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repo stringlengths 2 152 ⌀ | file stringlengths 15 239 | code stringlengths 0 58.4M | file_length int64 0 58.4M | avg_line_length float64 0 1.81M | max_line_length int64 0 12.7M | extension_type stringclasses 364
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pipelines | pipelines-master/components/aws/sagemaker/create_simulation_app/README.md | # RoboMaker Create Simulation Application Kubeflow Pipelines component
## Summary
Component to create RoboMaker Simulation Application's from a Kubeflow Pipelines workflow.
https://docs.aws.amazon.com/robomaker/latest/dg/create-simulation-application.html
## Intended Use
For running your simulation workloads using AW... | 2,976 | 61.020833 | 243 | md |
pipelines | pipelines-master/components/aws/sagemaker/create_simulation_app/component.yaml | name: RoboMaker - Create Simulation Application
description: Creates a simulation application.
inputs:
- {name: region, type: String, description: The region for the SageMaker resource.}
- {name: endpoint_url, type: String, description: The URL to use when communicating
with the SageMaker service., default: ''}
- {... | 3,126 | 43.671429 | 89 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/create_simulation_app/src/robomaker_create_simulation_app_component.py | """RoboMaker component for creating a simulation application."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | 5,793 | 34.987578 | 159 | py |
pipelines | pipelines-master/components/aws/sagemaker/create_simulation_app/src/robomaker_create_simulation_app_spec.py | """Specification for the RoboMaker create simulation application component."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required... | 4,896 | 33.485915 | 94 | py |
pipelines | pipelines-master/components/aws/sagemaker/delete_simulation_app/README.md | # RoboMaker Delete Simulation Application Kubeflow Pipelines component
## Summary
Component to delete RoboMaker Simulation Application's from a Kubeflow Pipelines workflow.
https://docs.aws.amazon.com/robomaker/latest/dg/API_DeleteSimulationApplication.html
## Intended Use
For running your simulation workloads using ... | 2,249 | 63.285714 | 243 | md |
pipelines | pipelines-master/components/aws/sagemaker/delete_simulation_app/component.yaml | name: RoboMaker - Delete Simulation Application
description: Delete a simulation application.
inputs:
- {name: region, type: String, description: The region for the SageMaker resource.}
- {name: endpoint_url, type: String, description: The URL to use when communicating
with the SageMaker service., default: ''}
- {n... | 1,426 | 37.567568 | 89 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/delete_simulation_app/src/robomaker_delete_simulation_app_component.py | """RoboMaker component for deleting a simulation application."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | 4,549 | 34.546875 | 159 | py |
pipelines | pipelines-master/components/aws/sagemaker/delete_simulation_app/src/robomaker_delete_simulation_app_spec.py | """Specification for the RoboMaker delete. simulation application component."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 2,873 | 31.292135 | 88 | py |
pipelines | pipelines-master/components/aws/sagemaker/deploy/README.md | # SageMaker Hosting Services - Create Endpoint Kubeflow Pipeline component
## Summary
Component to deploy a model in SageMaker Hosting Service from a Kubeflow Pipelines workflow.
## Details
Deploying a model using Amazon SageMaker hosting services is a three-step process:
1. **Create a model in Amazon SageMaker** - ... | 6,377 | 95.636364 | 553 | md |
pipelines | pipelines-master/components/aws/sagemaker/deploy/component.yaml | name: SageMaker - Deploy Model
description: Deploy Machine Learning Model Endpoint in SageMaker
inputs:
- {name: region, type: String, description: The region for the SageMaker resource.}
- {name: endpoint_url, type: String, description: The URL to use when communicating
with the SageMaker service., default: ''}
- ... | 5,796 | 44.645669 | 90 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/deploy/src/sagemaker_deploy_component.py | """SageMaker component for deploy."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writin... | 13,137 | 36.112994 | 175 | py |
pipelines | pipelines-master/components/aws/sagemaker/deploy/src/sagemaker_deploy_spec.py | """Specification for the SageMaker deploy component."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 8,330 | 34.151899 | 168 | py |
pipelines | pipelines-master/components/aws/sagemaker/ground_truth/README.md | # SageMaker Ground Truth Kubeflow Pipelines component
## Summary
Component to submit SageMaker Ground Truth labeling jobs directly from a Kubeflow Pipelines workflow.
# Details
## Intended Use
For Ground Truth jobs using AWS SageMaker.
