if (undeleted_files == nullptr || undeleted_dirs == nullptr)
    return errors::FailedPrecondition(
        "DeleteRecursively must not be called with `undeleted_files` or "
        "`undeleted_dirs` set to NULL");

  if (ops_->delete_recursively == nullptr)
    return FileSystem::DeleteRecursively(dirname, token, undeleted_files,
                                         undeleted_dirs);

        std::vector<char> got;
        TF_EXPECT_OK(ReadCache(&cache, "", offset, n, &got));
        // Verify the size of the read.
        if (offset + n <= size) {
          // Expect a full read.
          EXPECT_EQ(got.size(), n) << "block size = " << block_size
                                   << ", offset = " << offset << ", n = " << n;
        } else {
          // Expect a partial read.

#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/framework/full_type.pb.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/test.h"

using tensorflow::Status;
using tensorflow::string;

add them to //tensorflow/tools/pip_package/BUILD. Otherwise, add the no_pip tag
to the test, or change code_check_full.bats in the SIG Build repository. That's
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/tf_sig_build_dockerfiles/devel.usertools/code_check_full.bats
Here are the affected tests:
EOF
    while read dep; do
      echo "For dependency $dep:"

pull requests are approved and pass continuous integration checks, a TensorFlow
team member will apply `ready to pull` label to your change. This means we are
working on getting your pull request submitted to our internal repository. After
the change has been submitted internally, your pull request will be merged
automatically on GitHub.

If you want to contribute, start working through the TensorFlow codebase,

TF_CAPI_EXPORT extern void TFE_OpSetAttrType(TFE_Op* op, const char* attr_name,
                                             TF_DataType value);
// If the number of dimensions is unknown, `num_dims` must be set to
// -1 and `dims` can be null.  If a dimension is unknown, the
// corresponding entry in the `dims` array must be -1.
TF_CAPI_EXPORT extern void TFE_OpSetAttrShape(TFE_Op* op, const char* attr_name,

// 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

    gtl::ArraySlice<AbstractTensorHandle*> output_gradients,
    absl::Span<AbstractTensorHandle*> result) const {
  if (gradient_function == nullptr) {
    return errors::InvalidArgument(
        "Provided null gradient_function for '", op_type, "'.\n",
        "If the intent is to treat this op as non-differentiable consider "
        "using RegisterNotDifferentiable or "
        "NotDifferentiableGradientFunction.");
  }

  const string malformed_text_proto(R"(cluster {
  job {
    name: "worker")");
  TF_Buffer* null_result =
      TFE_GetServerDef(malformed_text_proto.c_str(), status);
  EXPECT_NE(TF_GetCode(status), TF_OK);
  EXPECT_TRUE(absl::StrContains(TF_Message(status),
                                "Invalid text proto for ServerDef"));
  EXPECT_EQ(null_result, nullptr);

  // Cleanup
  TF_DeleteBuffer(result);
  TF_DeleteStatus(status);
}

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   SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

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