mirror of
https://github.com/vale981/ray
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2918 lines
91 KiB
Text
2918 lines
91 KiB
Text
# --------------------------------------------------------------------
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# BAZEL/Buildkite-CI test cases.
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# --------------------------------------------------------------------
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# To add new RLlib tests, first find the correct category of your new test
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# within this file.
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# All new tests - within their category - should be added alphabetically!
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# Do not just add tests to the bottom of the file.
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# Currently we have the following categories:
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# - Learning tests/regression, tagged:
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# -- "learning_tests_[discrete|continuous]": distinguish discrete
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# actions vs continuous actions.
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# -- "fake_gpus": Tests that run using 2 fake GPUs.
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# - Quick agent compilation/tune-train tests, tagged "quick_train".
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# NOTE: These should be obsoleted in favor of "trainers_dir" tests as
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# they cover the same functionaliy.
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# - Folder-bound tests, tagged with the name of the top-level dir:
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# - `env` directory tests.
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# - `evaluation` directory tests.
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# - `execution` directory tests.
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# - `models` directory tests.
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# - `policy` directory tests.
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# - `utils` directory tests.
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# - Trainer ("agents") tests, tagged "trainers_dir".
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# - Tests directory (everything in rllib/tests/...), tagged: "tests_dir" and
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# "tests_dir_[A-Z]"
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# - Examples directory (everything in rllib/examples/...), tagged: "examples" and
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# "examples_[A-Z]"
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# Note: The "examples" and "tests_dir" tags have further sub-tags going by the
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# starting letter of the test name (e.g. "examples_A", or "tests_dir_F") for
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# split-up purposes in buildkite.
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# Note: There is a special directory in examples: "documentation" which contains
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# all code that is linked to from within the RLlib docs. This code is tested
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# separately via the "documentation" tag.
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# Additional tags are:
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# - "team:ml": Indicating that all tests in this file are the responsibility of
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# the ML Team.
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# - "needs_gpu": Indicating that a test needs to have a GPU in order to run.
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# - "gpu": Indicating that a test may (but doesn't have to) be run in the GPU
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# pipeline, defined in .buildkite/pipeline.gpu.yaml.
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# - "multi-gpu": Indicating that a test will definitely be run in the Large GPU
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# pipeline, defined in .buildkite/pipeline.gpu.large.yaml.
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# - "no_gpu": Indicating that a test should not be run in the GPU pipeline due
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# to certain incompatibilities.
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# - "no_tf_eager_tracing": Exclude this test from tf-eager tracing tests.
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# - "torch_only": Only run this test case with framework=torch.
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# Our .buildkite/pipeline.yml and .buildkite/pipeline.gpu.yml files execute all
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# these tests in n different jobs.
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# --------------------------------------------------------------------
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# Agents learning regression tests.
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#
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# Tag: learning_tests
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#
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# This will test all yaml files (via `rllib train`)
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# inside rllib/tuned_examples/[algo-name] for actual learning success.
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# --------------------------------------------------------------------
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# A2C/A3C
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py_test(
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name = "learning_tests_cartpole_a2c",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/a3c/cartpole-a2c.yaml"],
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args = ["--yaml-dir=tuned_examples/a3c"]
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)
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py_test(
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name = "learning_tests_cartpole_a2c_fake_gpus",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete", "fake_gpus"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/a3c/cartpole-a2c-fake-gpus.yaml"],
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args = ["--yaml-dir=tuned_examples/a3c"]
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)
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py_test(
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name = "learning_tests_cartpole_a3c",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/a3c/cartpole-a3c.yaml"],
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args = ["--yaml-dir=tuned_examples/a3c"]
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)
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# AlphaStar
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py_test(
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name = "learning_tests_cartpole_alpha_star",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/alpha_star/multi-agent-cartpole-alpha-star.yaml"],
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args = ["--yaml-dir=tuned_examples/alpha_star", "--num-cpus=20"]
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)
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# APEX-DQN
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py_test(
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name = "learning_tests_cartpole_apex",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = [
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"tuned_examples/dqn/cartpole-apex.yaml",
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],
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args = ["--yaml-dir=tuned_examples/dqn", "--num-cpus=6"]
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)
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# Once APEX supports multi-GPU.
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# py_test(
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# name = "learning_cartpole_apex_fake_gpus",
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# main = "tests/run_regression_tests.py",
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# tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete", "fake_gpus"],
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# size = "large",
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# srcs = ["tests/run_regression_tests.py"],
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# data = ["tuned_examples/dqn/cartpole-apex-fake-gpus.yaml"],
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# args = ["--yaml-dir=tuned_examples/dqn"]
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# )
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# APPO
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py_test(
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name = "learning_tests_cartpole_appo_no_vtrace",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/ppo/cartpole-appo.yaml"],
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args = ["--yaml-dir=tuned_examples/ppo"]
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)
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py_test(
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name = "learning_tests_cartpole_appo_vtrace",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/ppo/cartpole-appo-vtrace.yaml"],
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args = ["--yaml-dir=tuned_examples/ppo"]
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)
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py_test(
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name = "learning_tests_cartpole_separate_losses_appo",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "tf_only", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = [
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"tuned_examples/ppo/cartpole-appo-vtrace-separate-losses.yaml"
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],
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args = ["--yaml-dir=tuned_examples/ppo"]
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)
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py_test(
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name = "learning_tests_frozenlake_appo",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/ppo/frozenlake-appo-vtrace.yaml"],
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args = ["--yaml-dir=tuned_examples/ppo"]
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)
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py_test(
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name = "learning_tests_cartpole_appo_fake_gpus",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete", "fake_gpus"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/ppo/cartpole-appo-vtrace-fake-gpus.yaml"],
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args = ["--yaml-dir=tuned_examples/ppo"]
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)
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# ARS
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py_test(
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name = "learning_tests_cartpole_ars",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/ars/cartpole-ars.yaml"],
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args = ["--yaml-dir=tuned_examples/ars"]
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)
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# CQL
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py_test(
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name = "learning_tests_pendulum_cql",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_pendulum", "learning_tests_continuous"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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# Include the zipped json data file as well.
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data = [
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"tuned_examples/cql/pendulum-cql.yaml",
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"tests/data/pendulum/enormous.zip",
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],
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args = ["--yaml-dir=tuned_examples/cql"]
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)
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# DDPG
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py_test(
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name = "learning_tests_pendulum_ddpg",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_pendulum", "learning_tests_continuous"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = glob(["tuned_examples/ddpg/pendulum-ddpg.yaml"]),
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args = ["--yaml-dir=tuned_examples/ddpg"]
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)
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py_test(
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name = "learning_tests_pendulum_ddpg_tf2",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests_continuous_tf2_eager_off_policy"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = glob(["tuned_examples/ddpg/pendulum-ddpg.yaml"]),
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args = ["--yaml-dir=tuned_examples/ddpg", "--override-mean-reward=-750.0"]
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)
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py_test(
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name = "learning_tests_pendulum_ddpg_fake_gpus",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_pendulum", "learning_tests_continuous", "fake_gpus"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/ddpg/pendulum-ddpg-fake-gpus.yaml"],
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args = ["--yaml-dir=tuned_examples/ddpg"]
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)
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# DDPPO
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py_test(
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name = "learning_tests_cartpole_ddppo",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "torch_only", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = glob(["tuned_examples/ppo/cartpole-ddppo.yaml"]),
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args = ["--yaml-dir=tuned_examples/ppo"]
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)
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# DQN
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py_test(
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name = "learning_tests_cartpole_dqn",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/dqn/cartpole-dqn.yaml"],
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args = ["--yaml-dir=tuned_examples/dqn"]
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)
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py_test(
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name = "learning_tests_cartpole_dqn_softq",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/dqn/cartpole-dqn-softq.yaml"],
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args = ["--yaml-dir=tuned_examples/dqn"]
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)
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# Does not work with tf-eager tracing due to Exploration's postprocessing
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# method injecting a tensor into a new graph. Revisit when tf-eager tracing
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# is better supported.
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py_test(
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name = "learning_tests_cartpole_dqn_param_noise",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete", "no_tf_eager_tracing"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/dqn/cartpole-dqn-param-noise.yaml"],
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args = ["--yaml-dir=tuned_examples/dqn"]
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)
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py_test(
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name = "learning_tests_cartpole_dqn_fake_gpus",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete", "fake_gpus"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/dqn/cartpole-dqn-fake-gpus.yaml"],
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args = ["--yaml-dir=tuned_examples/dqn"]
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)
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# Simple-Q
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py_test(
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name = "learning_tests_cartpole_simpleq",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = [
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"tuned_examples/dqn/cartpole-simpleq.yaml",
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],
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args = ["--yaml-dir=tuned_examples/dqn"]
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)
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py_test(
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name = "learning_tests_cartpole_simpleq_fake_gpus",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete", "fake_gpus"],
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size = "medium",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/dqn/cartpole-simpleq-fake-gpus.yaml"],
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args = ["--yaml-dir=tuned_examples/dqn"]
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)
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# ES
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py_test(
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name = "learning_tests_cartpole_es",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/es/cartpole-es.yaml"],
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args = ["--yaml-dir=tuned_examples/es"]
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)
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# IMPALA
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py_test(
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name = "learning_tests_cartpole_impala",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/impala/cartpole-impala.yaml"],
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args = ["--yaml-dir=tuned_examples/impala"]
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)
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py_test(
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name = "learning_tests_cartpole_impala_fake_gpus",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete", "fake_gpus"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/impala/cartpole-impala-fake-gpus.yaml"],
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args = ["--yaml-dir=tuned_examples/impala"]
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)
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# Working, but takes a long time to learn (>15min).