## Runtime Arguments
Argument | Description | Optional |... | 6,021 | 90.242424 | 292 | md |
pipelines | pipelines-master/components/aws/sagemaker/ground_truth/component.yaml | name: SageMaker - Ground Truth
description: Ground Truth Jobs in SageMaker
inputs:
- {name: region, type: String, description: The region for the SageMaker resource.}
- {name: endpoint_url, type: String, description: The URL to use when communicating
with the SageMaker service., default: ''}
- {name: assume_role, t... | 7,215 | 45.857143 | 93 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/ground_truth/src/sagemaker_ground_truth_component.py | """SageMaker component for ground truth."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in ... | 14,321 | 39.117647 | 178 | py |
pipelines | pipelines-master/components/aws/sagemaker/ground_truth/src/sagemaker_ground_truth_spec.py | """Specification for the SageMaker ground truth component."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable la... | 9,742 | 36.473077 | 201 | py |
pipelines | pipelines-master/components/aws/sagemaker/hyperparameter_tuning/README.md | # SageMaker hyperparameter optimization Kubeflow Pipeline component
## Summary
Component to submit hyperparameter tuning jobs to SageMaker directly from a Kubeflow Pipelines workflow.
# Details
## Intended Use
For hyperparameter tuning jobs using AWS SageMaker.
## Runtime Arguments
Argument | Description ... | 8,585 | 94.4 | 545 | md |
pipelines | pipelines-master/components/aws/sagemaker/hyperparameter_tuning/component.yaml | name: SageMaker - Hyperparameter Tuning
description: Hyperparameter Tuning Jobs in SageMaker
inputs:
- name: spot_instance
type: Bool
description: Use managed spot training.
default: "False"
- {name: max_wait_time, type: Integer, description: The maximum time in seconds you
are willing to wait for a managed s... | 8,622 | 44.624339 | 101 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/hyperparameter_tuning/src/sagemaker_tuning_component.py | """SageMaker component for tuning."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writin... | 13,644 | 40.348485 | 185 | py |
pipelines | pipelines-master/components/aws/sagemaker/hyperparameter_tuning/src/sagemaker_tuning_spec.py | """Specification for the SageMaker tuning component."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 10,810 | 36.538194 | 149 | py |
pipelines | pipelines-master/components/aws/sagemaker/model/README.md | # SageMaker Hosting Services - Create Model Kubeflow Pipeline component
## Summary
Component to create a model in SageMaker from a Kubeflow Pipelines workflow.
## Details
Deploying a model using Amazon SageMaker hosting services is a three-step process:
1. **Create a model in Amazon SageMaker** - Specify the S3 path... | 7,136 | 89.341772 | 549 | md |
pipelines | pipelines-master/components/aws/sagemaker/model/component.yaml | name: SageMaker - Create Model
description: Create Models in SageMaker
inputs:
- {name: region, type: String, description: The region for the SageMaker resource.}
- {name: endpoint_url, type: String, description: The URL to use when communicating
with the SageMaker service., default: ''}
- {name: assume_role, type:... | 3,317 | 42.657895 | 89 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/model/src/sagemaker_model_component.py | """SageMaker component for create model."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in ... | 4,574 | 34.742188 | 146 | py |
pipelines | pipelines-master/components/aws/sagemaker/model/src/sagemaker_model_spec.py | """Specification for the SageMaker create model component."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable la... | 5,201 | 34.148649 | 173 | py |
pipelines | pipelines-master/components/aws/sagemaker/process/README.md | # SageMaker Processing Kubeflow Pipelines component
## Summary
Component to submit SageMaker Processing jobs directly from a Kubeflow Pipelines workflow.
https://docs.aws.amazon.com/sagemaker/latest/dg/processing-job.html
## Intended Use
For running your data processing workloads, such as feature engineering, data va... | 5,545 | 67.469136 | 541 | md |
pipelines | pipelines-master/components/aws/sagemaker/process/component.yaml | name: SageMaker - Processing Job
description: Perform data pre-processing, post-processing, feature engineering, data
validation, and model evaluation, and interpretation on using SageMaker
inputs:
- {name: region, type: String, description: The region for the SageMaker resource.}
- {name: endpoint_url, type: String,... | 4,949 | 43.196429 | 91 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/process/src/sagemaker_process_component.py | """SageMaker component for process."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writi... | 7,935 | 35.237443 | 187 | py |
pipelines | pipelines-master/components/aws/sagemaker/process/src/sagemaker_process_spec.py | """Specification for the SageMaker processing component."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law ... | 7,038 | 34.730964 | 147 | py |
pipelines | pipelines-master/components/aws/sagemaker/rlestimator/README.md | # SageMaker RLEstimator Kubeflow Pipelines component
## Summary
Component to submit SageMaker RLEstimator (Reinforcement Learning) training jobs directly from a Kubeflow Pipelines workflow.
https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-rl-workflow.html
## Intended Use
For running your data processing work... | 6,774 | 71.849462 | 541 | md |
pipelines | pipelines-master/components/aws/sagemaker/rlestimator/component.yaml | name: SageMaker - RLEstimator Training Job
description: Handle end-to-end training and deployment of custom RLEstimator code.
