mirror of
https://github.com/wassname/ray.git
synced 2026-06-27 19:32:11 +08:00
Enable direct calls by default (#6367)
* wip * add * timeout fix * const ref * comments * fix * fix * Move actor state into actor handle * comments 2 * enable by default * temp reorder * some fixes * add debug code * tmp * fix * wip * remove dbg * fix compile * fix * fix check * remove non direct tests * Increment ref count before resolving value * rename * fix another bug * tmp * tmp * Fix object pinning * build change * lint * ActorManager * tmp * ActorManager * fix test component failures * Remove old code * Remove unused * fix * fix * fix resources * fix advanced * eric's diff * blacklist * blacklist * cleanup * annotate * disable tests for now * remove * fix * fix * clean up verbosity * fix test * fix concurrency test * Update .travis.yml * Update .travis.yml * Update .travis.yml * split up analysis suite * split up trial runner suite * fix detached direct actors * fix * split up advanced tesT * lint * fix core worker test hang * fix bad check fail which breaks test_cluster.py in tune * fix some minor diffs in test_cluster * less workers * make less stressful * split up test * retry flaky tests * remove old test flags * fixes * lint * Update worker_pool.cc * fix race * fix * fix bugs in node failure handling * fix race condition * fix bugs in node failure handling * fix race condition * nits * fix test * disable heartbeatS * disable heartbeatS * fix * fix * use worker id * fix max fail * debug exit * fix merge, and apply [PATCH] fix concurrency test * [patch] fix core worker test hang * remove NotifyActorCreation, and return worker on completion of actor creation task * remove actor diied callback * Update core_worker.cc * lint * use task manager * fix merge * fix deadlock * wip * merge conflits * fix * better sysexit handling * better sysexit handling * better sysexit handling * check id * better debug * task failed msg * task failed msg * retry failed tasks with delay * retry failed tasks with delay * clip deps * fix * fix core worker tests * fix task manager test * fix all tests * cleanup * set to 0 for direct tests * dont check worker id for ownership rpc * dont check worker id for ownership rpc * debug messages * add comment * remove debug statements * nit * check worker id * fix test * owner * fix tests
This commit is contained in:
Eric Liang
+4
-4
@@ -147,13 +147,13 @@ script:
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- ./ci/suppress_output bazel test --build_tests_only --show_progress_rate_limit=100 --test_output=errors //:all
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# ray serve tests
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- if [ $RAY_CI_SERVE_AFFECTED == "1" ]; then python -c 'import sys;exit(sys.version_info>=(3,5))' || python -m pytest -v --durations=5 --timeout=300 python/ray/experimental/serve/tests; fi
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- if [ $RAY_CI_SERVE_AFFECTED == "1" ]; then python -c 'import sys;exit(sys.version_info>=(3,5))' || ./ci/suppress_output python python/ray/experimental/serve/examples/echo_full.py; fi
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- if [ $RAY_CI_SERVE_AFFECTED == "1" ]; then python -c 'import sys;exit(sys.version_info>=(3,5))' || RAY_FORCE_DIRECT=0 python -m pytest -v --durations=5 --timeout=300 python/ray/experimental/serve/tests; fi
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- if [ $RAY_CI_SERVE_AFFECTED == "1" ]; then python -c 'import sys;exit(sys.version_info>=(3,5))' || RAY_FORCE_DIRECT=0 ./ci/suppress_output python python/ray/experimental/serve/examples/echo_full.py; fi
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# ray tests
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# Python3.5+ only. Otherwise we will get `SyntaxError` regardless of how we set the tester.
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- if [ $RAY_CI_PYTHON_AFFECTED == "1" ]; then python -c 'import sys;exit(sys.version_info>=(3,5))' || python -m pytest -v --durations=5 --timeout=300 python/ray/experimental/test/async_test.py; fi
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- if [ $RAY_CI_PYTHON_AFFECTED == "1" ]; then python -c 'import sys;exit(sys.version_info>=(3,5))' || python -m pytest -v --durations=5 --timeout=300 python/ray/tests/py3_test.py; fi
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- if [ $RAY_CI_PYTHON_AFFECTED == "1" ]; then python -c 'import sys;exit(sys.version_info>=(3,5))' || RAY_FORCE_DIRECT=0 python -m pytest -v --durations=5 --timeout=300 python/ray/experimental/test/async_test.py; fi
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- if [ $RAY_CI_PYTHON_AFFECTED == "1" ]; then python -c 'import sys;exit(sys.version_info>=(3,5))' || RAY_FORCE_DIRECT=0 python -m pytest -v --durations=5 --timeout=300 python/ray/tests/py3_test.py; fi
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# py bazel tests, run using local strategy since PY2 breaks with sandbox
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- ./ci/keep_alive bazel test --spawn_strategy=local --flaky_test_attempts=3 --python_version=$BAZEL_PYTHON_VERSION --nocache_test_results --test_verbose_timeout_warnings --incompatible_allow_python_version_transitions=false --incompatible_py3_is_default=false --progress_report_interval=100 --show_progress_rate_limit=100 --show_timestamps --test_output=errors --test_tag_filters=-jenkins_only python/ray/...
