AttributeError: 'Convolution2D' object has no attribute 'get_output'

[RaviTej310]

import theano
from scipy import misc
from PIL import Image
import PIL.ImageOps
from keras.models import Sequential
from keras.layers.core import Flatten, Dense, Dropout
from keras.layers.convolutional import Convolution2D, MaxPooling2D, ZeroPadding2D
from keras.optimizers import SGD
import numpy as np

def VGG_16(weights_path=None):
    model = Sequential()
    model.add(ZeroPadding2D((1,1),input_shape=(3,224,224)))
    model.add(Convolution2D(64, 3, 3, activation='relu'))
    model.add(ZeroPadding2D((1,1)))
    model.add(Convolution2D(64, 3, 3, activation='relu'))
    model.add(MaxPooling2D((2,2), strides=(2,2)))

    model.add(ZeroPadding2D((1,1)))
    model.add(Convolution2D(128, 3, 3, activation='relu'))
    model.add(ZeroPadding2D((1,1)))
    model.add(Convolution2D(128, 3, 3, activation='relu'))
    model.add(MaxPooling2D((2,2), strides=(2,2)))

    model.add(ZeroPadding2D((1,1)))
    model.add(Convolution2D(256, 3, 3, activation='relu'))
    model.add(ZeroPadding2D((1,1)))
    model.add(Convolution2D(256, 3, 3, activation='relu'))
    model.add(ZeroPadding2D((1,1)))
    model.add(Convolution2D(256, 3, 3, activation='relu'))
    model.add(MaxPooling2D((2,2), strides=(2,2)))

    model.add(ZeroPadding2D((1,1)))
    model.add(Convolution2D(512, 3, 3, activation='relu'))
    model.add(ZeroPadding2D((1,1)))
    model.add(Convolution2D(512, 3, 3, activation='relu'))
    model.add(ZeroPadding2D((1,1)))
    model.add(Convolution2D(512, 3, 3, activation='relu'))
    model.add(MaxPooling2D((2,2), strides=(2,2)))

    model.add(ZeroPadding2D((1,1)))
    model.add(Convolution2D(512, 3, 3, activation='relu'))
    model.add(ZeroPadding2D((1,1)))
    model.add(Convolution2D(512, 3, 3, activation='relu'))
    model.add(ZeroPadding2D((1,1)))
    model.add(Convolution2D(512, 3, 3, activation='relu'))
    model.add(MaxPooling2D((2,2), strides=(2,2)))

    model.add(Flatten())
    model.add(Dense(4096, activation='relu'))
    model.add(Dropout(0.5))
    model.add(Dense(4096, activation='relu'))
    model.add(Dropout(0.5))
    model.add(Dense(1000, activation='softmax'))

    if weights_path:
        model.load_weights("/home/srilatha/Desktop/Research_intern/vgg16_weights.h5")

    return model

if __name__ == "__main__":
    #f="/home/srilatha/Desktop/Research_intern/Data_sets/Data_set_2/FGNET/male/007A23.JPG"
    f="/home/srilatha/Desktop/Research_intern/Data_sets/Cropped_data_set/1/7.JPG"
    image = Image.open(f)
    new_width  = 224
    new_height = 224
    im = image.resize((new_width, new_height), Image.ANTIALIAS)
    im=np.array(im)
    im=np.tile(im[:,:,None],(1,1,3))
    #imRGB = np.repeat(im[:, :, np.newaxis], 3, axis=2)
    print(im)
    #print(type(im))
    im = im.transpose((2,0,1))
    im = np.expand_dims(im, axis=0)


    # Test pretrained model
    model = VGG_16('/home/srilatha/Desktop/Research_intern/vgg16_weights.h5')
    sgd = SGD(lr=0.1, decay=1e-6, momentum=0.9, nesterov=True)
    model.compile(optimizer=sgd, loss='categorical_crossentropy')
    out = model.predict(im)
    #get_feature = theano.function([model.layers[0].input], model.layers[3].get_output(train=False), allow_input_downcast=False)
    #feat = get_feature(im)
    get_activations = theano.function([model.layers[0].input], model.layers[1].get_output(train=False), allow_input_downcast=True)
    activations = get_activations(im) 
    print np.argmax(out)

Error:

File "./VGG_Keras.py", line 86, in <module> get_activations = theano.function([model.layers[0].input], model.layers[1].get_output(train=False), allow_input_downcast=True) AttributeError: 'Convolution2D' object has no attribute 'get_output'

I have also tried .output and .get_out_at both of which aren't working. I have the updated versions of keras and theano. Please help.

[JonathanKChang]

The new backend API requires the output to also be a list, not sure if this applies to using the pure theano.function. You should also pass in the learning phase (e.g. train vs test). Try using this function from here

from keras import backend as K
def get_activations(model, layer_idx, X_batch):
    get_activations = K.function([model.layers[0].input, K.learning_phase()], [model.layers[layer_idx].output,])
    activations = get_activations([X_batch,0])
    return activations

[RaviTej310]

What could I pass as an argument to this get_activations function instead of ([model.layers[0].input], model.layers[1].get_output(train=False), allow_input_downcast=True)

[JonathanKChang]

activations = get_activations(model, 1, im)

[RaviTej310]

Thanks a ton! But what about other usages like:
get_feature = theano.function([model.layers[0].input], model.layers[15].get_output(train=False), allow_input_downcast=False) feat = get_feature(im) plt.imshow(feat[0][13])

[JonathanKChang]

Just pass in that layer number as the 2nd parameter

activations = get_activations(model, 15, im)
plt.imshow(activations[0][13])

You could also modify it to use the layer name, to accept a list of layers (and get a list of activations), or also to return the backend function that you can call with data yourself

[vishalcool1401]

I am getting this error for w

model.layers[0].w.get_value() #weights of the parameters

---

AttributeError Traceback (most recent call last)
in ()
----> 1 model.layers[0].w.get_value() #weights of the parameters

AttributeError: 'Convolution2D' object has no attribute 'w'

[gsmshsns]

same issue as above..
someone told me to change it to layer.kernel, layer.bias instead..
not sure how to do that..

[fragiacalone]

Hello. I arranged my code as above

def get_activations(model,layer_idx, X_batch):
    get_activations = K.function([model.layers[0].input, K.learning_phase()], [model.layers[layer_idx].output,])
    activations = get_activations([X_batch,0])
    return activations


feat = get_activations(model, 3, im_converted)
plt.imshow(feat[0][2])
plt.show()

but then I get this error

plt.imshow(feat[0][2])
IndexError: index 2 is out of bounds for axis 0 with size 1

What's wrong with imshow? Please help

[AchmnShukla]

@fragiacalone Hi, did you find whats wrong with imshow I am stuck on the same.

[Abdoulzen]

hello everyboby I have some error after executing this part of code:

visualizing intermediate layers

output_layer = model.layers[0].get_output()
output_fn = theano.function([model.layers[0].get_input()], output_layer)

It give me this error:
output_layer = model.layers[0].get_output()
output_fn = theano.function([model.layers[0].get_input()], output_layer)

Traceback (most recent call last):

File "", line 1, in
output_layer = model.layers[0].get_output()

AttributeError: 'Conv2D' object has no attribute 'get_output'

Need someone help

Ps: the full code==>https://learnandshare645.blogspot.com/2016/06/feeding-your-own-data-set-into-cnn.html?showComment=1519292737662#c3337302287175052994