step]

 def _verify_execution(exe_step_name, execution, with_custom_job_prefix):
 assert not execution.failure_reason
 assert execution.status == _LocalExecutionStatus.SUCCEEDED.value

 step_execution = execution.step_execution[exe_step_name]
 assert step_execution.status == _LocalExecutionStatus.SUCCEEDED.value

 if step_execution.type == StepTypeEnum.PROCESSING:
 job_name_field = "ProcessingJobName"
 elif step_execution.type == StepTypeEnum.TRAINING:
 job_name_field = "TrainingJobName"

 if with_custom_job_prefix:
 assert step_execution.properties[job_name_field] == TEST_JOB_NAME
 else:
 assert step_execution.properties[job_name_field].startswith(step_execution.name)

 for exe_step in exe_steps:
 pipeline = Pipeline(
 name="MyPipelineX-" + exe_step.name,
 steps=[exe_step],
 sagemaker_session=local_sagemaker_session,
 parameters=[INSTANCE_COUNT_PIPELINE_PARAMETER],
 )

 execution = LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 _verify_execution(
 exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=False
 )

 pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)
 execution = LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + exe_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 _verify_execution(
 exe_step_name=exe_step.name, execution=execution, with_custom_job_prefix=True
 )


@patch("sagemaker.local.local_session.LocalSagemakerClient.create_transform_job")
def test_pipeline_definition_config_in_local_mode_for_transform_step(
 create_transform_job, local_sagemaker_session, transform_step
):
 pipeline = Pipeline(
 name="MyPipelineX-" + transform_step.name,
 steps=[transform_step],
 sagemaker_session=local_sagemaker_session,
 )
 LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 assert create_transform_job.call_args.args[0].startswith(transform_step.name)

 pipeline.pipeline_definition_config = PipelineDefinitionConfig(use_custom_job_prefix=True)

 LocalPipelineExecutor(
 _LocalPipelineExecution("my-execution-x-" + transform_step.name, pipeline),
 local_sagemaker_session,
 ).execute()

 assert create_transform_job.call_args.args[0] == TEST_JOB_NAME