feature: all predictors support serializer/deserializer overrides#1997

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
ajaykarpur merged 4 commits into from
Dec 3, 2020
Merged

feature: all predictors support serializer/deserializer overrides #1997

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
55303b8
feat: framework predictor de/serial override args
athewsey Nov 20, 2020
028b844
feat: Amz algo predictor de/serial override args
athewsey Nov 20, 2020
ff26090
change: add unit tests for de/ser overrides
athewsey Nov 24, 2020
94a10db
Merge branch 'master' into feat/predictorargs
ajaykarpur Dec 3, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/factorization_machines.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -277,13 +277,20 @@ class FactorizationMachinesPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"score"`` key of
the ``Record.label`` field. Please refer to the formats details described:
https://docs.aws.amazon.com/sagemaker/latest/dg/fm-in-formats.html
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -292,12 +299,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(FactorizationMachinesPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
16 changes: 13 additions & 3 deletions src/sagemaker/amazon/ipinsights.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -191,7 +191,13 @@ class IPInsightsPredictor(Predictor):
second column should contain the IPv4 address in dot notation.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -200,12 +206,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to text/csv.
deserializer (callable): Optional. Default parses JSON responses
using ``json.load(...)``.
"""
super(IPInsightsPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/kmeans.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -210,12 +210,19 @@ class KMeansPredictor(Predictor):
to fit the model this Predictor performs inference on.

``predict()`` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The nearest cluster is stored in the
``closest_cluster`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -224,12 +231,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KMeansPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/knn.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -199,12 +199,19 @@ class KNNPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -213,12 +220,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KNNPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/lda.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -183,12 +183,19 @@ class LDAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -197,12 +204,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LDAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/linear_learner.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -444,12 +444,19 @@ class LinearLearnerPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -458,12 +465,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LinearLearnerPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/ntm.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -212,12 +212,19 @@ class NTMPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -226,12 +233,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(NTMPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/pca.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -193,12 +193,19 @@ class PCAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -207,12 +214,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(PCAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/randomcutforest.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -171,12 +171,19 @@ class RandomCutForestPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input. Each row's score is stored in the key ``score`` of the
``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -185,12 +192,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(RandomCutForestPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
18 changes: 16 additions & 2 deletions src/sagemaker/chainer/model.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -38,7 +38,13 @@ class ChainerPredictor(Predictor):
multidimensional tensors for Chainer inference.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=NumpySerializer(),
deserializer=NumpyDeserializer(),
):
"""Initialize an ``ChainerPredictor``.

Args:
Expand All@@ -48,9 +54,17 @@ def __init__(self, endpoint_name, sagemaker_session=None):
manages interactions with Amazon SageMaker APIs and any other
AWS services needed. If not specified, the estimator creates one
using the default AWS configuration chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to .npy format. Handles lists and numpy
arrays.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses the response from .npy format to numpy array.
"""
super(ChainerPredictor, self).__init__(
endpoint_name, sagemaker_session, NumpySerializer(), NumpyDeserializer()
endpoint_name,
sagemaker_session,
serializer=serializer,
deserializer=deserializer,
)


Expand Down
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all \u003cpre\u003e\u003ccode\u003e blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks"); } } catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); } })(); (function(){ try { var __m = "github.com"; var __re = new RegExp('^' + "github\\.com" + '
Skip to content

feature: all predictors support serializer/deserializer overrides#1997

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
ajaykarpur merged 4 commits into from
Dec 3, 2020
Merged

feature: all predictors support serializer/deserializer overrides #1997

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
55303b8
feat: framework predictor de/serial override args
athewsey Nov 20, 2020
028b844
feat: Amz algo predictor de/serial override args
athewsey Nov 20, 2020
ff26090
change: add unit tests for de/ser overrides
athewsey Nov 24, 2020
94a10db
Merge branch 'master' into feat/predictorargs
ajaykarpur Dec 3, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/factorization_machines.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -277,13 +277,20 @@ class FactorizationMachinesPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"score"`` key of
the ``Record.label`` field. Please refer to the formats details described:
https://docs.aws.amazon.com/sagemaker/latest/dg/fm-in-formats.html
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -292,12 +299,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(FactorizationMachinesPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
16 changes: 13 additions & 3 deletions src/sagemaker/amazon/ipinsights.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -191,7 +191,13 @@ class IPInsightsPredictor(Predictor):
second column should contain the IPv4 address in dot notation.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -200,12 +206,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to text/csv.
deserializer (callable): Optional. Default parses JSON responses
using ``json.load(...)``.
"""
super(IPInsightsPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/kmeans.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -210,12 +210,19 @@ class KMeansPredictor(Predictor):
to fit the model this Predictor performs inference on.

