# Tests that there are variables in the model.
    variable_node_defs = _find_variables(output_graphdef)
    self.assertLen(variable_node_defs, 1)

    # Reads the variables from the checkpoint file and matches with the
    # variables found in the graph.
    checkpoint_path = os.path.join(
        self._output_saved_model_path, 'variables', 'variables'
    )

const (
	replicateMetadata replicationAction = "metadata"
	replicateNone     replicationAction = "none"
	replicateAll      replicationAction = "all"
)

// matches k1 with all keys, returns 'true' if one of them matches
func equals(k1 string, keys ...string) bool {
	for _, k2 := range keys {
		if strings.EqualFold(k1, k2) {
			return true
		}
	}
	return false
}

                             llvm::StringRef function_name) -> mlir::Location {
    // Use the catenation of function and node names as the lookup key into the
    // debug info. This matches the way that the key is formed on the python
    // side.
    //
    // We also use this as the name for the NameLoc for ops in function, since
    // otherwise our names could collide across functions.

    platform.assumeNotConscrypt()
    platform.assumeNotBouncyCastle()

    // The _anon_ suites became unsupported in "1.8.0_201" and "11.0.2".
    assumeFalse(
      System.getProperty("java.version", "unknown").matches(Regex("1\\.8\\.0_1\\d\\d")),
    )
    server.enqueue(MockResponse())
    val cipherSuite = CipherSuite.TLS_DH_anon_WITH_AES_128_GCM_SHA256
    val clientCertificates =
      HandshakeCertificates.Builder()

{
  "components": {
    "schemas": {
      "io.k8s.api.core.v1.Toleration": {
        "description": "The pod this Toleration is attached to tolerates any taint that matches the triple <key,value,effect> using the matching operator <operator>.",
        "properties": {
          "effect": {

   * the original {@code ClosingFuture} instance.
   *
   * @param exceptionType the exception type that triggers use of {@code fallback}. The exception
   *     type is matched against this step's exception. "This step's exception" means the cause of
   *     the {@link ExecutionException} thrown by {@link Future#get()} on the {@link Future}

    TFL_OperandHasAtleastRank<0, 2>,
    PredOpTrait<"input and result must have the same element type",
      TFL_TCresVTEtIsSameAsOp<0, 0>>,
    Pure]> {
  let summary = [{
    Returns a batched matrix tensor with new batched diagonal values.
  }];

  let description = [{
Given `input` and `diagonal`, this operation returns a tensor with the
same shape and values as `input`, except for the main diagonal of the

   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *

	case C_SOREG:
		return cmp(C_ZOREG, b)

	case C_LOREG:
		return cmp(C_SOREG, b)

	case C_XOREG:
		return cmp(C_REG, b) || cmp(C_ZOREG, b)

	// An even/odd register input always matches the regular register types.
	case C_REG:
		return cmp(C_REGP, b) || (b == C_ZCON && r0iszero != 0)
	case C_FREG:
		return cmp(C_FREGP, b)
	case C_VSREG:
		/* Allow any VR argument as a VSR operand. */

   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *