ASSERT_EQ(TF_OK, TF_GetCode(status));
  const OpDef* expected_op_def;
  TF_ASSERT_OK(OpRegistry::Global()->LookUpOpDef("Add", &expected_op_def));
  string expected_serialized;
  expected_op_def->SerializeToString(&expected_serialized);
  string actual_string(reinterpret_cast<const char*>(buffer->data),
                       buffer->length);
  EXPECT_EQ(expected_serialized, actual_string);

void TF_DeleteOutputList(TF_OutputList* o) { delete unwrap(o); }
void TF_OutputListSetNumOutputs(TF_OutputList* o, int num_outputs,
                                TF_Status* s) {
  unwrap(o)->expected_num_outputs = num_outputs;
  unwrap(o)->outputs.clear();
  unwrap(o)->outputs.resize(num_outputs);
}
int TF_OutputListNumOutputs(TF_OutputList* o) {
  return unwrap(o)->outputs.size();
}

  if (shape.dims() != 2) {
    return errors::InvalidArgument(
        "Tensor expected to have rank 2 found rank: ", shape.dims());
  }
  int64_t dim_sizes[] = {2, 4};
  for (int i = 0; i < shape.dims(); i++) {
    if (shape.dim_size(i) != dim_sizes[i]) {
      return errors::InvalidArgument("Dim ", i, " expected to be of size ",
                                     dim_sizes[i],

  bool valid = true;
  int64_t expected_stride = 1;
  for (int i = ndim - 1; i >= 0; --i) {
    // Empty tensors are always compact regardless of strides.
    if (shape_arr[i] == 0) return true;
    // Note that dimensions with size=1 can have any stride.
    if (shape_arr[i] != 1 && stride_arr[i] != expected_stride) {
      valid = false;
    }
    expected_stride *= shape_arr[i];
  }
  return valid;
}

      }
      AbstractFunction* func = nullptr;
      OutputList output_list;
      output_list.expected_num_outputs = 0;
      output_list.outputs.reserve(outputs.size());
      for (int i = 0; i < model_outputs.size(); i++) {
        if (model_outputs[i]) {
          output_list.outputs.emplace_back(model_outputs[i]);
          output_list.expected_num_outputs += 1;
        } else {
          null_indices.insert(i);
        }
      }

                        const TFE_OpAttrs* attributes, int expected_max_outputs,
                        TF_Status* status) const {
  std::vector<PartialTensorShape> expected_output_shapes(expected_max_outputs);
  StartExecute(context, inputs, operation_name, attributes,
               expected_max_outputs, *default_cancellation_manager_);
  auto result = Join(expected_output_shapes, status);
  if (TF_GetCode(status) != TF_OK) {

        | grep -v "**** Module" \
        | tee $BATS_TEST_TMPDIR/needs_help.txt
    [[ ! -s $BATS_TEST_TMPDIR/needs_help.txt ]]
}

@test "API compatibility test passes, ensuring no unexpected changes to the TF API" {
    bazel test $TFCI_BAZEL_COMMON_ARGS //tensorflow/tools/api/tests:api_compatibility_test
    echo "You have to re-generate the TF API goldens and have the API changes reviewed."

EOF

  license_query "attr('licenses', 'notice', deps($BUILD_TARGET))" > $BATS_TEST_TMPDIR/expected_licenses
  license_query "deps($LICENSES_TARGET)" > $BATS_TEST_TMPDIR/actual_licenses

  # Column 1 is left only, Column 2 is right only, Column 3 is shared lines
  # Select lines unique to actual_licenses, i.e. extra licenses.

                                       TF_Status* status);

// Enables only graph collection in RunMetadata on the functions executed from
// this context.
TF_CAPI_EXPORT extern void TFE_ContextEnableGraphCollection(TFE_Context* ctx);

// Disables only graph collection in RunMetadata on the functions executed from
// this context.
TF_CAPI_EXPORT extern void TFE_ContextDisableGraphCollection(TFE_Context* ctx);

    const auto tensor_interface =
        tensorflow::down_cast<const tensorflow::TensorInterface*>(src->tensor);

    if (dst->dims() != 0) {
      return InvalidArgument(
          "Malformed TF_RESOURCE tensor: expected a scalar, got a tensor with "
          "shape ",
          dst->shape().DebugString());
    }
    *dst = tensorflow::Tensor(tensorflow::DT_RESOURCE, dst->shape());