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# Removed due to Higher API conflicts with Pytorch-Import tests
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## MB-MPO
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#py_test(
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# name = "learning_tests_pendulum_mbmpo",
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# main = "tests/run_regression_tests.py",
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# tags = ["team:ml", "torch_only", "learning_tests", "learning_tests_pendulum", "learning_tests_continuous"],
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# size = "large",
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# srcs = ["tests/run_regression_tests.py"],
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# data = ["tuned_examples/mbmpo/pendulum-mbmpo.yaml"],
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# args = ["--yaml-dir=tuned_examples/mbmpo"]
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#)
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# PG
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py_test(
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name = "learning_tests_cartpole_pg",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/pg/cartpole-pg.yaml"],
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args = ["--yaml-dir=tuned_examples/pg"]
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)
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py_test(
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name = "learning_tests_cartpole_pg_fake_gpus",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete", "fake_gpus"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/pg/cartpole-pg-fake-gpus.yaml"],
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args = ["--yaml-dir=tuned_examples/pg"]
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)
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# PPO
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py_test(
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name = "learning_tests_cartpole_ppo",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/ppo/cartpole-ppo.yaml"],
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args = ["--yaml-dir=tuned_examples/ppo"]
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)
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py_test(
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name = "learning_tests_pendulum_ppo",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_pendulum", "learning_tests_continuous"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/ppo/pendulum-ppo.yaml"],
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args = ["--yaml-dir=tuned_examples/ppo"]
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)
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py_test(
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name = "learning_tests_transformed_actions_pendulum_ppo",
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main = "tests/run_regression_tests.py",
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tags = ["team:ml", "learning_tests", "learning_tests_pendulum", "learning_tests_continuous"],
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size = "large",
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srcs = ["tests/run_regression_tests.py"],
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data = ["tuned_examples/ppo/pendulum-transformed-actions-ppo.yaml"],
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args = ["--yaml-dir=tuned_examples/ppo"]
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)
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py_test(
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name = "learning_tests_repeat_after_me_ppo",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests", "learning_tests_discrete"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/ppo/repeatafterme-ppo-lstm.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/ppo"]
|
|
)
|
|
|
|
py_test(
|
|
name = "learning_tests_cartpole_ppo_fake_gpus",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete", "fake_gpus"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/ppo/cartpole-ppo-fake-gpus.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/ppo"]
|
|
)
|
|
|
|
# QMIX
|
|
py_test(
|
|
name = "learning_tests_two_step_game_qmix",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests", "learning_tests_discrete"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/qmix/two-step-game-qmix.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/qmix", "--framework=torch"]
|
|
)
|
|
|
|
py_test(
|
|
name = "learning_tests_two_step_game_qmix_vdn_mixer",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests", "learning_tests_discrete"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/qmix/two-step-game-qmix-vdn-mixer.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/qmix", "--framework=torch"]
|
|
)
|
|
|
|
py_test(
|
|
name = "learning_tests_two_step_game_qmix_no_mixer",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests", "learning_tests_discrete"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/qmix/two-step-game-qmix-no-mixer.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/qmix", "--framework=torch"]
|
|
)
|
|
|
|
# R2D2
|
|
py_test(
|
|
name = "learning_tests_stateless_cartpole_r2d2",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/dqn/stateless-cartpole-r2d2.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/dqn"]
|
|
)
|
|
|
|
py_test(
|
|
name = "learning_tests_stateless_cartpole_r2d2_fake_gpus",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "fake_gpus"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/dqn/stateless-cartpole-r2d2-fake-gpus.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/dqn"]
|
|
)
|
|
|
|
# SAC
|
|
py_test(
|
|
name = "learning_tests_cartpole_sac",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_discrete"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/sac/cartpole-sac.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/sac"]
|
|
)
|
|
|
|
py_test(
|
|
name = "learning_tests_cartpole_continuous_pybullet_sac",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests", "learning_tests_cartpole", "learning_tests_continuous"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/sac/cartpole-continuous-pybullet-sac.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/sac"]
|
|
)
|
|
|
|
py_test(
|
|
name = "learning_tests_pendulum_sac",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests", "learning_tests_pendulum", "learning_tests_continuous"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/sac/pendulum-sac.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/sac"]
|
|
)
|
|
|
|
py_test(
|
|
name = "learning_tests_transformed_actions_pendulum_sac",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests", "learning_tests_pendulum", "learning_tests_continuous"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/sac/pendulum-transformed-actions-sac.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/sac"]
|
|
)
|
|
|
|
py_test(
|
|
name = "learning_tests_pendulum_sac_tf2",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests_continuous_tf2_eager_off_policy"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/sac/pendulum-sac.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/sac", "--override-mean-reward=-900.0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "learning_tests_transformed_actions_pendulum_sac_tf2",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests_continuous_tf2_eager_off_policy"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/sac/pendulum-transformed-actions-sac.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/sac" ,"--override-mean-reward=-850.0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "learning_tests_pendulum_sac_fake_gpus",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests", "learning_tests_pendulum", "learning_tests_continuous", "fake_gpus"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/sac/pendulum-sac-fake-gpus.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/sac"]
|
|
)
|
|
|
|
# SlateQ
|
|
py_test(
|
|
name = "learning_tests_interest_evolution_10_candidates_recsim_env_slateq",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests", "learning_tests_discrete", "tf2_only"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/slateq/interest-evolution-10-candidates-recsim-env-slateq.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/slateq"]
|
|
)
|
|
|
|
# TD3
|
|
py_test(
|
|
name = "learning_tests_pendulum_td3",
|
|
main = "tests/run_regression_tests.py",
|
|
tags = ["team:ml", "learning_tests", "learning_tests_pendulum", "learning_tests_continuous"],
|
|
size = "large",
|
|
srcs = ["tests/run_regression_tests.py"],
|
|
data = ["tuned_examples/ddpg/pendulum-td3.yaml"],
|
|
args = ["--yaml-dir=tuned_examples/ddpg"]
|
|
)
|
|
|
|
|
|
# --------------------------------------------------------------------
|
|
# Agents (Compilation, Losses, simple agent functionality tests)
|
|
# rllib/agents/
|
|
#
|
|
# Tag: trainers_dir
|
|
# --------------------------------------------------------------------
|
|
|
|
# Generic (all Trainers)
|
|
py_test(
|
|
name = "test_callbacks",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "medium",
|
|
srcs = ["agents/tests/test_callbacks.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_trainer",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
srcs = ["agents/tests/test_trainer.py"]
|
|
)
|
|
|
|
# A2/3CTrainer
|
|
py_test(
|
|
name = "test_a2c",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
srcs = ["agents/a3c/tests/test_a2c.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_a3c",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
srcs = ["agents/a3c/tests/test_a3c.py"]
|
|
)
|
|
|
|
# AlphaStar
|
|
py_test(
|
|
name = "test_alpha_star",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
srcs = ["agents/alpha_star/tests/test_alpha_star.py"]
|
|
)
|
|
|
|
# APEXTrainer (DQN)
|
|
py_test(
|
|
name = "test_apex_dqn",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
srcs = ["agents/dqn/tests/test_apex_dqn.py"]
|
|
)
|
|
|
|
# APEXDDPGTrainer
|
|
py_test(
|
|
name = "test_apex_ddpg",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "medium",
|
|
srcs = ["agents/ddpg/tests/test_apex_ddpg.py"]
|
|
)
|
|
|
|
# ARS
|
|
py_test(
|
|
name = "test_ars",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "medium",
|
|
srcs = ["agents/ars/tests/test_ars.py"]
|
|
)
|
|
|
|
# Bandits
|
|
py_test(
|
|
name = "test_bandits",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "medium",
|
|
srcs = ["agents/bandit/tests/test_bandits.py"],
|
|
)
|
|
|
|
# CQLTrainer
|
|
py_test(
|
|
name = "test_cql",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "medium",
|
|
srcs = ["agents/cql/tests/test_cql.py"]
|
|
)
|
|
|
|
# DDPGTrainer
|
|
py_test(
|
|
name = "test_ddpg",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
srcs = ["agents/ddpg/tests/test_ddpg.py"]
|
|
)
|
|
|
|
# DQNTrainer
|
|
py_test(
|
|
name = "test_dqn",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
srcs = ["agents/dqn/tests/test_dqn.py"]
|
|
)
|
|
|
|
# Dreamer
|
|
py_test(
|
|
name = "test_dreamer",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "small",
|
|
srcs = ["agents/dreamer/tests/test_dreamer.py"]
|
|
)
|
|
|
|
# ES
|
|
py_test(
|
|
name = "test_es",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "medium",
|
|
srcs = ["agents/es/tests/test_es.py"]
|
|
)
|
|
|
|
# IMPALA
|
|
py_test(
|
|
name = "test_impala",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
srcs = ["agents/impala/tests/test_impala.py"]
|
|
)
|
|
py_test(
|
|
name = "test_vtrace",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "small",
|
|
srcs = ["agents/impala/tests/test_vtrace.py"]
|
|
)
|
|
|
|
# MARWILTrainer
|
|
py_test(
|
|
name = "test_marwil",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
# Include the json data file.
|
|
data = ["tests/data/cartpole/large.json"],
|
|
srcs = ["agents/marwil/tests/test_marwil.py"]
|
|
)
|
|
|
|
# BCTrainer (sub-type of MARWIL)
|
|
py_test(
|
|
name = "test_bc",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
# Include the json data file.
|
|
data = ["tests/data/cartpole/large.json"],
|
|
srcs = ["agents/marwil/tests/test_bc.py"]
|
|
)
|
|
|
|
# MAMLTrainer
|
|
py_test(
|
|
name = "test_maml",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "medium",
|
|
srcs = ["agents/maml/tests/test_maml.py"]
|
|
)
|
|
|
|
# MBMPOTrainer
|
|
py_test(
|
|
name = "test_mbmpo",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "medium",
|
|
srcs = ["agents/mbmpo/tests/test_mbmpo.py"]
|
|
)
|
|
|
|
# PGTrainer
|
|
py_test(
|
|
name = "test_pg",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
srcs = ["agents/pg/tests/test_pg.py"]
|
|
)
|
|
|
|
# PPOTrainer
|
|
py_test(
|
|
name = "test_ppo",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
srcs = ["agents/ppo/tests/test_ppo.py"]
|
|
)
|
|
|
|
# PPO: DDPPO
|
|
py_test(
|
|
name = "test_ddppo",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "medium",
|
|
srcs = ["agents/ppo/tests/test_ddppo.py"]
|
|
)
|
|
|
|
# PPO: APPO
|
|
py_test(
|
|
name = "test_appo",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
srcs = ["agents/ppo/tests/test_appo.py"]
|
|
)
|
|
|
|
# QMixTrainer
|
|
py_test(
|
|
name = "test_qmix",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "medium",
|
|
srcs = ["agents/qmix/tests/test_qmix.py"]
|
|
)
|
|
|
|
# R2D2Trainer
|
|
py_test(
|
|
name = "test_r2d2",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
srcs = ["agents/dqn/tests/test_r2d2.py"]
|
|
)
|
|
|
|
# RNNSACTrainer
|
|
py_test(
|
|
name = "test_rnnsac",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "medium",
|
|
srcs = ["agents/sac/tests/test_rnnsac.py"]
|
|
)
|
|
|
|
# SACTrainer
|
|
py_test(
|
|
name = "test_sac",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
srcs = ["agents/sac/tests/test_sac.py"]
|
|
)
|
|
|
|
# SimpleQTrainer
|
|
py_test(
|
|
name = "test_simple_q",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "medium",
|
|
srcs = ["agents/dqn/tests/test_simple_q.py"]
|
|
)
|
|
|
|
# SlateQTrainer
|
|
py_test(
|
|
name = "test_slateq",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "medium",
|
|
srcs = ["agents/slateq/tests/test_slateq.py"]
|
|
)
|
|
|
|
# TD3Trainer
|
|
py_test(
|
|
name = "test_td3",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
size = "large",
|
|
srcs = ["agents/ddpg/tests/test_td3.py"]
|
|
)
|
|
|
|
# --------------------------------------------------------------------
|
|
# contrib Agents
|
|
# --------------------------------------------------------------------
|
|
|
|
py_test(
|
|
name = "random_agent",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
main = "contrib/random_agent/random_agent.py",
|
|
size = "small",
|
|
srcs = ["contrib/random_agent/random_agent.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "alpha_zero_cartpole",
|
|
tags = ["team:ml", "trainers_dir"],
|
|
main = "contrib/alpha_zero/examples/train_cartpole.py",
|
|
size = "large",
|
|
srcs = ["contrib/alpha_zero/examples/train_cartpole.py"],
|
|
args = ["--training-iteration=1", "--num-workers=2", "--ray-num-cpus=3"]
|
|
)
