Fix description of an argument of sagemaker.session.train by shotarok · Pull Request #69 · aws/sagemaker-python-sdk

shotarok · 2018-02-02T08:40:46Z

Fix description of an argument of sagemaker.session.train. input_config should be an array which has channel objects. The description of input_config is taken from https://botocore.readthedocs.io/en/latest/reference/services/sagemaker.html#SageMaker.Client.create_training_job.

'input_config' should be an array which has channel objects.

laurenyu

Nice catch - thanks for submitting a PR!

laurenyu · 2018-02-02T23:04:38Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source.


Could you add a link to the botocore docs?

There are no links to botocore docs in this module. How about putting a link to ChannelAPI document like session.py#L744?

I meant the link you referenced in your PR description - since there's more information there about InputDataConfig, I think it'd be nice to make it clear where to find more information. A link to the Channel API doc would be a nice addition as well

I see. I added the link to the description in 3671efe.

winstonaws · 2018-02-06T18:12:24Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source. Please refer to


Should be "A list of Channel objects". "Array" in python actually refers to a different type: https://docs.python.org/3/library/array.html

@winstonaws Thanks. I fixed it in a7178c3.

* 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)

Removed: README from xgboost direct marketing

* 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

shotarok · 2018-02-02T08:40:46Z

Fix description of an argument of sagemaker.session.train. input_config should be an array which has channel objects. The description of input_config is taken from https://botocore.readthedocs.io/en/latest/reference/services/sagemaker.html#SageMaker.Client.create_training_job.

'input_config' should be an array which has channel objects.

laurenyu

Nice catch - thanks for submitting a PR!

laurenyu · 2018-02-02T23:04:38Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source.


Could you add a link to the botocore docs?

There are no links to botocore docs in this module. How about putting a link to ChannelAPI document like session.py#L744?

I meant the link you referenced in your PR description - since there's more information there about InputDataConfig, I think it'd be nice to make it clear where to find more information. A link to the Channel API doc would be a nice addition as well

I see. I added the link to the description in 3671efe.

winstonaws · 2018-02-06T18:12:24Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source. Please refer to


Should be "A list of Channel objects". "Array" in python actually refers to a different type: https://docs.python.org/3/library/array.html

@winstonaws Thanks. I fixed it in a7178c3.

* 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)

Removed: README from xgboost direct marketing

* 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

shotarok · 2018-02-02T08:40:46Z

Fix description of an argument of sagemaker.session.train. input_config should be an array which has channel objects. The description of input_config is taken from https://botocore.readthedocs.io/en/latest/reference/services/sagemaker.html#SageMaker.Client.create_training_job.

'input_config' should be an array which has channel objects.

laurenyu

Nice catch - thanks for submitting a PR!

laurenyu · 2018-02-02T23:04:38Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source.


Could you add a link to the botocore docs?

There are no links to botocore docs in this module. How about putting a link to ChannelAPI document like session.py#L744?

I meant the link you referenced in your PR description - since there's more information there about InputDataConfig, I think it'd be nice to make it clear where to find more information. A link to the Channel API doc would be a nice addition as well

I see. I added the link to the description in 3671efe.

winstonaws · 2018-02-06T18:12:24Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source. Please refer to


Should be "A list of Channel objects". "Array" in python actually refers to a different type: https://docs.python.org/3/library/array.html

@winstonaws Thanks. I fixed it in a7178c3.

* 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)

Removed: README from xgboost direct marketing

* 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

shotarok · 2018-02-02T08:40:46Z

Fix description of an argument of sagemaker.session.train. input_config should be an array which has channel objects. The description of input_config is taken from https://botocore.readthedocs.io/en/latest/reference/services/sagemaker.html#SageMaker.Client.create_training_job.

'input_config' should be an array which has channel objects.

laurenyu

Nice catch - thanks for submitting a PR!

laurenyu · 2018-02-02T23:04:38Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source.