inputs:
- name: spot_instance
type: Bool
description: Use managed spot training.
default: "False"
- {name: max_wait_time, type: Integer, description: The maximum time in seconds you
ar... | 6,600 | 43.302013 | 93 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/rlestimator/src/sagemaker_rlestimator_component.py | """SageMaker component for RLEstimator."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in w... | 10,816 | 37.910072 | 185 | py |
pipelines | pipelines-master/components/aws/sagemaker/rlestimator/src/sagemaker_rlestimator_spec.py | """Specification for the SageMaker RLEstimator component."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law... | 8,473 | 35.369099 | 144 | py |
pipelines | pipelines-master/components/aws/sagemaker/simulation_job/README.md | # RoboMaker Simulation Job Kubeflow Pipelines component
## Summary
Component to run a RoboMaker Simulation Job from a Kubeflow Pipelines workflow.
https://docs.aws.amazon.com/robomaker/latest/dg/API_CreateSimulationJob.html
## Intended Use
For running your simulation workloads using AWS RoboMaker.
## Runtime Argumen... | 4,311 | 54.282051 | 243 | md |
pipelines | pipelines-master/components/aws/sagemaker/simulation_job/component.yaml | name: RoboMaker - Create Simulation Job
description: Creates a simulation job.
inputs:
- {name: region, type: String, description: The region for the SageMaker resource.}
- {name: endpoint_url, type: String, description: The URL to use when communicating
with the SageMaker service., default: ''}
- {name: assume_rol... | 4,743 | 42.127273 | 95 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/simulation_job/src/robomaker_simulation_job_component.py | """RoboMaker component for creating a simulation job."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ... | 9,610 | 36.988142 | 150 | py |
pipelines | pipelines-master/components/aws/sagemaker/simulation_job/src/robomaker_simulation_job_spec.py | """Specification for the RoboMaker create simulation job component."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 7,053 | 34.094527 | 120 | py |
pipelines | pipelines-master/components/aws/sagemaker/simulation_job_batch/README.md | # RoboMaker Simulation Job Batch Kubeflow Pipelines component
## Summary
Component to run a RoboMaker Simulation Job Batch from a Kubeflow Pipelines workflow.
https://docs.aws.amazon.com/robomaker/latest/dg/API_StartSimulationJobBatch.html
## Intended Use
For running your simulation workloads using AWS RoboMaker.
... | 3,488 | 46.794521 | 261 | md |
pipelines | pipelines-master/components/aws/sagemaker/simulation_job_batch/component.yaml | name: RoboMaker - Create Simulation Job Batch
description: Creates a simulation job batch.
inputs:
- {name: region, type: String, description: The region for the SageMaker resource.}
- {name: endpoint_url, type: String, description: The URL to use when communicating
with the SageMaker service., default: ''}
- {name... | 2,259 | 41.641509 | 89 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/simulation_job_batch/src/robomaker_simulation_job_batch_component.py | """RoboMaker component for creating a simulation job batch."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... | 7,826 | 39.138462 | 155 | py |
pipelines | pipelines-master/components/aws/sagemaker/simulation_job_batch/src/robomaker_simulation_job_batch_spec.py | """Specification for the RoboMaker create simulation job batch component."""
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 3,870 | 33.5625 | 140 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/README.md | ## Requirements
1. [Docker](https://www.docker.com/)
1. [IAM Role](https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html) with a SageMakerFullAccess, RoboMakerFullAccess and AmazonS3FullAccess
1. IAM User credentials with SageMakerFullAccess, RoboMakerFullAccess, AWSCloudFormationFullAccess, IAMFullAcces... | 3,929 | 94.853659 | 355 | md |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/conftest.py | import pytest
import boto3
import kfp
import os
from utils import sagemaker_utils
import utils
from datetime import datetime
from filelock import FileLock
from sagemaker import image_uris
from botocore.config import Config
def pytest_addoption(parser):
parser.addoption(
"--region",
default="us-we... | 8,522 | 31.406844 | 112 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/component_tests/test_batch_transform_component.py | import utils
import os
import pytest
from utils import kfp_client_utils
from utils import minio_utils
from utils import sagemaker_utils
from utils import s3_utils
from utils import argo_utils
@pytest.mark.parametrize(
"test_file_dir",
[
pytest.param(
"resources/config/kmeans-mnist-batch-t... | 4,457 | 33.828125 | 108 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/component_tests/test_deploy_component.py | import pytest