|
|
|
|
|
|
# --------------------------------------------------------------------
|
|
# Agents (quick training test iterations via `rllib train`)
|
|
#
|
|
# Tag: quick_train
|
|
#
|
|
# These are not(!) learning tests, we only test here compilation and
|
|
# support for certain envs, spaces, setups.
|
|
# Should all be very short tests with label: "quick_train".
|
|
# --------------------------------------------------------------------
|
|
|
|
# A2C/A3C
|
|
|
|
py_test(
|
|
name = "test_a3c_torch_pong_deterministic_v4",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "PongDeterministic-v4",
|
|
"--run", "A3C",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"torch\", \"num_workers\": 2, \"sample_async\": false, \"model\": {\"use_lstm\": false, \"grayscale\": true, \"zero_mean\": false, \"dim\": 84}, \"preprocessor_pref\": \"rllib\"}'",
|
|
"--ray-num-cpus", "4"
|
|
]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_a3c_tf_pong_ram_v4",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "Pong-ram-v4",
|
|
"--run", "A3C",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"num_workers\": 2}'",
|
|
"--ray-num-cpus", "4"
|
|
]
|
|
)
|
|
|
|
# DDPG/APEX-DDPG/TD3
|
|
|
|
py_test(
|
|
name = "test_ddpg_mountaincar_continuous_v0_num_workers_0",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "MountainCarContinuous-v0",
|
|
"--run", "DDPG",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"num_workers\": 0}'"
|
|
]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_ddpg_mountaincar_continuous_v0_num_workers_1",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "MountainCarContinuous-v0",
|
|
"--run", "DDPG",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"num_workers\": 1}'"
|
|
]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_apex_ddpg_pendulum_v0_complete_episode_batches",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "Pendulum-v1",
|
|
"--run", "APEX_DDPG",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"num_workers\": 2, \"optimizer\": {\"num_replay_buffer_shards\": 1}, \"learning_starts\": 100, \"min_time_s_per_reporting\": 1, \"batch_mode\": \"complete_episodes\"}'",
|
|
"--ray-num-cpus", "4",
|
|
]
|
|
)
|
|
|
|
# DQN/APEX
|
|
|
|
py_test(
|
|
name = "test_dqn_frozenlake_v1",
|
|
main = "train.py", srcs = ["train.py"],
|
|
size = "small",
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "FrozenLake-v1",
|
|
"--run", "DQN",
|
|
"--config", "'{\"framework\": \"tf\"}'",
|
|
"--stop", "'{\"training_iteration\": 1}'"
|
|
]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_dqn_cartpole_v0_no_dueling",
|
|
main = "train.py", srcs = ["train.py"],
|
|
size = "small",
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "CartPole-v0",
|
|
"--run", "DQN",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"lr\": 1e-3, \"exploration_config\": {\"epsilon_timesteps\": 10000, \"final_epsilon\": 0.02}, \"dueling\": false, \"hiddens\": [], \"model\": {\"fcnet_hiddens\": [64], \"fcnet_activation\": \"relu\"}}'"
|
|
]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_dqn_cartpole_v0",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "CartPole-v0",
|
|
"--run", "DQN",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"num_workers\": 2}'",
|
|
"--ray-num-cpus", "4"
|
|
]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_dqn_cartpole_v0_with_offline_input_and_softq",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train", "external_files"],
|
|
size = "small",
|
|
# Include the json data file.
|
|
data = ["tests/data/cartpole/small.json"],
|
|
args = [
|
|
"--env", "CartPole-v0",
|
|
"--run", "DQN",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"input\": \"tests/data/cartpole\", \"learning_starts\": 0, \"input_evaluation\": [\"wis\", \"is\"], \"exploration_config\": {\"type\": \"SoftQ\"}}'"
|
|
]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_dqn_pong_deterministic_v4",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "PongDeterministic-v4",
|
|
"--run", "DQN",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"lr\": 1e-4, \"exploration_config\": {\"epsilon_timesteps\": 200000, \"final_epsilon\": 0.01}, \"buffer_size\": 10000, \"rollout_fragment_length\": 4, \"learning_starts\": 10000, \"target_network_update_freq\": 1000, \"gamma\": 0.99, \"prioritized_replay\": true}'"
|
|
]
|
|
)
|
|
|
|
# IMPALA
|
|
|
|
py_test(
|
|
name = "test_impala_buffers_2",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "CartPole-v0",
|
|
"--run", "IMPALA",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"num_gpus\": 0, \"num_workers\": 2, \"min_time_s_per_reporting\": 1, \"num_multi_gpu_tower_stacks\": 2, \"replay_buffer_num_slots\": 100, \"replay_proportion\": 1.0}'",
|
|
"--ray-num-cpus", "4",
|
|
]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_impala_cartpole_v0_buffers_2_lstm",
|
|
main = "train.py",
|
|
srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "CartPole-v0",
|
|
"--run", "IMPALA",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"num_gpus\": 0, \"num_workers\": 2, \"min_time_s_per_reporting\": 1, \"num_multi_gpu_tower_stacks\": 2, \"replay_buffer_num_slots\": 100, \"replay_proportion\": 1.0, \"model\": {\"use_lstm\": true}}'",
|
|
"--ray-num-cpus", "4",
|
|
]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_impala_pong_deterministic_v4_40k_ts_1G_obj_store",
|
|
main = "train.py",
|
|
srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
size = "medium",
|
|
args = [
|
|
"--env", "PongDeterministic-v4",
|
|
"--run", "IMPALA",
|
|
"--stop", "'{\"timesteps_total\": 30000}'",
|
|
"--ray-object-store-memory=1000000000",
|
|
"--config", "'{\"framework\": \"tf\", \"num_workers\": 1, \"num_gpus\": 0, \"num_envs_per_worker\": 32, \"rollout_fragment_length\": 50, \"train_batch_size\": 50, \"learner_queue_size\": 1}'"
|
|
]
|
|
)
|
|
|
|
# PG
|
|
|
|
py_test(
|
|
name = "test_pg_tf_cartpole_v0_lstm",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "CartPole-v0",
|
|
"--run", "PG",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"rollout_fragment_length\": 500, \"num_workers\": 1, \"model\": {\"use_lstm\": true, \"max_seq_len\": 100}}'"
|
|
]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_pg_tf_cartpole_v0_multi_envs_per_worker",
|
|
main = "train.py", srcs = ["train.py"],
|
|
size = "small",
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "CartPole-v0",
|
|
"--run", "PG",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"rollout_fragment_length\": 500, \"num_workers\": 1, \"num_envs_per_worker\": 10}'"
|
|
]
|
|
)
|
|
|
|
|
|
py_test(
|
|
name = "test_pg_tf_pong_v0",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "Pong-v0",
|
|
"--run", "PG",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"rollout_fragment_length\": 500, \"num_workers\": 1}'"
|
|
]
|
|
)
|
|
|
|
# PPO/APPO
|
|
|
|
py_test(
|
|
name = "test_ppo_tf_cartpole_v1_complete_episode_batches",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "CartPole-v1",
|
|
"--run", "PPO",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"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\"}'"
|
|
]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_ppo_tf_cartpole_v1_remote_worker_envs",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "CartPole-v1",
|
|
"--run", "PPO",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"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}'"
|
|
]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_ppo_tf_cartpole_v1_remote_worker_envs_b",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "CartPole-v1",
|
|
"--run", "PPO",
|
|
"--stop", "'{\"training_iteration\": 2}'",
|
|
"--config", "'{\"framework\": \"tf\", \"remote_worker_envs\": true, \"num_envs_per_worker\": 2, \"num_workers\": 1, \"train_batch_size\": 100, \"sgd_minibatch_size\": 50}'"
|
|
]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_appo_tf_pendulum_v1_no_gpus",
|
|
main = "train.py", srcs = ["train.py"],
|
|
tags = ["team:ml", "quick_train"],
|
|
args = [
|
|
"--env", "Pendulum-v1",
|
|
"--run", "APPO",
|
|
"--stop", "'{\"training_iteration\": 1}'",
|
|
"--config", "'{\"framework\": \"tf\", \"num_workers\": 2, \"num_gpus\": 0}'",
|
|
"--ray-num-cpus", "4"
|
|
]
|
|
)
|
|
|
|
# --------------------------------------------------------------------
|
|
# Env tests
|
|
# rllib/env/
|
|
#
|
|
# Tag: env
|
|
# --------------------------------------------------------------------
|
|
|
|
sh_test(
|
|
name = "env/tests/test_local_inference_cartpole",
|
|