Could you add a link to the botocore docs?

There are no links to botocore docs in this module. How about putting a link to ChannelAPI document like session.py#L744?

I meant the link you referenced in your PR description - since there's more information there about InputDataConfig, I think it'd be nice to make it clear where to find more information. A link to the Channel API doc would be a nice addition as well

I see. I added the link to the description in 3671efe.

winstonaws · 2018-02-06T18:12:24Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source. Please refer to


Should be "A list of Channel objects". "Array" in python actually refers to a different type: https://docs.python.org/3/library/array.html

@winstonaws Thanks. I fixed it in a7178c3.

* 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)

Removed: README from xgboost direct marketing

* 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

shotarok · 2018-02-02T08:40:46Z

Fix description of an argument of sagemaker.session.train. input_config should be an array which has channel objects. The description of input_config is taken from https://botocore.readthedocs.io/en/latest/reference/services/sagemaker.html#SageMaker.Client.create_training_job.

'input_config' should be an array which has channel objects.

laurenyu

Nice catch - thanks for submitting a PR!

laurenyu · 2018-02-02T23:04:38Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source.


Could you add a link to the botocore docs?

There are no links to botocore docs in this module. How about putting a link to ChannelAPI document like session.py#L744?

I meant the link you referenced in your PR description - since there's more information there about InputDataConfig, I think it'd be nice to make it clear where to find more information. A link to the Channel API doc would be a nice addition as well

I see. I added the link to the description in 3671efe.

winstonaws · 2018-02-06T18:12:24Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source. Please refer to


Should be "A list of Channel objects". "Array" in python actually refers to a different type: https://docs.python.org/3/library/array.html

@winstonaws Thanks. I fixed it in a7178c3.

* 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)

Removed: README from xgboost direct marketing

* 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

shotarok · 2018-02-02T08:40:46Z

Fix description of an argument of sagemaker.session.train. input_config should be an array which has channel objects. The description of input_config is taken from https://botocore.readthedocs.io/en/latest/reference/services/sagemaker.html#SageMaker.Client.create_training_job.

'input_config' should be an array which has channel objects.

laurenyu

Nice catch - thanks for submitting a PR!

laurenyu · 2018-02-02T23:04:38Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source.


Could you add a link to the botocore docs?

There are no links to botocore docs in this module. How about putting a link to ChannelAPI document like session.py#L744?

I meant the link you referenced in your PR description - since there's more information there about InputDataConfig, I think it'd be nice to make it clear where to find more information. A link to the Channel API doc would be a nice addition as well

I see. I added the link to the description in 3671efe.

winstonaws · 2018-02-06T18:12:24Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source. Please refer to


Should be "A list of Channel objects". "Array" in python actually refers to a different type: https://docs.python.org/3/library/array.html

@winstonaws Thanks. I fixed it in a7178c3.

* 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)

Removed: README from xgboost direct marketing

* 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

shotarok · 2018-02-02T08:40:46Z

Fix description of an argument of sagemaker.session.train. input_config should be an array which has channel objects. The description of input_config is taken from https://botocore.readthedocs.io/en/latest/reference/services/sagemaker.html#SageMaker.Client.create_training_job.

'input_config' should be an array which has channel objects.

laurenyu

Nice catch - thanks for submitting a PR!

laurenyu · 2018-02-02T23:04:38Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source.


Could you add a link to the botocore docs?

There are no links to botocore docs in this module. How about putting a link to ChannelAPI document like session.py#L744?

I meant the link you referenced in your PR description - since there's more information there about InputDataConfig, I think it'd be nice to make it clear where to find more information. A link to the Channel API doc would be a nice addition as well

I see. I added the link to the description in 3671efe.

winstonaws · 2018-02-06T18:12:24Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source. Please refer to


Should be "A list of Channel objects". "Array" in python actually refers to a different type: https://docs.python.org/3/library/array.html

@winstonaws Thanks. I fixed it in a7178c3.

