// destroy an instance of this class.
  virtual void Release() = 0;

  // Creates an operation builder and ties it to this context.
  // The returned object can be used for setting operation's attributes,
  // adding inputs and finally executing (immediately or lazily as in tracing)
  // it in this context.
  virtual AbstractOperation* CreateOperation() = 0;

      num_virtual_gpus > 0) {
    tensorflow::GPUOptions* gpu_options =
        server_def.mutable_default_session_config()->mutable_gpu_options();
    auto virtual_devices =
        gpu_options->mutable_experimental()->add_virtual_devices();
    for (int i = 0; i < num_virtual_gpus; ++i) {
      virtual_devices->add_memory_limit_mb(200);
    }
  }
  return server_def;

//   return registry->Register("Add", AddRegisterer);
// }
class GradientFunction {
 public:
  virtual Status Compute(AbstractContext* ctx,
                         absl::Span<AbstractTensorHandle* const> grad_outputs,
                         absl::Span<AbstractTensorHandle*> grad_inputs) = 0;
  virtual ~GradientFunction() {}
};

// Metadata from the forward operation that is made available to the

class VSpace {
 public:
  virtual ~VSpace() {}

  // Returns the number of elements in the gradient tensor.
  virtual int64_t NumElements(Gradient* tensor) const = 0;

  // Consumes references to the tensors in the gradient_tensors list and returns
  // a tensor with the result.
  virtual Gradient* AggregateGradients(
      gtl::ArraySlice<Gradient*> gradient_tensors) const = 0;

// Create a multi-client ServerDef with the given `job_name`, add `num_tasks`
// tasks and `num_virtual_gpus` virtual GPUs in it.
tensorflow::ServerDef GetMultiClientServerDef(const std::string& job_name,
                                              int num_tasks,
                                              int num_virtual_gpus = 0);

// Create a variable handle with name `variable_name` on a device with name
// `device_name`.

# "pip tests" run a similar suite of tests the "nonpip" tests, but do something
# odd to attempt to validate the quality of the pip package. The wheel is
# installed into a virtual environment, and then that venv is used to run all
# bazel tests with a special flag "--define=no_tensorflow_py_deps=true", which
# drops all the bazel dependencies for each py_test; this makes all the tests

# the Python version set in "TFCI_PYTHON_VERSION" and use it as default.
# We enable this in the nightly and release builds because before uploading the
# wheels, we install them in a virtual environment and run some smoke tests on
# it. TFCI Mac VMs only have one Python version installed so we need to install
# the other versions manually.
if [[ "${TFCI_MACOS_PYENV_INSTALL_ENABLE}" == 1 ]]; then

    }),
    out = "__init__.py",
)

genrule(
    name = "virtual_root_init_gen",
    srcs = select({
        "api_version_2": [":virtual_root_template_v2.__init__.py"],
        "//conditions:default": [":virtual_root_template_v1.__init__.py"],
    }),
    outs = ["virtual_root.__init__.py"],
    cmd = "cp $(SRCS) $(OUTS)",
)

generate_apis(

        -Name LongPathsEnabled -Value 1 -PropertyType DWORD -Force

# Install Visual C++ Redistributable for Visual Studio 2015-2022.
RUN New-Item -Path "C:/" -Name "TEMP" -ItemType "directory"; \
    Invoke-WebRequest "https://aka.ms/vs/17/release/vc_redist.x64.exe" \
        -OutFile C:/TEMP/vc_redist.x64.exe -UseBasicParsing; \

        'you want to build with.\nYou can find the compute capability of your '
        'device at: https://developer.nvidia.com/cuda-gpus. Each capability '
        'can be specified as "x.y" or "compute_xy" to include both virtual and'
        ' binary GPU code, or as "sm_xy" to only include the binary '
        'code.\nPlease note that each additional compute capability '
        'significantly increases your build time and binary size, and that '