tags = ["team:ml", "env"],
|
|
size = "medium",
|
|
srcs = ["env/tests/test_policy_client_server_setup.sh"],
|
|
args = ["local", "cartpole"],
|
|
data = glob(["examples/serving/*.py"]),
|
|
)
|
|
|
|
sh_test(
|
|
name = "env/tests/test_remote_inference_cartpole",
|
|
tags = ["team:ml", "env"],
|
|
size = "medium",
|
|
srcs = ["env/tests/test_policy_client_server_setup.sh"],
|
|
args = ["remote", "cartpole"],
|
|
data = glob(["examples/serving/*.py"]),
|
|
)
|
|
|
|
sh_test(
|
|
name = "env/tests/test_local_inference_cartpole_w_2_concurrent_episodes",
|
|
tags = ["team:ml", "env"],
|
|
size = "medium",
|
|
srcs = ["env/tests/test_policy_client_server_setup.sh"],
|
|
args = ["local", "cartpole-dummy-2-episodes"],
|
|
data = glob(["examples/serving/*.py"]),
|
|
)
|
|
|
|
sh_test(
|
|
name = "env/tests/test_remote_inference_cartpole_w_2_concurrent_episodes",
|
|
tags = ["team:ml", "env"],
|
|
size = "medium",
|
|
srcs = ["env/tests/test_policy_client_server_setup.sh"],
|
|
args = ["remote", "cartpole-dummy-2-episodes"],
|
|
data = glob(["examples/serving/*.py"]),
|
|
)
|
|
|
|
sh_test(
|
|
name = "env/tests/test_local_inference_unity3d",
|
|
tags = ["team:ml", "env"],
|
|
size = "medium",
|
|
srcs = ["env/tests/test_policy_client_server_setup.sh"],
|
|
args = ["local", "unity3d"],
|
|
data = glob(["examples/serving/*.py"]),
|
|
)
|
|
|
|
sh_test(
|
|
name = "env/tests/test_remote_inference_unity3d",
|
|
tags = ["team:ml", "env"],
|
|
size = "medium",
|
|
srcs = ["env/tests/test_policy_client_server_setup.sh"],
|
|
args = ["remote", "unity3d"],
|
|
data = glob(["examples/serving/*.py"]),
|
|
)
|
|
|
|
py_test(
|
|
name = "env/tests/test_record_env_wrapper",
|
|
tags = ["team:ml", "env"],
|
|
size = "small",
|
|
srcs = ["env/tests/test_record_env_wrapper.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "env/tests/test_remote_worker_envs",
|
|
tags = ["team:ml", "env"],
|
|
size = "medium",
|
|
srcs = ["env/tests/test_remote_worker_envs.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "env/wrappers/tests/test_unity3d_env",
|
|
tags = ["team:ml", "env"],
|
|
size = "small",
|
|
srcs = ["env/wrappers/tests/test_unity3d_env.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "env/wrappers/tests/test_recsim_wrapper",
|
|
tags = ["team:ml", "env"],
|
|
size = "small",
|
|
srcs = ["env/wrappers/tests/test_recsim_wrapper.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "env/wrappers/tests/test_exception_wrapper",
|
|
tags = ["team:ml", "env"],
|
|
size = "small",
|
|
srcs = ["env/wrappers/tests/test_exception_wrapper.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "env/wrappers/tests/test_group_agents_wrapper",
|
|
tags = ["team:ml", "env"],
|
|
size = "small",
|
|
srcs = ["env/wrappers/tests/test_group_agents_wrapper.py"]
|
|
)
|
|
|
|
# --------------------------------------------------------------------
|
|
# Evaluation components
|
|
# rllib/evaluation/
|
|
#
|
|
# Tag: evaluation
|
|
# --------------------------------------------------------------------
|
|
|
|
py_test(
|
|
name = "evaluation/tests/test_postprocessing",
|
|
tags = ["team:ml", "evaluation"],
|
|
size = "small",
|
|
srcs = ["evaluation/tests/test_postprocessing.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "evaluation/tests/test_rollout_worker",
|
|
tags = ["team:ml", "evaluation"],
|
|
size = "medium",
|
|
srcs = ["evaluation/tests/test_rollout_worker.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "evaluation/tests/test_trajectory_view_api",
|
|
tags = ["team:ml", "evaluation"],
|
|
size = "medium",
|
|
srcs = ["evaluation/tests/test_trajectory_view_api.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "evaluation/tests/test_episode",
|
|
tags = ["team:ml", "evaluation"],
|
|
size = "small",
|
|
srcs = ["evaluation/tests/test_episode.py"]
|
|
)
|
|
|
|
# --------------------------------------------------------------------
|
|
# Optimizers and Memories
|
|
# rllib/execution/
|
|
#
|
|
# Tag: execution
|
|
# --------------------------------------------------------------------
|
|
|
|
py_test(
|
|
name = "test_segment_tree",
|
|
tags = ["team:ml", "execution"],
|
|
size = "small",
|
|
srcs = ["execution/tests/test_segment_tree.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_prioritized_replay_buffer",
|
|
tags = ["team:ml", "execution"],
|
|
size = "small",
|
|
srcs = ["execution/tests/test_prioritized_replay_buffer.py"]
|
|
)
|
|
|
|
# --------------------------------------------------------------------
|
|
# Models and Distributions
|
|
# rllib/models/
|
|
#
|
|
# Tag: models
|
|
# --------------------------------------------------------------------
|
|
|
|
py_test(
|
|
name = "test_attention_nets",
|
|
tags = ["team:ml", "models"],
|
|
size = "large",
|
|
srcs = ["models/tests/test_attention_nets.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_conv2d_default_stacks",
|
|
tags = ["team:ml", "models"],
|
|
size = "medium",
|
|
srcs = ["models/tests/test_conv2d_default_stacks.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_convtranspose2d_stack",
|
|
tags = ["team:ml", "models"],
|
|
size = "small",
|
|
data = glob(["tests/data/images/obstacle_tower.png"]),
|
|
srcs = ["models/tests/test_convtranspose2d_stack.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_distributions",
|
|
tags = ["team:ml", "models"],
|
|
size = "medium",
|
|
srcs = ["models/tests/test_distributions.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_lstms",
|
|
tags = ["team:ml", "models"],
|
|
size = "large",
|
|
srcs = ["models/tests/test_lstms.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_models",
|
|
tags = ["team:ml", "models"],
|
|
size = "medium",
|
|
srcs = ["models/tests/test_models.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_preprocessors",
|
|
tags = ["team:ml", "models"],
|
|
size = "large",
|
|
srcs = ["models/tests/test_preprocessors.py"]
|
|
)
|
|
|
|
# --------------------------------------------------------------------
|
|
# Policies
|
|
# rllib/policy/
|
|
#
|
|
# Tag: policy
|
|
# --------------------------------------------------------------------
|
|
|
|
py_test(
|
|
name = "policy/tests/test_compute_log_likelihoods",
|
|
tags = ["team:ml", "policy"],
|
|
size = "medium",
|
|
srcs = ["policy/tests/test_compute_log_likelihoods.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "policy/tests/test_policy",
|
|
tags = ["team:ml", "policy"],
|
|
size = "medium",
|
|
srcs = ["policy/tests/test_policy.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "policy/tests/test_rnn_sequencing",
|
|
tags = ["team:ml", "policy"],
|
|
size = "small",
|
|
srcs = ["policy/tests/test_rnn_sequencing.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "policy/tests/test_sample_batch",
|
|
tags = ["team:ml", "policy"],
|
|
size = "small",
|
|
srcs = ["policy/tests/test_sample_batch.py"]
|
|
)
|
|
|
|
# --------------------------------------------------------------------
|
|
# Utils:
|
|
# rllib/utils/
|
|
#
|
|
# Tag: utils
|
|
# --------------------------------------------------------------------
|
|
|
|
py_test(
|
|
name = "test_curiosity",
|
|
tags = ["team:ml", "utils"],
|
|
size = "large",
|
|
srcs = ["utils/exploration/tests/test_curiosity.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_explorations",
|
|
tags = ["team:ml", "utils"],
|
|
size = "large",
|
|
srcs = ["utils/exploration/tests/test_explorations.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_parameter_noise",
|
|
tags = ["team:ml", "utils"],
|
|
size = "medium",
|
|
srcs = ["utils/exploration/tests/test_parameter_noise.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_random_encoder",
|
|
tags = ["team:ml", "utils"],
|
|
size = "large",
|
|
srcs = ["utils/exploration/tests/test_random_encoder.py"]
|
|
)
|
|
|
|
# Schedules
|
|
py_test(
|
|
name = "test_schedules",
|
|
tags = ["team:ml", "utils"],
|
|
size = "small",
|
|
srcs = ["utils/schedules/tests/test_schedules.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_framework_agnostic_components",
|
|
tags = ["team:ml", "utils"],
|
|
size = "small",
|
|
data = glob(["utils/tests/**"]),
|
|
srcs = ["utils/tests/test_framework_agnostic_components.py"]
|
|
)
|
|
|
|
# Spaces/Space utils.
|
|
py_test(
|
|
name = "test_space_utils",
|
|
tags = ["team:ml", "utils"],
|
|
size = "large",
|
|
srcs = ["utils/spaces/tests/test_space_utils.py"]
|
|
)
|
|
|
|
|
|
# TaskPool
|
|
py_test(
|
|
name = "test_taskpool",
|
|
tags = ["team:ml", "utils"],
|
|
size = "small",
|
|
srcs = ["utils/tests/test_taskpool.py"]
|
|
)
