mirror of
https://github.com/wassname/ray.git
synced 2026-07-02 21:56:20 +08:00
Eric Liang
313 lines
11 KiB
Python
313 lines
11 KiB
Python
import pytest
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import time
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import yaml
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import tempfile
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import shutil
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import unittest
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import ray
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from ray.tests.test_autoscaler import SMALL_CLUSTER, MockProvider, \
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MockProcessRunner
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from ray.autoscaler.autoscaler import StandardAutoscaler
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from ray.autoscaler.load_metrics import LoadMetrics
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from ray.autoscaler.node_provider import NODE_PROVIDERS
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from ray.autoscaler.commands import get_or_create_head_node
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from ray.autoscaler.tags import TAG_RAY_USER_NODE_TYPE
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from ray.autoscaler.resource_demand_scheduler import _utilization_score, \
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get_bin_pack_residual, get_instances_for
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from time import sleep
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TYPES_A = {
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"m4.large": {
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"node_config": {
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"FooProperty": 42,
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},
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"resources": {
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"CPU": 2
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},
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"max_workers": 10,
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},
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"m4.4xlarge": {
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"node_config": {},
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"resources": {
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"CPU": 16
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},
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"max_workers": 8,
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},
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"m4.16xlarge": {
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"node_config": {},
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"resources": {
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"CPU": 64
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},
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"max_workers": 4,
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},
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"p2.xlarge": {
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"node_config": {},
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"resources": {
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"CPU": 16,
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"GPU": 1
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},
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"max_workers": 10,
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},
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"p2.8xlarge": {
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"node_config": {},
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"resources": {
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"CPU": 32,
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"GPU": 8
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},
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"max_workers": 4,
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},
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}
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MULTI_WORKER_CLUSTER = dict(
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SMALL_CLUSTER, **{
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"available_node_types": TYPES_A,
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"head_node_type": "m4.large",
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"worker_default_node_type": "m4.large",
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})
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def test_util_score():
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assert _utilization_score({"CPU": 64}, [{"TPU": 16}]) is None
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assert _utilization_score({"GPU": 4}, [{"GPU": 2}]) == (0.5, 0.5)
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assert _utilization_score({"GPU": 4}, [{"GPU": 1}, {"GPU": 1}]) == \
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(0.5, 0.5)
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assert _utilization_score({"GPU": 2}, [{"GPU": 2}]) == (2, 2)
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assert _utilization_score({"GPU": 2}, [{"GPU": 1}, {"GPU": 1}]) == (2, 2)
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assert _utilization_score({"GPU": 2, "TPU": 1}, [{"GPU": 2}]) == (0, 1)
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assert _utilization_score({"CPU": 64}, [{"CPU": 64}]) == (64, 64)
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assert _utilization_score({"CPU": 64}, [{"CPU": 32}]) == (8, 8)
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assert _utilization_score({"CPU": 64}, [{"CPU": 16}, {"CPU": 16}]) == \
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(8, 8)
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def test_bin_pack():
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assert get_bin_pack_residual([], [{"GPU": 2}, {"GPU": 2}]) == \
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[{"GPU": 2}, {"GPU": 2}]
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assert get_bin_pack_residual([{"GPU": 2}], [{"GPU": 2}, {"GPU": 2}]) == \
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[{"GPU": 2}]
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assert get_bin_pack_residual([{"GPU": 4}], [{"GPU": 2}, {"GPU": 2}]) == []
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arg = [{"GPU": 2}, {"GPU": 2, "CPU": 2}]
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assert get_bin_pack_residual(arg, [{"GPU": 2}, {"GPU": 2}]) == []
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arg = [{"CPU": 2}, {"GPU": 2}]
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assert get_bin_pack_residual(arg, [{"GPU": 2}, {"GPU": 2}]) == [{"GPU": 2}]
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def test_get_instances_packing_heuristic():
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assert get_instances_for(TYPES_A, {}, 9999, [{"GPU": 8}]) == \
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[("p2.8xlarge", 1)]
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assert get_instances_for(TYPES_A, {}, 9999, [{"GPU": 1}] * 6) == \
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[("p2.8xlarge", 1)]
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assert get_instances_for(TYPES_A, {}, 9999, [{"GPU": 1}] * 4) == \
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[("p2.xlarge", 4)]
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assert get_instances_for(TYPES_A, {}, 9999, [{"CPU": 32, "GPU": 1}] * 3) \
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== [("p2.8xlarge", 3)]
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assert get_instances_for(TYPES_A, {}, 9999, [{"CPU": 64, "GPU": 1}] * 3) \
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== []
