I am stuck by this problem in customlayers.py, please help

[Rickgewu]

40 alexnet = get_alexnet(input_size,nb_classes,mean_flag)
41
42 print (alexnet.summary())

E:\TEMP\R\KERAS\AlexNet-Experiments-Keras-master\AlexNet-Experiments-Keras-master\Code\alexnet_base.py in get_alexnet(input_shape, nb_classes, mean_flag)
36
37 conv_2 = MaxPooling2D((3, 3), strides=(2,2))(conv_1)
---> 38 conv_2 = crosschannelnormalization(name="convpool_1")(conv_2)
39 conv_2 = ZeroPadding2D((2,2))(conv_2)
40 conv_2 = merge([

d:\ProgramData\Anaconda3\lib\site-packages\keras\engine\topology.py in call(self, inputs, **kwargs)
583
584 # Actually call the layer, collecting output(s), mask(s), and shape(s).
--> 585 output = self.call(inputs, **kwargs)
586 output_mask = self.compute_mask(inputs, previous_mask)
587

d:\ProgramData\Anaconda3\lib\site-packages\keras\layers\core.py in call(self, inputs, mask)
657 if 'mask' in arg_spec.args:
658 arguments['mask'] = mask
--> 659 return self.function(inputs, **arguments)
660
661 def compute_mask(self, inputs, mask=None):

E:\TEMP\R\KERAS\AlexNet-Experiments-Keras-master\AlexNet-Experiments-Keras-master\convnets-keras\convnetskeras\customlayers.py in f(X)
16 square = K.square(X)
17 extra_channels = K.spatial_2d_padding(K.permute_dimensions(square,(0,2,3,1))
---> 18 , (0,half))
19 extra_channels = K.permute_dimensions(extra_channels, (0,3,1,2))
20 scale = k

d:\ProgramData\Anaconda3\lib\site-packages\keras\backend\theano_backend.py in spatial_2d_padding(x, padding, data_format)
995 """
996 assert len(padding) == 2
--> 997 assert len(padding[0]) == 2
998 assert len(padding[1]) == 2
999 top_pad, bottom_pad = padding[0]

TypeError: object of type 'int' has no len()

[duggalrahul]

@Rickgewu,
Which versions of keras and theano have you configured?

[Rickgewu]

keras: 2.0.4
theano: 0.9.0

[duggalrahul]

My bad @Rickgewu .

This project was written using Keras 1.2. Try downgrading to version 1.2 via the command pip install keras==1.2 .

After this, modify the ~/.keras/keras.json file as follows

{
  "image_dim_ordering": "th",
  "epsilon": 1e-07,
  "floatx": "float32",
  "backend": "theano"
}

Somehow forgot to mention the keras version in the README. Let me know if this solves your problem.

[Rickgewu]

I have downgraded keras to 1.2, but still got the below error:

40 alexnet = get_alexnet(input_size,nb_classes,mean_flag)
41
42 print (alexnet.summary())

E:\TEMP\R\KERAS\AlexNet-Experiments-Keras-master\AlexNet-Experiments-Keras-master\Code\alexnet_base.pyc in get_alexnet(input_shape, nb_classes, mean_flag)
63
64 dense_1 = Flatten(name="flatten")(dense_1)
---> 65 dense_1 = Dense(4096, activation='relu',name='dense_1',init='he_normal')(dense_1)
66 dense_2 = Dropout(0.5)(dense_1)
67 dense_2 = Dense(4096, activation='relu',name='dense_2',init='he_normal')(dense_2)

d:\ProgramData\Anaconda2\lib\site-packages\keras\engine\topology.pyc in call(self, x, mask)
541 'layer.build(batch_input_shape)')
542 if len(input_shapes) == 1:
--> 543 self.build(input_shapes[0])
544 else:
545 self.build(input_shapes)

d:\ProgramData\Anaconda2\lib\site-packages\keras\layers\core.pyc in build(self, input_shape)
750 name='{}_W'.format(self.name),
751 regularizer=self.W_regularizer,
--> 752 constraint=self.W_constraint)
753 if self.bias:
754 self.b = self.add_weight((self.output_dim,),

d:\ProgramData\Anaconda2\lib\site-packages\keras\engine\topology.pyc in add_weight(self, shape, initializer, name, trainable, regularizer, constraint)
413 '''
414 initializer = initializations.get(initializer)
--> 415 weight = initializer(shape, name=name)
416 if regularizer is not None:
417 self.add_loss(regularizer(weight))

