#include <algorithm>
#include <cstring>
#include <limits>
#include <memory>
#include <optional>
#include <unordered_set>
#include <utility>
#include <vector>

#include "absl/strings/match.h"
// Required for IS_MOBILE_PLATFORM
#include "tensorflow/core/platform/platform.h"  // NOLINT

#if !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
#include "tensorflow/c/experimental/filesystem/modular_filesystem.h"

  TF_SetStatus(status, TF_OK, "");
}

static void NewAppendableFile(const TF_Filesystem* filesystem, const char* path,
                              TF_WritableFile* file, TF_Status* status) {
  FILE* f = fopen(path, "a");
  if (f == nullptr) {
    TF_SetStatusFromIOError(status, errno, path);
    return;
  }

  file->plugin_file = new tf_writable_file::PosixFile({strdup(path), f});

                              absl::Span<AbstractTensorHandle* const> inputs,
                              absl::Span<AbstractTensorHandle*> outputs) {
  Tape tape(/*persistent=*/false);
  tape.Watch(inputs[0]);  // Watch x.
  AbstractTensorHandle* exp_output;
  TF_RETURN_IF_ERROR(ops::Exp(ctx, inputs[0], &exp_output, "Exp"));
  std::unique_ptr<GradientFunction> gradient_function(
      new PassThroughGradientFunction);

             absl::Span<AbstractTensorHandle* const> inputs,
             absl::Span<AbstractTensorHandle*> outputs) -> Status {
    Tape tape(/*persistent=*/false);
    for (size_t i{}; i < inputs.size(); ++i) {
      tape.Watch(inputs[i]);
    }
    std::vector<AbstractTensorHandle*> temp_outputs(1);
    AbstractContextPtr tape_ctx(new TapeContext(ctx, &tape, grad_registry));
    TF_RETURN_IF_ERROR(

void TapeVSpace::MarkAsResult(AbstractTensorHandle* gradient) const {}

void TapeVSpace::DeleteGradient(AbstractTensorHandle* gradient) const {
  gradient->Unref();
}

void Tape::Watch(const AbstractTensorHandle* t) {
  GradientTape::Watch(ToId(t));
}
void Tape::RecordOperation(absl::Span<AbstractTensorHandle* const> inputs,
                           absl::Span<AbstractTensorHandle* const> outputs,

    default:
      return tensorflow::errors::InvalidArgument("Unsupported Type Codes: ",
                                                 dtype.code);
  }
}

// Wraps the deleter function of DLManagedTensor to match the function signature
// TFE_NewTensorHandleFromDeviceMemory.
void DeallocatorWrapperFunc(void* data, size_t len, void* dlmt_vptr) {
  TFE_CallDLManagedTensorDeleter(dlmt_vptr);
}

Status RecordOperationWithNullGradientFunctionModel(
    AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs,
    absl::Span<AbstractTensorHandle*> outputs) {
  Tape tape(/*persistent=*/false);
  tape.Watch(inputs[0]);
  AbstractTensorHandle* neg_output;
  TF_RETURN_IF_ERROR(ops::Neg(ctx, inputs[0], &neg_output, "Neg"));
  tape.RecordOperation(inputs, {neg_output}, nullptr, "Neg");
  return tape.ComputeGradient(ctx,

==============================================================================*/

#include <algorithm>
#include <unordered_map>
#include <unordered_set>
#include <utility>

#include "absl/strings/match.h"
#include "tensorflow/c/c_api_internal.h"
#include "tensorflow/c/tf_buffer_internal.h"
#include "tensorflow/core/framework/attr_value_util.h"
#include "tensorflow/core/framework/function.h"

  if (!status->status.ok()) {
    return nullptr;
  }

  TF_DataType dtype = TFE_TensorHandleDataType(components[0].get());
  // Verify that the TensorHandle's shape and dtype match all of the component
  // shapes and dtypes.
  for (TensorHandlePtr& component : components) {
    TFE_TensorHandleGetStatus(component.get(), status);
    if (!status->status.ok()) {
      return nullptr;
    }

              path, stat.generation_number)) {
        TF_VLog(
            1,
            "File signature has been changed. Refreshing the cache. Path: %s",
            path.c_str());
      }
      read = gcs_file->file_block_cache->Read(path, offset, n, buffer, status);
    } else {
      read = LoadBufferFromGCS(path, offset, n, buffer, gcs_file, status);
    }