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Training on ADE20K

See original GitHub issue

Hello! I try to train default models from on ADE20K, but I see such error:

Input arguments:
batch_size_per_gpu 2
workers          16
lr_pow           0.9
seed             304
epoch_iters      5000
weight_decay     0.0001
root_dataset     ./data/
list_train       ./data/train.odgt
optim            SGD
num_epoch        20
ckpt             ./ckpt
list_val         ./data/validation.odgt
id               baseline
imgMaxSize       1000
deep_sup_scale   0.4
fix_bn           False
lr_encoder       0.02
gpus             0
beta1            0.9
random_flip      True
num_class        150
start_epoch      1
imgSize          [300, 375, 450, 525, 600]
arch_decoder     ppm_deepsup
disp_iter        20
padding_constant 8
segm_downsampling_rate 8
lr_decoder       0.02
fc_dim           2048
arch_encoder     resnet50dilated
Model ID: baseline-resnet50dilated-ppm_deepsup-ngpus1-batchSize2-imgMaxSize1000-paddingConst8-segmDownsampleRate8-LR_encoder0.02-LR_decoder0.02-epoch20
# samples: 20210
1 Epoch = 5000 iters
Traceback (most recent call last):
  File "", line 325, in <module>
  File "", line 200, in main
    train(segmentation_module, iterator_train, optimizers, history, epoch, args)
  File "", line 37, in train
    loss, acc = segmentation_module(batch_data)
  File "/home/ponomareva/.local/lib/python3.5/site-packages/torch/nn/modules/", line 477, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/ponomareva/semantic-segmentation-pytorch/models/", line 34, in forward
    (pred, pred_deepsup) = self.decoder(self.encoder(feed_dict['img_data'], return_feature_maps=True))
TypeError: list indices must be integers or slices, not str

Issue Analytics

  • State:open
  • Created 4 years ago
  • Reactions:2
  • Comments:5 (1 by maintainers)

github_iconTop GitHub Comments

ShihuaiXucommented, Sep 12, 2019

@hangzhaomit thanks your help and now this project supports single gpu?

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