mirror of
https://github.com/vale981/ray
synced 2025-03-06 10:31:39 -05:00
547 lines
18 KiB
Python
547 lines
18 KiB
Python
import copy
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import logging
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import os
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import sys
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import yaml
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# Env variables:
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# RAY_REPO Repo to use for finding the wheel
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# RAY_BRANCH Branch to find the wheel
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# RAY_VERSION Version to find the wheel
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# RAY_WHEELS Direct Ray wheel URL
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# RAY_TEST_REPO Repo to use for test scripts
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# RAY_TEST_BRANCH Branch for test scripts
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# FILTER_FILE File filter
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# FILTER_TEST Test name filter
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# RELEASE_TEST_SUITE Release test suite (e.g. manual, nightly)
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class ReleaseTest:
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def __init__(self, name: str, smoke_test: bool = False, retry: int = 0):
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self.name = name
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self.smoke_test = smoke_test
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self.retry = retry
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def __str__(self):
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return self.name
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def __repr__(self):
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return self.name
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def __contains__(self, item):
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return self.name.__contains__(item)
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def __iter__(self):
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return iter(self.name)
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def __len__(self):
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return len(self.name)
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class SmokeTest(ReleaseTest):
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def __init__(self, name: str, retry: int = 0):
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super(SmokeTest, self).__init__(
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name=name, smoke_test=True, retry=retry)
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CORE_NIGHTLY_TESTS = {
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"~/ray/release/nightly_tests/nightly_tests.yaml": [
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"shuffle_10gb",
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"shuffle_50gb",
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"shuffle_50gb_large_partition",
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"shuffle_100gb",
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"non_streaming_shuffle_100gb",
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"non_streaming_shuffle_50gb_large_partition",
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"non_streaming_shuffle_50gb",
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"dask_on_ray_10gb_sort",
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"dask_on_ray_100gb_sort",
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SmokeTest("dask_on_ray_large_scale_test_no_spilling"),
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SmokeTest("dask_on_ray_large_scale_test_spilling"),
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"stress_test_placement_group",
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"shuffle_1tb_1000_partition",
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"non_streaming_shuffle_1tb_1000_partition",
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"shuffle_1tb_5000_partitions",
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# TODO(sang): It doesn't even work without spilling
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# as it hits the scalability limit.
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# "non_streaming_shuffle_1tb_5000_partitions",
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"decision_tree_autoscaling",
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"autoscaling_shuffle_1tb_1000_partitions",
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SmokeTest("stress_test_many_tasks"),
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SmokeTest("stress_test_dead_actors"),
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"shuffle_data_loader",
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"dask_on_ray_1tb_sort",
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"many_nodes_actor_test",
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],
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"~/ray/benchmarks/benchmark_tests.yaml": [
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"single_node",
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"object_store",
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"many_actors_smoke_test",
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"many_tasks_smoke_test",
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"many_pgs_smoke_test",
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],
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"~/ray/release/nightly_tests/dataset/dataset_test.yaml": [
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"inference",
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"shuffle_data_loader",
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"pipelined_training_50_gb",
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"pipelined_ingestion_1500_gb_15_windows",
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],
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}
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NIGHTLY_TESTS = {
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# "~/ray/release/horovod_tests/horovod_tests.yaml": [
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# SmokeTest("horovod_test"),
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# ], # Should we enable this?