import os
import utils
import json
from utils import kfp_client_utils
from utils import minio_utils
from utils import sagemaker_utils
@pytest.mark.parametrize(
"test_file_dir",
[
pytest.param("resources/config/kmeans-mnist-update-endpoint"),
pytest.param(
"resources... | 3,969 | 36.45283 | 100 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/component_tests/test_groundtruth_component.py | import pytest
import os
import utils
from utils import kfp_client_utils
from utils import sagemaker_utils
from test_workteam_component import create_workteamjob
def create_initial_workteam(
kfp_client, experiment_id, region, sagemaker_client, test_file_dir, download_dir
):
test_params = utils.load_params(
... | 5,372 | 35.80137 | 105 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/component_tests/test_hpo_component.py | import pytest
import os
import json
import utils
from utils import kfp_client_utils
from utils import minio_utils
from utils import sagemaker_utils
@pytest.mark.parametrize(
"test_file_dir",
[pytest.param("resources/config/kmeans-mnist-hpo", marks=pytest.mark.canary_test)],
)
def test_hyperparameter_tuning(
... | 5,076 | 34.503497 | 88 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/component_tests/test_model_component.py | import pytest
import os
import utils
from utils import kfp_client_utils
from utils import minio_utils
from utils import sagemaker_utils
@pytest.mark.parametrize(
"test_file_dir", ["resources/config/kmeans-mnist-model"],
)
def test_createmodel(kfp_client, experiment_id, sagemaker_client, test_file_dir):
down... | 1,715 | 30.2 | 90 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/component_tests/test_processing_component.py | import pytest
import os
import json
import utils
from utils import kfp_client_utils
from utils import minio_utils
from utils import sagemaker_utils
from utils import argo_utils
@pytest.mark.parametrize(
"test_file_dir",
[
pytest.param(
"resources/config/kmeans-algo-mnist-processing",
... | 4,319 | 33.83871 | 108 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/component_tests/test_rlestimator_component.py | import random
import string
import pytest
import os
import utils
from utils import kfp_client_utils
from utils import minio_utils
from utils import sagemaker_utils
from utils import argo_utils
@pytest.mark.parametrize(
"test_file_dir",
[
pytest.param(
"resources/config/rlestimator-trainin... | 4,234 | 32.085938 | 108 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/component_tests/test_robomaker_simulation_app.py | import pytest
import os
import utils
from utils import kfp_client_utils
from utils import minio_utils
from utils import robomaker_utils
from utils import get_s3_data_bucket
def create_simulation_app(kfp_client, experiment_id, creat_app_dir, app_name):
download_dir = utils.mkdir(os.path.join(creat_app_dir + "/gen... | 7,117 | 31.354545 | 88 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/component_tests/test_train_component.py | import pytest
import os
import utils
from utils import kfp_client_utils
from utils import minio_utils
from utils import sagemaker_utils
from utils import argo_utils
@pytest.mark.parametrize(
"test_file_dir",
[
pytest.param(
"resources/config/simple-mnist-training", marks=pytest.mark.canary... | 4,126 | 33.680672 | 108 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/component_tests/test_v2_hosting.py | import pytest
import os
import utils
from utils import kfp_client_utils
from utils import ack_utils
from utils import sagemaker_utils
from utils import minio_utils
import json
@pytest.mark.parametrize(
"test_file_dir",
[
pytest.param(
"resources/config/ack-hosting",
marks=[pyt... | 7,521 | 36.054187 | 120 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/component_tests/test_v2_monitoring_job_definition_component.py | import pytest
import os
import utils
from utils import kfp_client_utils
from utils import ack_utils
from utils import minio_utils
# Testing data quality job definition component and model explainability job definition component
@pytest.mark.parametrize(
"test_file_dir",
[
pytest.param(
"re... | 3,089 | 32.225806 | 97 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/component_tests/test_v2_monitoring_schedule_component.py | import pytest
import os
import utils
from utils import kfp_client_utils
from utils import ack_utils
from utils import minio_utils
FINAL_STATUS = "Scheduled"
def verify_monitoring_schedule_component_outputs(
workflow_json, download_dir, monitoring_schedule_name
):
# Verify component outputs
outputs = {
... | 10,541 | 32.047022 | 87 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/component_tests/test_v2_train_component.py | import pytest
import os
import utils
from utils import kfp_client_utils
from utils import minio_utils
from utils import ack_utils
import ast
import json
@pytest.mark.parametrize(
"test_file_dir",
