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ci/official/utilities/cleanup_summary.sh
Shell Script - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Nov 08 17:50:27 GMT 2023 - 1.8K bytes - Viewed (0) -
ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
cat > $BATS_TEST_TMPDIR/ignore_deps_for_these_packages <<EOF //tensorflow/lite //tensorflow/compiler/mlir/lite //tensorflow/compiler/mlir/tfrt //tensorflow/core/runtime_fallback //tensorflow/core/tfrt //tensorflow/python/kernel_tests/signal //tensorflow/examples //tensorflow/tools/android //tensorflow/python/eager/benchmarks EOF
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.bazelrc
low/compiler/mlir/tfrt/transforms/mlrt,tensorflow/core/runtime_fallback,tensorflow/core/runtime_fallback/conversion,tensorflow/core/runtime_fallback/kernel,tensorflow/core/runtime_fallback/opdefs,tensorflow/core/runtime_fallback/runtime,tensorflow/core/runtime_fallback/util,tensorflow/core/runtime_fallback/test,tensorflow/core/runtime_fallback/test/gpu,tensorflow/core/runtime_fallback/test/saved_model,tensorflow/core/runtime_fallback/test/testdata,tensorflow/core/tfrt/stubs,tensorflow/core/tfrt/...
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tensorflow/c/eager/c_api_experimental_test.cc
TFE_CancelCallback callback1; callback1.callback = [](void* context) { ADD_FAILURE() << "Callback1 should be deregistered."; }; TFE_CancellationToken token1 = TFE_CancellationManagerGetToken(c_mgr); EXPECT_TRUE(TFE_CancellationManagerRegisterCallback(c_mgr, token1, &callback1, "callback1")); TFE_CancelCallback callback2;
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.github/workflows/issue-on-pr-rollback.yml
branches: - master permissions: {} jobs: create-issue-on-pr-rollback: 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
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tensorflow/c/experimental/filesystem/plugins/gcs/ram_file_block_cache.cc
TF_Status* status) { bool downloaded_block = false; auto reconcile_state = MakeCleanup([this, &downloaded_block, &key, &block] { // Perform this action in a cleanup callback to avoid locking mu_ after // locking block->mu. if (downloaded_block) { absl::MutexLock l(&mu_); // Do not update state if the block is already to be evicted. if (block->timestamp != 0) {
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Thu Jul 16 01:39:09 GMT 2020 - 11.1K bytes - Viewed (0) -
tensorflow/c/c_api_experimental.h
// Set XLA's internal BuildXlaOpsPassFlags.tf_xla_enable_lazy_compilation to the // value of 'enabled'. Also returns the original value of that flag. // // Use in tests to allow XLA to fallback to TF classic. This has global effect. TF_CAPI_EXPORT unsigned char TF_SetXlaEnableLazyCompilation( unsigned char enable); TF_CAPI_EXPORT unsigned char TF_SetTfXlaCpuGlobalJit(unsigned char enable);
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Apr 27 21:07:00 GMT 2023 - 15.1K bytes - Viewed (0) -
ci/official/utilities/code_check_full.bats
cat > $BATS_TEST_TMPDIR/ignore_deps_for_these_packages <<EOF //tensorflow/lite //tensorflow/compiler/mlir/lite //tensorflow/compiler/mlir/tfrt //tensorflow/core/runtime_fallback //tensorflow/core/tfrt //tensorflow/python/kernel_tests/signal //tensorflow/examples //tensorflow/tools/android //tensorflow/python/eager/benchmarks EOF
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tensorflow/c/eager/immediate_execution_context.h
virtual void ClearCachesAndThreadExecutors() = 0; // Initialize the step resource container for a training step. This is used // in current TF runtime. For tfrt, it is used by fallback op handler. virtual void StartStep() = 0; // Destroy the step resource container for a training step. virtual void EndStep() = 0; // Return the Eager Executor for current thread. Please note that Eager
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tensorflow/c/c_api_experimental.cc
// threadpool, so that we avoid the possibility of running the runner_ in the // threadpool of GPU event mgr, as that can trigger more callbacks to be // scheduled on that same threadpool, causing a deadlock in cases where the // caller of event_mgr->ThenExecute() blocks on the completion of the callback // (as in the case of ConstOp kernel creation on GPU, which involves copying a // CPU tensor to GPU).
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