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Alex Wu
40 lines
1.4 KiB
Python
40 lines
1.4 KiB
Python
import ray
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from ray.monitor import parse_resource_demands
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def test_parse_resource_demands():
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resource_load_by_shape = ray.gcs_utils.ResourceLoad(resource_demands=[
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ray.gcs_utils.ResourceDemand(
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shape={"CPU": 1},
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num_ready_requests_queued=1,
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num_infeasible_requests_queued=0,
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backlog_size=0),
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ray.gcs_utils.ResourceDemand(
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shape={"CPU": 2},
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num_ready_requests_queued=1,
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num_infeasible_requests_queued=0,
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backlog_size=1),
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ray.gcs_utils.ResourceDemand(
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shape={"CPU": 3},
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num_ready_requests_queued=0,
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num_infeasible_requests_queued=1,
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backlog_size=2),
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ray.gcs_utils.ResourceDemand(
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shape={"CPU": 4},
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num_ready_requests_queued=1,
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num_infeasible_requests_queued=1,
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backlog_size=2),
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])
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waiting, infeasible = \
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parse_resource_demands(resource_load_by_shape)
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assert waiting.count({"CPU": 1}) == 1
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assert waiting.count({"CPU": 2}) == 2
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assert infeasible.count({"CPU": 3}) == 3
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# The {"CPU": 4} case here is inconsistent, but could happen. Since the
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# heartbeats are eventually consistent, we won't worry about whether it's
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# counted as infeasible or waiting, as long as it's accounted for and
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# doesn't cause an error.
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assert len(waiting + infeasible) == 10
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