``predict()`` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The nearest cluster is stored in the
``closest_cluster`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -224,12 +231,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KMeansPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/knn.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -199,12 +199,19 @@ class KNNPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -213,12 +220,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KNNPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/lda.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -183,12 +183,19 @@ class LDAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -197,12 +204,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LDAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/linear_learner.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -444,12 +444,19 @@ class LinearLearnerPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -458,12 +465,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LinearLearnerPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/ntm.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -212,12 +212,19 @@ class NTMPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -226,12 +233,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(NTMPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/pca.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -193,12 +193,19 @@ class PCAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -207,12 +214,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(PCAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/randomcutforest.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -171,12 +171,19 @@ class RandomCutForestPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input. Each row's score is stored in the key ``score`` of the
``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -185,12 +192,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(RandomCutForestPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
18 changes: 16 additions & 2 deletions src/sagemaker/chainer/model.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -38,7 +38,13 @@ class ChainerPredictor(Predictor):
multidimensional tensors for Chainer inference.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=NumpySerializer(),
deserializer=NumpyDeserializer(),
):
"""Initialize an ``ChainerPredictor``.

Args:
Expand All@@ -48,9 +54,17 @@ def __init__(self, endpoint_name, sagemaker_session=None):
manages interactions with Amazon SageMaker APIs and any other
AWS services needed. If not specified, the estimator creates one
using the default AWS configuration chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to .npy format. Handles lists and numpy
arrays.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses the response from .npy format to numpy array.
"""
super(ChainerPredictor, self).__init__(
endpoint_name, sagemaker_session, NumpySerializer(), NumpyDeserializer()
endpoint_name,
sagemaker_session,
serializer=serializer,
deserializer=deserializer,
)


Expand Down
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

feature: all predictors support serializer/deserializer overrides#1997

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
ajaykarpur merged 4 commits into from
Dec 3, 2020
Merged

feature: all predictors support serializer/deserializer overrides #1997

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
55303b8
feat: framework predictor de/serial override args
athewsey Nov 20, 2020
028b844
feat: Amz algo predictor de/serial override args
athewsey Nov 20, 2020
ff26090
change: add unit tests for de/ser overrides
athewsey Nov 24, 2020
94a10db
Merge branch 'master' into feat/predictorargs
ajaykarpur Dec 3, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/factorization_machines.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -277,13 +277,20 @@ class FactorizationMachinesPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"score"`` key of
the ``Record.label`` field. Please refer to the formats details described:
https://docs.aws.amazon.com/sagemaker/latest/dg/fm-in-formats.html
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -292,12 +299,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(FactorizationMachinesPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
16 changes: 13 additions & 3 deletions src/sagemaker/amazon/ipinsights.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -191,7 +191,13 @@ class IPInsightsPredictor(Predictor):
second column should contain the IPv4 address in dot notation.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -200,12 +206,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to text/csv.
deserializer (callable): Optional. Default parses JSON responses
using ``json.load(...)``.
"""
super(IPInsightsPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/kmeans.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -210,12 +210,19 @@ class KMeansPredictor(Predictor):
to fit the model this Predictor performs inference on.

``predict()`` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The nearest cluster is stored in the
``closest_cluster`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -224,12 +231,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KMeansPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/knn.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -199,12 +199,19 @@ class KNNPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -213,12 +220,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KNNPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/lda.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -183,12 +183,19 @@ class LDAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -197,12 +204,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LDAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/linear_learner.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -444,12 +444,19 @@ class LinearLearnerPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -458,12 +465,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LinearLearnerPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/ntm.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -212,12 +212,19 @@ class NTMPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -226,12 +233,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(NTMPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/pca.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -193,12 +193,19 @@ class PCAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -207,12 +214,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(PCAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/randomcutforest.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -171,12 +171,19 @@ class RandomCutForestPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input. Each row's score is stored in the key ``score`` of the
``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -185,12 +192,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(RandomCutForestPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
18 changes: 16 additions & 2 deletions src/sagemaker/chainer/model.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -38,7 +38,13 @@ class ChainerPredictor(Predictor):
multidimensional tensors for Chainer inference.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=NumpySerializer(),
deserializer=NumpyDeserializer(),
):
"""Initialize an ``ChainerPredictor``.

