如何安装torchcrf并修复导入错误？
如何安装torchcrf并修复导入错误？
提问于 2022-09-27 14:12:00
我使用Windows11pro x64，PyCharm 2022.2.2 (专业版)- Build #PY-222.4167.33，建于2022年9月15日。Python版本：
Microsoft Windows [Version 10.0.22621.521]
(c) Microsoft Corporation. All rights reserved.
C:\Users\donhu>python
Python 3.10.7 (tags/v3.10.7:6cc6b13, Sep 5 2022, 14:08:36) [MSC v.1933 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>>我的代码
import argparse
import yaml
import pandas as pd
import torch
import torchcrf
import transformers
from data import Dataset
from engines import train_fn
import warnings
warnings.filterwarnings("ignore")
parser = argparse.ArgumentParser()
parser.add_argument("--data_file", type=str)
parser.add_argument("--hyps_file", type=str)
args = parser.parse_args()
data_file = yaml.load(open(args.data_file), Loader=yaml.FullLoader)
hyps_file = yaml.load(open(args.hyps_file), Loader=yaml.FullLoader)
train_loader = torch.utils.data.DataLoader(
Dataset(
df=pd.read_csv(data_file["train_df_path"]),
tag_names=data_file["tag_names"],
tokenizer=transformers.AutoTokenizer.from_pretrained(hyps_file["encoder"], use_fast=False),
),
num_workers=hyps_file["num_workers"],
batch_size=hyps_file["batch_size"],
shuffle=True,
)
val_loader = torch.utils.data.DataLoader(
Dataset(
df=pd.read_csv(data_file["val_df_path"]),
tag_names=data_file["tag_names"],
tokenizer=transformers.AutoTokenizer.from_pretrained(hyps_file["encoder"], use_fast=False),
),
num_workers=hyps_file["num_workers"],
batch_size=hyps_file["batch_size"] * 2,
)
loaders = {
"train": train_loader,
"val": val_loader,
}
model = transformers.RobertaForTokenClassification.from_pretrained(hyps_file["encoder"],
num_labels=data_file["num_tags"])
if hyps_file["use_crf"]:
criterion = torchcrf.CRF(num_tags=data_file["num_tags"], batch_first=True)
else:
criterion = torch.nn.CrossEntropyLoss()
optimizer = torch.optim.Adam(model.parameters(), lr=float(hyps_file["lr"]))
train_fn(
loaders, model, torch.device(hyps_file["device"]), hyps_file["device_ids"],
criterion,
optimizer,
epochs=hyps_file["epochs"],
ckp_path="../ckps/{}.pt".format(hyps_file["encoder"].split("/")[-1]),
)我用PyCharm安装
我还按命令安装
pip install torchcrf我也试着
pip install pytorch-crf但我不是成功。
如何安装torchcrf并修复导入错误？
回答 1
Stack Overflow用户
发布于 2022-09-27 14:25:03
安装
from TorchCRF import CRF重写代码
import argparse
import yaml
import pandas as pd
import torch
from TorchCRF import CRF
import transformers
from data import Dataset
from engines import train_fn
import warnings
warnings.filterwarnings("ignore")
parser = argparse.ArgumentParser()
parser.add_argument("--data_file", type=str)
parser.add_argument("--hyps_file", type=str)
args = parser.parse_args()
data_file = yaml.load(open(args.data_file), Loader=yaml.FullLoader)
hyps_file = yaml.load(open(args.hyps_file), Loader=yaml.FullLoader)
train_loader = torch.utils.data.DataLoader(
Dataset(
df=pd.read_csv(data_file["train_df_path"]),
tag_names=data_file["tag_names"],
tokenizer=transformers.AutoTokenizer.from_pretrained(hyps_file["encoder"], use_fast=False),
),
num_workers=hyps_file["num_workers"],
batch_size=hyps_file["batch_size"],
shuffle=True,
)
val_loader = torch.utils.data.DataLoader(
Dataset(
df=pd.read_csv(data_file["val_df_path"]),
tag_names=data_file["tag_names"],
tokenizer=transformers.AutoTokenizer.from_pretrained(hyps_file["encoder"], use_fast=False),
),
num_workers=hyps_file["num_workers"],
batch_size=hyps_file["batch_size"] * 2,
)
loaders = {
"train": train_loader,
"val": val_loader,
}
model = transformers.RobertaForTokenClassification.from_pretrained(hyps_file["encoder"],
num_labels=data_file["num_tags"])
if hyps_file["use_crf"]:
criterion = CRF(num_tags=data_file["num_tags"], batch_first=True)
else:
criterion = torch.nn.CrossEntropyLoss()
optimizer = torch.optim.Adam(model.parameters(), lr=float(hyps_file["lr"]))
train_fn(
loaders, model, torch.device(hyps_file["device"]), hyps_file["device_ids"],
criterion,
optimizer,
epochs=hyps_file["epochs"],
ckp_path="../ckps/{}.pt".format(hyps_file["encoder"].split("/")[-1]),
)页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/73869068
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