TEST(CAPI, ShapeInferenceError) {
  // TF_FinishOperation should fail if the shape of the added operation cannot
  // be inferred.
  TF_Status* status = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

  // Create this failure by trying to add two nodes with incompatible shapes
  // (A tensor with shape [2] and a tensor with shape [3] cannot be added).
  const char data[] = {1, 2, 3};
  const int64_t vec2_dims[] = {2};

    status->status = tensorflow::errors::OutOfRange(
        "Cannot update edge. Input index [", dst.index,
        "] is greater than the number of total inputs [", ic_dst->num_inputs(),
        "].");
    return;
  }
  if (!ic_dst->MergeInput(dst.index, shape)) {
    status->status = tensorflow::errors::InvalidArgument(
        "Cannot update edge, incompatible shapes: ", ic_dst->DebugString(shape),

-   Once the PR is in the Google codebase, we make sure it integrates well with
    its dependencies and the rest of the system.
-   Rarely, If the tests fail at this stage, we cannot merge the code.
-   If needed, we may come to you to make some changes. At times, it may not be
    you, it may be us who may have hit a snag. Please be patient while we work
    to fix this.

### Bug Fixes and Other Changes

*   Hot-fix was needed for an issue affecting the TensorFlow installation
    process.
    *   TensorFlow 2.15.0 Python package was requesting `tensorrt`-related
        packages that cannot be found unless the user installs them beforehand
        or provides additional installation flags.
    *   This dependency affected anyone installing TensorFlow 2.15 alongside

    # Check if the path is valid
    if os.path.isfile(python_bin_path) and os.access(python_bin_path, os.X_OK):
      break
    elif not os.path.exists(python_bin_path):
      print('Invalid python path: {} cannot be found.'.format(python_bin_path))
    else:
      print('{} is not executable.  Is it the python binary?'.format(
          python_bin_path))
    environ_cp['PYTHON_BIN_PATH'] = ''

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

  // We cannot rename directories yet, so prevent this.
  if (stat(src, &st) != 0) {
    TF_SetStatusFromIOError(status, errno, src);
    return;
  } else if (S_ISDIR(st.st_mode)) {

// Operations the tape needs to perform on tensors to do backpropagation. Named
// "vspace" because a subset of these are related to a vector space, such as
// adding gradients, getting zeroes, etc. Currently cannot be implemented
// without using tensorflow python code, hence left unspecified here.
//
// Gradient is the type returned by gradient functions. In Python TF it's either

  TF_ShapeAndType& shape = shape_list->items[index];
  DCHECK(shape.dims == nullptr) << "Shape at " << index << " is already set!";
  DCHECK(num_dims >= 0) << "Number of dimensions cannot be negative!";
  shape.num_dims = num_dims;
  shape.dims = new int64_t[num_dims];
  memcpy(shape.dims, dims, sizeof(int64_t) * num_dims);
}

void TF_ShapeAndTypeListSetUnknownShape(TF_ShapeAndTypeList* shape_list,

build:rbe_cross_compile_base_xla --strategy_regexp='Generating flatbuffer files.*=remote'
build:rbe_cross_compile_base_xla --strategy_regexp='Executing genrule @llvm-project.*=remote'

# Test-related settings below this point
# We cannot run cross-compiled tests on the remote Linux x86 VMs so we need to
# force all tests to run locally on the Aarch64 host.
test:rbe_cross_compile_base --strategy=TestRunner=local --build_tests_only

                          const TF_Function* grad, TF_Status* status) {
  if (func == nullptr) {
    status->status = InvalidArgument(
        "'func' argument to TF_GraphCopyFunction cannot be null");
    return;
  }

  tensorflow::mutex_lock l(g->mu);
  status->status = g->graph.AddFunctionDef(func->record->fdef(),
                                           func->record->stack_traces());