# Add signtool.exe to the PATH. Note this path may need to be edited if updates
# are made to the Windows 10 SDK.
RUN $old_path = [Environment]::GetEnvironmentVariable(\"PATH\", \"Machine\"); \

  }
  if (!ShouldRecord(input_tensor_id, input_dtypes)) {
    return absl::OkStatus();
  }

  // We may need to allocate zero inputs for trainable dtypes we don't have JVPs
  // for. Make sure they get cleaned up.
  std::vector<Gradient*> new_zeros;
  auto delete_new_zeros = gtl::MakeCleanup([&new_zeros, this] {
    for (Gradient* tensor : new_zeros) {
      this->vspace_.DeleteGradient(tensor);
    }

@@ -29,54 +25,16 @@
 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

  CHECK_OK(buffer.status());

  return new PJRT_Buffer{std::move(*buffer), c_api_client->pjrt_c_client()};
}

TEST(TensorPjRtBufferUtilTest, GetPjRtCBufferFromTensorNoBuffer) {
  auto allocator = std::make_unique<AsyncValueAllocator>();
  tensorflow::Tensor tensor(allocator.get(), DT_FLOAT, {1});

  EXPECT_THAT(
      GetPjRtCBufferFromTensor(&tensor),
      StatusIs(error::INTERNAL, HasSubstr(absl::StrCat(

  else:
    p.text += (
        "\n      Since there were not three failures, this is probably a flake."
    )
    p.text += (
        "\n      Flakes make this pkg/pip_and_nonpip_tests target show "
        "as failing,"
    )
    p.text += "\n      but do not make the Kokoro invocation fail."

os.makedirs(os.path.dirname(sys.argv[2]), exist_ok=True)
result.update_statistics()

        - Documentation Feature Request
        - Documentation Bug
        - Others
    validations:
      required: true
  - type: markdown
    attributes:
      value: |
        Please make sure that this is a bug. As per our [GitHub Policy](https://github.com/tensorflow/tensorflow/blob/master/ISSUES.md), we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub.

  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);

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
#
# Common setup for all TF scripts.
#
# Make as FEW changes to this file as possible. It should not contain utility
# functions (except for tfrun); use dedicated scripts instead and reference them
# specifically. Use your best judgment to keep the scripts in this directory

  int num_retvals = 1;
  std::vector<AbstractTensorHandle*> outputs(1);
  GradientRegistry registry;
  s = RegisterGradients(&registry);
  ASSERT_EQ(errors::OK, s.code()) << s.message();
  auto tape = std::make_unique<Tape>(/*persistent=*/false);
  s = Execute(check_numerics_op.get(), ctx.get(), absl::MakeSpan(outputs),
              &num_retvals, &forward_op, tape.get(), registry);
  ASSERT_EQ(errors::OK, s.code()) << s.message();

//
// Questions left to address:
// * Might at some point need a way for callers to provide their own Env.
// * Maybe add TF_TensorShape that encapsulates dimension info.
//
// Design decisions made:
// * Backing store for tensor memory has an associated deallocation
//   function.  This deallocation function will point to client code
//   for tensors populated by the client.  So the client can do things