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+104
-104
@@ -1,270 +1,270 @@
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_catalog.py
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/ray/ci/suppress_output python /ray/rllib/tests/test_catalog.py
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_optimizers.py
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/ray/ci/suppress_output python /ray/rllib/tests/test_optimizers.py
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_filters.py
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/ray/ci/suppress_output python /ray/rllib/tests/test_filters.py
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_evaluators.py
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/ray/ci/suppress_output python /ray/rllib/tests/test_evaluators.py
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_eager_support.py
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/ray/ci/suppress_output python /ray/rllib/tests/test_eager_support.py
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env PongDeterministic-v0 \
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--run A3C \
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--stop '{"training_iteration": 1}' \
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--config '{"num_workers": 2}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env Pong-ram-v4 \
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--run A3C \
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--stop '{"training_iteration": 1}' \
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--config '{"num_workers": 2}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env PongDeterministic-v0 \
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--run A2C \
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--stop '{"training_iteration": 1}' \
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--config '{"num_workers": 2}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v1 \
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--run PPO \
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--stop '{"training_iteration": 1}' \
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--config '{"kl_coeff": 1.0, "num_sgd_iter": 10, "lr": 1e-4, "sgd_minibatch_size": 64, "train_batch_size": 2000, "num_workers": 1, "model": {"free_log_std": true}}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v1 \
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--run PPO \
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--stop '{"training_iteration": 1}' \
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--config '{"simple_optimizer": false, "num_sgd_iter": 2, "model": {"use_lstm": true}}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v1 \
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--run PPO \
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--stop '{"training_iteration": 1}' \
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--config '{"simple_optimizer": true, "num_sgd_iter": 2, "model": {"use_lstm": true}}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v1 \
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--run PPO \
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--stop '{"training_iteration": 1}' \
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--config '{"kl_coeff": 1.0, "num_sgd_iter": 10, "lr": 1e-4, "sgd_minibatch_size": 64, "train_batch_size": 2000, "num_workers": 1, "use_gae": false, "batch_mode": "complete_episodes"}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v1 \
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--run PPO \
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--stop '{"training_iteration": 1}' \
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--config '{"remote_worker_envs": true, "remote_env_batch_wait_ms": 99999999, "num_envs_per_worker": 2, "num_workers": 1, "train_batch_size": 100, "sgd_minibatch_size": 50}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v1 \
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--run PPO \
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--stop '{"training_iteration": 2}' \
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--config '{"remote_worker_envs": true, "num_envs_per_worker": 2, "num_workers": 1, "train_batch_size": 100, "sgd_minibatch_size": 50}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env Pendulum-v0 \
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--run APPO \
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--stop '{"training_iteration": 1}' \
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--config '{"num_workers": 2, "num_gpus": 0}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env Pendulum-v0 \
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--run ES \
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--stop '{"training_iteration": 1}' \
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--config '{"stepsize": 0.01, "episodes_per_batch": 20, "train_batch_size": 100, "num_workers": 2}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env Pong-v0 \
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--run ES \
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--stop '{"training_iteration": 1}' \
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--config '{"stepsize": 0.01, "episodes_per_batch": 20, "train_batch_size": 100, "num_workers": 2}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v0 \
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--run A3C \
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--stop '{"training_iteration": 1}' \
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v0 \
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--run DQN \
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--stop '{"training_iteration": 1}' \
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--config '{"lr": 1e-3, "schedule_max_timesteps": 100000, "exploration_fraction": 0.1, "exploration_final_eps": 0.02, "dueling": false, "hiddens": [], "model": {"fcnet_hiddens": [64], "fcnet_activation": "relu"}}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v0 \
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--run DQN \
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--stop '{"training_iteration": 1}' \
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--config '{"num_workers": 2}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v0 \
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--run APEX \
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--stop '{"training_iteration": 1}' \
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--config '{"num_workers": 2, "timesteps_per_iteration": 1000, "num_gpus": 0, "min_iter_time_s": 1}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env FrozenLake-v0 \
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--run DQN \
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--stop '{"training_iteration": 1}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env FrozenLake-v0 \
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--run PPO \
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--stop '{"training_iteration": 1}' \
