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.github/workflows/arm-ci.yml
permissions: contents: read jobs: build: # Don't do this in forks, and if labeled, only for 'kokoro:force-run' if: github.repository == 'tensorflow/tensorflow' && (github.event.action != 'labeled' || (github.event.action == 'labeled' && github.event.label.name == 'kokoro:force-run')) runs-on: [self-hosted, linux, ARM64] strategy: matrix: pyver: ['3.10'] steps:
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ci/official/utilities/generate_index_html.sh
</ul> <h2>Googlers-Only Links</h2> <ul> <li><a href="http://sponge2/$KOKORO_BUILD_ID">Sponge2</a></li> <li><a href="http://sponge/target:$KOKORO_JOB_NAME">Sponge - recent jobs</a></li> <li><a href="http://fusion2/ci/kokoro/prod:$(echo "$KOKORO_JOB_NAME" | sed 's!/!%2F!g')">Test Fusion - recent jobs</a></li> <li><a href="http://cs/f:devtools/kokoro/config/prod/$KOKORO_JOB_NAME">Codesearch - job definition</a></li>
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tensorflow/c/experimental/filesystem/plugins/gcs/expiring_lru_cache_test.cc
cache.Insert(key, 41); env->SetNowSeconds(2); cache.Insert(key, 42); // 1 second after the most recent insertion, the entry is still valid. env->SetNowSeconds(3); int value = 0; EXPECT_TRUE(cache.Lookup(key, &value)); EXPECT_EQ(value, 42); // 2 seconds after the most recent insertion, the entry is no longer valid. env->SetNowSeconds(4); EXPECT_FALSE(cache.Lookup(key, &value));
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.github/workflows/issue-on-pr-rollback.yml
runs-on: ubuntu-latest permissions: contents: read issues: write pull-requests: read if: | github.repository == 'tensorflow/tensorflow' && startsWith(github.event.head_commit.message, 'Rollback of PR #') steps: - name: Checkout repo uses: actions/checkout@755da8c3cf115ac066823e79a1e1788f8940201b # v3.2.0 - name: Create a new Github Issue
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.github/bot_config.yml
* Try Google Colab to use TensorFlow. * The easiest way to use TF will be to switch to [google colab](https://colab.sandbox.google.com/notebooks/welcome.ipynb#recent=true). You get pre-installed latest stable TF version. Also you can use ```pip install``` to install any other preferred TF version.
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CONTRIBUTING.md
you're running the same code that you're testing: * Use an up to date [tf-nightly](https://pypi.org/project/tf-nightly/) `pip install -U tf-nightly` * Rebase your pull request onto a recent pull from [TensorFlow's](https://github.com/tensorflow/tensorflow) master branch. 2. If you are changing the code and the docstring of a class/function/method, then you will need to
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tensorflow/c/experimental/next_pluggable_device/c_api.h
TF_CoordinationServiceAgent* agent); TF_CAPI_EXPORT extern void TF_CoordinationServiceInsertKeyValue( const char* key, int64_t key_size, const char* value, int64_t value_size, TF_CoordinationServiceAgent* agent, TF_Status* status); // Obtains key-value from coordination service agent. The returned `TF_Buffer` // is a newly allocated buffer to hold the string key-value, and caller is
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tensorflow/c/eager/c_api_experimental.cc
tensorflow::unwrap(ctx)->GetDistributedManager(); tsl::CoordinationServiceAgent* coord_agent = dist_mgr->GetCoordinationServiceAgent(); if (coord_agent == nullptr) { status->status = tensorflow::errors::FailedPrecondition( "Coordination service agent is not enabled."); return; } status->status = coord_agent->InsertKeyValue(key, value); }
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LICENSE
## Some of TensorFlow's code is derived from Caffe, which is subject to the following copyright notice: COPYRIGHT All contributions by the University of California: Copyright (c) 2014, The Regents of the University of California (Regents) All rights reserved. All other contributions: Copyright (c) 2014, the respective contributors All rights reserved.
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RELEASE.md
`tf.math.rsqrt`, `tf.math.segment_max`, `tf.math.segment_mean`, `tf.math.segment_min`, `tf.math.segment_prod`, `tf.math.segment_sum`, `tf.math.sin`, `tf.math.sinh`, `tf.math.softplus`, `tf.math.softsign`, `tf.math.squared_difference`, `tf.math.tan`, `tf.math.unsorted_segment_max`, `tf.math.unsorted_segment_min`, `tf.math.unsorted_segment_prod`, `tf.math.unsorted_segment_sum`,
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