Fix Estimator role expansion by iquintero · Pull Request #68 · aws/sagemaker-python-sdk

iquintero · 2018-02-01T18:57:37Z

Instead of manually constructing the role ARN, use the IAM boto client
to do it. This properly expands service-roles and regular roles.

This fixes#43

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

mvsusp

@iquintero, can we write a unit test for that?

iquintero · 2018-02-02T22:10:21Z

It doesn't really make sense to have a unit test for this, as I would have to mock the boto call to IAM and at that point there is nothing else left to test. Also the ARN is not being manually crafted anymore so we should be able to trust that boto is doing the right thing here.

mvsusp · 2018-02-02T22:49:22Z

Agreed.

* Add data_type to hyperparameters (aws#54) When we describe a training job the data type of the hyper parameters is lost because we use a dict[str, str]. This adds a new field to Hyperparameter so that we can convert the datatypes at runtime. instead of validating with isinstance(), we cast the hp value to the type it is meant to be. This enforces a "strongly typed" value. When we deserialize from the API string responses it becomes easier to deal with too. * Add wrapper for LDA. (aws#56) Update CHANGELOG and bump the version number. * Add support for async fit() (aws#59) when calling fit(wait=False) it will return immediately. The training job will carry on even if the process exits. by using attach() the estimator can be retrieved by providing the training job name. _prepare_init_params_from_job_description() is now a classmethod instead of being a static method. Each class is responsible to implement their specific logic to convert a training job description into arguments that can be passed to its own __init__() * Fix Estimator role expansion (aws#68) Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles. * Add FM and LDA to the documentation. (aws#66) * Fix description of an argument of sagemaker.session.train (aws#69) * Fix description of an argument of sagemaker.session.train 'input_config' should be an array which has channel objects. * Add a link to the botocore docs * Use 'list' instead of 'array' in the description * Add ntm algorithm with doc, unit tests, integ tests (aws#73) * JSON serializer: predictor.predict accepts dictionaries (aws#62) Add support for serializing python dictionaries to json Add prediction with dictionary in tf iris integ test * Fixing timeouts for PCA async integration test. (aws#78) Execute tf_cifar test without logs to eliminate delay to detect that job has finished. * Fixes in LinearLearner and unit tests addition. (aws#77) * Print out billable seconds after training completes (aws#30) * Added: print out billable seconds after training completes * Fixed: test_session.py to pass unit tests * Fixed: removed offending tzlocal() * Use sagemaker_timestamp when creating endpoint names in integration tests. (aws#81) * Support TensorFlow-1.5.0 and MXNet-1.0.0 (aws#82) * Update .gitignore to ignore pytest_cache. * Support TensorFlow-1.5.0 and MXNet-1.0.0 * Update and refactor tests. Add tests for fw_utils. * Fix typo. * Update changelog for 1.1.0 (aws#85)

Updated: XGBoost direct marketing notebook markdown at the end

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero · 2018-02-01T18:57:37Z

Instead of manually constructing the role ARN, use the IAM boto client
to do it. This properly expands service-roles and regular roles.

This fixes#43

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

mvsusp

@iquintero, can we write a unit test for that?

iquintero · 2018-02-02T22:10:21Z

It doesn't really make sense to have a unit test for this, as I would have to mock the boto call to IAM and at that point there is nothing else left to test. Also the ARN is not being manually crafted anymore so we should be able to trust that boto is doing the right thing here.

mvsusp · 2018-02-02T22:49:22Z

Agreed.

