import org.apache.maven.artifact.resolver.ArtifactResolutionResult;
import org.apache.maven.artifact.versioning.InvalidVersionSpecificationException;
import org.apache.maven.artifact.versioning.VersionRange;
import org.apache.maven.bridge.MavenRepositorySystem;
import org.apache.maven.model.Dependency;
import org.apache.maven.model.Plugin;
import org.apache.maven.model.Repository;
import org.apache.maven.model.io.ModelReader;

  bool use_mlir_bridge = false;
  if (!flags.mlir_components.empty() && flags.mlir_components != "None") {
    for (auto component : absl::StrSplit(flags.mlir_components, ',')) {
      if (component == "Bridge") {
        use_mlir_bridge = true;
      } else if (component == "HloLowering") {
        use_mlir_hlo_lowering = true;
      } else {
        return errors::Unknown("Unknown mlir_component ", component);
      }

   * (In other words, this method must allocate a new array). The caller is thus free to modify the
   * returned array.
   *
   * <p>This method acts as bridge between array-based and collection-based APIs.
   *
   * @return an array containing all of the elements in this queue
   */
  @CanIgnoreReturnValue
  @Override
  public Object[] toArray() {

#include "mlir/Transforms/DialectConversion.h"  // from @llvm-project
#include "stablehlo/dialect/ChloOps.h"  // from @stablehlo
#include "tensorflow/compiler/mlir/quantization/stablehlo/passes/bridge/passes.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/utils/tf_type_utils.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_dialect.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

# tf_compile, so this allows the configurations to be specified in one place.
# suffix, mlir_component
tfcompile_test_dep_configs = [
    ("", "None"),
    ("_mlir_bridge", "Bridge"),
]

[
    [
        tf_library(
            name = "test_graph_tfadd" + suffix,
            testonly = 1,
            config = "test_graph_tfadd.config.pbtxt",
            cpp_class = "AddComp",

// Checks if `type` is allowed for XLA. String and resources are not XLA types.
// There are other TF types that are not XLA types which will be removed by
// successive passes in TF/XLA bridge phase 2.
bool TypeValidForXLA(const mlir::Type& type);

// Returns the map from core to the host that is associated with the
// core. If `cluster` is not replicated then the core is a physical core index

   * (In other words, this method must allocate a new array). The caller is thus free to modify the
   * returned array.
   *
   * <p>This method acts as bridge between array-based and collection-based APIs.
   *
   * @return an array containing all of the elements in this queue
   */
  @CanIgnoreReturnValue
  @Override
  public Object[] toArray() {

using quant::tensorflow::IsTFQintType;
using quant::tensorflow::IsTFUniformQuantizedOp;

#define GEN_PASS_DEF_CONVERTTFQUANTTYPES
#include "tensorflow/compiler/mlir/quantization/stablehlo/passes/bridge/passes.h.inc"

// TODO: b/290366702 - Temporarily added metrics for debugging.
auto *mlir_tf_quant_op_count = ::tensorflow::monitoring::Counter<1>::New(
    "/tensorflow/core/tf2xla/tf_quant_op_count" /*metric_name*/,

import org.apache.maven.artifact.repository.ArtifactRepository;
import org.apache.maven.artifact.repository.ArtifactRepositoryPolicy;
import org.apache.maven.artifact.repository.layout.ArtifactRepositoryLayout;
import org.apache.maven.bridge.MavenRepositorySystem;
import org.apache.maven.execution.DefaultMavenExecutionRequest;
import org.apache.maven.execution.DefaultMavenExecutionResult;
import org.apache.maven.execution.MavenSession;

import java.util.List;
import java.util.Map;
import java.util.Properties;

import org.apache.maven.artifact.InvalidRepositoryException;
import org.apache.maven.artifact.repository.ArtifactRepository;
import org.apache.maven.bridge.MavenRepositorySystem;
import org.apache.maven.eventspy.internal.EventSpyDispatcher;
import org.apache.maven.execution.DefaultMavenExecutionRequest;
import org.apache.maven.execution.MavenExecutionRequest;