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change: add py2 deprecation message to estimators and models #768

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Merged
merged 5 commits into from
May 1, 2019
Merged

change: add py2 deprecation message to estimators and models #768

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77a6523
add py2 deprecation message to estimators and models
Apr 26, 2019
9784c43
Merge branch 'master' into warning_msg
ChoiByungWook Apr 30, 2019
9015fe5
test
Apr 30, 2019
c2067d5
add py2 warning message
Apr 30, 2019
5008e94
add newline to warning message
Apr 30, 2019
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4 changes: 4 additions & 0 deletions src/sagemaker/chainer/estimator.py
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Expand Up @@ -90,6 +90,10 @@ def __init__(self, entry_point, use_mpi=None, num_processes=None, process_slots_

super(Chainer, self).__init__(entry_point, source_dir, hyperparameters,
image_name=image_name, **kwargs)

if py_version == 'py2':
logger.warning('chainer py2 container will be deprecated soon.')
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  • s/chainer py2 container/The Python 2 Chainer images
    • same applies to the others (also make sure the right framework name is in the message for some of the ones below)
  • I'd add a more actionable statement after the warning, e.g. "Set py_version='py3' to use a Python 3 image." This would be especially helpful with the frameworks where Python 2 is the default - users may not be aware of the py_version kwarg when using those.


self.py_version = py_version
self.use_mpi = use_mpi
self.num_processes = num_processes
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7 changes: 7 additions & 0 deletions src/sagemaker/chainer/model.py
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Expand Up @@ -12,12 +12,16 @@
# language governing permissions and limitations under the License.
from __future__ import absolute_import

import logging

import sagemaker
from sagemaker.fw_utils import create_image_uri, model_code_key_prefix
from sagemaker.model import FrameworkModel, MODEL_SERVER_WORKERS_PARAM_NAME
from sagemaker.chainer.defaults import CHAINER_VERSION
from sagemaker.predictor import RealTimePredictor, npy_serializer, numpy_deserializer

logger = logging.getLogger('sagemaker')


class ChainerPredictor(RealTimePredictor):
"""A RealTimePredictor for inference against Chainer Endpoints.
Expand Down Expand Up @@ -66,6 +70,9 @@ def __init__(self, model_data, role, entry_point, image=None, py_version='py3',
"""
super(ChainerModel, self).__init__(model_data, image, role, entry_point, predictor_cls=predictor_cls,
**kwargs)
if py_version == 'py2':
logger.warning('chainer py2 container will be deprecated soon.')

self.py_version = py_version
self.framework_version = framework_version
self.model_server_workers = model_server_workers
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4 changes: 4 additions & 0 deletions src/sagemaker/mxnet/estimator.py
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Expand Up @@ -79,6 +79,10 @@ def __init__(self, entry_point, source_dir=None, hyperparameters=None, py_versio

super(MXNet, self).__init__(entry_point, source_dir, hyperparameters,
image_name=image_name, **kwargs)

if py_version == 'py2':
logger.warning('mxnet py2 container will be deprecated soon.')

self.py_version = py_version
self._configure_distribution(distributions)

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8 changes: 8 additions & 0 deletions src/sagemaker/mxnet/model.py
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Expand Up @@ -12,12 +12,16 @@
# language governing permissions and limitations under the License.
from __future__ import absolute_import

import logging

import sagemaker
from sagemaker.fw_utils import create_image_uri, model_code_key_prefix
from sagemaker.model import FrameworkModel, MODEL_SERVER_WORKERS_PARAM_NAME
from sagemaker.mxnet.defaults import MXNET_VERSION
from sagemaker.predictor import RealTimePredictor, json_serializer, json_deserializer

logger = logging.getLogger('sagemaker')


class MXNetPredictor(RealTimePredictor):
"""A RealTimePredictor for inference against MXNet Endpoints.
Expand Down Expand Up @@ -66,6 +70,10 @@ def __init__(self, model_data, role, entry_point, image=None, py_version='py2',
"""
super(MXNetModel, self).__init__(model_data, image, role, entry_point, predictor_cls=predictor_cls,
**kwargs)

if py_version == 'py2':
logger.warning('chainer py2 container will be deprecated soon.')