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--config '{"num_sgd_iter": 10, "sgd_minibatch_size": 64, "train_batch_size": 1000, "num_workers": 1}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env PongDeterministic-v4 \
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--run DQN \
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--stop '{"training_iteration": 1}' \
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--config '{"lr": 1e-4, "schedule_max_timesteps": 2000000, "buffer_size": 10000, "exploration_fraction": 0.1, "exploration_final_eps": 0.01, "sample_batch_size": 4, "learning_starts": 10000, "target_network_update_freq": 1000, "gamma": 0.99, "prioritized_replay": true}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env MontezumaRevenge-v0 \
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--run PPO \
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--stop '{"training_iteration": 1}' \
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--config '{"kl_coeff": 1.0, "num_sgd_iter": 10, "lr": 1e-4, "sgd_minibatch_size": 64, "train_batch_size": 2000, "num_workers": 1, "model": {"dim": 40, "conv_filters": [[16, [8, 8], 4], [32, [4, 4], 2], [512, [5, 5], 1]]}}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v1 \
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--run A3C \
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--stop '{"training_iteration": 1}' \
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--config '{"num_workers": 2, "model": {"use_lstm": true}}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v0 \
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--run DQN \
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--stop '{"training_iteration": 1}' \
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--config '{"num_workers": 2}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v0 \
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--run PG \
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--stop '{"training_iteration": 1}' \
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--config '{"sample_batch_size": 500, "num_workers": 1}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v0 \
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--run PG \
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--stop '{"training_iteration": 1}' \
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--config '{"sample_batch_size": 500, "use_pytorch": true}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v0 \
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--run PG \
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--stop '{"training_iteration": 1}' \
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--config '{"sample_batch_size": 500, "num_workers": 1, "model": {"use_lstm": true, "max_seq_len": 100}}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env CartPole-v0 \
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--run PG \
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--stop '{"training_iteration": 1}' \
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--config '{"sample_batch_size": 500, "num_workers": 1, "num_envs_per_worker": 10}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env Pong-v0 \
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--run PG \
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--stop '{"training_iteration": 1}' \
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--config '{"sample_batch_size": 500, "num_workers": 1}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env FrozenLake-v0 \
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--run PG \
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--stop '{"training_iteration": 1}' \
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--config '{"sample_batch_size": 500, "num_workers": 1}'
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docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
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/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
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/ray/ci/suppress_output /ray/rllib/train.py \
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--env Pendulum-v0 \
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--run DDPG \
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--stop '{"training_iteration": 1}' \
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--config '{"num_workers": 1}'
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|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env CartPole-v0 \
|
||||
--run IMPALA \
|
||||
--stop '{"training_iteration": 1}' \
|
||||
--config '{"num_gpus": 0, "num_workers": 2, "min_iter_time_s": 1}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env CartPole-v0 \
|
||||
--run IMPALA \
|
||||
--stop '{"training_iteration": 1}' \
|
||||
--config '{"num_gpus": 0, "num_workers": 2, "num_aggregation_workers": 2, "min_iter_time_s": 1}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env CartPole-v0 \
|
||||
--run IMPALA \
|
||||
--stop '{"training_iteration": 1}' \
|
||||
--config '{"num_gpus": 0, "num_workers": 2, "min_iter_time_s": 1, "model": {"use_lstm": true}}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env CartPole-v0 \
|
||||
--run IMPALA \
|
||||
--stop '{"training_iteration": 1}' \
|
||||
--config '{"num_gpus": 0, "num_workers": 2, "min_iter_time_s": 1, "num_data_loader_buffers": 2, "replay_buffer_num_slots": 100, "replay_proportion": 1.0}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env CartPole-v0 \
|
||||
--run IMPALA \
|
||||
--stop '{"training_iteration": 1}' \
|
||||
--config '{"num_gpus": 0, "num_workers": 2, "min_iter_time_s": 1, "num_data_loader_buffers": 2, "replay_buffer_num_slots": 100, "replay_proportion": 1.0, "model": {"use_lstm": true}}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env MountainCarContinuous-v0 \
|
||||
--run DDPG \
|
||||
--stop '{"training_iteration": 1}' \
|
||||
--config '{"num_workers": 1}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env MountainCarContinuous-v0 \
|
||||
--run DDPG \
|
||||
--stop '{"training_iteration": 1}' \
|
||||
--config '{"num_workers": 1}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env Pendulum-v0 \
|
||||
--run APEX_DDPG \
|
||||
--ray-num-cpus 8 \
|
||||
@@ -272,7 +272,7 @@ docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
--config '{"num_workers": 2, "optimizer": {"num_replay_buffer_shards": 1}, "learning_starts": 100, "min_iter_time_s": 1}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env Pendulum-v0 \
|
||||
--run APEX_DDPG \
|
||||
--ray-num-cpus 8 \
|
||||
@@ -280,199 +280,199 @@ docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
--config '{"num_workers": 2, "optimizer": {"num_replay_buffer_shards": 1}, "learning_starts": 100, "min_iter_time_s": 1, "batch_mode": "complete_episodes", "parameter_noise": false}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env CartPole-v0 \
|
||||
--run MARWIL \
|
||||
--stop '{"training_iteration": 1}' \
|
||||
