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tensorflow/c/experimental/filesystem/plugins/gcs/ram_file_block_cache_test.cc
// but file "b" is not stale yet. Thus, once the pruning thread wakes up (in // one second of wall time), it should remove "a" and leave "b" alone. uint64 start = Env::Default()->NowSeconds(); do { Env::Default()->SleepForMicroseconds(100000); } while (cache.CacheSize() == 24 && Env::Default()->NowSeconds() - start < 3); // There should be one block left in the cache, and it should be the first
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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# > TF's gen_api_init_files has a genrule to run the core TensorFlow code # > on the host machine. If we don't have --distinct_host_configuration=false, # > the core TensorFlow code will be built once for the host and once for the # > target platform. # See also https://docs.bazel.build/versions/master/guide.html#build-configurations-and-cross-compilation build --distinct_host_configuration=false
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ci/official/wheel_test/README.md
description will be provided once it's integrated into presubmit. ### test_import_api_packages This Python test verifies whether the API v2 packages can be imported from the current build. It utilizes the `_api/v2/api_packages.txt` list of packages from the local wheel file specified in the `requirements_lock_<python_version>.txt`. Packages are imported one by one in alphabetical order during runtime.
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tensorflow/c/experimental/filesystem/modular_filesystem_test.cc
static std::vector<std::string>* schemes = new std::vector<std::string>; return schemes; } // `INSTANTIATE_TEST_SUITE_P` is called once for every `TEST_P`. However, we // only want to analyze the user provided schemes and those that are registered // only once. Hence, this function keeping another static pointer to a vector // which contains only the schemes under test. //
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CONTRIBUTING.md
your response for more than 2 weeks. **4. Approved** - Once the PR is approved, it gets `kokoro:force-run` label applied and it initiates CI/CD tests. - We can't move forward if these tests fail. - In such situations, we may request you to make further changes to your PR for the tests to pass. - Once the tests pass, we now bring all the code into the internal code base,
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# > the core TensorFlow code will be built once for the host and once for the # > target platform. # See also https://docs.bazel.build/versions/master/guide.html#build-configurations-and-cross-compilation build --distinct_host_configuration=false # Disable clang extension that rejects type definitions within offsetof. # This was added in clang-16 by https://reviews.llvm.org/D133574.
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tensorflow/c/experimental/filesystem/BUILD
# Experimental filesystem C APIs for TensorFlow. # Will be moved in proper place once all filesystems are converted to the # modular framework. load("//tensorflow:tensorflow.bzl", "tf_cc_test") load("//tensorflow/core/platform:rules_cc.bzl", "cc_library") package( # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"], licenses = ["notice"], ) # This is only for plugins cc_library( name = "filesystem_interface",
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ci/official/containers/linux_arm64/cuda.packages.txt
# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation libcudnn8=8.9.6.50-1+cuda12.2 libcudnn8-dev=8.9.6.50-1+cuda12.2 # This can be removed once NVIDIA publishes a cuda-12.3.2 Docker image. # For now it ensures that we install at least version 12.3.107 of PTXAS, # since 12.3.103 has a bug.
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tensorflow/c/checkpoint_reader.h
std::pair<std::unique_ptr<TensorSliceReader::VarToShapeMap>, std::unique_ptr<TensorSliceReader::VarToDataTypeMap> > BuildV2VarMaps(); // Invariant: exactly one of "reader_" and "v2_reader_" is non-null. std::unique_ptr<TensorSliceReader> reader_; std::unique_ptr<BundleReader> v2_reader_; std::unique_ptr<TensorSliceReader::VarToShapeMap> var_to_shape_map_;
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tensorflow/c/c_api_test.cc
TF_Graph* graph = TF_NewGraph(); // Make two scalar constants. TF_Operation* one = ScalarConst(1, graph, s, "one"); ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s); TF_Operation* two = ScalarConst(2, graph, s, "two"); ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s); // Add oper. TF_Operation* add = Add(one, two, graph, s, "add"); ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
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