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"~/ray/release/golden_notebook_tests/golden_notebook_tests.yaml": [
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"dask_xgboost_test",
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"modin_xgboost_test",
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"torch_tune_serve_test",
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],
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"~/ray/release/nightly_tests/nightly_tests.yaml": [
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"dask_on_ray_large_scale_test_no_spilling",
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"dask_on_ray_large_scale_test_spilling",
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"pg_autoscaling_regression_test",
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],
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"~/ray/release/long_running_tests/long_running_tests.yaml": [
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SmokeTest("actor_deaths"),
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SmokeTest("apex"),
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SmokeTest("impala"),
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SmokeTest("many_actor_tasks"),
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SmokeTest("many_drivers"),
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SmokeTest("many_ppo"),
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SmokeTest("many_tasks"),
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SmokeTest("many_tasks_serialized_ids"),
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SmokeTest("node_failures"),
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SmokeTest("pbt"),
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# SmokeTest("serve"),
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# SmokeTest("serve_failure"),
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],
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"~/ray/release/microbenchmark/microbenchmark.yaml": [
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"microbenchmark",
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],
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"~/ray/release/sgd_tests/sgd_tests.yaml": [
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"sgd_gpu",
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],
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"~/ray/release/tune_tests/scalability_tests/tune_tests.yaml": [
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"bookkeeping_overhead",
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"durable_trainable",
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SmokeTest("long_running_large_checkpoints"),
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SmokeTest("network_overhead"),
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"result_throughput_cluster",
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"result_throughput_single_node",
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"xgboost_sweep",
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],
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"~/ray/release/xgboost_tests/xgboost_tests.yaml": [
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"train_small",
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"train_moderate",
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"train_gpu",
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"tune_small",
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"tune_4x32",
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"tune_32x4",
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"ft_small_elastic",
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"ft_small_non_elastic",
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"distributed_api_test",
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],
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"~/ray/release/rllib_tests/rllib_tests.yaml": [
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SmokeTest("learning_tests"),
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SmokeTest("stress_tests"),
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"multi_gpu_learning_tests",
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"multi_gpu_with_lstm_learning_tests",
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"multi_gpu_with_attention_learning_tests",
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# We'll have these as per-PR tests soon.
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# "example_scripts_on_gpu_tests",
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],
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"~/ray/release/serve_tests/serve_tests.yaml": [
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"single_deployment_1k_noop_replica",
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"multi_deployment_1k_noop_replica",
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"serve_micro_benchmark",
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"serve_cluster_fault_tolerance",
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],
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"~/ray/release/runtime_env_tests/runtime_env_tests.yaml": [
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"rte_many_tasks_actors",
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"wheel_urls",
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],
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}
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WEEKLY_TESTS = {
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"~/ray/benchmarks/benchmark_tests.yaml": [
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"many_actors",
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"many_tasks",
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"many_pgs",
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"many_nodes",
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],
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"~/ray/release/nightly_tests/nightly_tests.yaml": [
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"stress_test_many_tasks",
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"stress_test_dead_actors",
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],
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"~/ray/release/horovod_tests/horovod_tests.yaml": [
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"horovod_test",
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],
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"~/ray/release/long_running_distributed_tests"
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"/long_running_distributed.yaml": [
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"pytorch_pbt_failure",
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],
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# Full long running tests (1 day runtime)
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"~/ray/release/long_running_tests/long_running_tests.yaml": [
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"actor_deaths",
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"apex",
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"impala",
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"many_actor_tasks",
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"many_drivers",
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"many_ppo",
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"many_tasks",
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"many_tasks_serialized_ids",
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"node_failures",
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"pbt",
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"serve",
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"serve_failure",
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],
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"~/ray/release/tune_tests/scalability_tests/tune_tests.yaml": [
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"network_overhead",
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"long_running_large_checkpoints",
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],
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"~/ray/release/rllib_tests/rllib_tests.yaml": [
