update version to 0.2.7
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zhuofeng
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372eb295e9
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140
dedependency-py4j.patch
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140
dedependency-py4j.patch
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From 9584ff6ea8b4127e1fb7eb9ca4302eb553918c37 Mon Sep 17 00:00:00 2001
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From: zhuofeng <zhuofeng2@huawei.com>
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Date: Sat, 29 Jul 2023 11:20:51 +0800
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Subject: [PATCH] 2
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---
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hyperopt/spark.py | 23 +++++++---------
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hyperopt/tests/integration/test_spark.py | 34 ------------------------
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setup.py | 1 -
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3 files changed, 9 insertions(+), 49 deletions(-)
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diff --git a/hyperopt/spark.py b/hyperopt/spark.py
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index 7c1e739..d90d36f 100644
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--- a/hyperopt/spark.py
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+++ b/hyperopt/spark.py
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@@ -8,8 +8,6 @@ from hyperopt import base, fmin, Trials
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from hyperopt.base import validate_timeout, validate_loss_threshold
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from hyperopt.utils import coarse_utcnow, _get_logger, _get_random_id
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-from py4j.clientserver import ClientServer
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-
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try:
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from pyspark.sql import SparkSession
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from pyspark.util import VersionUtils
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@@ -88,12 +86,13 @@ class SparkTrials(Trials):
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else spark_session
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)
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self._spark_context = self._spark.sparkContext
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- self._spark_pinned_threads_enabled = isinstance(
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- self._spark_context._gateway, ClientServer
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- )
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# The feature to support controlling jobGroupIds is in SPARK-22340
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self._spark_supports_job_cancelling = (
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- self._spark_pinned_threads_enabled
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+ _spark_major_minor_version
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+ >= (
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+ 3,
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+ 2,
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+ )
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or hasattr(self._spark_context.parallelize([1]), "collectWithJobGroup")
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)
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spark_default_parallelism = self._spark_context.defaultParallelism
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@@ -479,7 +478,7 @@ class _SparkFMinState:
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try:
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worker_rdd = self.spark.sparkContext.parallelize([0], 1)
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if self.trials._spark_supports_job_cancelling:
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- if self.trials._spark_pinned_threads_enabled:
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+ if _spark_major_minor_version >= (3, 2):
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spark_context = self.spark.sparkContext
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spark_context.setLocalProperty(
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"spark.jobGroup.id", self._job_group_id
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@@ -520,14 +519,10 @@ class _SparkFMinState:
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# The exceptions captured in run_task_on_executor would be returned in the result_or_e
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finish_trial_run(result_or_e)
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- if self.trials._spark_pinned_threads_enabled:
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- try:
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- # pylint: disable=no-name-in-module,import-outside-toplevel
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- from pyspark import inheritable_thread_target
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+ if _spark_major_minor_version >= (3, 2):
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+ from pyspark import inheritable_thread_target
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- run_task_thread = inheritable_thread_target(run_task_thread)
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- except ImportError:
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- pass
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+ run_task_thread = inheritable_thread_target(run_task_thread)
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task_thread = threading.Thread(target=run_task_thread)
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task_thread.setDaemon(True)
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diff --git a/hyperopt/tests/integration/test_spark.py b/hyperopt/tests/integration/test_spark.py
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index 9ea0f19..3146d74 100644
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--- a/hyperopt/tests/integration/test_spark.py
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+++ b/hyperopt/tests/integration/test_spark.py
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@@ -14,7 +14,6 @@ from six import StringIO
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from hyperopt import SparkTrials, anneal, base, fmin, hp, rand
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from hyperopt.tests.unit.test_fmin import test_quadratic1_tpe
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-from py4j.clientserver import ClientServer
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@contextlib.contextmanager
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@@ -62,7 +61,6 @@ class BaseSparkContext:
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.getOrCreate()
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)
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cls._sc = cls._spark.sparkContext
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- cls._pin_mode_enabled = isinstance(cls._sc._gateway, ClientServer)
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cls.checkpointDir = tempfile.mkdtemp()
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cls._sc.setCheckpointDir(cls.checkpointDir)
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# Small tests run much faster with spark.sql.shuffle.partitions=4
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@@ -590,35 +588,3 @@ class FMinTestCase(unittest.TestCase, BaseSparkContext):
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call_count = len(os.listdir(output_dir))
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self.assertEqual(NUM_TRIALS, call_count)
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-
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- def test_pin_thread_off(self):
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- if self._pin_mode_enabled:
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- raise unittest.SkipTest()
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-
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- spark_trials = SparkTrials(parallelism=2)
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- self.assertFalse(spark_trials._spark_pinned_threads_enabled)
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- self.assertTrue(spark_trials._spark_supports_job_cancelling)
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- fmin(
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- fn=lambda x: x + 1,
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- space=hp.uniform("x", -1, 1),
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- algo=rand.suggest,
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- max_evals=5,
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- trials=spark_trials,
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- )
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- self.assertEqual(spark_trials.count_successful_trials(), 5)
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-
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- def test_pin_thread_on(self):
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- if not self._pin_mode_enabled:
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- raise unittest.SkipTest()
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-
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- spark_trials = SparkTrials(parallelism=2)
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- self.assertTrue(spark_trials._spark_pinned_threads_enabled)
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- self.assertTrue(spark_trials._spark_supports_job_cancelling)
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- fmin(
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- fn=lambda x: x + 1,
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- space=hp.uniform("x", -1, 1),
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- algo=rand.suggest,
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- max_evals=5,
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- trials=spark_trials,
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- )
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- self.assertEqual(spark_trials.count_successful_trials(), 5)
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diff --git a/setup.py b/setup.py
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index d21c3a1..cdfcd62 100644
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--- a/setup.py
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+++ b/setup.py
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@@ -48,7 +48,6 @@ setuptools.setup(
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"future",
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"tqdm",
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"cloudpickle",
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- "py4j",
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],
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extras_require={
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"SparkTrials": "pyspark",
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--
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2.37.3.1
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Binary file not shown.
BIN
hyperopt-0.2.7.tar.gz
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BIN
hyperopt-0.2.7.tar.gz
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Binary file not shown.
@ -1,11 +1,14 @@
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%global _empty_manifest_terminate_build 0
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Name: python-hyperopt
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Version: 0.2.4
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Version: 0.2.7
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Release: 1
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Summary: Distributed Asynchronous Hyperparameter Optimization
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License: BSD
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URL: http://hyperopt.github.com/hyperopt/
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Source0: https://files.pythonhosted.org/packages/b0/69/ee6a5596e925778e5aaaaf2eda3c07ac362aaad43ff66a75bef02b9f6bf6/hyperopt-0.2.4.tar.gz
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Source0: https://files.pythonhosted.org/packages/58/75/0c4712e3f3a21c910778b8f9f4622601a823cefcae24181467674a0352f9/hyperopt-0.2.7.tar.gz
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Patch1: dedependency-py4j.patch
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BuildArch: noarch
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Requires: python3-numpy
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@ -48,7 +51,7 @@ search spaces, which may include real-valued, discrete, and conditional
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dimensions.
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%prep
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%autosetup -n hyperopt-0.2.4
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%autosetup -n hyperopt-%{version} -p1
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%build
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%py3_build
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@ -88,5 +91,8 @@ mv %{buildroot}/doclist.lst .
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%{_docdir}/*
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%changelog
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* Sat Jul 29 2023 zhuofeng <zhuofeng2@huawei.com> - 0.2.7-1
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- Update package to version 0.2.7
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* Wed Sep 30 2020 Python_Bot <Python_Bot@openeuler.org>
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- Package Spec generated
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