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tensorflow/c/experimental/filesystem/modular_filesystem_test.cc
// (or, if none is supplied, all existing schemes are used). As a scheme can // become available after a shared object with a filesystem implementation is // loaded, we can only check for availability after all arguments have been // parsed. // // Furthermore, as `INSTANTIATE_TEST_SUITE_P` needs to be at global level and we // don't want to have a `std::vector<std::string>` at global level, we use a
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri May 27 20:25:58 GMT 2022 - 71K bytes - Viewed (0) -
ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
} @test "Pip package generated license includes all dependencies' licenses" { do_external_licenses_check \ "//tensorflow/tools/pip_package:build_pip_package" \ "//tensorflow/tools/pip_package:licenses" } @test "Libtensorflow generated license includes all dependencies' licenses" { do_external_licenses_check \ "//tensorflow:libtensorflow.so" \ "//tensorflow/tools/lib_package:clicenses_generate" }
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ci/official/README.md
- Nightly jobs (Run nightly on the `nightly` branch) - Uses `wheel.sh`, `libtensorflow.sh`, `code_check_full.sh` - Continuous jobs (Run on every GitHub commit) - Uses `pycpp.sh` - Presubmit jobs (Run on every GitHub PR) - Uses `pycpp.sh`, `code_check_changed_files.sh` These "env" files match up with an environment matrix that roughly covers: - Different Python versions
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ci/official/containers/linux_arm64/devel.usertools/rename_and_verify_wheels.sh
# Check and rename wheels with auditwheel. Inserts the platform tags like # "manylinux_xyz" into the wheel filename. set -euxo pipefail for wheel in /tf/pkg/*.whl; do echo "Checking and renaming $wheel..." time python3 -m auditwheel repair --plat manylinux2014_aarch64 "$wheel" --wheel-dir /tf/pkg 2>&1 | tee check.txt # We don't need the original wheel if it was renamed
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CONTRIBUTING.md
**1. New PR** - As a contributor, you submit a New PR on GitHub. - We inspect every incoming PR and add certain labels to the PR such as `size:`, `comp:` etc. At this stage we check if the PR is valid and meets certain quality requirements. For example, we check if the CLA is signed, PR has sufficient description, if applicable unit tests are added, if it is a reasonable contribution (meaning it is not a single liner cosmetic PR).
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tensorflow/c/eager/c_api_experimental_reader_test.cc
auto* counter = CreateCounter0(counter_name); auto* reader = TFE_MonitoringNewCounterReader(counter_name); IncrementCounter0(counter); int64_t actual = TFE_MonitoringReadCounter0(reader); CHECK_EQ(actual, 1); } TEST(CAPI, MonitoringCellReader1) { auto counter_name = "test/counter1"; auto label_name = "test/label"; auto* counter = CreateCounter1(counter_name, label_name);
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.github/workflows/release-branch-cherrypick.yml
# Usage: Go to # https://github.com/tensorflow/tensorflow/actions/workflows/release-branch-cherrypick.yml # and click "Run Workflow." Leave "Use Workflow From" set to "master", then # input the branch name and paste the cherry-pick commit and click Run. A PR # will be created. name: Release Branch Cherrypick on: workflow_dispatch: inputs:
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ci/official/wheel_test/update_requirements.sh
# -e: abort script if one command fails # -u: error if undefined variable used # -o pipefail: entire command fails if pipe fails. watch out for yes | ... # -o history: record shell history set -euo pipefail -o history # Check for required arguments if [ -z "$1" ]; then echo "Usage: $0 <path_to_tensorflow_wheel> <python_version>" exit 1 fi TENSORFLOW_WHEEL_PATH="$1" PYTHON_VERSION="$2"
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tensorflow/c/c_api.cc
} // Populate return_nodes DCHECK(tf_results->return_nodes.empty()); tf_results->return_nodes.resize(results.return_nodes.size()); for (int i = 0; i < results.return_nodes.size(); ++i) { tf_results->return_nodes[i] = ToOperation(results.return_nodes[i]); } // Populate missing unused map keys DCHECK(tf_results->missing_unused_key_names.empty()); DCHECK(tf_results->missing_unused_key_indexes.empty());
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tensorflow/c/BUILD
], "//conditions:default": [], }) + if_tensorrt([ "//tensorflow/compiler/tf2tensorrt:trt_convert_api", ]), ) # Check that c_api_no_xla does not depend on xla. check_deps( name = "c_api_no_xla_check_deps", disallowed_deps = ["//tensorflow/compiler/jit:xla_kernel_creator"], deps = [":c_api_no_xla"], ) tf_cuda_library( name = "c_api_no_xla",
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