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"learning_tests",
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"stress_tests",
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],
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}
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MANUAL_TESTS = {
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"~/ray/release/long_running_tests/long_running_tests.yaml": [
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SmokeTest("serve"),
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SmokeTest("serve_failure"),
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]
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}
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SUITES = {
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"core-nightly": CORE_NIGHTLY_TESTS,
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"nightly": NIGHTLY_TESTS,
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"weekly": WEEKLY_TESTS,
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"manual": MANUAL_TESTS,
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}
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DEFAULT_STEP_TEMPLATE = {
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"env": {
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"ANYSCALE_CLOUD_ID": "cld_4F7k8814aZzGG8TNUGPKnc",
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"ANYSCALE_PROJECT": "prj_2xR6uT6t7jJuu1aCwWMsle",
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"RELEASE_AWS_BUCKET": "ray-release-automation-results",
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"RELEASE_AWS_LOCATION": "dev",
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"RELEASE_AWS_DB_NAME": "ray_ci",
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"RELEASE_AWS_DB_TABLE": "release_test_result",
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"AWS_REGION": "us-west-2"
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},
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"agents": {
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"queue": "runner_queue_branch"
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},
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"plugins": [{
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"docker#v3.8.0": {
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"image": "rayproject/ray",
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"propagate-environment": True,
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"volumes": [
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"/tmp/ray_release_test_artifacts:"
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"/tmp/ray_release_test_artifacts"
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],
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}
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}],
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"commands": [],
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"artifact_paths": ["/tmp/ray_release_test_artifacts/**/*"],
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}
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def ask_configuration():
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RAY_BRANCH = os.environ.get("RAY_BRANCH", "master")
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RAY_REPO = os.environ.get("RAY_REPO",
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"https://github.com/ray-project/ray.git")
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RAY_VERSION = os.environ.get("RAY_VERSION", "")
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RAY_WHEELS = os.environ.get("RAY_WHEELS", "")
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RAY_TEST_BRANCH = os.environ.get("RAY_TEST_BRANCH", RAY_BRANCH)
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RAY_TEST_REPO = os.environ.get("RAY_TEST_REPO", RAY_REPO)
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RELEASE_TEST_SUITE = os.environ.get("RELEASE_TEST_SUITE", "nightly")
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FILTER_FILE = os.environ.get("FILTER_FILE", "")
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FILTER_TEST = os.environ.get("FILTER_TEST", "")
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input_ask_step = {
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"input": "Input required: Please specify tests to run",
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"fields": [
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{
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"text": ("RAY_REPO: Please specify the Ray repository used "
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"to find the wheel."),
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"hint": ("Repository from which to fetch the latest "
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"commits to find the Ray wheels. Usually you don't "
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"need to change this."),
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"default": RAY_REPO,
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"key": "ray_repo"
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},
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{
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"text": ("RAY_BRANCH: Please specify the Ray branch used "
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"to find the wheel."),
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"hint": "For releases, this will be e.g. `releases/1.x.0`",
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"default": RAY_BRANCH,
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"key": "ray_branch"
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},
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{
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"text": ("RAY_VERSION: Please specify the Ray version used "
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"to find the wheel."),
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"hint": ("Leave empty for latest master. For releases, "
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"specify the release version."),
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"required": False,
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"default": RAY_VERSION,
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"key": "ray_version"
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},
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{
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"text": "RAY_WHEELS: Please specify the Ray wheel URL.",
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"hint": ("ATTENTION: If you provide this, RAY_REPO, "
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"RAY_BRANCH and RAY_VERSION will be ignored! "
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"Please also make sure to provide the wheels URL "
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"for Python 3.7 on Linux.\n"
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"You can also insert a commit hash here instead "
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"of a full URL.\n"
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"NOTE: You can specify multiple commits or URLs "
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"for easy bisection (one per line) - this will "
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"run each test on each of the specified wheels."),
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"required": False,
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"default": RAY_WHEELS,
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"key": "ray_wheels"
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},
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{
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"text": ("RAY_TEST_REPO: Please specify the Ray repository "
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"used to find the tests you would like to run."),
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"hint": ("If you're developing a new release test, this "
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"will most likely be your GitHub fork."),
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"default": RAY_TEST_REPO,
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"key": "ray_test_repo"