* Add data_type to hyperparameters (aws#54) When we describe a training job the data type of the hyper parameters is lost because we use a dict[str, str]. This adds a new field to Hyperparameter so that we can convert the datatypes at runtime. instead of validating with isinstance(), we cast the hp value to the type it is meant to be. This enforces a "strongly typed" value. When we deserialize from the API string responses it becomes easier to deal with too. * Add wrapper for LDA. (aws#56) Update CHANGELOG and bump the version number. * Add support for async fit() (aws#59) when calling fit(wait=False) it will return immediately. The training job will carry on even if the process exits. by using attach() the estimator can be retrieved by providing the training job name. _prepare_init_params_from_job_description() is now a classmethod instead of being a static method. Each class is responsible to implement their specific logic to convert a training job description into arguments that can be passed to its own __init__() * Fix Estimator role expansion (aws#68) Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles. * Add FM and LDA to the documentation. (aws#66) * Fix description of an argument of sagemaker.session.train (aws#69) * Fix description of an argument of sagemaker.session.train 'input_config' should be an array which has channel objects. * Add a link to the botocore docs * Use 'list' instead of 'array' in the description * Add ntm algorithm with doc, unit tests, integ tests (aws#73) * JSON serializer: predictor.predict accepts dictionaries (aws#62) Add support for serializing python dictionaries to json Add prediction with dictionary in tf iris integ test * Fixing timeouts for PCA async integration test. (aws#78) Execute tf_cifar test without logs to eliminate delay to detect that job has finished. * Fixes in LinearLearner and unit tests addition. (aws#77) * Print out billable seconds after training completes (aws#30) * Added: print out billable seconds after training completes * Fixed: test_session.py to pass unit tests * Fixed: removed offending tzlocal() * Use sagemaker_timestamp when creating endpoint names in integration tests. (aws#81) * Support TensorFlow-1.5.0 and MXNet-1.0.0 (aws#82) * Update .gitignore to ignore pytest_cache. * Support TensorFlow-1.5.0 and MXNet-1.0.0 * Update and refactor tests. Add tests for fw_utils. * Fix typo. * Update changelog for 1.1.0 (aws#85)

Updated: XGBoost direct marketing notebook markdown at the end

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero · 2018-02-01T18:57:37Z

Instead of manually constructing the role ARN, use the IAM boto client
to do it. This properly expands service-roles and regular roles.

This fixes#43

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

mvsusp

@iquintero, can we write a unit test for that?

iquintero · 2018-02-02T22:10:21Z

It doesn't really make sense to have a unit test for this, as I would have to mock the boto call to IAM and at that point there is nothing else left to test. Also the ARN is not being manually crafted anymore so we should be able to trust that boto is doing the right thing here.

mvsusp · 2018-02-02T22:49:22Z

Agreed.

* Add data_type to hyperparameters (aws#54) When we describe a training job the data type of the hyper parameters is lost because we use a dict[str, str]. This adds a new field to Hyperparameter so that we can convert the datatypes at runtime. instead of validating with isinstance(), we cast the hp value to the type it is meant to be. This enforces a "strongly typed" value. When we deserialize from the API string responses it becomes easier to deal with too. * Add wrapper for LDA. (aws#56) Update CHANGELOG and bump the version number. * Add support for async fit() (aws#59) when calling fit(wait=False) it will return immediately. The training job will carry on even if the process exits. by using attach() the estimator can be retrieved by providing the training job name. _prepare_init_params_from_job_description() is now a classmethod instead of being a static method. Each class is responsible to implement their specific logic to convert a training job description into arguments that can be passed to its own __init__() * Fix Estimator role expansion (aws#68) Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles. * Add FM and LDA to the documentation. (aws#66) * Fix description of an argument of sagemaker.session.train (aws#69) * Fix description of an argument of sagemaker.session.train 'input_config' should be an array which has channel objects. * Add a link to the botocore docs * Use 'list' instead of 'array' in the description * Add ntm algorithm with doc, unit tests, integ tests (aws#73) * JSON serializer: predictor.predict accepts dictionaries (aws#62) Add support for serializing python dictionaries to json Add prediction with dictionary in tf iris integ test * Fixing timeouts for PCA async integration test. (aws#78) Execute tf_cifar test without logs to eliminate delay to detect that job has finished. * Fixes in LinearLearner and unit tests addition. (aws#77) * Print out billable seconds after training completes (aws#30) * Added: print out billable seconds after training completes * Fixed: test_session.py to pass unit tests * Fixed: removed offending tzlocal() * Use sagemaker_timestamp when creating endpoint names in integration tests. (aws#81) * Support TensorFlow-1.5.0 and MXNet-1.0.0 (aws#82) * Update .gitignore to ignore pytest_cache. * Support TensorFlow-1.5.0 and MXNet-1.0.0 * Update and refactor tests. Add tests for fw_utils. * Fix typo. * Update changelog for 1.1.0 (aws#85)

Updated: XGBoost direct marketing notebook markdown at the end

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero · 2018-02-01T18:57:37Z

Instead of manually constructing the role ARN, use the IAM boto client
to do it. This properly expands service-roles and regular roles.

