feature: support TensorFlow training 2.2#1521

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chuyang-deng merged 33 commits into from
May 22, 2020
Merged

feature: support TensorFlow training 2.2 #1521

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1c9dd16
update with aws/master
chuyang-deng May 15, 2020
aa349fd
upate with aws master
chuyang-deng May 18, 2020
c875c47
update with aws master
chuyang-deng May 19, 2020
3e23a39
feature: TensorFlow 2.2 support
May 19, 2020
e9a96ec
Merge branch 'master' into tf-2-2
chuyang-deng May 19, 2020
1d66433
prevent TFS test pulling 2.2.0 images
May 20, 2020
dc8e4f7
Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …
May 20, 2020
98a0a5e
fix flake8 error
May 20, 2020
7f44c65
update tfs test versions
May 21, 2020
b33deb9
use tfs 2.1.0 in model monitor tests
May 21, 2020
8da6509
distinguish tf and tfs latest versions in test
May 21, 2020
4f85786
add latest serving version
May 21, 2020
cb2a489
let py_version pick up tf_training_version
May 21, 2020
c9dcdd0
Merge branch 'master' into tf-2-2
chuyang-deng May 21, 2020
ed177e8
fix typo
May 21, 2020
816030e
Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …
May 21, 2020
0b77be7
no py37 for tfs 2.1
May 21, 2020
89bb6d6
fix black error
May 21, 2020
40da473
prevent tfs pulling 2.2 image
May 20, 2020
c251fcc
tf 2.2 using py37
May 21, 2020
e010da9
Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …
May 21, 2020
edeb501
Merge branch 'master' into tf-2-2
chuyang-deng May 21, 2020
3255b04
test_data_capture_config use TFS latest version
May 21, 2020
403298e
Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …
May 21, 2020
2a7f154
fix flake8 error
May 21, 2020
3b10a76
update model monitoring test
May 21, 2020
9c2bb6c
update python version for tuner integ test
May 21, 2020
fe14848
address comments
May 22, 2020
fa84753
Merge branch 'ChuyangDeng-tf-2-2'
May 22, 2020
ff376d8
fix import error
May 22, 2020
598f833
resolve conflicts
May 22, 2020
31110b4
hardcode py_version for tensorflow-training 2.2 tests
May 22, 2020
fa04c1a
import LATEST_SERVING_VERSION from TensorFlow.defaults
May 22, 2020
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2 changes: 1 addition & 1 deletion doc/using_tf.rst
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Expand Up@@ -20,7 +20,7 @@ For general information about using the SageMaker Python SDK, see :ref:`overview

.. contents::

Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``.
Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``, ``1.15``, ``2.0``.


*****************************
Expand Down
5 changes: 4 additions & 1 deletion src/sagemaker/tensorflow/defaults.py
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Expand Up@@ -18,7 +18,10 @@
This is no longer updated so as to not break existing workflows.
"""

LATEST_VERSION = "2.1.0"
LATEST_VERSION = "2.2.0"
"""The latest version of TensorFlow included in the SageMaker pre-built Docker images."""

LATEST_SERVING_VERSION = "2.1.0"
"""The latest version of TensorFlow Serving included in the SageMaker pre-built Docker images."""

LATEST_PY2_VERSION = "2.1.0"
12 changes: 10 additions & 2 deletions tests/conftest.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,8 @@
from sagemaker.pytorch import PyTorch
from sagemaker.rl import RLEstimator
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.tensorflow.estimator import TensorFlow
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION, LATEST_SERVING_VERSION

DEFAULT_REGION = "us-west-2"
CUSTOM_BUCKET_NAME_PREFIX = "sagemaker-custom-bucket"
Expand DownExpand Up@@ -259,7 +260,7 @@ def sklearn_full_version(request):
return request.config.getoption("--sklearn-full-version")


@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, TensorFlow.LATEST_VERSION])
@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, LATEST_VERSION])
def tf_full_version(request):
tf_version = request.config.getoption("--tf-full-version")
if tf_version is None:
Expand DownExpand Up@@ -335,3 +336,10 @@ def pytest_generate_tests(metafunc):
@pytest.fixture(scope="module")
def xgboost_full_version(request):
return request.config.getoption("--xgboost-full-version")


@pytest.fixture(scope="module")
def tf_serving_version(tf_full_version):
if tf_full_version == LATEST_VERSION:
return LATEST_SERVING_VERSION
return tf_full_version
12 changes: 6 additions & 6 deletions tests/integ/test_data_capture_config.py
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Expand Up@@ -41,7 +41,7 @@


def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
sagemaker_session, tf_full_version
sagemaker_session, tf_serving_version
):
endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
model_data = sagemaker_session.upload_data(
Expand All@@ -52,7 +52,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
model = Model(
model_data=model_data,
role=ROLE,
framework_version=tf_full_version,
framework_version=tf_serving_version,
sagemaker_session=sagemaker_session,
)
predictor = model.deploy(
Expand DownExpand Up@@ -98,7 +98,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
sagemaker_session, tf_full_version
sagemaker_session, tf_serving_version
):
endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
model_data = sagemaker_session.upload_data(
Expand All@@ -109,7 +109,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
model = Model(
model_data=model_data,
role=ROLE,
framework_version=tf_full_version,
framework_version=tf_serving_version,
sagemaker_session=sagemaker_session,
)
destination_s3_uri = os.path.join(
Expand DownExpand Up@@ -184,7 +184,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
sagemaker_session, tf_full_version
sagemaker_session, tf_serving_version
):
endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
model_data = sagemaker_session.upload_data(
Expand All@@ -195,7 +195,7 @@ def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
model = Model(
model_data=model_data,
role=ROLE,
framework_version=tf_full_version,
framework_version=tf_serving_version,
sagemaker_session=sagemaker_session,
)
destination_s3_uri = os.path.join(
Expand Down
4 changes: 2 additions & 2 deletions tests/integ/test_model_monitor.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -88,7 +88,7 @@


@pytest.fixture(scope="module")
def predictor(sagemaker_session, tf_full_version):
def predictor(sagemaker_session, tf_serving_version):
endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
model_data = sagemaker_session.upload_data(
path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -100,7 +100,7 @@ def predictor(sagemaker_session, tf_full_version):
model = Model(
model_data=model_data,
role=ROLE,
framework_version=tf_full_version,
framework_version=tf_serving_version,
sagemaker_session=sagemaker_session,
)
predictor = model.deploy(
Expand Down
23 changes: 12 additions & 11 deletions tests/integ/test_tf_script_mode.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
import pytest

from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.utils import unique_name_from_base, sagemaker_timestamp

import tests.integ
Expand All@@ -40,10 +41,8 @@


@pytest.fixture(scope="module")
def py_version(tf_full_version):
return (
"py37" if tf_full_version == TensorFlow._LATEST_1X_VERSION else tests.integ.PYTHON_VERSION
)
def py_version(tf_full_version, tf_serving_version):
return "py37" if tf_full_version == tf_serving_version else tests.integ.PYTHON_VERSION


def test_mnist_with_checkpoint_config(
Expand All@@ -61,7 +60,7 @@ def test_mnist_with_checkpoint_config(
sagemaker_session=sagemaker_session,
script_mode=True,
framework_version=tf_full_version,
py_version=py_version,
py_version="py37",
Comment thread
laurenyu marked this conversation as resolved.
metric_definitions=[{"Name": "train:global_steps", "Regex": r"global_step\/sec:\s(.*)"}],
checkpoint_s3_uri=checkpoint_s3_uri,
checkpoint_local_path=checkpoint_local_path,
Expand DownExpand Up@@ -91,7 +90,7 @@ def test_mnist_with_checkpoint_config(
assert actual_training_checkpoint_config == expected_training_checkpoint_config


def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
def test_server_side_encryption(sagemaker_session, tf_serving_version, py_version):
with kms_utils.bucket_with_encryption(sagemaker_session, ROLE) as (bucket_with_kms, kms_key):
output_path = os.path.join(
bucket_with_kms, "test-server-side-encryption", time.strftime("%y%m%d-%H%M")
Expand All@@ -105,7 +104,7 @@ def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
train_instance_type="ml.c5.xlarge",
sagemaker_session=sagemaker_session,
script_mode=True,
framework_version=tf_full_version,
framework_version=tf_serving_version,

@laurenyulaurenyuMay 22, 2020

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why switch to using a serving version for training?

@chuyang-dengchuyang-dengMay 22, 2020

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because this test is doing a deploy later and TFS does not support 2.2 yet.

py_version=py_version,
code_location=output_path,
output_path=output_path,
Expand DownExpand Up@@ -140,7 +139,7 @@ def test_mnist_distributed(sagemaker_session, instance_type, tf_full_version, py
train_instance_count=2,
train_instance_type=instance_type,
sagemaker_session=sagemaker_session,
py_version=py_version,
py_version="py37",
script_mode=True,
framework_version=tf_full_version,
distributions=PARAMETER_SERVER_DISTRIBUTION,
Expand DownExpand Up@@ -168,7 +167,7 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
sagemaker_session=sagemaker_session,
script_mode=True,
# testing py-sdk functionality, no need to run against all TF versions
framework_version=TensorFlow.LATEST_VERSION,
framework_version=LATEST_SERVING_VERSION,
tags=TAGS,
)
inputs = estimator.sagemaker_session.upload_data(
Expand DownExpand Up@@ -200,7 +199,9 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
_assert_model_name_match(sagemaker_session.sagemaker_client, endpoint_name, model_name)


def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_version, py_version):
def test_deploy_with_input_handlers(
sagemaker_session, instance_type, tf_serving_version, py_version
):
estimator = TensorFlow(
entry_point="training.py",
source_dir=TFS_RESOURCE_PATH,
Expand All@@ -210,7 +211,7 @@ def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_ve
py_version=py_version,
sagemaker_session=sagemaker_session,
script_mode=True,
framework_version=tf_full_version,
framework_version=tf_serving_version,
tags=TAGS,
)

Expand Down
12 changes: 6 additions & 6 deletions tests/integ/test_tfs.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,7 @@


@pytest.fixture(scope="module")
def tfs_predictor(sagemaker_session, tf_full_version):
def tfs_predictor(sagemaker_session, tf_serving_version):
endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
model_data = sagemaker_session.upload_data(
path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -37,7 +37,7 @@ def tfs_predictor(sagemaker_session, tf_full_version):
model = Model(
model_data=model_data,
role="SageMakerRole",
framework_version=tf_full_version,
framework_version=tf_serving_version,
sagemaker_session=sagemaker_session,
)
predictor = model.deploy(1, "ml.c5.xlarge", endpoint_name=endpoint_name)
Expand All@@ -54,7 +54,7 @@ def tar_dir(directory, tmpdir):

@pytest.fixture
def tfs_predictor_with_model_and_entry_point_same_tar(
sagemaker_local_session, tf_full_version, tmpdir
sagemaker_local_session, tf_serving_version, tmpdir
):
endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -65,7 +65,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(
model = Model(
model_data="file://" + model_tar,
role="SageMakerRole",
framework_version=tf_full_version,
framework_version=tf_serving_version,
sagemaker_session=sagemaker_local_session,
)
predictor = model.deploy(1, "local", endpoint_name=endpoint_name)
Expand All@@ -78,7 +78,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(

@pytest.fixture(scope="module")
def tfs_predictor_with_model_and_entry_point_and_dependencies(
sagemaker_local_session, tf_full_version
sagemaker_local_session, tf_serving_version
):
endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -98,7 +98,7 @@ def tfs_predictor_with_model_and_entry_point_and_dependencies(
model_data=model_data,
role="SageMakerRole",
dependencies=dependencies,
framework_version=tf_full_version,
framework_version=tf_serving_version,
sagemaker_session=sagemaker_local_session,
)

Expand Down
3 changes: 2 additions & 1 deletion tests/integ/test_transformer.py
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Expand Up@@ -25,6 +25,7 @@
from sagemaker.mxnet import MXNet
from sagemaker.pytorch import PyTorchModel
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.transformer import Transformer
from sagemaker.estimator import Estimator
from sagemaker.utils import unique_name_from_base
Expand DownExpand Up@@ -351,7 +352,7 @@ def test_transform_tf_kms_network_isolation(sagemaker_session, cpu_instance_type
role="SageMakerRole",
train_instance_count=1,
train_instance_type=cpu_instance_type,
framework_version=TensorFlow.LATEST_VERSION,
framework_version=LATEST_SERVING_VERSION,
script_mode=True,
py_version=PYTHON_VERSION,
sagemaker_session=sagemaker_session,
Expand Down
12 changes: 10 additions & 2 deletions tests/integ/test_tuner.py
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Expand Up@@ -37,6 +37,7 @@
from sagemaker.predictor import json_deserializer
from sagemaker.pytorch import PyTorch
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION
from sagemaker.tuner import (
IntegerParameter,
ContinuousParameter,
Expand All@@ -51,6 +52,13 @@

