安裝中文字典英文字典辭典工具!
安裝中文字典英文字典辭典工具!
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- Build production-grade data and ML workflows, hassle-free with Flyte
Flyte is the infinitely scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks
- Welcome to Flyte! — Flyte
Flyte is an open-source, Kubernetes-native workflow orchestrator implemented in Go It enables highly concurrent, scalable and reproducible workflows for data processing, machine learning and analytics
- User guide | Union. ai Docs - Flyte
Flyte is an open-source, Kubernetes-native workflow orchestrator implemented in Go Flyte empowers AI development teams to rapidly ship high-quality code to production by offering optimized performance, unparalleled resource efficiency, and a delightful workflow authoring experience
- Mitigate the trade-off between scalability and ease of use - Flyte
With its meticulous design, robust architecture, and simple SDKs, Flyte makes it easy to orchestrate your data and ML workflows It is an ideal choice for high-performance teams to build workflows better and deploy faster Make the switch — your team will thank you for it
- Registering workflows — Flyte
In this guide, you learned about the Flyte demo cluster, Flyte configuration, and the different registration patterns you can leverage during the workflow development lifecycle In the next guide, we’ll learn how to run and schedule workflows programmatically
- Pyflyte CLI — Flyte
Retrieve Inputs Outputs for a Flyte Execution or any of the inner node executions from the remote server The URI can be retrieved from the Flyte Console, or by invoking the get_data API
- Versions — Flyte
In Flyte, every task is versioned, and it precisely captures the dependency set For external tasks, memoization is recommended so that the constructed dataset can be cached on the Flyte side This way, one can guarantee reproducible behavior from the external systems
- Map tasks — Flyte
Using a map task in Flyte allows for the execution of a pod task or a regular task across a series of inputs within a single workflow node This capability eliminates the need to create individual nodes for each instance, leading to substantial performance improvements
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