Args:
Expand All@@ -48,9 +54,17 @@ def __init__(self, endpoint_name, sagemaker_session=None):
manages interactions with Amazon SageMaker APIs and any other
AWS services needed. If not specified, the estimator creates one
using the default AWS configuration chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to .npy format. Handles lists and numpy
arrays.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses the response from .npy format to numpy array.
"""
super(ChainerPredictor, self).__init__(
endpoint_name, sagemaker_session, NumpySerializer(), NumpyDeserializer()
endpoint_name,
sagemaker_session,
serializer=serializer,
deserializer=deserializer,
)


Expand Down
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length \u003e 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

feature: all predictors support serializer/deserializer overrides#1997

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
ajaykarpur merged 4 commits into from
Dec 3, 2020
Merged

feature: all predictors support serializer/deserializer overrides #1997

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
55303b8
feat: framework predictor de/serial override args
athewsey Nov 20, 2020
028b844
feat: Amz algo predictor de/serial override args
athewsey Nov 20, 2020
ff26090
change: add unit tests for de/ser overrides
athewsey Nov 24, 2020
94a10db
Merge branch 'master' into feat/predictorargs
ajaykarpur Dec 3, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/factorization_machines.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -277,13 +277,20 @@ class FactorizationMachinesPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"score"`` key of
the ``Record.label`` field. Please refer to the formats details described:
https://docs.aws.amazon.com/sagemaker/latest/dg/fm-in-formats.html
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -292,12 +299,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(FactorizationMachinesPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
16 changes: 13 additions & 3 deletions src/sagemaker/amazon/ipinsights.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -191,7 +191,13 @@ class IPInsightsPredictor(Predictor):
second column should contain the IPv4 address in dot notation.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -200,12 +206,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to text/csv.
deserializer (callable): Optional. Default parses JSON responses
using ``json.load(...)``.
"""
super(IPInsightsPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/kmeans.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -210,12 +210,19 @@ class KMeansPredictor(Predictor):
to fit the model this Predictor performs inference on.

``predict()`` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The nearest cluster is stored in the
``closest_cluster`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -224,12 +231,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KMeansPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/knn.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -199,12 +199,19 @@ class KNNPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -213,12 +220,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KNNPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/lda.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -183,12 +183,19 @@ class LDAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -197,12 +204,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LDAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/linear_learner.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -444,12 +444,19 @@ class LinearLearnerPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -458,12 +465,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LinearLearnerPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/ntm.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -212,12 +212,19 @@ class NTMPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -226,12 +233,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(NTMPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/pca.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -193,12 +193,19 @@ class PCAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -207,12 +214,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(PCAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/randomcutforest.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -171,12 +171,19 @@ class RandomCutForestPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input. Each row's score is stored in the key ``score`` of the
``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -185,12 +192,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(RandomCutForestPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
18 changes: 16 additions & 2 deletions src/sagemaker/chainer/model.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -38,7 +38,13 @@ class ChainerPredictor(Predictor):
multidimensional tensors for Chainer inference.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=NumpySerializer(),
deserializer=NumpyDeserializer(),
):
"""Initialize an ``ChainerPredictor``.

Args:
Expand All@@ -48,9 +54,17 @@ def __init__(self, endpoint_name, sagemaker_session=None):
manages interactions with Amazon SageMaker APIs and any other
AWS services needed. If not specified, the estimator creates one
using the default AWS configuration chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to .npy format. Handles lists and numpy
arrays.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses the response from .npy format to numpy array.
"""
super(ChainerPredictor, self).__init__(
endpoint_name, sagemaker_session, NumpySerializer(), NumpyDeserializer()
endpoint_name,
sagemaker_session,
serializer=serializer,
deserializer=deserializer,
)