|
|
|
|
# --------------------------------------------------------------------
|
|
# rllib/tests/ directory
|
|
#
|
|
# Tag: tests_dir, tests_dir_[A-Z]
|
|
#
|
|
# NOTE: Add tests alphabetically into this list and make sure, to tag
|
|
# it correctly by its starting letter, e.g. tags=["tests_dir", "tests_dir_A"]
|
|
# for `tests/test_all_stuff.py`.
|
|
# --------------------------------------------------------------------
|
|
|
|
py_test(
|
|
name = "tests/test_catalog",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_C"],
|
|
size = "medium",
|
|
srcs = ["tests/test_catalog.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_checkpoint_restore_pg",
|
|
main = "tests/test_checkpoint_restore.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_C"],
|
|
size = "large",
|
|
srcs = ["tests/test_checkpoint_restore.py"],
|
|
args = ["TestCheckpointRestorePG"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_checkpoint_restore_off_policy",
|
|
main = "tests/test_checkpoint_restore.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_C"],
|
|
size = "large",
|
|
srcs = ["tests/test_checkpoint_restore.py"],
|
|
args = ["TestCheckpointRestoreOffPolicy"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_checkpoint_restore_evolution_algos",
|
|
main = "tests/test_checkpoint_restore.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_C"],
|
|
size = "large",
|
|
srcs = ["tests/test_checkpoint_restore.py"],
|
|
args = ["TestCheckpointRestoreEvolutionAlgos"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_dependency_tf",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_D"],
|
|
size = "small",
|
|
srcs = ["tests/test_dependency_tf.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_dependency_torch",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_D"],
|
|
size = "small",
|
|
srcs = ["tests/test_dependency_torch.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_eager_support_pg",
|
|
main = "tests/test_eager_support.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_E"],
|
|
size = "large",
|
|
srcs = ["tests/test_eager_support.py"],
|
|
args = ["TestEagerSupportPG"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_eager_support_off_policy",
|
|
main = "tests/test_eager_support.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_E"],
|
|
size = "large",
|
|
srcs = ["tests/test_eager_support.py"],
|
|
args = ["TestEagerSupportOffPolicy"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_env_with_subprocess",
|
|
main = "tests/test_env_with_subprocess.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_E"],
|
|
size = "medium",
|
|
srcs = ["tests/test_env_with_subprocess.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_exec_api",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_E"],
|
|
size = "medium",
|
|
srcs = ["tests/test_exec_api.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_execution",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_E"],
|
|
size = "medium",
|
|
srcs = ["tests/test_execution.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_export",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_E"],
|
|
size = "medium",
|
|
srcs = ["tests/test_export.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_external_env",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_E"],
|
|
size = "large",
|
|
srcs = ["tests/test_external_env.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_external_multi_agent_env",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_E"],
|
|
size = "medium",
|
|
srcs = ["tests/test_external_multi_agent_env.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_filters",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_F"],
|
|
size = "small",
|
|
srcs = ["tests/test_filters.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_gpus",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_G"],
|
|
size = "large",
|
|
srcs = ["tests/test_gpus.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_ignore_worker_failure",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_I"],
|
|
size = "large",
|
|
srcs = ["tests/test_ignore_worker_failure.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_io",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_I"],
|
|
size = "large",
|
|
srcs = ["tests/test_io.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_local",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_L"],
|
|
size = "medium",
|
|
srcs = ["tests/test_local.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_lstm",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_L"],
|
|
size = "medium",
|
|
srcs = ["tests/test_lstm.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_model_imports",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_M", "model_imports"],
|
|
size = "medium",
|
|
data = glob(["tests/data/model_weights/**"]),
|
|
srcs = ["tests/test_model_imports.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_multi_agent_env",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_M"],
|
|
size = "medium",
|
|
srcs = ["tests/test_multi_agent_env.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_multi_agent_pendulum",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_M"],
|
|
size = "large",
|
|
srcs = ["tests/test_multi_agent_pendulum.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_nested_action_spaces",
|
|
main = "tests/test_nested_action_spaces.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_N"],
|
|
size = "medium",
|
|
srcs = ["tests/test_nested_action_spaces.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_nested_observation_spaces",
|
|
main = "tests/test_nested_observation_spaces.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_N"],
|
|
size = "medium",
|
|
srcs = ["tests/test_nested_observation_spaces.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_nn_framework_import_errors",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_N"],
|
|
size = "small",
|
|
srcs = ["tests/test_nn_framework_import_errors.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_pettingzoo_env",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_P"],
|
|
size = "medium",
|
|
srcs = ["tests/test_pettingzoo_env.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_placement_groups",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_P"],
|
|
size = "medium",
|
|
srcs = ["tests/test_placement_groups.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_ray_client",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_R"],
|
|
size = "large",
|
|
srcs = ["tests/test_ray_client.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_reproducibility",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_R"],
|
|
size = "medium",
|
|
srcs = ["tests/test_reproducibility.py"]
|
|
)
|
|
|
|
# Test [train|evaluate].py scripts (w/o confirming evaluation performance).
|
|
py_test(
|
|
name = "test_rllib_evaluate_1",
|
|
main = "tests/test_rllib_train_and_evaluate.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_R"],
|
|
size = "large",
|
|
data = ["train.py", "evaluate.py"],
|
|
srcs = ["tests/test_rllib_train_and_evaluate.py"],
|
|
args = ["TestEvaluate1"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_rllib_evaluate_2",
|
|
main = "tests/test_rllib_train_and_evaluate.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_R"],
|
|
size = "large",
|
|
data = ["train.py", "evaluate.py"],
|
|
srcs = ["tests/test_rllib_train_and_evaluate.py"],
|
|
args = ["TestEvaluate2"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_rllib_evaluate_3",
|
|
main = "tests/test_rllib_train_and_evaluate.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_R"],
|
|
size = "large",
|
|
data = ["train.py", "evaluate.py"],
|
|
srcs = ["tests/test_rllib_train_and_evaluate.py"],
|
|
args = ["TestEvaluate3"]
|
|
)
|
|
|
|
py_test(
|
|
name = "test_rllib_evaluate_4",
|
|
main = "tests/test_rllib_train_and_evaluate.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_R"],
|
|
size = "large",
|
|
data = ["train.py", "evaluate.py"],
|
|
srcs = ["tests/test_rllib_train_and_evaluate.py"],
|
|
args = ["TestEvaluate4"]
|
|
)
|
|
|
|
# Test [train|evaluate].py scripts (and confirm `rllib evaluate` performance is same
|
|
# as the final one from the `rllib train` run).
|
|
py_test(
|
|
name = "test_rllib_train_and_evaluate",
|
|
main = "tests/test_rllib_train_and_evaluate.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_R"],
|
|
size = "large",
|
|
data = ["train.py", "evaluate.py"],
|
|
srcs = ["tests/test_rllib_train_and_evaluate.py"],
|
|
args = ["TestTrainAndEvaluate"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_supported_multi_agent_pg",
|
|
main = "tests/test_supported_multi_agent.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_S"],
|
|
size = "medium",
|
|
srcs = ["tests/test_supported_multi_agent.py"],
|
|
args = ["TestSupportedMultiAgentPG"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_supported_multi_agent_off_policy",
|
|
main = "tests/test_supported_multi_agent.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_S"],
|
|
size = "medium",
|
|
srcs = ["tests/test_supported_multi_agent.py"],
|
|
args = ["TestSupportedMultiAgentOffPolicy"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_supported_spaces_pg",
|
|
main = "tests/test_supported_spaces.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_S"],
|
|
size = "large",
|
|
srcs = ["tests/test_supported_spaces.py"],
|
|
args = ["TestSupportedSpacesPG"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_supported_spaces_off_policy",
|
|
main = "tests/test_supported_spaces.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_S"],
|
|
size = "medium",
|
|
srcs = ["tests/test_supported_spaces.py"],
|
|
args = ["TestSupportedSpacesOffPolicy"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_supported_spaces_evolution_algos",
|
|
main = "tests/test_supported_spaces.py",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_S"],
|
|
size = "large",
|
|
srcs = ["tests/test_supported_spaces.py"],
|
|
args = ["TestSupportedSpacesEvolutionAlgos"]
|
|
)
|
|
|
|
py_test(
|
|
name = "tests/test_timesteps",
|
|
tags = ["team:ml", "tests_dir", "tests_dir_T"],
|
|
size = "small",
|
|
srcs = ["tests/test_timesteps.py"]
|
|
)
|
|
|
|
# --------------------------------------------------------------------
|
|
# examples/ directory (excluding examples/documentation/...)
|
|
#
|
|
# Tag: examples, examples_[A-Z]
|
|
#
|
|
# NOTE: Add tests alphabetically into this list and make sure, to tag
|
|
# it correctly by its starting letter, e.g. tags=["examples", "examples_A"]
|
|
# for `examples/all_stuff.py`.
|
|
# --------------------------------------------------------------------
|
|
|
|
py_test(
|
|
name = "examples/action_masking_tf",
|
|
main = "examples/action_masking.py",
|
|
tags = ["team:ml", "examples", "examples_A"],
|
|
size = "medium",
|
|
srcs = ["examples/action_masking.py"],
|
|
args = ["--stop-iter=2"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/action_masking_torch",
|
|
main = "examples/action_masking.py",
|
|
tags = ["team:ml", "examples", "examples_A"],
|
|
size = "medium",
|
|
srcs = ["examples/action_masking.py"],
|
|
args = ["--stop-iter=2", "--framework=torch"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/attention_net_tf",
|
|
main = "examples/attention_net.py",
|
|
tags = ["team:ml", "examples", "examples_A"],
|
|
size = "medium",
|
|
srcs = ["examples/attention_net.py"],
|
|
args = ["--as-test", "--stop-reward=70"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/attention_net_torch",
|
|
main = "examples/attention_net.py",
|
|
tags = ["team:ml", "examples", "examples_A"],
|
|
size = "medium",
|
|
srcs = ["examples/attention_net.py"],
|
|
args = ["--as-test", "--stop-reward=70", "--framework torch"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/autoregressive_action_dist_tf",
|
|
main = "examples/autoregressive_action_dist.py",
|
|
tags = ["team:ml", "examples", "examples_A"],
|
|
size = "medium",
|
|
srcs = ["examples/autoregressive_action_dist.py"],
|
|
args = ["--as-test", "--stop-reward=150", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/autoregressive_action_dist_torch",
|
|
main = "examples/autoregressive_action_dist.py",
|
|
tags = ["team:ml", "examples", "examples_A"],
|
|
size = "medium",
|
|
srcs = ["examples/autoregressive_action_dist.py"],
|
|
args = ["--as-test", "--framework=torch", "--stop-reward=150", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/bare_metal_policy_with_custom_view_reqs",
|
|
main = "examples/bare_metal_policy_with_custom_view_reqs.py",
|
|
tags = ["team:ml", "examples", "examples_B"],
|
|
size = "medium",
|
|
srcs = ["examples/bare_metal_policy_with_custom_view_reqs.py"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/batch_norm_model_ppo_tf",
|
|
main = "examples/batch_norm_model.py",
|
|
tags = ["team:ml", "examples", "examples_B"],
|
|
size = "medium",
|
|
srcs = ["examples/batch_norm_model.py"],
|
|
args = ["--as-test", "--run=PPO", "--stop-reward=80"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/batch_norm_model_ppo_torch",
|
|
main = "examples/batch_norm_model.py",
|
|
tags = ["team:ml", "examples", "examples_B"],
|
|
size = "medium",
|
|
srcs = ["examples/batch_norm_model.py"],
|
|
args = ["--as-test", "--framework=torch", "--run=PPO", "--stop-reward=80"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/batch_norm_model_dqn_tf",
|
|
main = "examples/batch_norm_model.py",
|
|
tags = ["team:ml", "examples", "examples_B"],
|
|
size = "medium",
|
|
srcs = ["examples/batch_norm_model.py"],
|
|
args = ["--as-test", "--run=DQN", "--stop-reward=70"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/batch_norm_model_dqn_torch",
|
|
main = "examples/batch_norm_model.py",
|
|
tags = ["team:ml", "examples", "examples_B"],
|
|
size = "large", # DQN learns much slower with BatchNorm.
