[Relay] GradientCell Relay Pass #5039
Conversation
|
had you rebased? |
|
Just to be clear, this pass save 50% memory for reverse mode ad. |
hypercubestart
changed the title
hypercubestart
force-pushed
the
ad
branch
2 times, most recently
from
1783a45
to
807c8e8
Compare
| * module must have TypeDefinition of GradCell (defined in gradient.rly) | ||
| */ | ||
| Constructor getGradCellConstructor(IRModule module, std::string name_hint) { | ||
| TypeData gradCell = module->LookupTypeDef("GradCell"); |
There was a problem hiding this comment.
can you refactor this function into module?
There was a problem hiding this comment.
yeah, added it as GetConstructor function although it may be more appropriate to be a separate PR
| @@ -219,6 +219,18 @@ def DeadCodeElimination(inline_once=False): | |||
| """ | |||
| return _ffi_api.DeadCodeElimination(inline_once) | |||
|
|
|||
| def GradientCell(): | |||
There was a problem hiding this comment.
Is gradient cell really the right name for this given it is just making 1/0s lazy.
There was a problem hiding this comment.
renamed to LazyGradientInit, highlight that this pass should be used after reverse mode ad to lazily initiate tensor gradients
|
It would be great if you can add some information on why this pass is useful / needed. I understand that its important to conserve memory when computing gradients, but converting all tensors to a new type just lazily evaluate constant fills seems somewhat drastic. Can you give some numbers on the impact of this pass for typical functions? |
|
@jwfromm this pass should be used in conjunction with the gradient pass. Since tensors for reverse-mode ad are instantiated as 0-filled tensors but are actually not useful during the forward pass, this PR should reduce memory allocation by 50% during the forward pass. I don't have any data on this but mathematically this would make sense |
hypercubestart
force-pushed
the
ad
branch
2 times, most recently
from
5456d56
to
0d78212
Compare
|
thanks @jroesch ! |
* save * gradient.rly * fix * NOT WORKING: gradient cell pass * test gradient pass * fixed basic call ops * more tests * fix bug * transform calls to one ones_like zero zero_like * maintenance stuff * fix linting * linting * linting * throw default * remove unrelated changes * import gradent.rly in pass * comment * linting * remove changes to test files * move gradient_cell.cc to transforms * revert change * update files with new commits * type * wrapper function to main outermost function type * fix linting * fix unsigned and signed int comparison * review * GetConstructor definition in module and change op comparison * update node instantiations * increase code readability Co-authored-by: Marisa Kirisame <lolisa@marisa.moe>
* save * gradient.rly * fix * NOT WORKING: gradient cell pass * test gradient pass * fixed basic call ops * more tests * fix bug * transform calls to one ones_like zero zero_like * maintenance stuff * fix linting * linting * linting * throw default * remove unrelated changes * import gradent.rly in pass * comment * linting * remove changes to test files * move gradient_cell.cc to transforms * revert change * update files with new commits * type * wrapper function to main outermost function type * fix linting * fix unsigned and signed int comparison * review * GetConstructor definition in module and change op comparison * update node instantiations * increase code readability Co-authored-by: Marisa Kirisame <lolisa@marisa.moe>
Add GradientCell relay pass which introduces the GradCell datatype. This pass can delay memory allocation and potentially improve memory usage and performance by delaying instantiations of zero-filled/one-filled tensors until necessary.