mirror of
https://github.com/wassname/ray.git
synced 2026-06-28 22:37:36 +08:00
Robert Nishihara
61139e1509
* Implement GPU IDs and fractional resources. * Add documentation and python exceptions. * Fix signed/unsigned comparison. * Fix linting. * Fixes from rebase. * Re-enable tests that use ray.wait. * Don't kill the raylet if an infeasible task is submitted. * Ignore tests that require better load balancing. * Linting * Ignore array test. * Ignore stress test reconstructions tests. * Don't kill node manager if remote node manager disconnects. * Ignore more stress tests. * Naming changes * Remove outdated todo * Small fix * Re-enable test. * Linting * Fix resource bookkeeping for blocked tasks. * Fix linting * Fix Java client. * Ignore test * Ignore put error tests
64 lines
2.5 KiB
Python
64 lines
2.5 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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"""Ray constants used in the Python code."""
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import os
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def env_integer(key, default):
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if key in os.environ:
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return int(os.environ(key))
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return default
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# If a remote function or actor (or some other export) has serialized size
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# greater than this quantity, print an warning.
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PICKLE_OBJECT_WARNING_SIZE = 10**7
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# The maximum resource quantity that is allowed. TODO(rkn): This could be
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# relaxed, but the current implementation of the node manager will be slower
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# for large resource quantities due to bookkeeping of specific resource IDs.
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MAX_RESOURCE_QUANTITY = 512
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# Different types of Ray errors that can be pushed to the driver.
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# TODO(rkn): These should be defined in flatbuffers and must be synced with
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# the existing C++ definitions.
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WAIT_FOR_CLASS_PUSH_ERROR = "wait_for_class"
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PICKLING_LARGE_OBJECT_PUSH_ERROR = "pickling_large_object"
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WAIT_FOR_FUNCTION_PUSH_ERROR = "wait_for_function"
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TASK_PUSH_ERROR = "task"
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REGISTER_REMOTE_FUNCTION_PUSH_ERROR = "register_remote_function"
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FUNCTION_TO_RUN_PUSH_ERROR = "function_to_run"
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VERSION_MISMATCH_PUSH_ERROR = "version_mismatch"
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CHECKPOINT_PUSH_ERROR = "checkpoint"
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REGISTER_ACTOR_PUSH_ERROR = "register_actor"
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WORKER_CRASH_PUSH_ERROR = "worker_crash"
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WORKER_DIED_PUSH_ERROR = "worker_died"
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PUT_RECONSTRUCTION_PUSH_ERROR = "put_reconstruction"
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HASH_MISMATCH_PUSH_ERROR = "object_hash_mismatch"
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# Abort autoscaling if more than this number of errors are encountered. This
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# is a safety feature to prevent e.g. runaway node launches.
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AUTOSCALER_MAX_NUM_FAILURES = env_integer("AUTOSCALER_MAX_NUM_FAILURES", 5)
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# The maximum number of nodes to launch in a single request.
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# Multiple requests may be made for this batch size, up to
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# the limit of AUTOSCALER_MAX_CONCURRENT_LAUNCHES.
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AUTOSCALER_MAX_LAUNCH_BATCH = env_integer("AUTOSCALER_MAX_LAUNCH_BATCH", 5)
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# Max number of nodes to launch at a time.
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AUTOSCALER_MAX_CONCURRENT_LAUNCHES = env_integer(
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"AUTOSCALER_MAX_CONCURRENT_LAUNCHES", 10)
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# Interval at which to perform autoscaling updates.
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AUTOSCALER_UPDATE_INTERVAL_S = env_integer("AUTOSCALER_UPDATE_INTERVAL_S", 5)
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# The autoscaler will attempt to restart Ray on nodes it hasn't heard from
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# in more than this interval.
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AUTOSCALER_HEARTBEAT_TIMEOUT_S = env_integer("AUTOSCALER_HEARTBEAT_TIMEOUT_S",
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30)
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# Max number of retries to AWS (default is 5, time increases exponentially)
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BOTO_MAX_RETRIES = env_integer("BOTO_MAX_RETRIES", 12)
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