DATA_PATH = os.path.join(DATA_DIR, "iris", "data")

PY37_SUPPORTED_FRAMEWORK_VERSION = [TensorFlow._LATEST_1X_VERSION, LATEST_VERSION]


@pytest.fixture(scope="module")
def py_version(tf_full_version):
return "py37" if tf_full_version in PY37_SUPPORTED_FRAMEWORK_VERSION else PYTHON_VERSION


@pytest.fixture(scope="module")
def kmeans_train_set(sagemaker_session):
Expand DownExpand Up@@ -590,7 +598,7 @@ def test_tuning_mxnet(sagemaker_session, mxnet_full_version, cpu_instance_type):


@pytest.mark.canary_quick
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version):
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version, py_version):
resource_path = os.path.join(DATA_DIR, "tensorflow_mnist")
script_path = os.path.join(resource_path, "mnist.py")

Expand All@@ -601,7 +609,7 @@ def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_ver
train_instance_type=cpu_instance_type,
script_mode=True,
sagemaker_session=sagemaker_session,
py_version=PYTHON_VERSION,
py_version=py_version,
framework_version=tf_full_version,
)

Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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feature: support TensorFlow training 2.2#1521

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 Merged

chuyang-deng
merged 33 commits into

from

May 22, 2020
 Merged


feature: support TensorFlow training 2.2
#1521
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1c9dd16

update with aws/master


chuyang-deng May 15, 2020
aa349fd

upate with aws master


chuyang-deng May 18, 2020
c875c47

update with aws master


chuyang-deng May 19, 2020
3e23a39

feature: TensorFlow 2.2 support

May 19, 2020
e9a96ec

Merge branch 'master' into tf-2-2


chuyang-deng May 19, 2020
1d66433

prevent TFS test pulling 2.2.0 images

May 20, 2020
dc8e4f7

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 20, 2020
98a0a5e

fix flake8 error

May 20, 2020
7f44c65

update tfs test versions

May 21, 2020
b33deb9

use tfs 2.1.0 in model monitor tests

May 21, 2020
8da6509

distinguish tf and tfs latest versions in test

May 21, 2020
4f85786

add latest serving version

May 21, 2020
cb2a489

let py_version pick up tf_training_version

May 21, 2020
c9dcdd0

Merge branch 'master' into tf-2-2


chuyang-deng May 21, 2020
ed177e8

fix typo

May 21, 2020
816030e

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
0b77be7

no py37 for tfs 2.1

May 21, 2020
89bb6d6

fix black error

May 21, 2020
40da473

prevent tfs pulling 2.2 image

May 20, 2020
c251fcc

tf 2.2 using py37

May 21, 2020
e010da9

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
edeb501

Merge branch 'master' into tf-2-2


chuyang-deng May 21, 2020
3255b04

test_data_capture_config use TFS latest version

May 21, 2020
403298e

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
2a7f154

fix flake8 error

May 21, 2020
3b10a76

update model monitoring test

May 21, 2020
9c2bb6c

update python version for tuner integ test

May 21, 2020
fe14848

address comments

May 22, 2020
fa84753

Merge branch 'ChuyangDeng-tf-2-2'

May 22, 2020
ff376d8

fix import error

May 22, 2020
598f833

resolve conflicts

May 22, 2020
31110b4

hardcode py_version for tensorflow-training 2.2 tests

May 22, 2020
fa04c1a

import LATEST_SERVING_VERSION from TensorFlow.defaults

May 22, 2020

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2 changes: 1 addition & 1 deletion
doc/using_tf.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -20,7 +20,7 @@ For general information about using the SageMaker Python SDK, see :ref:`overview

.. contents::

Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``.
Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``, ``1.15``, ``2.0``.


*****************************
Expand Down

5 changes: 4 additions & 1 deletion
src/sagemaker/tensorflow/defaults.py

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Expand Up@@ -18,7 +18,10 @@
This is no longer updated so as to not break existing workflows.
"""

LATEST_VERSION = "2.1.0"
LATEST_VERSION = "2.2.0"
"""The latest version of TensorFlow included in the SageMaker pre-built Docker images."""

LATEST_SERVING_VERSION = "2.1.0"
"""The latest version of TensorFlow Serving included in the SageMaker pre-built Docker images."""

LATEST_PY2_VERSION = "2.1.0"

12 changes: 10 additions & 2 deletions
tests/conftest.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,8 @@
from sagemaker.pytorch import PyTorch
from sagemaker.rl import RLEstimator
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.tensorflow.estimator import TensorFlow
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION, LATEST_SERVING_VERSION

DEFAULT_REGION = "us-west-2"
CUSTOM_BUCKET_NAME_PREFIX = "sagemaker-custom-bucket"
Expand DownExpand Up@@ -259,7 +260,7 @@ def sklearn_full_version(request):
 return request.config.getoption("--sklearn-full-version")


@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, TensorFlow.LATEST_VERSION])
@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, LATEST_VERSION])
def tf_full_version(request):
 tf_version = request.config.getoption("--tf-full-version")
 if tf_version is None:
Expand DownExpand Up@@ -335,3 +336,10 @@ def pytest_generate_tests(metafunc):
@pytest.fixture(scope="module")
def xgboost_full_version(request):
 return request.config.getoption("--xgboost-full-version")


@pytest.fixture(scope="module")
def tf_serving_version(tf_full_version):
 if tf_full_version == LATEST_VERSION:
 return LATEST_SERVING_VERSION
 return tf_full_version

12 changes: 6 additions & 6 deletions
tests/integ/test_data_capture_config.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -41,7 +41,7 @@


def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -52,7 +52,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(
Expand DownExpand Up@@ -98,7 +98,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -109,7 +109,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 destination_s3_uri = os.path.join(
Expand DownExpand Up@@ -184,7 +184,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -195,7 +195,7 @@ def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 destination_s3_uri = os.path.join(
Expand Down

4 changes: 2 additions & 2 deletions
tests/integ/test_model_monitor.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -88,7 +88,7 @@


@pytest.fixture(scope="module")
def predictor(sagemaker_session, tf_full_version):
def predictor(sagemaker_session, tf_serving_version):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
 path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -100,7 +100,7 @@ def predictor(sagemaker_session, tf_full_version):
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(
Expand Down

23 changes: 12 additions & 11 deletions
tests/integ/test_tf_script_mode.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
import pytest

from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.utils import unique_name_from_base, sagemaker_timestamp

import tests.integ
Expand All@@ -40,10 +41,8 @@


@pytest.fixture(scope="module")
def py_version(tf_full_version):
 return (
 "py37" if tf_full_version == TensorFlow._LATEST_1X_VERSION else tests.integ.PYTHON_VERSION
 )
def py_version(tf_full_version, tf_serving_version):
 return "py37" if tf_full_version == tf_serving_version else tests.integ.PYTHON_VERSION


def test_mnist_with_checkpoint_config(
Expand All@@ -61,7 +60,7 @@ def test_mnist_with_checkpoint_config(
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 py_version=py_version,
 py_version="py37",
Comment thread
laurenyu marked this conversation as resolved.

 metric_definitions=[{"Name": "train:global_steps", "Regex": r"global_step\/sec:\s(.*)"}],
 checkpoint_s3_uri=checkpoint_s3_uri,
 checkpoint_local_path=checkpoint_local_path,
Expand DownExpand Up@@ -91,7 +90,7 @@ def test_mnist_with_checkpoint_config(
 assert actual_training_checkpoint_config == expected_training_checkpoint_config


def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
def test_server_side_encryption(sagemaker_session, tf_serving_version, py_version):
 with kms_utils.bucket_with_encryption(sagemaker_session, ROLE) as (bucket_with_kms, kms_key):
 output_path = os.path.join(
 bucket_with_kms, "test-server-side-encryption", time.strftime("%y%m%d-%H%M")
Expand All@@ -105,7 +104,7 @@ def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
 train_instance_type="ml.c5.xlarge",
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
@laurenyulaurenyuMay 22, 2020

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why switch to using a serving version for training?
@chuyang-dengchuyang-dengMay 22, 2020

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because this test is doing a deploy later and TFS does not support 2.2 yet.
 py_version=py_version,
 code_location=output_path,
 output_path=output_path,
Expand DownExpand Up@@ -140,7 +139,7 @@ def test_mnist_distributed(sagemaker_session, instance_type, tf_full_version, py
 train_instance_count=2,
 train_instance_type=instance_type,
 sagemaker_session=sagemaker_session,
 py_version=py_version,
 py_version="py37",
 script_mode=True,
 framework_version=tf_full_version,
 distributions=PARAMETER_SERVER_DISTRIBUTION,
Expand DownExpand Up@@ -168,7 +167,7 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
 sagemaker_session=sagemaker_session,
 script_mode=True,
 # testing py-sdk functionality, no need to run against all TF versions
 framework_version=TensorFlow.LATEST_VERSION,
 framework_version=LATEST_SERVING_VERSION,
 tags=TAGS,
 )
 inputs = estimator.sagemaker_session.upload_data(
Expand DownExpand Up@@ -200,7 +199,9 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
 _assert_model_name_match(sagemaker_session.sagemaker_client, endpoint_name, model_name)


def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_version, py_version):
def test_deploy_with_input_handlers(
 sagemaker_session, instance_type, tf_serving_version, py_version
):
 estimator = TensorFlow(
 entry_point="training.py",
 source_dir=TFS_RESOURCE_PATH,
Expand All@@ -210,7 +211,7 @@ def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_ve
 py_version=py_version,
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 tags=TAGS,
 )

Expand Down

12 changes: 6 additions & 6 deletions
tests/integ/test_tfs.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,7 @@


@pytest.fixture(scope="module")
def tfs_predictor(sagemaker_session, tf_full_version):
def tfs_predictor(sagemaker_session, tf_serving_version):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
 path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -37,7 +37,7 @@ def tfs_predictor(sagemaker_session, tf_full_version):
 model = Model(
 model_data=model_data,
 role="SageMakerRole",
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(1, "ml.c5.xlarge", endpoint_name=endpoint_name)
Expand All@@ -54,7 +54,7 @@ def tar_dir(directory, tmpdir):

@pytest.fixture
def tfs_predictor_with_model_and_entry_point_same_tar(
 sagemaker_local_session, tf_full_version, tmpdir
 sagemaker_local_session, tf_serving_version, tmpdir
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -65,7 +65,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(
 model = Model(
 model_data="file://" + model_tar,
 role="SageMakerRole",
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_local_session,
 )
 predictor = model.deploy(1, "local", endpoint_name=endpoint_name)
Expand All@@ -78,7 +78,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(

@pytest.fixture(scope="module")
def tfs_predictor_with_model_and_entry_point_and_dependencies(
 sagemaker_local_session, tf_full_version
 sagemaker_local_session, tf_serving_version
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -98,7 +98,7 @@ def tfs_predictor_with_model_and_entry_point_and_dependencies(
 model_data=model_data,
 role="SageMakerRole",
 dependencies=dependencies,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_local_session,
 )

Expand Down

3 changes: 2 additions & 1 deletion
tests/integ/test_transformer.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -25,6 +25,7 @@
from sagemaker.mxnet import MXNet
from sagemaker.pytorch import PyTorchModel
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.transformer import Transformer
from sagemaker.estimator import Estimator
from sagemaker.utils import unique_name_from_base
Expand DownExpand Up@@ -351,7 +352,7 @@ def test_transform_tf_kms_network_isolation(sagemaker_session, cpu_instance_type
 role="SageMakerRole",
 train_instance_count=1,
 train_instance_type=cpu_instance_type,
 framework_version=TensorFlow.LATEST_VERSION,
 framework_version=LATEST_SERVING_VERSION,
 script_mode=True,
 py_version=PYTHON_VERSION,
 sagemaker_session=sagemaker_session,
Expand Down

12 changes: 10 additions & 2 deletions
tests/integ/test_tuner.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -37,6 +37,7 @@
from sagemaker.predictor import json_deserializer
from sagemaker.pytorch import PyTorch
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION
from sagemaker.tuner import (
 IntegerParameter,
 ContinuousParameter,
Expand All@@ -51,6 +52,13 @@

DATA_PATH = os.path.join(DATA_DIR, "iris", "data")

PY37_SUPPORTED_FRAMEWORK_VERSION = [TensorFlow._LATEST_1X_VERSION, LATEST_VERSION]