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assert get_instances_for(TYPES_A, {}, 9999, [{"CPU": 64}] * 3) == \
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[("m4.16xlarge", 3)]
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assert get_instances_for(TYPES_A, {}, 9999, [{"CPU": 64}, {"CPU": 1}]) \
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== [("m4.16xlarge", 1), ("m4.large", 1)]
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assert get_instances_for(
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TYPES_A, {}, 9999, [{"CPU": 64}, {"CPU": 9}, {"CPU": 9}]) == \
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[("m4.16xlarge", 1), ("m4.4xlarge", 2)]
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assert get_instances_for(TYPES_A, {}, 9999, [{"CPU": 16}] * 5) == \
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[("m4.16xlarge", 1), ("m4.4xlarge", 1)]
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assert get_instances_for(TYPES_A, {}, 9999, [{"CPU": 8}] * 10) == \
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[("m4.16xlarge", 1), ("m4.4xlarge", 1)]
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assert get_instances_for(TYPES_A, {}, 9999, [{"CPU": 1}] * 100) == \
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[("m4.16xlarge", 1), ("m4.4xlarge", 2), ("m4.large", 2)]
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assert get_instances_for(
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TYPES_A, {}, 9999, [{"GPU": 1}] + ([{"CPU": 1}] * 64)) == \
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[("m4.16xlarge", 1), ("p2.xlarge", 1)]
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assert get_instances_for(
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TYPES_A, {}, 9999, ([{"GPU": 1}] * 8) + ([{"CPU": 1}] * 64)) == \
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[("m4.16xlarge", 1), ("p2.8xlarge", 1)]
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def test_get_instances_respects_max_limit():
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types = {
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"m4.large": {
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"resources": {
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"CPU": 2
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},
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"max_workers": 10,
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},
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"gpu": {
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"resources": {
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"GPU": 1
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},
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"max_workers": 99999,
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},
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}
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assert get_instances_for(types, {}, 2, [{"CPU": 1}] * 10) == \
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[("m4.large", 2)]
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assert get_instances_for(types, {"m4.large": 9999}, 9999, [{
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"CPU": 1
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}] * 10) == []
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assert get_instances_for(types, {"m4.large": 0}, 9999, [{
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"CPU": 1
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}] * 10) == [("m4.large", 5)]
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assert get_instances_for(types, {"m4.large": 7}, 4, [{
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"CPU": 1
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}] * 10) == [("m4.large", 3)]
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assert get_instances_for(types, {"m4.large": 7}, 2, [{
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"CPU": 1
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}] * 10) == [("m4.large", 2)]
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class AutoscalingTest(unittest.TestCase):
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def setUp(self):
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NODE_PROVIDERS["mock"] = \
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lambda config: self.create_provider
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self.provider = None
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self.tmpdir = tempfile.mkdtemp()
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def tearDown(self):
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self.provider = None
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del NODE_PROVIDERS["mock"]
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shutil.rmtree(self.tmpdir)
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ray.shutdown()
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def waitForNodes(self, expected, comparison=None, tag_filters={}):
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MAX_ITER = 50
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for i in range(MAX_ITER):
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n = len(self.provider.non_terminated_nodes(tag_filters))
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if comparison is None:
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comparison = self.assertEqual
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try:
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comparison(n, expected)
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return
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except Exception:
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if i == MAX_ITER - 1:
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raise
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time.sleep(.1)
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def create_provider(self, config, cluster_name):
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assert self.provider
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return self.provider
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def write_config(self, config):
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path = self.tmpdir + "/simple.yaml"
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with open(path, "w") as f:
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f.write(yaml.dump(config))
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return path
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def testGetOrCreateMultiNodeType(self):
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config_path = self.write_config(MULTI_WORKER_CLUSTER)
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self.provider = MockProvider()
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runner = MockProcessRunner()
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get_or_create_head_node(
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MULTI_WORKER_CLUSTER,
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config_path,
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no_restart=False,
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restart_only=False,
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yes=True,
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override_cluster_name=None,
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_provider=self.provider,
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_runner=runner)
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self.waitForNodes(1)
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runner.assert_has_call("1.2.3.4", "init_cmd")
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runner.assert_has_call("1.2.3.4", "head_setup_cmd")
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runner.assert_has_call("1.2.3.4", "start_ray_head")
