Merge branch 'master' into patch-2

Author: ajaykarpur

CHANGELOG.md

@@ -1,5 +1,52 @@
 # Changelog
 
+## v2.14.0 (2020-10-05)
+
+### Features
+
+ * upgrade Neo MxNet to 1.7
+
+### Bug Fixes and Other Changes
+
+ * add a condition to retrieve correct image URI for xgboost
+
+## v2.13.0 (2020-09-30)
+
+### Features
+
+ * add xgboost framework version 1.2-1
+
+### Bug Fixes and Other Changes
+
+ * revert "feature: upgrade Neo MxNet to 1.7 (#1928)"
+
+## v2.12.0 (2020-09-29)
+
+### Features
+
+ * upgrade Neo MxNet to 1.7
+
+## v2.11.0 (2020-09-28)
+
+### Features
+
+ * Add SDK support for SparkML Serving Container version 2.4
+
+### Bug Fixes and Other Changes
+
+ * pin pytest version <6.1.0 to avoid pytest-rerunfailures breaking changes
+ * temporarily skip the MxNet Neo test until we fix them
+
+### Documentation Changes
+
+ * fix conda setup for docs
+
+## v2.10.0 (2020-09-23)
+
+### Features
+
+ * add inferentia pytorch inference container config
+
 ## v2.9.2 (2020-09-21)
 
 ### Bug Fixes and Other Changes

README.rst

@@ -164,7 +164,7 @@ Setup a Python environment, and install the dependencies listed in ``doc/require
     # conda
     conda create -n sagemaker python=3.7
     conda activate sagemaker
-    conda install --file doc/requirements.txt
+    conda install sphinx=3.1.1 sphinx_rtd_theme=0.5.0
 
     # pip
     pip install -r doc/requirements.txt
@@ -201,7 +201,7 @@ In order to host a SparkML model in SageMaker, it should be serialized with ``ML
 
 For more information on MLeap, see https://github.com/combust/mleap .
 
-Supported major version of Spark: 2.2 (MLeap version - 0.9.6)
+Supported major version of Spark: 2.4 (MLeap version - 0.9.6)
 
 Here is an example on how to create an instance of  ``SparkMLModel`` class and use ``deploy()`` method to create an
 endpoint which can be used to perform prediction against your trained SparkML Model.

VERSION

@@ -1 +1 @@
-2.9.3.dev0
+2.14.1.dev0

doc/overview.rst

@@ -672,7 +672,7 @@ You can install all necessary for this feature dependencies using pip:
 For more detailed examples of running hyperparameter tuning jobs, see:
 
 - `Using the TensorFlow estimator with hyperparameter tuning <https://github.com/awslabs/amazon-sagemaker-examples/blob/master/hyperparameter_tuning/tensorflow_mnist/hpo_tensorflow_mnist.ipynb>`__
-- `Bringing your own estimator for hyperparameter tuning <https://github.com/awslabs/amazon-sagemaker-examples/blob/master/hyperparameter_tuning/r_bring_your_own/hpo_r_bring_your_own.ipynb>`__
+- `Bringing your own estimator for hyperparameter tuning <https://github.com/awslabs/amazon-sagemaker-examples/blob/master/hyperparameter_tuning/r_bring_your_own/tune_r_bring_your_own.ipynb>`__
 - `Analyzing results <https://github.com/awslabs/amazon-sagemaker-examples/blob/master/hyperparameter_tuning/analyze_results/HPO_Analyze_TuningJob_Results.ipynb>`__
 
 You can also find these notebooks in the **Hyperprameter Tuning** section of the **SageMaker Examples** section in a notebook instance.