Expand Down
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
Skip to content

feature: all predictors support serializer/deserializer overrides#1997

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
ajaykarpur merged 4 commits into from
Dec 3, 2020
Merged

feature: all predictors support serializer/deserializer overrides #1997

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
55303b8
feat: framework predictor de/serial override args
athewsey Nov 20, 2020
028b844
feat: Amz algo predictor de/serial override args
athewsey Nov 20, 2020
ff26090
change: add unit tests for de/ser overrides
athewsey Nov 24, 2020
94a10db
Merge branch 'master' into feat/predictorargs
ajaykarpur Dec 3, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/factorization_machines.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -277,13 +277,20 @@ class FactorizationMachinesPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"score"`` key of
the ``Record.label`` field. Please refer to the formats details described:
https://docs.aws.amazon.com/sagemaker/latest/dg/fm-in-formats.html
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -292,12 +299,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(FactorizationMachinesPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
16 changes: 13 additions & 3 deletions src/sagemaker/amazon/ipinsights.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -191,7 +191,13 @@ class IPInsightsPredictor(Predictor):
second column should contain the IPv4 address in dot notation.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -200,12 +206,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to text/csv.
deserializer (callable): Optional. Default parses JSON responses
using ``json.load(...)``.
"""
super(IPInsightsPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/kmeans.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -210,12 +210,19 @@ class KMeansPredictor(Predictor):
to fit the model this Predictor performs inference on.

``predict()`` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The nearest cluster is stored in the
``closest_cluster`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -224,12 +231,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KMeansPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/knn.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -199,12 +199,19 @@ class KNNPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -213,12 +220,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KNNPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/lda.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -183,12 +183,19 @@ class LDAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -197,12 +204,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LDAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/linear_learner.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -444,12 +444,19 @@ class LinearLearnerPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -458,12 +465,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LinearLearnerPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/ntm.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -212,12 +212,19 @@ class NTMPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -226,12 +233,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(NTMPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/pca.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -193,12 +193,19 @@ class PCAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -207,12 +214,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(PCAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/randomcutforest.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -171,12 +171,19 @@ class RandomCutForestPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input. Each row's score is stored in the key ``score`` of the
``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -185,12 +192,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(RandomCutForestPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
18 changes: 16 additions & 2 deletions src/sagemaker/chainer/model.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -38,7 +38,13 @@ class ChainerPredictor(Predictor):
multidimensional tensors for Chainer inference.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=NumpySerializer(),
deserializer=NumpyDeserializer(),
):
"""Initialize an ``ChainerPredictor``.

Args:
Expand All@@ -48,9 +54,17 @@ def __init__(self, endpoint_name, sagemaker_session=None):
manages interactions with Amazon SageMaker APIs and any other
AWS services needed. If not specified, the estimator creates one
using the default AWS configuration chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to .npy format. Handles lists and numpy
arrays.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses the response from .npy format to numpy array.
"""
super(ChainerPredictor, self).__init__(
endpoint_name, sagemaker_session, NumpySerializer(), NumpyDeserializer()
endpoint_name,
sagemaker_session,
serializer=serializer,
deserializer=deserializer,
)


Expand Down
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

feature: all predictors support serializer/deserializer overrides#1997

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
ajaykarpur merged 4 commits into from
Dec 3, 2020
Merged

feature: all predictors support serializer/deserializer overrides #1997

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
55303b8
feat: framework predictor de/serial override args
athewsey Nov 20, 2020
028b844
feat: Amz algo predictor de/serial override args
athewsey Nov 20, 2020
ff26090
change: add unit tests for de/ser overrides
athewsey Nov 24, 2020
94a10db
Merge branch 'master' into feat/predictorargs
ajaykarpur Dec 3, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/factorization_machines.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -277,13 +277,20 @@ class FactorizationMachinesPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"score"`` key of
the ``Record.label`` field. Please refer to the formats details described:
https://docs.aws.amazon.com/sagemaker/latest/dg/fm-in-formats.html
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -292,12 +299,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(FactorizationMachinesPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
16 changes: 13 additions & 3 deletions src/sagemaker/amazon/ipinsights.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -191,7 +191,13 @@ class IPInsightsPredictor(Predictor):
second column should contain the IPv4 address in dot notation.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -200,12 +206,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to text/csv.
deserializer (callable): Optional. Default parses JSON responses
using ``json.load(...)``.
"""
super(IPInsightsPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/kmeans.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -210,12 +210,19 @@ class KMeansPredictor(Predictor):
to fit the model this Predictor performs inference on.

