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Make from apex import amp argument dependent #87

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Make from apex import amp argument dependent #87

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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -219,7 +219,7 @@ In our original paper, we acknowledge that there were anomalies in the test data
## 👉 Train
Prepare your own dataset and refer to the samples in `SAM-Med2D/data_demo` to replace them according to your specific scenario. You need to generate the `image2label_train.json` file before running `train.py`.

If you want to use mixed-precision training, please install [Apex](https://github.com/NVIDIA/apex). If you don't want to install Apex, you can comment out the line `from apex import amp` and set `use_amp` to False.
If you want to use mixed-precision training, please install [Apex](https://github.com/NVIDIA/apex).

```bash
cd ./SAM-Med2D
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3 changes: 2 additions & 1 deletion train.py
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Expand Up @@ -13,7 +13,6 @@
import numpy as np
import datetime
from torch.nn import functional as F
from apex import amp
import random


Expand Down Expand Up @@ -102,6 +101,8 @@ def prompt_and_decoder(args, batched_input, model, image_embeddings, decoder_ite


def train_one_epoch(args, model, optimizer, train_loader, epoch, criterion):
if args.use_amp:
from apex import amp
train_loader = tqdm(train_loader)
train_losses = []
train_iter_metrics = [0] * len(args.metrics)
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