setup.py

@@ -61,7 +61,7 @@ def read_version():
         extras["all"],
         "tox",
         "flake8",
-        "pytest",
+        "pytest<6.1.0",
         "pytest-cov",
         "pytest-rerunfailures",
         "pytest-xdist",

src/sagemaker/algorithm.py

@@ -17,6 +17,7 @@
 import sagemaker.parameter
 from sagemaker import vpc_utils
 from sagemaker.deserializers import BytesDeserializer
+from sagemaker.deprecations import removed_kwargs
 from sagemaker.estimator import EstimatorBase
 from sagemaker.serializers import IdentitySerializer
 from sagemaker.transformer import Transformer
@@ -291,6 +292,9 @@ def create_model(
         Returns:
             a Model ready for deployment.
         """
+        removed_kwargs("content_type", kwargs)
+        removed_kwargs("accept", kwargs)
+
         if predictor_cls is None:
 
             def predict_wrapper(endpoint, session):

src/sagemaker/amazon/amazon_estimator.py

@@ -23,6 +23,7 @@
 from sagemaker.amazon import validation
 from sagemaker.amazon.hyperparameter import Hyperparameter as hp  # noqa
 from sagemaker.amazon.common import write_numpy_to_dense_tensor
+from sagemaker.deprecations import renamed_warning
 from sagemaker.estimator import EstimatorBase, _TrainingJob
 from sagemaker.inputs import FileSystemInput, TrainingInput
 from sagemaker.utils import sagemaker_timestamp
@@ -454,3 +455,22 @@ def upload_numpy_to_s3_shards(
                 s3.Object(bucket, key_prefix + file).delete()
         finally:
             raise ex
+
+
+def get_image_uri(region_name, repo_name, repo_version=1):
+    """Deprecated method. Please use sagemaker.image_uris.retrieve().
+
+    Args:
+        region_name: name of the region
+        repo_name: name of the repo (e.g. xgboost)
+        repo_version: version of the repo
+
+    Returns:
+        the image uri
+    """
+    renamed_warning("The method get_image_uri")
+    return image_uris.retrieve(
+        framework=repo_name,
+        region=region_name,
+        version=repo_version,
+    )

src/sagemaker/amazon/common.py

@@ -21,6 +21,7 @@
 import numpy as np
 
 from sagemaker.amazon.record_pb2 import Record
+from sagemaker.deprecations import deprecated_class
 from sagemaker.deserializers import BaseDeserializer
 from sagemaker.serializers import BaseSerializer
 from sagemaker.utils import DeferredError
@@ -298,3 +299,7 @@ def _resolve_type(dtype):
     if dtype == np.dtype("float32"):
         return "Float32"
     raise ValueError("Unsupported dtype {} on array".format(dtype))
+
+
+numpy_to_record_serializer = deprecated_class(RecordSerializer, "numpy_to_record_serializer")
+record_deserializer = deprecated_class(RecordDeserializer, "record_deserializer")

src/sagemaker/content_types.py

@@ -0,0 +1,23 @@
+# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"). You
+# may not use this file except in compliance with the License. A copy of
+# the License is located at
+#
+#     http://aws.amazon.com/apache2.0/
+#
+# or in the "license" file accompanying this file. This file is
+# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific
+# language governing permissions and limitations under the License.
+"""Deprecated content type constants. Just use the mime type strings."""
+from __future__ import absolute_import
+
+import deprecations
+
+deprecations.removed_warning("The sagemaker.content_types module")
+
+CONTENT_TYPE_JSON = "application/json"
+CONTENT_TYPE_CSV = "text/csv"
+CONTENT_TYPE_OCTET_STREAM = "application/octet-stream"
+CONTENT_TYPE_NPY = "application/x-npy"

