|
18 | 18 | import time
|
19 | 19 | import uuid
|
20 | 20 |
|
21 |
| -import boto3 |
22 | 21 | import pytest
|
23 | 22 |
|
24 |
| -from botocore.config import Config |
25 | 23 | from botocore.exceptions import WaiterError
|
26 | 24 | from sagemaker.debugger import (
|
27 | 25 | DebuggerHookConfig,
|
|
32 | 30 | from sagemaker.model import Model
|
33 | 31 | from sagemaker.processing import ProcessingInput, ProcessingOutput
|
34 | 32 | from sagemaker.pytorch.estimator import PyTorch
|
35 |
| -from sagemaker.session import get_execution_role, Session |
| 33 | +from sagemaker.session import get_execution_role |
36 | 34 | from sagemaker.sklearn.estimator import SKLearn
|
37 | 35 | from sagemaker.sklearn.processing import SKLearnProcessor
|
38 | 36 | from sagemaker.workflow.conditions import ConditionGreaterThanOrEqualTo
|
@@ -75,21 +73,6 @@ def role(sagemaker_session):
|
75 | 73 | return get_execution_role(sagemaker_session)
|
76 | 74 |
|
77 | 75 |
|
78 |
| -@pytest.fixture(scope="module") |
79 |
| -def workflow_session(region_name): |
80 |
| - boto_session = boto3.Session(region_name=region_name) |
81 |
| - |
82 |
| - sagemaker_client_config = dict() |
83 |
| - sagemaker_client_config.setdefault("config", Config(retries=dict(max_attempts=2))) |
84 |
| - sagemaker_client = boto_session.client("sagemaker", **sagemaker_client_config) |
85 |
| - |
86 |
| - return Session( |
87 |
| - boto_session=boto_session, |
88 |
| - sagemaker_client=sagemaker_client, |
89 |
| - sagemaker_runtime_client=None, |
90 |
| - ) |
91 |
| - |
92 |
| - |
93 | 76 | @pytest.fixture(scope="module")
|
94 | 77 | def script_dir():
|
95 | 78 | return os.path.join(DATA_DIR, "sklearn_processing")
|
@@ -120,7 +103,6 @@ def athena_dataset_definition(sagemaker_session):
|
120 | 103 |
|
121 | 104 | def test_three_step_definition(
|
122 | 105 | sagemaker_session,
|
123 |
| - workflow_session, |
124 | 106 | region_name,
|
125 | 107 | role,
|
126 | 108 | script_dir,
|
@@ -206,7 +188,7 @@ def test_three_step_definition(
|
206 | 188 | name=pipeline_name,
|
207 | 189 | parameters=[instance_type, instance_count, output_prefix],
|
208 | 190 | steps=[step_process, step_train, step_model],
|
209 |
| - sagemaker_session=workflow_session, |
| 191 | + sagemaker_session=sagemaker_session, |
210 | 192 | )
|
211 | 193 |
|
212 | 194 | definition = json.loads(pipeline.definition())
|
@@ -278,7 +260,6 @@ def test_three_step_definition(
|
278 | 260 |
|
279 | 261 | def test_one_step_sklearn_processing_pipeline(
|
280 | 262 | sagemaker_session,
|
281 |
| - workflow_session, |
282 | 263 | role,
|
283 | 264 | sklearn_latest_version,
|
284 | 265 | cpu_instance_type,
|
@@ -317,7 +298,7 @@ def test_one_step_sklearn_processing_pipeline(
|
317 | 298 | name=pipeline_name,
|
318 | 299 | parameters=[instance_count],
|
319 | 300 | steps=[step_sklearn],
|
320 |
| - sagemaker_session=workflow_session, |
| 301 | + sagemaker_session=sagemaker_session, |
321 | 302 | )
|
322 | 303 |
|
323 | 304 | try:
|
@@ -372,7 +353,6 @@ def test_one_step_sklearn_processing_pipeline(
|
372 | 353 |
|
373 | 354 | def test_conditional_pytorch_training_model_registration(
|
374 | 355 | sagemaker_session,
|
375 |
| - workflow_session, |
376 | 356 | role,
|
377 | 357 | cpu_instance_type,
|
378 | 358 | pipeline_name,
|
@@ -442,7 +422,7 @@ def test_conditional_pytorch_training_model_registration(
|
442 | 422 | name=pipeline_name,
|
443 | 423 | parameters=[good_enough_input, instance_count, instance_type],
|
444 | 424 | steps=[step_cond],
|
445 |
| - sagemaker_session=workflow_session, |
| 425 | + sagemaker_session=sagemaker_session, |
446 | 426 | )
|
447 | 427 |
|
448 | 428 | try:
|
|
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