EXPECT_EQ("test/gauge", metrics->point_set_map.at("test/gauge")->metric_name);
  EXPECT_EQ(1,
            metrics->point_set_map.at("test/gauge")->points.at(0)->int64_value);

  TFE_MonitoringIntGaugeCellSet(cell, 5);
  metrics = collection_registry->CollectMetrics(options);
  EXPECT_EQ(5,
            metrics->point_set_map.at("test/gauge")->points.at(0)->int64_value);
  TFE_MonitoringDeleteIntGauge0(gauge);

}

TEST(RamFileBlockCacheTest, ParallelReads) {
  // This fetcher won't respond until either `callers` threads are calling it
  // concurrently (at which point it will respond with success to all callers),
  // or 10 seconds have elapsed (at which point it will respond with an error).
  const int callers = 4;
  BlockingCounter counter(callers);
  auto fetcher = [&counter](const string& filename, size_t offset, size_t n,

of dynamically. Here's the output from bazel query:
EOF
  cat $BATS_TEST_TMPDIR/out
  [[ ! -s $BATS_TEST_TMPDIR/out ]]
}

@test "All tensorflow.org/code links point to real files" {
    for i in $(grep -onI 'https://www.tensorflow.org/code/[a-zA-Z0-9/._-]\+' -r tensorflow); do
        target=$(echo $i | sed 's!.*https://www.tensorflow.org/code/!!g')

                                                TF_Status* status);

// Execute the operation defined by 'op' and return handles to computed
// 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

of dynamically. Here's the output from bazel query:
EOF
  cat $BATS_TEST_TMPDIR/out
  [[ ! -s $BATS_TEST_TMPDIR/out ]]
}

@test "All tensorflow.org/code links point to real files" {
    for i in $(grep -onI 'https://www.tensorflow.org/code/[a-zA-Z0-9/._-]\+' -r tensorflow); do
        target=$(echo $i | sed 's!.*https://www.tensorflow.org/code/!!g')

    return;
  } else if (S_ISDIR(st.st_mode)) {
    TF_SetStatus(status, TF_FAILED_PRECONDITION, "source path is a directory");
    return;
  }

  // Both `src` and `dst` point to files here. Delegate to helper.
  if (TransferFileContents(src, dst, st.st_mode, st.st_size) < 0)
    TF_SetStatusFromIOError(status, errno, dst);
  else
    TF_SetStatus(status, TF_OK, "");
}

  TFE_TensorHandle* h0 = TestVariable(ctx, 1.0, task1_name);
  TFE_TensorHandle* h1 = TestVariable(ctx, 2.0, task2_name);
  TFE_TensorHandle* h2 = TestVariable(ctx, 3.0, task0_name);

  // Add a sync point to make sure that variables have been initialized
  // before the function execution starts.
  TFE_ContextAsyncWait(ctx, status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

 char *
 STRNCAT (char *s1, const char *s2, size_t n)
 {
-  char c;
   char *s = s1;
 
   /* Find the end of S1.  */
-  do
-    c = *s1++;
-  while (c != '\0');
-
-  /* Make S1 point before next character, so we can increment
-     it while memory is read (wins on pipelined cpus).  */
-  s1 -= 2;
+  s1 += strlen (s1);
 
-  if (n >= 4)
-    {
-      size_t n4 = n >> 2;
-      do
-	{

    tree.write(f)
    if verbose:
      print(f'\nWrote XML with Bazel invocation results to {file_path}')


def print_invocation_results(result_store_dict: ResultDictType):
  """Prints out a short summary of the found ResultStore links (if any)."""
  print()
  if not result_store_dict:
    print('Found no ResultStore links for Bazel build/test invocations.')
  else:

// explicitly by running a TPUReplicatedOutput operation on the parallel device.
//
// TODO(allenl): There are some use-cases that are only supported by copying to
// host at the moment (e.g. debug print on a tensor, .numpy(), etc.). We either
// need to return something here or address these use-cases one by one.
TFE_TensorHandle* CopyTensorFromParallelDevice(TFE_Context* context,