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self.assertEqual(self.provider.mock_nodes[0].node_type, "m4.large")
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self.assertEqual(
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self.provider.mock_nodes[0].node_config.get("FooProperty"), 42)
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self.assertEqual(
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self.provider.mock_nodes[0].node_config.get("TestProp"), 1)
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self.assertEqual(
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self.provider.mock_nodes[0].tags.get(TAG_RAY_USER_NODE_TYPE),
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"m4.large")
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def testScaleUpMinSanity(self):
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config_path = self.write_config(MULTI_WORKER_CLUSTER)
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self.provider = MockProvider()
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runner = MockProcessRunner()
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autoscaler = StandardAutoscaler(
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config_path,
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LoadMetrics(),
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max_failures=0,
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process_runner=runner,
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update_interval_s=0)
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assert len(self.provider.non_terminated_nodes({})) == 0
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autoscaler.update()
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self.waitForNodes(2)
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autoscaler.update()
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self.waitForNodes(2)
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def testRequestBundles(self):
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config = MULTI_WORKER_CLUSTER.copy()
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config["min_workers"] = 0
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config["max_workers"] = 50
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config_path = self.write_config(config)
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self.provider = MockProvider()
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runner = MockProcessRunner()
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autoscaler = StandardAutoscaler(
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config_path,
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LoadMetrics(),
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max_failures=0,
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process_runner=runner,
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update_interval_s=0)
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assert len(self.provider.non_terminated_nodes({})) == 0
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autoscaler.update()
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self.waitForNodes(0)
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autoscaler.request_resources([{"CPU": 1}])
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autoscaler.update()
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self.waitForNodes(1)
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assert self.provider.mock_nodes[0].node_type == "m4.large"
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autoscaler.request_resources([{"GPU": 8}])
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autoscaler.update()
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self.waitForNodes(2)
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assert self.provider.mock_nodes[1].node_type == "p2.8xlarge"
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autoscaler.request_resources([{"CPU": 32}] * 4)
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autoscaler.update()
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self.waitForNodes(4)
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assert self.provider.mock_nodes[2].node_type == "m4.16xlarge"
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assert self.provider.mock_nodes[3].node_type == "m4.16xlarge"
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def testResourcePassing(self):
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config = MULTI_WORKER_CLUSTER.copy()
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config["min_workers"] = 0
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config["max_workers"] = 50
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config_path = self.write_config(config)
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self.provider = MockProvider()
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runner = MockProcessRunner()
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autoscaler = StandardAutoscaler(
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config_path,
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LoadMetrics(),
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max_failures=0,
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process_runner=runner,
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update_interval_s=0)
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assert len(self.provider.non_terminated_nodes({})) == 0
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autoscaler.update()
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self.waitForNodes(0)
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autoscaler.request_resources([{"CPU": 1}])
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autoscaler.update()
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self.waitForNodes(1)
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assert self.provider.mock_nodes[0].node_type == "m4.large"
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autoscaler.request_resources([{"GPU": 8}])
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autoscaler.update()
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self.waitForNodes(2)
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assert self.provider.mock_nodes[1].node_type == "p2.8xlarge"
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# TODO (Alex): Autoscaler creates the node during one update then
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# starts the updater in the enxt update. The sleep is largely
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# unavoidable because the updater runs in its own thread and we have no
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# good way of ensuring that the commands are sent in time.
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autoscaler.update()
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sleep(0.1)
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# These checks are done separately because we have no guarantees on the
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# order the dict is serialized in.
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runner.assert_has_call("172.0.0.0", "RAY_OVERRIDE_RESOURCES=")
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runner.assert_has_call("172.0.0.0", "CPU: 2")
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runner.assert_has_call("172.0.0.1", "RAY_OVERRIDE_RESOURCES=")
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runner.assert_has_call("172.0.0.1", "CPU: 32")
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runner.assert_has_call("172.0.0.1", "GPU: 8")
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if __name__ == "__main__":
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import sys
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sys.exit(pytest.main(["-v", __file__]))
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