Comments (6)
The environment we used is as follows:
- Python == 3.8.3
- torch ==1.8.1+cu111
- torchvision == 0.9.1+cu111
and it can work.
The version of pip is not the same version published on github
Yes. The code on github is lastest. We will release the lastest version on PyPi soon.
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Thanks,I have a another question:
The framework's encoding and decoding must be used or can pass empty objects(like nn.nn.Module)
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Actually, I don't understand your question and I hope you can clarify it or give some examples. In fact, encoder_class
here must be a class, not an instantiated object, but decoders
is the opposite.
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Yes,I didn't express it very clearly
I wondered if it was possible not to use Encoder
and decoders
class
Because not all models have to be encoded and decoded
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encoder_class
and decoders
are used to define the network architecture of the model and they are necessary.
The meanings of encoder_class
and decoders
may be more general. For example, in the hard-parameter sharing pattern, encoder_class
represents the task-sharing parameters (usually the feature extractor in cv problems), and decoders
denotes the task-specific parameters (usually the output modules).
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In train.py, .next() can't run
I got a same error! -> "AttributeError: 'dict_keyiterator' object has no attribute 'next'"
This method has been deleted in python 3?
Why not use next(iter)?
or what should I do to fix it?
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Related Issues (20)
- 关于rep_grads参数的问题 HOT 5
- 关于tabular数据的训练问题 HOT 4
- Not found the script for testing in examples/* HOT 6
- Image size of NYUv2 dataset should be 3*288*384 HOT 3
- Error while "from torchvision.models.utils import load_state_dict_from_url" HOT 3
- How to implement MTL scenario when each sample has some of the labels available and not for all the tasks. HOT 1
- GradNorm求梯度 HOT 5
- Inconsistency between formula and implementation in count_improvement function HOT 2
- It seems that some functions are not compatible with the latest pytorch HOT 1
- 关于abstract_weighting.py中get_share_params的问题 HOT 2
- MMOE - Replicate the Original paper Chapter 3.2 (Synthetic Data) HOT 1
- Question about my understanding of aligned-MTL HOT 6
- Distributed DataParallel support HOT 2
- AttributeError: 'Net' object has no attribute 'conv1' HOT 2
- Aligned-MTL-UB Efficient version HOT 2
- 如何更新DWA中的train_loss_buffer HOT 2
- Question regarding the results in Table 1 of the paper HOT 2
- 训练效果会受到epoch大小的影响吗,我只有一个任务同时使用6个loss,想看一下效果 HOT 3
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