dsl = userQuestions.selectOption("Select build script DSL", initializer.getDsls(), initializer.getDefaultDsl());
        } else {
            dsl = BuildInitDsl.fromName(getDsl());
            if (!initializer.getDsls().contains(dsl)) {
                throw new GradleException("The requested DSL '" + getDsl() + "' is not supported for '" + initializer.getId() + "' build type");
            }
        }

 */
@LocalOnly(because = "Needs Android environment")
abstract class AbstractKotlinPluginAndroidSmokeTest extends AbstractSmokeTest implements RunnerFactory {
    abstract String getSampleName()
    abstract GradleDsl getDSL()

    VersionNumber kotlinPluginVersion

					failed = true
				}
				s = s[1:]
			}
			chunk = chunk[1:]
		}
	}
	if failed {
		return "", false, nil
	}
	return s, true, nil
}

// getEsc gets a possibly-escaped character from chunk, for a character class.
func getEsc(chunk string) (r rune, nchunk string, err error) {
	if len(chunk) == 0 || chunk[0] == '-' || chunk[0] == ']' {
		err = ErrBadPattern
		return
	}

    }
  }
  return true;
}

GlobalTensorUsesMap CreateGlobalTensorUsesMap(ModuleOp module) {
  GlobalTensorUsesMap global_tensor_uses;

  SymbolTable symbol_table(module);
  for (auto func : module.getOps<func::FuncOp>()) {
    for (size_t i = 0, e = func.getNumArguments(); i < e; i++) {
      auto sym =
          func.getArgAttrOfType<SymbolRefAttr>(i, "tf_saved_model.bound_input");
      if (!sym) {
        continue;

	r.mu.Lock()
	defer r.mu.Unlock()
	getDst := func(n int) []byte {
		if cap(dst) < n {
			return make([]byte, n)
		}
		return dst[:n]
	}

	if r.w == r.r {
		if r.isFull {
			buf := getDst(r.size)
			copy(buf, r.buf[r.r:])
			copy(buf[r.size-r.r:], r.buf[:r.w])
			return buf
		}
		return nil
	}

	if r.w > r.r {
		buf := getDst(r.w - r.r)
		copy(buf, r.buf[r.r:r.w])

            hasPackageStatement = source.getAST().getPackageName() != null;
        }
    }

    private static class EmptyScriptDetector extends CompilationUnit.SourceUnitOperation {
        private boolean emptyScript;
        private boolean hasMethods;

        @Override
        public void call(SourceUnit source) {
            if (!source.getAST().getMethods().isEmpty()) {
                hasMethods = true;

  TF::LoadResourceDataflowAnalysis(solver);
  if (failed(solver.initializeAndRun(module))) return signalPassFailure();

  DenseSet<GlobalTensorOp> remaining_global_tensor_ops;
  {
    auto ops = module.getOps<GlobalTensorOp>();
    remaining_global_tensor_ops.insert(ops.begin(), ops.end());
  }

  for (auto global_tensor : remaining_global_tensor_ops) {
    // This pass assumes that all global tensors as immutable (e.g. by a

  return ConvertDot(
      rewriter, dot_op.getLhs(), dot_op.getRhs(), dot_dimension_numbers,
      mlir::cast<ShapedType>(dot_op.getResult().getType()), dot_op.getLoc());
}

Value ConvertDotGeneralOp(PatternRewriter& rewriter, Operation* old_op) {
  auto dot_general_op = cast<mhlo::DotGeneralOp>(old_op);
  return ConvertDot(
      rewriter, dot_general_op.getLhs(), dot_general_op.getRhs(),
      dot_general_op.getDotDimensionNumbers(),

}

static LogicalResult convertTFGlobals(ModuleOp module) {
  OpBuilder globalBuilder(module.getBodyRegion());
  DenseMap<Operation *, std::string> opToName;
  for (auto globalTensor : module.getOps<tf_saved_model::GlobalTensorOp>()) {
    auto exportedNames = tf_saved_model::GetExportedNames(globalTensor);
    std::string name;
    if (exportedNames.empty()) {
      name = "global_ml_" + globalTensor.getSymName().str();

    Value constant_val = add_op ? add_op.getRhs() : sub_op.getRhs();
    if (!matchPattern(constant_val, m_Constant(&added_value))) return failure();

    // Check the add op is applied to begin.
    mlir::TypedValue<::mlir::TensorType> begin_tensor =
        strided_slice_op.getBegin();
    mlir::TypedValue<::mlir::TensorType> add_source_tensor =
        add_op ? add_op.getLhs() : sub_op.getLhs();
    if (begin_tensor != add_source_tensor) {