This fixes#43

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

mvsusp

@iquintero, can we write a unit test for that?

iquintero · 2018-02-02T22:10:21Z

It doesn't really make sense to have a unit test for this, as I would have to mock the boto call to IAM and at that point there is nothing else left to test. Also the ARN is not being manually crafted anymore so we should be able to trust that boto is doing the right thing here.

mvsusp · 2018-02-02T22:49:22Z

Agreed.

* Add data_type to hyperparameters (aws#54) When we describe a training job the data type of the hyper parameters is lost because we use a dict[str, str]. This adds a new field to Hyperparameter so that we can convert the datatypes at runtime. instead of validating with isinstance(), we cast the hp value to the type it is meant to be. This enforces a "strongly typed" value. When we deserialize from the API string responses it becomes easier to deal with too. * Add wrapper for LDA. (aws#56) Update CHANGELOG and bump the version number. * Add support for async fit() (aws#59) when calling fit(wait=False) it will return immediately. The training job will carry on even if the process exits. by using attach() the estimator can be retrieved by providing the training job name. _prepare_init_params_from_job_description() is now a classmethod instead of being a static method. Each class is responsible to implement their specific logic to convert a training job description into arguments that can be passed to its own __init__() * Fix Estimator role expansion (aws#68) Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles. * Add FM and LDA to the documentation. (aws#66) * Fix description of an argument of sagemaker.session.train (aws#69) * Fix description of an argument of sagemaker.session.train 'input_config' should be an array which has channel objects. * Add a link to the botocore docs * Use 'list' instead of 'array' in the description * Add ntm algorithm with doc, unit tests, integ tests (aws#73) * JSON serializer: predictor.predict accepts dictionaries (aws#62) Add support for serializing python dictionaries to json Add prediction with dictionary in tf iris integ test * Fixing timeouts for PCA async integration test. (aws#78) Execute tf_cifar test without logs to eliminate delay to detect that job has finished. * Fixes in LinearLearner and unit tests addition. (aws#77) * Print out billable seconds after training completes (aws#30) * Added: print out billable seconds after training completes * Fixed: test_session.py to pass unit tests * Fixed: removed offending tzlocal() * Use sagemaker_timestamp when creating endpoint names in integration tests. (aws#81) * Support TensorFlow-1.5.0 and MXNet-1.0.0 (aws#82) * Update .gitignore to ignore pytest_cache. * Support TensorFlow-1.5.0 and MXNet-1.0.0 * Update and refactor tests. Add tests for fw_utils. * Fix typo. * Update changelog for 1.1.0 (aws#85)

Updated: XGBoost direct marketing notebook markdown at the end

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero · 2018-02-01T18:57:37Z

Instead of manually constructing the role ARN, use the IAM boto client
to do it. This properly expands service-roles and regular roles.

This fixes#43

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

mvsusp

@iquintero, can we write a unit test for that?

iquintero · 2018-02-02T22:10:21Z

It doesn't really make sense to have a unit test for this, as I would have to mock the boto call to IAM and at that point there is nothing else left to test. Also the ARN is not being manually crafted anymore so we should be able to trust that boto is doing the right thing here.

mvsusp · 2018-02-02T22:49:22Z

Agreed.

