// SECTION 3. Implementation for `TF_ReadOnlyMemoryRegion`
// ----------------------------------------------------------------------------
namespace tf_read_only_memory_region {

// TODO(b/139060984): Implement later

}  // namespace tf_read_only_memory_region

// SECTION 4. Implementation for `TF_Filesystem`, the actual filesystem
// ----------------------------------------------------------------------------

  ops->read_only_memory_region_ops = static_cast<TF_ReadOnlyMemoryRegionOps*>(
      plugin_memory_allocate(TF_READ_ONLY_MEMORY_REGION_OPS_SIZE));
  ops->read_only_memory_region_ops->cleanup =
      tf_read_only_memory_region::Cleanup;
  ops->read_only_memory_region_ops->data = tf_read_only_memory_region::Data;
  ops->read_only_memory_region_ops->length = tf_read_only_memory_region::Length;

  std::string result;
  result.resize(6);
  int64_t read = tf_random_access_file::Read(file, 0, 6, &result[0], status_);
  ASSERT_EQ(read, 6) << "Read: " << read << "\n";
  ASSERT_TF_OK(status_);
  ASSERT_EQ(result, "012345") << "Result: " << result << "\n";

  read = tf_random_access_file::Read(file, 6, 6, &result[0], status_);
  ASSERT_EQ(read, 4) << "Read: " << read << "\n";

  executed = false;
  num_retvals = 0;
  TFE_Execute(op.get(), nullptr, &num_retvals, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  ASSERT_TRUE(executed);

  // Read the variable's value.
  op.reset(TFE_NewOp(context.get(), "ReadVariableOp", status.get()));
  TFE_OpAddInput(op.get(), var_handle, status.get());
  TFE_OpSetDevice(op.get(), name, status.get());

  }

  // Read from the variable and verify that we have a parallel tensor.
  {
    TensorHandlePtr read = variable->Read(context, status.get());
    ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
    std::array<TensorHandlePtr, 2> components;
    ExtractPerDeviceValues(context, read.get(), &components, status.get());

  }
  std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> read_op(
      TFE_NewOp(context.get(), "ReadVariableOp", status.get()), TFE_DeleteOp);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  TFE_OpSetAttrType(read_op.get(), "dtype", TF_FLOAT);
  parallel_device.Execute(context.get(), handle_inputs, "ReadVariableOp",
                          TFE_OpGetAttrs(read_op.get()),

              &num_retvals, &forward_op, tape.get(), registry);
  ASSERT_EQ(errors::OK, s.code()) << s.message();

  string read_message;
  s = forward_op.attrs.Get("message", &read_message);
  ASSERT_EQ(errors::OK, s.code()) << s.message();
  ASSERT_EQ(read_message, message);
}

Status RecordOperationWithNullGradientFunctionModel(
    AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs,

  TFE_ExecutorWaitForAllPendingNodes(executor, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_DeleteExecutor(executor);
  TF_DeleteStatus(status);
}

// Read the value of variable `var` and save it into `out_value`.
void ReadVariable(TFE_Context* ctx, TFE_TensorHandle* var,
                  TFE_TensorHandle** out_value) {
  TF_Status* status = TF_NewStatus();

#include "tensorflow/core/platform/errors.h"

namespace tensorflow {
namespace gradients {
namespace {

// TODO(b/172558015): Using the pointer address as the identifier for the tensor
// may lead to collisions. Introduce another way to get a unique id for this
// tensor.
int64_t ToId(const AbstractTensorHandle* t) {
  return static_cast<int64_t>(reinterpret_cast<uintptr_t>(t));
}

  std::vector<char> out;

  // First read.
  EXPECT_TRUE(cache.ValidateAndUpdateFileSignature(filename, 123));
  TF_EXPECT_OK(ReadCache(&cache, filename, 0, 16, &out));
  EXPECT_EQ(calls, 1);

  // Second read. Hit cache.
  EXPECT_TRUE(cache.ValidateAndUpdateFileSignature(filename, 123));
  TF_EXPECT_OK(ReadCache(&cache, filename, 0, 16, &out));
  EXPECT_EQ(calls, 1);

  // Third read. File signatures are different.