TF_CAPI_EXPORT extern void* TFE_HandleToDLPack(TFE_TensorHandle* h,
                                               TF_Status* status);

// Converts DLPack (DLManagedTensor*) to eager tensor handle.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_HandleFromDLPack(void* dlm,
                                                             TF_Status* status,
                                                             TFE_Context* ctx);

                                                 TF_Status* s) {
  TFE_Context* c_ctx = TFE_NewContext(options, s);
  if (TF_GetCode(s) != TF_OK) {
    return nullptr;
  }
  return wrap(static_cast<AbstractContext*>(unwrap(c_ctx)));
}

TF_AbstractTensor* TF_CreateAbstractTensorFromEagerTensor(TFE_TensorHandle* t,
                                                          TF_Status* s) {

#ifndef TENSORFLOW_C_EAGER_ABSTRACT_FUNCTION_H_
#define TENSORFLOW_C_EAGER_ABSTRACT_FUNCTION_H_

#include "absl/status/statusor.h"
#include "tensorflow/core/framework/function.pb.h"
#include "tensorflow/core/platform/intrusive_ptr.h"
#include "tensorflow/core/platform/refcount.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

class FunctionRecord;

abstract: TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. TensorFlow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. It maps the nodes of a dataflow graph across many machines in a cluster, and within a machine across multiple computational devices, including multicore CPUs, general purpose GPUs, and custom-designed ASICs known as Tensor Processing...

#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {
namespace tracing {
namespace graph {
GraphFunction::GraphFunction(FunctionDef fdef)
    : AbstractFunction(kGraph),
      func_record_(new FunctionRecord(std::move(fdef), {}, true)) {}
GraphFunction::~GraphFunction() {}
Status GraphFunction::GetFunctionDef(const FunctionDef **fdef) {
  *fdef = &(func_record_->fdef());

#include "tensorflow/c/experimental/filesystem/filesystem_interface.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {
namespace filesystem_registration {

// Implementation for filesystem registration
//
// Don't call this directly. Instead call `RegisterFilesystemPlugin`.
// Exposed only for static registration of local filesystems.
Status RegisterFilesystemPluginImpl(const TF_FilesystemPluginInfo* info);

class TapeContext : public AbstractContext {
 public:
  explicit TapeContext(AbstractContext*, Tape*, const GradientRegistry&);
  void Release() override;
  TapeOperation* CreateOperation() override;
  Status RegisterFunction(AbstractFunction*) override;
  Status RemoveFunction(const string& func) override;
  // For LLVM style RTTI.
  static bool classof(const AbstractContext* ptr) {
    return ptr->getKind() == kTape;
  }
  ~TapeContext() override;

*/

const get_email_domain = async ({github, username}) => {
  const user = await github.rest.users.getByUsername({
    username
  });
  if (user.status >= 400) {
    console.log(user);
    throw `Error Getting user data for ${username}`;
  }
  const email = user.data.email;
  let domain = "";
  if (email && email.lastIndexOf("@") != -1)

    size = "small",
    srcs = [
        "custom_gradient_test.cc",
    ],
    args = ["--heap_check="],  # TODO(b/174752220): Remove
    tags = tf_cuda_tests_tags(),
    deps = [
        "//tensorflow/c:tf_status_helper",
        "//tensorflow/c/eager:abstract_context",
        "//tensorflow/c/eager:c_api",
        "//tensorflow/c/eager:c_api_experimental",
        "//tensorflow/c/eager:c_api_unified_internal",

    srcs = ["posix_filesystem.cc"],
    hdrs = ["posix_filesystem.h"],
    deps = [
        ":posix_filesystem_helper",
        "//tensorflow/c:tf_file_statistics",
        "//tensorflow/c:tf_status",
        "//tensorflow/c/experimental/filesystem:filesystem_interface",
    ],
)

# Since building pip package and API tests require a filesystem, we provide a
# static registration target that they should link against.