d:\ProgramData\Anaconda2\lib\site-packages\keras\initializations.pyc in he_normal(shape, name, dim_ordering)
66 fan_in, fan_out = get_fans(shape, dim_ordering=dim_ordering)
67 s = np.sqrt(2. / fan_in)
---> 68 return normal(shape, s, name=name)
69
70
d:\ProgramData\Anaconda2\lib\site-packages\keras\initializations.pyc in normal(shape, scale, name)
35
36 def normal(shape, scale=0.05, name=None):
---> 37 return K.random_normal_variable(shape, 0.0, scale, name=name)
38
39

d:\ProgramData\Anaconda2\lib\site-packages\keras\backend\theano_backend.pyc in random_normal_variable(shape, mean, scale, dtype, name)
181
182 def random_normal_variable(shape, mean, scale, dtype=None, name=None):
--> 183 return variable(np.random.normal(loc=0.0, scale=scale, size=shape),
184 dtype=dtype, name=name)
185
mtrand.pyx in mtrand.RandomState.normal (numpy\random\mtrand\mtrand.c:20639)()

ValueError: scale < 0

[duggalrahul]

@Rickgewu . I think the previous problem is solved.

To resolve this issue, please try as follows.

1. Does the code work if you remove the 'init' parameter from each layer?
2. Are you sure you updated the keras.json file correctly? Could you post the contents of that file here?

[Rickgewu]

It works after appending this entry to the json "image_dim_ordering": "th",
now I need to get my GPU working with python 27, thanks

[duggalrahul]

@Rickgewu ,

Glad your issue is resolved.

[DNXie]

I've encountered the same problem.
However, is there any way to solve the problem without install keras version1.2?
Can I use the code with keras 2 ?
@duggalrahul

[duggalrahul]

@DNXie The current code would need some revision to make it work with Keras 2 since some keras API's have changed. If you need to do fast prototyping, I'd suggest installing keras 1.2 on a fresh virtual environment.

[geetanjalisharma]

is it possible to run it into miniconda environment.

[geetanjalisharma]

---

TypeError Traceback (most recent call last)
in ()
----> 1 alexnet = get_alexnet(input_size,nb_classes,mean_flag)

~/Desktop/alx/Code/alexnet_base.py in get_alexnet(input_shape, nb_classes, mean_flag)
36
37 conv_2 = MaxPooling2D((3, 3), strides=(2,2))(conv_1)
---> 38 conv_2 = crosschannelnormalization(name="convpool_1")(conv_2)
39 conv_2 = ZeroPadding2D((2,2))(conv_2)
40 conv_2 = merge([

~/miniconda3/envs/intel_python/lib/python3.5/site-packages/keras/engine/topology.py in call(self, inputs, **kwargs)
615
616 # Actually call the layer, collecting output(s), mask(s), and shape(s).
--> 617 output = self.call(inputs, **kwargs)
618 output_mask = self.compute_mask(inputs, previous_mask)
619

~/miniconda3/envs/intel_python/lib/python3.5/site-packages/keras/layers/core.py in call(self, inputs, mask)
661 if has_arg(self.function, 'mask'):
662 arguments['mask'] = mask
--> 663 return self.function(inputs, **arguments)
664
665 def compute_mask(self, inputs, mask=None):

~/Desktop/alx/convnets-keras/convnetskeras/customlayers.py in f(X)
17 square = K.square(X)
18 extra_channels = K.spatial_2d_padding(K.permute_dimensions(square, (0,2,3,1))
---> 19 , (0,half))
20 extra_channels = K.permute_dimensions(extra_channels, (0,3,1,2))
21 scale = k

~/miniconda3/envs/intel_python/lib/python3.5/site-packages/keras/backend/theano_backend.py in spatial_2d_padding(x, padding, data_format)
1066 """
1067 assert len(padding) == 2
-> 1068 assert len(padding[0]) == 2
1069 assert len(padding[1]) == 2
1070 top_pad, bottom_pad = padding[0]

TypeError: object of type 'int' has no len()

i have done all these thing which have already mentioned in the above comments...
plz hlp me how can i fix it and i have used keras 2..
plz hlp me...........