// 20.8: Single-Precision Floating-Point Compare Instructions
	FEQS	F0, F1, X7				// d3a300a0
	FLTS	F0, F1, X7				// d39300a0
	FLES	F0, F1, X7				// d38300a0

	// 20.9: Single-Precision Floating-Point Classify Instruction
	FCLASSS	F0, X5					// d31200e0

	// 21.3: Double-Precision Load and Store Instructions
	FLD	(X5), F0				// 07b00200
	FLD	4(X5), F0				// 07b04200
	FSD	F0, (X5)				// 27b00200

quarkus/extensions/resteasy-classic/resteasy-mutiny/deployment/pom.xml
	quarkus/extensions/resteasy-classic/resteasy-mutiny-common/deployment/pom.xml
	quarkus/extensions/resteasy-classic/resteasy/deployment/pom.xml
	quarkus/extensions/resteasy-classic/resteasy-mutiny/runtime/pom.xml
	quarkus/test-framework/junit5-internal/pom.xml
	quarkus/extensions/resteasy-classic/resteasy-jsonb/deployment/pom.xml

        ch.qos.logback.classic.Level value;
        switch (level) {
            case DEBUG:
                value = ch.qos.logback.classic.Level.DEBUG;
                break;

            case INFO:
                value = ch.qos.logback.classic.Level.INFO;
                break;

            default:
                value = ch.qos.logback.classic.Level.ERROR;
                break;
        }

import java.util.ArrayList;
import java.util.List;

import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.core.WhitespaceAnalyzer;
import org.apache.lucene.queryparser.classic.ParseException;
import org.apache.lucene.queryparser.classic.QueryParser.Operator;
import org.apache.lucene.queryparser.ext.ExtendableQueryParser;
import org.apache.lucene.queryparser.ext.Extensions.Pair;
import org.apache.lucene.search.PhraseQuery;

class TracingTensorHandle : public AbstractTensorHandle {
 protected:
  explicit TracingTensorHandle(AbstractTensorHandleKind kind)
      : AbstractTensorHandle(kind) {}

 public:
  // For LLVM style RTTI.
  static bool classof(const AbstractTensorHandle* ptr) {
    return ptr->getKind() == kGraph || ptr->getKind() == kMlir;
  }
};

// An abstract operation describes an operation by its type, name, and

    prediction-flavored outputs, in addition to the classification-flavored one.
    Building signatures from these allows TF Serving to honor requests using the
    different APIs (Classify, Regress, and Predict). Furthermore,
    `serving_input_receiver_fn()` may now specify alternative subsets of nodes
    that may act as inputs. This allows, for instance, producing a prediction

    List<Class<?>> classes = Lists.newArrayList();
    String packageName = getClass().getPackage().getName();
    for (ClassPath.ClassInfo classInfo :
        ClassPath.from(getClass().getClassLoader()).getTopLevelClasses(packageName)) {
      Class<?> cls;
      try {
        cls = classInfo.load();
      } catch (NoClassDefFoundError e) {

  absl::StatusOr<core::RefCountPtr<FunctionRecord>> GetFunctionRecord()
      override {
    return func_record_.GetNewRef();
  }

  // For LLVM style RTTI.
  static bool classof(const AbstractFunction* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  core::RefCountPtr<FunctionRecord> func_record_;
};
}  // namespace graph
}  // namespace tracing
}  // namespace tensorflow

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    if (ft == nullptr) {
      return FullTypeDef();
    } else {
      return *ft;
    }
  }

  TF_Output output_;

  // For LLVM style RTTI.
  static bool classof(const AbstractTensorHandle* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  TF_Graph* graph_;  // For shape inference.
};

// GraphOperation wraps and populates a TF_OperationDescription.