* Add data_type to hyperparameters (aws#54) When we describe a training job the data type of the hyper parameters is lost because we use a dict[str, str]. This adds a new field to Hyperparameter so that we can convert the datatypes at runtime. instead of validating with isinstance(), we cast the hp value to the type it is meant to be. This enforces a "strongly typed" value. When we deserialize from the API string responses it becomes easier to deal with too. * Add wrapper for LDA. (aws#56) Update CHANGELOG and bump the version number. * Add support for async fit() (aws#59) when calling fit(wait=False) it will return immediately. The training job will carry on even if the process exits. by using attach() the estimator can be retrieved by providing the training job name. _prepare_init_params_from_job_description() is now a classmethod instead of being a static method. Each class is responsible to implement their specific logic to convert a training job description into arguments that can be passed to its own __init__() * Fix Estimator role expansion (aws#68) Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles. * Add FM and LDA to the documentation. (aws#66) * Fix description of an argument of sagemaker.session.train (aws#69) * Fix description of an argument of sagemaker.session.train 'input_config' should be an array which has channel objects. * Add a link to the botocore docs * Use 'list' instead of 'array' in the description * Add ntm algorithm with doc, unit tests, integ tests (aws#73) * JSON serializer: predictor.predict accepts dictionaries (aws#62) Add support for serializing python dictionaries to json Add prediction with dictionary in tf iris integ test * Fixing timeouts for PCA async integration test. (aws#78) Execute tf_cifar test without logs to eliminate delay to detect that job has finished. * Fixes in LinearLearner and unit tests addition. (aws#77) * Print out billable seconds after training completes (aws#30) * Added: print out billable seconds after training completes * Fixed: test_session.py to pass unit tests * Fixed: removed offending tzlocal() * Use sagemaker_timestamp when creating endpoint names in integration tests. (aws#81) * Support TensorFlow-1.5.0 and MXNet-1.0.0 (aws#82) * Update .gitignore to ignore pytest_cache. * Support TensorFlow-1.5.0 and MXNet-1.0.0 * Update and refactor tests. Add tests for fw_utils. * Fix typo. * Update changelog for 1.1.0 (aws#85)

Updated: XGBoost direct marketing notebook markdown at the end

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero · 2018-02-01T18:57:37Z

Instead of manually constructing the role ARN, use the IAM boto client
to do it. This properly expands service-roles and regular roles.

This fixes#43

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

mvsusp

@iquintero, can we write a unit test for that?

iquintero · 2018-02-02T22:10:21Z

It doesn't really make sense to have a unit test for this, as I would have to mock the boto call to IAM and at that point there is nothing else left to test. Also the ARN is not being manually crafted anymore so we should be able to trust that boto is doing the right thing here.

mvsusp · 2018-02-02T22:49:22Z

Agreed.

* Add data_type to hyperparameters (aws#54) When we describe a training job the data type of the hyper parameters is lost because we use a dict[str, str]. This adds a new field to Hyperparameter so that we can convert the datatypes at runtime. instead of validating with isinstance(), we cast the hp value to the type it is meant to be. This enforces a "strongly typed" value. When we deserialize from the API string responses it becomes easier to deal with too. * Add wrapper for LDA. (aws#56) Update CHANGELOG and bump the version number. * Add support for async fit() (aws#59) when calling fit(wait=False) it will return immediately. The training job will carry on even if the process exits. by using attach() the estimator can be retrieved by providing the training job name. _prepare_init_params_from_job_description() is now a classmethod instead of being a static method. Each class is responsible to implement their specific logic to convert a training job description into arguments that can be passed to its own __init__() * Fix Estimator role expansion (aws#68) Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles. * Add FM and LDA to the documentation. (aws#66) * Fix description of an argument of sagemaker.session.train (aws#69) * Fix description of an argument of sagemaker.session.train 'input_config' should be an array which has channel objects. * Add a link to the botocore docs * Use 'list' instead of 'array' in the description * Add ntm algorithm with doc, unit tests, integ tests (aws#73) * JSON serializer: predictor.predict accepts dictionaries (aws#62) Add support for serializing python dictionaries to json Add prediction with dictionary in tf iris integ test * Fixing timeouts for PCA async integration test. (aws#78) Execute tf_cifar test without logs to eliminate delay to detect that job has finished. * Fixes in LinearLearner and unit tests addition. (aws#77) * Print out billable seconds after training completes (aws#30) * Added: print out billable seconds after training completes * Fixed: test_session.py to pass unit tests * Fixed: removed offending tzlocal() * Use sagemaker_timestamp when creating endpoint names in integration tests. (aws#81) * Support TensorFlow-1.5.0 and MXNet-1.0.0 (aws#82) * Update .gitignore to ignore pytest_cache. * Support TensorFlow-1.5.0 and MXNet-1.0.0 * Update and refactor tests. Add tests for fw_utils. * Fix typo. * Update changelog for 1.1.0 (aws#85)