[
pytest.param(
"resources/config/ack-training-job",
marks=[pytest.mark.canary_tes... | 4,097 | 32.590164 | 88 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/component_tests/test_workteam_component.py | import pytest
import os
import utils
from utils import kfp_client_utils
from utils import sagemaker_utils
from utils import minio_utils
def create_workteamjob(
kfp_client, test_params, experiment_id, region, sagemaker_client, download_dir
):
# Get the account, region specific user_pool and client_id for the S... | 3,052 | 32.549451 | 97 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/ack-hosting-update/config.yaml | PipelineDefinition: resources/definition/update_hosting_v2_pipeline.py
TestName: ack-update-endpoint-test
Timeout: 3600
ExpectedPrediction:
predictions:
- distance_to_cluster: 7.448746204376221
closest_cluster: 2.0
ExpectedEndpointConfig: ept2
Arguments:
region: ((REGION))
execution_role_arn: ((SAGEMAKE... | 877 | 32.769231 | 97 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/ack-hosting/config.yaml | PipelineDefinition: resources/definition/create_hosting_v2_pipeline.py
TestName: ack-endpoint-test
Timeout: 3600
ExpectedPrediction:
predictions:
- distance_to_cluster: 7.448746204376221
closest_cluster: 2.0
Arguments:
region: ((REGION))
execution_role_arn: ((SAGEMAKER_ROLE_ARN))
primary_container:
... | 688 | 33.45 | 97 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/ack-training-job/config.yaml | PipelineDefinition: resources/definition/trainingv2_pipeline.py
TestName: ack-training-job
Timeout: 1500
ExpectedTrainingImage: ((KMEANS_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/kmeans:1
Arguments:
region: ((REGION))
algorithm_specification:
trainingImage: ((KMEANS_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com... | 1,121 | 32 | 84 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/assume-role-processing/config.yaml | PipelineDefinition: resources/definition/processing_pipeline.py
TestName: assume-role-processing
Timeout: 1800
Arguments:
region: ((REGION))
assume_role: ((ASSUME_ROLE_ARN))
job_name: process-mnist-for-kmeans
image: 763104351884.dkr.ecr.((REGION)).amazonaws.com/pytorch-training:1.5.0-cpu-py36-ubuntu16.04
cont... | 1,638 | 33.87234 | 98 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/assume-role-training/config.yaml | PipelineDefinition: resources/definition/training_pipeline.py
TestName: assume-role-training
Timeout: 3600
ExpectedTrainingImage: ((KMEANS_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/kmeans:1
Arguments:
region: ((REGION))
image: ((KMEANS_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/kmeans:1
assume_role: ((ASSUME_R... | 1,037 | 29.529412 | 84 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/create-workteam/config.yaml | PipelineDefinition: resources/definition/workteam_pipeline.py
TestName: create-workteam
Timeout: 3600
Arguments:
region: ((REGION))
team_name: 'test-workteam'
description: 'Team for GroundTruth Integ Test'
user_pool: 'user-pool'
user_groups: 'user-group'
client_id: 'client-id'
| 290 | 25.454545 | 61 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/fsx-mnist-training/config.yaml | PipelineDefinition: resources/definition/training_pipeline.py
TestName: fsx-mnist-training
Timeout: 3600
ExpectedTrainingImage: ((KMEANS_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/kmeans:1
Arguments:
region: ((REGION))
image: ((KMEANS_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/kmeans:1
training_input_mode: File... | 1,146 | 30 | 84 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/image-classification-groundtruth/config.yaml | PipelineDefinition: resources/definition/groundtruth_pipeline.py
TestName: image-classification-groundtruth
Timeout: 300
StatusToCheck: 'running'
Arguments:
region: ((REGION))
role: ((SAGEMAKER_ROLE_ARN))
ground_truth_train_job_name: 'image-labeling'
ground_truth_label_attribute_name: 'category'
ground_truth_... | 1,165 | 49.695652 | 122 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/kmeans-algo-mnist-processing/config.yaml | PipelineDefinition: resources/definition/processing_pipeline.py
TestName: kmeans-algo-mnist-processing
Timeout: 1800
Arguments:
region: ((REGION))
job_name: process-mnist-for-kmeans
image: 763104351884.dkr.ecr.((REGION)).amazonaws.com/pytorch-training:1.5.0-cpu-py36-ubuntu16.04
container_entrypoint:
- pytho... | 1,609 | 34 | 98 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/kmeans-mnist-batch-transform/config.yaml | PipelineDefinition: resources/definition/transform_job_pipeline.py
TestName: kmeans-batch-transform-test
Timeout: 1200
ExpectedOutputFile: valid_data.csv.out
Arguments:
region: ((REGION))
model_name: kmeans-mnist-model
job_name: kmeans-mnist-model
