ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  EXPECT_EQ(dims[0], returned_dims[0]);
  EXPECT_EQ(dims[1], returned_dims[1]);

  // Set to a new valid shape: [2, 3]
  dims[1] = 3;
  TF_GraphSetTensorShape(graph, feed_out_0, dims, 2, s);
  EXPECT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Fetch and see that the new value is returned.

  `comp:` etc.  At this stage we check if the PR is valid and meets certain
  quality requirements. For example, we check if the CLA is signed, PR has
  sufficient description, if applicable unit tests are added, if it is a
  reasonable contribution (meaning it is not a single liner cosmetic PR).

**2. Valid?**

-   If the PR passes all the quality checks then we go ahead and assign a
    reviewer.

# Checks TFCI_BAZEL_COMMON_ARGS for "gpu" or "cuda", implying that the test is
# relevant. All of the GPU test machines have CUDA installed via other means,
# so I am not sure how to verify that the dependencies themselves are valid for
# the moment.
if [[ "$TFCI_BAZEL_COMMON_ARGS" =~ gpu|cuda ]]; then
  echo "Checking to make sure tensorflow[and-cuda] is installable..."
  "$python" -m pip install "$(echo *.whl)[and-cuda]" $TFCI_PYTHON_VERIFY_PIP_INSTALL_ARGS

  return tensorflow::wrap(tensorflow::TensorHandle::CreateLocalHandle(
      std::move(t), device, device, context));
}

// This function will block till the operation that produces `h` has
// completed. This is only valid on local TFE_TensorHandles. Returns the size in
// bytes of the memory pointed to by the device pointer returned above.
size_t TFE_TensorHandleDeviceMemorySize(TFE_TensorHandle* h,

        *   Using `functools.wraps` on a function with different signature
        *   Using `functools.partial` with an invalid `tf.function` input
    *   `tf.function` now enforces input parameter names to be valid Python identifiers. Incompatible names are automatically sanitized similarly to existing SavedModel signature behavior.

                                 n_ask_attempts=_DEFAULT_PROMPT_ASK_ATTEMPTS):
  """Loop over user prompts for an ENV param until receiving a valid response.

  For the env param var_name, read from the environment or verify user input
  until receiving valid input. When done, set var_name in the environ_cp to its
  new value.

  Args:
    environ_cp: (Dict) copy of the os.environ.

#
# We can't test on the windows toolchains because they're using a legacy
# toolchain format (or something) that specifies the toolchain directly instead
# of as a "repository". They can't be valid on Linux because Linux can't do
# anything with a Windows-only toolchain, and bazel errors if trying to build
# that directory.
@test "bazel nobuild passes on all of TF except TF Lite and win toolchains" {