Updated: XGBoost direct marketing notebook markdown at the end

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero · 2018-02-01T18:57:37Z

Instead of manually constructing the role ARN, use the IAM boto client
to do it. This properly expands service-roles and regular roles.

This fixes#43

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

mvsusp

@iquintero, can we write a unit test for that?

iquintero · 2018-02-02T22:10:21Z

It doesn't really make sense to have a unit test for this, as I would have to mock the boto call to IAM and at that point there is nothing else left to test. Also the ARN is not being manually crafted anymore so we should be able to trust that boto is doing the right thing here.

mvsusp · 2018-02-02T22:49:22Z

Agreed.

* Add data_type to hyperparameters (aws#54) When we describe a training job the data type of the hyper parameters is lost because we use a dict[str, str]. This adds a new field to Hyperparameter so that we can convert the datatypes at runtime. instead of validating with isinstance(), we cast the hp value to the type it is meant to be. This enforces a "strongly typed" value. When we deserialize from the API string responses it becomes easier to deal with too. * Add wrapper for LDA. (aws#56) Update CHANGELOG and bump the version number. * Add support for async fit() (aws#59) when calling fit(wait=False) it will return immediately. The training job will carry on even if the process exits. by using attach() the estimator can be retrieved by providing the training job name. _prepare_init_params_from_job_description() is now a classmethod instead of being a static method. Each class is responsible to implement their specific logic to convert a training job description into arguments that can be passed to its own __init__() * Fix Estimator role expansion (aws#68) Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles. * Add FM and LDA to the documentation. (aws#66) * Fix description of an argument of sagemaker.session.train (aws#69) * Fix description of an argument of sagemaker.session.train 'input_config' should be an array which has channel objects. * Add a link to the botocore docs * Use 'list' instead of 'array' in the description * Add ntm algorithm with doc, unit tests, integ tests (aws#73) * JSON serializer: predictor.predict accepts dictionaries (aws#62) Add support for serializing python dictionaries to json Add prediction with dictionary in tf iris integ test * Fixing timeouts for PCA async integration test. (aws#78) Execute tf_cifar test without logs to eliminate delay to detect that job has finished. * Fixes in LinearLearner and unit tests addition. (aws#77) * Print out billable seconds after training completes (aws#30) * Added: print out billable seconds after training completes * Fixed: test_session.py to pass unit tests * Fixed: removed offending tzlocal() * Use sagemaker_timestamp when creating endpoint names in integration tests. (aws#81) * Support TensorFlow-1.5.0 and MXNet-1.0.0 (aws#82) * Update .gitignore to ignore pytest_cache. * Support TensorFlow-1.5.0 and MXNet-1.0.0 * Update and refactor tests. Add tests for fw_utils. * Fix typo. * Update changelog for 1.1.0 (aws#85)

Updated: XGBoost direct marketing notebook markdown at the end

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero · 2018-02-01T18:57:37Z

Instead of manually constructing the role ARN, use the IAM boto client
to do it. This properly expands service-roles and regular roles.

This fixes#43

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

mvsusp

@iquintero, can we write a unit test for that?

iquintero · 2018-02-02T22:10:21Z

It doesn't really make sense to have a unit test for this, as I would have to mock the boto call to IAM and at that point there is nothing else left to test. Also the ARN is not being manually crafted anymore so we should be able to trust that boto is doing the right thing here.

mvsusp · 2018-02-02T22:49:22Z

Agreed.