src/sagemaker/deprecations.py

@@ -0,0 +1,175 @@
+# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"). You
+# may not use this file except in compliance with the License. A copy of
+# the License is located at
+#
+#     http://aws.amazon.com/apache2.0/
+#
+# or in the "license" file accompanying this file. This file is
+# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific
+# language governing permissions and limitations under the License.
+"""Module for deprecation abstractions."""
+from __future__ import absolute_import
+
+import logging
+import warnings
+
+logging.captureWarnings(True)
+
+
+def _warn(msg):
+    """Generic warning raiser referencing V2
+
+    Args:
+        phrase: The phrase to include in the warning.
+    """
+    warnings.warn(
+        f"{msg} in sagemaker>=2.\n"
+        "See: https://sagemaker.readthedocs.io/en/stable/v2.html for details.",
+        DeprecationWarning,
+        stacklevel=2,
+    )
+
+
+def removed_warning(phrase):
+    """Raise a warning for a no-op in sagemaker>=2
+
+    Args:
+        phrase: the prefix phrase of the warning message.
+    """
+    _warn(f"{phrase} is a no-op")
+
+
+def renamed_warning(phrase):
+    """Raise a warning for a rename in sagemaker>=2
+
+    Args:
+        phrase: the prefix phrase of the warning message.
+    """
+    _warn(f"{phrase} has been renamed")
+
+
+def renamed_kwargs(old_name, new_name, value, kwargs):
+    """Checks if the deprecated argument is in kwargs
+
+    Raises warning, if present.
+
+    Args:
+        old_name: name of deprecated argument
+        new_name: name of the new argument
+        value: value associated with new name, if supplied
+        kwargs: keyword arguments dict
+
+    Returns:
+        value of the keyword argument, if present
+    """
+    if old_name in kwargs:
+        value = kwargs.get(old_name, value)
+        kwargs[new_name] = value
+        renamed_warning(old_name)
+    return value
+
+
+def removed_arg(name, arg):
+    """Checks if the deprecated argument is populated.
+
+    Raises warning, if not None.
+
+    Args:
+        name: name of deprecated argument
+        arg: the argument to check
+    """
+    if arg is not None:
+        removed_warning(name)
+
+
+def removed_kwargs(name, kwargs):
+    """Checks if the deprecated argument is in kwargs
+
+    Raises warning, if present.
+
+    Args:
+        name: name of deprecated argument
+        kwargs: keyword arguments dict
+    """
+    if name in kwargs:
+        removed_warning(name)
+
+
+def removed_function(name):
+    """A no-op deprecated function factory."""
+
+    def func(*args, **kwargs):  # pylint: disable=W0613
+        removed_warning(f"The function {name}")
+
+    return func
+
+
+def deprecated_function(func, name):
+    """Wrap a function with a deprecation warning.
+
+    Args:
+        func: Function to wrap in a deprecation warning.
+        name: The name that has been deprecated.
+
+    Returns:
+        The modified function
+    """
+
+    def deprecate(*args, **kwargs):
+        renamed_warning(f"The {name}")
+        return func(*args, **kwargs)
+
+    return deprecate
+
+
+def deprecated_serialize(instance, name):
+    """Modifies a serializer instance serialize method.
+
+    Args:
+        instance: Instance to modify serialize method.
+        name: The name that has been deprecated.
+
+    Returns:
+        The modified instance
+    """
+    instance.serialize = deprecated_function(instance.serialize, name)
+    return instance
+
+
+def deprecated_deserialize(instance, name):
+    """Modifies a deserializer instance deserialize method.
+
+    Args:
+        instance: Instance to modify deserialize method.
+        name: The name that has been deprecated.
+
+    Returns:
+        The modified instance
+    """
+    instance.deserialize = deprecated_function(instance.deserialize, name)
+    return instance
+
+
+def deprecated_class(cls, name):
+    """Returns a class based on super class with a deprecation warning.
+
+    Args:
+        cls: The class to derive with a deprecation warning on __init__
+        name: The name of the class.
+
+    Returns:
+        The modified class.
+    """
+
+    class DeprecatedClass(cls):
+        """Provides a warning for the class name."""
+
+        def __init__(self, *args, **kwargs):
+            """Provides a warning for the class name."""
+            renamed_warning(f"The class {name}")
+            super(DeprecatedClass, self).__init__(*args, **kwargs)
+
+    return DeprecatedClass