@pytest.fixture(scope="module")
def py_version(tf_full_version):
 return "py37" if tf_full_version in PY37_SUPPORTED_FRAMEWORK_VERSION else PYTHON_VERSION


@pytest.fixture(scope="module")
def kmeans_train_set(sagemaker_session):
Expand DownExpand Up@@ -590,7 +598,7 @@ def test_tuning_mxnet(sagemaker_session, mxnet_full_version, cpu_instance_type):


@pytest.mark.canary_quick
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version):
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version, py_version):
 resource_path = os.path.join(DATA_DIR, "tensorflow_mnist")
 script_path = os.path.join(resource_path, "mnist.py")

Expand All@@ -601,7 +609,7 @@ def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_ver
 train_instance_type=cpu_instance_type,
 script_mode=True,
 sagemaker_session=sagemaker_session,
 py_version=PYTHON_VERSION,
 py_version=py_version,
 framework_version=tf_full_version,
 )

Expand Down

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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");
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 Merged

chuyang-deng
merged 33 commits into

from

May 22, 2020
 Merged


feature: support TensorFlow training 2.2
#1521
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1c9dd16

update with aws/master


chuyang-deng May 15, 2020
aa349fd

upate with aws master


chuyang-deng May 18, 2020
c875c47

update with aws master


chuyang-deng May 19, 2020
3e23a39

feature: TensorFlow 2.2 support

May 19, 2020
e9a96ec

Merge branch 'master' into tf-2-2


chuyang-deng May 19, 2020
1d66433

prevent TFS test pulling 2.2.0 images

May 20, 2020
dc8e4f7

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 20, 2020
98a0a5e

fix flake8 error

May 20, 2020
7f44c65

update tfs test versions

May 21, 2020
b33deb9

use tfs 2.1.0 in model monitor tests

May 21, 2020
8da6509

distinguish tf and tfs latest versions in test

May 21, 2020
4f85786

add latest serving version

May 21, 2020
cb2a489

let py_version pick up tf_training_version

May 21, 2020
c9dcdd0

Merge branch 'master' into tf-2-2


chuyang-deng May 21, 2020
ed177e8

fix typo

May 21, 2020
816030e

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
0b77be7

no py37 for tfs 2.1

May 21, 2020
89bb6d6

fix black error

May 21, 2020
40da473

prevent tfs pulling 2.2 image

May 20, 2020
c251fcc

tf 2.2 using py37

May 21, 2020
e010da9

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
edeb501

Merge branch 'master' into tf-2-2


chuyang-deng May 21, 2020
3255b04

test_data_capture_config use TFS latest version

May 21, 2020
403298e

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
2a7f154

fix flake8 error

May 21, 2020
3b10a76

update model monitoring test

May 21, 2020
9c2bb6c

update python version for tuner integ test

May 21, 2020
fe14848

address comments

May 22, 2020
fa84753

Merge branch 'ChuyangDeng-tf-2-2'

May 22, 2020
ff376d8

fix import error

May 22, 2020
598f833

resolve conflicts

May 22, 2020
31110b4

hardcode py_version for tensorflow-training 2.2 tests

May 22, 2020
fa04c1a

import LATEST_SERVING_VERSION from TensorFlow.defaults

May 22, 2020

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2 changes: 1 addition & 1 deletion
doc/using_tf.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -20,7 +20,7 @@ For general information about using the SageMaker Python SDK, see :ref:`overview

.. contents::

Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``.
Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``, ``1.15``, ``2.0``.


*****************************
Expand Down

5 changes: 4 additions & 1 deletion
src/sagemaker/tensorflow/defaults.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -18,7 +18,10 @@
This is no longer updated so as to not break existing workflows.
"""

LATEST_VERSION = "2.1.0"
LATEST_VERSION = "2.2.0"
"""The latest version of TensorFlow included in the SageMaker pre-built Docker images."""

LATEST_SERVING_VERSION = "2.1.0"
"""The latest version of TensorFlow Serving included in the SageMaker pre-built Docker images."""

LATEST_PY2_VERSION = "2.1.0"

12 changes: 10 additions & 2 deletions
tests/conftest.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,8 @@
from sagemaker.pytorch import PyTorch
from sagemaker.rl import RLEstimator
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.tensorflow.estimator import TensorFlow
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION, LATEST_SERVING_VERSION

DEFAULT_REGION = "us-west-2"
CUSTOM_BUCKET_NAME_PREFIX = "sagemaker-custom-bucket"
Expand DownExpand Up@@ -259,7 +260,7 @@ def sklearn_full_version(request):
 return request.config.getoption("--sklearn-full-version")


@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, TensorFlow.LATEST_VERSION])
@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, LATEST_VERSION])
def tf_full_version(request):
 tf_version = request.config.getoption("--tf-full-version")
 if tf_version is None:
Expand DownExpand Up@@ -335,3 +336,10 @@ def pytest_generate_tests(metafunc):
@pytest.fixture(scope="module")
def xgboost_full_version(request):
 return request.config.getoption("--xgboost-full-version")


@pytest.fixture(scope="module")
def tf_serving_version(tf_full_version):
 if tf_full_version == LATEST_VERSION:
 return LATEST_SERVING_VERSION
 return tf_full_version

12 changes: 6 additions & 6 deletions
tests/integ/test_data_capture_config.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -41,7 +41,7 @@


def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -52,7 +52,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(
Expand DownExpand Up@@ -98,7 +98,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -109,7 +109,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 destination_s3_uri = os.path.join(
Expand DownExpand Up@@ -184,7 +184,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -195,7 +195,7 @@ def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 destination_s3_uri = os.path.join(
Expand Down

4 changes: 2 additions & 2 deletions
tests/integ/test_model_monitor.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -88,7 +88,7 @@


@pytest.fixture(scope="module")
def predictor(sagemaker_session, tf_full_version):
def predictor(sagemaker_session, tf_serving_version):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
 path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -100,7 +100,7 @@ def predictor(sagemaker_session, tf_full_version):
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(
Expand Down

23 changes: 12 additions & 11 deletions
tests/integ/test_tf_script_mode.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
import pytest

from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.utils import unique_name_from_base, sagemaker_timestamp

import tests.integ
Expand All@@ -40,10 +41,8 @@


@pytest.fixture(scope="module")
def py_version(tf_full_version):
 return (
 "py37" if tf_full_version == TensorFlow._LATEST_1X_VERSION else tests.integ.PYTHON_VERSION
 )
def py_version(tf_full_version, tf_serving_version):
 return "py37" if tf_full_version == tf_serving_version else tests.integ.PYTHON_VERSION


def test_mnist_with_checkpoint_config(
Expand All@@ -61,7 +60,7 @@ def test_mnist_with_checkpoint_config(
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 py_version=py_version,
 py_version="py37",
Comment thread
laurenyu marked this conversation as resolved.

 metric_definitions=[{"Name": "train:global_steps", "Regex": r"global_step\/sec:\s(.*)"}],
 checkpoint_s3_uri=checkpoint_s3_uri,
 checkpoint_local_path=checkpoint_local_path,
Expand DownExpand Up@@ -91,7 +90,7 @@ def test_mnist_with_checkpoint_config(
 assert actual_training_checkpoint_config == expected_training_checkpoint_config


def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
def test_server_side_encryption(sagemaker_session, tf_serving_version, py_version):
 with kms_utils.bucket_with_encryption(sagemaker_session, ROLE) as (bucket_with_kms, kms_key):
 output_path = os.path.join(
 bucket_with_kms, "test-server-side-encryption", time.strftime("%y%m%d-%H%M")
Expand All@@ -105,7 +104,7 @@ def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
 train_instance_type="ml.c5.xlarge",
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
@laurenyulaurenyuMay 22, 2020

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why switch to using a serving version for training?
@chuyang-dengchuyang-dengMay 22, 2020

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because this test is doing a deploy later and TFS does not support 2.2 yet.
 py_version=py_version,
 code_location=output_path,
 output_path=output_path,
Expand DownExpand Up@@ -140,7 +139,7 @@ def test_mnist_distributed(sagemaker_session, instance_type, tf_full_version, py
 train_instance_count=2,
 train_instance_type=instance_type,
 sagemaker_session=sagemaker_session,
 py_version=py_version,
 py_version="py37",
 script_mode=True,
 framework_version=tf_full_version,
 distributions=PARAMETER_SERVER_DISTRIBUTION,
Expand DownExpand Up@@ -168,7 +167,7 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
 sagemaker_session=sagemaker_session,
 script_mode=True,
 # testing py-sdk functionality, no need to run against all TF versions
 framework_version=TensorFlow.LATEST_VERSION,
 framework_version=LATEST_SERVING_VERSION,
 tags=TAGS,
 )
 inputs = estimator.sagemaker_session.upload_data(
Expand DownExpand Up@@ -200,7 +199,9 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
 _assert_model_name_match(sagemaker_session.sagemaker_client, endpoint_name, model_name)


def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_version, py_version):
def test_deploy_with_input_handlers(
 sagemaker_session, instance_type, tf_serving_version, py_version
):
 estimator = TensorFlow(
 entry_point="training.py",
 source_dir=TFS_RESOURCE_PATH,
Expand All@@ -210,7 +211,7 @@ def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_ve
 py_version=py_version,
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 tags=TAGS,
 )

Expand Down

12 changes: 6 additions & 6 deletions
tests/integ/test_tfs.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,7 @@


@pytest.fixture(scope="module")
def tfs_predictor(sagemaker_session, tf_full_version):
def tfs_predictor(sagemaker_session, tf_serving_version):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
 path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -37,7 +37,7 @@ def tfs_predictor(sagemaker_session, tf_full_version):
 model = Model(
 model_data=model_data,
 role="SageMakerRole",
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(1, "ml.c5.xlarge", endpoint_name=endpoint_name)
Expand All@@ -54,7 +54,7 @@ def tar_dir(directory, tmpdir):

@pytest.fixture
def tfs_predictor_with_model_and_entry_point_same_tar(
 sagemaker_local_session, tf_full_version, tmpdir
 sagemaker_local_session, tf_serving_version, tmpdir
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -65,7 +65,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(
 model = Model(
 model_data="file://" + model_tar,
 role="SageMakerRole",
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_local_session,
 )
 predictor = model.deploy(1, "local", endpoint_name=endpoint_name)
Expand All@@ -78,7 +78,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(

@pytest.fixture(scope="module")
def tfs_predictor_with_model_and_entry_point_and_dependencies(
 sagemaker_local_session, tf_full_version
 sagemaker_local_session, tf_serving_version
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -98,7 +98,7 @@ def tfs_predictor_with_model_and_entry_point_and_dependencies(
 model_data=model_data,
 role="SageMakerRole",
 dependencies=dependencies,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_local_session,
 )

Expand Down

3 changes: 2 additions & 1 deletion
tests/integ/test_transformer.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -25,6 +25,7 @@
from sagemaker.mxnet import MXNet
from sagemaker.pytorch import PyTorchModel
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.transformer import Transformer
from sagemaker.estimator import Estimator
from sagemaker.utils import unique_name_from_base
Expand DownExpand Up@@ -351,7 +352,7 @@ def test_transform_tf_kms_network_isolation(sagemaker_session, cpu_instance_type
 role="SageMakerRole",
 train_instance_count=1,
 train_instance_type=cpu_instance_type,
 framework_version=TensorFlow.LATEST_VERSION,
 framework_version=LATEST_SERVING_VERSION,
 script_mode=True,
 py_version=PYTHON_VERSION,
 sagemaker_session=sagemaker_session,
Expand Down

12 changes: 10 additions & 2 deletions
tests/integ/test_tuner.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -37,6 +37,7 @@
from sagemaker.predictor import json_deserializer
from sagemaker.pytorch import PyTorch
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION
from sagemaker.tuner import (
 IntegerParameter,
 ContinuousParameter,
Expand All@@ -51,6 +52,13 @@

DATA_PATH = os.path.join(DATA_DIR, "iris", "data")

PY37_SUPPORTED_FRAMEWORK_VERSION = [TensorFlow._LATEST_1X_VERSION, LATEST_VERSION]


@pytest.fixture(scope="module")
def py_version(tf_full_version):
 return "py37" if tf_full_version in PY37_SUPPORTED_FRAMEWORK_VERSION else PYTHON_VERSION


@pytest.fixture(scope="module")
def kmeans_train_set(sagemaker_session):
Expand DownExpand Up@@ -590,7 +598,7 @@ def test_tuning_mxnet(sagemaker_session, mxnet_full_version, cpu_instance_type):


