How to use Learner with pure PyTorch DataLoader

Hi,
Suppose I already have pure PyTorch code defining datset + dataloader. I want to use fastai v2 learner to train the model. See Jeremy’s blog https://www.fast.ai/2020/02/13/fastai-A-Layered-API-for-Deep-Learning/ (Section " Incrementally adapting PyTorch code")

data = DataLoaders(train_loader, test_loader).cuda()
learn = Learner(data, Net(), loss_func=F.nll_loss, opt_func=Adam, metrics=accuracy)
learn.fit_one_cycle(epochs, lr)

However, I encountered error --> DataLoader object has no attribute ‘to’

Hi SidNg,

The issue is that both torch and fastai2 define class DataLoader, with the fastai version having extra methods. You need to create your loaders using the fastai2 version of DataLoader. Then
dls = DataLoaders(trainDL, validDL).to(device)
will work.

HTH, Malcolm

3 Likes

Not working for me :frowning:

Pkgs versions:

  • pytorch: 1.8.0
  • fastai: 2.3.0

I have 2 torch.utils.data.DataLoader: train_dl and valid_dl

If I do

from fastai.learner       import Learner
from fastai.data.core     import DataLoaders
from fastai.callback.data import CudaCallback

learn = Learner(dls = DataLoaders(train_dl, valid_dl),
                # model, loss, metrics, ...
                cbs = [CudaCallback] # And other callbacks
               )

I get: AttributeError: 'DataLoader' object has no attribute 'device'

And if I change to some of this inside the Learner:

  • dls = DataLoaders(train_dl, valid_dl, device="cuda")
  • dls = DataLoaders(train_dl, valid_dl).cuda()
  • dls = DataLoaders(train_dl, valid_dl).to("cuda")

I get: AttributeError: 'DataLoader' object has no attribute 'to'

References

I follow the indications of:

Thanks in advance for the help :slight_smile:

Can you give us a full stack trace please?

Hola Javier,

See solution three posts above. Note that both “DataLoader” and “DataLoaders” must be fastai’s versions.

:slightly_smiling_face:

Only DataLoaders needs to be.

1 Like

The last time I tried, fit() fails when dls was created with PyTorch DataLoader’s (using CUDA). Has it been fixed?

I use raw torch DataLoaders in my tutorial. Did you include the CUDA callback?

This is my error when I use the fit() method of the Learner with:

  • dls = DataLoaders(train_dl, valid_dl) # train_dl and valid_dl are Pytorch Dataloader
  • cbs = [CudaCallback] # and others
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-29-b60c6a88c37b> in <module>
----> 1 learn.fit(1, 1e-2) # learn.fit_one_cycle(1, 1e-2)

~/.local/lib/python3.9/site-packages/fastai/learner.py in fit(self, n_epoch, lr, wd, cbs, reset_opt)
    210             self.opt.set_hypers(lr=self.lr if lr is None else lr)
    211             self.n_epoch = n_epoch
--> 212             self._with_events(self._do_fit, 'fit', CancelFitException, self._end_cleanup)
    213 
    214     def _end_cleanup(self): self.dl,self.xb,self.yb,self.pred,self.loss = None,(None,),(None,),None,None

~/.local/lib/python3.9/site-packages/fastai/learner.py in _with_events(self, f, event_type, ex, final)
    158 
    159     def _with_events(self, f, event_type, ex, final=noop):
--> 160         try: self(f'before_{event_type}');  f()
    161         except ex: self(f'after_cancel_{event_type}')
    162         self(f'after_{event_type}');  final()

~/.local/lib/python3.9/site-packages/fastai/learner.py in _do_fit(self)
    201         for epoch in range(self.n_epoch):
    202             self.epoch=epoch
--> 203             self._with_events(self._do_epoch, 'epoch', CancelEpochException)
    204 
    205     def fit(self, n_epoch, lr=None, wd=None, cbs=None, reset_opt=False):

~/.local/lib/python3.9/site-packages/fastai/learner.py in _with_events(self, f, event_type, ex, final)
    158 
    159     def _with_events(self, f, event_type, ex, final=noop):
--> 160         try: self(f'before_{event_type}');  f()
    161         except ex: self(f'after_cancel_{event_type}')
    162         self(f'after_{event_type}');  final()

~/.local/lib/python3.9/site-packages/fastai/learner.py in _do_epoch(self)
    195 
    196     def _do_epoch(self):
--> 197         self._do_epoch_train()
    198         self._do_epoch_validate()
    199 

~/.local/lib/python3.9/site-packages/fastai/learner.py in _do_epoch_train(self)
    187     def _do_epoch_train(self):
    188         self.dl = self.dls.train
--> 189         self._with_events(self.all_batches, 'train', CancelTrainException)
    190 
    191     def _do_epoch_validate(self, ds_idx=1, dl=None):

~/.local/lib/python3.9/site-packages/fastai/learner.py in _with_events(self, f, event_type, ex, final)
    158 
    159     def _with_events(self, f, event_type, ex, final=noop):
--> 160         try: self(f'before_{event_type}');  f()
    161         except ex: self(f'after_cancel_{event_type}')
    162         self(f'after_{event_type}');  final()

~/.local/lib/python3.9/site-packages/fastai/learner.py in all_batches(self)
    164     def all_batches(self):
    165         self.n_iter = len(self.dl)
--> 166         for o in enumerate(self.dl): self.one_batch(*o)
    167 
    168     def _do_one_batch(self):

