int dst_fd = open(dst, O_WRONLY | O_CREAT | O_TRUNC, open_mode);
  if (dst_fd < 0) {
    close(src_fd);
    return -1;
  }

  // Both files have been opened, do the transfer.
  // Since errno would be overridden by `close` below, save it here.
  int error_code = 0;
  if (CopyFileContents(dst_fd, src_fd, size) < 0) error_code = errno;

  close(src_fd);
  close(dst_fd);
  if (error_code != 0) {

            false
        fi
    done
}

@test "No duplicate files on Windows" {
    cat <<EOF
Please rename files so there are no repeats. For example, README.md and
Readme.md would be the same file on Windows. In this test, you would get a
warning for "readme.md" because it makes everything lowercase. There are
repeats of these filename(s) with different casing:
EOF

# use the wheel's TensorFlow installation instead of the one made available
# through bazel. This must be done in a different root directory, //bazel_pip/...,
# because "import tensorflow" run from the root directory would instead import
# the folder instead of the venv package.
# 
# Pass --config=pip to run the same suite of tests. If you want to run just one
# test for investigation, you'll need --config=pip_venv instead, and then you

-
-  ElfW(Addr) static_addr;
-  ElfW(Addr) dynamic_addr;
-
-  asm ("					\n\
-	adrp	%1, _dl_start;			\n\
-        add	%1, %1, #:lo12:_dl_start        \n\
-        ldr	%w0, 1f				\n\
-	b	2f				\n\
-1:	.word	_dl_start			\n\
-2:						\n\
-       " : "=r" (static_addr),  "=r" (dynamic_addr));
-  return dynamic_addr - static_addr;
+    _DYNAMIC sysmbol is used here as its link-time address stored in

the problem. If possible, please share a link to Colab/Jupyter/any notebook.

Also, please include a link to a GraphDef or the model if possible.

**Any other info / logs**

Include any logs or source code that would be helpful to diagnose the problem.
If including tracebacks, please include the full traceback. Large logs and files

name: TensorFlow Issue Template
description: Use this template to report TensorFlow-related issues
body:
  - type: dropdown
    id: issue-type
    attributes:
      label: Issue type
      description: What type of issue would you like to report?
      multiple: false
      options:
        - Bug
        - Build/Install
        - Performance
        - Support
        - Feature Request
        - Documentation Feature Request

                        const int in_flight_nodes_limit)
      : status_(TF_NewStatus()),
        // If the context's default exector is set to async, re-using that in
        // each thread would cause collectives to deadlock. For consistency we
        // create a new sync executor for every thread.
        //
        // TODO(allenl): We should have an async API that works with the
        // parallel device.

  // A sequence of thread wrappers, one per device, for executing operations in
  // parallel.
  //
  // Conceptually this is a thread pool with one thread per device. It requires
  // less synchronization than a thread pool would for this task, since Execute
  // acquires each thread in order (and so only one Execute will schedule
  // blocking collective operations at a time), and avoids some dynamic
  // allocation/scheduling.
  //

// least `max_values`.
//
// The elements of values will point to addresses in `storage` which must be at
// least `storage_size` bytes in length.  Ideally, max_values would be set to
// TF_AttrMetadata.list_size and `storage` would be at least
// TF_AttrMetadata.total_size, obtained from TF_OperationGetAttrMetadata(oper,
// attr_name).
//
// Fails if storage_size is too small to hold the requested number of strings.

  tensorflow::FunctionDef def;
  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(