--config '{"input": "/ray/rllib/tests/data/cartpole_small", "learning_starts": 0, "input_evaluation": ["wis", "is"], "shuffle_buffer_size": 10}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env CartPole-v0 \
|
||||
--run DQN \
|
||||
--stop '{"training_iteration": 1}' \
|
||||
--config '{"input": "/ray/rllib/tests/data/cartpole_small", "learning_starts": 0, "input_evaluation": ["wis", "is"], "soft_q": true}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_local.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_local.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_reproducibility.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_reproducibility.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_dependency.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_dependency.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_legacy.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_legacy.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_io.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_io.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_checkpoint_restore.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_checkpoint_restore.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_rollout_worker.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_rollout_worker.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_nested_spaces.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_nested_spaces.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_external_env.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_external_env.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_external_multi_agent_env.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_external_multi_agent_env.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/custom_keras_model.py --run=A2C --stop=50
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/custom_keras_model.py --run=A2C --stop=50
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/custom_keras_model.py --run=PPO --stop=50
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/custom_keras_model.py --run=PPO --stop=50
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/custom_keras_model.py --run=DQN --stop=50
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/custom_keras_model.py --run=DQN --stop=50
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/parametric_action_cartpole.py --run=PG --stop=50
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/parametric_action_cartpole.py --run=PG --stop=50
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/parametric_action_cartpole.py --run=PPO --stop=50
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/parametric_action_cartpole.py --run=PPO --stop=50
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/parametric_action_cartpole.py --run=DQN --stop=50
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/parametric_action_cartpole.py --run=DQN --stop=50
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_lstm.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_lstm.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/batch_norm_model.py --num-iters=1 --run=PPO
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/batch_norm_model.py --num-iters=1 --run=PPO
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/batch_norm_model.py --num-iters=1 --run=PG
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/batch_norm_model.py --num-iters=1 --run=PG
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/batch_norm_model.py --num-iters=1 --run=DQN
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/batch_norm_model.py --num-iters=1 --run=DQN
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/batch_norm_model.py --num-iters=1 --run=DDPG
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/batch_norm_model.py --num-iters=1 --run=DDPG
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_multi_agent_env.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_multi_agent_env.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_supported_spaces.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_supported_spaces.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_env_with_subprocess.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_env_with_subprocess.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/tests/test_rollout.sh
|
||||
/ray/ci/suppress_output /ray/rllib/tests/test_rollout.sh
|
||||
|
||||
# Run all single-agent regression tests (3x retry each)
|
||||
for yaml in $(ls $ROOT_DIR/../../rllib/tuned_examples/regression_tests); do
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/run_regression_tests.py \
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/run_regression_tests.py \
|
||||
/ray/rllib/tuned_examples/regression_tests/$yaml
|
||||
done
|
||||
|
||||
# Try a couple times since it's stochastic
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/multiagent_pendulum.py || \
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/multiagent_pendulum.py || \
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/multiagent_pendulum.py || \
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/multiagent_pendulum.py || \
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/multiagent_pendulum.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/multiagent_pendulum.py
|
||||
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/multiagent_cartpole.py --num-iters=2
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/multiagent_cartpole.py --num-iters=2
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/multiagent_two_trainers.py --num-iters=2
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/multiagent_two_trainers.py --num-iters=2
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_avail_actions_qmix.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_avail_actions_qmix.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/cartpole_lstm.py --run=PPO --stop=200
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/cartpole_lstm.py --run=PPO --stop=200
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/cartpole_lstm.py --run=IMPALA --stop=100
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/cartpole_lstm.py --run=IMPALA --stop=100
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/cartpole_lstm.py --stop=200 --use-prev-action-reward
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/cartpole_lstm.py --stop=200 --use-prev-action-reward
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/custom_loss.py --iters=2
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/custom_loss.py --iters=2
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/rollout_worker_custom_workflow.py
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/rollout_worker_custom_workflow.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/eager_execution.py --iters=2
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/eager_execution.py --iters=2
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/custom_tf_policy.py --iters=2
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/custom_tf_policy.py --iters=2
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/custom_torch_policy.py --iters=2
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/custom_torch_policy.py --iters=2