* Add data_type to hyperparameters (aws#54) When we describe a training job the data type of the hyper parameters is lost because we use a dict[str, str]. This adds a new field to Hyperparameter so that we can convert the datatypes at runtime. instead of validating with isinstance(), we cast the hp value to the type it is meant to be. This enforces a "strongly typed" value. When we deserialize from the API string responses it becomes easier to deal with too. * Add wrapper for LDA. (aws#56) Update CHANGELOG and bump the version number. * Add support for async fit() (aws#59) when calling fit(wait=False) it will return immediately. The training job will carry on even if the process exits. by using attach() the estimator can be retrieved by providing the training job name. _prepare_init_params_from_job_description() is now a classmethod instead of being a static method. Each class is responsible to implement their specific logic to convert a training job description into arguments that can be passed to its own __init__() * Fix Estimator role expansion (aws#68) Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles. * Add FM and LDA to the documentation. (aws#66) * Fix description of an argument of sagemaker.session.train (aws#69) * Fix description of an argument of sagemaker.session.train 'input_config' should be an array which has channel objects. * Add a link to the botocore docs * Use 'list' instead of 'array' in the description * Add ntm algorithm with doc, unit tests, integ tests (aws#73) * JSON serializer: predictor.predict accepts dictionaries (aws#62) Add support for serializing python dictionaries to json Add prediction with dictionary in tf iris integ test * Fixing timeouts for PCA async integration test. (aws#78) Execute tf_cifar test without logs to eliminate delay to detect that job has finished. * Fixes in LinearLearner and unit tests addition. (aws#77) * Print out billable seconds after training completes (aws#30) * Added: print out billable seconds after training completes * Fixed: test_session.py to pass unit tests * Fixed: removed offending tzlocal() * Use sagemaker_timestamp when creating endpoint names in integration tests. (aws#81) * Support TensorFlow-1.5.0 and MXNet-1.0.0 (aws#82) * Update .gitignore to ignore pytest_cache. * Support TensorFlow-1.5.0 and MXNet-1.0.0 * Update and refactor tests. Add tests for fw_utils. * Fix typo. * Update changelog for 1.1.0 (aws#85)

Updated: XGBoost direct marketing notebook markdown at the end

Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

Fix Estimator role expansion
58d1bda
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero requested a review from owen-t February 1, 2018 18:57

mvsusp reviewed Feb 2, 2018
View reviewed changes

mvsusp approved these changes Feb 2, 2018
View reviewed changes

iquintero merged commit b45d79c into aws:masterFeb 2, 2018

iquintero deleted the service_role branch April 2, 2018 00:05

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#68from awslabs/arpin_xgb_dm_fix
36db30d
Updated: XGBoost direct marketing notebook markdown at the end

Evan-W-ang added a commit to Evan-W-ang/sagemaker-python-sdk that referenced this pull request Jun 8, 2026
Fix Estimator role expansion (aws#68)
7a5b5d7
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

Fix Estimator role expansion
58d1bda
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero requested a review from owen-t February 1, 2018 18:57

mvsusp reviewed Feb 2, 2018
View reviewed changes

mvsusp approved these changes Feb 2, 2018
View reviewed changes

iquintero merged commit b45d79c into aws:masterFeb 2, 2018

iquintero deleted the service_role branch April 2, 2018 00:05

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#68from awslabs/arpin_xgb_dm_fix
36db30d
Updated: XGBoost direct marketing notebook markdown at the end

Evan-W-ang added a commit to Evan-W-ang/sagemaker-python-sdk that referenced this pull request Jun 8, 2026
Fix Estimator role expansion (aws#68)
7a5b5d7
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

Fix Estimator role expansion
58d1bda
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero requested a review from owen-t February 1, 2018 18:57

mvsusp reviewed Feb 2, 2018
View reviewed changes

mvsusp approved these changes Feb 2, 2018
View reviewed changes

iquintero merged commit b45d79c into aws:masterFeb 2, 2018

iquintero deleted the service_role branch April 2, 2018 00:05

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#68from awslabs/arpin_xgb_dm_fix
36db30d
Updated: XGBoost direct marketing notebook markdown at the end

