// between theoretical and numerical jacobians:
//   fabs(jac_t - jac_n) / max(fabs(jac_t), fabs(jac_n))

// TODO(andydavis) Vectorize and/or multi-thread Jacobian computations if
// performance becomes an issue.

// BaseUnitsForType provides a list of typed unit values for each basis in the
// requested type.
// When T is real,

  // `forward_function` is null, a GradientTape is used on the backward function
  // to compute the jvp, which will waste computation when executing eagerly.
  //
  // Unlike GradientTape::RecordOperation, Accumulate runs gradient computation
  // immediately. It stores the results, which feed into Accumulate for future
  // operations and may be fetched by calling FetchJVP. ForwardAccumulator

output.
### `-tf-tpu-host-computation-expansion`

_Expands host computation before and after TPU computation._

This pass expands outside compilation attributes to Identity/Cast ops
at the head of TPU computation if it's only used by outside compiled ops.
### `-tf-tpu-identity-pruning`

_Removes Identity/IdentityN ops from the TPU computation_

### `-tf-tpu-merge-variables-with-execute`

	// If a pod doesn't have any volume attached to it, the predicate will always be true.
	// Thus we make a fast path for it, to avoid unnecessary computations in this case.
	if len(pod.Spec.Volumes) == 0 {
		return nil
	}

	logger := klog.FromContext(ctx)
	newVolumes := sets.New[string]()

	GOROOTpkg string
	GOROOTsrc string

	GOBIN                         = Getenv("GOBIN")
	GOMODCACHE, GOMODCACHEChanged = EnvOrAndChanged("GOMODCACHE", gopathDir("pkg/mod"))

	// Used in envcmd.MkEnv and build ID computations.
	GOARM64, goARM64Changed     = EnvOrAndChanged("GOARM64", fmt.Sprint(buildcfg.GOARM64))
	GOARM, goARMChanged         = EnvOrAndChanged("GOARM", fmt.Sprint(buildcfg.GOARM))

	atomic.StoreInt64(&connectionNumber, 0)
}

// initProxyMetadata initializes just the basic metadata of a proxy. This is decoupled from
// initProxyState such that we can perform authorization before attempting expensive computations to
// fully initialize the proxy.
func (s *DiscoveryServer) initProxyMetadata(node *core.Node) (*model.Proxy, error) {
	meta, err := model.ParseMetadata(node.Metadata)
	if err != nil {

      %computation = "tf_device.cluster_func"(%read) {func = @computation, use_spmd_for_xla_partitioning = true} : (tensor<i32>) -> tensor<i32>
      "tf.AssignVariableOp"(%partitioned_variable, %computation) : (tensor<!tf_type.resource<tensor<i32>>>, tensor<i32>) -> ()
      return
    }

    func @computation(%arg0: tensor<i32>) -> tensor<i32> {
      return %arg0: tensor<i32>

        [](Operation* user) { return isa<TF::AssignVariableOp>(user); });

    // TODO(b/186717563): Eliminate all pass through results once XLA correctly
    // handles empty computations. Another approach could be to drop empty
    // clusters within MLIR but that seems to trigger other failures but can be
    // considered again.
    // Old bridge only removes unsupported TPU types (only string for now)

  // Internal tensors are those that do not flow in or out of the operation,
  // but instead are part of internal computation. As such, the operation's
  // implementation may manage its memory more efficiently. They are needed
  // however (i.e. not just an implementation detail) since they are part of the
  // computation, which may require relevant metadata such as quantization
  // parameters.
  intermediates:[int];

//
// (Note that this can be viewed equivalently as:
//
//	actionID(binary)/buildID(main.a)/contentID(binary)
//
// Storing the buildID(main.a) in the middle lets the computations that care
// about the prefix or suffix halves ignore the middle and preserves the
// original build ID as a contiguous string.)
//
// During the build, when it's time to build main.a, the gofmt binary has the