if (MappedRange.InlineDelta.MAX_VALUE >= abs(codePointDelta)) {
        return MappedRange.InlineDelta(mapping.rangeStart, codePointDelta)
      }
    }
  }
  return null
}

/**
 * Inputs must have applied [withoutSectionSpans].
 */
internal fun sections(mappings: List<Mapping>): Map<Int, List<MappedRange>> {
  val result = mutableMapOf<Int, MutableList<MappedRange>>()

  for (mapping in mappings) {

import com.google.common.primitives.Ints;
import java.math.BigInteger;
import java.util.List;
import java.util.stream.DoubleStream;
import org.jspecify.annotations.NullUnmarked;

/**
 * Inputs, expected outputs, and helper methods for tests of {@link StatsAccumulator}, {@link
 * Stats}, {@link PairedStatsAccumulator}, and {@link PairedStats}.
 *
 * @author Pete Gillin
 */
@NullUnmarked
@J2ktIncompatible

  }
  // required as we rely on junit4 rules
  integTestImplementation "org.spockframework:spock-junit4"
  integTestImplementation "org.xmlunit:xmlunit-core:2.8.2"
}

tasks.register("integTest", Test) {
  inputs.dir(file("src/testKit")).withPropertyName("testkit dir").withPathSensitivity(PathSensitivity.RELATIVE)
  systemProperty 'test.version_under_test', version
  testClassesDirs = sourceSets.integTest.output.classesDirs

    TFE_TensorHandle* input = TFE_OpGetFlatInput(original_op, j, s);
    if (TF_GetCode(s) != TF_OK) return;
    const char* input_device = TFE_TensorHandleDeviceName(input, s);
    if (TF_GetCode(s) != TF_OK) return;
    if (dev->device_name == input_device) {
      LoggedTensor* t = reinterpret_cast<LoggedTensor*>(
          TFE_TensorHandleDevicePointer(input, s));
      if (TF_GetCode(s) != TF_OK) return;

import org.jspecify.annotations.NullUnmarked;

/**
 * A generator of {@code TestSuite} instances for testing {@code ByteSource} implementations.
 * Generates tests of all methods on a {@code ByteSource} given various inputs the source is
 * expected to contain as well as sub-suites for testing the {@code CharSource} view and {@code
 * slice()} views in the same way.
 *
 * @author Colin Decker
 */

    AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs,
    absl::Span<AbstractTensorHandle*> outputs) {
  Tape tape(/*persistent=*/false);
  tape.Watch(inputs[0]);
  AbstractTensorHandle* neg_output;
  TF_RETURN_IF_ERROR(ops::Neg(ctx, inputs[0], &neg_output, "Neg"));
  tape.RecordOperation(inputs, {neg_output}, nullptr, "Neg");
  return tape.ComputeGradient(ctx,

	// LDADDx/SWPx/CASx atomic instructions
	return arm64.IsAtomicInstruction(op)
}

// IsARM64TBL reports whether the op (as defined by an arm64.A*
// constant) is one of the TBL-like instructions and one of its
// inputs does not fit into prog.Reg, so require special handling.
func IsARM64TBL(op obj.As) bool {
	switch op {
	case arm64.AVTBL, arm64.AVTBX, arm64.AVMOVQ:
		return true
	}
	return false
}

ame:"dimension",validatorFunction:function(b,d,e,g,h){if(c){var i=e.get(0).files||[],j=this;e.attr("data-validation").indexOf("mime")===-1?(alert("You should validate file type being jpg, gif or png on input "+e[0].name),b(!1)):i.length>1?(alert("Validating image dimensions does not support inputs allowing multiple files"),b(!1)):0===i.length?b(!0):f(i[0],function(c){var d=!1;e.valAttr("dimension")&&(d=a.formUtils.checkImageDimension(c,e.valAttr("dimension"),h)),!d&&e.valAttr("ratio")&&(d=a.form...

  }

  /**
   * Returns a {@code Collector} that accumulates elements into an {@code ImmutableMultiset} whose
   * elements are the result of applying {@code elementFunction} to the inputs, with counts equal to
   * the result of applying {@code countFunction} to the inputs.
   *
   * <p>If the mapped elements contain duplicates (according to {@link Object#equals}), the first

                                    <label for="inputs" class="col-sm-3 text-sm-right col-form-label"><la:message
                                            key="labels.dict_mapping_source"/></label>
                                    <div class="col-sm-9">
                                        <la:errors property="inputs"/>
                                        <la:textarea styleId="inputs" property="inputs" rows="5"