@pytest.mark.canary_quick
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version):
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version, py_version):
 resource_path = os.path.join(DATA_DIR, "tensorflow_mnist")
 script_path = os.path.join(resource_path, "mnist.py")

Expand All@@ -601,7 +609,7 @@ def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_ver
 train_instance_type=cpu_instance_type,
 script_mode=True,
 sagemaker_session=sagemaker_session,
 py_version=PYTHON_VERSION,
 py_version=py_version,
 framework_version=tf_full_version,
 )

Expand Down

, '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 > 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('^' + ".*" + '

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feature: support TensorFlow training 2.2#1521

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 Merged

chuyang-deng
merged 33 commits into

from

May 22, 2020
 Merged


feature: support TensorFlow training 2.2
#1521
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1c9dd16

update with aws/master


chuyang-deng May 15, 2020
aa349fd

upate with aws master


chuyang-deng May 18, 2020
c875c47

update with aws master


chuyang-deng May 19, 2020
3e23a39

feature: TensorFlow 2.2 support

May 19, 2020
e9a96ec

Merge branch 'master' into tf-2-2


chuyang-deng May 19, 2020
1d66433

prevent TFS test pulling 2.2.0 images

May 20, 2020
dc8e4f7

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 20, 2020
98a0a5e

fix flake8 error

May 20, 2020
7f44c65

update tfs test versions

May 21, 2020
b33deb9

use tfs 2.1.0 in model monitor tests

May 21, 2020
8da6509

distinguish tf and tfs latest versions in test

May 21, 2020
4f85786

add latest serving version

May 21, 2020
cb2a489

let py_version pick up tf_training_version

May 21, 2020
c9dcdd0

Merge branch 'master' into tf-2-2


chuyang-deng May 21, 2020
ed177e8

fix typo

May 21, 2020
816030e

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
0b77be7

no py37 for tfs 2.1

May 21, 2020
89bb6d6

fix black error

May 21, 2020
40da473

prevent tfs pulling 2.2 image

May 20, 2020
c251fcc

tf 2.2 using py37

May 21, 2020
e010da9

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
edeb501

Merge branch 'master' into tf-2-2


chuyang-deng May 21, 2020
3255b04

test_data_capture_config use TFS latest version

May 21, 2020
403298e

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
2a7f154

fix flake8 error

May 21, 2020
3b10a76

update model monitoring test

May 21, 2020
9c2bb6c

update python version for tuner integ test

May 21, 2020
fe14848

address comments

May 22, 2020
fa84753

Merge branch 'ChuyangDeng-tf-2-2'

May 22, 2020
ff376d8

fix import error

May 22, 2020
598f833

resolve conflicts

May 22, 2020
31110b4

hardcode py_version for tensorflow-training 2.2 tests

May 22, 2020
fa04c1a

import LATEST_SERVING_VERSION from TensorFlow.defaults

May 22, 2020

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2 changes: 1 addition & 1 deletion
doc/using_tf.rst

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -20,7 +20,7 @@ For general information about using the SageMaker Python SDK, see :ref:`overview

.. contents::

Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``.
Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``, ``1.15``, ``2.0``.


*****************************
Expand Down

5 changes: 4 additions & 1 deletion
src/sagemaker/tensorflow/defaults.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -18,7 +18,10 @@
This is no longer updated so as to not break existing workflows.
"""

LATEST_VERSION = "2.1.0"
LATEST_VERSION = "2.2.0"
"""The latest version of TensorFlow included in the SageMaker pre-built Docker images."""

LATEST_SERVING_VERSION = "2.1.0"
"""The latest version of TensorFlow Serving included in the SageMaker pre-built Docker images."""

LATEST_PY2_VERSION = "2.1.0"

12 changes: 10 additions & 2 deletions
tests/conftest.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,8 @@
from sagemaker.pytorch import PyTorch
from sagemaker.rl import RLEstimator
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.tensorflow.estimator import TensorFlow
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION, LATEST_SERVING_VERSION

DEFAULT_REGION = "us-west-2"
CUSTOM_BUCKET_NAME_PREFIX = "sagemaker-custom-bucket"
Expand DownExpand Up@@ -259,7 +260,7 @@ def sklearn_full_version(request):
 return request.config.getoption("--sklearn-full-version")


@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, TensorFlow.LATEST_VERSION])
@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, LATEST_VERSION])
def tf_full_version(request):
 tf_version = request.config.getoption("--tf-full-version")
 if tf_version is None:
Expand DownExpand Up@@ -335,3 +336,10 @@ def pytest_generate_tests(metafunc):
@pytest.fixture(scope="module")
def xgboost_full_version(request):
 return request.config.getoption("--xgboost-full-version")


@pytest.fixture(scope="module")
def tf_serving_version(tf_full_version):
 if tf_full_version == LATEST_VERSION:
 return LATEST_SERVING_VERSION
 return tf_full_version

12 changes: 6 additions & 6 deletions
tests/integ/test_data_capture_config.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -41,7 +41,7 @@


def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -52,7 +52,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(
Expand DownExpand Up@@ -98,7 +98,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -109,7 +109,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 destination_s3_uri = os.path.join(
Expand DownExpand Up@@ -184,7 +184,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -195,7 +195,7 @@ def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 destination_s3_uri = os.path.join(
Expand Down

4 changes: 2 additions & 2 deletions
tests/integ/test_model_monitor.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -88,7 +88,7 @@


@pytest.fixture(scope="module")
def predictor(sagemaker_session, tf_full_version):
def predictor(sagemaker_session, tf_serving_version):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
 path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -100,7 +100,7 @@ def predictor(sagemaker_session, tf_full_version):
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(
Expand Down

23 changes: 12 additions & 11 deletions
tests/integ/test_tf_script_mode.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
import pytest

from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.utils import unique_name_from_base, sagemaker_timestamp

import tests.integ
Expand All@@ -40,10 +41,8 @@


@pytest.fixture(scope="module")
def py_version(tf_full_version):
 return (
 "py37" if tf_full_version == TensorFlow._LATEST_1X_VERSION else tests.integ.PYTHON_VERSION
 )
def py_version(tf_full_version, tf_serving_version):
 return "py37" if tf_full_version == tf_serving_version else tests.integ.PYTHON_VERSION


def test_mnist_with_checkpoint_config(
Expand All@@ -61,7 +60,7 @@ def test_mnist_with_checkpoint_config(
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 py_version=py_version,
 py_version="py37",
Comment thread
laurenyu marked this conversation as resolved.

 metric_definitions=[{"Name": "train:global_steps", "Regex": r"global_step\/sec:\s(.*)"}],
 checkpoint_s3_uri=checkpoint_s3_uri,
 checkpoint_local_path=checkpoint_local_path,
Expand DownExpand Up@@ -91,7 +90,7 @@ def test_mnist_with_checkpoint_config(
 assert actual_training_checkpoint_config == expected_training_checkpoint_config


def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
def test_server_side_encryption(sagemaker_session, tf_serving_version, py_version):
 with kms_utils.bucket_with_encryption(sagemaker_session, ROLE) as (bucket_with_kms, kms_key):
 output_path = os.path.join(
 bucket_with_kms, "test-server-side-encryption", time.strftime("%y%m%d-%H%M")
Expand All@@ -105,7 +104,7 @@ def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
 train_instance_type="ml.c5.xlarge",
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
@laurenyulaurenyuMay 22, 2020

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why switch to using a serving version for training?
@chuyang-dengchuyang-dengMay 22, 2020

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because this test is doing a deploy later and TFS does not support 2.2 yet.
 py_version=py_version,
 code_location=output_path,
 output_path=output_path,
Expand DownExpand Up@@ -140,7 +139,7 @@ def test_mnist_distributed(sagemaker_session, instance_type, tf_full_version, py
 train_instance_count=2,
 train_instance_type=instance_type,
 sagemaker_session=sagemaker_session,
 py_version=py_version,
 py_version="py37",
 script_mode=True,
 framework_version=tf_full_version,
 distributions=PARAMETER_SERVER_DISTRIBUTION,
Expand DownExpand Up@@ -168,7 +167,7 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
 sagemaker_session=sagemaker_session,
 script_mode=True,
 # testing py-sdk functionality, no need to run against all TF versions
 framework_version=TensorFlow.LATEST_VERSION,
 framework_version=LATEST_SERVING_VERSION,
 tags=TAGS,
 )
 inputs = estimator.sagemaker_session.upload_data(
Expand DownExpand Up@@ -200,7 +199,9 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
 _assert_model_name_match(sagemaker_session.sagemaker_client, endpoint_name, model_name)


def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_version, py_version):
def test_deploy_with_input_handlers(
 sagemaker_session, instance_type, tf_serving_version, py_version
):
 estimator = TensorFlow(
 entry_point="training.py",
 source_dir=TFS_RESOURCE_PATH,
Expand All@@ -210,7 +211,7 @@ def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_ve
 py_version=py_version,
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 tags=TAGS,
 )

Expand Down

12 changes: 6 additions & 6 deletions
tests/integ/test_tfs.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,7 @@


@pytest.fixture(scope="module")
def tfs_predictor(sagemaker_session, tf_full_version):
def tfs_predictor(sagemaker_session, tf_serving_version):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
 path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -37,7 +37,7 @@ def tfs_predictor(sagemaker_session, tf_full_version):
 model = Model(
 model_data=model_data,
 role="SageMakerRole",
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(1, "ml.c5.xlarge", endpoint_name=endpoint_name)
Expand All@@ -54,7 +54,7 @@ def tar_dir(directory, tmpdir):

@pytest.fixture
def tfs_predictor_with_model_and_entry_point_same_tar(
 sagemaker_local_session, tf_full_version, tmpdir
 sagemaker_local_session, tf_serving_version, tmpdir
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -65,7 +65,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(
 model = Model(
 model_data="file://" + model_tar,
 role="SageMakerRole",
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_local_session,
 )
 predictor = model.deploy(1, "local", endpoint_name=endpoint_name)
Expand All@@ -78,7 +78,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(

@pytest.fixture(scope="module")
def tfs_predictor_with_model_and_entry_point_and_dependencies(
 sagemaker_local_session, tf_full_version
 sagemaker_local_session, tf_serving_version
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -98,7 +98,7 @@ def tfs_predictor_with_model_and_entry_point_and_dependencies(
 model_data=model_data,
 role="SageMakerRole",
 dependencies=dependencies,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_local_session,
 )

Expand Down

3 changes: 2 additions & 1 deletion
tests/integ/test_transformer.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -25,6 +25,7 @@
from sagemaker.mxnet import MXNet
from sagemaker.pytorch import PyTorchModel
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.transformer import Transformer
from sagemaker.estimator import Estimator
from sagemaker.utils import unique_name_from_base
Expand DownExpand Up@@ -351,7 +352,7 @@ def test_transform_tf_kms_network_isolation(sagemaker_session, cpu_instance_type
 role="SageMakerRole",
 train_instance_count=1,
 train_instance_type=cpu_instance_type,
 framework_version=TensorFlow.LATEST_VERSION,
 framework_version=LATEST_SERVING_VERSION,
 script_mode=True,
 py_version=PYTHON_VERSION,
 sagemaker_session=sagemaker_session,
Expand Down

12 changes: 10 additions & 2 deletions
tests/integ/test_tuner.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -37,6 +37,7 @@
from sagemaker.predictor import json_deserializer
from sagemaker.pytorch import PyTorch
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION
from sagemaker.tuner import (
 IntegerParameter,
 ContinuousParameter,
Expand All@@ -51,6 +52,13 @@

DATA_PATH = os.path.join(DATA_DIR, "iris", "data")

PY37_SUPPORTED_FRAMEWORK_VERSION = [TensorFlow._LATEST_1X_VERSION, LATEST_VERSION]


@pytest.fixture(scope="module")
def py_version(tf_full_version):
 return "py37" if tf_full_version in PY37_SUPPORTED_FRAMEWORK_VERSION else PYTHON_VERSION


@pytest.fixture(scope="module")
def kmeans_train_set(sagemaker_session):
Expand DownExpand Up@@ -590,7 +598,7 @@ def test_tuning_mxnet(sagemaker_session, mxnet_full_version, cpu_instance_type):


@pytest.mark.canary_quick
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version):
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version, py_version):
 resource_path = os.path.join(DATA_DIR, "tensorflow_mnist")
 script_path = os.path.join(resource_path, "mnist.py")

Expand All@@ -601,7 +609,7 @@ def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_ver
 train_instance_type=cpu_instance_type,
 script_mode=True,
 sagemaker_session=sagemaker_session,
 py_version=PYTHON_VERSION,
 py_version=py_version,
 framework_version=tf_full_version,
 )

