NVIDIA / NVIDIA/apex

Get amp handler in a more decent way

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enhancement
Dominant language
Python
Stars
9k
Forks
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Avg merge
2d 4h
Merged PRs (30d)
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Description

Usually, the location of amp.init() is far from loss.backward(). While it is possible to pass the handler as a parameter to the function which calls loss.backward(), but it is not very decent. I wonder if we can do something like:

import torch
import apex
apex.amp.apex.init()

........


def backward(loss):
    with apex.amp.get_default_handler().scale_loss(loss, optimizer) as scaled_loss:
        scaled_loss.backward()
    optimizer.step()

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First steps

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Research direction

Start by tracing the existing amp.init() and scale_loss usage; the issue names no files, tests, or implementation entry points. Before coding, establish the intended default-handler API and define tests that show how initialization and backward usage should work; the issue currently provides no concrete completion criteria.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch
Domain
machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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