|
|
srcs = ["examples/batch_norm_model.py"],
|
|
args = ["--as-test", "--framework=torch", "--run=DQN", "--stop-reward=70"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/batch_norm_model_ddpg_tf",
|
|
main = "examples/batch_norm_model.py",
|
|
tags = ["team:ml", "examples", "examples_B"],
|
|
size = "medium",
|
|
srcs = ["examples/batch_norm_model.py"],
|
|
args = ["--run=DDPG", "--stop-iters=1"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/batch_norm_model_ddpg_torch",
|
|
main = "examples/batch_norm_model.py",
|
|
tags = ["team:ml", "examples", "examples_B"],
|
|
size = "medium",
|
|
srcs = ["examples/batch_norm_model.py"],
|
|
args = ["--framework=torch", "--run=DDPG", "--stop-iters=1"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/cartpole_lstm_impala_tf",
|
|
main = "examples/cartpole_lstm.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_AtoT"],
|
|
size = "medium",
|
|
srcs = ["examples/cartpole_lstm.py"],
|
|
args = ["--as-test", "--run=IMPALA", "--stop-reward=40", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/cartpole_lstm_impala_torch",
|
|
main = "examples/cartpole_lstm.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_AtoT"],
|
|
size = "medium",
|
|
srcs = ["examples/cartpole_lstm.py"],
|
|
args = ["--as-test", "--framework=torch", "--run=IMPALA", "--stop-reward=40", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/cartpole_lstm_ppo_tf",
|
|
main = "examples/cartpole_lstm.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_AtoT"],
|
|
size = "medium",
|
|
srcs = ["examples/cartpole_lstm.py"],
|
|
args = ["--as-test", "--framework=tf", "--run=PPO", "--stop-reward=40", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/cartpole_lstm_ppo_tf2",
|
|
main = "examples/cartpole_lstm.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_AtoT"],
|
|
size = "large",
|
|
srcs = ["examples/cartpole_lstm.py"],
|
|
args = ["--as-test", "--framework=tf2", "--run=PPO", "--stop-reward=40", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/cartpole_lstm_ppo_torch",
|
|
main = "examples/cartpole_lstm.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_AtoT"],
|
|
size = "medium",
|
|
srcs = ["examples/cartpole_lstm.py"],
|
|
args = ["--as-test", "--framework=torch", "--run=PPO", "--stop-reward=40", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/cartpole_lstm_ppo_tf_with_prev_a_and_r",
|
|
main = "examples/cartpole_lstm.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_AtoT"],
|
|
size = "medium",
|
|
srcs = ["examples/cartpole_lstm.py"],
|
|
args = ["--as-test", "--run=PPO", "--stop-reward=40", "--use-prev-action", "--use-prev-reward", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/centralized_critic_tf",
|
|
main = "examples/centralized_critic.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_AtoT"],
|
|
size = "large",
|
|
srcs = ["examples/centralized_critic.py"],
|
|
args = ["--as-test", "--stop-reward=7.2"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/centralized_critic_torch",
|
|
main = "examples/centralized_critic.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_AtoT"],
|
|
size = "large",
|
|
srcs = ["examples/centralized_critic.py"],
|
|
args = ["--as-test", "--framework=torch", "--stop-reward=7.2"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/centralized_critic_2_tf",
|
|
main = "examples/centralized_critic_2.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_AtoT"],
|
|
size = "medium",
|
|
srcs = ["examples/centralized_critic_2.py"],
|
|
args = ["--as-test", "--stop-reward=6.0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/centralized_critic_2_torch",
|
|
main = "examples/centralized_critic_2.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_AtoT"],
|
|
size = "medium",
|
|
srcs = ["examples/centralized_critic_2.py"],
|
|
args = ["--as-test", "--framework=torch", "--stop-reward=6.0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/checkpoint_by_custom_criteria",
|
|
main = "examples/checkpoint_by_custom_criteria.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_AtoT"],
|
|
size = "medium",
|
|
srcs = ["examples/checkpoint_by_custom_criteria.py"],
|
|
args = ["--stop-iters=3 --num-cpus=3"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/complex_struct_space_tf",
|
|
main = "examples/complex_struct_space.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_AtoT"],
|
|
size = "medium",
|
|
srcs = ["examples/complex_struct_space.py"],
|
|
args = ["--framework=tf"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/complex_struct_space_tf_eager",
|
|
main = "examples/complex_struct_space.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_AtoT"],
|
|
size = "medium",
|
|
srcs = ["examples/complex_struct_space.py"],
|
|
args = ["--framework=tfe"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/complex_struct_space_torch",
|
|
main = "examples/complex_struct_space.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_AtoT"],
|
|
size = "medium",
|
|
srcs = ["examples/complex_struct_space.py"],
|
|
args = ["--framework=torch"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/curriculum_learning",
|
|
main = "examples/curriculum_learning.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/curriculum_learning.py"],
|
|
args = ["--as-test", "--stop-reward=800.0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_env_tf",
|
|
main = "examples/custom_env.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_env.py"],
|
|
args = ["--as-test"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_env_torch",
|
|
main = "examples/custom_env.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "large",
|
|
srcs = ["examples/custom_env.py"],
|
|
args = ["--as-test", "--framework=torch"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_eval_tf",
|
|
main = "examples/custom_eval.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_eval.py"],
|
|
args = ["--num-cpus=4", "--as-test"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_eval_torch",
|
|
main = "examples/custom_eval.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_eval.py"],
|
|
args = ["--num-cpus=4", "--as-test", "--framework=torch"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_experiment",
|
|
main = "examples/custom_experiment.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_experiment.py"],
|
|
args = ["--train-iterations=10"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_fast_model_tf",
|
|
main = "examples/custom_fast_model.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_fast_model.py"],
|
|
args = ["--stop-iters=1"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_fast_model_torch",
|
|
main = "examples/custom_fast_model.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_fast_model.py"],
|
|
args = ["--stop-iters=1", "--framework=torch"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_keras_model_a2c",
|
|
main = "examples/custom_keras_model.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "large",
|
|
srcs = ["examples/custom_keras_model.py"],
|
|
args = ["--run=A2C", "--stop=50", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_keras_model_dqn",
|
|
main = "examples/custom_keras_model.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_keras_model.py"],
|
|
args = ["--run=DQN", "--stop=50"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_keras_model_ppo",
|
|
main = "examples/custom_keras_model.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_keras_model.py"],
|
|
args = ["--run=PPO", "--stop=50", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_metrics_and_callbacks",
|
|
main = "examples/custom_metrics_and_callbacks.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "small",
|
|
srcs = ["examples/custom_metrics_and_callbacks.py"],
|
|
args = ["--stop-iters=2"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_metrics_and_callbacks_legacy",
|
|
main = "examples/custom_metrics_and_callbacks_legacy.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "small",
|
|
srcs = ["examples/custom_metrics_and_callbacks_legacy.py"],
|
|
args = ["--stop-iters=2"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_model_api_tf",
|
|
main = "examples/custom_model_api.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "small",
|
|
srcs = ["examples/custom_model_api.py"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_model_api_torch",
|
|
main = "examples/custom_model_api.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "small",
|
|
srcs = ["examples/custom_model_api.py"],
|
|
args = ["--framework=torch"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_model_loss_and_metrics_ppo_tf",
|
|
main = "examples/custom_model_loss_and_metrics.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
# Include the json data file.
|
|
data = ["tests/data/cartpole/small.json"],
|
|
srcs = ["examples/custom_model_loss_and_metrics.py"],
|
|
args = ["--run=PPO", "--stop-iters=1", "--input-files=tests/data/cartpole"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_model_loss_and_metrics_ppo_torch",
|
|
main = "examples/custom_model_loss_and_metrics.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
# Include the json data file.
|
|
data = ["tests/data/cartpole/small.json"],
|
|
srcs = ["examples/custom_model_loss_and_metrics.py"],
|
|
args = ["--run=PPO", "--framework=torch", "--stop-iters=1", "--input-files=tests/data/cartpole"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_model_loss_and_metrics_pg_tf",
|
|
main = "examples/custom_model_loss_and_metrics.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
# Include the json data file.
|
|
data = ["tests/data/cartpole/small.json"],
|
|
srcs = ["examples/custom_model_loss_and_metrics.py"],
|
|
args = ["--run=PG", "--stop-iters=1", "--input-files=tests/data/cartpole"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_model_loss_and_metrics_pg_torch",
|
|
main = "examples/custom_model_loss_and_metrics.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
# Include the json data file.
|
|
data = ["tests/data/cartpole/small.json"],
|
|
srcs = ["examples/custom_model_loss_and_metrics.py"],
|
|
args = ["--run=PG", "--framework=torch", "--stop-iters=1", "--input-files=tests/data/cartpole"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_observation_filters",
|
|
main = "examples/custom_observation_filters.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_observation_filters.py"],
|
|
args = ["--stop-iters=3"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_rnn_model_repeat_after_me_tf",
|
|
main = "examples/custom_rnn_model.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_rnn_model.py"],
|
|
args = ["--as-test", "--run=PPO", "--stop-reward=40", "--env=RepeatAfterMeEnv", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_rnn_model_repeat_initial_obs_tf",
|
|
main = "examples/custom_rnn_model.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_rnn_model.py"],
|
|
args = ["--as-test", "--run=PPO", "--stop-reward=10", "--stop-timesteps=300000", "--env=RepeatInitialObsEnv", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_rnn_model_repeat_after_me_torch",
|
|
main = "examples/custom_rnn_model.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_rnn_model.py"],
|
|
args = ["--as-test", "--framework=torch", "--run=PPO", "--stop-reward=40", "--env=RepeatAfterMeEnv", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_rnn_model_repeat_initial_obs_torch",
|
|
main = "examples/custom_rnn_model.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_rnn_model.py"],
|
|
args = ["--as-test", "--framework=torch", "--run=PPO", "--stop-reward=10", "--stop-timesteps=300000", "--env=RepeatInitialObsEnv", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_tf_policy",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_tf_policy.py"],
|
|
args = ["--stop-iters=2", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_torch_policy",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_torch_policy.py"],
|
|
args = ["--stop-iters=2", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_train_fn",
|
|
main = "examples/custom_train_fn.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_train_fn.py"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_vector_env_tf",
|
|
main = "examples/custom_vector_env.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_vector_env.py"],
|
|
args = ["--as-test", "--stop-reward=40.0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/custom_vector_env_torch",
|
|
main = "examples/custom_vector_env.py",
|
|
tags = ["team:ml", "examples", "examples_C", "examples_C_UtoZ"],
|
|
size = "medium",
|
|
srcs = ["examples/custom_vector_env.py"],
|
|
args = ["--as-test", "--framework=torch", "--stop-reward=40.0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/deterministic_training_tf",
|
|
main = "examples/deterministic_training.py",
|
|
tags = ["team:ml", "multi_gpu"],
|
|
size = "medium",
|
|
srcs = ["examples/deterministic_training.py"],
|
|
args = ["--as-test", "--stop-iters=1", "--framework=tf", "--num-gpus-trainer=1", "--num-gpus-per-worker=1"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/deterministic_training_tf2",
|
|
main = "examples/deterministic_training.py",
|
|
tags = ["team:ml", "multi_gpu"],
|
|
size = "medium",
|
|
srcs = ["examples/deterministic_training.py"],
|
|
args = ["--as-test", "--stop-iters=1", "--framework=tf2", "--num-gpus-trainer=1", "--num-gpus-per-worker=1"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/deterministic_training_torch",
|
|
main = "examples/deterministic_training.py",
|
|
tags = ["team:ml", "multi_gpu"],
|
|
size = "medium",
|
|
srcs = ["examples/deterministic_training.py"],
|
|
args = ["--as-test", "--stop-iters=1", "--framework=torch", "--num-gpus-trainer=1", "--num-gpus-per-worker=1"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/eager_execution",
|
|
tags = ["team:ml", "examples", "examples_E"],
|
|
size = "small",
|
|
srcs = ["examples/eager_execution.py"],
|
|
args = ["--stop-iters=2"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/export/cartpole_dqn_export",
|
|
main = "examples/export/cartpole_dqn_export.py",
|
|
tags = ["team:ml", "examples", "examples_E"],
|
|
size = "medium",
|
|
srcs = ["examples/export/cartpole_dqn_export.py"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/export/onnx_tf",
|
|
main = "examples/export/onnx_tf.py",
|
|
tags = ["team:ml", "examples", "examples_E"],
|
|
size = "medium",
|
|
srcs = ["examples/export/onnx_tf.py"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/export/onnx_torch",
|
|
main = "examples/export/onnx_torch.py",
|
|
tags = ["team:ml", "examples", "examples_E"],
|
|
size = "medium",
|
|
srcs = ["examples/export/onnx_torch.py"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/fractional_gpus",
|
|
main = "examples/fractional_gpus.py",
|
|
tags = ["team:ml", "examples", "examples_F"],
|
|
size = "medium",
|
|
srcs = ["examples/fractional_gpus.py"],
|
|
args = ["--as-test", "--stop-reward=40.0", "--num-gpus=0", "--num-workers=0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/hierarchical_training_tf",
|
|
main = "examples/hierarchical_training.py",
|
|
tags = ["team:ml", "examples", "examples_H"],
|
|
size = "medium",
|
|
srcs = ["examples/hierarchical_training.py"],
|
|
args = ["--stop-reward=0.0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/hierarchical_training_torch",
|
|
main = "examples/hierarchical_training.py",
|
|
tags = ["team:ml", "examples", "examples_H"],
|
|
size = "medium",
|
|
srcs = ["examples/hierarchical_training.py"],
|
|
args = ["--framework=torch", "--stop-reward=0.0"]
|
|
)
