status->status =
        InvalidArgument("Node ", node->name(), " was not found in the graph");
    return -1;
  }

  tensorflow::shape_inference::ShapeHandle shape = ic->output(output.index);

  // Unknown rank means the number of dimensions is -1.
  if (!ic->RankKnown(shape)) {
    return -1;
  }

  return ic->Rank(shape);
}

void TF_GraphGetTensorShape(TF_Graph* graph, TF_Output output, int64_t* dims,

                                   " dimensions which is over the limit of ",
                                   TensorShape::MaxDimensions(), ".");
  }
  TensorShapeProto proto;
  if (num_dims < 0) {
    proto.set_unknown_rank(true);
  } else {
    for (int d = 0; d < num_dims; ++d) {
      proto.add_dim()->set_size(dims[d]);
    }
  }

  forward_op_->attrs.Set(attr_name, proto);

            "shape ",
            first_shape.DebugString(), " and another had shape ",
            component_shape.DebugString()));
      } else {
        // Generalize differing axis lengths to "variable"/"unknown".
        for (int axis_index = 0; axis_index < combined_shape.dims();
             ++axis_index) {
          int64_t axis_length = combined_shape.dim_size(axis_index);

    ASSERT_EQ(errors::OK, s.code()) << s.message();
    x.reset(x_raw);
  }

  PartialTensorShape shape;
  Status s = x->Shape(&shape);
  ASSERT_EQ(errors::OK, s.code()) << s.message();
  ASSERT_TRUE(shape.unknown_rank());
}

TEST_P(UnifiedAPI, TestPartialShapeTracing) {
  if (!UseFunction()) {
    GTEST_SKIP() << "Tracing only test.";
  }
  if (UseMlir()) {

                                                                    &device)) {
    methods.deallocator(data);
    status->status =
        tensorflow::errors::InvalidArgument(device_name, " unknown device.");
    return nullptr;
  }
  return tensorflow::wrap(new tensorflow::CAPICustomDeviceTensorHandle(
      context, device, *reinterpret_cast<tensorflow::DataType*>(&dtype), data,
      methods));
}

    TF_RETURN_IF_ERROR(
        operation->SetOpName(absl::StrCat("_input_", inputs_.size()).c_str()));
    TF_RETURN_IF_ERROR(operation->SetAttrType("dtype", dtype));
    if (!shape.unknown_rank()) {
      TF_RETURN_IF_ERROR(operation->SetAttrShape(
          "shape", reinterpret_cast<int64_t*>(shape.dim_sizes().data()),
          shape.dims()));
    }
    int num_outputs = 1;

}

TEST(CAPI, StatusEnum) {
  EXPECT_EQ(TF_OK, static_cast<TF_Code>(tensorflow::error::OK));
  EXPECT_EQ(TF_CANCELLED, static_cast<TF_Code>(tensorflow::error::CANCELLED));
  EXPECT_EQ(TF_UNKNOWN, static_cast<TF_Code>(tensorflow::error::UNKNOWN));
  EXPECT_EQ(TF_INVALID_ARGUMENT,
            static_cast<TF_Code>(absl::StatusCode::kInvalidArgument));
  EXPECT_EQ(TF_DEADLINE_EXCEEDED,