image: ((KMEANS_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/kmea... | 826 | 33.458333 | 101 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/kmeans-mnist-endpoint/config.yaml | PipelineDefinition: resources/definition/create_endpoint_pipeline.py
TestName: kmeans-create-endpoint-test
Timeout: 3600
ExpectedPrediction:
predictions:
- distance_to_cluster: 7.448746204376221
closest_cluster: 2.0
Arguments:
region: ((REGION))
model_name: kmeans-mnist-model
endpoint_config_name: kme... | 728 | 33.714286 | 101 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/kmeans-mnist-hpo/config.yaml | PipelineDefinition: resources/definition/hpo_pipeline.py
TestName: kmeans-mnist-hpo-training
Timeout: 3600
ExpectedTrainingImage: ((KMEANS_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/kmeans:1
Arguments:
region: ((REGION))
algorithm_name: K-Means
training_input_mode: File
static_parameters:
k: "10"
featu... | 1,590 | 26.912281 | 84 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/kmeans-mnist-model/config.yaml | PipelineDefinition: resources/definition/create_model_pipeline.py
TestName: kmeans-create-model-test
Timeout: 300
Arguments:
region: ((REGION))
model_name: kmeans-mnist-model
image: ((KMEANS_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/kmeans:1
model_artifact_url: s3://((DATA_BUCKET))/mnist_kmeans_example/model/... | 413 | 36.636364 | 101 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/kmeans-mnist-update-endpoint/config.yaml | PipelineDefinition: resources/definition/update_endpoint_pipeline.py
TestName: kmeans-update-endpoint-test
Timeout: 7200
ExpectedInstanceType: ml.m5.large
ExpectedPrediction:
predictions:
- distance_to_cluster: 7.448746204376221
closest_cluster: 2.0
Arguments:
region: ((REGION))
model_name: kmeans-mnist... | 834 | 32.4 | 101 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/rlestimator-training/config.yaml | PipelineDefinition: resources/definition/rlestimator_training_job_pipeline.py
TestName: rlestimator-pipeline-training
Timeout: 1500
ExpectedTrainingImage: 462105765813.dkr.ecr.((REGION)).amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-cpu-py36
Arguments:
region: ((REGION))
role: ((SAGEMAKER_ROLE_ARN))
entry... | 691 | 33.6 | 117 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/robomaker-create-simulation-app/config.yaml | PipelineDefinition: resources/definition/robomaker_create_simulation_app_pipeline.py
TestName: robomaker-create-simulation-app-test
Timeout: 300
Arguments:
region: ((REGION))
app_name: robomaker-create-simulation-app-test
sources:
- s3Bucket: ((DATA_BUCKET))
s3Key: "robomaker/simulation_ws.tar"
ar... | 544 | 31.058824 | 84 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/robomaker-delete-simulation-app/config.yaml | PipelineDefinition: resources/definition/robomaker_delete_simulation_app_pipeline.py
TestName: robomaker-delete-simulation-app-test
Timeout: 300
Arguments:
region: ((REGION))
arn: ""
| 187 | 25.857143 | 84 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/robomaker-simulation-job/config.yaml | PipelineDefinition: resources/definition/robomaker_simulation_job_pipeline.py
TestName: robomaker-run-simulation-job-test
Timeout: 600
Arguments:
region: ((REGION))
output_bucket: ((DATA_BUCKET))
output_path: "robomaker-output-key"
max_run: 300
failure_behavior: "Fail"
sim_app_arn:
sim_app_launch_config:
... | 666 | 29.318182 | 77 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/simple-mnist-training/config.yaml | PipelineDefinition: resources/definition/training_pipeline.py
TestName: simple-mnist-training
Timeout: 3600
ExpectedTrainingImage: ((KMEANS_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/kmeans:1
Arguments:
region: ((REGION))
image: ((KMEANS_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/kmeans:1
training_input_mode: F... | 1,003 | 29.424242 | 84 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/spot-sample-pipeline-training/config.yaml | PipelineDefinition: ../../../../../samples/contrib/aws-samples/simple_train_pipeline/training-pipeline.py
TestName: sample-pipeline-training
Timeout: 3600
ExpectedTrainingImage: ((KMEANS_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/kmeans:1
Arguments:
region: ((REGION))
image: ((KMEANS_REGISTRY)).dkr.ecr.((REGION)).... | 924 | 34.576923 | 105 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/v2-monitoring-job-data-quality/config.yaml | PipelineDefinition: resources/definition/data_quality_job_defi_v2_pipeline.py
TestName: v2-data-quality-job-definition
Timeout: 4000
Plural: dataqualityjobdefinitions
JobInputName: data_quality_job_input
ModelImage: ((XGBOOST_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/sagemaker-xgboost:0.90-1-cpu-py3
ModelUrl: s3://((... | 1,478 | 40.083333 | 103 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/v2-monitoring-job-model-bias/config.yaml | PipelineDefinition: resources/definition/model_bias_job_defi_v2_pipeline.py
TestName: v2-model-bias-job-definition
Timeout: 2000
