**Use case**

Generate models once and reuse them.

**Describe the solution you'd like**

Add command line options:
```
--save file - write serialized models on disk after training and before generating the data; the user can set --limit to 0 to only train the models and save them without proceeding to data generation;
--load file - instead of training the models, load the prepared models from the file and start generating the data.
```

Serialization format: one byte for version (equals to 0), then simple binary serialization of all the models; the whole file is compressed with ZSTD level 1 using CompressedWriteBuffer (no need to allow any compression options to choose).
{
private:
    UInt64 seed;
public:
    explicit UUIDModel(UInt64 seed_) : seed(seed_) {}
    void train(const IColumn &) override {}
    void finalize() override {}
    ColumnPtr generate(const IColumn & column) override
    {
        const ColumnUUID & src_column = assert_cast<const ColumnUUID &>(column);
        const auto & src_data = src_column.getData();
        auto res_column = ColumnUUID::create();
        auto & res_data = res_column->getData();
        res_data.resize(src_data.size());
        for (size_t i = 0; i < src_column.size(); ++i)
            transformUUID(src_data[i], res_data[i], seed);
        return res_column;
    }
    void updateSeed() override
    {
        seed = hash(seed);
    }
};
class DateTimeModel : public IModel