mikethreeacer opened a new issue #18540:
URL: https://github.com/apache/incubator-mxnet/issues/18540
## Description
I tried to use custom dataset with dataloader to train a model.
The error appears when use dataloader to get a batch.
Images are loaded in dataset correctly but all images and labels are None in
batch.
```
import glob
from PIL import Image
import mxnet
from mxnet import nd
from mxnet.gluon.data.vision import transforms
from mxnet.gluon.data import Dataset
class data(Dataset):
def __init__(self, root_dir):
self.files = sorted(glob.glob(root_dir + '/*/*'))
self.label = [nd.array(0) if x.split('/')[-1] == 'test' else
nd.array(1) for x in self.files]
def __len__(self):
return len(self.files)
def __getitem__(self, idx):
image = Image.open(self.files[idx])
image = nd.array(image)
label = self.label[idx]
return image, label
dataset = data(data_root)
test_dataset = dataset
test_loader = mxnet.gluon.data.DataLoader(test_dataset, batch_size = 4)
for (image, label) in train_loader:
print(image)
print(label)
```
### Error Message
```
mxnet.base.MXNetError: [11:21:44] src/imperative/./imperative_utils.h:146:
Operator stack inferring shapes failed.
input shapes:
None
None
None
None
output shapes:
None
operator attributes:
num_args : 4
Stack trace:
[bt] (0)
/home/***/.virtualenvs/torch/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x6d554b)
[0x7fed620f254b]
[bt] (1)
/home/***/.virtualenvs/torch/lib/python3.6/site-packages/mxnet/libmxnet.so(mxnet::imperative::SetShapeType(mxnet::Context
const&, nnvm::NodeAttrs const&, std::vector<mxnet::NDArray*,
std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::NDArray*,
std::allocator<mxnet::NDArray*> > const&, mxnet::DispatchMode*)+0x363b)
[0x7fed6538de8b]
[bt] (2)
/home/***/.virtualenvs/torch/lib/python3.6/site-packages/mxnet/libmxnet.so(mxnet::Imperative::Invoke(mxnet::Context
const&, nnvm::NodeAttrs const&, std::vector<mxnet::NDArray*,
std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::NDArray*,
std::allocator<mxnet::NDArray*> > const&)+0x1db) [0x7fed65395dcb]
[bt] (3)
/home/***/.virtualenvs/torch/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x3839f1f)
[0x7fed65256f1f]
[bt] (4)
/home/***/.virtualenvs/torch/lib/python3.6/site-packages/mxnet/libmxnet.so(MXImperativeInvokeEx+0x62)
[0x7fed652574e2]
[bt] (5) /usr/lib/x86_64-linux-gnu/libffi.so.6(ffi_call_unix64+0x4c)
[0x7fedacfc9dae]
[bt] (6) /usr/lib/x86_64-linux-gnu/libffi.so.6(ffi_call+0x22f)
[0x7fedacfc971f]
[bt] (7)
/usr/lib/python3.6/lib-dynload/_ctypes.cpython-36m-x86_64-linux-gnu.so(_ctypes_callproc+0x2b4)
[0x7fedad20a5c4]
[bt] (8)
/usr/lib/python3.6/lib-dynload/_ctypes.cpython-36m-x86_64-linux-gnu.so(+0x11c33)
[0x7fedad20ac33]
```
## Environment
mxnet-cu101mkl 1.6.0
ubuntu 18.04
cuda 10.1
python 3.6.9
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