Plural: modelbiasjobdefinitions
JobInputName: model_bias_job_input
ModelImage: ((XGBOOST_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/sagemaker-xgboost:0.90-1-cpu-py3
ModelUrl: s3://((DATA_BUC... | 1,569 | 40.315789 | 98 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/v2-monitoring-job-model-explainability/config.yaml | PipelineDefinition: resources/definition/model_explainability_job_defi_v2_pipeline.py
TestName: v2-model-explainability-job-definition
Timeout: 4000
Plural: modelexplainabilityjobdefinitions
JobInputName: model_explainability_job_input
ModelImage: ((XGBOOST_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/sagemaker-xgboost:... | 1,430 | 42.363636 | 103 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/v2-monitoring-job-model-quality/config.yaml | PipelineDefinition: resources/definition/model_quality_job_defi_v2_pipeline.py
TestName: v2-model-quality-job-definition
Timeout: 2000
Plural: modelqualityjobdefinitions
JobInputName: model_quality_job_input
ModelImage: ((XGBOOST_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/sagemaker-xgboost:0.90-1-cpu-py3
ModelUrl: s3:... | 1,579 | 39.512821 | 98 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/v2-monitoring-schedule-update/config.yaml | PipelineDefinition: resources/definition/monitoring_schedule_update_v2_pipeline.py
TestName: v2-monitoring-schedule-update
Timeout: 4000
Plural: dataqualityjobdefinitions
JobInputName: data_quality_job_input
ModelImage: ((XGBOOST_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/sagemaker-xgboost:0.90-1-cpu-py3
ModelUrl: s3:... | 1,522 | 40.162162 | 103 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/v2-monitoring-schedule/config.yaml | PipelineDefinition: resources/definition/monitoring_schedule_v2_pipeline.py
TestName: v2-monitoring-schedule
Timeout: 4000
ModelImage: ((XGBOOST_REGISTRY)).dkr.ecr.((REGION)).amazonaws.com/sagemaker-xgboost:0.90-1-cpu-py3
ModelUrl: s3://((DATA_BUCKET))/model-monitor/xgboost-churn-model.tar.gz
EndpointCapture: s3://((DA... | 1,549 | 37.75 | 103 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/config/xgboost-mnist-trainingjob-debugger/config.yaml | PipelineDefinition: ../../../../../samples/contrib/aws-samples/sagemaker_debugger_demo/debugger-training-pipeline.py
TestName: xgboost-mnist-trainingjob-debugger
Timeout: 3600
ExpectedTrainingImage: 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:0.90-2-cpu-py3
Arguments:
bucket_name: ((DATA_BUCKET))
... | 354 | 43.375 | 116 | yaml |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/create_endpoint_pipeline.py | import kfp
from kfp import components
from kfp import dsl
sagemaker_model_op = components.load_component_from_file("../../model/component.yaml")
sagemaker_deploy_op = components.load_component_from_file("../../deploy/component.yaml")
@dsl.pipeline(
name="Create Hosting Endpoint in SageMaker",
description="Sa... | 1,583 | 26.789474 | 88 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/create_hosting_v2_pipeline.py | import kfp
from kfp import components
from kfp import dsl
sagemaker_Model_op = components.load_component_from_file("../../Modelv2/component.yaml")
sagemaker_EndpointConfig_op = components.load_component_from_file(
"../../EndpointConfig/component.yaml"
)
sagemaker_Endpoint_op = components.load_component_from_file... | 1,232 | 25.804348 | 88 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/create_model_pipeline.py | import kfp
from kfp import components
from kfp import dsl
sagemaker_model_op = components.load_component_from_file("../../model/component.yaml")
@dsl.pipeline(
name="Create Model in SageMaker", description="SageMaker model component test"
)
def create_model_pipeline(
region="",
endpoint_url="",
image... | 811 | 22.2 | 86 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/data_quality_job_defi_v2_pipeline.py | import kfp
from kfp import components
from kfp import dsl
sagemaker_DataQualityJobDefinition_op = components.load_component_from_file(
"../../DataQualityJobDefinition/component.yaml"
)
@dsl.pipeline(
name="DataQualityJobDefinition",
description="SageMaker DataQualityJobDefinition component",
)
def DataQu... | 1,203 | 29.871795 | 79 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/groundtruth_pipeline.py | import kfp
from kfp import components
from kfp import dsl
sagemaker_gt_op = components.load_component_from_file(
"../../ground_truth/component.yaml"
)
@dsl.pipeline(
name="SageMaker GroundTruth image classification test pipeline",
description="SageMaker GroundTruth image classification test pipeline",
)
... | 1,863 | 31.701754 | 75 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/hpo_pipeline.py | import kfp
from kfp import components
from kfp import dsl
sagemaker_hpo_op = components.load_component_from_file(
"../../hyperparameter_tuning/component.yaml"
)
@dsl.pipeline(
