"tooltip": false,
              "viz": false
            },
            "insertNulls": false,
            "lineInterpolation": "linear",
            "lineWidth": 1,
            "pointSize": 5,
            "scaleDistribution": {
              "type": "linear"
            },
            "showPoints": "never",
            "spanNulls": false,
            "stacking": {
              "group": "A",

import com.google.common.base.CharMatcher.NamedFastMatcher;
import java.util.BitSet;

/**
 * An immutable version of CharMatcher for smallish sets of characters that uses a hash table with
 * linear probing to check for matches.
 *
 * @author Christopher Swenson
 */
@GwtIncompatible // no precomputation is done in GWT
@ElementTypesAreNonnullByDefault
final class SmallCharMatcher extends NamedFastMatcher {

              "tooltip": false,
              "viz": false
            },
            "insertNulls": false,
            "lineInterpolation": "linear",
            "lineWidth": 1,
            "pointSize": 5,
            "scaleDistribution": {
              "type": "linear"
            },
            "showPoints": "never",
            "spanNulls": false,
            "stacking": {
              "group": "A",

import com.google.common.base.CharMatcher.NamedFastMatcher;
import java.util.BitSet;

/**
 * An immutable version of CharMatcher for smallish sets of characters that uses a hash table with
 * linear probing to check for matches.
 *
 * @author Christopher Swenson
 */
@GwtIncompatible // no precomputation is done in GWT
@ElementTypesAreNonnullByDefault
final class SmallCharMatcher extends NamedFastMatcher {

xt","axisLabel":"","axisPlacement":"auto","barAlignment":0,"drawStyle":"line","fillOpacity":10,"gradientMode":"none","hideFrom":{"legend":false,"tooltip":false,"viz":false},"insertNulls":false,"lineInterpolation":"linear","lineWidth":1,"pointSize":5,"scaleDistribution":{"type":"linear"},"showPoints":"never","spanNulls":false,"stacking":{"group":"A","mode":"none"},"thresholdsStyle":{"mode":"off"}},"mappings":[],"thresholds":{"mode":"absolute","steps":[{"color":"green","value":null},{"color":"red"...

              "tooltip": false,
              "viz": false
            },
            "insertNulls": false,
            "lineInterpolation": "linear",
            "lineWidth": 1,
            "pointSize": 5,
            "scaleDistribution": {
              "type": "linear"
            },
            "showPoints": "never",
            "spanNulls": false,
            "stacking": {
              "group": "A",

        }

        // Note, that the potential side effect of the transformed provider
        // is going to be executed before this fixed side effect.
        // It is not possible to preserve linear execution order in the general case,
        // as the transformed provider can have side effects hidden under other wrapping providers.
        return Providers.internal(transformedProvider).withSideEffect(SideEffect.fixedFrom(value));

#include "xla/service/hlo.pb.h"
#include "tensorflow/core/platform/path.h"
#include "tensorflow/core/public/session.h"

namespace tensorflow {
namespace {

// Creates a float tensor of linearly increasing values, starting from offset.
Tensor CreateInputTensor(const TensorShape& shape, float offset) {
  Tensor tensor(DT_FLOAT, shape);
  for (int64 i = 0; i < tensor.flat<float>().size(); ++i) {

  mutex_lock lock(mu_);
  if (!definition_event_) {
    return;
  }

  // The set of defined streams is expected to be very small indeed (usually
  // 1-2), so a simple linear scan should be fast enough.
  if (std::find(streams_defined_on_.begin(), streams_defined_on_.end(),
                stream) != streams_defined_on_.end()) {
    // stream is in streams_defined_on_; it doesn't need to be waited on.

    }
    return this;
  }

  /**
   * Adds each member of {@code elements} as a candidate for the top {@code k} elements. This
   * operation takes amortized linear time in the length of {@code elements}.
   *
   * <p>If all input data to this {@code TopKSelector} is in a single {@code Iterable}, prefer