Evan-W-ang added a commit to Evan-W-ang/sagemaker-python-sdk that referenced this pull request Jun 8, 2026
Fix Estimator role expansion (aws#68)
7a5b5d7
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

Fix Estimator role expansion
58d1bda
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero requested a review from owen-t February 1, 2018 18:57

mvsusp reviewed Feb 2, 2018
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mvsusp approved these changes Feb 2, 2018
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iquintero merged commit b45d79c into aws:masterFeb 2, 2018

iquintero deleted the service_role branch April 2, 2018 00:05

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#68from awslabs/arpin_xgb_dm_fix
36db30d
Updated: XGBoost direct marketing notebook markdown at the end

Evan-W-ang added a commit to Evan-W-ang/sagemaker-python-sdk that referenced this pull request Jun 8, 2026
Fix Estimator role expansion (aws#68)
7a5b5d7
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

Fix Estimator role expansion
58d1bda
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero requested a review from owen-t February 1, 2018 18:57

mvsusp reviewed Feb 2, 2018
View reviewed changes

mvsusp approved these changes Feb 2, 2018
View reviewed changes

iquintero merged commit b45d79c into aws:masterFeb 2, 2018

iquintero deleted the service_role branch April 2, 2018 00:05

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#68from awslabs/arpin_xgb_dm_fix
36db30d
Updated: XGBoost direct marketing notebook markdown at the end

Evan-W-ang added a commit to Evan-W-ang/sagemaker-python-sdk that referenced this pull request Jun 8, 2026
Fix Estimator role expansion (aws#68)
7a5b5d7
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

Fix Estimator role expansion
58d1bda
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero requested a review from owen-t February 1, 2018 18:57

mvsusp reviewed Feb 2, 2018
View reviewed changes

mvsusp approved these changes Feb 2, 2018
View reviewed changes

iquintero merged commit b45d79c into aws:masterFeb 2, 2018

iquintero deleted the service_role branch April 2, 2018 00:05

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#68from awslabs/arpin_xgb_dm_fix
36db30d
Updated: XGBoost direct marketing notebook markdown at the end

Evan-W-ang added a commit to Evan-W-ang/sagemaker-python-sdk that referenced this pull request Jun 8, 2026
Fix Estimator role expansion (aws#68)
7a5b5d7
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

Fix Estimator role expansion
58d1bda
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero requested a review from owen-t February 1, 2018 18:57

mvsusp reviewed Feb 2, 2018
View reviewed changes

mvsusp approved these changes Feb 2, 2018
View reviewed changes

iquintero merged commit b45d79c into aws:masterFeb 2, 2018

iquintero deleted the service_role branch April 2, 2018 00:05

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#68from awslabs/arpin_xgb_dm_fix
36db30d
Updated: XGBoost direct marketing notebook markdown at the end

Evan-W-ang added a commit to Evan-W-ang/sagemaker-python-sdk that referenced this pull request Jun 8, 2026
Fix Estimator role expansion (aws#68)
7a5b5d7
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

Fix Estimator role expansion
58d1bda
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

iquintero requested a review from owen-t February 1, 2018 18:57

mvsusp reviewed Feb 2, 2018
View reviewed changes

mvsusp approved these changes Feb 2, 2018
View reviewed changes

iquintero merged commit b45d79c into aws:masterFeb 2, 2018

iquintero deleted the service_role branch April 2, 2018 00:05

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#68from awslabs/arpin_xgb_dm_fix
36db30d
Updated: XGBoost direct marketing notebook markdown at the end

Evan-W-ang added a commit to Evan-W-ang/sagemaker-python-sdk that referenced this pull request Jun 8, 2026
Fix Estimator role expansion (aws#68)
7a5b5d7
Instead of manually constructing the role ARN, use the IAM boto client to do it. This properly expands service-roles and regular roles.

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