name="SageMaker HyperParameter Tuning", description="SageMaker HPO job test"
)
def hpo_pipeline(
region="",
job_name="",
... | 1,778 | 25.161765 | 80 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/model_bias_job_defi_v2_pipeline.py | import kfp
from kfp import components
from kfp import dsl
sagemaker_ModelBiasJobDefinition_op = components.load_component_from_file(
"../../ModelBiasJobDefinition/component.yaml"
)
@dsl.pipeline(
name="ModelBiasJobDefinition",
description="SageMaker ModelBiasJobDefinition component",
)
def ModelBiasJobDe... | 1,165 | 28.897436 | 77 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/model_explainability_job_defi_v2_pipeline.py | import kfp
from kfp import components
from kfp import dsl
sagemaker_ModelExplainabilityJobDefinition_op = components.load_component_from_file(
"../../ModelExplainabilityJobDefinition/component.yaml"
)
@dsl.pipeline(
name="ModelExplainabilityJobDefinition",
description="SageMaker ModelExplainabilityJobDef... | 1,227 | 32.189189 | 87 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/model_quality_job_defi_v2_pipeline.py | import kfp
from kfp import components
from kfp import dsl
sagemaker_ModelQualityJobDefinition_op = components.load_component_from_file(
"../../ModelQualityJobDefinition/component.yaml"
)
@dsl.pipeline(
name="ModelQualityJobDefinition",
description="SageMaker ModelQualityJobDefinition component",
)
def Mo... | 1,284 | 30.341463 | 80 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/monitoring_schedule_update_v2_pipeline.py | import kfp
from kfp import components
from kfp import dsl
sagemaker_MonitoringSchedule_op = components.load_component_from_file(
"../../MonitoringSchedule/component.yaml"
)
sagemaker_DataQualityJobDefinition_op = components.load_component_from_file(
"../../DataQualityJobDefinition/component.yaml"
)
@dsl.pipe... | 1,866 | 31.189655 | 83 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/monitoring_schedule_v2_pipeline.py | import kfp
from kfp import components
from kfp import dsl
sagemaker_MonitoringSchedule_op = components.load_component_from_file(
"../../MonitoringSchedule/component.yaml"
)
sagemaker_ModelBiasJobDefinition_op = components.load_component_from_file(
"../../ModelBiasJobDefinition/component.yaml"
)
@dsl.pipeline... | 1,471 | 30.319149 | 83 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/processing_pipeline.py | import kfp
from kfp import components
from kfp import dsl
sagemaker_process_op = components.load_component_from_file(
"../../process/component.yaml"
)
@dsl.pipeline(name="SageMaker Processing", description="SageMaker processing job test")
def processing_pipeline(
region="",
job_name="",
image="",
... | 1,280 | 24.117647 | 87 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/rlestimator_training_job_pipeline.py | import kfp
from kfp import components
from kfp import dsl
rlestimator_training_job_op = components.load_component_from_file(
"../../rlestimator/component.yaml"
)
@dsl.pipeline(
name="RLEstimator Toolkit & Framework Pipeline test",
description="RLEstimator training job test where the AWS Docker image is a... | 1,362 | 25.211538 | 137 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/robomaker_create_simulation_app_pipeline.py | import kfp
from kfp import components
from kfp import dsl
robomaker_create_sim_app_op = components.load_component_from_file(
"../../create_simulation_app/component.yaml"
)
@dsl.pipeline(
name="RoboMaker Create Simulation App",
description="RoboMaker Create Simulation App test pipeline",
)
def robomaker_c... | 1,181 | 26.488372 | 66 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/robomaker_delete_simulation_app_pipeline.py | import kfp
from kfp import components
from kfp import dsl
robomaker_delete_sim_app_op = components.load_component_from_file(
"../../delete_simulation_app/component.yaml"
)
@dsl.pipeline(
name="RoboMaker Delete Simulation App",
description="RoboMaker Delete Simulation App test pipeline",
)
def robomaker_d... | 582 | 20.592593 | 66 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/robomaker_simulation_job_pipeline.py | import kfp
from kfp import components
from kfp import dsl
robomaker_sim_job_op = components.load_component_from_file(
"../../simulation_job/component.yaml"
)
@dsl.pipeline(
name="Run RoboMaker Simulation Job",
description="RoboMaker Simulation Job test pipeline",
)
def robomaker_simulation_job_test(
... | 1,043 | 23.27907 | 86 | py |
pipelines | pipelines-master/components/aws/sagemaker/tests/integration_tests/resources/definition/training_pipeline.py | import kfp
from kfp import components
from kfp import dsl
sagemaker_train_op = components.load_component_from_file("../../train/component.yaml")
@dsl.pipeline(name="SageMaker Training", description="SageMaker training job test")
def training_pipeline(
region="",
endpoint_url="",
image="",
job_name=""... | 1,734 | 26.539683 | 86 | py |