* 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)

Removed: README from xgboost direct marketing

* 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

shotarok · 2018-02-02T08:40:46Z

Fix description of an argument of sagemaker.session.train. input_config should be an array which has channel objects. The description of input_config is taken from https://botocore.readthedocs.io/en/latest/reference/services/sagemaker.html#SageMaker.Client.create_training_job.

'input_config' should be an array which has channel objects.

laurenyu

Nice catch - thanks for submitting a PR!

laurenyu · 2018-02-02T23:04:38Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source.


Could you add a link to the botocore docs?

There are no links to botocore docs in this module. How about putting a link to ChannelAPI document like session.py#L744?

I meant the link you referenced in your PR description - since there's more information there about InputDataConfig, I think it'd be nice to make it clear where to find more information. A link to the Channel API doc would be a nice addition as well

I see. I added the link to the description in 3671efe.

winstonaws · 2018-02-06T18:12:24Z

- additional information about the training dataset. See :func:`sagemaker.session.s3_input`
- for full details.
-
+ input_config (list): An array of Channel objects. Each channel is a named input source. Please refer to


Should be "A list of Channel objects". "Array" in python actually refers to a different type: https://docs.python.org/3/library/array.html

@winstonaws Thanks. I fixed it in a7178c3.

* 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)

Removed: README from xgboost direct marketing

* 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

Fix description of an argument of sagemaker.session.train
762650f
'input_config' should be an array which has channel objects.

winstonaws requested a review from owen-t February 2, 2018 20:56

laurenyu reviewed Feb 2, 2018
View reviewed changes

Add a link to the botocore docs
3671efe

winstonaws suggested changes Feb 6, 2018
View reviewed changes

Use 'list' instead of 'array' in the description
a7178c3

winstonaws approved these changes Feb 7, 2018
View reviewed changes

Merge branch 'master' into fix-session-train-doc
7052518

laurenyu merged commit b400fa4 into aws:masterFeb 7, 2018

shotarok deleted the fix-session-train-doc branch February 7, 2018 23:45

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#69from awslabs/arpin_xgb_fix
045a68b
Removed: README from xgboost direct marketing

Fix description of an argument of sagemaker.session.train
762650f
'input_config' should be an array which has channel objects.

winstonaws requested a review from owen-t February 2, 2018 20:56

laurenyu reviewed Feb 2, 2018
View reviewed changes

Add a link to the botocore docs
3671efe

winstonaws suggested changes Feb 6, 2018
View reviewed changes

Use 'list' instead of 'array' in the description
a7178c3

winstonaws approved these changes Feb 7, 2018
View reviewed changes

Merge branch 'master' into fix-session-train-doc
7052518

laurenyu merged commit b400fa4 into aws:masterFeb 7, 2018

shotarok deleted the fix-session-train-doc branch February 7, 2018 23:45

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#69from awslabs/arpin_xgb_fix
045a68b
Removed: README from xgboost direct marketing

Fix description of an argument of sagemaker.session.train
762650f
'input_config' should be an array which has channel objects.

winstonaws requested a review from owen-t February 2, 2018 20:56

laurenyu reviewed Feb 2, 2018
View reviewed changes

Add a link to the botocore docs
3671efe

winstonaws suggested changes Feb 6, 2018
View reviewed changes

Use 'list' instead of 'array' in the description
a7178c3

winstonaws approved these changes Feb 7, 2018
View reviewed changes

Merge branch 'master' into fix-session-train-doc
7052518

laurenyu merged commit b400fa4 into aws:masterFeb 7, 2018

shotarok deleted the fix-session-train-doc branch February 7, 2018 23:45

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#69from awslabs/arpin_xgb_fix
045a68b
Removed: README from xgboost direct marketing

Fix description of an argument of sagemaker.session.train
762650f
'input_config' should be an array which has channel objects.