Expand Down

, '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" + '

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 Merged

chuyang-deng
merged 33 commits into

from

May 22, 2020
 Merged


feature: support TensorFlow training 2.2
#1521
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1c9dd16

update with aws/master


chuyang-deng May 15, 2020
aa349fd

upate with aws master


chuyang-deng May 18, 2020
c875c47

update with aws master


chuyang-deng May 19, 2020
3e23a39

feature: TensorFlow 2.2 support

May 19, 2020
e9a96ec

Merge branch 'master' into tf-2-2


chuyang-deng May 19, 2020
1d66433

prevent TFS test pulling 2.2.0 images

May 20, 2020
dc8e4f7

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 20, 2020
98a0a5e

fix flake8 error

May 20, 2020
7f44c65

update tfs test versions

May 21, 2020
b33deb9

use tfs 2.1.0 in model monitor tests

May 21, 2020
8da6509

distinguish tf and tfs latest versions in test

May 21, 2020
4f85786

add latest serving version

May 21, 2020
cb2a489

let py_version pick up tf_training_version

May 21, 2020
c9dcdd0

Merge branch 'master' into tf-2-2


chuyang-deng May 21, 2020
ed177e8

fix typo

May 21, 2020
816030e

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
0b77be7

no py37 for tfs 2.1

May 21, 2020
89bb6d6

fix black error

May 21, 2020
40da473

prevent tfs pulling 2.2 image

May 20, 2020
c251fcc

tf 2.2 using py37

May 21, 2020
e010da9

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
edeb501

Merge branch 'master' into tf-2-2


chuyang-deng May 21, 2020
3255b04

test_data_capture_config use TFS latest version

May 21, 2020
403298e

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
2a7f154

fix flake8 error

May 21, 2020
3b10a76

update model monitoring test

May 21, 2020
9c2bb6c

update python version for tuner integ test

May 21, 2020
fe14848

address comments

May 22, 2020
fa84753

Merge branch 'ChuyangDeng-tf-2-2'

May 22, 2020
ff376d8

fix import error

May 22, 2020
598f833

resolve conflicts

May 22, 2020
31110b4

hardcode py_version for tensorflow-training 2.2 tests

May 22, 2020
fa04c1a

import LATEST_SERVING_VERSION from TensorFlow.defaults

May 22, 2020

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2 changes: 1 addition & 1 deletion
doc/using_tf.rst

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -20,7 +20,7 @@ For general information about using the SageMaker Python SDK, see :ref:`overview

.. contents::

Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``.
Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``, ``1.15``, ``2.0``.


*****************************
Expand Down

5 changes: 4 additions & 1 deletion
src/sagemaker/tensorflow/defaults.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -18,7 +18,10 @@
This is no longer updated so as to not break existing workflows.
"""

LATEST_VERSION = "2.1.0"
LATEST_VERSION = "2.2.0"
"""The latest version of TensorFlow included in the SageMaker pre-built Docker images."""

LATEST_SERVING_VERSION = "2.1.0"
"""The latest version of TensorFlow Serving included in the SageMaker pre-built Docker images."""

LATEST_PY2_VERSION = "2.1.0"

12 changes: 10 additions & 2 deletions
tests/conftest.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,8 @@
from sagemaker.pytorch import PyTorch
from sagemaker.rl import RLEstimator
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.tensorflow.estimator import TensorFlow
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION, LATEST_SERVING_VERSION

DEFAULT_REGION = "us-west-2"
CUSTOM_BUCKET_NAME_PREFIX = "sagemaker-custom-bucket"
Expand DownExpand Up@@ -259,7 +260,7 @@ def sklearn_full_version(request):
 return request.config.getoption("--sklearn-full-version")


@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, TensorFlow.LATEST_VERSION])
@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, LATEST_VERSION])
def tf_full_version(request):
 tf_version = request.config.getoption("--tf-full-version")
 if tf_version is None:
Expand DownExpand Up@@ -335,3 +336,10 @@ def pytest_generate_tests(metafunc):
@pytest.fixture(scope="module")
def xgboost_full_version(request):
 return request.config.getoption("--xgboost-full-version")


@pytest.fixture(scope="module")
def tf_serving_version(tf_full_version):
 if tf_full_version == LATEST_VERSION:
 return LATEST_SERVING_VERSION
 return tf_full_version

12 changes: 6 additions & 6 deletions
tests/integ/test_data_capture_config.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -41,7 +41,7 @@


def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -52,7 +52,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(
Expand DownExpand Up@@ -98,7 +98,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -109,7 +109,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 destination_s3_uri = os.path.join(
Expand DownExpand Up@@ -184,7 +184,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -195,7 +195,7 @@ def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 destination_s3_uri = os.path.join(
Expand Down

4 changes: 2 additions & 2 deletions
tests/integ/test_model_monitor.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -88,7 +88,7 @@


@pytest.fixture(scope="module")
def predictor(sagemaker_session, tf_full_version):
def predictor(sagemaker_session, tf_serving_version):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
 path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -100,7 +100,7 @@ def predictor(sagemaker_session, tf_full_version):
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(
Expand Down

23 changes: 12 additions & 11 deletions
tests/integ/test_tf_script_mode.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
import pytest

from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.utils import unique_name_from_base, sagemaker_timestamp

import tests.integ
Expand All@@ -40,10 +41,8 @@


@pytest.fixture(scope="module")
def py_version(tf_full_version):
 return (
 "py37" if tf_full_version == TensorFlow._LATEST_1X_VERSION else tests.integ.PYTHON_VERSION
 )
def py_version(tf_full_version, tf_serving_version):
 return "py37" if tf_full_version == tf_serving_version else tests.integ.PYTHON_VERSION


def test_mnist_with_checkpoint_config(
Expand All@@ -61,7 +60,7 @@ def test_mnist_with_checkpoint_config(
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 py_version=py_version,
 py_version="py37",
Comment thread
laurenyu marked this conversation as resolved.

 metric_definitions=[{"Name": "train:global_steps", "Regex": r"global_step\/sec:\s(.*)"}],
 checkpoint_s3_uri=checkpoint_s3_uri,
 checkpoint_local_path=checkpoint_local_path,
Expand DownExpand Up@@ -91,7 +90,7 @@ def test_mnist_with_checkpoint_config(
 assert actual_training_checkpoint_config == expected_training_checkpoint_config


def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
def test_server_side_encryption(sagemaker_session, tf_serving_version, py_version):
 with kms_utils.bucket_with_encryption(sagemaker_session, ROLE) as (bucket_with_kms, kms_key):
 output_path = os.path.join(
 bucket_with_kms, "test-server-side-encryption", time.strftime("%y%m%d-%H%M")
Expand All@@ -105,7 +104,7 @@ def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
 train_instance_type="ml.c5.xlarge",
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
@laurenyulaurenyuMay 22, 2020

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why switch to using a serving version for training?
@chuyang-dengchuyang-dengMay 22, 2020

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because this test is doing a deploy later and TFS does not support 2.2 yet.
 py_version=py_version,
 code_location=output_path,
 output_path=output_path,
Expand DownExpand Up@@ -140,7 +139,7 @@ def test_mnist_distributed(sagemaker_session, instance_type, tf_full_version, py
 train_instance_count=2,
 train_instance_type=instance_type,
 sagemaker_session=sagemaker_session,
 py_version=py_version,
 py_version="py37",
 script_mode=True,
 framework_version=tf_full_version,
 distributions=PARAMETER_SERVER_DISTRIBUTION,
Expand DownExpand Up@@ -168,7 +167,7 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
 sagemaker_session=sagemaker_session,
 script_mode=True,
 # testing py-sdk functionality, no need to run against all TF versions
 framework_version=TensorFlow.LATEST_VERSION,
 framework_version=LATEST_SERVING_VERSION,
 tags=TAGS,
 )
 inputs = estimator.sagemaker_session.upload_data(
Expand DownExpand Up@@ -200,7 +199,9 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
 _assert_model_name_match(sagemaker_session.sagemaker_client, endpoint_name, model_name)


def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_version, py_version):
def test_deploy_with_input_handlers(
 sagemaker_session, instance_type, tf_serving_version, py_version
):
 estimator = TensorFlow(
 entry_point="training.py",
 source_dir=TFS_RESOURCE_PATH,
Expand All@@ -210,7 +211,7 @@ def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_ve
 py_version=py_version,
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 tags=TAGS,
 )

Expand Down

12 changes: 6 additions & 6 deletions
tests/integ/test_tfs.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,7 @@


@pytest.fixture(scope="module")
def tfs_predictor(sagemaker_session, tf_full_version):
def tfs_predictor(sagemaker_session, tf_serving_version):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
 path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -37,7 +37,7 @@ def tfs_predictor(sagemaker_session, tf_full_version):
 model = Model(
 model_data=model_data,
 role="SageMakerRole",
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(1, "ml.c5.xlarge", endpoint_name=endpoint_name)
Expand All@@ -54,7 +54,7 @@ def tar_dir(directory, tmpdir):

@pytest.fixture
def tfs_predictor_with_model_and_entry_point_same_tar(
 sagemaker_local_session, tf_full_version, tmpdir
 sagemaker_local_session, tf_serving_version, tmpdir
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -65,7 +65,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(
 model = Model(
 model_data="file://" + model_tar,
 role="SageMakerRole",
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_local_session,
 )
 predictor = model.deploy(1, "local", endpoint_name=endpoint_name)
Expand All@@ -78,7 +78,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(

@pytest.fixture(scope="module")
def tfs_predictor_with_model_and_entry_point_and_dependencies(
 sagemaker_local_session, tf_full_version
 sagemaker_local_session, tf_serving_version
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -98,7 +98,7 @@ def tfs_predictor_with_model_and_entry_point_and_dependencies(
 model_data=model_data,
 role="SageMakerRole",
 dependencies=dependencies,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_local_session,
 )

Expand Down

3 changes: 2 additions & 1 deletion
tests/integ/test_transformer.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -25,6 +25,7 @@
from sagemaker.mxnet import MXNet
from sagemaker.pytorch import PyTorchModel
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.transformer import Transformer
from sagemaker.estimator import Estimator
from sagemaker.utils import unique_name_from_base
Expand DownExpand Up@@ -351,7 +352,7 @@ def test_transform_tf_kms_network_isolation(sagemaker_session, cpu_instance_type
 role="SageMakerRole",
 train_instance_count=1,
 train_instance_type=cpu_instance_type,
 framework_version=TensorFlow.LATEST_VERSION,
 framework_version=LATEST_SERVING_VERSION,
 script_mode=True,
 py_version=PYTHON_VERSION,
 sagemaker_session=sagemaker_session,
Expand Down

12 changes: 10 additions & 2 deletions
tests/integ/test_tuner.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -37,6 +37,7 @@
from sagemaker.predictor import json_deserializer
from sagemaker.pytorch import PyTorch
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION
from sagemaker.tuner import (
 IntegerParameter,
 ContinuousParameter,
Expand All@@ -51,6 +52,13 @@

DATA_PATH = os.path.join(DATA_DIR, "iris", "data")

PY37_SUPPORTED_FRAMEWORK_VERSION = [TensorFlow._LATEST_1X_VERSION, LATEST_VERSION]


@pytest.fixture(scope="module")
def py_version(tf_full_version):
 return "py37" if tf_full_version in PY37_SUPPORTED_FRAMEWORK_VERSION else PYTHON_VERSION


@pytest.fixture(scope="module")
def kmeans_train_set(sagemaker_session):
Expand DownExpand Up@@ -590,7 +598,7 @@ def test_tuning_mxnet(sagemaker_session, mxnet_full_version, cpu_instance_type):


@pytest.mark.canary_quick
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version):
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version, py_version):
 resource_path = os.path.join(DATA_DIR, "tensorflow_mnist")
 script_path = os.path.join(resource_path, "mnist.py")

Expand All@@ -601,7 +609,7 @@ def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_ver
 train_instance_type=cpu_instance_type,
 script_mode=True,
 sagemaker_session=sagemaker_session,
 py_version=PYTHON_VERSION,
 py_version=py_version,
 framework_version=tf_full_version,
 )

Expand Down

, '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); }
})();
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try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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feature: support TensorFlow training 2.2#1521

