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hub / github.com/apple/axlearn / PartitionedGradientTransformation

Class PartitionedGradientTransformation

axlearn/common/optimizer_base.py:71–82  ·  view source on GitHub ↗

An optax-style optimizer with a function to partition the inputs across devices. For new optimizers, using `UpdateTransformation` is preferred instead because it supports more types of optimizers and allows better reuse of functionality across different optimizers. Despite this, there

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69
70
71class PartitionedGradientTransformation(NamedTuple):
72 """An optax-style optimizer with a function to partition the inputs across devices.
73
74 For new optimizers, using `UpdateTransformation` is preferred instead because it supports
75 more types of optimizers and allows better reuse of functionality across different optimizers.
76
77 Despite this, there are no plans to stop supporting this class.
78 """
79
80 init: TransformInitFn
81 update: TransformUpdateFn
82 partition: TransformPartitionSpecFn

Callers 15

scale_by_factored_rmsFunction · 0.90
_counterFunction · 0.90
chainFunction · 0.90
named_chainFunction · 0.90
_no_opFunction · 0.90
with_partition_fnFunction · 0.90
replace_with_updatesFunction · 0.90
scale_by_scheduleFunction · 0.90
scale_update_per_paramFunction · 0.90
add_decayed_weightsFunction · 0.90
l2_regularizerFunction · 0.90
emaFunction · 0.90

Calls

no outgoing calls

Tested by 1

_counterFunction · 0.72