winstonaws requested a review from owen-t February 2, 2018 20:56

laurenyu reviewed Feb 2, 2018
View reviewed changes

Add a link to the botocore docs
3671efe

winstonaws suggested changes Feb 6, 2018
View reviewed changes

Use 'list' instead of 'array' in the description
a7178c3

winstonaws approved these changes Feb 7, 2018
View reviewed changes

Merge branch 'master' into fix-session-train-doc
7052518

laurenyu merged commit b400fa4 into aws:masterFeb 7, 2018

shotarok deleted the fix-session-train-doc branch February 7, 2018 23:45

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#69from awslabs/arpin_xgb_fix
045a68b
Removed: README from xgboost direct marketing

Fix description of an argument of sagemaker.session.train
762650f
'input_config' should be an array which has channel objects.

winstonaws requested a review from owen-t February 2, 2018 20:56

laurenyu reviewed Feb 2, 2018
View reviewed changes

Add a link to the botocore docs
3671efe

winstonaws suggested changes Feb 6, 2018
View reviewed changes

Use 'list' instead of 'array' in the description
a7178c3

winstonaws approved these changes Feb 7, 2018
View reviewed changes

Merge branch 'master' into fix-session-train-doc
7052518

laurenyu merged commit b400fa4 into aws:masterFeb 7, 2018

shotarok deleted the fix-session-train-doc branch February 7, 2018 23:45

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#69from awslabs/arpin_xgb_fix
045a68b
Removed: README from xgboost direct marketing

Fix description of an argument of sagemaker.session.train
762650f
'input_config' should be an array which has channel objects.

winstonaws requested a review from owen-t February 2, 2018 20:56

laurenyu reviewed Feb 2, 2018
View reviewed changes

Add a link to the botocore docs
3671efe

winstonaws suggested changes Feb 6, 2018
View reviewed changes

Use 'list' instead of 'array' in the description
a7178c3

winstonaws approved these changes Feb 7, 2018
View reviewed changes

Merge branch 'master' into fix-session-train-doc
7052518

laurenyu merged commit b400fa4 into aws:masterFeb 7, 2018

shotarok deleted the fix-session-train-doc branch February 7, 2018 23:45

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#69from awslabs/arpin_xgb_fix
045a68b
Removed: README from xgboost direct marketing

Fix description of an argument of sagemaker.session.train
762650f
'input_config' should be an array which has channel objects.

winstonaws requested a review from owen-t February 2, 2018 20:56

laurenyu reviewed Feb 2, 2018
View reviewed changes

Add a link to the botocore docs
3671efe

winstonaws suggested changes Feb 6, 2018
View reviewed changes

Use 'list' instead of 'array' in the description
a7178c3

winstonaws approved these changes Feb 7, 2018
View reviewed changes

Merge branch 'master' into fix-session-train-doc
7052518

laurenyu merged commit b400fa4 into aws:masterFeb 7, 2018

shotarok deleted the fix-session-train-doc branch February 7, 2018 23:45

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#69from awslabs/arpin_xgb_fix
045a68b
Removed: README from xgboost direct marketing

Fix description of an argument of sagemaker.session.train
762650f
'input_config' should be an array which has channel objects.

winstonaws requested a review from owen-t February 2, 2018 20:56

laurenyu reviewed Feb 2, 2018
View reviewed changes

Add a link to the botocore docs
3671efe

winstonaws suggested changes Feb 6, 2018
View reviewed changes

Use 'list' instead of 'array' in the description
a7178c3

winstonaws approved these changes Feb 7, 2018
View reviewed changes

Merge branch 'master' into fix-session-train-doc
7052518

laurenyu merged commit b400fa4 into aws:masterFeb 7, 2018

shotarok deleted the fix-session-train-doc branch February 7, 2018 23:45

apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Merge pull requestaws#69from awslabs/arpin_xgb_fix
045a68b
Removed: README from xgboost direct marketing

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