mlir::Operation* GetXlaShardingFromOperand(Value value) {
  Value value_to_visit = value;
  if (auto read_var = value_to_visit.getDefiningOp<mlir::TF::ReadVariableOp>())
    value_to_visit = read_var.getResource();

  if (auto partitioned_input =
          value_to_visit.getDefiningOp<mlir::TF::TPUPartitionedInputV2Op>()) {
    return NullUnlessSharded(partitioned_input);
  }

  return nullptr;
}

    // Only values defined by IslandOp were inserted in the worklist.
    IslandOp current_island = cast<IslandOp>(control_barrier.getDefiningOp());

    for (auto control_input : current_island.getControlInputs()) {
      ops_connected_to_fetch->insert(control_input.getDefiningOp());
      if (IsNoOpControlBarrier(control_input))
        control_barrier_worklist.push(control_input);
    }
    current_island.erase();

    if (handle_user == assign_var) continue;
    auto assign_var_user = dyn_cast<TF::AssignVariableOp>(handle_user);
    if (!assign_var_user) continue;
    if (assign_var_user.getValue().getDefiningOp() == cluster_func)
      return resource;
  }

  resource.resource = assign_var.getResource();
  resource.subtype = assign_var.getValue().getType();
  return resource;
}

  // hoisted.
  auto read_var_op = llvm::dyn_cast<ReadVariableOp>(op);
  if (!read_var_op) return false;
  auto var_handle_op = llvm::dyn_cast_or_null<VarHandleOp>(
      read_var_op.getResource().getDefiningOp());
  if (!var_handle_op) return false;
  return read_only_vars.contains(GetResourceHandle(var_handle_op));
}

bool ShouldMoveOutOfRegion(
    Operation *op, Region *region,

        func_op.getRegion().getBlocks().front().getTerminator());
    if (!return_op) return failure();
    auto req_op = llvm::dyn_cast_or_null<mlir::stablehlo::UniformQuantizeOp>(
        return_op.getOperands()[0].getDefiningOp());
    if (!req_op) return failure();

    // Create a new func.call op with f32 output.
    auto new_call_op = call_op.clone();
    new_call_op->getResult(0).setType(

      >();
}

OpFoldResult StorageCastOp::fold(FoldAdaptor) {
  // Matches x -> [scast -> scast] -> y, replacing the second scast with the
  // value of x if the casts invert each other.
  auto srcScastOp = getArg().getDefiningOp<StorageCastOp>();
  if (!srcScastOp || srcScastOp.getArg().getType() != getType())
    return OpFoldResult();
  return srcScastOp.getArg();
}

/// The quantization specification should match the expressed type.

      >();
}

OpFoldResult StorageCastOp::fold(FoldAdaptor) {
  // Matches x -> [scast -> scast] -> y, replacing the second scast with the
  // value of x if the casts invert each other.
  auto srcScastOp = getArg().getDefiningOp<StorageCastOp>();
  if (!srcScastOp || srcScastOp.getArg().getType() != getType())
    return OpFoldResult();
  return srcScastOp.getArg();
}

/// The quantization specification should match the expressed type.

      if (matchPattern(quantize_operand, m_Constant(&attr))) {
        // Const-> QuantizeOp pattern will be handled separately.
        return failure();
      }
      if (Operation* quantizing_op = quantize_operand.getDefiningOp()) {
        quantizing_ops.push_back(quantizing_op);
      }
    }

    tensorflow::DataType inference_type =
        quant_params_.quant_spec.inference_type;
    bool weight_only_quantization =

                                    Value max_size, Operation* op,
                                    Type element_dtype, OpBuilder builder,
                                    Value* buffer) {
  auto max_count_op = max_size.getDefiningOp();
  if (!max_count_op) return op->emitOpError("unknown max element count");
  auto max_count_const_op = llvm::dyn_cast<TF::ConstOp>(max_count_op);
  if (!max_count_const_op) return op->emitOpError("unknown max element count");

        all_reduce.getGroupSize()
            .getDefiningOp<TF::CollectiveAssignGroupV2Op>();

    if (assign_group) {
      // Found a group assignment. Use replica_groups to represent group
      // assignment.

      if (assign_group != all_reduce.getGroupKey()
                              .getDefiningOp<TF::CollectiveAssignGroupV2Op>()) {
        return all_reduce->emitOpError()