wy1iu / dcnets Goto Github PK

rt。Do you plan to implement with pytorch？？ Or someone want to try？？

thank you for your greate jobs. I see you report the result with res-18 for imagenet in your paper. Do you have trained more deep layers for imagenet or some other largescale dataset? for example res101, or res152 ? can you share some experience for that?

Hi, I am a little confused with the code.
Do you decoupled all the conv layers except for the last one( Fully connection layer) ?
So the vector w is 3D filter and vectorized into columns ?
Thx.

Traceback (most recent call last):
File "/home/tanglin/data/Code/DCNets/dcnet_cifar100/linear_cos/train_resnet.py", line 161, in
train(args.base_lr, args.batch_size)
File "/home/tanglin/data/Code/DCNets/dcnet_cifar100/linear_cos/train_resnet.py", line 49, in train
vgg.build(images, n_class, is_training)
File "/home/tanglin/data/Code/DCNets/dcnet_cifar100/linear_cos/architecture.py", line 168, in build
name='root', bn=True, pad='SAME', norm=True, reg=False, orth=True)
File "/home/tanglin/data/Code/DCNets/dcnet_cifar100/linear_cos/architecture.py", line 118, in _conv_layer
self._add_orthogonal_constraint(filt, n_filt)
File "/home/tanglin/data/Code/DCNets/dcnet_cifar100/linear_cos/architecture.py", line 99, in _add_orthogonal_constraint
wnorm = self._get_filter_norm(filt)
File "/home/tanglin/data/Code/DCNets/dcnet_cifar100/linear_cos/architecture.py", line 87, in _get_filter_norm
return tf.sqrt(tf.reduce_sum(filt*filt, [0, 1, 2], keep_dims=True)+eps)
File "/home/tanglin/anaconda3/envs/tf1.9/lib/python2.7/site-packages/tensorflow/python/ops/math_ops.py", line 1206, in reduce_sum
name=name)
File "/home/tanglin/anaconda3/envs/tf1.9/lib/python2.7/site-packages/tensorflow/python/ops/gen_math_ops.py", line 2804, in _sum
keep_dims=keep_dims, name=name)
File "/home/tanglin/anaconda3/envs/tf1.9/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op
op_def=op_def)
File "/home/tanglin/anaconda3/envs/tf1.9/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2329, in create_op
set_shapes_for_outputs(ret)
File "/home/tanglin/anaconda3/envs/tf1.9/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1717, in set_shapes_for_outputs
shapes = shape_func(op)
File "/home/tanglin/anaconda3/envs/tf1.9/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1667, in call_with_requiring
return call_cpp_shape_fn(op, require_shape_fn=True)
File "/home/tanglin/anaconda3/envs/tf1.9/lib/python2.7/site-packages/tensorflow/python/framework/common_shapes.py", line 610, in call_cpp_shape_fn
debug_python_shape_fn, require_shape_fn)
File "/home/tanglin/anaconda3/envs/tf1.9/lib/python2.7/site-packages/tensorflow/python/framework/common_shapes.py", line 676, in _call_cpp_shape_fn_impl
raise ValueError(err.message)
ValueError: Invalid reduction dimension 2 for input with 2 dimensions. for 'root/Sum' (op: 'Sum') with input shapes: [27,96], [3].