CheckOutputShapes(matmul_op,
                    /*input_shapes*/ {make_shape({3, 2}), make_shape({2, 4})},
                    /*input_tensors*/ {},
                    /*expected_shape*/ make_shape({3, 4}));

  // Infer shape when second operand has unknown shape.
  CheckOutputShapes(matmul_op,
                    /*input_shapes*/ {make_shape({3, 2}), unknown_shape()},
                    /*input_tensors*/ {},

                                           size_t plugin_size) {
  if (plugin_ops == nullptr) return nullptr;

  size_t copy_size = std::min(plugin_size, sizeof(T));
  auto core_ops = std::make_unique<T>();
  memset(core_ops.get(), 0, sizeof(T));
  memcpy(core_ops.get(), plugin_ops, copy_size);
  return core_ops;
}

// Registers one filesystem from the plugin.
//

      /*run_eager_op_as_function=*/opts->run_eager_op_as_function,
      /*jit_compile_rewrite=*/opts->jit_compile_rewrite);
#if !defined(IS_MOBILE_PLATFORM)
  eager_context->SetDistributedManager(
      std::make_unique<tensorflow::EagerContextDistributedManager>(
          eager_context));
#endif  // !IS_MOBILE_PLATFORM
  return tensorflow::wrap(eager_context);
}

void TFE_DeleteContext(TFE_Context* ctx) {

  file_block_cache = std::make_unique<RamFileBlockCache>(
      block_size, max_bytes, max_staleness,
      [this](const std::string& filename, size_t offset, size_t buffer_size,
             char* buffer, TF_Status* status) {
        return LoadBufferFromGCS(filename, offset, buffer_size, buffer, this,
                                 status);
      });
  stat_cache = std::make_unique<ExpiringLRUCache<GcsFileStat>>(

  std::vector<StackFrame> feed_frames = {{"feed.cc", 10, "alpha"}};
  std::vector<StackFrame> neg_frames = {{"neg.cc", 15, "beta"}};
  feed->node.SetStackTrace(std::make_shared<FrozenStackTrace>(feed_frames));
  neg->node.SetStackTrace(std::make_shared<FrozenStackTrace>(neg_frames));

  TF_Output inputs[] = {{feed, 0}};
  TF_Output outputs[] = {{neg, 0}};
  *func = TF_GraphToFunction(func_graph.get(), name, append_hash, -1,

  auto file = std::make_unique<TF_RandomAccessFile>();
  std::string translated_name = TranslateName(fname);
  ops_->new_random_access_file(filesystem_.get(), translated_name.c_str(),
                               file.get(), plugin_status.get());

  if (TF_GetCode(plugin_status.get()) == TF_OK)
    *result = std::make_unique<ModularRandomAccessFile>(

  EXPECT_EQ(string("fake"), string(src_names[0]));
  EXPECT_EQ(0, src_indexes[0]);

  TF_DeleteImportGraphDefResults(results);
  TF_DeleteImportGraphDefOptions(opts);
  TF_DeleteBuffer(graph_def);
  TF_DeleteGraph(graph);
  TF_DeleteStatus(s);
}

TEST(CAPI, Session) {
  TF_Status* s = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

  // Make a placeholder operation.

    (*var_to_shape_map)[key] = TensorShape(entry.shape());
    (*var_to_data_type_map)[key] = DataType(entry.dtype());
  }
  // The returned pointers are owned by the caller.
  return std::make_pair(std::move(var_to_shape_map),
                        std::move(var_to_data_type_map));
}

}  // namespace checkpoint

  outputs[0]->Unref();
}

TEST_P(CppGradients, TestSparseSoftmaxCrossEntropyWithLogitsGrad) {
  if (UseFunction()) {
    // TODO(b/168850692): Enable this.
    GTEST_SKIP() << "Can't take gradient of "
                    "SparseSoftmaxCrossEntropyWithLogits in tracing mode.";
  }

  // Score
  float X_vals[] = {1.0f, 2.0f, 3.0f, -5.0f, -4.0f, -3.0f, 2.0f, 0.0f, -1.0f};
  int64_t X_dims[] = {3, 3};