self.py_version = py_version
self.framework_version = framework_version
self.model_server_workers = model_server_workers
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4 changes: 4 additions & 0 deletions src/sagemaker/pytorch/estimator.py
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Expand Up @@ -74,6 +74,10 @@ def __init__(self, entry_point, source_dir=None, hyperparameters=None, py_versio
self.framework_version = framework_version or PYTORCH_VERSION

super(PyTorch, self).__init__(entry_point, source_dir, hyperparameters, image_name=image_name, **kwargs)

if py_version == 'py2':
logger.warning('pytorch py2 container will be deprecated soon.')

self.py_version = py_version

def create_model(self, model_server_workers=None, role=None, vpc_config_override=VPC_CONFIG_DEFAULT):
Expand Down
9 changes: 9 additions & 0 deletions src/sagemaker/pytorch/model.py
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Expand Up @@ -11,12 +11,17 @@
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
from __future__ import absolute_import

import logging

import sagemaker
from sagemaker.fw_utils import create_image_uri, model_code_key_prefix
from sagemaker.model import FrameworkModel, MODEL_SERVER_WORKERS_PARAM_NAME
from sagemaker.pytorch.defaults import PYTORCH_VERSION, PYTHON_VERSION
from sagemaker.predictor import RealTimePredictor, npy_serializer, numpy_deserializer

logger = logging.getLogger('sagemaker')


class PyTorchPredictor(RealTimePredictor):
"""A RealTimePredictor for inference against PyTorch Endpoints.
Expand Down Expand Up @@ -65,6 +70,10 @@ def __init__(self, model_data, role, entry_point, image=None, py_version=PYTHON_
**kwargs: Keyword arguments passed to the ``FrameworkModel`` initializer.
"""
super(PyTorchModel, self).__init__(model_data, image, role, entry_point, predictor_cls=predictor_cls, **kwargs)

if py_version == 'py2':
logger.warning('pytorch py2 container will be deprecated soon.')

self.py_version = py_version
self.framework_version = framework_version
self.model_server_workers = model_server_workers
Expand Down
4 changes: 4 additions & 0 deletions src/sagemaker/tensorflow/estimator.py
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Expand Up @@ -236,6 +236,10 @@ def __init__(self, training_steps=None, evaluation_steps=None, checkpoint_path=N

super(TensorFlow, self).__init__(image_name=image_name, **kwargs)
self.checkpoint_path = checkpoint_path

if py_version == 'py2':
LOGGER.warning('tensorflow py2 container will be deprecated soon.')

self.py_version = py_version
self.training_steps = training_steps
self.evaluation_steps = evaluation_steps
Expand Down
8 changes: 8 additions & 0 deletions src/sagemaker/tensorflow/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,13 +12,17 @@
# language governing permissions and limitations under the License.
from __future__ import absolute_import

import logging

import sagemaker
from sagemaker.fw_utils import create_image_uri, model_code_key_prefix
from sagemaker.model import FrameworkModel, MODEL_SERVER_WORKERS_PARAM_NAME
from sagemaker.predictor import RealTimePredictor
from sagemaker.tensorflow.defaults import TF_VERSION
from sagemaker.tensorflow.predictor import tf_json_serializer, tf_json_deserializer

LOGGER = logging.getLogger('sagemaker')


class TensorFlowPredictor(RealTimePredictor):
"""A ``RealTimePredictor`` for inference against TensorFlow endpoint.
Expand Down Expand Up @@ -67,6 +71,10 @@ def __init__(self, model_data, role, entry_point, image=None, py_version='py2',
"""
super(TensorFlowModel, self).__init__(model_data, image, role, entry_point, predictor_cls=predictor_cls,
**kwargs)

if py_version == 'py2':
LOGGER.warning('tensorflow py2 container will be deprecated soon.')

self.py_version = py_version
self.framework_version = framework_version
self.model_server_workers = model_server_workers
Expand Down