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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
# the dependencies of that target which include a license notice file are then # included when generating that license. Necessary because the license targets # in TensorFlow are manually enumerated rather than generated automatically. do_external_licenses_check(){ BUILD_TARGET="$1" LICENSES_TARGET="$2" # grep patterns for targets which are allowed to be missing from the licenses
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tensorflow/c/eager/c_api.h
// tensors in `retvals`. // // 'retvals' must point to a pre-allocated array of TFE_TensorHandle* and // '*num_retvals' should be set to the size of this array. It is an error if // the size of 'retvals' is less than the number of outputs. This call sets // *num_retvals to the number of outputs. // // If async execution is enabled, the call may simply enqueue the execution
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tensorflow/c/c_api.cc
" but actual rank is ", rank); return; } if (num_dims == 0) { // Output shape is a scalar. return; } // Rank is greater than 0, so fill in the values, if known, and // -1 for unknown values. for (int i = 0; i < num_dims; ++i) { auto dim = ic->Dim(shape, i); int64_t value = -1; if (ic->ValueKnown(dim)) {
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ci/official/utilities/cleanup_summary.sh
function resultstore_extract_fallback { # In case the main script fails somehow. cat <<EOF IMPORTANT: For bazel invocations that uploaded to ResultStore (e.g. RBE), you can view more detailed results that are probably easier to read than this log. Try the links below: EOF # Find any "Streaming build results to" line, then print the last word in it, # and don't print duplicates
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CONTRIBUTING.md
- You make the change and submit it for the review again. - This cycle repeats itself until the PR gets approved. - Note: As a friendly reminder, we may reach out to you if the PR is awaiting 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.
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tensorflow/c/eager/c_api_experimental.h
// is for performance optimization by reusing an exiting unused op rather than // creating a new op every time. If `raw_device_name` is `NULL` or empty, it // does not set the device name. If it's not `NULL`, then it attempts to parse // and set the device name. It's effectively `TFE_OpSetDevice`, but it is faster // than separately calling it because if the existing op has the same
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tensorflow/c/c_api_test.cc
EXPECT_TRUE(absl::StrContains(s, expected)) << "'" << s << "' does not contain '" << expected << "'"; } // Returns the GPU device name if there is one (with arbitrary tie breaking if // there are more than one), or "" otherwise. string GPUDeviceName(TF_Session* session) { std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( TF_NewStatus(), TF_DeleteStatus); TF_Status* s = status.get();
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tensorflow/build_cleaner_spec.textproto
# proto-file: devtools/build_cleaner/proto/actions.proto # proto-message: ActionSpecs # Python rules should not have more than one source file. action_spec { action: CHECK_FILE_COUNT file_count_params { rule_selector { rule_kind_regex: "^.*py(type)?(_strict)?_(binary|library|test).*$" generator_function_regex: "^(?!boq_header)$" } max_source_count: 1 }
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ci/official/upload.sh
source ci/official/utilities/get_versions.sh # Note on gsutil commands: # "gsutil cp" always "copies into". It cannot act on the contents of a directory # and it does not seem possible to e.g. copy "gs://foo/bar" as anything other than # "/path/bar". This script uses "gsutil rsync" instead, which acts on directory # contents. About arguments to gsutil: # "gsutil -m rsync" runs in parallel. # "gsutil rsync -r" is recursive and makes directories work.
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tensorflow/c/eager/c_api_distributed_test.cc
CHECK(tensorflow::protobuf::TextFormat::ParseFromString( VariableAddFunctionSignature(), &def)); return def.SerializeAsString(); } // A graph optimization pass that would fail when triggered for more than once. class GraphErrorInjectionPass : public tensorflow::GraphOptimizationPass { public: static bool enabled_; GraphErrorInjectionPass() {} tensorflow::Status Run(
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