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chuyang-deng
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feature: support TensorFlow training 2.2
#1521
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1c9dd16

update with aws/master


chuyang-deng May 15, 2020
aa349fd

upate with aws master


chuyang-deng May 18, 2020
c875c47

update with aws master


chuyang-deng May 19, 2020
3e23a39

feature: TensorFlow 2.2 support

May 19, 2020
e9a96ec

Merge branch 'master' into tf-2-2


chuyang-deng May 19, 2020
1d66433

prevent TFS test pulling 2.2.0 images

May 20, 2020
dc8e4f7

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 20, 2020
98a0a5e

fix flake8 error

May 20, 2020
7f44c65

update tfs test versions

May 21, 2020
b33deb9

use tfs 2.1.0 in model monitor tests

May 21, 2020
8da6509

distinguish tf and tfs latest versions in test

May 21, 2020
4f85786

add latest serving version

May 21, 2020
cb2a489

let py_version pick up tf_training_version

May 21, 2020
c9dcdd0

Merge branch 'master' into tf-2-2


chuyang-deng May 21, 2020
ed177e8

fix typo

May 21, 2020
816030e

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
0b77be7

no py37 for tfs 2.1

May 21, 2020
89bb6d6

fix black error

May 21, 2020
40da473

prevent tfs pulling 2.2 image

May 20, 2020
c251fcc

tf 2.2 using py37

May 21, 2020
e010da9

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
edeb501

Merge branch 'master' into tf-2-2


chuyang-deng May 21, 2020
3255b04

test_data_capture_config use TFS latest version

May 21, 2020
403298e

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
2a7f154

fix flake8 error

May 21, 2020
3b10a76

update model monitoring test

May 21, 2020
9c2bb6c

update python version for tuner integ test

May 21, 2020
fe14848

address comments

May 22, 2020
fa84753

Merge branch 'ChuyangDeng-tf-2-2'

May 22, 2020
ff376d8

fix import error

May 22, 2020
598f833

resolve conflicts

May 22, 2020
31110b4

hardcode py_version for tensorflow-training 2.2 tests

May 22, 2020
fa04c1a

import LATEST_SERVING_VERSION from TensorFlow.defaults

May 22, 2020

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2 changes: 1 addition & 1 deletion
doc/using_tf.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -20,7 +20,7 @@ For general information about using the SageMaker Python SDK, see :ref:`overview

.. contents::

Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``.
Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``, ``1.15``, ``2.0``.


*****************************
Expand Down

5 changes: 4 additions & 1 deletion
src/sagemaker/tensorflow/defaults.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -18,7 +18,10 @@
This is no longer updated so as to not break existing workflows.
"""

LATEST_VERSION = "2.1.0"
LATEST_VERSION = "2.2.0"
"""The latest version of TensorFlow included in the SageMaker pre-built Docker images."""

LATEST_SERVING_VERSION = "2.1.0"
"""The latest version of TensorFlow Serving included in the SageMaker pre-built Docker images."""

LATEST_PY2_VERSION = "2.1.0"

12 changes: 10 additions & 2 deletions
tests/conftest.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,8 @@
from sagemaker.pytorch import PyTorch
from sagemaker.rl import RLEstimator
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.tensorflow.estimator import TensorFlow
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION, LATEST_SERVING_VERSION

DEFAULT_REGION = "us-west-2"
CUSTOM_BUCKET_NAME_PREFIX = "sagemaker-custom-bucket"
Expand DownExpand Up@@ -259,7 +260,7 @@ def sklearn_full_version(request):
 return request.config.getoption("--sklearn-full-version")


@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, TensorFlow.LATEST_VERSION])
@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, LATEST_VERSION])
def tf_full_version(request):
 tf_version = request.config.getoption("--tf-full-version")
 if tf_version is None:
Expand DownExpand Up@@ -335,3 +336,10 @@ def pytest_generate_tests(metafunc):
@pytest.fixture(scope="module")
def xgboost_full_version(request):
 return request.config.getoption("--xgboost-full-version")


@pytest.fixture(scope="module")
def tf_serving_version(tf_full_version):
 if tf_full_version == LATEST_VERSION:
 return LATEST_SERVING_VERSION
 return tf_full_version

12 changes: 6 additions & 6 deletions
tests/integ/test_data_capture_config.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -41,7 +41,7 @@


def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -52,7 +52,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(
Expand DownExpand Up@@ -98,7 +98,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -109,7 +109,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 destination_s3_uri = os.path.join(
Expand DownExpand Up@@ -184,7 +184,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -195,7 +195,7 @@ def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 destination_s3_uri = os.path.join(
Expand Down

4 changes: 2 additions & 2 deletions
tests/integ/test_model_monitor.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -88,7 +88,7 @@


@pytest.fixture(scope="module")
def predictor(sagemaker_session, tf_full_version):
def predictor(sagemaker_session, tf_serving_version):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
 path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -100,7 +100,7 @@ def predictor(sagemaker_session, tf_full_version):
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(
Expand Down

23 changes: 12 additions & 11 deletions
tests/integ/test_tf_script_mode.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
import pytest

from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.utils import unique_name_from_base, sagemaker_timestamp

import tests.integ
Expand All@@ -40,10 +41,8 @@


@pytest.fixture(scope="module")
def py_version(tf_full_version):
 return (
 "py37" if tf_full_version == TensorFlow._LATEST_1X_VERSION else tests.integ.PYTHON_VERSION
 )
def py_version(tf_full_version, tf_serving_version):
 return "py37" if tf_full_version == tf_serving_version else tests.integ.PYTHON_VERSION


def test_mnist_with_checkpoint_config(
Expand All@@ -61,7 +60,7 @@ def test_mnist_with_checkpoint_config(
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 py_version=py_version,
 py_version="py37",
Comment thread
laurenyu marked this conversation as resolved.

 metric_definitions=[{"Name": "train:global_steps", "Regex": r"global_step\/sec:\s(.*)"}],
 checkpoint_s3_uri=checkpoint_s3_uri,
 checkpoint_local_path=checkpoint_local_path,
Expand DownExpand Up@@ -91,7 +90,7 @@ def test_mnist_with_checkpoint_config(
 assert actual_training_checkpoint_config == expected_training_checkpoint_config


def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
def test_server_side_encryption(sagemaker_session, tf_serving_version, py_version):
 with kms_utils.bucket_with_encryption(sagemaker_session, ROLE) as (bucket_with_kms, kms_key):
 output_path = os.path.join(
 bucket_with_kms, "test-server-side-encryption", time.strftime("%y%m%d-%H%M")
Expand All@@ -105,7 +104,7 @@ def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
 train_instance_type="ml.c5.xlarge",
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
@laurenyulaurenyuMay 22, 2020

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why switch to using a serving version for training?
@chuyang-dengchuyang-dengMay 22, 2020

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because this test is doing a deploy later and TFS does not support 2.2 yet.
 py_version=py_version,
 code_location=output_path,
 output_path=output_path,
Expand DownExpand Up@@ -140,7 +139,7 @@ def test_mnist_distributed(sagemaker_session, instance_type, tf_full_version, py
 train_instance_count=2,
 train_instance_type=instance_type,
 sagemaker_session=sagemaker_session,
 py_version=py_version,
 py_version="py37",
 script_mode=True,
 framework_version=tf_full_version,
 distributions=PARAMETER_SERVER_DISTRIBUTION,
Expand DownExpand Up@@ -168,7 +167,7 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
 sagemaker_session=sagemaker_session,
 script_mode=True,
 # testing py-sdk functionality, no need to run against all TF versions
 framework_version=TensorFlow.LATEST_VERSION,
 framework_version=LATEST_SERVING_VERSION,
 tags=TAGS,
 )
 inputs = estimator.sagemaker_session.upload_data(
Expand DownExpand Up@@ -200,7 +199,9 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
 _assert_model_name_match(sagemaker_session.sagemaker_client, endpoint_name, model_name)


def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_version, py_version):
def test_deploy_with_input_handlers(
 sagemaker_session, instance_type, tf_serving_version, py_version
):
 estimator = TensorFlow(
 entry_point="training.py",
 source_dir=TFS_RESOURCE_PATH,
Expand All@@ -210,7 +211,7 @@ def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_ve
 py_version=py_version,
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 tags=TAGS,
 )

Expand Down

12 changes: 6 additions & 6 deletions
tests/integ/test_tfs.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,7 @@


@pytest.fixture(scope="module")
def tfs_predictor(sagemaker_session, tf_full_version):
def tfs_predictor(sagemaker_session, tf_serving_version):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
 path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -37,7 +37,7 @@ def tfs_predictor(sagemaker_session, tf_full_version):
 model = Model(
 model_data=model_data,
 role="SageMakerRole",
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(1, "ml.c5.xlarge", endpoint_name=endpoint_name)
Expand All@@ -54,7 +54,7 @@ def tar_dir(directory, tmpdir):

@pytest.fixture
def tfs_predictor_with_model_and_entry_point_same_tar(
 sagemaker_local_session, tf_full_version, tmpdir
 sagemaker_local_session, tf_serving_version, tmpdir
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -65,7 +65,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(
 model = Model(
 model_data="file://" + model_tar,
 role="SageMakerRole",
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_local_session,
 )
 predictor = model.deploy(1, "local", endpoint_name=endpoint_name)
Expand All@@ -78,7 +78,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(

@pytest.fixture(scope="module")
def tfs_predictor_with_model_and_entry_point_and_dependencies(
 sagemaker_local_session, tf_full_version
 sagemaker_local_session, tf_serving_version
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -98,7 +98,7 @@ def tfs_predictor_with_model_and_entry_point_and_dependencies(
 model_data=model_data,
 role="SageMakerRole",
 dependencies=dependencies,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_local_session,
 )

Expand Down

3 changes: 2 additions & 1 deletion
tests/integ/test_transformer.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -25,6 +25,7 @@
from sagemaker.mxnet import MXNet
from sagemaker.pytorch import PyTorchModel
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.transformer import Transformer
from sagemaker.estimator import Estimator
from sagemaker.utils import unique_name_from_base
Expand DownExpand Up@@ -351,7 +352,7 @@ def test_transform_tf_kms_network_isolation(sagemaker_session, cpu_instance_type
 role="SageMakerRole",
 train_instance_count=1,
 train_instance_type=cpu_instance_type,
 framework_version=TensorFlow.LATEST_VERSION,
 framework_version=LATEST_SERVING_VERSION,
 script_mode=True,
 py_version=PYTHON_VERSION,
 sagemaker_session=sagemaker_session,
Expand Down

12 changes: 10 additions & 2 deletions
tests/integ/test_tuner.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -37,6 +37,7 @@
from sagemaker.predictor import json_deserializer
from sagemaker.pytorch import PyTorch
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION
from sagemaker.tuner import (
 IntegerParameter,
 ContinuousParameter,
Expand All@@ -51,6 +52,13 @@

DATA_PATH = os.path.join(DATA_DIR, "iris", "data")

PY37_SUPPORTED_FRAMEWORK_VERSION = [TensorFlow._LATEST_1X_VERSION, LATEST_VERSION]


@pytest.fixture(scope="module")
def py_version(tf_full_version):
 return "py37" if tf_full_version in PY37_SUPPORTED_FRAMEWORK_VERSION else PYTHON_VERSION


@pytest.fixture(scope="module")
def kmeans_train_set(sagemaker_session):
Expand DownExpand Up@@ -590,7 +598,7 @@ def test_tuning_mxnet(sagemaker_session, mxnet_full_version, cpu_instance_type):


@pytest.mark.canary_quick
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version):
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version, py_version):
 resource_path = os.path.join(DATA_DIR, "tensorflow_mnist")
 script_path = os.path.join(resource_path, "mnist.py")

Expand All@@ -601,7 +609,7 @@ def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_ver
 train_instance_type=cpu_instance_type,
 script_mode=True,
 sagemaker_session=sagemaker_session,
 py_version=PYTHON_VERSION,
 py_version=py_version,
 framework_version=tf_full_version,
 )

Expand Down

, '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: support TensorFlow training 2.2#1521

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 Merged

chuyang-deng
merged 33 commits into

from

May 22, 2020
 Merged


feature: support TensorFlow training 2.2
#1521
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1c9dd16

update with aws/master


chuyang-deng May 15, 2020
aa349fd

upate with aws master


chuyang-deng May 18, 2020
c875c47

update with aws master


chuyang-deng May 19, 2020
3e23a39

feature: TensorFlow 2.2 support

May 19, 2020
e9a96ec

Merge branch 'master' into tf-2-2


chuyang-deng May 19, 2020
1d66433

prevent TFS test pulling 2.2.0 images

May 20, 2020
dc8e4f7

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 20, 2020
98a0a5e

fix flake8 error

May 20, 2020
7f44c65

update tfs test versions

May 21, 2020
b33deb9

use tfs 2.1.0 in model monitor tests

May 21, 2020
8da6509

distinguish tf and tfs latest versions in test

May 21, 2020
4f85786

add latest serving version

May 21, 2020
cb2a489

let py_version pick up tf_training_version

May 21, 2020
c9dcdd0

Merge branch 'master' into tf-2-2


chuyang-deng May 21, 2020
ed177e8

fix typo

May 21, 2020
816030e

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
0b77be7

no py37 for tfs 2.1

May 21, 2020
89bb6d6

fix black error

May 21, 2020
40da473

prevent tfs pulling 2.2 image

May 20, 2020
c251fcc

tf 2.2 using py37

May 21, 2020
e010da9

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
edeb501

Merge branch 'master' into tf-2-2


chuyang-deng May 21, 2020
3255b04

test_data_capture_config use TFS latest version

May 21, 2020
403298e

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
2a7f154

fix flake8 error

May 21, 2020
3b10a76

update model monitoring test

May 21, 2020
9c2bb6c

update python version for tuner integ test

May 21, 2020
fe14848

address comments

May 22, 2020
fa84753

Merge branch 'ChuyangDeng-tf-2-2'

May 22, 2020
ff376d8

fix import error

May 22, 2020
598f833

resolve conflicts

May 22, 2020
31110b4

hardcode py_version for tensorflow-training 2.2 tests

May 22, 2020
fa04c1a

import LATEST_SERVING_VERSION from TensorFlow.defaults

May 22, 2020

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2 changes: 1 addition & 1 deletion
doc/using_tf.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -20,7 +20,7 @@ For general information about using the SageMaker Python SDK, see :ref:`overview

.. contents::

Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``.
Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``, ``1.15``, ``2.0``.


