Has anyone seen this error.. if so how is it fixed?

from keras.layers import Conv2D, UpSampling2D, LeakyReLU, Concatenate, Lambda, Input, UpSampling2D from tensorflow.keras import Model from keras.applications.densenet import DenseNet169 ”’ Following is to get layers for skip connection and num_filters ”’ base_model = DenseNet169(include_top=False,input_shape=(224,224,3)) base_model_output_shape=base_model.layers[-1].output.shape decoder_filters = int(base_model_output_shape[-1]/2) def UpProject(array,filters,name,concat_with): up_i = UpSampling2D((2,2),interpolation=’bilinear’)(array) up_i=Concatenate(name=name+’_concat’)([up_i,base_model.get_layer(concat_with).output]) #skip connection up_i=Conv2D(filters=filters,kernel_size=3,strides=1,padding=’same’,name=name+’_convA’)(up_i) up_i=LeakyReLU(alpha=.2)(up_i) up_i=Conv2D(filters=filters,kernel_size=3,strides=1,padding=’same’,name=name+’_convB’)(up_i) up_i=LeakyReLU(alpha=.2)(up_i) return up_i def get_Model(): #encoder network…

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