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doc: remove D212 from ignore to comply with PEP257 standards (#2065)
1 parent 01c6ee3 commit 1fdefe0

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‎.pydocstylerc

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[pydocstyle]
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inherit = false
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ignore = D104,D107,D202,D203,D212,D213,D214,D400,D401,D404,D406,D407,D411,D413,D414,D415,D417
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ignore = D104,D107,D202,D203,D213,D214,D400,D401,D404,D406,D407,D411,D413,D414,D415,D417
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match = (?!record_pb2).*\.py

‎src/sagemaker/amazon/factorization_machines.py

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@@ -290,8 +290,7 @@ def __init__(
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serializer=RecordSerializer(),
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deserializer=RecordDeserializer(),
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):
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"""
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Initialization for FactorizationMachinesPredictor class.
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"""Initialization for FactorizationMachinesPredictor class.
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Args:
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endpoint_name (str): Name of the Amazon SageMaker endpoint to which
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"""
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def __init__(self, model_data, role, sagemaker_session=None, **kwargs):
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"""
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Initialization for FactorizationMachinesModel class.
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"""Initialization for FactorizationMachinesModel class.
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model_data (str): The S3 location of a SageMaker model data

‎src/sagemaker/amazon/ipinsights.py

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serializer=CSVSerializer(),
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deserializer=JSONDeserializer(),
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):
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"""
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Args:
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"""Creates object to be used to get dot product of entity nad IP address.
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Args:
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endpoint_name (str): Name of the Amazon SageMaker endpoint to which
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requests are sent.
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sagemaker_session (sagemaker.session.Session): A SageMaker Session
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"""
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def __init__(self, model_data, role, sagemaker_session=None, **kwargs):
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"""
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Args:
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"""Creates object to get insights on S3 model data.
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Args:
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model_data (str): The S3 location of a SageMaker model data
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``.tar.gz`` file.
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role (str): An AWS IAM role (either name or full ARN). The Amazon

‎src/sagemaker/amazon/kmeans.py

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serializer=RecordSerializer(),
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deserializer=RecordDeserializer(),
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):
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"""
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Initialization for KMeansPredictor class.
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"""Initialization for KMeansPredictor class.
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Args:
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endpoint_name (str): Name of the Amazon SageMaker endpoint to which
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"""
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def __init__(self, model_data, role, sagemaker_session=None, **kwargs):
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"""
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Initialization for KMeansModel class.
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"""Initialization for KMeansModel class.
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Args:
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model_data (str): The S3 location of a SageMaker model data

‎src/sagemaker/amazon/knn.py

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@@ -209,8 +209,7 @@ def __init__(
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serializer=RecordSerializer(),
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deserializer=RecordDeserializer(),
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):
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"""
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Function to initialize KNNPredictor.
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"""Function to initialize KNNPredictor.
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endpoint_name (str): Name of the Amazon SageMaker endpoint to which
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"""
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def __init__(self, model_data, role, sagemaker_session=None, **kwargs):
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"""
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Function to initialize KNNModel.
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"""Function to initialize KNNModel.
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model_data (str): The S3 location of a SageMaker model data

‎src/sagemaker/amazon/lda.py

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@@ -53,8 +53,7 @@ def __init__(
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tol=None,
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**kwargs
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):
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"""
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Latent Dirichlet Allocation (LDA) is :class:`Estimator` used for unsupervised learning.
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"""Latent Dirichlet Allocation (LDA) is :class:`Estimator` used for unsupervised learning.
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Amazon SageMaker Latent Dirichlet Allocation is an unsupervised
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learning algorithm that attempts to describe a set of observations as a
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serializer=RecordSerializer(),
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deserializer=RecordDeserializer(),
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):
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"""
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"""Creates "LDAPredictor" object to be used for transforming input vectors.
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Args:
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endpoint_name (str): Name of the Amazon SageMaker endpoint to which
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requests are sent.
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sagemaker_session (sagemaker.session.Session): A SageMaker Session
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"""
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def __init__(self, model_data, role, sagemaker_session=None, **kwargs):
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"""
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Initialization for LDAModel class.
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"""Initialization for LDAModel class.
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model_data (str): The S3 location of a SageMaker model data

‎src/sagemaker/amazon/linear_learner.py

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serializer=RecordSerializer(),
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deserializer=RecordDeserializer(),
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):
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"""
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Initialization for LinearLearnerPredictor.
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"""Initialization for LinearLearnerPredictor.
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endpoint_name (str): Name of the Amazon SageMaker endpoint to which
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"""
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def __init__(self, model_data, role, sagemaker_session=None, **kwargs):
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"""
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Initialization for LinearLearnerModel.
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"""Initialization for LinearLearnerModel.
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model_data (str): The S3 location of a SageMaker model data

‎src/sagemaker/amazon/ntm.py

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serializer=RecordSerializer(),
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deserializer=RecordDeserializer(),
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):
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"""
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Initialization for NTMPredictor class.
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"""Initialization for NTMPredictor class.
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endpoint_name (str): Name of the Amazon SageMaker endpoint to which
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"""
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def __init__(self, model_data, role, sagemaker_session=None, **kwargs):
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"""
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Initialization for NTMModel class.
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"""Initialization for NTMModel class.
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model_data (str): The S3 location of a SageMaker model data

‎src/sagemaker/amazon/object2vec.py

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@@ -345,8 +345,7 @@ class Object2VecModel(Model):
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"""
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def __init__(self, model_data, role, sagemaker_session=None, **kwargs):
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"""
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Initialization for Object2VecModel class.
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"""Initialization for Object2VecModel class.
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model_data (str): The S3 location of a SageMaker model data

‎src/sagemaker/amazon/pca.py

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serializer=RecordSerializer(),
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deserializer=RecordDeserializer(),
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):
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"""
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Initialization for PCAPredictor.
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"""Initialization for PCAPredictor.
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"""
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def __init__(self, model_data, role, sagemaker_session=None, **kwargs):
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"""
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Initialization for PCAModel.
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"""Initialization for PCAModel.
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model_data (str): The S3 location of a SageMaker model data

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