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fix: skip pytorch ei test in unsupported regions #1337

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Merged
merged 3 commits into from
Mar 9, 2020
Merged

fix: skip pytorch ei test in unsupported regions #1337

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ac88fa0
fix: skip pytorch ei test in unsupported regions
Mar 9, 2020
d81afe8
fix flake8 error
Mar 9, 2020
ce11531
Merge branch 'master' into master
chuyang-deng Mar 9, 2020
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22 changes: 15 additions & 7 deletions tests/integ/test_pytorch_train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,18 +12,23 @@
# language governing permissions and limitations under the License.
from __future__ import absolute_import

import os

import numpy
import os
import pytest
from tests.integ import DATA_DIR, PYTHON_VERSION, TRAINING_DEFAULT_TIMEOUT_MINUTES
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

from sagemaker.pytorch.defaults import LATEST_PY2_VERSION
from sagemaker.pytorch.estimator import PyTorch
from sagemaker.pytorch.model import PyTorchModel
from sagemaker.pytorch.defaults import LATEST_PY2_VERSION
from sagemaker.utils import sagemaker_timestamp

from tests.integ import (
test_region,
DATA_DIR,
PYTHON_VERSION,
TRAINING_DEFAULT_TIMEOUT_MINUTES,
EI_SUPPORTED_REGIONS,
)
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name

MNIST_DIR = os.path.join(DATA_DIR, "pytorch_mnist")
MNIST_SCRIPT = os.path.join(MNIST_DIR, "mnist.py")

Expand Down Expand Up @@ -120,6 +125,9 @@ def test_deploy_model(pytorch_training_job, sagemaker_session, cpu_instance_type


@pytest.mark.skipif(PYTHON_VERSION == "py2", reason="PyTorch EIA does not support Python 2.")
@pytest.mark.skipif(
test_region() not in EI_SUPPORTED_REGIONS, reason="EI isn't supported in that specific region."
)
def test_deploy_model_with_accelerator(sagemaker_session, cpu_instance_type):
endpoint_name = "test-pytorch-deploy-eia-{}".format(sagemaker_timestamp())
model_data = sagemaker_session.upload_data(path=EIA_MODEL)
Expand All @@ -134,7 +142,7 @@ def test_deploy_model_with_accelerator(sagemaker_session, cpu_instance_type):
predictor = pytorch.deploy(
initial_instance_count=1,
instance_type=cpu_instance_type,
accelerator_type="ml.eia2.medium",
accelerator_type="ml.eia1.medium",
endpoint_name=endpoint_name,
)

Expand Down