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},
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{
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"text": ("RAY_TEST_BRANCH: Please specify the Ray branch used "
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"to find the tests you would like to run."),
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"hint": ("If you're developing a new release test, this "
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"will most likely be a branch living on your "
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"GitHub fork."),
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"default": RAY_TEST_BRANCH,
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"key": "ray_test_branch"
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},
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{
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"select": ("RELEASE_TEST_SUITE: Please specify the release "
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"test suite containing the tests you would like "
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"to run."),
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"hint": ("Check in the `build_pipeline.py` if you're "
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"unsure which suite contains your tests."),
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"required": True,
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"options": sorted(SUITES.keys()),
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"default": RELEASE_TEST_SUITE,
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"key": "release_test_suite"
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},
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{
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"text": ("FILTER_FILE: Please specify a filter for the "
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"test files that should be included in this build."),
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"hint": ("Only test files (e.g. xgboost_tests.yml) that "
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"match this string will be included in the test"),
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"default": FILTER_FILE,
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"required": False,
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"key": "filter_file"
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},
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{
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"text": ("FILTER_TEST: Please specify a filter for the "
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"test names that should be included in this build."),
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"hint": ("Only test names (e.g. tune_4x32) that match "
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"this string will be included in the test"),
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"default": FILTER_TEST,
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"required": False,
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"key": "filter_test"
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},
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],
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"key": "input_ask_step",
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}
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run_again_step = {
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"commands": [
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f"export {v}=$(buildkite-agent meta-data get \"{k}\")"
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for k, v in {
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"ray_branch": "RAY_BRANCH",
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"ray_repo": "RAY_REPO",
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"ray_version": "RAY_VERSION",
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"ray_wheels": "RAY_WHEELS",
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"ray_test_branch": "RAY_TEST_BRANCH",
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"ray_test_repo": "RAY_TEST_REPO",
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"release_test_suite": "RELEASE_TEST_SUITE",
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"filter_file": "FILTER_FILE",
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"filter_test": "FILTER_TEST",
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}.items()
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] + [
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"export AUTOMATIC=1",
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"python3 -m pip install --user pyyaml",
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"rm -rf ~/ray || true",
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"git clone -b $${RAY_TEST_BRANCH} $${RAY_TEST_REPO} ~/ray",
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("python3 ~/ray/release/.buildkite/build_pipeline.py "
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"| buildkite-agent pipeline upload"),
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],
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"label": ":pipeline: Again",
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"agents": {
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"queue": "runner_queue_branch"
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},
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"depends_on": "input_ask_step",
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"key": "run_again_step",
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}
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return [
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input_ask_step,
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run_again_step,
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]
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def create_test_step(
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ray_repo: str,
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ray_branch: str,
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ray_version: str,
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ray_wheels: str,
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ray_test_repo: str,
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ray_test_branch: str,
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test_file: str,
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test_name: ReleaseTest,
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):
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if ray_wheels:
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ray_wheels_str = f" ({ray_wheels}) "
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logging.info(f"Creating step for {test_file}/{test_name}{ray_wheels_str}")
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cmd = str(f"RAY_REPO=\"{ray_repo}\" "
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f"RAY_BRANCH=\"{ray_branch}\" "
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f"RAY_VERSION=\"{ray_version}\" "
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f"RAY_WHEELS=\"{ray_wheels}\" "
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f"RELEASE_RESULTS_DIR=/tmp/artifacts "
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f"python release/e2e.py "
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f"--category {ray_branch} "
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f"--test-config {test_file} "
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f"--test-name {test_name} "
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f"--keep-results-dir")
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if test_name.smoke_test:
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logging.info("This test will run as a smoke test.")
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cmd += " --smoke-test"
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step_conf = copy.deepcopy(DEFAULT_STEP_TEMPLATE)
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if test_name.retry:
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logging.info(f"This test will be retried up to "
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f"{test_name.retry} times.")
