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[gptj] support older pytorch version (#22325)

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* [gptj] support older pytorch version

* contributor

* contributor

* make copies

---------

Co-authored-by: Michael Wyatt <michaelwyatt@microsoft.com>
Co-authored-by: Nick Hill <nickhill@us.ibm.com>
This commit is contained in:
Stas Bekman 2023-03-22 18:35:04 -07:00 committed by GitHub
parent 80e3b36361
commit 61f79b2986
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2 changed files with 3 additions and 2 deletions
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2
src/transformers/models/codegen/modeling_codegen.py
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@ -55,7 +55,7 @@ CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST = [
def create_sinusoidal_positions(num_pos: int, dim: int) -> torch.Tensor:
inv_freq = 1.0 / (10000 ** (torch.arange(0, dim, 2) / dim))
sinusoid_inp = torch.einsum("i , j -> i j", torch.arange(num_pos, dtype=torch.float), inv_freq).float()
return torch.concat((torch.sin(sinusoid_inp), torch.cos(sinusoid_inp)), dim=1)
return torch.cat((torch.sin(sinusoid_inp), torch.cos(sinusoid_inp)), dim=1)
# Copied from transformers.models.gptj.modeling_gptj.rotate_every_two

3
src/transformers/models/gptj/modeling_gptj.py
View File

@ -18,6 +18,7 @@ import warnings
from typing import Optional, Tuple, Union
import torch
import torch.fx
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
@ -57,7 +58,7 @@ GPTJ_PRETRAINED_MODEL_ARCHIVE_LIST = [
def create_sinusoidal_positions(num_pos: int, dim: int) -> torch.Tensor:
inv_freq = 1.0 / (10000 ** (torch.arange(0, dim, 2) / dim))
sinusoid_inp = torch.einsum("i , j -> i j", torch.arange(num_pos, dtype=torch.float), inv_freq).float()
return torch.concat((torch.sin(sinusoid_inp), torch.cos(sinusoid_inp)), dim=1)
return torch.cat((torch.sin(sinusoid_inp), torch.cos(sinusoid_inp)), dim=1)
@torch.fx.wrap