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[release] update torch_tune_serve_test to use anyscale connect #16754

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merged 4 commits into from
Jul 7, 2021
Merged

[release] update torch_tune_serve_test to use anyscale connect #16754

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1bb42d9
[release] update torch_tune_serve_test to use anyscale connect
matthewdeng Jun 29, 2021
55dc78f
use download_results to download model checkpoint
matthewdeng Jul 2, 2021
c3cd376
Merge branch 'master' of https://github.com/ray-project/ray into torc…
matthewdeng Jul 2, 2021
9942402
clean up code to support both OSS and Anyscale
matthewdeng Jul 7, 2021
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clean up code to support both OSS and Anyscale
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@matthewdeng
matthewdeng committed Jul 7, 2021
commit 9942402c66611ab1aa38ca3b4d4d14313d54778a
17 changes: 13 additions & 4 deletions release/golden_notebook_tests/workloads/torch_tune_serve_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,13 @@
from torchvision.datasets import MNIST


def _is_anyscale_connect():
address = os.environ.get("RAY_ADDRESS")
is_anyscale_connect = address is not None and address.startswith(
"anyscale:https://")
return is_anyscale_connect


def load_mnist_data(train: bool, download: bool):
transform = transforms.Compose(
[transforms.ToTensor(),
Expand Down Expand Up @@ -86,8 +93,7 @@ def train_mnist(test_mode=False, num_workers=1, use_gpu=False):


def get_remote_model(remote_model_checkpoint_path):
address = os.environ.get("RAY_ADDRESS")
if address is not None and address.startswith("anyscale:https://"):
if _is_anyscale_connect():
# Download training results to local client.
local_dir = "~/ray_results"
# TODO(matt): remove the following line when Anyscale Connect
Expand Down Expand Up @@ -210,8 +216,11 @@ def test_predictions(test_mode=False):

start = time.time()

job_name = os.environ.get("RAY_JOB_NAME", "torch_tune_serve_test")
ray.client().job_name(job_name).connect()
client_builder = ray.client()
if (_is_anyscale_connect()):
job_name = os.environ.get("RAY_JOB_NAME", "torch_tune_serve_test")
client_builder.job_name(job_name)
client_builder.connect()

num_workers = 2
use_gpu = True
Expand Down