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guava-tests/test/com/google/common/primitives/FloatsTest.java
testRotate(new float[] {1}, 0, 0, 1, new float[] {1}); testRotate(new float[] {1}, 1, 0, 1, new float[] {1}); testRotate(new float[] {1}, 1, 1, 1, new float[] {1}); // Rotate the central 5 elements, leaving the ends as-is testRotate(new float[] {0, 1, 2, 3, 4, 5, 6}, -6, 1, 6, new float[] {0, 2, 3, 4, 5, 1, 6}); testRotate(new float[] {0, 1, 2, 3, 4, 5, 6}, -1, 1, 6, new float[] {0, 2, 3, 4, 5, 1, 6});
Registered: Fri Nov 01 12:43:10 UTC 2024 - Last Modified: Sat Oct 19 02:56:12 UTC 2024 - 30.3K bytes - Viewed (0) -
guava-tests/test/com/google/common/primitives/LongsTest.java
testRotate(new long[] {1}, 0, 0, 1, new long[] {1}); testRotate(new long[] {1}, 1, 0, 1, new long[] {1}); testRotate(new long[] {1}, 1, 1, 1, new long[] {1}); // Rotate the central 5 elements, leaving the ends as-is testRotate(new long[] {0, 1, 2, 3, 4, 5, 6}, -6, 1, 6, new long[] {0, 2, 3, 4, 5, 1, 6}); testRotate(new long[] {0, 1, 2, 3, 4, 5, 6}, -1, 1, 6, new long[] {0, 2, 3, 4, 5, 1, 6});
Registered: Fri Nov 01 12:43:10 UTC 2024 - Last Modified: Sat Oct 19 02:56:12 UTC 2024 - 29.8K bytes - Viewed (0) -
android/guava-tests/test/com/google/common/util/concurrent/JSR166TestCase.java
* <li>These tests are "conformance tests", and do not attempt to test throughput, latency, * scalability or other performance factors (see the separate "jtreg" tests for a set intended * to check these for the most central aspects of functionality.) So, most tests use the * smallest sensible numbers of threads, collection sizes, etc needed to check basic * conformance.
Registered: Fri Nov 01 12:43:10 UTC 2024 - Last Modified: Thu Oct 17 02:42:09 UTC 2024 - 37.9K bytes - Viewed (0) -
docs/en/docs/async.md
And as most of the execution time is taken by actual work (instead of waiting), and the work in a computer is done by a <abbr title="Central Processing Unit">CPU</abbr>, they call these problems "CPU bound". --- Common examples of CPU bound operations are things that require complex math processing. For example:
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Wed Aug 28 23:33:37 UTC 2024 - 23.5K bytes - Viewed (0) -
docs/fr/docs/async.md
Et comme la plupart du temps d'exécution est pris par du "vrai" travail (et non de l'attente), et que le travail dans un ordinateur est fait par un <abbr title="Central Processing Unit">CPU</abbr>, ce sont des problèmes dits "CPU bound". --- Des exemples communs d'opérations "CPU bounds" sont les procédés qui requièrent des traitements mathématiques complexes. Par exemple :
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Tue Aug 06 04:48:30 UTC 2024 - 25.4K bytes - Viewed (0) -
tensorflow/BUILD
"//learning/brain/mlir/...", "//learning/brain/tfrt/...", "//learning/lib/ami/simple_ml/...", "//learning/pathways/...", "//learning/serving/contrib/tfrt/mlir/canonical_ops/...", "//learning/serving/experimental/remote_predict/...", "//perftools/accelerators/xprof/convert/...", "//perftools/accelerators/xprof/integration_tests/...",
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Wed Oct 16 05:28:35 UTC 2024 - 53.5K bytes - Viewed (0) -
guava-tests/test/com/google/common/util/concurrent/JSR166TestCase.java
* <li>These tests are "conformance tests", and do not attempt to test throughput, latency, * scalability or other performance factors (see the separate "jtreg" tests for a set intended * to check these for the most central aspects of functionality.) So, most tests use the * smallest sensible numbers of threads, collection sizes, etc needed to check basic * conformance.
Registered: Fri Nov 01 12:43:10 UTC 2024 - Last Modified: Thu Oct 17 02:42:09 UTC 2024 - 37.9K bytes - Viewed (0) -
docs/de/docs/async.md
Und da die meiste Ausführungszeit durch tatsächliche Arbeit (anstatt durch Warten) in Anspruch genommen wird und die Arbeit in einem Computer von einer <abbr title="Central Processing Unit – Zentrale Recheneinheit">CPU</abbr> erledigt wird, werden diese Probleme als „CPU-lastig“ („CPU bound“) bezeichnet. ---
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Tue Aug 06 04:48:30 UTC 2024 - 26.6K bytes - Viewed (0) -
docs/zh/docs/async.md
无论是否轮流执行(并发),都需要相同的时间来完成,而你也会完成相同的工作量。 但在这种情况下,如果你能带上 8 名前收银员/厨师,现在是清洁工一起清扫,他们中的每一个人(加上你)都能占据房子的一个区域来清扫,你就可以在额外的帮助下并行的更快地完成所有工作。 在这个场景中,每个清洁工(包括您)都将是一个处理器,完成这个工作的一部分。 由于大多数执行时间是由实际工作(而不是等待)占用的,并且计算机中的工作是由 <abbr title="Central Processing Unit">CPU</abbr> 完成的,所以他们称这些问题为"CPU 密集型"。 --- CPU 密集型操作的常见示例是需要复杂的数学处理。 例如: * **音频**或**图像**处理; * **计算机视觉**: 一幅图像由数百万像素组成,每个像素有3种颜色值,处理通常需要同时对这些像素进行计算;
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Tue Aug 06 04:48:30 UTC 2024 - 21.1K bytes - Viewed (0) -
configure.py
These files could interfere with Bazel parsing. """ makefile_download_dir = os.path.join(_TF_WORKSPACE_ROOT, 'tensorflow', 'contrib', 'makefile', 'downloads') if os.path.isdir(makefile_download_dir): for root, _, filenames in os.walk(makefile_download_dir): for f in filenames: if f.endswith('BUILD'):
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Wed Oct 02 22:16:02 UTC 2024 - 48.2K bytes - Viewed (0)