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/rollout_worker_custom_workflow.py
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/rollout_worker_custom_workflow.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/custom_metrics_and_callbacks.py --num-iters=2
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/custom_metrics_and_callbacks.py --num-iters=2
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/contrib/random_agent/random_agent.py
|
||||
/ray/ci/suppress_output python /ray/rllib/contrib/random_agent/random_agent.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/contrib/alpha_zero/examples/train_cartpole.py --training-iteration=1
|
||||
/ray/ci/suppress_output python /ray/rllib/contrib/alpha_zero/examples/train_cartpole.py --training-iteration=1
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/centralized_critic.py --stop=2000
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/centralized_critic.py --stop=2000
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/centralized_critic_2.py --stop=2000
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/centralized_critic_2.py --stop=2000
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/twostep_game.py --stop=2000 --run=contrib/MADDPG
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/twostep_game.py --stop=2000 --run=contrib/MADDPG
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/twostep_game.py --stop=2000 --run=PG
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/twostep_game.py --stop=2000 --run=PG
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/twostep_game.py --stop=2000 --run=QMIX
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/twostep_game.py --stop=2000 --run=QMIX
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/twostep_game.py --stop=2000 --run=APEX_QMIX
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/twostep_game.py --stop=2000 --run=APEX_QMIX
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/autoregressive_action_dist.py --stop=150
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/autoregressive_action_dist.py --stop=150
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env PongDeterministic-v4 \
|
||||
--run A3C \
|
||||
--stop '{"training_iteration": 1}' \
|
||||
--config '{"num_workers": 2, "use_pytorch": true, "sample_async": false, "model": {"use_lstm": false, "grayscale": true, "zero_mean": false, "dim": 84}, "preprocessor_pref": "rllib"}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env CartPole-v1 \
|
||||
--run A3C \
|
||||
--stop '{"training_iteration": 1}' \
|
||||
--config '{"num_workers": 2, "use_pytorch": true, "sample_async": false}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env Pendulum-v0 \
|
||||
--run A3C \
|
||||
--stop '{"training_iteration": 1}' \
|
||||
--config '{"num_workers": 2, "use_pytorch": true, "sample_async": false}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct /ray/rllib/train.py \
|
||||
/ray/ci/suppress_output /ray/rllib/train.py \
|
||||
--env PongDeterministic-v4 \
|
||||
--run IMPALA \
|
||||
--stop='{"timesteps_total": 40000}' \
|
||||
@@ -480,13 +480,13 @@ docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
--config '{"num_workers": 1, "num_gpus": 0, "num_envs_per_worker": 32, "sample_batch_size": 50, "train_batch_size": 50, "learner_queue_size": 1}'
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/agents/impala/vtrace_test.py
|
||||
/ray/ci/suppress_output python /ray/rllib/agents/impala/vtrace_test.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/tests/test_ignore_worker_failure.py
|
||||
/ray/ci/suppress_output python /ray/rllib/tests/test_ignore_worker_failure.py
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/custom_keras_rnn_model.py --run=PPO --stop=50 --env=RepeatAfterMeEnv
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/custom_keras_rnn_model.py --run=PPO --stop=50 --env=RepeatAfterMeEnv
|
||||
|
||||
docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
/ray/ci/suppress_output --force-direct python /ray/rllib/examples/custom_keras_rnn_model.py --run=PPO --stop=50 --env=RepeatInitialEnv
|
||||
/ray/ci/suppress_output python /ray/rllib/examples/custom_keras_rnn_model.py --run=PPO --stop=50 --env=RepeatInitialEnv
|
||||
|
||||
@@ -31,147 +31,147 @@ fi
|
||||
|
||||
echo "Using Docker image" $DOCKER_SHA
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
pytest /ray/python/ray/tune/tests/test_cluster.py
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
pytest /ray/python/ray/tune/tests/test_actor_reuse.py
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
pytest /ray/python/ray/tune/tests/test_tune_restore.py
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/tests/example.py
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
bash -c 'pip install -U tensorflow && python /ray/python/ray/tune/tests/test_logger.py'
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
bash -c 'pip install -U tensorflow==1.15 && python /ray/python/ray/tune/tests/test_logger.py'
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
bash -c 'pip install -U tensorflow==1.14 && python /ray/python/ray/tune/tests/test_logger.py'
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
bash -c 'pip install -U tensorflow==1.12 && python /ray/python/ray/tune/tests/test_logger.py'
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} -e MPLBACKEND=Agg $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} -e MPLBACKEND=Agg $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/tests/tutorial.py
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/pbt_example.py \
|
||||
--smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/hyperband_example.py \
|
||||
--smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/async_hyperband_example.py \
|
||||
--smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/tf_mnist_example.py --smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/lightgbm_example.py
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/xgboost_example.py
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/logging_example.py \
|
||||
--smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/mlflow_example.py
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/bayesopt_example.py \
|
||||
--smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/hyperopt_example.py \
|
||||
--smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} -e SIGOPT_KEY $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} -e SIGOPT_KEY $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/sigopt_example.py \
|
||||
--smoke-test
|
||||
|
||||
# Runs only on Python3
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/nevergrad_example.py \
|
||||
--smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/tune_mnist_keras.py \
|
||||
--smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/mnist_pytorch.py --smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/mnist_pytorch_trainable.py \
|
||||
--smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/genetic_example.py \
|
||||
--smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/skopt_example.py \
|
||||
--smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/tune/examples/pbt_memnn_example.py \
