[fx] provide a stable but not accurate enough version of profiler. (#1547)

* [fx] compute memory stat and flop count for MetaInfoProp.

* [fx] modify node attribute.

* [fx] modify ckpt_chen.

* [fx] fix compatibility.

* [fx] fix import error.

* [fx] skip test for MetaInfoProp.

* [fx] skip test for MetaInfoProp.

* [fx] skip test for MetaInfoProp.

* [fx] skip test for MetaInfoProp.

* [fx] skip if torch 1.11.0.

* [fx] recover MetaInfoProp support for PyTorch 1.11.

* [fx] provide a stable but not accurate enough version of profiler.

* [fx] provide a stable but not accurate enough version of profiler.

* [fx] fix compatibility in tests.

* [fx] fix compatibility in tests.

* [fx] fix compatibility in tests.

* [fx] fix compatibility in tests.

* [fx] fix compatibility in tests.

* [fx] fix compatibility in tests.

* [fx] fix compatibility in tests.

* [fx] fix compatibility in tests.

* [fx] fix compatibility in tests.

* [fx] fix compatibility in tests.

* [fx] fix import error.
This commit is contained in:
Super Daniel
2022-09-07 11:21:04 +08:00
committed by GitHub
parent 7d49e7b2db
commit 4f59693207
38 changed files with 776 additions and 263 deletions

View File

@@ -0,0 +1,11 @@
from typing import Tuple
import torch
from ..registry import meta_profiler_module
@meta_profiler_module.register(torch.nn.Embedding)
def torch_nn_embedding(self: torch.nn.Embedding, input: torch.Tensor) -> Tuple[int, int]:
# nn.Embedding is a dictionary lookup, so technically it has 0 FLOPs. (https://discuss.pytorch.org/t/correct-way-to-calculate-flops-in-model/67198/6)
flops = 0
macs = 0
return flops, macs