CODEWITHSUNDEEP
python-3.xtensorflowimage-processingkerasconv-neural-network
Danish Xavier
Danish Xavier

Reputation: 1217

Type error for merge() function in Keras for 2d convolutional layer

I am trying to recreate the Inception model version 4. But i want to train it on my image data set standard shape (224,224,3) ,so i am not taking in any pretrained weights. But I am getting an error like this.

x = merge([x1, x2], mode='concat', concat_axis=channel_axis)
TypeError: 'module' object is not callable

Here is the code:

def inception_stem(input):
    if K.image_dim_ordering() == "th":
        channel_axis = 1
    else:
        channel_axis = -1

    # Input Shape is 299 x 299 x 3 (th) or 3 x 299 x 299 (th)
    x = conv_block(input, 32, 3, 3, subsample=(2, 2), border_mode='valid')
    x = conv_block(x, 32, 3, 3, border_mode='valid')
    x = conv_block(x, 64, 3, 3)

    x1 = MaxPooling2D((3, 3), strides=(2, 2), border_mode='valid')(x)
    x2 = conv_block(x, 96, 3, 3, subsample=(2, 2), border_mode='valid')
    x = tf.concat([x1,x2],axis=channel_axis)
    #x = merge([x1, x2], mode='concat', concat_axis=channel_axis) #here is the error occuring try find out the reason behind it

    x1 = conv_block(x, 64, 1, 1)
    x1 = conv_block(x1, 96, 3, 3, border_mode='valid')

    x2 = conv_block(x, 64, 1, 1)
    x2 = conv_block(x2, 64, 1, 7)
    x2 = conv_block(x2, 64, 7, 1)
    x2 = conv_block(x2, 96, 3, 3, border_mode='valid')

    x = merge([x1, x2], mode='concat', concat_axis=channel_axis)

    x1 = conv_block(x, 192, 3, 3, subsample=(2, 2), border_mode='valid')
    x2 = MaxPooling2D((3, 3), strides=(2, 2), border_mode='valid')(x)

    x = merge([x1, x2], mode='concat', concat_axis=channel_axis)
    return x

I am using python 3.6,keras 2.2.2 , tensorflow-gpu 1.9.0.

I followed the GitHub for the issue, but the answers were not clear and exact. Can anyone find the solution.

Upvotes: 1

Views: 935

Answers (1)

Srihari Humbarwadi
Srihari Humbarwadi

Reputation: 2632

Use the concatenate layer, that should help you

from tensorflow.python.keras.layers import concatenate
x = concatenate([x1, x2], axis=channel_axis)
return x

Upvotes: 2

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