|
||||
--smoke-test
|
||||
|
||||
# uncomment once statsmodels is updated.
|
||||
# $SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
# $SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
# python /ray/python/ray/tune/examples/bohb_example.py \
|
||||
# --smoke-test
|
||||
|
||||
|
||||
######################## SGD TESTS #################################
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python -m pytest /ray/python/ray/experimental/sgd/tests
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/experimental/sgd/examples/train_example.py
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/experimental/sgd/examples/train_example.py --num-replicas=2
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/experimental/sgd/examples/tune_example.py
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/experimental/sgd/examples/tune_example.py --num-replicas=2
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/experimental/sgd/examples/cifar_pytorch_example.py --smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/experimental/sgd/examples/cifar_pytorch_example.py --smoke-test --num-replicas=2
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/experimental/sgd/examples/cifar_pytorch_example.py --smoke-test --tune
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/experimental/sgd/examples/tensorflow_train_example.py
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/experimental/sgd/examples/tensorflow_train_example.py --num-replicas=2
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/experimental/sgd/examples/tensorflow_train_example.py --tune
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/experimental/sgd/examples/cifar_tf_example.py --smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/experimental/sgd/examples/cifar_tf_example.py --num-replicas 2 --smoke-test
|
||||
|
||||
$SUPPRESS_OUTPUT --force-direct docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
$SUPPRESS_OUTPUT docker run --rm --shm-size=${SHM_SIZE} --memory=${MEMORY_SIZE} $DOCKER_SHA \
|
||||
python /ray/python/ray/experimental/sgd/examples/cifar_tf_example.py --num-replicas 2 --smoke-test --augment-data
|
||||
|
||||
@@ -19,12 +19,6 @@ watchdog() {
|
||||
watchdog & 2>/dev/null
|
||||
WATCHDOG_PID=$!
|
||||
|
||||
if [ "$1" == "--force-direct" ]; then
|
||||
echo "Setting RAY_FORCE_DIRECT=1"
|
||||
export RAY_FORCE_DIRECT=1
|
||||
shift
|
||||
fi
|
||||
|
||||
time "$@" >$TMPFILE 2>&1
|
||||
|
||||
CODE=$?
|
||||
|
||||
@@ -17,7 +17,7 @@ def env_integer(key, default):
|
||||
|
||||
|
||||
def direct_call_enabled():
|
||||
return bool(int(os.environ.get("RAY_FORCE_DIRECT", "0")))
|
||||
return bool(int(os.environ.get("RAY_FORCE_DIRECT", "1")))
|
||||
|
||||
|
||||
ID_SIZE = 20
|
||||
|
||||
+11
-36
@@ -151,19 +151,22 @@ def main():
|
||||
|
||||
timeit("1:1 actor calls async", actor_async, 1000)
|
||||
|
||||
a = Actor.options(is_direct_call=True).remote()
|
||||
a = Actor.options(max_concurrency=16).remote()
|
||||
|
||||
def actor_concurrent():
|
||||
ray.get([a.small_value.remote() for _ in range(1000)])
|
||||
|
||||
timeit("1:1 direct actor calls async", actor_concurrent, 1000)
|
||||
timeit("1:1 actor calls concurrent", actor_concurrent, 1000)
|
||||
|
||||
a = Actor.options(is_direct_call=True, max_concurrency=16).remote()
|
||||
n = 5000
|
||||
n_cpu = multiprocessing.cpu_count() // 2
|
||||
actors = [Actor._remote() for _ in range(n_cpu)]
|
||||
client = Client.remote(actors)
|
||||
|
||||
def actor_concurrent():
|
||||
ray.get([a.small_value.remote() for _ in range(1000)])
|
||||
def actor_async_direct():
|
||||
ray.get(client.small_value_batch.remote(n))
|
||||
|
||||
timeit("1:1 direct actor calls concurrent", actor_concurrent, 1000)
|
||||
timeit("1:n actor calls async", actor_async_direct, n * len(actors))
|
||||
|
||||
n_cpu = multiprocessing.cpu_count() // 2
|
||||
a = [Actor.remote() for _ in range(n_cpu)]
|
||||
@@ -177,44 +180,16 @@ def main():
|
||||
|
||||
timeit("n:n actor calls async", actor_multi2, m * n)
|
||||
|
||||
n = 5000
|
||||
n_cpu = multiprocessing.cpu_count() // 2
|
||||
actors = [Actor._remote(is_direct_call=True) for _ in range(n_cpu)]
|
||||
client = Client.remote(actors)
|
||||
|
||||
def actor_async_direct():
|
||||
ray.get(client.small_value_batch.remote(n))
|
||||
|
||||
timeit("1:n direct actor calls async", actor_async_direct, n * len(actors))
