this happened to me even after copying the files to data directory,
88e9fe53272d:image-classification vikumar$ python train_cifar10.py --network
resnet --num-layers 50
/Users/vikumar/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:36:
FutureWarning: Conversion of the second argument of issubdtype from `float` to
`np.floating` is deprecated. In future, it will be treated as `np.float64 ==
np.dtype(float).type`.
from ._conv import register_converters as _register_converters
objc[43816]: Class CaptureDelegate is implemented in both
/usr/local/opt/opencv/lib/libopencv_videoio.3.4.dylib (0x10f345938) and
/Users/vikumar/anaconda3/lib/python3.6/site-packages/cv2/cv2.cpython-36m-darwin.so
(0x1a1b272ce0). One of the two will be used. Which one is undefined.
INFO:root:start with arguments Namespace(batch_size=128, benchmark=0,
brightness=0, contrast=0, data_nthreads=4, data_train='data/cifar10_train.rec',
data_train_idx='', data_val='data/cifar10_val.rec', data_val_idx='',
disp_batches=20, dtype='float32', fill_value=127, gc_threshold=0.5,
gc_type='none', gpus=None, image_shape='3,28,28', initializer='default',
kv_store='device', load_epoch=None, loss='', lr=0.05, lr_factor=0.1,
lr_step_epochs='200,250', macrobatch_size=0, max_crop_size=-1,
max_random_area=1, max_random_aspect_ratio=0, max_random_h=0, max_random_l=0,
max_random_rotate_angle=0, max_random_s=0, max_random_scale=1,
max_random_shear_ratio=0, min_crop_size=-1, min_random_area=1,
min_random_aspect_ratio=None, min_random_scale=1, model_prefix=None, mom=0.9,
monitor=0, network='resnet', num_classes=10, num_epochs=300,
num_examples=50000, num_layers=50, optimizer='sgd', pad_size=4, pca_noise=0,
profile_server_suffix='', profile_worker_suffix='', random_crop=0,
random_mirror=0, ra
ndom_resized_crop=0, rgb_mean='123.68,116.779,103.939', rgb_std='1,1,1',
saturation=0, save_period=1, test_io=0, top_k=0, warmup_epochs=5,
warmup_strategy='linear', wd=0.0001)
[13:07:51] src/io/iter_image_recordio_2.cc:170: ImageRecordIOParser2:
data/cifar10_train.rec, use 1 threads for decoding..
Traceback (most recent call last):
File "train_cifar10.py", line 76, in <module>
fit.fit(args, sym, data.get_rec_iter)
File
"/Users/vikumar/incubator-mxnet/example/image-classification/common/fit.py",
line 180, in fit
(train, val) = data_loader(args, kv)
File
"/Users/vikumar/incubator-mxnet/example/image-classification/common/data.py",
line 184, in get_rec_iter
part_index = rank)
File "/Users/vikumar/incubator-mxnet/python/mxnet/io/io.py", line 947, in
creator
return MXDataIter(iter_handle, **kwargs)
File "/Users/vikumar/incubator-mxnet/python/mxnet/io/io.py", line 806, in
__init__
self.first_batch = self.next()
File "/Users/vikumar/incubator-mxnet/python/mxnet/io/io.py", line 840, in next
check_call(_LIB.MXDataIterNext(self.handle, ctypes.byref(next_res)))
File "/Users/vikumar/incubator-mxnet/python/mxnet/base.py", line 252, in
check_call
raise MXNetError(py_str(_LIB.MXGetLastError()))
mxnet.base.MXNetError: [13:07:51] src/recordio.cc:125: Check failed: pbegin_ <=
pend_ Invalid RecordIO Format
[ Full content available at:
https://github.com/apache/incubator-mxnet/issues/7450 ]
This message was relayed via gitbox.apache.org for [email protected]