*****************************
Expand Down

5 changes: 4 additions & 1 deletion
src/sagemaker/tensorflow/defaults.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -18,7 +18,10 @@
This is no longer updated so as to not break existing workflows.
"""

LATEST_VERSION = "2.1.0"
LATEST_VERSION = "2.2.0"
"""The latest version of TensorFlow included in the SageMaker pre-built Docker images."""

LATEST_SERVING_VERSION = "2.1.0"
"""The latest version of TensorFlow Serving included in the SageMaker pre-built Docker images."""

LATEST_PY2_VERSION = "2.1.0"

12 changes: 10 additions & 2 deletions
tests/conftest.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,8 @@
from sagemaker.pytorch import PyTorch
from sagemaker.rl import RLEstimator
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.tensorflow.estimator import TensorFlow
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION, LATEST_SERVING_VERSION

DEFAULT_REGION = "us-west-2"
CUSTOM_BUCKET_NAME_PREFIX = "sagemaker-custom-bucket"
Expand DownExpand Up@@ -259,7 +260,7 @@ def sklearn_full_version(request):
 return request.config.getoption("--sklearn-full-version")


@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, TensorFlow.LATEST_VERSION])
@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, LATEST_VERSION])
def tf_full_version(request):
 tf_version = request.config.getoption("--tf-full-version")
 if tf_version is None:
Expand DownExpand Up@@ -335,3 +336,10 @@ def pytest_generate_tests(metafunc):
@pytest.fixture(scope="module")
def xgboost_full_version(request):
 return request.config.getoption("--xgboost-full-version")


@pytest.fixture(scope="module")
def tf_serving_version(tf_full_version):
 if tf_full_version == LATEST_VERSION:
 return LATEST_SERVING_VERSION
 return tf_full_version

12 changes: 6 additions & 6 deletions
tests/integ/test_data_capture_config.py

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Expand Up@@ -41,7 +41,7 @@


def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -52,7 +52,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(
Expand DownExpand Up@@ -98,7 +98,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -109,7 +109,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 destination_s3_uri = os.path.join(
Expand DownExpand Up@@ -184,7 +184,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -195,7 +195,7 @@ def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 destination_s3_uri = os.path.join(
Expand Down

4 changes: 2 additions & 2 deletions
tests/integ/test_model_monitor.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -88,7 +88,7 @@


@pytest.fixture(scope="module")
def predictor(sagemaker_session, tf_full_version):
def predictor(sagemaker_session, tf_serving_version):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
 path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -100,7 +100,7 @@ def predictor(sagemaker_session, tf_full_version):
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(
Expand Down

23 changes: 12 additions & 11 deletions
tests/integ/test_tf_script_mode.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
import pytest

from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.utils import unique_name_from_base, sagemaker_timestamp

import tests.integ
Expand All@@ -40,10 +41,8 @@


@pytest.fixture(scope="module")
def py_version(tf_full_version):
 return (
 "py37" if tf_full_version == TensorFlow._LATEST_1X_VERSION else tests.integ.PYTHON_VERSION
 )
def py_version(tf_full_version, tf_serving_version):
 return "py37" if tf_full_version == tf_serving_version else tests.integ.PYTHON_VERSION


def test_mnist_with_checkpoint_config(
Expand All@@ -61,7 +60,7 @@ def test_mnist_with_checkpoint_config(
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 py_version=py_version,
 py_version="py37",
Comment thread
laurenyu marked this conversation as resolved.

 metric_definitions=[{"Name": "train:global_steps", "Regex": r"global_step\/sec:\s(.*)"}],
 checkpoint_s3_uri=checkpoint_s3_uri,
 checkpoint_local_path=checkpoint_local_path,
Expand DownExpand Up@@ -91,7 +90,7 @@ def test_mnist_with_checkpoint_config(
 assert actual_training_checkpoint_config == expected_training_checkpoint_config


def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
def test_server_side_encryption(sagemaker_session, tf_serving_version, py_version):
 with kms_utils.bucket_with_encryption(sagemaker_session, ROLE) as (bucket_with_kms, kms_key):
 output_path = os.path.join(
 bucket_with_kms, "test-server-side-encryption", time.strftime("%y%m%d-%H%M")
Expand All@@ -105,7 +104,7 @@ def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
 train_instance_type="ml.c5.xlarge",
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
@laurenyulaurenyuMay 22, 2020

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why switch to using a serving version for training?
@chuyang-dengchuyang-dengMay 22, 2020

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because this test is doing a deploy later and TFS does not support 2.2 yet.
 py_version=py_version,
 code_location=output_path,
 output_path=output_path,
Expand DownExpand Up@@ -140,7 +139,7 @@ def test_mnist_distributed(sagemaker_session, instance_type, tf_full_version, py
 train_instance_count=2,
 train_instance_type=instance_type,
 sagemaker_session=sagemaker_session,
 py_version=py_version,
 py_version="py37",
 script_mode=True,
 framework_version=tf_full_version,
 distributions=PARAMETER_SERVER_DISTRIBUTION,
Expand DownExpand Up@@ -168,7 +167,7 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
 sagemaker_session=sagemaker_session,
 script_mode=True,
 # testing py-sdk functionality, no need to run against all TF versions
 framework_version=TensorFlow.LATEST_VERSION,
 framework_version=LATEST_SERVING_VERSION,
 tags=TAGS,
 )
 inputs = estimator.sagemaker_session.upload_data(
Expand DownExpand Up@@ -200,7 +199,9 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
 _assert_model_name_match(sagemaker_session.sagemaker_client, endpoint_name, model_name)


def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_version, py_version):
def test_deploy_with_input_handlers(
 sagemaker_session, instance_type, tf_serving_version, py_version
):
 estimator = TensorFlow(
 entry_point="training.py",
 source_dir=TFS_RESOURCE_PATH,
Expand All@@ -210,7 +211,7 @@ def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_ve
 py_version=py_version,
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 tags=TAGS,
 )

Expand Down

12 changes: 6 additions & 6 deletions
tests/integ/test_tfs.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,7 @@


@pytest.fixture(scope="module")
def tfs_predictor(sagemaker_session, tf_full_version):
def tfs_predictor(sagemaker_session, tf_serving_version):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
 path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -37,7 +37,7 @@ def tfs_predictor(sagemaker_session, tf_full_version):
 model = Model(
 model_data=model_data,
 role="SageMakerRole",
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(1, "ml.c5.xlarge", endpoint_name=endpoint_name)
Expand All@@ -54,7 +54,7 @@ def tar_dir(directory, tmpdir):

@pytest.fixture
def tfs_predictor_with_model_and_entry_point_same_tar(
 sagemaker_local_session, tf_full_version, tmpdir
 sagemaker_local_session, tf_serving_version, tmpdir
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -65,7 +65,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(
 model = Model(
 model_data="file://" + model_tar,
 role="SageMakerRole",
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_local_session,
 )
 predictor = model.deploy(1, "local", endpoint_name=endpoint_name)
Expand All@@ -78,7 +78,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(

@pytest.fixture(scope="module")
def tfs_predictor_with_model_and_entry_point_and_dependencies(
 sagemaker_local_session, tf_full_version
 sagemaker_local_session, tf_serving_version
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -98,7 +98,7 @@ def tfs_predictor_with_model_and_entry_point_and_dependencies(
 model_data=model_data,
 role="SageMakerRole",
 dependencies=dependencies,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_local_session,
 )

Expand Down

3 changes: 2 additions & 1 deletion
tests/integ/test_transformer.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -25,6 +25,7 @@
from sagemaker.mxnet import MXNet
from sagemaker.pytorch import PyTorchModel
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.transformer import Transformer
from sagemaker.estimator import Estimator
from sagemaker.utils import unique_name_from_base
Expand DownExpand Up@@ -351,7 +352,7 @@ def test_transform_tf_kms_network_isolation(sagemaker_session, cpu_instance_type
 role="SageMakerRole",
 train_instance_count=1,
 train_instance_type=cpu_instance_type,
 framework_version=TensorFlow.LATEST_VERSION,
 framework_version=LATEST_SERVING_VERSION,
 script_mode=True,
 py_version=PYTHON_VERSION,
 sagemaker_session=sagemaker_session,
Expand Down

12 changes: 10 additions & 2 deletions
tests/integ/test_tuner.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -37,6 +37,7 @@
from sagemaker.predictor import json_deserializer
from sagemaker.pytorch import PyTorch
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION
from sagemaker.tuner import (
 IntegerParameter,
 ContinuousParameter,
Expand All@@ -51,6 +52,13 @@

DATA_PATH = os.path.join(DATA_DIR, "iris", "data")

PY37_SUPPORTED_FRAMEWORK_VERSION = [TensorFlow._LATEST_1X_VERSION, LATEST_VERSION]


@pytest.fixture(scope="module")
def py_version(tf_full_version):
 return "py37" if tf_full_version in PY37_SUPPORTED_FRAMEWORK_VERSION else PYTHON_VERSION


@pytest.fixture(scope="module")
def kmeans_train_set(sagemaker_session):
Expand DownExpand Up@@ -590,7 +598,7 @@ def test_tuning_mxnet(sagemaker_session, mxnet_full_version, cpu_instance_type):


@pytest.mark.canary_quick
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version):
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version, py_version):
 resource_path = os.path.join(DATA_DIR, "tensorflow_mnist")
 script_path = os.path.join(resource_path, "mnist.py")

Expand All@@ -601,7 +609,7 @@ def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_ver
 train_instance_type=cpu_instance_type,
 script_mode=True,
 sagemaker_session=sagemaker_session,
 py_version=PYTHON_VERSION,
 py_version=py_version,
 framework_version=tf_full_version,
 )

Expand Down

, '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); }
})();
})();

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feature: support TensorFlow training 2.2#1521

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 Merged

chuyang-deng
merged 33 commits into

from

May 22, 2020
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feature: support TensorFlow training 2.2
#1521
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1c9dd16

update with aws/master


chuyang-deng May 15, 2020
aa349fd

upate with aws master


chuyang-deng May 18, 2020
c875c47

update with aws master


chuyang-deng May 19, 2020
3e23a39

feature: TensorFlow 2.2 support

May 19, 2020
e9a96ec

Merge branch 'master' into tf-2-2


chuyang-deng May 19, 2020
1d66433

prevent TFS test pulling 2.2.0 images

May 20, 2020
dc8e4f7

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 20, 2020
98a0a5e

fix flake8 error

May 20, 2020
7f44c65

update tfs test versions

May 21, 2020
b33deb9

use tfs 2.1.0 in model monitor tests

May 21, 2020
8da6509

distinguish tf and tfs latest versions in test

May 21, 2020
4f85786

add latest serving version

May 21, 2020
cb2a489

let py_version pick up tf_training_version

May 21, 2020
c9dcdd0

Merge branch 'master' into tf-2-2


chuyang-deng May 21, 2020
ed177e8

fix typo

May 21, 2020
816030e

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
0b77be7

no py37 for tfs 2.1

May 21, 2020
89bb6d6

fix black error

May 21, 2020
40da473

prevent tfs pulling 2.2 image

May 20, 2020
c251fcc

tf 2.2 using py37

May 21, 2020
e010da9

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
edeb501

Merge branch 'master' into tf-2-2


chuyang-deng May 21, 2020
3255b04

test_data_capture_config use TFS latest version

May 21, 2020
403298e

Merge branch 'tf-2-2' of github.com:ChuyangDeng/sagemaker-python-sdk …

May 21, 2020
2a7f154

fix flake8 error

May 21, 2020
3b10a76

update model monitoring test

May 21, 2020
9c2bb6c

update python version for tuner integ test

May 21, 2020
fe14848

address comments

May 22, 2020
fa84753

Merge branch 'ChuyangDeng-tf-2-2'

May 22, 2020
ff376d8

fix import error

May 22, 2020
598f833

resolve conflicts

May 22, 2020
31110b4

hardcode py_version for tensorflow-training 2.2 tests

May 22, 2020
fa04c1a

import LATEST_SERVING_VERSION from TensorFlow.defaults

May 22, 2020

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2 changes: 1 addition & 1 deletion
doc/using_tf.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -20,7 +20,7 @@ For general information about using the SageMaker Python SDK, see :ref:`overview

.. contents::

Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``.
Supported versions of TensorFlow for Elastic Inference: ``1.11``, ``1.12``, ``1.13``, ``1.14``, ``1.15``, ``2.0``.