|
||||
|
||||
clients = [Client.remote(a) for a in actors]
|
||||
|
||||
def actor_multi2_direct():
|
||||
ray.get([c.small_value_batch.remote(n) for c in clients])
|
||||
|
||||
timeit("n:n direct actor calls async", actor_multi2_direct,
|
||||
n * len(clients))
|
||||
|
||||
n = 1000
|
||||
actors = [Actor._remote(is_direct_call=True) for _ in range(n_cpu)]
|
||||
actors = [Actor._remote() for _ in range(n_cpu)]
|
||||
clients = [Client.remote(a) for a in actors]
|
||||
|
||||
def actor_multi2_direct_arg():
|
||||
ray.get([c.small_value_batch_arg.remote(n) for c in clients])
|
||||
|
||||
timeit("n:n direct actor calls with arg async", actor_multi2_direct_arg,
|
||||
timeit("n:n actor calls with arg async", actor_multi2_direct_arg,
|
||||
n * len(clients))
|
||||
|
||||
n = 1000
|
||||
actors = [Actor._remote(is_direct_call=True) for _ in range(n_cpu)]
|
||||
clients = [Client.remote(a) for a in actors]
|
||||
|
||||
def actor_multi2_direct_arg():
|
||||
ray.get([c.small_value_batch_arg.remote(n) for c in clients])
|
||||
|
||||
timeit("multi client direct actor calls with arg async",
|
||||
actor_multi2_direct_arg, n * len(clients))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
||||
+6
-51
@@ -6,14 +6,6 @@ py_test(
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
py_test(
|
||||
name = "test_actor_direct",
|
||||
size = "medium",
|
||||
srcs = ["test_actor_direct.py", "test_actor.py"],
|
||||
tags = ["exclusive"],
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
py_test(
|
||||
name = "test_actor_resources",
|
||||
size = "medium",
|
||||
@@ -22,19 +14,12 @@ py_test(
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
py_test(
|
||||
name = "test_actor_resources_direct",
|
||||
size = "medium",
|
||||
srcs = ["test_actor_resources_direct.py", "test_actor_resources.py"],
|
||||
tags = ["exclusive"],
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
py_test(
|
||||
name = "test_actor_failures",
|
||||
size = "medium",
|
||||
srcs = ["test_actor_failures.py"],
|
||||
tags = ["exclusive"],
|
||||
# TODO(ekl) enable this once we support actor reconstruction again
|
||||
tags = ["exclusive", "manual"],
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
@@ -46,14 +31,6 @@ py_test(
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
py_test(
|
||||
name = "test_basic_direct",
|
||||
size = "medium",
|
||||
srcs = ["test_basic_direct.py", "test_basic.py"],
|
||||
tags = ["exclusive"],
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
py_test(
|
||||
name = "test_advanced",
|
||||
size = "medium",
|
||||
@@ -126,14 +103,6 @@ py_test(
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
py_test(
|
||||
name = "test_stress_direct",
|
||||
size = "medium",
|
||||
srcs = ["test_stress_direct.py", "test_stress.py"],
|
||||
tags = ["exclusive"],
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
py_test(
|
||||
name = "test_stress_sharded",
|
||||
size = "medium",
|
||||
@@ -142,19 +111,12 @@ py_test(
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
py_test(
|
||||
name = "test_stress_sharded_direct",
|
||||
size = "medium",
|
||||
srcs = ["test_stress_sharded_direct.py", "test_stress_sharded.py"],
|
||||
tags = ["exclusive"],
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
py_test(
|
||||
name = "test_stress_failure",
|
||||
size = "large",
|
||||
srcs = ["test_stress_failure.py"],
|
||||
tags = ["exclusive"],
|
||||
# TODO(ekl) enable again once we support direct call reconstruction
|
||||
tags = ["exclusive", "manual"],
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
@@ -209,14 +171,6 @@ py_test(
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
py_test(
|
||||
name = "test_failure_direct",
|
||||
size = "medium",
|
||||
srcs = ["test_failure_direct.py", "test_failure.py"],
|
||||
tags = ["exclusive"],
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
py_test(
|
||||
name = "test_garbage_collection",
|
||||
size = "small",
|
||||
@@ -276,7 +230,8 @@ py_test(
|
||||
name = "test_monitors",
|
||||
size = "small",
|
||||
srcs = ["test_monitors.py"],
|
||||
tags = ["exclusive"],
|
||||
# TODO(ekl) tasks() and objects() are different in direct call mode.
|
||||
tags = ["exclusive", "manual"],
|
||||
deps = ["//:ray_lib"],
|
||||
)
|
||||
|
||||
|
||||
@@ -1,16 +0,0 @@
|
||||
"""Wrapper script that sets RAY_FORCE_DIRECT."""