``predict()`` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The nearest cluster is stored in the
``closest_cluster`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -224,12 +231,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KMeansPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/knn.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -199,12 +199,19 @@ class KNNPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -213,12 +220,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KNNPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/lda.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -183,12 +183,19 @@ class LDAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -197,12 +204,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LDAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/linear_learner.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -444,12 +444,19 @@ class LinearLearnerPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -458,12 +465,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LinearLearnerPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/ntm.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -212,12 +212,19 @@ class NTMPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -226,12 +233,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(NTMPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/pca.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -193,12 +193,19 @@ class PCAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -207,12 +214,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(PCAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/randomcutforest.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -171,12 +171,19 @@ class RandomCutForestPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input. Each row's score is stored in the key ``score`` of the
``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -185,12 +192,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(RandomCutForestPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
18 changes: 16 additions & 2 deletions src/sagemaker/chainer/model.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -38,7 +38,13 @@ class ChainerPredictor(Predictor):
multidimensional tensors for Chainer inference.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=NumpySerializer(),
deserializer=NumpyDeserializer(),
):
"""Initialize an ``ChainerPredictor``.

Args:
Expand All@@ -48,9 +54,17 @@ def __init__(self, endpoint_name, sagemaker_session=None):
manages interactions with Amazon SageMaker APIs and any other
AWS services needed. If not specified, the estimator creates one
using the default AWS configuration chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to .npy format. Handles lists and numpy
arrays.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses the response from .npy format to numpy array.
"""
super(ChainerPredictor, self).__init__(
endpoint_name, sagemaker_session, NumpySerializer(), NumpyDeserializer()
endpoint_name,
sagemaker_session,
serializer=serializer,
deserializer=deserializer,
)


Expand Down
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

feature: all predictors support serializer/deserializer overrides#1997

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
ajaykarpur merged 4 commits into from
Dec 3, 2020
Merged

feature: all predictors support serializer/deserializer overrides #1997

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
55303b8
feat: framework predictor de/serial override args
athewsey Nov 20, 2020
028b844
feat: Amz algo predictor de/serial override args
athewsey Nov 20, 2020
ff26090
change: add unit tests for de/ser overrides
athewsey Nov 24, 2020
94a10db
Merge branch 'master' into feat/predictorargs
ajaykarpur Dec 3, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/factorization_machines.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -277,13 +277,20 @@ class FactorizationMachinesPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"score"`` key of
the ``Record.label`` field. Please refer to the formats details described:
https://docs.aws.amazon.com/sagemaker/latest/dg/fm-in-formats.html
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -292,12 +299,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(FactorizationMachinesPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
16 changes: 13 additions & 3 deletions src/sagemaker/amazon/ipinsights.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -191,7 +191,13 @@ class IPInsightsPredictor(Predictor):
second column should contain the IPv4 address in dot notation.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -200,12 +206,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to text/csv.
deserializer (callable): Optional. Default parses JSON responses
using ``json.load(...)``.
"""
super(IPInsightsPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/kmeans.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -210,12 +210,19 @@ class KMeansPredictor(Predictor):
to fit the model this Predictor performs inference on.

``predict()`` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The nearest cluster is stored in the
``closest_cluster`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -224,12 +231,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KMeansPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/knn.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -199,12 +199,19 @@ class KNNPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -213,12 +220,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KNNPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/lda.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -183,12 +183,19 @@ class LDAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -197,12 +204,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LDAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/linear_learner.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -444,12 +444,19 @@ class LinearLearnerPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -458,12 +465,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LinearLearnerPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/ntm.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -212,12 +212,19 @@ class NTMPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -226,12 +233,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(NTMPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/pca.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -193,12 +193,19 @@ class PCAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -207,12 +214,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(PCAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/randomcutforest.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -171,12 +171,19 @@ class RandomCutForestPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input. Each row's score is stored in the key ``score`` of the
``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -185,12 +192,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(RandomCutForestPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
18 changes: 16 additions & 2 deletions src/sagemaker/chainer/model.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -38,7 +38,13 @@ class ChainerPredictor(Predictor):
multidimensional tensors for Chainer inference.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=NumpySerializer(),
deserializer=NumpyDeserializer(),
):
"""Initialize an ``ChainerPredictor``.