*****************************
Expand Down

5 changes: 4 additions & 1 deletion
src/sagemaker/tensorflow/defaults.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -18,7 +18,10 @@
This is no longer updated so as to not break existing workflows.
"""

LATEST_VERSION = "2.1.0"
LATEST_VERSION = "2.2.0"
"""The latest version of TensorFlow included in the SageMaker pre-built Docker images."""

LATEST_SERVING_VERSION = "2.1.0"
"""The latest version of TensorFlow Serving included in the SageMaker pre-built Docker images."""

LATEST_PY2_VERSION = "2.1.0"

12 changes: 10 additions & 2 deletions
tests/conftest.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,8 @@
from sagemaker.pytorch import PyTorch
from sagemaker.rl import RLEstimator
from sagemaker.sklearn.defaults import SKLEARN_VERSION
from sagemaker.tensorflow.estimator import TensorFlow
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION, LATEST_SERVING_VERSION

DEFAULT_REGION = "us-west-2"
CUSTOM_BUCKET_NAME_PREFIX = "sagemaker-custom-bucket"
Expand DownExpand Up@@ -259,7 +260,7 @@ def sklearn_full_version(request):
 return request.config.getoption("--sklearn-full-version")


@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, TensorFlow.LATEST_VERSION])
@pytest.fixture(scope="module", params=[TensorFlow._LATEST_1X_VERSION, LATEST_VERSION])
def tf_full_version(request):
 tf_version = request.config.getoption("--tf-full-version")
 if tf_version is None:
Expand DownExpand Up@@ -335,3 +336,10 @@ def pytest_generate_tests(metafunc):
@pytest.fixture(scope="module")
def xgboost_full_version(request):
 return request.config.getoption("--xgboost-full-version")


@pytest.fixture(scope="module")
def tf_serving_version(tf_full_version):
 if tf_full_version == LATEST_VERSION:
 return LATEST_SERVING_VERSION
 return tf_full_version

12 changes: 6 additions & 6 deletions
tests/integ/test_data_capture_config.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -41,7 +41,7 @@


def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -52,7 +52,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(
Expand DownExpand Up@@ -98,7 +98,7 @@ def test_enabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -109,7 +109,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 destination_s3_uri = os.path.join(
Expand DownExpand Up@@ -184,7 +184,7 @@ def test_disabling_data_capture_on_endpoint_shows_correct_data_capture_status(


def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
 sagemaker_session, tf_full_version
 sagemaker_session, tf_serving_version
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
Expand All@@ -195,7 +195,7 @@ def test_updating_data_capture_on_endpoint_shows_correct_data_capture_status(
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 destination_s3_uri = os.path.join(
Expand Down

4 changes: 2 additions & 2 deletions
tests/integ/test_model_monitor.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -88,7 +88,7 @@


@pytest.fixture(scope="module")
def predictor(sagemaker_session, tf_full_version):
def predictor(sagemaker_session, tf_serving_version):
 endpoint_name = unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
 path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -100,7 +100,7 @@ def predictor(sagemaker_session, tf_full_version):
 model = Model(
 model_data=model_data,
 role=ROLE,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(
Expand Down

23 changes: 12 additions & 11 deletions
tests/integ/test_tf_script_mode.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
import pytest

from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.utils import unique_name_from_base, sagemaker_timestamp

import tests.integ
Expand All@@ -40,10 +41,8 @@


@pytest.fixture(scope="module")
def py_version(tf_full_version):
 return (
 "py37" if tf_full_version == TensorFlow._LATEST_1X_VERSION else tests.integ.PYTHON_VERSION
 )
def py_version(tf_full_version, tf_serving_version):
 return "py37" if tf_full_version == tf_serving_version else tests.integ.PYTHON_VERSION


def test_mnist_with_checkpoint_config(
Expand All@@ -61,7 +60,7 @@ def test_mnist_with_checkpoint_config(
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 py_version=py_version,
 py_version="py37",
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laurenyu marked this conversation as resolved.

 metric_definitions=[{"Name": "train:global_steps", "Regex": r"global_step\/sec:\s(.*)"}],
 checkpoint_s3_uri=checkpoint_s3_uri,
 checkpoint_local_path=checkpoint_local_path,
Expand DownExpand Up@@ -91,7 +90,7 @@ def test_mnist_with_checkpoint_config(
 assert actual_training_checkpoint_config == expected_training_checkpoint_config


def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
def test_server_side_encryption(sagemaker_session, tf_serving_version, py_version):
 with kms_utils.bucket_with_encryption(sagemaker_session, ROLE) as (bucket_with_kms, kms_key):
 output_path = os.path.join(
 bucket_with_kms, "test-server-side-encryption", time.strftime("%y%m%d-%H%M")
Expand All@@ -105,7 +104,7 @@ def test_server_side_encryption(sagemaker_session, tf_full_version, py_version):
 train_instance_type="ml.c5.xlarge",
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
@laurenyulaurenyuMay 22, 2020

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why switch to using a serving version for training?
@chuyang-dengchuyang-dengMay 22, 2020

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because this test is doing a deploy later and TFS does not support 2.2 yet.
 py_version=py_version,
 code_location=output_path,
 output_path=output_path,
Expand DownExpand Up@@ -140,7 +139,7 @@ def test_mnist_distributed(sagemaker_session, instance_type, tf_full_version, py
 train_instance_count=2,
 train_instance_type=instance_type,
 sagemaker_session=sagemaker_session,
 py_version=py_version,
 py_version="py37",
 script_mode=True,
 framework_version=tf_full_version,
 distributions=PARAMETER_SERVER_DISTRIBUTION,
Expand DownExpand Up@@ -168,7 +167,7 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
 sagemaker_session=sagemaker_session,
 script_mode=True,
 # testing py-sdk functionality, no need to run against all TF versions
 framework_version=TensorFlow.LATEST_VERSION,
 framework_version=LATEST_SERVING_VERSION,
 tags=TAGS,
 )
 inputs = estimator.sagemaker_session.upload_data(
Expand DownExpand Up@@ -200,7 +199,9 @@ def test_mnist_async(sagemaker_session, cpu_instance_type, tf_full_version, py_v
 _assert_model_name_match(sagemaker_session.sagemaker_client, endpoint_name, model_name)


def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_version, py_version):
def test_deploy_with_input_handlers(
 sagemaker_session, instance_type, tf_serving_version, py_version
):
 estimator = TensorFlow(
 entry_point="training.py",
 source_dir=TFS_RESOURCE_PATH,
Expand All@@ -210,7 +211,7 @@ def test_deploy_with_input_handlers(sagemaker_session, instance_type, tf_full_ve
 py_version=py_version,
 sagemaker_session=sagemaker_session,
 script_mode=True,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 tags=TAGS,
 )

Expand Down

12 changes: 6 additions & 6 deletions
tests/integ/test_tfs.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -27,7 +27,7 @@


@pytest.fixture(scope="module")
def tfs_predictor(sagemaker_session, tf_full_version):
def tfs_predictor(sagemaker_session, tf_serving_version):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
 model_data = sagemaker_session.upload_data(
 path=os.path.join(tests.integ.DATA_DIR, "tensorflow-serving-test-model.tar.gz"),
Expand All@@ -37,7 +37,7 @@ def tfs_predictor(sagemaker_session, tf_full_version):
 model = Model(
 model_data=model_data,
 role="SageMakerRole",
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_session,
 )
 predictor = model.deploy(1, "ml.c5.xlarge", endpoint_name=endpoint_name)
Expand All@@ -54,7 +54,7 @@ def tar_dir(directory, tmpdir):

@pytest.fixture
def tfs_predictor_with_model_and_entry_point_same_tar(
 sagemaker_local_session, tf_full_version, tmpdir
 sagemaker_local_session, tf_serving_version, tmpdir
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -65,7 +65,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(
 model = Model(
 model_data="file://" + model_tar,
 role="SageMakerRole",
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_local_session,
 )
 predictor = model.deploy(1, "local", endpoint_name=endpoint_name)
Expand All@@ -78,7 +78,7 @@ def tfs_predictor_with_model_and_entry_point_same_tar(

@pytest.fixture(scope="module")
def tfs_predictor_with_model_and_entry_point_and_dependencies(
 sagemaker_local_session, tf_full_version
 sagemaker_local_session, tf_serving_version
):
 endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")

Expand All@@ -98,7 +98,7 @@ def tfs_predictor_with_model_and_entry_point_and_dependencies(
 model_data=model_data,
 role="SageMakerRole",
 dependencies=dependencies,
 framework_version=tf_full_version,
 framework_version=tf_serving_version,
 sagemaker_session=sagemaker_local_session,
 )

Expand Down

3 changes: 2 additions & 1 deletion
tests/integ/test_transformer.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -25,6 +25,7 @@
from sagemaker.mxnet import MXNet
from sagemaker.pytorch import PyTorchModel
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_SERVING_VERSION
from sagemaker.transformer import Transformer
from sagemaker.estimator import Estimator
from sagemaker.utils import unique_name_from_base
Expand DownExpand Up@@ -351,7 +352,7 @@ def test_transform_tf_kms_network_isolation(sagemaker_session, cpu_instance_type
 role="SageMakerRole",
 train_instance_count=1,
 train_instance_type=cpu_instance_type,
 framework_version=TensorFlow.LATEST_VERSION,
 framework_version=LATEST_SERVING_VERSION,
 script_mode=True,
 py_version=PYTHON_VERSION,
 sagemaker_session=sagemaker_session,
Expand Down

12 changes: 10 additions & 2 deletions
tests/integ/test_tuner.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -37,6 +37,7 @@
from sagemaker.predictor import json_deserializer
from sagemaker.pytorch import PyTorch
from sagemaker.tensorflow import TensorFlow
from sagemaker.tensorflow.defaults import LATEST_VERSION
from sagemaker.tuner import (
 IntegerParameter,
 ContinuousParameter,
Expand All@@ -51,6 +52,13 @@

DATA_PATH = os.path.join(DATA_DIR, "iris", "data")

PY37_SUPPORTED_FRAMEWORK_VERSION = [TensorFlow._LATEST_1X_VERSION, LATEST_VERSION]


@pytest.fixture(scope="module")
def py_version(tf_full_version):
 return "py37" if tf_full_version in PY37_SUPPORTED_FRAMEWORK_VERSION else PYTHON_VERSION


@pytest.fixture(scope="module")
def kmeans_train_set(sagemaker_session):
Expand DownExpand Up@@ -590,7 +598,7 @@ def test_tuning_mxnet(sagemaker_session, mxnet_full_version, cpu_instance_type):


@pytest.mark.canary_quick
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version):
def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_version, py_version):
 resource_path = os.path.join(DATA_DIR, "tensorflow_mnist")
 script_path = os.path.join(resource_path, "mnist.py")

Expand All@@ -601,7 +609,7 @@ def test_tuning_tf_script_mode(sagemaker_session, cpu_instance_type, tf_full_ver
 train_instance_type=cpu_instance_type,
 script_mode=True,
 sagemaker_session=sagemaker_session,
 py_version=PYTHON_VERSION,
 py_version=py_version,
 framework_version=tf_full_version,
 )

Expand Down