Data input/output

An LLM-optimized bundle of this entire section is available at section.md. This single file contains all pages in this section, optimized for AI coding agent context.

This section covers how to manage data input and output in Union.ai. Union.ai also supports all the Data input/output features of Flyte.

Section	Description
`FlyteFile`	Use `FlyteFile` to easily pass files across tasks.
`FlyteDirectory`	Use `FlyteDirectory` to easily pass directories across tasks.
`Downloading with FlyteFile and FlyteDirectory`	Details on how files and directories or downloaded with `FlyteFile`.
`StructuredDataset`	Details on how `StructuredDataset`is used as a general dataframe type.
`Dataclass`	Details on how to uses dataclasses across tasks.
`Pydantic BaseModel`	Details on how to use pydantic models across tasks.
`Accessing Attributes`	Details on how to directly access attributes on output promises for
`Enums`	Details on how use Enums across tasks.
`Pickle`	Details on how use pickled objects across tasks for generalized typ
`Pytorch`	Details on how use torch tensors and models across tasks.
`Tensorflow`	Details on how use tensorflow tensors and models across tasks.
`Accelerated datasets`	Upload your data once and access it from any task.