pytorch/ignite

enable automatic mixed precision for xla

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#1,931 建立於 2021年4月12日

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 (8 留言) (1 反應) (0 負責人)Python (4,313 star) (602 fork)batch import
enhancementhelp wanted

描述

Feature

Automatic mixed precision for xla has landed in pytorch 1.8.1 and torch/xla nightly. We should enable it in create_supervised_* helper functions.

Suggested solution

Remove xla and amp checks in _check_arg().

  • For create_supervised_trainer, update supervised_training_step_tpu() function to accept scaler argument just like supervised_training_step_amp().
  • For create_supervised_evaluator, just removing xla and amp checks in _check_arg() should work.
  • For tests, we could remove xla checks and only run with pytorch 1.8.1.

Additional context

This feature should not be included in ignite release until the next torch and xla comes out.

貢獻者指南

技術棧
pythonpytorch
領域
machine learningperformance
議題類型
feature
難度面向新貢獻者的預計實作難度，1 表示很小改動，5 表示專家級工作。
3
預計時間有經驗貢獻者完成調查、實作、測試並準備 pull request 的粗略時間範圍。
1-3 hours
活動狀態議題目前的可參與程度：新鮮、活躍、陳舊、阻塞或等待維護者輸入。
stale
清晰度議題是否清楚說明預期改動、驗收標準和下一步。
clear
前置要求
PyTorchIgniteAMPXLA
新手友善度1-100 的估計分數，表示該議題對首次貢獻者的友善程度。
50
研究方向
Implement the changes as described in the issue: remove XLA and AMP checks in ` check arg()` in `ignite/engine/ init .py`. Update `supervised training step tpu()` to accept a `scaler` argument similar to `supervised training step amp()`. For the evaluator, just removing checks should suffice. Also update tests to run only with PyTorch 1.8.1.