|
|
|
|
# Do not run this test (MobileNetV2 is gigantic and takes forever for 1 iter).
|
|
# py_test(
|
|
# name = "examples/mobilenet_v2_with_lstm_tf",
|
|
# main = "examples/mobilenet_v2_with_lstm.py",
|
|
# tags = ["team:ml", "examples", "examples_M"],
|
|
# size = "small",
|
|
# srcs = ["examples/mobilenet_v2_with_lstm.py"]
|
|
# )
|
|
|
|
py_test(
|
|
name = "examples/multi_agent_cartpole_tf",
|
|
main = "examples/multi_agent_cartpole.py",
|
|
tags = ["team:ml", "examples", "examples_M"],
|
|
size = "medium",
|
|
srcs = ["examples/multi_agent_cartpole.py"],
|
|
args = ["--as-test", "--stop-reward=70.0", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/multi_agent_cartpole_torch",
|
|
main = "examples/multi_agent_cartpole.py",
|
|
tags = ["team:ml", "examples", "examples_M"],
|
|
size = "medium",
|
|
srcs = ["examples/multi_agent_cartpole.py"],
|
|
args = ["--as-test", "--framework=torch", "--stop-reward=70.0", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/multi_agent_custom_policy_tf",
|
|
main = "examples/multi_agent_custom_policy.py",
|
|
tags = ["team:ml", "examples", "examples_M"],
|
|
size = "small",
|
|
srcs = ["examples/multi_agent_custom_policy.py"],
|
|
args = ["--as-test", "--stop-reward=80"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/multi_agent_custom_policy_torch",
|
|
main = "examples/multi_agent_custom_policy.py",
|
|
tags = ["team:ml", "examples", "examples_M"],
|
|
size = "small",
|
|
srcs = ["examples/multi_agent_custom_policy.py"],
|
|
args = ["--as-test", "--framework=torch", "--stop-reward=80"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/multi_agent_two_trainers_tf",
|
|
main = "examples/multi_agent_two_trainers.py",
|
|
tags = ["team:ml", "examples", "examples_M"],
|
|
size = "medium",
|
|
srcs = ["examples/multi_agent_two_trainers.py"],
|
|
args = ["--as-test", "--stop-reward=70"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/multi_agent_two_trainers_torch",
|
|
main = "examples/multi_agent_two_trainers.py",
|
|
tags = ["team:ml", "examples", "examples_M"],
|
|
size = "medium",
|
|
srcs = ["examples/multi_agent_two_trainers.py"],
|
|
args = ["--as-test", "--framework=torch", "--stop-reward=70"]
|
|
)
|
|
|
|
# Taking out this test for now: Mixed torch- and tf- policies within the same
|
|
# Trainer never really worked.
|
|
# py_test(
|
|
# name = "examples/multi_agent_two_trainers_mixed_torch_tf",
|
|
# main = "examples/multi_agent_two_trainers.py",
|
|
# tags = ["team:ml", "examples", "examples_M"],
|
|
# size = "medium",
|
|
# srcs = ["examples/multi_agent_two_trainers.py"],
|
|
# args = ["--as-test", "--mixed-torch-tf", "--stop-reward=70"]
|
|
# )
|
|
|
|
py_test(
|
|
name = "examples/nested_action_spaces_ppo_tf",
|
|
main = "examples/nested_action_spaces.py",
|
|
tags = ["team:ml", "examples", "examples_N"],
|
|
size = "medium",
|
|
srcs = ["examples/nested_action_spaces.py"],
|
|
args = ["--as-test", "--stop-reward=-600", "--run=PPO"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/nested_action_spaces_ppo_torch",
|
|
main = "examples/nested_action_spaces.py",
|
|
tags = ["team:ml", "examples", "examples_N"],
|
|
size = "medium",
|
|
srcs = ["examples/nested_action_spaces.py"],
|
|
args = ["--as-test", "--framework=torch", "--stop-reward=-600", "--run=PPO"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/parallel_evaluation_and_training_13_episodes_tf",
|
|
main = "examples/parallel_evaluation_and_training.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/parallel_evaluation_and_training.py"],
|
|
args = ["--as-test", "--stop-reward=50.0", "--num-cpus=6", "--evaluation-duration=13"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/parallel_evaluation_and_training_auto_episodes_tf",
|
|
main = "examples/parallel_evaluation_and_training.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/parallel_evaluation_and_training.py"],
|
|
args = ["--as-test", "--stop-reward=50.0", "--num-cpus=6", "--evaluation-duration=auto"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/parallel_evaluation_and_training_211_ts_tf2",
|
|
main = "examples/parallel_evaluation_and_training.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/parallel_evaluation_and_training.py"],
|
|
args = ["--as-test", "--framework=tf2", "--stop-reward=30.0", "--num-cpus=6", "--evaluation-num-workers=3", "--evaluation-duration=211", "--evaluation-duration-unit=timesteps"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/parallel_evaluation_and_training_auto_ts_torch",
|
|
main = "examples/parallel_evaluation_and_training.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/parallel_evaluation_and_training.py"],
|
|
args = ["--as-test", "--framework=torch", "--stop-reward=30.0", "--num-cpus=6", "--evaluation-num-workers=3", "--evaluation-duration=auto", "--evaluation-duration-unit=timesteps"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/parametric_actions_cartpole_pg_tf",
|
|
main = "examples/parametric_actions_cartpole.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/parametric_actions_cartpole.py"],
|
|
args = ["--as-test", "--stop-reward=60.0", "--run=PG"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/parametric_actions_cartpole_dqn_tf",
|
|
main = "examples/parametric_actions_cartpole.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/parametric_actions_cartpole.py"],
|
|
args = ["--as-test", "--stop-reward=60.0", "--run=DQN"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/parametric_actions_cartpole_pg_torch",
|
|
main = "examples/parametric_actions_cartpole.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/parametric_actions_cartpole.py"],
|
|
args = ["--as-test", "--framework=torch", "--stop-reward=60.0", "--run=PG"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/parametric_actions_cartpole_dqn_torch",
|
|
main = "examples/parametric_actions_cartpole.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/parametric_actions_cartpole.py"],
|
|
args = ["--as-test", "--framework=torch", "--stop-reward=60.0", "--run=DQN"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/parametric_actions_cartpole_embeddings_learnt_by_model",
|
|
main = "examples/parametric_actions_cartpole_embeddings_learnt_by_model.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/parametric_actions_cartpole_embeddings_learnt_by_model.py"],
|
|
args = ["--as-test", "--stop-reward=80.0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/inference_and_serving/policy_inference_after_training_tf",
|
|
main = "examples/inference_and_serving/policy_inference_after_training.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/inference_and_serving/policy_inference_after_training.py"],
|
|
args = ["--stop-iters=3", "--framework=tf"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/inference_and_serving/policy_inference_after_training_torch",
|
|
main = "examples/inference_and_serving/policy_inference_after_training.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/inference_and_serving/policy_inference_after_training.py"],
|
|
args = ["--stop-iters=3", "--framework=torch"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/inference_and_serving/policy_inference_after_training_with_attention_tf",
|
|
main = "examples/inference_and_serving/policy_inference_after_training_with_attention.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/inference_and_serving/policy_inference_after_training_with_attention.py"],
|
|
args = ["--stop-iters=2", "--framework=tf"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/inference_and_serving/policy_inference_after_training_with_attention_torch",
|
|
main = "examples/inference_and_serving/policy_inference_after_training_with_attention.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/inference_and_serving/policy_inference_after_training_with_attention.py"],
|
|
args = ["--stop-iters=2", "--framework=torch"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/inference_and_serving/policy_inference_after_training_with_lstm_tf",
|
|
main = "examples/inference_and_serving/policy_inference_after_training_with_lstm.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/inference_and_serving/policy_inference_after_training_with_lstm.py"],
|
|
args = ["--stop-iters=1", "--framework=tf"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/inference_and_serving/policy_inference_after_training_with_lstm_torch",
|
|
main = "examples/inference_and_serving/policy_inference_after_training_with_lstm.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/inference_and_serving/policy_inference_after_training_with_lstm.py"],
|
|
args = ["--stop-iters=1", "--framework=torch"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/preprocessing_disabled_tf",
|
|
main = "examples/preprocessing_disabled.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/preprocessing_disabled.py"],
|
|
args = ["--stop-iters=2"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/preprocessing_disabled_torch",
|
|
main = "examples/preprocessing_disabled.py",
|
|
tags = ["team:ml", "examples", "examples_P"],
|
|
size = "medium",
|
|
srcs = ["examples/preprocessing_disabled.py"],
|
|
args = ["--framework=torch", "--stop-iters=2"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/recommender_system_with_recsim_and_slateq_tf2",
|
|
main = "examples/recommender_system_with_recsim_and_slateq.py",
|
|
tags = ["team:ml", "examples", "examples_R"],
|
|
size = "large",
|
|
srcs = ["examples/recommender_system_with_recsim_and_slateq.py"],
|
|
args = ["--stop-iters=2", "--learning-starts=100", "--framework=tf2", "--use-tune", "--random-test-episodes=10", "--env-num-candidates=50", "--env-slate-size=2"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/remote_envs_with_inference_done_on_main_node_tf",
|
|
main = "examples/remote_envs_with_inference_done_on_main_node.py",
|
|
tags = ["team:ml", "examples", "examples_R"],
|
|
size = "medium",
|
|
srcs = ["examples/remote_envs_with_inference_done_on_main_node.py"],
|
|
args = ["--as-test"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/remote_envs_with_inference_done_on_main_node_torch",
|
|
main = "examples/remote_envs_with_inference_done_on_main_node.py",
|
|
tags = ["team:ml", "examples", "examples_R"],
|
|
size = "medium",
|
|
srcs = ["examples/remote_envs_with_inference_done_on_main_node.py"],
|
|
args = ["--as-test", "--framework=torch"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/remote_base_env_with_custom_api",
|
|
tags = ["team:ml", "examples", "examples_R"],
|
|
size = "medium",
|
|
srcs = ["examples/remote_base_env_with_custom_api.py"],
|
|
args = ["--stop-iters=3"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/restore_1_of_n_agents_from_checkpoint",
|
|
tags = ["team:ml", "examples", "examples_R"],
|
|
size = "medium",
|
|
srcs = ["examples/restore_1_of_n_agents_from_checkpoint.py"],
|
|
args = ["--pre-training-iters=1", "--stop-iters=1", "--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/rnnsac_stateless_cartpole",
|
|
tags = ["team:ml", "gpu"],
|
|
size = "large",
|
|
srcs = ["examples/rnnsac_stateless_cartpole.py"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/rollout_worker_custom_workflow",
|
|
tags = ["team:ml", "examples", "examples_R"],
|
|
size = "small",
|
|
srcs = ["examples/rollout_worker_custom_workflow.py"],
|
|
args = ["--num-cpus=4"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/rock_paper_scissors_multiagent_tf",
|
|
main = "examples/rock_paper_scissors_multiagent.py",
|
|
tags = ["team:ml", "examples", "examples_R"],
|
|
size = "medium",
|
|
srcs = ["examples/rock_paper_scissors_multiagent.py"],
|
|
args = ["--as-test"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/rock_paper_scissors_multiagent_torch",
|
|
main = "examples/rock_paper_scissors_multiagent.py",
|
|
tags = ["team:ml", "examples", "examples_R"],
|
|
size = "medium",
|
|
srcs = ["examples/rock_paper_scissors_multiagent.py"],
|
|
args = ["--as-test", "--framework=torch"],
|
|
)
