def test_parallel(config_updates):
"""Hyperparam tuning smoke test."""
# No need for TemporaryDirectory because the hyperparameter tuning script
# itself generates no artifacts, and "debug_log_root" sets inner experiment's
# log_root="/tmp/parallel_debug/".
run = parallel_ex.run(named_configs=["debug_log_root"],
config_updates=config_updates)
assert run.status == 'COMPLETED'
def test_parallel(config_updates):
"""Hyperparam tuning smoke test."""
# CI server only has 2 cores
config_updates = dict(config_updates)
config_updates.update(PARALLEL_CONFIG_LOW_RESOURCE)
# No need for TemporaryDirectory because the hyperparameter tuning script
# itself generates no artifacts, and "debug_log_root" sets inner experiment's
# log_root="/tmp/parallel_debug/".
run = parallel_ex.run(named_configs=["debug_log_root"],
config_updates=config_updates)
assert run.status == "COMPLETED"
def test_analyze_gather_tb(tmpdir: str):
config_updates = dict(local_dir=tmpdir, run_name="test")
config_updates.update(PARALLEL_CONFIG_LOW_RESOURCE)
parallel_run = parallel_ex.run(named_configs=["generate_test_data"],
config_updates=config_updates)
assert parallel_run.status == "COMPLETED"
run = analysis_ex.run(command_name="gather_tb_directories",
config_updates=dict(source_dir=tmpdir, ))
assert run.status == "COMPLETED"
assert isinstance(run.result, dict)
assert run.result["n_tb_dirs"] == 4
def test_analyze_gather_tb(tmpdir: str):
parallel_run = parallel_ex.run(named_configs=["generate_test_data"],
config_updates=dict(
local_dir=tmpdir,
run_name="test",
))
assert parallel_run.status == 'COMPLETED'
run = analysis_ex.run(command_name="gather_tb_directories",
config_updates=dict(source_dir=tmpdir, ))
assert run.status == 'COMPLETED'
assert isinstance(run.result, dict)
assert run.result["n_tb_dirs"] == 4
def test_parallel_train_adversarial_custom_env(tmpdir):
env_named_config = "custom_ant"
rollout_path = _generate_test_rollouts(tmpdir, env_named_config)
config_updates = dict(
sacred_ex_name="train_adversarial",
n_seeds=1,
base_named_configs=[env_named_config, "fast"],
base_config_updates=dict(
init_trainer_kwargs=dict(
parallel=True,
num_vec=2,
),
rollout_path=rollout_path,
),
)
config_updates.update(PARALLEL_CONFIG_LOW_RESOURCE)
run = parallel_ex.run(named_configs=["debug_log_root"],
config_updates=config_updates)
assert run.status == "COMPLETED"