|
||||
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import pytest
|
||||
import sys
|
||||
import os
|
||||
|
||||
if __name__ == "__main__":
|
||||
os.environ["RAY_FORCE_DIRECT"] = "1"
|
||||
sys.exit(
|
||||
pytest.main(
|
||||
["-v",
|
||||
os.path.join(os.path.dirname(__file__), "test_actor.py")]))
|
||||
@@ -1,17 +0,0 @@
|
||||
"""Wrapper script that sets RAY_FORCE_DIRECT."""
|
||||
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import pytest
|
||||
import sys
|
||||
import os
|
||||
|
||||
if __name__ == "__main__":
|
||||
os.environ["RAY_FORCE_DIRECT"] = "1"
|
||||
sys.exit(
|
||||
pytest.main([
|
||||
"-v",
|
||||
os.path.join(os.path.dirname(__file__), "test_actor_resources.py")
|
||||
]))
|
||||
@@ -1,16 +0,0 @@
|
||||
"""Wrapper script that sets RAY_FORCE_DIRECT."""
|
||||
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import pytest
|
||||
import sys
|
||||
import os
|
||||
|
||||
if __name__ == "__main__":
|
||||
os.environ["RAY_FORCE_DIRECT"] = "1"
|
||||
sys.exit(
|
||||
pytest.main(
|
||||
["-v",
|
||||
os.path.join(os.path.dirname(__file__), "test_basic.py")]))
|
||||
@@ -1,16 +0,0 @@
|
||||
"""Wrapper script that sets RAY_FORCE_DIRECT."""
|
||||
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import pytest
|
||||
import sys
|
||||
import os
|
||||
|
||||
if __name__ == "__main__":
|
||||
os.environ["RAY_FORCE_DIRECT"] = "1"
|
||||
sys.exit(
|
||||
pytest.main(
|
||||
["-v",
|
||||
os.path.join(os.path.dirname(__file__), "test_failure.py")]))
|
||||
@@ -1,18 +0,0 @@
|
||||
"""Wrapper script that sets RAY_FORCE_DIRECT."""
|
||||
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import pytest
|
||||
import sys
|
||||
import os
|
||||
|
||||
if __name__ == "__main__":
|
||||
os.environ["RAY_FORCE_DIRECT"] = "1"
|
||||
sys.exit(
|
||||
pytest.main([
|
||||
"-v",
|
||||
os.path.join(
|
||||
os.path.dirname(__file__), "test_multinode_failures.py")
|
||||
]))
|
||||
@@ -1,16 +0,0 @@
|
||||
"""Wrapper script that sets RAY_FORCE_DIRECT."""
|
||||
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import pytest
|
||||
import sys
|
||||
import os
|
||||
|
||||
if __name__ == "__main__":
|
||||
os.environ["RAY_FORCE_DIRECT"] = "1"
|
||||
sys.exit(
|
||||
pytest.main(
|
||||
["-v",
|
||||
os.path.join(os.path.dirname(__file__), "test_stress.py")]))
|
||||
@@ -1,17 +0,0 @@
|
||||
"""Wrapper script that sets RAY_FORCE_DIRECT."""
|
||||
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import pytest
|
||||
import sys
|
||||
import os
|
||||
|
||||
if __name__ == "__main__":
|
||||
os.environ["RAY_FORCE_DIRECT"] = "1"
|
||||
sys.exit(
|
||||
pytest.main([
|
||||
"-v",
|
||||
os.path.join(os.path.dirname(__file__), "test_stress_sharded.py")
|
||||
]))
|
||||
@@ -14,6 +14,7 @@ import types
|
||||
|
||||
import ray.cloudpickle as cloudpickle
|
||||
from ray.tune import TuneError
|
||||
from ray.tune.progress_reporter import trial_progress_str
|
||||
from ray.tune.ray_trial_executor import RayTrialExecutor
|
||||
from ray.tune.result import (TIME_THIS_ITER_S, RESULT_DUPLICATE,
|
||||
SHOULD_CHECKPOINT)
|
||||
@@ -380,7 +381,8 @@ class TrialRunner(object):
|
||||
def debug_string(self, delim="\n"):
|
||||
messages = [
|
||||
self._scheduler_alg.debug_string(),
|
||||
self.trial_executor.debug_string()
|
||||
self.trial_executor.debug_string(),
|
||||
trial_progress_str(self.get_trials()),
|
||||
]
|
||||
return delim.join(messages)
|
||||
|
||||
|
||||
@@ -73,4 +73,6 @@ class TestEagerSupport(unittest.TestCase):
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main(verbosity=2)
|
||||
import pytest
|
||||
import sys
|
||||
sys.exit(pytest.main(["-v", __file__]))
|
||||
|
||||
Reference in New Issue
Block a user