|
|
|
|
# Deactivated for now due to open-spiel's dependency on an outdated
|
|
# tensorflow-probability version.
|
|
# py_test(
|
|
# name = "examples/self_play_with_open_spiel_connect_4_tf",
|
|
# main = "examples/self_play_with_open_spiel.py",
|
|
# tags = ["team:ml", "examples", "examples_S"],
|
|
# size = "medium",
|
|
# srcs = ["examples/self_play_with_open_spiel.py"],
|
|
# args = ["--framework=tf", "--env=connect_four", "--win-rate-threshold=0.6", "--stop-iters=2", "--num-episodes-human-play=0"]
|
|
# )
|
|
|
|
# py_test(
|
|
# name = "examples/self_play_with_open_spiel_connect_4_torch",
|
|
# main = "examples/self_play_with_open_spiel.py",
|
|
# tags = ["team:ml", "examples", "examples_S"],
|
|
# size = "medium",
|
|
# srcs = ["examples/self_play_with_open_spiel.py"],
|
|
# args = ["--framework=torch", "--env=connect_four", "--win-rate-threshold=0.6", "--stop-iters=2", "--num-episodes-human-play=0"]
|
|
# )
|
|
|
|
# py_test(
|
|
# name = "examples/self_play_league_based_with_open_spiel_markov_soccer_tf",
|
|
# main = "examples/self_play_league_based_with_open_spiel.py",
|
|
# tags = ["team:ml", "examples", "examples_S"],
|
|
# size = "medium",
|
|
# srcs = ["examples/self_play_league_based_with_open_spiel.py"],
|
|
# args = ["--framework=tf", "--env=markov_soccer", "--win-rate-threshold=0.6", "--stop-iters=2", "--num-episodes-human-play=0"]
|
|
# )
|
|
|
|
# py_test(
|
|
# name = "examples/self_play_league_based_with_open_spiel_markov_soccer_torch",
|
|
# main = "examples/self_play_league_based_with_open_spiel.py",
|
|
# tags = ["team:ml", "examples", "examples_S"],
|
|
# size = "medium",
|
|
# srcs = ["examples/self_play_league_based_with_open_spiel_markov_soccer.py"],
|
|
# args = ["--framework=torch", "--env=markov_soccer", "--win-rate-threshold=0.6", "--stop-iters=2", "--num-episodes-human-play=0"]
|
|
# )
|
|
|
|
py_test(
|
|
name = "examples/trajectory_view_api_tf",
|
|
main = "examples/trajectory_view_api.py",
|
|
tags = ["team:ml", "examples", "examples_T"],
|
|
size = "medium",
|
|
srcs = ["examples/trajectory_view_api.py"],
|
|
args = ["--as-test", "--framework=tf", "--stop-reward=100.0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/trajectory_view_api_torch",
|
|
main = "examples/trajectory_view_api.py",
|
|
tags = ["team:ml", "examples", "examples_T"],
|
|
size = "medium",
|
|
srcs = ["examples/trajectory_view_api.py"],
|
|
args = ["--as-test", "--framework=torch", "--stop-reward=100.0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/tune/framework",
|
|
main = "examples/tune/framework.py",
|
|
tags = ["team:ml", "examples", "examples_F"],
|
|
size = "medium",
|
|
srcs = ["examples/tune/framework.py"],
|
|
args = ["--smoke-test"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/two_trainer_workflow_tf",
|
|
main = "examples/two_trainer_workflow.py",
|
|
tags = ["team:ml", "examples", "examples_T"],
|
|
size = "small",
|
|
srcs = ["examples/two_trainer_workflow.py"],
|
|
args = ["--as-test", "--stop-reward=100.0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/two_trainer_workflow_torch",
|
|
main = "examples/two_trainer_workflow.py",
|
|
tags = ["team:ml", "examples", "examples_T"],
|
|
size = "small",
|
|
srcs = ["examples/two_trainer_workflow.py"],
|
|
args = ["--as-test", "--torch", "--stop-reward=100.0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/two_trainer_workflow_mixed_torch_tf",
|
|
main = "examples/two_trainer_workflow.py",
|
|
tags = ["team:ml", "examples", "examples_T"],
|
|
size = "small",
|
|
srcs = ["examples/two_trainer_workflow.py"],
|
|
args = ["--as-test", "--mixed-torch-tf", "--stop-reward=100.0"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/two_step_game_maddpg",
|
|
main = "examples/two_step_game.py",
|
|
tags = ["team:ml", "examples", "examples_T"],
|
|
size = "medium",
|
|
srcs = ["examples/two_step_game.py"],
|
|
args = ["--as-test", "--stop-reward=7.1", "--run=contrib/MADDPG"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/two_step_game_pg_tf",
|
|
main = "examples/two_step_game.py",
|
|
tags = ["team:ml", "examples", "examples_T"],
|
|
size = "medium",
|
|
srcs = ["examples/two_step_game.py"],
|
|
args = ["--as-test", "--stop-reward=7", "--run=PG"]
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/two_step_game_pg_torch",
|
|
main = "examples/two_step_game.py",
|
|
tags = ["team:ml", "examples", "examples_T"],
|
|
size = "medium",
|
|
srcs = ["examples/two_step_game.py"],
|
|
args = ["--as-test", "--framework=torch", "--stop-reward=7", "--run=PG"]
|
|
)
|
|
|
|
|
|
py_test(
|
|
name = "examples/bandit/lin_ts_train_wheel_env",
|
|
main = "examples/bandit/lin_ts_train_wheel_env.py",
|
|
tags = ["team:ml", "examples"],
|
|
size = "small",
|
|
srcs = ["examples/bandit/lin_ts_train_wheel_env.py"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/bandit/tune_lin_ts_train_wheel_env",
|
|
main = "examples/bandit/tune_lin_ts_train_wheel_env.py",
|
|
tags = ["team:ml", "examples"],
|
|
size = "small",
|
|
srcs = ["examples/bandit/tune_lin_ts_train_wheel_env.py"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/bandit/tune_lin_ucb_train_recommendation",
|
|
main = "examples/bandit/tune_lin_ucb_train_recommendation.py",
|
|
tags = ["team:ml", "examples", ],
|
|
size = "small",
|
|
srcs = ["examples/bandit/tune_lin_ucb_train_recommendation.py"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/bandit/tune_lin_ucb_train_recsim_env",
|
|
main = "examples/bandit/tune_lin_ucb_train_recsim_env.py",
|
|
tags = ["team:ml", "examples", ],
|
|
size = "small",
|
|
srcs = ["examples/bandit/tune_lin_ucb_train_recsim_env.py"],
|
|
)
|
|
|
|
# --------------------------------------------------------------------
|
|
# examples/documentation directory
|
|
#
|
|
# Tag: documentation
|
|
#
|
|
# NOTE: Add tests alphabetically to this list.
|
|
# --------------------------------------------------------------------
|
|
|
|
py_test(
|
|
name = "examples/documentation/custom_gym_env",
|
|
main = "examples/documentation/custom_gym_env.py",
|
|
tags = ["team:ml", "documentation"],
|
|
size = "medium",
|
|
srcs = ["examples/documentation/custom_gym_env.py"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/documentation/rllib_in_60s",
|
|
main = "examples/documentation/rllib_in_60s.py",
|
|
tags = ["team:ml", "documentation"],
|
|
size = "medium",
|
|
srcs = ["examples/documentation/rllib_in_60s.py"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/documentation/rllib_on_ray_readme",
|
|
main = "examples/documentation/rllib_on_ray_readme.py",
|
|
tags = ["team:ml", "documentation"],
|
|
size = "medium",
|
|
srcs = ["examples/documentation/rllib_on_ray_readme.py"],
|
|
)
|
|
|
|
py_test(
|
|
name = "examples/documentation/rllib_on_rllib_readme",
|
|
main = "examples/documentation/rllib_on_rllib_readme.py",
|
|
tags = ["team:ml", "documentation"],
|
|
size = "medium",
|
|
srcs = ["examples/documentation/rllib_on_rllib_readme.py"],
|
|
)
|