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step_conf["retry"] = {
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"automatic": [{
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"exit_status": "*",
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"limit": test_name.retry
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}]
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}
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step_conf["commands"] = [
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"pip install -q -r release/requirements.txt",
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"pip install -U boto3 botocore",
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f"git clone -b {ray_test_branch} {ray_test_repo} ~/ray", cmd,
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"sudo cp -rf /tmp/artifacts/* /tmp/ray_release_test_artifacts "
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"|| true"
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]
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step_conf["label"] = f"{ray_wheels_str}{test_name} ({ray_branch}) - " \
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f"{ray_test_branch}/{ray_test_repo}"
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return step_conf
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def build_pipeline(steps):
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all_steps = []
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RAY_BRANCH = os.environ.get("RAY_BRANCH", "master")
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RAY_REPO = os.environ.get("RAY_REPO",
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"https://github.com/ray-project/ray.git")
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RAY_VERSION = os.environ.get("RAY_VERSION", "")
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RAY_WHEELS = os.environ.get("RAY_WHEELS", "")
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RAY_TEST_BRANCH = os.environ.get("RAY_TEST_BRANCH", RAY_BRANCH)
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RAY_TEST_REPO = os.environ.get("RAY_TEST_REPO", RAY_REPO)
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FILTER_FILE = os.environ.get("FILTER_FILE", "")
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FILTER_TEST = os.environ.get("FILTER_TEST", "")
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ray_wheels_list = [""]
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if RAY_WHEELS:
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ray_wheels_list = RAY_WHEELS.split("\n")
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if len(ray_wheels_list) > 1:
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logging.info(f"This will run a bisec on the following URLs/commits: "
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f"{ray_wheels_list}")
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logging.info(
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f"Building pipeline \n"
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f"Ray repo/branch to test:\n"
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f" RAY_REPO = {RAY_REPO}\n"
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f" RAY_BRANCH = {RAY_BRANCH}\n\n"
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f" RAY_VERSION = {RAY_VERSION}\n\n"
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f" RAY_WHEELS = {RAY_WHEELS}\n\n"
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f"Ray repo/branch containing the test configurations and scripts:"
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f" RAY_TEST_REPO = {RAY_TEST_REPO}\n"
|
|
f" RAY_TEST_BRANCH = {RAY_TEST_BRANCH}\n\n"
|
|
f"Filtering for these tests:\n"
|
|
f" FILTER_FILE = {FILTER_FILE}\n"
|
|
f" FILTER_TEST = {FILTER_TEST}\n\n")
|
|
|
|
for test_file, test_names in steps.items():
|
|
if FILTER_FILE and FILTER_FILE not in test_file:
|
|
continue
|
|
|
|
test_base = os.path.basename(test_file)
|
|
for test_name in test_names:
|
|
if FILTER_TEST and FILTER_TEST not in test_name:
|
|
continue
|
|
|
|
if not isinstance(test_name, ReleaseTest):
|
|
test_name = ReleaseTest(name=test_name)
|
|
|
|
logging.info(f"Adding test: {test_base}/{test_name}")
|
|
|
|
for ray_wheels in ray_wheels_list:
|
|
step_conf = create_test_step(
|
|
ray_repo=RAY_REPO,
|
|
ray_branch=RAY_BRANCH,
|
|
ray_version=RAY_VERSION,
|
|
ray_wheels=ray_wheels,
|
|
ray_test_repo=RAY_TEST_REPO,
|
|
ray_test_branch=RAY_TEST_BRANCH,
|
|
test_file=test_file,
|
|
test_name=test_name)
|
|
|
|
all_steps.append(step_conf)
|
|
|
|
return all_steps
|
|
|
|
|
|
def alert_pipeline(stats: bool = False):
|
|
step_conf = copy.deepcopy(DEFAULT_STEP_TEMPLATE)
|
|
|
|
cmd = "python release/alert.py"
|
|
if stats:
|
|
cmd += " --stats"
|
|
|
|
step_conf["commands"] = [
|
|
"pip install -q -r release/requirements.txt",
|
|
"pip install -U boto3 botocore",
|
|
cmd,
|
|
]
|
|
step_conf["label"] = f"Send periodic alert (stats_only = {stats})"
|
|
return [step_conf]
|
|
|
|
|
|
if __name__ == "__main__":
|
|
alert = os.environ.get("RELEASE_ALERT", "0")
|
|
|
|
ask_for_config = not bool(int(os.environ.get("AUTOMATIC", "0")))
|
|
|
|
if alert in ["1", "stats"]:
|
|
steps = alert_pipeline(alert == "stats")
|
|
elif ask_for_config:
|
|
steps = ask_configuration()
|
|
else:
|
|
TEST_SUITE = os.environ.get("RELEASE_TEST_SUITE", "nightly")
|
|
PIPELINE_SPEC = SUITES[TEST_SUITE]
|
|
|
|
steps = build_pipeline(PIPELINE_SPEC)
|
|
|
|
yaml.dump({"steps": steps}, sys.stdout)
|