mirror of
https://github.com/hpcaitech/ColossalAI.git
synced 2025-08-25 19:21:17 +00:00
4f59693207
* [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.
20 lines
630 B
Python
20 lines
630 B
Python
import torch
|
|
from typing import Optional
|
|
from ..registry import meta_profiler_function
|
|
|
|
|
|
@meta_profiler_function.register(torch.nn.functional.embedding)
|
|
def torch_nn_functional_embedding(
|
|
input: torch.Tensor,
|
|
weight: torch.Tensor,
|
|
padding_idx: Optional[int] = None,
|
|
max_norm: Optional[float] = None,
|
|
norm_type: float = 2.0,
|
|
scale_grad_by_freq: bool = False,
|
|
sparse: bool = False,
|
|
) -> torch.Tensor:
|
|
# F.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
|