auto collectOps = [this](Operation *op) {
    const auto &op_name = op->getName().getStringRef().str();
    if (absl::StartsWith(op_name, "tf.") || absl::StartsWith(op_name, "tfl.")) {
      loc_to_name_.emplace(op->getLoc(), op_name);
    }
  };

  for (auto &region : module->getRegions()) {
    region.walk(collectOps);
  }

  pass_name_ = extract_pass_name(pass->getName().str());
  error_collector_->Clear();
}

    for (int i = 0; i < op->getNumOperands(); i++) {
      Value input = op->getOperand(i);
      if (getElementTypeOrSelf(input).isBF16()) {
        Value f32_cast = rewriter.create<TF::CastOp>(
            op->getLoc(),
            CloneTypeWithNewElementType(input.getType(), rewriter.getF32Type()),
            input);
        op->setOperand(i, f32_cast);
      }
    }

    // Casts BF16 outputs of the operation.

    auto new_reshape_type = RankedTensorType::get(new_reshape_dims, el_ty);
    ReshapeOp new_reshape =
        rewriter.create<ReshapeOp>(new_reshape_shape.getLoc(), new_reshape_type,
                                   op.getInput(), new_reshape_shape);
    TF::ConstOp new_broadcast_shape =
        GetI64ConstantTensor(rewriter, reshape_shape, op.getLoc());

  for (Value result : new_launch_op_results)
    new_launch_op_results_types.push_back(result.getType());

  auto new_launch_op = builder.create<tf_device::LaunchOp>(
      old_launch_op->getLoc(), old_launch_op->getDeviceAttr(),
      /*result_types=*/new_launch_op_results_types);

  new_launch_op.getBody().takeBody(old_launch_op->getBody());

  // When creating the new const op, use a fused location that combines the
  // original const and the qbarrier that led to the quantization.
  auto fusedLoc = rewriter.getFusedLoc(
      {qbarrier.getArg().getDefiningOp()->getLoc(), qbarrier.getLoc()});
  auto newConstOp = rewriter.create<arith::ConstantOp>(
      fusedLoc, newConstValueType, cast<TypedAttr>(newConstValue));
  rewriter.replaceOpWithNewOp<StorageCastOp>(qbarrier, qbarrier.getType(),

		// reuse.
		x, _ = l.shared.popHead()
		if x == nil {
			x = p.getSlow(pid)
		}
	}
	runtime_procUnpin()
	if race.Enabled {
		race.Enable()
		if x != nil {
			race.Acquire(poolRaceAddr(x))
		}
	}
	if x == nil && p.New != nil {
		x = p.New()
	}
	return x
}

func (p *Pool) getSlow(pid int) any {
	// See the comment in pin regarding ordering of the loads.

      other.addEntryBlock();
      OpBuilder builder(other.getRegion());
      auto call_op = builder.create<mlir::func::CallOp>(
          f.getLoc(), f.getFunctionType().getResults(), f.getSymName(),
          other.getRegion().getArguments());
      builder.create<mlir::func::ReturnOp>(f.getLoc(), call_op.getResults());
    }

    Unexport(f);
  }
}

}  // namespace

std::unique_ptr<OperationPass<ModuleOp>>

    // be created and updated, rather than updating the old op. Thus we use an
    // OperationState so we can add regions to the new op.
    OperationState state(op->getLoc(), op->getName().getStringRef(), operands,
                         new_results, op->getAttrs(), op->getSuccessors());
    for (Region& region : op->getRegions()) {
      Region& new_region = *state.addRegion();

        returned_type = quant::ConvertSignedQuantizedToUnsigned(
            dequantize_input.getType(), dequantize_op.getLoc());
        // replace the dequantize op by a quantize op
        TypeAttr type_attr = TypeAttr::get(returned_type);
        auto quantize_op = builder.create<QuantizeOp>(
            dequantize_op.getLoc(), returned_type, dequantize_input, type_attr);
        returned_value = quantize_op.getOutput();
      } else {

  builder.create<tf_saved_model::SessionInitializerOp>(
      module->getLoc(), builder.getArrayAttr(func_names));
  // Create AssetOp; this holds the checkpoint_path.
  // TODO(b/318761632): Cleanup usage of string literals, instead use constants.
  auto asset_op = builder.create<tf_saved_model::AssetOp>(
      module->getLoc(),
      /*sym_name=*/