Args:
Expand All@@ -48,9 +54,17 @@ def __init__(self, endpoint_name, sagemaker_session=None):
manages interactions with Amazon SageMaker APIs and any other
AWS services needed. If not specified, the estimator creates one
using the default AWS configuration chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to .npy format. Handles lists and numpy
arrays.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses the response from .npy format to numpy array.
"""
super(ChainerPredictor, self).__init__(
endpoint_name, sagemaker_session, NumpySerializer(), NumpyDeserializer()
endpoint_name,
sagemaker_session,
serializer=serializer,
deserializer=deserializer,
)


Expand Down
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
Skip to content

feature: all predictors support serializer/deserializer overrides#1997

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
ajaykarpur merged 4 commits into from
Dec 3, 2020
Merged

feature: all predictors support serializer/deserializer overrides #1997

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
55303b8
feat: framework predictor de/serial override args
athewsey Nov 20, 2020
028b844
feat: Amz algo predictor de/serial override args
athewsey Nov 20, 2020
ff26090
change: add unit tests for de/ser overrides
athewsey Nov 24, 2020
94a10db
Merge branch 'master' into feat/predictorargs
ajaykarpur Dec 3, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/factorization_machines.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -277,13 +277,20 @@ class FactorizationMachinesPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"score"`` key of
the ``Record.label`` field. Please refer to the formats details described:
https://docs.aws.amazon.com/sagemaker/latest/dg/fm-in-formats.html
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -292,12 +299,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(FactorizationMachinesPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
16 changes: 13 additions & 3 deletions src/sagemaker/amazon/ipinsights.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -191,7 +191,13 @@ class IPInsightsPredictor(Predictor):
second column should contain the IPv4 address in dot notation.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -200,12 +206,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to text/csv.
deserializer (callable): Optional. Default parses JSON responses
using ``json.load(...)``.
"""
super(IPInsightsPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=CSVSerializer(),
deserializer=JSONDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/kmeans.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -210,12 +210,19 @@ class KMeansPredictor(Predictor):
to fit the model this Predictor performs inference on.

``predict()`` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The nearest cluster is stored in the
``closest_cluster`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -224,12 +231,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KMeansPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/knn.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -199,12 +199,19 @@ class KNNPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -213,12 +220,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(KNNPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/lda.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -183,12 +183,19 @@ class LDAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -197,12 +204,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LDAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/linear_learner.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -444,12 +444,19 @@ class LinearLearnerPredictor(Predictor):
to fit the model this Predictor performs inference on.

:func:`predict` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The prediction is stored in the ``"predicted_label"``
key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -458,12 +465,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(LinearLearnerPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/ntm.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -212,12 +212,19 @@ class NTMPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -226,12 +233,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(NTMPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/pca.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -193,12 +193,19 @@ class PCAPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input ``ndarray``. The lower dimension vector result is stored in the
``projection`` key of the ``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -207,12 +214,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(PCAPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
19 changes: 15 additions & 4 deletions src/sagemaker/amazon/randomcutforest.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -171,12 +171,19 @@ class RandomCutForestPredictor(Predictor):
to fit the model this Predictor performs inference on.

:meth:`predict()` returns a list of
:class:`~sagemaker.amazon.record_pb2.Record` objects, one for each row in
:class:`~sagemaker.amazon.record_pb2.Record` objects (assuming the default
recordio-protobuf ``deserializer`` is used), one for each row in
the input. Each row's score is stored in the key ``score`` of the
``Record.label`` field.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
):
"""
Args:
endpoint_name (str): Name of the Amazon SageMaker endpoint to which
Expand All@@ -185,12 +192,16 @@ def __init__(self, endpoint_name, sagemaker_session=None):
object, used for SageMaker interactions (default: None). If not
specified, one is created using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to x-recordio-protobuf format.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses responses from x-recordio-protobuf format.
"""
super(RandomCutForestPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=RecordSerializer(),
deserializer=RecordDeserializer(),
serializer=serializer,
deserializer=deserializer,
)


Expand Down
18 changes: 16 additions & 2 deletions src/sagemaker/chainer/model.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -38,7 +38,13 @@ class ChainerPredictor(Predictor):
multidimensional tensors for Chainer inference.
"""

def __init__(self, endpoint_name, sagemaker_session=None):
def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=NumpySerializer(),
deserializer=NumpyDeserializer(),
):
"""Initialize an ``ChainerPredictor``.

Args:
Expand All@@ -48,9 +54,17 @@ def __init__(self, endpoint_name, sagemaker_session=None):
manages interactions with Amazon SageMaker APIs and any other
AWS services needed. If not specified, the estimator creates one
using the default AWS configuration chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to .npy format. Handles lists and numpy
arrays.
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses the response from .npy format to numpy array.
"""
super(ChainerPredictor, self).__init__(
endpoint_name, sagemaker_session, NumpySerializer(), NumpyDeserializer()
endpoint_name,
sagemaker_session,
serializer=serializer,
deserializer=deserializer,
)


Expand Down
Loading