}

        if (compareResult < 0) {
          high = mid - 1
        } else if (compareResult > 0) {
          low = mid + end + 1
        } else {
          // We found a match, but are the lengths equal?
          val publicSuffixBytesLeft = publicSuffixLength - publicSuffixByteIndex
          var labelBytesLeft = labels[currentLabelIndex].size - currentLabelByteIndex

                                                   const char* attr_name,
                                                   const void* const* values,
                                                   const size_t* lengths,
                                                   int num_values);
TF_CAPI_EXPORT extern void TFE_OpSetAttrIntList(TFE_Op* op,
                                                const char* attr_name,

            "shape ",
            first_shape.DebugString(), " and another had shape ",
            component_shape.DebugString()));
      } else {
        // Generalize differing axis lengths to "variable"/"unknown".
        for (int axis_index = 0; axis_index < combined_shape.dims();
             ++axis_index) {
          int64_t axis_length = combined_shape.dim_size(axis_index);

// ending offset is aligned down to the nearest block edge.
//
// Even though the Go tar Reader and the BSD tar utility can handle entries
// with arbitrary offsets and lengths, the GNU tar utility can only handle
// offsets and lengths that are multiples of blockSize.
func alignSparseEntries(src []sparseEntry, size int64) []sparseEntry {
	dst := src[:0]
	for _, s := range src {
		pos, end := s.Offset, s.endOffset()

### Validation

* Validation for most (or all?) Python **data types**, including:
    * JSON objects (`dict`).
    * JSON array (`list`) defining item types.
    * String (`str`) fields, defining min and max lengths.
    * Numbers (`int`, `float`) with min and max values, etc.

* Validation for more exotic types, like:
    * URL.
    * Email.
    * UUID.
    * ...and others.

}

void TFE_OpSetAttrStringList(TFE_Op* op, const char* attr_name,
                             const void* const* values, const size_t* lengths,
                             int num_values) {
  auto s = tensorflow::unwrap(op)->SetAttrStringList(attr_name, values, lengths,
                                                     num_values);
  if (!s.ok()) {
    LOG(WARNING) << "Unable to set attribute: " << attr_name;
  }
}

                          const void* const* values, const size_t* lengths,
                          int num_values) {
  if (strcmp(attr_name, tensorflow::kColocationAttrName) == 0) {
    desc->colocation_constraints.clear();
    for (int i = 0; i < num_values; ++i) {
      desc->colocation_constraints.emplace(static_cast<const char*>(values[i]),
                                           lengths[i]);
    }
  } else {

   * Equivalence}.
   *
   * <p>For example, given an {@link Equivalence} for {@link String strings} named {@code equiv}
   * that tests equivalence using their lengths:
   *
   * <pre>{@code
   * equiv.wrap("a").equals(equiv.wrap("b")) // true
   * equiv.wrap("a").equals(equiv.wrap("hello")) // false
   * }</pre>
   *

    assertFalse(elementsEqual(b.iterator(), a.iterator()));

    // Different lengths.
    a = asList(4, 8, 15, 16, 23);
    b = asList(4, 8, 15, 16, 23, 42);
    assertFalse(elementsEqual(a.iterator(), b.iterator()));
    assertFalse(elementsEqual(b.iterator(), a.iterator()));

    // Different lengths, one is empty.
    a = emptySet();
    b = asList(4, 8, 15, 16, 23, 42);

		// Set the compression method to Store to ensure data length is truly zero,
		// which the writeHeader method always encodes for the size fields.
		// This is necessary as most compression formats have non-zero lengths
		// even when compressing an empty string.
		fh.Method = Store
		fh.Flags &^= 0x8 // we will not write a data descriptor

		// Explicitly clear sizes as they have no meaning for directories.
		fh.CompressedSize = 0