I have an image classification assignment and we are not supposed to use transfer learning. So I’m trying to create a CNN form scratch using torch.nn and Learner.
So far I’m having a lot of problem in syncing the dimensions of the output layer with that of nn.CrossEntropy (it is a multiclass classification problem). I have looked around the net but could not find something that would help.
I had another previous model in which I tried to manually to manually decrease the size of the matrices in each channel to 6x6 (the nnumber of classes is 6), but then I was again stuck. So like I want a general way/tip in which I can get out of this situation.
Thanks a lot
Edit 1: Note: The data object passed in learner is of type ImageDataBunch
Here is the code
class Model(nn.Module):
def __init__(self, inp_dim=150, inp_channels=3):
super(Model, self).__init__()
self.g1 = nn.Sequential(
nn.Conv2d(inp_channels, 10, 3),
nn.ReLU(),
nn.Flatten()
)
def forward(self, x):
x = self.g1(x)
print(x.shape)
# x = x.view(-1, 6)
return x
model = Model().cuda()
# doc(Learner)
learner = Learner(data, model, loss_func=nn.CrossEntropyLoss())
learner.fit_one_cycle(2)
I’m getting the following error
RuntimeError Traceback (most recent call last)
<ipython-input-75-97c25af695bc> in <module>
----> 1 learner.fit_one_cycle(2)
/opt/conda/envs/fastai/lib/python3.6/site-packages/fastai/train.py in fit_one_cycle(learn, cyc_len, max_lr, moms, div_factor, pct_start, final_div, wd, callbacks, tot_epochs, start_epoch)
21 callbacks.append(OneCycleScheduler(learn, max_lr, moms=moms, div_factor=div_factor, pct_start=pct_start,
22 final_div=final_div, tot_epochs=tot_epochs, start_epoch=start_epoch))
---> 23 learn.fit(cyc_len, max_lr, wd=wd, callbacks=callbacks)
24
25 def fit_fc(learn:Learner, tot_epochs:int=1, lr:float=defaults.lr, moms:Tuple[float,float]=(0.95,0.85), start_pct:float=0.72,
/opt/conda/envs/fastai/lib/python3.6/site-packages/fastai/basic_train.py in fit(self, epochs, lr, wd, callbacks)
198 else: self.opt.lr,self.opt.wd = lr,wd
199 callbacks = [cb(self) for cb in self.callback_fns + listify(defaults.extra_callback_fns)] + listify(callbacks)
--> 200 fit(epochs, self, metrics=self.metrics, callbacks=self.callbacks+callbacks)
201
202 def create_opt(self, lr:Floats, wd:Floats=0.)->None:
/opt/conda/envs/fastai/lib/python3.6/site-packages/fastai/basic_train.py in fit(epochs, learn, callbacks, metrics)
97 cb_handler.set_dl(learn.data.train_dl)
98 cb_handler.on_epoch_begin()
---> 99 for xb,yb in progress_bar(learn.data.train_dl, parent=pbar):
100 xb, yb = cb_handler.on_batch_begin(xb, yb)
101 loss = loss_batch(learn.model, xb, yb, learn.loss_func, learn.opt, cb_handler)
/opt/conda/envs/fastai/lib/python3.6/site-packages/fastprogress/fastprogress.py in __iter__(self)
45 except Exception as e:
46 self.on_interrupt()
---> 47 raise e
48
49 def update(self, val):
/opt/conda/envs/fastai/lib/python3.6/site-packages/fastprogress/fastprogress.py in __iter__(self)
39 if self.total != 0: self.update(0)
40 try:
---> 41 for i,o in enumerate(self.gen):
42 if i >= self.total: break
43 yield o
/opt/conda/envs/fastai/lib/python3.6/site-packages/fastai/basic_data.py in __iter__(self)
73 def __iter__(self):
74 "Process and returns items from `DataLoader`."
---> 75 for b in self.dl: yield self.proc_batch(b)
76
77 @classmethod
/opt/conda/envs/fastai/lib/python3.6/site-packages/torch/utils/data/dataloader.py in __next__(self)
343
344 def __next__(self):
--> 345 data = self._next_data()
346 self._num_yielded += 1
347 if self._dataset_kind == _DatasetKind.Iterable and \
/opt/conda/envs/fastai/lib/python3.6/site-packages/torch/utils/data/dataloader.py in _next_data(self)
836 if len(self._task_info[self._rcvd_idx]) == 2:
837 data = self._task_info.pop(self._rcvd_idx)[1]
--> 838 return self._process_data(data)
839
840 assert not self._shutdown and self._tasks_outstanding > 0
/opt/conda/envs/fastai/lib/python3.6/site-packages/torch/utils/data/dataloader.py in _process_data(self, data)
879 self._try_put_index()
880 if isinstance(data, ExceptionWrapper):
--> 881 data.reraise()
882 return data
883
/opt/conda/envs/fastai/lib/python3.6/site-packages/torch/_utils.py in reraise(self)
392 # (https://bugs.python.org/issue2651), so we work around it.
393 msg = KeyErrorMessage(msg)
--> 394 raise self.exc_type(msg)
RuntimeError: Caught RuntimeError in DataLoader worker process 1.
Original Traceback (most recent call last):
File "/opt/conda/envs/fastai/lib/python3.6/site-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop
data = fetcher.fetch(index)
File "/opt/conda/envs/fastai/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 47, in fetch
return self.collate_fn(data)
File "/opt/conda/envs/fastai/lib/python3.6/site-packages/fastai/torch_core.py", line 127, in data_collate
return torch.utils.data.dataloader.default_collate(to_data(batch))
File "/opt/conda/envs/fastai/lib/python3.6/site-packages/torch/utils/data/_utils/collate.py", line 79, in default_collate
return [default_collate(samples) for samples in transposed]
File "/opt/conda/envs/fastai/lib/python3.6/site-packages/torch/utils/data/_utils/collate.py", line 79, in <listcomp>
return [default_collate(samples) for samples in transposed]
File "/opt/conda/envs/fastai/lib/python3.6/site-packages/torch/utils/data/_utils/collate.py", line 55, in default_collate
return torch.stack(batch, 0, out=out)
RuntimeError: invalid argument 0: Sizes of tensors must match except in dimension 0. Got 150 and 136 in dimension 2 at /opt/conda/conda-bld/pytorch_1579022034529/work/aten/src/TH/generic/THTensor.cpp:612
