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@ericl ericl commented Mar 21, 2018

What do these changes do?

This renames resources => trial_resources, and cpu / driver_cpu_limit => cpu / extra_cpu.

Related issue number

#1759

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(e.g. env, hyperparams). Defaults to empty dict.
resources (dict): Machine resources to allocate per trial,
trial_resources (dict): Machine resources to allocate per trial,
e.g. ``{"cpu": 64, "gpu": 8}``. Note that GPUs will not be
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the docstring should be fixed for clarity

parser.add_argument(
"--trial-resources", default='{"cpu": 1}', type=json_to_resources,
help="Machine resources to allocate per trial, e.g. "
"'{\"cpu\": 64, \"gpu\": 8}'. Note that GPUs will not be assigned "
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the docstring should be fixed for clarity

"checkpoint_freq": args.checkpoint_freq,
"local_dir": args.local_dir,
"resources": resources_to_json(args.resources),
"trial_resources": resources_to_json(args.resources),
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args.trial_resources?

"run": "A3C",
"env": "carla_env",
"resources": {"cpu": 5, "gpu": 2, "driver_gpu_limit": 0},
"trial_resources": {"cpu": 5, "gpu": 2, "driver_gpu_limit": 0},
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driver_gpu_limit deprecated

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Updated

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@pcmoritz pcmoritz merged commit 72595cc into ray-project:master Mar 23, 2018
@pcmoritz pcmoritz deleted the tune-resource-update branch March 23, 2018 13:25
royf added a commit to royf/ray that referenced this pull request Apr 22, 2018
* commit 'f69cbd35d4e86f2a3c2ace875aaf8166edb69f5d': (64 commits)
  Bump version to 0.4.0. (ray-project#1745)
  Fix monitor.py bottleneck by removing excess Redis queries. (ray-project#1786)
  Convert the ObjectTable implementation to a Log (ray-project#1779)
  Acquire worker lock when importing actor. (ray-project#1783)
  Introduce a log interface for the new GCS (ray-project#1771)
  [tune] Fix linting error (ray-project#1777)
  [tune] Added pbt with keras on cifar10 dataset example (ray-project#1729)
  Add a GCS table for the xray task flatbuffer (ray-project#1775)
  [tune] Change tune resource request syntax to be less confusing (ray-project#1764)
  Remove from X import Y convention in RLlib ES. (ray-project#1774)
  Check if the provider is external before getting the config. (ray-project#1743)
  Request and cancel notifications in the new GCS API (ray-project#1758)
  Fix resource bookkeeping for blocked actor methods. (ray-project#1766)
  Fix bug when connecting another driver in local case. (ray-project#1760)
  Define string prefixes for all tables in the new GCS API (ray-project#1755)
  [rllib] Update RLlib to work with new actor scheduling behavior (ray-project#1754)
  Redirect output of all processes by default. (ray-project#1752)
  Add API for getting total cluster resources. (ray-project#1736)
  Always send actor creation tasks to the global scheduler. (ray-project#1757)
  Print error when actor takes too long to start, and refactor error me… (ray-project#1747)
  ...

# Conflicts:
#	python/ray/rllib/__init__.py
#	python/ray/rllib/dqn/dqn.py
#	python/ray/rllib/dqn/dqn_evaluator.py
#	python/ray/rllib/dqn/dqn_replay_evaluator.py
#	python/ray/rllib/optimizers/__init__.py
#	python/ray/rllib/tuned_examples/pong-dqn.yaml
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4 participants