~/.local/lib/python3.9/site-packages/fastai/learner.py in one_batch(self, i, b)
    181     def one_batch(self, i, b):
    182         self.iter = i
--> 183         b_on_device = tuple( e.to(device=self.dls.device) for e in b if hasattr(e, "to")) if self.dls.device is not None else b
    184         self._split(b_on_device)
    185         self._with_events(self._do_one_batch, 'batch', CancelBatchException)

~/.local/lib/python3.9/site-packages/fastcore/basics.py in __getattr__(self, k)
    386         if self._component_attr_filter(k):
    387             attr = getattr(self,self._default,None)
--> 388             if attr is not None: return getattr(attr,k)
    389         raise AttributeError(k)
    390     def __dir__(self): return custom_dir(self,self._dir())

AttributeError: 'DataLoader' object has no attribute 'device'

And this is my error at creating the Learner with on of these options for the dls:

  • dls = DataLoaders(train_dl, valid_dl, device="cuda")
  • dls = DataLoaders(train_dl, valid_dl).cuda()
  • dls = DataLoaders(train_dl, valid_dl).to("cuda")
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-33-5e8af8ac536d> in <module>
----> 1 learn = Learner(dls       = DataLoaders(train_dl, valid_dl, device="cuda"),
      2                 model     = MyModel(),
      3                 loss_func = CrossEntropyLossFlat())

~/.local/lib/python3.9/site-packages/fastai/data/core.py in __init__(self, path, device, *loaders)
    142     def __init__(self, *loaders, path='.', device=None):
    143         self.loaders,self.path = list(loaders),Path(path)
--> 144         if device is not None or hasattr(loaders[0],'to'): self.device = device
    145 
    146     def __getitem__(self, i): return self.loaders[i]

~/.local/lib/python3.9/site-packages/fastai/data/core.py in device(self, d)
    158     @device.setter
    159     def device(self, d):
--> 160         for dl in self.loaders: dl.to(d)
    161         self._device = d
    162 

AttributeError: 'DataLoader' object has no attribute 'to'

Hi,
have you tried to instantiate first the cbs as CudaCallback()?
In my code I used pytorch models with fastai and there’re no problems with that.

Same error of AttributeError: 'DataLoader' object has no attribute 'device'

Actually, this is an active bug. This used to work but something’s changed, let me go dig

I can guarantee this will work with:

!pip install fastai==2.2.5 fastcore==1.3.19

cc @Pomo

Edit: Here’s the breaking commit, will be opening an issue:

Issue is here if anyone wants to track its progress:

4 Likes

Thanks, switching to fastai 2.2.5 meanwhile.

I’ve submitted a PR which reduces what’s needed by you to train your model on the gpu with raw torch loaders, once this get’s merged it’ll be live on the master branch, so install fastai with:

pip install git+https://github.com/fastai/fastai
pip install git+https://github.com/fastai/fastcore

This also will remove the necessary addition of the CudaCallback when training, and instead fastai will just move the tensors to the right device

Edit: Merged!

1 Like

Awesome. Thanks for the PR and making the Learner simpler by removing the necessary addition of the CudaCallback

I have a couple of questions:

The .fit() function of Learner with Pythorch dataloaders works perfectly. But .lr_find() and .fit_one_cycle() dont work.

Error when learn.lr_find():

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-29-fa2b36ab6009> in <module>
----> 1 learn.lr_find()
      2 #fig = learn.recorder.plot(suggestion=True, return_fig=True);
      3 #lr  = learn.recorder.min_grad_lr

~/.local/lib/python3.9/site-packages/fastcore/basics.py in __getattr__(self, k)
    386         if self._component_attr_filter(k):
    387             attr = getattr(self,self._default,None)
--> 388             if attr is not None: return getattr(attr,k)
    389         raise AttributeError(k)
    390     def __dir__(self): return custom_dir(self,self._dir())

/usr/lib/python3.9/site-packages/torch/nn/modules/module.py in __getattr__(self, name)
    945             if name in modules:
    946                 return modules[name]
--> 947         raise AttributeError("'{}' object has no attribute '{}'".format(
    948             type(self).__name__, name))
    949 

AttributeError: 'MyModel' object has no attribute 'lr_find'

Error when learn.fit_one_cycle(1, 1e-2):

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-31-3ea49add0339> in <module>
----> 1 learn.fit_one_cycle(1, 1e-2)

~/.local/lib/python3.9/site-packages/fastcore/basics.py in __getattr__(self, k)
    386         if self._component_attr_filter(k):
    387             attr = getattr(self,self._default,None)
--> 388             if attr is not None: return getattr(attr,k)
    389         raise AttributeError(k)
    390     def __dir__(self): return custom_dir(self,self._dir())

/usr/lib/python3.9/site-packages/torch/nn/modules/module.py in __getattr__(self, name)
    945             if name in modules:
    946                 return modules[name]
--> 947         raise AttributeError("'{}' object has no attribute '{}'".format(
    948             type(self).__name__, name))
    949 

AttributeError: 'MyModel' object has no attribute 'fit_one_cycle'

Maybe for the fit_one_cycle i can solve it by specifiyng schedulers callbacks (ParamScheduler) like the original implementation: https://github.com/fastai/fastai/blob/master/fastai/callback/schedule.py#L110

Did you import them? Try doing:

from fastai.callback.all import *

Before trying to fit

Thanks, with from fastai.callback.all import * i can use learn.lr_find() and learn.fit_one_cycle(1, 1e-2) :slight_smile:

I thought these methods were inside from fastai.learner import Learner